bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards the Construction of an Analog Solver for the Schrödinger and Ginzburg–Landau Equations Based on a Transmission Line
Authors: Pomorski Krzysztof , Pluszyński Łukasz , Hałubek Eryk
Published: September 2024

The model presented by Gabriel Kron in 1945 is an example of an analog computer simulating quantum phenomena on a hardware level. It uses passive RLC elements to construct a hardware solver for the problem of quantum particles confined by rectangular or other classes of potential. The analytical and numerical validation of Kron’s second model is conducted for different shapes of particle-confining potentials in the one-dimensional case using an LTspice simulator. Thus, there remains potential for obtaining solutions in two- and three-dimensional cases. Here, a circuit model representing a linearized Ginzburg–Landau equation is given. Kron’s second model is generalized by the introduction of linear and non-linear resistive elements. This transforms the deformed Schrödinger equation into a linear dissipative Schrödinger equation and its non-linear form. The quantum mechanical roton problem is the main result of this work and is formulated by means of classical physical states naturally present in the LC classical circular electrical transmission line. The experimental verification of Kron’s model is confirmed.
Multiscale Simulation Study on the Spallation Characteristics of Ductile Metal Ta under High Strain Rate Impact
Authors: Wang Yuntian , Guo Yuzhu , Li Sheng , Li Yushu , Yang Min , Shi Weimei
Published: September 2024

This work employs a multiscale simulation framework to systematically explore the spallation behavior of ductile tantalum (Ta) subjected to high strain rate impacts. The approach integrates macroscopic simulations, utilizing both the Lagrangian mesh and Smoothed Particle Hydrodynamics (SPH) methods, with microscopic molecular dynamics (MD) simulations to dissect the dynamic failure processes of tantalum. The macroscopic simulations, validated against experimental data, demonstrate the effectiveness of the SPH method in accurately capturing the spallation process. An exponential correlation between spallation strength and tensile strain rate has been established. An in-depth analysis of the free surface velocity profile indicates that the pullback signal is associated with microvoid nucleation, where the velocity drop signifies the initiation conditions for microvoid development. Additionally, the rebound rate following the pullback signal reflects the progression of damage within the spallation region. By integrating results across macro- and microscales, this work offers comprehensive insights into the complex spallation behavior of ductile tantalum under extreme conditions, advancing the understanding of its failure mechanisms at high strain rates.
Microwave-Assisted Enzymatic Reactions toward Medicinally Active Heterocycles
Authors: Das Aparna , Banik Bimal Krishna
Published: September 2024

Microwaves in the presence of enzymes can contribute to the preparation of a variety of medicinally active compounds. Microwave-induced enzymatic reactions are influenced by variables such as frequency, field strength, waveform, duration, and modulation. The activation of enzymes under microwave irradiation allows the study of simple and complex reactions that have never before been reported under these conditions. By combining enzyme catalysis with microwave technology and solvent-free chemical reactions, it is possible to prepare drug-related molecules. This review presents the most interesting microwave reactions performed by enzymes toward medicinally active molecules.
Open-Source Indoor Horizontal Grow Structure Designs
Authors: Qian Jun-Yu , Pearce Joshua M.
Published: September 2024

Agrivoltaic agrotunnels are currently designed for high-density grow walls that are not amenable to bush berries or root crops. Commercial grow bins provide deeper substrates for produce with more root systems but have high costs per unit growing area. To overcome the economic limitations of grow bins, this study applies the distributed manufacturing open-source design paradigm to develop four designs for low-cost open-source structures. The designs target root vegetables and bush fruit specifically to be adopted by remote communities with limited or no outdoor growing environment to offset the market price for imported fresh produce. The indoor growing designs provide the necessary structure for supporting grow lights and grow bins and enable the transplanted berry plants to flower and produce fruits. They provide a comparable amount (110 L) or more of grow volume from 106 to 192 L. The water reservoir volume for the commercial system (62 L) and grow area (0.5 m3) is surpassed by all new designs that range from 64 to 192 L and 0.51 to 0.76 m3, respectively. These superior properties are possible with material costs for all four designs that save more than 90% of the economic cost of the commercial systems.
On the Exploration of Quantum Polar Stabilizer Codes and Quantum Stabilizer Codes with High Coding Rate
Authors: Yi Zhengzhong , Liang Zhipeng , Wu Yulin , Wang Xuan
Published: September 2024

Inspired by classical polar codes, whose coding rate can asymptotically achieve the Shannon capacity, researchers are trying to find their analogs in the quantum information field, which are called quantum polar codes. However, no one has designed a quantum polar coding scheme that applies to quantum computing yet. There are two intuitions in previous research. The first is that directly converting classical polar coding circuits to quantum ones will produce the polarization phenomenon of a pure quantum channel, which has been proved in our previous work. The second is that based on this quantum polarization phenomenon, one can design a quantum polar coding scheme that applies to quantum computing. There are several previous work following the second intuition, none of which has been verified by experiments. In this paper, we follow the second intuition and propose a more reasonable quantum polar stabilizer code construction algorithm than any previous ones by using the theory of stabilizer codes. Unfortunately, simulation experiments show that even the stabilizer codes obtained from this more reasonable construction algorithm do not work, which implies that the second intuition leads to a dead end. Based on the analysis of why the second intuition does not work, we provide a possible future direction for designing quantum stabilizer codes with a high coding rate by borrowing the idea of classical polar codes. Following this direction, we find a class of quantum stabilizer codes with a coding rate of 0.5, which can correct two of the Pauli errors.
Superstatistics Applied to Cucurbitaceae DNA Sequences
Authors: Costa M. O. , Silva R. , de Lima M. M. F. , Anselmo D. H. A. L.
Published: September 2024

The short and long statistical correlations are essential in the genomic sequence. Such correlations are long-range for introns, whereas, for exons, these are short. In this study, we employed superstatistics to investigate correlations and fluctuations in the distribution of nucleotide sequence lengths of the Cucurbitaceae family. We established a time series for exon sizes to probe these correlations and fluctuations. We used data from the National Center for Biotechnology Information (NCBI) gene database to extract the temporal evolution of exon sizes, measured in terms of the number of base pairs (bp). To assess the model’s viability, we utilized a timescale extraction method to determine the statistical properties of our time series, including the local distribution and fluctuations, which provide the exon size distributions based on the q-Gamma and inverse q-Gamma distributions. From the Bayesian statistics standpoint, both distributions are excellent for capturing the correlations and fluctuations from the data.
On the Elimination of Fast Variables from the Langevin Equation
Authors: Bedeaux Dick
Published: September 2024

In a multivariable system, there are usually a number of relaxation times. When some of the relaxation times are shorter than others, the corresponding variables will decay to their equilibrium value faster than the others. After the fast variables have decayed, the system can be described with a smaller number of variables. From the theory of nonequilibrium thermodynamics, as formulated by Onsager, we know that the coefficients in the linear flux–force relations satisfy the so-called Onsager symmetry relations. The question we will address in this paper is how to eliminate the fast variables in such a way that the coefficients in the reduced description for the slow variables still satisfy the Onsager relations. As the proof that Onsager gave of the symmetry relations does not depend on the choice of the variables, it is equally valid for the subset of slow variables. Elimination procedures that lead to symmetry breaking are possible, but do not consider systems that satisfy the laws of nonequilibrium thermodynamics.
Polymer Composites Containing Ionic Liquids: A Study of Electrical Conductivity
Authors: Shamsuri Ahmad Adlie , Md. Jamil Siti Nurul Ain , Yusoff Mohd Zuhri Mohamed , Abdan Khalina
Published: September 2024

Polymer composites are engineered materials that combine polymers with diverse fillers to enhance their physicochemical properties. The electrical conductivity of polymer composites is a vital characteristic that significantly broadens their use, particularly in electronic applications. The addition of ionic liquids into polymer composites represents a new method to enhance their functional properties, particularly in terms of electrical conductivity. In this brief review, several polymer matrices, conductive fillers, and ionic liquids utilized in polymer composites are categorized. Additionally, the effect of ionic liquids on the electrical conductivity of polymer composites is concisely explained. This review gives brief information that increases the understanding of electrical conductivity in polymer composites containing ionic liquids. In summary, most studies show that adding ionic liquids enhances the electrical conductivity of polymer composites regardless of the polymer matrix or conductive filler type. This enhancement is due to ionic liquids improving filler dispersion and promoting the creation of effective three-dimensional conductive networks within the matrix, thus boosting electron transport and mobility throughout the structure. This review provides new insights into the behavior of ionic liquids in composite systems, highlighting their role in improving properties for advanced applications. It encourages innovation in next-generation conductive materials and assists future research and development of more efficient materials for electronics.
Modeling of the Fourth-Generation Toyota Prius Traction Machine as the Reference for Future Designs
Authors: Gierczynski Michal , Jakubowski Rafal , Kupiec Emil , Seredynski Miroslaw , Jaworski Maciej , Grzesiak Lech M.
Published: September 2024

The automotive market is very competitive and demands consistently improving the technologies used and reducing the product cost and dimensions with each product model iteration. Hence, it is important to have access to well-defined reference designs of high-quality products to evaluate new ideas and technologies. This paper provides readers with a numerical model of such a high-quality product, i.e., the IPMSM-type traction motor from the fourth generation of the Toyota Prius hybrid transaxle. The presented results also serve for a discussion regarding the design decisions of the Toyota engineers and the applicability of the linearized machine model for the approximated torque calculations. In the introductory section, a brief history of the Prius model and references to the reverse engineering reports are given. Afterward, the machine dimensions, material properties, and winding configuration are described. Then, the model is validated with the torque measurements at constant speed. The simulation results are presented in the next chapters, and the numerical source data are supplied to the reader. Finally, the design philosophy of the Toyota drive is briefly discussed in comparison with the BMWi3 drive and the results are concluded in the last section.
Problems of Measuring Gas Content in Oil in a Two-Phase Flow: A Review
Authors: Edling Cezary , Śliwiński Paweł
Published: September 2024

In view of the necessity of measuring the air content in oil in two-phase flows in the context of general industry, a review of the most popular methods of measuring the air content in oil was carried out. This review includes an assessment of their advantages and disadvantages and of whether they meet criteria such as the degree of filling, the size and number of bubbles, verification, the absence of additional pressure drops, simplicity, and repeatability. In the review, the following methods were examined: the classic trapping method, a modified trapping method, a trapping method using hydrostatic pressure loss, the pressure loss due to frictional flow resistance, the pressure loss with a rapid increase in diameter, the pressure drop in a Venturi tube, the pressure drop in an orifice, a method using the Coriolis effect, the electrical resistance method, the electrical conductivity method, the electromagnetic method, the electrical capacitance method, the thermal anemometry method, the liquid–solid contact electrification method, the photographic method, holography, light scattering, sound dispersion, the ultrasonic transit-time method, X-ray radiation, gamma radiation, neutron radiation, and fiber-optic methods.
Enhancing Photovoltaic Grid Integration through Generative Adversarial Network-Enhanced Robust Optimization
Authors: Gu Zhiming , Pan Tingzhe , Li Bo , Jin Xin , Liao Yaohua , Feng Junhao , Su Shi , Liu Xiaoxin
Published: September 2024

This paper presents a novel two-stage optimization framework enhanced by deep learning-based robust optimization (GAN-RO) aimed at advancing the integration of photovoltaic (PV) systems into the power grid. Facing the challenge of inherent variability and unpredictability of renewable energy sources, such as solar and wind, traditional energy management systems often struggle with efficiency and grid stability. This research addresses these challenges by implementing a Generative Adversarial Network (GAN) to generate realistic and diverse scenarios of solar energy availability and demand patterns, which are integrated into a robust optimization model to dynamically adjust operational strategies. The proposed GAN-RO framework is demonstrated to significantly enhance grid management by improving several key performance metrics: reducing average energy costs by 20%, lowering carbon emissions by 30%, and increasing system efficiency by 8.5%. Additionally, it has effectively halved the operational downtime from 120 to 60 h annually. The scenario-based analysis further illustrates the framework’s capacity to adapt and optimize under varying conditions, achieving up to 96% system efficiency and demonstrating substantial reductions in energy costs across different scenarios. This study not only underscores the technical advancements in managing renewable energy integration, but also highlights the economic and environmental benefits of utilizing AI-driven optimization techniques. The integration of GAN-generated scenarios with robust optimization represents a significant stride towards developing resilient, efficient, and sustainable energy management systems for the future.
A New Method of Failure Mode and Severity Effects Analysis for Hydrogen-Fueled Combustion Systems
Authors: Gill Adrian , Pielecha Ireneusz , Szwajca Filip
Published: September 2024

This article aims to align its content with current trends in hybrid risk analysis methods while utilizing experimental research. This paper presents a hybrid methodology for analyzing the failure severity of a two-stage hydrogen-powered combustion system and details its implementation. This methodology assumes the use of the original FMESA method (Failure Mode and Effects Severity Analysis) with dedicated tabular scales of the failure severity. Obtaining results under the FMESA using experimental research is intended to reduce epistemic uncertainty, which is an important component of hazard severity or risk models. Its essence is to change the way of obtaining the results of the basic components of known methods such as FMEA/FMECA (Failure Mode and Effect Analysis/Failure Mode, Effects and Criticality Analysis). Experimental research was also used to develop the original failure severity scales for a two-stage hydrogen-fueled combustion system. The article presents a review of the literature on methods for identifying and analyzing hazards in hydrogen systems, the FMESA method with its mathematical model, results in the form of tabular scales of the failure severity, results of selected experimental tests, and quantitative results of a severity analysis of eleven failure modes of a two-stage hydrogen-fueled combustion system for a selected engine operating point.
Analysis of the Effectiveness of ARIMA, SARIMA, and SVR Models in Time Series Forecasting: A Case Study of Wind Farm Energy Production
Authors: Szostek Kamil , Mazur Damian , Drałus Grzegorz , Kusznier Jacek
Published: September 2024

The primary objective of this study is to evaluate the accuracy of different forecasting models for monthly wind farm electricity production. This study compares the effectiveness of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), and Support Vector Regression (SVR). This study utilizes data from two wind farms located in Poland—‘Gizałki’ and ‘Łęki Dukielskie’—to exclude the possibility of biased results due to specific characteristics of a single farm and to allow for a more comprehensive comparison of the effectiveness of both time series analysis methods. Model parameterization was optimized through a grid search based on the Mean Absolute Percentage Error (MAPE). The performance of the best models was evaluated using Mean Bias Error (MBE), MAPE, Mean Absolute Error (MAE), and R2Score. For the Gizałki farm, the ARIMA model outperformed SARIMA and SVR, while for the Łęki Dukielskie farm, SARIMA proved to be the most accurate, highlighting the importance of optimizing seasonal parameters. The SVR method demonstrated the lowest effectiveness for both datasets. The results indicate that the ARIMA and SARIMA models are effective for forecasting wind farm energy production. However, their performance is influenced by the specificity of the data and seasonal patterns. The study provides an in-depth analysis of the results and offers suggestions for future research, such as extending the data to include multidimensional time series. Our findings have practical implications for enhancing the accuracy of wind farm energy forecasts, which can significantly improve operational efficiency and planning.
The Influence of Hydrogen Concentration on the Hazards Associated with the Use of Coke Oven Gas
Authors: Klejnowski Mateusz , Stolecka-Antczak Katarzyna
Published: September 2024

Coke oven gas (COG), as a by-product of the coking process and a mixture with a high hydrogen content, is an important potential component of the sustainable economy of the coking industry. Ongoing studies and analyses are looking at many opportunities for the utilization of coke oven gas, including for the production of hydrogen, methanol or other chemicals. However, it is important not to forget that all processes for the utilization of this gas may pose a potential hazard to humans and the environment. This is due to the physicochemical properties of COG and the content of flammable gases such as hydrogen, methane or carbon monoxide in its composition. Potential hazardous events are also related to the content of toxic substances in the composition of coke oven gas. The publication focuses on the occurrence of a fire or explosion as a result of the uncontrolled release of purified coke oven gas from the installation. The potential hazard zones associated with the occurrence of these phenomena are presented concerning different levels of hydrogen concentration in coke oven gas and the influence of selected factors on the range of these zones. Zones related to human deaths due to fire of coke oven gas reached a maximum range of about 130 m from the site of the failure, depending on the gas composition, level of damage and parameters of the installation. Zones related to human deaths due to the explosion of the coke oven gas did not occur. The zone related to the injury of humans as a result of the COG explosion reached a maximum range of about 12 m.
Mine Water as a Source of Energy—Case Study from Poland
Authors: Starczewska Magdalena , Sowiżdżał Anna , d’Obyrn Kajetan , Cień Damian
Published: September 2024

The energy sector in Poland is primarily based on fossil fuels, mainly coal. Hard coal mining is one of the most important industries in Poland. Hard coal deposits in Poland are found in three basins, but mining is currently carried out in the Upper Silesian Coal Basin (USCB) and the Lublin Coal Basin (LCB). The Upper Silesian Coal Basin is Poland’s central hard coal basin, with the most significant coal production extending across Poland and the Czech Republic. Approximately 80% of proven hard coal resources in Poland are found in the Upper Silesian Coal Basin (USCB). There is a tremendous amount of water in active and abandoned hard coal mines, which must be drained daily. Relatively high temperatures characterize mine water. This study analyzed the geological and hydrogeological conditions of the Upper Silesian Coal Basin and determined the potential for the use of mine waters for energy purposes. Depending on the location of the mine, the volume of mine water inflow ranges from 1 to 60 m3/min. The temperature of the pumped water is between 13 and 25 °C. In Poland, several such pilot installations have already been created; it is worth taking a closer look at the following examples. Heat recovery from mine drainage water can significantly reduce atmospheric emissions, which is particularly important in mining areas affected by low emissions. Therefore, Poland must raise the issue of using mined water for energy purposes, especially when making decisions related to decommissioning mines and developing post-mining areas.
Harnessing Switchgrass for Sustainable Energy: Bioethanol Production Processes and Pretreatment Technologies
Authors: Unyay Hilal , Perendeci Nuriye Altınay , Piersa Piotr , Szufa Szymon , Skwarczynska-Wojsa Agata
Published: September 2024

This paper investigates bioethanol production from switchgrass, focusing on enhancement of efficiency through various pretreatment methods and comparing two bioethanol production processes: simultaneous saccharification and fermentation (SSF) and separate hydrolysis and fermentation (SHF). Physical, chemical, and biological pretreatment processes are applied to enhance the breakdown of switchgrass’s lignocellulosic structure. Effects of pretreatments, enzymatic hydrolysis, and fermentation on ethanol yield are discussed in detail. The comparative analysis reveals that SSF yields higher ethanol outputs within shorter times by integrating hydrolysis and fermentation into a single process. In contrast, SHF offers more control by separating these stages. The comparative analysis highlights that SSF achieves higher ethanol yields more efficiently, although it might restrict SHF’s operational flexibility. This study aims to provide a comprehensive overview of the current pretreatments, hydrolysis methods, and fermentation processes in bioethanol production from switchgrass, offering insights into their scalability, economic viability, and potential environmental benefits. The findings are expected to contribute to the ongoing discussions and developments in renewable bioenergy solutions, supporting advancing more sustainable and efficient bioethanol production techniques.
A Comprehensive Review of Multi-Use Platforms for Renewable Energy and Aquaculture Integration
Authors: Manolache Alexandra Ionelia , Andrei Gabriel
Published: September 2024

This review aims to find, classify, and discuss ongoing projects that fall into the category of multi-use platforms, concerning offshore energy exploitation and marine resource production, including aquaculture. The term multi-use platforms (MUPs) refer to areas that may accommodate multiple operations such as aquaculture, tourism, transportation, oil, or energy production. This research only examines the current situation of marine energy projects that entail the integration of either a single kind of renewable energy or other types of marine renewable energy, in conjunction with aquaculture. The particularity of this research consists in the exclusive choice of platforms that integrate two sources of renewable energy on a single platform. The study focuses on analyzing the projects set up over time on these platforms, all of which include aquaculture. The state of the art in MUPs for offshore applications was examined to generate the review. We devised a methodical search approach aiming to find relevant material from various academic fields. During this phase, we looked to understand as much as we could about MUPs, including their design, the nature of these projects, what kinds of projects they can include, how they integrate renewable energy sources, and whether aquaculture facilities can be put together. To preserve scientific integrity and guarantee the inclusion of relevant research, a search strategy was formulated. The bibliographic study was through critical analysis, and at the end, significant conclusions were drawn concerning the development of multi-use platforms.
The Trade of Woody Biomass in the Context of Environmental Economics in Poland
Authors: Wyszomierski Rafał , Bórawski Piotr , Holden Lisa , Bełdycka-Bórawska Aneta , Rokicki Tomasz , Parzonko Andrzej
Published: September 2024

One of the most important problems in economic development is the supply of stable amounts of renewable energy sources, including biomass. The production of biomass in Poland is not satisfactory; thus, this country has to import this product. As with other products, the trade of stable biomass includes both imports and exports and depends on the price and other characteristics of the market. This research aimed to assess the biomass trade in terms of energy and evaluate changes and trends in the import and export of biomass in Poland and its characteristics. Moreover, the export specialization index (SI index), Grubel–Lloyd index (IITk index) and foreign trade coverage index (CRK index) were evaluated. The considerations were based on the biomass trade in the context of environmental economics. This research found that the neighboring countries of Poland are the most important partners in both imports and exports. Germany and Lithuania are the most important countries in the trade of woody biomass. The export specialization index (SI index), in 2005–2008, was positive and growing, which means that exports exceeded imports; then, in 2009, there was a decline; from 2010 to 2013, the balance increased again, reaching significant positive values until 2019; and, in 2020, there was a decline. The Grubel–Lloyd index for the Polish wood and forestry industry showed a dynamic evolution in the analyzed period of 2005–2020, which reflects the industry’s adaptive strategies in the face of global changes. Raw wood and veneer sheets are more volatile, which may indicate periodic shifts in the structure of foreign trade and the flexibility of producers to respond to international trends and demands. The CRK index in the years 2005–2020 presents an astonishing picture of changes in competitiveness and the ability to maintain the balance of imports and exports. The significant increase in the ratio of firewood and raw wood may reflect an increase in interest in renewable energy sources and the expansion of the industry into new markets.
Terrestrial Heat Flow and Lithospheric Thermal Structure Characteristics in Nanping City of Hainan
Authors: Yan Xiaoxue , Wang Xiaolin , Xue Guicheng , Yuan Ruoxi , Yang Feng
Published: September 2024

The Nanping geothermal field in Hainan is situated within the Wuzhi Mountain fold belt of the South China fold system based on its geotectonic units. Although there is abundant surface heat detected and widespread distribution of Late Mesozoic granite in the area, the geological background of geothermal resources remains unclear. In this article, we collected core samples from boreholes within the Nanping geothermal field to conduct testing and analysis on rock thermal conductivity and heat-production rate. By combining these results with temperature logging data, we discuss a method for diterming the heat flow background of convective geothermal system. Furthermore, the study analyzed the geothermal flux and deep thermal structure of the research area. The results demonstrate that the average radioactive heat production rate of the Baocheng rock mass in the study area is 3.16 μW/m³, primarily attributed to the decay heat of Th and U, while the heat contribution of K is negligible. The thermal conductivity values of the rocks are relatively high, ranging from 2.29 to 3.75 W/(mK), slightly exceeding the average thermal conductivity of the upper crust. The study area represents a typical convective geothermal field influenced by groundwater convection, exhibiting a high geothermal temperature gradient. Using the groundwater-correction method, the geothermal flux in the study area is calculated to be 89–108.27 mW/m², of which the thermal conduction component is 73.17 mW/m² and the convective component is 15.83–35.1 mW/m². Among these components, heat generated from radioactive decay of crustal radioactive elements contributes 35.44 mW/m² to thermal conduction, while deep mantle conduction accounts for a heat flux is 37.73 mW/m², with a ratio of 1:1.07 between them. The difference between crustal and mantle heat fluxes is minimal in this region, indicating an approximation towards a “crust-mantle heat source balance zone”. Furthermore, the thickness of the “hot” lithosphere in the study area ranges from 42 to 46 km, indicating significant characteristics of extension-thinning.
Experimental Study on Phase Change Energy Storage Flooring for Low-Carbon Energy Systems in Grassland Pastoral
Authors: Wang Kai , Xu Guoqiang , Zhao Xiaochen , Li Guo , Mai Lisi
Published: September 2024

Phase change energy storage technology enhances the integration of renewable resources into low-carbon energy systems for grassland pastoral settlements, further addressing the balance between energy needs and environmental sustainability. This study examines a heating system using an experimental platform in an environmental chamber, where the thermal storage and release processes of phase change energy storage flooring were monitored. The results revealed that phase change energy storage flooring exhibits higher heat transfer efficiency and faster heating rates. Under 40 °C heating conditions, the heating rate of the thermal storage layer increased by 12.5% within 1 h. The flooring also demonstrated superior heat release performance, with the peak heat flux of the thermal storage layer delayed by 15 min. Higher heating temperatures shortened the heating time and extended the heat release duration of the phase change energy storage flooring. Under 45 °C heating conditions, the heat transfer efficiency of the surface temperature of the thermal storage layer increased by 38% within 1 hour and by 24.7% over 4 h. In addition, energy consumption in different tests was analyzed, and thermal conductivity was discussed according to the heat transfer model. Phase change energy storage flooring, when coupled with the abundant solar energy resources available in grassland pastoral areas, presents a viable option for the construction of low-carbon energy systems in grassland pastoral settlements.
Energy Awareness, Energy Use, and Energy-Saving Opportunities in the Caribbean: The Island Curaçao as a Case Study
Authors: Bulbaai Richenel R. , Halman Johannes I. M.
Published: September 2024

Household energy consumption represents a significant share of global energy usage, highlighting the importance of understanding the factors that influence energy use and identifying potential strategies for conservation. The Caribbean region faces unique challenges in energy sustainability, driven by its heavy dependence on fossil fuels and rising energy demand. The primary aim of this study is to evaluate the current levels of energy awareness and energy consumption among households on the tropical Caribbean island of Curaçao and to determine practical energy-saving opportunities that can significantly reduce both energy consumption and costs. This paper is one of the first to evaluate energy awareness, energy use, and energy-saving opportunities among households in the Caribbean. The study included a literature review of key theories, concepts, and energy-saving strategies, along with a telephone survey of 382 households in Curaçao to examine household energy use, the factors shaping energy behavior, and the connections between energy consumption, behavior, and household income. The main findings of this study reveal that energy-efficient appliances are predominantly used in high-income households, with much lower adoption rates in middle- and low-income households. Cost savings, rather than environmental concerns, emerge as the primary motivation behind energy-saving behavior. Notably, the study highlights that most households in Curaçao are largely unaware of the full range of energy-efficient options available to them for reducing energy consumption. Based on the field study results, several recommendations are offered to enhance energy awareness, expand energy-saving opportunities, and ultimately reduce energy usage.
Inclusive Growth, Energy Poverty and Digital and Social Development: Cross-Country Analysis of the European Union
Authors: Tundys Blanka , Bretyn Agnieszka
Published: September 2024

The present study delves into a critical concern on the relationship between energy poverty, digital and social development and inclusive growth. The main research hypothesis assumes a positive relationship between these areas, although differences between countries are inevitable. Therefore, the following research questions were asked: Is the impact of the level of energy poverty on inclusive growth the same in different EU countries? How does the use of renewable energy sources in individual countries affect energy poverty and thus inclusive growth? What is the link between energy poverty, digital and social development and inclusive growth in the countries studied. This study uses a critical analysis of the literature and methods of descriptive and mathematical–statistical tools/model. The main conclusions and findings of the analysis reveal that the link between energy poverty, use of renewable energy resources, digital and social development and inclusive growth varies across EU countries. The results of our analyses may be useful, for example, for government decision makers in terms of actions aimed at eliminating energy poverty through the country’s use of sustainable energy sources as well as designing and implementing actions aimed at increasing digital and social development, which will then contribute to inclusive growth.
Suppression and Analysis of Low-Frequency Oscillation in Hydropower Unit Regulation Systems with Complex Water Diversion Systems
Authors: Liu Zhao , Yan Zhenwu , Zhang Hongwei , Xie Huiping , Zou Yidong , Zheng Yang , Xiao Zhihuai , Chen Fei
Published: September 2024

Low-frequency oscillation (LFO) poses significant challenges to the dynamic performance of hydropower unit regulation systems (HURS) in hydropower units sharing a tailwater system. Previous methods have struggled to effectively suppress LFO, due to limitations in governor parameter optimization strategies. To address this issue, this paper proposes a governor parameter optimization strategy based on the crayfish optimization algorithm (COA). Considering the actual water diversion layout (WDL) of a HURS, a comprehensive mathematical model of the WDL is constructed and, combined with models of the governor, turbine, and generator, an overall HURS model for the shared tailwater system is derived. By utilizing the efficient optimization performance of the COA, the optimal PID parameters for the HURS controller are quickly obtained, providing robust support for PID parameter tuning. Simulation results showed that the proposed strategy effectively suppressed LFOs and significantly enhanced the dynamic performance of the HURS under grid-connected conditions. Specifically, compared to before optimization, the optimized system reduced the oscillation amplitude by at least 30% and improved the stabilization time by at least 25%. Additionally, the impact of the power grid system parameters on oscillations was studied, providing guidance for the optimization and tuning of specific system parameters.
Advanced Optimal System for Electricity Price Forecasting Based on Hybrid Techniques
Authors: Luo Hua , Shao Yuanyuan
Published: September 2024

In the context of the electricity sector’s liberalization and deregulation, the accurate forecasting of electricity prices has emerged as a crucial strategy for market participants and operators to minimize costs and maximize profits. However, their effectiveness is hampered by the variable temporal characteristics of real-time electricity prices and a wide array of influencing factors. These challenges hinder a single model’s ability to discern the regularity, thereby compromising forecast precision. This study introduces a novel hybrid system to enhance forecast accuracy. Firstly, by employing an advanced decomposition technique, this methodology identifies different variation features within the electricity price series, thus bolstering feature extraction efficiency. Secondly, the incorporation of a novel multi-objective intelligent optimization algorithm, which utilizes two objective functions to constrain estimation errors, facilitates the optimal integration of multiple deep learning models. The case study uses electricity market data from Australia and Singapore to validate the effectiveness of the algorithm. The forecast results indicate that the hybrid short-term electricity price forecasting system proposed in this paper exhibits higher prediction accuracy compared to traditional single-model predictions, with MAE values of 7.3363 and 4.2784, respectively.
Review and Evaluation of Multi-Agent Control Applications for Energy Management in Buildings
Authors: Michailidis Panagiotis , Michailidis Iakovos , Kosmatopoulos Elias
Published: September 2024

The current paper presents a comprehensive review analysis of Multi-agent control methodologies for Integrated Building Energy Management Systems (IBEMSs), considering combinations of multi-diverse equipment such as Heating, Ventilation, and Air conditioning (HVAC), domestic hot water (DHW), lighting systems (LS), renewable energy sources (RES), energy storage systems (ESS) as well as electric vehicles (EVs), integrated at the building level. Grounded in the evaluation of key control methodologies—such as Model Predictive Control (MPC) and reinforcement learning (RL) along with their synergistic hybrid integration—the current study integrates a large number of impactful applications of the last decade and evaluates their contribution to the field of energy management in buildings. To this end, over seventy key scholarly papers from the 2014–2024 period have been integrated and analyzed to provide a holistic evaluation on different areas of interest, including the utilized algorithms, agent interactions, energy system types, building typologies, application types and simulation tools. Moreover, by analyzing the latest advancements in the field, a fruitful trend identification is conducted in the realm of multi-agent control for IBEMS frameworks, highlighting the most prominent solutions to achieve sustainability and energy efficiency.
The Influence of Socio-Demographic Factors on Management Concerning Corporate Culture in the Forest and Wood-Processing Sector
Authors: Lorincová Silvia
Published: September 2024

In order to remain competitive, the company’s management must consider the corporate culture as a factor that influences the success of the company. The aim of this research study is to identify corporate culture and examine the influence of selected socio-demographic factors that can influence management concerning corporate culture. Research was carried out in the forest and wood-processing sector in Slovakia on a sample of 2447 respondents. It utilized the Organizational Culture Assessment Instrument. The findings indicate that a hierarchy and clan corporate culture were prevalent. The companies were characterized by their formalized and structured work environments as well as by their promotion of family-like relationships within the workplace, too. In terms of the preferred corporate culture, the clan corporate culture was clearly favored for the future. Success should be understood in relation to the internal environment and care for each employee. Following the results, the socio-demographic factors had an influence on management concerning the corporate culture. Therefore, it is essential for managers to tailor their approaches to the individual characteristics of each employee towards establishing a corporate culture that supports mutual relations in the workplace. This can affect the overall success and long-term sustainability of the company.
Scalable Mangrove Monitoring with Limited Field Data: Integrating MREDT and DACN-M
Authors: Zhao Yuchen , Wu Shulei , Zhang Xianyao , Chen Huandong , Zhuang Jiasen , Wu Zhongqiang
Published: September 2024

Mangroves play a crucial ecological and economic role but face significant threats, particularly on Hainan Island, which has the highest mangrove species diversity in China. Remote sensing and AI techniques offer potential solutions for monitoring these ecosystems, but challenges persist due to difficult access for field sampling. To address these issues, we propose a novel model combining a Mangrove Rough Extraction Decision Tree (MREDT) and a Dynamic Attention Convolutional Network (DACN-M). Initially, we used drones and field surveys to conduct multiple observations in Dongzhaigang Nature Reserve, identifying the boundaries of the mangroves. Based on these features, we constructed the MREDT model to mitigate model failure caused by light instability, simplifying transfer to other study areas without requiring annotated samples or extensive field surveys. Next, we developed the DACN-M model, which refines the rough extraction features from MREDT and incorporates contextual information for more accurate detection. Experimental results demonstrate that our proposed method effectively differentiates mangroves from other vegetation, achieving F1 Scores above 75% and IoU values greater than 60% across six study areas. In conclusion, our proposed method not only accurately identifies and monitors mangrove distribution but also offers the significant advantage of being transferable to other study areas without the need for annotated samples or field surveys. This provides a robust and scalable solution for protecting and preserving critical mangrove ecosystems and supports effective conservation efforts in various regions.
Effects of Biodiversity and Its Interactions on Ecosystem Multifunctionality
Authors: Li Jing , Luo Hongbin , Lai Jiandong , Zhang Rui
Published: September 2024

Global change and the intensification of human activities have led to a sharp decline in global biodiversity and other ecological issues. Over the past 30 years, ecologists have increasingly focused on the question of whether and how the ongoing loss of biodiversity affects ecosystem functioning. However, historically, researchers have predominantly concentrated on individual ecosystem functions, neglecting the capacity of ecosystems to provide multiple ecosystem functions simultaneously, known as ecosystem multifunctionality (EMF). As a result, the connection between biodiversity and ecosystem multifunctionality (BEMF) has become the central theme in BEF relationship research. In recent years, the research on the BEMF relationship has developed rapidly, and new progress has been made in different ecosystems, the driving mechanism of the BEMF relationship, and the proposal and application of new quantitative methods. However, there are still shortcomings, such as the lack of uniform standards for the selection of functional indicators in EMF research, insufficient attention to belowground microbial diversity, and less research on biological interactions in addition to biodiversity. In the future, we need to enhance standard research on the selection of functional indicators, thoroughly assess the combined effects of aboveground and belowground biodiversity along with abiotic factors on EMF, and bolster the research and application of ecosystem multiserviceability (EMS) methods.
Optimizing Urban Forest Multifunctionality through Strategic Community Configurations: Insights from Changchun, China
Authors: Yan Jinsheng , Zhang Juan , Wang Qi , He Xingyuan
Published: September 2024

The role of forest community configurations in multiple ecosystem functions remains poorly understood due to the absence of quantifiable metrics for evaluating these configurations. This limitation hinders our ability to use forests to enhance urban well-being effectively. This study integrates both observation and experimentation to elucidate the effects of community configurations on the multifunctionality of forests. We examine seven ecosystem functions in Changchun’s urban forests: carbon sequestration, rainwater interception, temperature reduction, humidity increase, particulate matter reduction, noise reduction, and water conservation. Assortment indices, derived from traditional diversity metrics and relative importance values, reveal a negative correlation with multifunctionality. This suggests that improving forest multifunctionality requires a strategically planned species composition rather than simply increasing diversity. Furthermore, the creation of comprehensive configuration indices for evaluating intraspecific configurations has confirmed their beneficial impact on multifunctionality. Our results highlight the significance of intraspecific structural configurations and advocate for using mixed-species plantings in urban forestry practices. We propose practical management strategies to enhance urban forest multifunctionality, including selecting tree species for their functional benefits, implementing uneven-aged plantings, and integrating both shade-tolerant and sun-loving species. Together, our findings underscore the essential role of community configuration in sustaining multifunctionality and strongly support the management of urban forests.
Artificial Intelligence-Driven FinTech Valuation: A Scalable Multilayer Network Approach
Authors: Moro Visconti Roberto
Published: September 2024

The integration of Artificial Intelligence (AI) in the FinTech industry has significantly reshaped operational workflows, product innovation, and risk management, all of which are pivotal to company valuation. This study investigates the impact of AI-enhanced multilayer networks on FinTech valuation, introducing a novel, scalable multilayer network model with AI-driven Copula Nodes that serve as connectors across operational layers. By incorporating AI, the research unveils a dynamic and interconnected approach to FinTech valuation, revealing new pathways for value co-creation through real-time adjustments and predictive capabilities. The research reveals that while operational efficiency is a major driver of market value, a balanced integration of AI across risk management, product innovation, and market perception is essential for maximizing value. Additionally, the findings highlight the importance of managing AI-driven risks such as algorithmic bias and regulatory challenges. This comprehensive framework offers critical insights for FinTechs, investors, and regulators seeking to understand the complex role of AI in enhancing valuation within the evolving financial services landscape.