bluuebunny/crossref_metadata_2025 huggingface dataset:
Tricoma (Tricoma) disparseta sp. nov. (Nematoda: Desmoscolecidae), a New Free-Living Marine Nematode from a Seamount in the Northwest Pacific Ocean, with a New Record of T. (T.) longirostris (Southern, 1914)
Authors: Lee Hyo Jin , Lee Heegab , Kihm Ji-Hoon , Rho Hyun Soo
Published: October 2024

During a survey of marine biodiversity in the deep sea off northeastern Guam, two marine desmoscolecid nematodes belonging to the subgenus Tricoma were discovered. Tricoma (Tricoma) disparseta sp. nov. was described based on specimens collected from sponge and starfish habitats on a seamount at depths ranging from 1300 to 1500 m. Tricoma (Tricoma) disparseta sp. nov. is distinguished by having 59 to 62 main rings, 9 to 10 subdorsal setae, and 14 to 18 subventral setae on each side. Notable features include the differentiation in length and insertion between the subdorsal and subventral setae, as well as the amphid extending to the second or third main ring. Additionally, the spicules have a relatively small capitulum at the proximal end, while the gubernaculum is bent into a hooked shape. The specimen of T. (T.) longirostris observed in this study closely resembles previously reported specimens, characterized by 78 main rings, a long and narrow head shape, eight to nine subdorsal setae, 14 to 15 subventral setae, and a gubernaculum with a knobbed apophysis. Two Tricoma species from the Northwest Pacific Ocean are described in detail, and pictorial keys and comparative tables for species identification are provided for groups with 50 to 64 main rings.
Asymmetric Effects of Temperature Change on Herbaceous Seed Germination: Implications for Climate Warming
Authors: Chen Kai , Chen Zi-Hong , Jiang Zhong-Hua
Published: October 2024

Seed germination is a critical ecological process that governs both the establishment and maintenance of plant diversity and is highly sensitive to temperature fluctuations. As climate change accelerates, particularly through increasing temperatures, the disruption to seed germination could pose significant risks to plant diversity. Therefore, understanding how temperature fluctuations affect seed germination is essential for predicting the future recruitment of mountain plants and for conserving biodiversity in the context of ongoing climate warming scenarios. In this study, we collected seeds from 14 Impatiens species (Balsaminaceae) in the Gaoligong Mountains (Southwest China) at an elevation of approximately 2000 m. Germination tests were conducted on seeds subjected to cold stratification (42 days at 4 °C) across a range of alternating temperatures (6/1, 11/6, 16/11, 21/16, 26/21, and 31/26 °C). We used generalized linear mixed-effects models (random intercept) with temperature and its higher-order terms as the fix-effect terms to construct four models describing the relationship between germination percentage and temperature. Results indicated that (1) the germination percentage varied significantly among species and temperature treatments; (2) the nonlinear and asymmetrical model, incorporating temperature and its quadratic and cubic terms, best fit the germination data; and (3) the decline in germination percentage above the optimum temperature (To) was significantly steeper than the increase below based on the best model. Overall, these findings suggest that seed plants at low elevations in mountain ecosystems may be particularly vulnerable to future climate warming due to the sharp decline in germination percentage at temperatures above To. Thus, protecting low-elevation plants should be a key priority in biodiversity conservation efforts as global temperatures continue to rise.
Noise Transfer Approach to GKP Quantum Circuits
Authors: Ralph Timothy C. , Winnel Matthew S. , Swain S. Nibedita , Marshman Ryan J.
Published: October 2024

The choice between the Schrödinger and Heisenberg pictures can significantly impact the computational resources needed to solve a problem, even though they are equivalent formulations of quantum mechanics. Here, we present a method for analysing Bosonic quantum circuits based on the Heisenberg picture which allows, under certain conditions, a useful factoring of the evolution into signal and noise contributions, similar way to what can be achieved with classical communication systems. We provide examples which suggest that this approach may be particularly useful in analysing quantum computing systems based on the Gottesman–Kitaev–Preskill (GKP) qubits.
Solving the B-SAT Problem Using Quantum Computing: Smaller Is Sometimes Better
Authors: Bennakhi Ahmad , Byrd Gregory T. , Franzon Paul
Published: October 2024

This paper aims to outline the effectiveness of modern universal gate quantum computers when utilizing different configurations to solve the B-SAT (Boolean satisfiability) problem. The quantum computing experiments were performed using Grover’s search algorithm to find a valid solution. The experiments were performed under different variations to demonstrate their effects on the results. Changing the number of shots, qubit mapping, and using a different quantum processor were all among the experimental variables. The study also branched into a dedicated experiment highlighting a peculiar behavior that IBM quantum processors exhibit when running circuits with a certain number of shots.
Advanced Exergy-Based Optimization of a Polygeneration System with CO2 as Working Fluid
Authors: Luo Jing , Zhu Qianxin , Morosuk Tatiana
Published: October 2024

Using polygeneration systems is one of the most cost-effective ways for energy efficiency improvement, which secures sustainable energy development and reduces environmental impacts. This paper investigates a polygeneration system powered by low- to medium-grade waste heat and using CO2 as a working fluid to simultaneously produce electric power, refrigeration, and heating capacities. The system is simulated in Aspen HYSYS® and evaluated by applying advanced exergy-based methods. With the split of exergy destruction and investment cost into avoidable and unavoidable parts, the avoidable part reveals the real improvement potential and priority of each component. Subsequently, an exergoeconomic graphical optimization is implemented at the component level to improve the system performance further. Optimization results and an engineering solution considering technical limitations are proposed. Compared to the base case, the system exergetic efficiency was improved by 15.4% and the average product cost was reduced by 7.1%; while the engineering solution shows an increase of 11.3% in system exergetic efficiency and a decrease of 8.5% in the average product cost.
Construction and Validation of a Survey on the Technological Difficulties in Italian Secondary Schools: The Mathematics Teacher Case
Authors: Messina Filippo , Tadeu Pedro
Published: October 2024

(1) Background: This study explores the technological difficulties of mathematics teachers in Italian secondary schools, focusing on the factors that influence their ability to integrate technology in teaching. (2) Methods: A questionnaire was developed and administered to a pilot group of 45 mathematics teachers from vocational secondary schools in Sicily and Veneto, followed by a larger survey with 557 mathematics teachers across Italy. The structural model was analysed using the maximum likelihood method via AMOS software (v.22 SPSS Inc., Chicago, IL, USA). (3) Results: The results highlight the importance of personal commitment in the school context and students’ problem-solving skills as key factors influencing the teachers’ technological challenges. The findings also indicate dissatisfaction with the school institution and families, as well as personal resistance to using information and communication technologies (ICT) in more advanced educational activities. (4) Conclusions: The study underscores the significant impact of these technological difficulties on teachers’ effectiveness in fostering students’ problem-solving abilities, calling attention to the need for better institutional support and strategies to reduce resistance to ICT use in education.
A Follow-Up Study of an Early Childhood Mentoring Program: Sustaining Impactful Change for Mentors and Mentees
Authors: Andrews Rebecca , Hadley Fay , Hay Iain
Published: October 2024

Government funded mentoring programs are one strategy to address the supply crisis of early childhood teachers (ECTs) in Australia. There is little or no published research on the long-term impacts of these programs. This paper presents the findings of an evaluation survey completed 18 months after the mentoring program finished, covering the perspectives of experienced ECTs (mentors) and beginning ECTs (mentees). The participants (N = 39) reported personal and professional growth over the period of the program. Subsequently, their enriched knowledge, skills and understanding of mentoring impacted their own, other individuals and wider practices within their workplaces. Enablers to participation were a supportive director and the scheduling of the program out of hours. The predominant challenge for ongoing enactment of learnings was time constraints due to daily demands of early childhood workplaces. Recommendations for sustainability of effective mentoring practices are proffered and warrant the attention of governments, employers and the sector.
Research on Electric Vehicle Powertrain Systems Based on Digital Twin Technology
Authors: Li Chong , Lei Jianmei , Yang Liangyi , Xu Wei , You Yong
Published: October 2024

As a critical component of electric vehicles, the powertrain has a significant impact on the overall performance of vehicles. In addressing the challenge of lengthy testing cycles, this study develops a para model of the powertrain, utilizing digital twin (DT) technology, thereby establishing a framework for simulation testing of multi-controller intermodulation. We establish functional definition coverage testing by designing specific functional requirement use cases, and we validate the failure mechanism via fault injection use cases. The results indicate that the DT testing platform can effectively simulate the operational interactions among various controllers within the powertrain system. In comparison to traditional field testing, the digital twin-based testing methodology offers enhanced operational efficiency and allows for the examination of testing conditions that are impractical to implement in real vehicles, particularly in the context of fault injection testing, thus facilitating the early detection of potential safety risks within the system. The advancement of this technical solution holds significant practical implications for the future mass production and development of electric vehicles.
A Rigid–Flexible Supernumerary Robotic Arm/Leg: Design, Modeling, and Control
Authors: Xu Jiajun , Zhao Mengcheng , Zhang Tianyi , Ji Aihong
Published: October 2024

As humans’ additional arms or legs, supernumerary robotic limbs (SRLs) have gained great application prospects in many fields. However, current SRLs lack both rigidity/flexibility adaptability and arm/leg function conversion. Inspired by the muscular hydrostat characteristics of octopus tentacles, fiber-reinforced actuators (FRAs) were employed to develop SRLs simultaneously realizing flexible operation and stable support. In this paper, an SRL with FRAs was designed and implemented. The analytic model of the FRA was established to formulate the movement trajectory and stiffness profile of the SRL. A hierarchical hidden Markov model (HHMM) was proposed to recognize the wearer’s motion intention and control the SRL to complete the specific working mode and motion type. Experiments were conducted to exhibit the feasibility and superiority of the proposed robot.
Application of the Salp Swarm Algorithm to Optimal Design of Tuned Inductive Choke
Authors: Knypiński Łukasz , Kurzawa Milena , Wojciechowski Rafał , Gwóźdź Michał
Published: October 2024

The article presents an algorithm and optimization software designed for the optimal configuration of a tuned inductive choke. The optimization software consists of two main parts: an optimization procedure and a mathematical model for the designed electromagnetic devices. A lumped-parameters model of a tuned inductive choke was developed, with the device’s structure described by three design variables. As an optimality criterion, the multi-objective compromise function was adopted. The objective function merges the total inductances of the electromagnetic device under different operation states. The optimized structure was analyzed using the finite element method. The developed lumped-parameters model is characterized by good accuracy and can be successfully applied to optimize tuned inductive chokes for various rated parameters. The optimization procedure was adapted to the tuned inductive choke model by appropriately selecting the characteristic coefficient of the salp swarm algorithm. The reliability of the optimization software was verified through experimental measurements.
Comparative Policy Analysis of Renewable Energy Expansion in Mongolia and Other Relevant Countries
Authors: Nergui Otgonpurev , Park Soojin , Cho Kang-wook
Published: October 2024

The study aims to conduct a comparative analysis of policies governing the expansion of renewable energy in Mongolia and selected countries. Against the backdrop of global energy transitions and Mongolia’s recent energy challenges, this research aims to identify and evaluate policy frameworks that facilitate the sustainable growth of renewable energy sources. The study delves into the unique socio-economic and geopolitical context of Mongolia, emphasizing the nation’s energy dependence on Russia. The findings of this comparative analysis provide valuable insights for Mongolian policymakers, offering recommendations for enhancing domestic policies that encourage the diversification of energy sources and attract foreign investment. By drawing on successful practices from some countries, this paper aims to contribute to the formulation of effective and context-specific strategies for Mongolia to achieve a more sustainable and resilient energy landscape.
Transition from Electric Vehicles to Energy Storage: Review on Targeted Lithium-Ion Battery Diagnostics
Authors: Kostenko Ganna , Zaporozhets Artur
Published: October 2024

This paper examines the transition of lithium-ion batteries from electric vehicles (EVs) to energy storage systems (ESSs), with a focus on diagnosing their state of health (SOH) to ensure efficient and safe repurposing. It compares direct methods, model-based diagnostics, and data-driven techniques, evaluating their strengths and limitations for both EV and ESS applications. This study underscores the necessity of accurate SOH diagnostics to maximize battery reuse, promoting sustainability and circular economy objectives. By providing a comprehensive overview of the battery lifecycle—from manufacturing to recycling—this research offers strategies for effective lifecycle management and cost-effective, environmentally sustainable secondary battery applications. Key findings highlight the potential of second-life EV batteries in ESSs. The integration of the considered diagnostic methods was shown to extend battery lifespan by up to 30%, reduce waste, and optimize resource efficiency, which is crucial for achieving circular economy objectives. This paper’s insights are crucial for advancing sustainable energy systems and informing future research on improving diagnostic methods for evolving battery technologies.
Analysis of Energy Efficiency Parameters of a Hybrid Vehicle Powered by Fuel with a Liquid Catalyst
Authors: Osipowicz Tomasz , Gołębiewski Wawrzyniec , Lewicki Wojciech , Koniuszy Adam , Abramek Karol Franciszek , Prajwowski Konrad , Klyus Oleh , Gałdyński Dominik
Published: October 2024

A notable trend in the modern automotive market is the increased interest in hybrid cars. Hybrid cars combine a standard internal combustion engine with an electric motor solution. Research into increasing the energy efficiency of a conventional unit while meeting increasingly stringent exhaust emission standards is becoming a key postulate in this matter. This article discusses an analysis of modifying the fuel used by hybrid vehicles using the example of a selected drive unit equipped with a spark-ignition engine. This effect was tested after the Eco Fuel Shot liquid catalyst was added to the fuel. The research process was carried out in two stages, as follows: in road conditions using the Dynomet road dynamometer; and on the V-tech VT4/B2 chassis dynamometer. Tests were carried out to replicate road tests with a catalytic additive in the fuel. A mathematical model was created and the following energy efficiency parameters of the hybrid vehicle were calculated: the torque of the internal combustion engine, electric motor, and generator; the rotational speeds of the internal combustion engine, electric motor, and generator; the power of the internal combustion engine, electric motor, and generator; the equivalent fuel consumption of the electric motor and generator; the fuel consumption of the internal combustion engine, electric motor, and generator; and the mileage fuel consumption of the internal combustion engine, electric motor, and generator. The results of the tests made it possible to identify the benefits of using the tested liquid catalyst on the operation of the drive system of the analyzed hybrid vehicle. This research will be of benefit to both the demand side in the form of users of this category of vehicles, and the supply side represented by the manufacturers of power units.
Enhanced Wavelet Transform Dynamic Attention Transformer Model for Recycled Lithium-Ion Battery Anomaly Detection
Authors: Liu Xin , Huang Haihong , Chang Wenjing , Cao Yongqi , Wang Yuhang
Published: October 2024

Rapid advancements in electric vehicle (EV) technology have highlighted the importance of lithium-ion (Li) batteries. These batteries are essential for safety and reliability. Battery data show non-stationarity and complex dynamics, presenting challenges for current monitoring and prediction methods. These methods often fail to manage the variability seen in real-world environments. To address these challenges, we propose a Transformer model with a wavelet transform dynamic attention mechanism (WADT). The dynamic attention mechanism uses wavelet transform. It focuses adaptively on the most informative parts of the battery data to enhance the anomaly detection accuracy. We also developed a deep learning model with an improved Transformer architecture. This architecture is tailored for the complex dynamics of battery data time series. The model accounts for temporal dependencies and adapts to non-stationary behavior. Experiments on public battery datasets show our approach’s effectiveness. Our model significantly outperforms existing technologies with an accuracy of 0.89 and an AUC score of 0.88. These results validate our method’s innovation and effectiveness.
Autoencoder-Driven Training Data Selection Based on Hidden Features for Improved Accuracy of ANN Short-Term Load Forecasting in ADMS
Authors: Pajić Zoran , Janković Zoran , Selakov Aleksandar
Published: October 2024

This paper presents a novel methodology for short-term load forecasting in the context of significant shifts in the daily load curve due to the rapid and extensive adoption of Distributed Energy Resources (DERs). The proposed solution, built upon the Similar Days Method (SDM) and Artificial Neural Network (ANN), introduces several novelties: (1) selection of similar days based on hidden representations of day data using Autoencoder (AE); (2) enhancement of model generalization by utilizing a broader set of training examples; (3) incorporating the relative importance of training examples derived from the similarity measure during training; and (4) mitigation of the influence of outliers by applying an ensemble of ANN models trained with different data splits. The presented AE configuration and procedure for selecting similar days generated a higher-quality training dataset, which led to more robust predictions by the ANN model for days with unexpected deviations. Experiments were conducted on actual load data from a Serbian electrical power system, and the results were compared to predictions obtained by the field-proven STLF tool. The experiments demonstrated an improved performance of the presented solution on test days when the existing STLF tool had poor predictions over the past year.
Effect of Potassium on the Co-Combustion Process of Coal Slime and Corn Stover
Authors: Zheng Jing , Cai Chuanchuan , Ge Tao , Zhang Mingxu
Published: October 2024

In this study, the combined combustion characteristics and gaseous product emissions of coal slime and corn stover were compared at different blending ratios. The TG-DTG curves indicate that the optimal performance is achieved when the corn straw blending ratio is 20%. Furthermore, the TG-FTIR coupling results demonstrated an increase in gas species as the blending ratio increased. The composition analysis of ash samples formed at various combustion temperatures using XRD and XRF indicated that a portion of KCl in the fuel was released as volatile matter, while another part reacted with Al2O3 and SiO2 components in the slime to form silica–aluminate compounds and other substances. Notably, interactions between the components of slime and potassium elements in corn stover primarily occurred within the temperature range of 800–1000 °C. These findings contribute to a comprehensive understanding of biomass and coal co-firing combustion chemistry, offering potential applications for enhancing energy efficiency and reducing emissions in industrial processes.
The Emissions of a Compression-Ignition Engine Fuelled by a Mixture of Crude Oil and Biodiesel from the Lipids Accumulated in the Waste Glycerol-Fed Culture of Schizochytrium sp.
Authors: Zieliński Marcin , Dębowski Marcin , Kazimierowicz Joanna , Michalski Ryszard
Published: October 2024

Microalgae are considered to be a promising and prospective source of lipids for the production of biocomponents for conventional liquid fuels. The available sources contain a lot of information about the cultivation of biomass and the amounts and composition of the resulting bio-oils. However, there is a lack of reliable and verified data on the impact of fuel blends based on microalgae biodiesel on the quality of the emitted exhaust gas. Therefore, the main objective of the study was to present the emission characteristics of a compression-ignition engine fuelled with a blend of diesel fuel and biodiesel produced from the lipids accumulated in the biomass of a heterotrophic culture of Schizochytrium sp. The final concentrations of microalgal biomass and lipids in the culture were 140.7 ± 13.9 g/L and 58.2 ± 1.1 g/L, respectively. The composition of fatty acids in the lipid fraction was dominated by decosahexaenoic acid (43.8 ± 2.8%) and palmitic acid (40.4 ± 2.8%). All parameters of the bio-oil met the requirements of the EN 14214 standard. It was found that the use of bio-components allowed lower concentrations of hydrocarbons in the exhaust gas, ranging between 33 ± 2 ppm and 38 ± 7 ppm, depending on the load level of the engine. For smoke opacity, lower emissions were found in the range of 50–100% engine load levels, where the observed content was between 23 ± 4% and 53 ± 8%.
A Cooperative Multi-Agent Q-Learning Control Framework for Real-Time Energy Management in Energy Communities
Authors: Tortorelli Andrea , Sabina Giulia , Marchetti Barbara
Published: October 2024

Residential and commercial buildings are responsible for 35% of the EU energy-related greenhouse gas (GHG) emissions. Reducing their emissions is crucial for meeting the challenging EU objective of the agenda for becoming a net-zero continent by 2050. The diffusion and integration of distributed renewable energy sources (RESs) and energy storage systems (ESSs), as well as the creation of energy communities (ECs), have proven to be crucial aspects in reducing GHG emissions. In this context, this article proposes a multi-agent AI-based control framework to solve the EC’s energy management problem in the presence of distributed RESs and ESSs as well as considering a shared ESS. The objectives of the proposed control framework are to satisfy the EC members’ load demand to maximize self-consumption and to manage ESSs charging and discharging processes, to enforce cooperative behavior among the EC members by adopting fair and personalized strategies and to maximize EC members’ profits. The proposed control procedure is based on three sequential stages, each solved by a dedicated local RL agent exploiting the Q-Learning algorithm. To reduce the computational complexity of the proposed approach, specifically defined state aggregation criteria were defined to map the RL agents’ continuous state spaces into discrete state spaces of limited dimensions. During the training phase, the EC members’ profiles and the ESSs’ and RESs’ characteristics were randomly changed to allow the RL agents to learn the correct policy to follow in any given scenario. Simulations proved the effectiveness of the proposed approach for different costumers’ load demand profiles and different EC configurations. Indeed, the trained RL agents proved to be able to satisfy the EC members’ load demands to maximize self-consumption, to correctly use the distributed and shared ESSs, to charge them according to respective personalized criteria and to sell the energy surplus, prioritizing sales to the EC. The proposed control framework also proved to be a useful tool for understanding EC performance in different configurations and, thus, for properly dimensioning the EC elements.
Navigating the Complexities of Energy Economics and Sustainable Development: Insights from the Special Issue
Authors: Peng Rui
Published: October 2024

The Special Issue “New Insights into Energy Economics and Sustainable Development” includes a total of eight papers, focusing on different problems related to energy economics and sustainable development [...]
Exploring the Impact of Environmental Conditions and Bioreactors on Microalgae Growth and Applications
Authors: Do Sally , Du Zhi-Yan
Published: October 2024

Microalgae and their bioproducts have diverse applications, including wastewater remediation, CO2 fixation, and the synthesis of nutraceuticals, pharmaceuticals, and biofuels. However, the production of these organisms heavily relies upon environmental conditions, which can significantly impact growth. Furthermore, microalgae cultivation itself can be a source of economic and environmental concerns. Thus, microalgae growth systems have become a critical consideration for both research and industry, to bolster microalgae cultivation and address its accompanying issues. Both open and closed systems, such as raceway ponds and photobioreactors, respectively, are commonly used during the growth process but have their own advantages and drawbacks. However, for microalgae growth, photobioreactors may address most concerns as the system’s design lowers the risk of contamination and provides the ability to control the delivery of desired growth factors. To determine the appropriate system for targeted microalgae cultivation, it is crucial to determine factors such as the scale of cultivation and growth and productivity targets. Additionally, efficient usage of these growth systems and carefully selected incubation factors can aid in addressing some of the economic and environmental issues associated with microalgae production. This review will summarize the current applications of bioreactors in both research and industrial capacities and summarize growth and incubation factors for microalgae.
Proposal of Three Methods for Deriving Representative Mean Radiant Temperatures Considering Zone Spatial Distributions
Authors: Kwon Sung-Jin , Jo Jae-Hun , Lee Dong-Seok
Published: October 2024

Mean radiant temperature (MRT), which is a crucial factor for thermal comfort, varies within a space. This renders deriving the representative values for radiant heating and cooling control challenging. This study reviewed existing methods for deriving MRT in previous research and addressed their limitations by proposing a method for determining a representative MRT value. The existing methods were categorized as air temperature, single location, and area weighted. Three methods for deriving representative MRT values were proposed, considering the building’s usage, scale, and applicable system installations. The proposed methods were categorized as single-zone averaged, multi-zone averaged, and point-zone MRT. Experiments were conducted by distinguishing cases based on the control of equipment systems during heating and cooling periods. During the cooling season, the single-zone averaged MRT and air temperature differed by up to 4 °C, and the difference between the multi-zone averaged MRT and MRT at a point in the perimeter zone reached up to 7 °C. During the heating season, the single-zone averaged MRT and air temperature differed by up to 2.2 °C. Thus, the results of this study emphasize the importance of applying different methods of deriving representative MRT values depending on the size and usage of the building, and demonstrate that this facilitated more effective heating and cooling control systems.
Development and Optimization of a Micro-Baffle for the Enhancement of Heat Transfer in Film Boiling
Authors: Sarikaya Onur Muhammed , Kuzay Mustafa , Yilmaz Sibel , Demirel Ender
Published: October 2024

This study represents the development and optimization of a micro-baffle design to enhance heat transfer in film boiling. Numerical simulations are performed using an open-source computational fluid dynamics (CFD) model, which incorporates the Lee model for momentum source associated with the phase change, and the Volume of Fluid (VOF) method to capture bubble dynamics. A comparison of the numerical results with the previous numerical and experimental data confirmed the validity of the numerical model. The influence of key design parameters was systematically investigated. The results revealed that a vertical baffle provided the maximum performance. The optimal baffle design achieved a 57.4% improvement in the Nusselt number and a 66.4% increase in critical heat flux (CHF). Furthermore, the proposed design facilitated continuous bubble formation, even with a reduced temperature difference between the heated surface and the subcooled liquid, which is crucial for energy-efficient thermal management in engineering systems. Ultimately, this study demonstrates the potential of micro-baffle designs in controlling bubble dynamics and improving heat transfer in film boiling, thereby aiding the design of efficient thermal systems.
Application of the FDTD Method for Multivariate Analysis of the Influence of Conductivity and the Arrangement of Hollows Inside Bricks on the Values of Electric Field Intensity
Authors: Choroszucho Agnieszka , Szczegielniak Tomasz , Kusiak Dariusz
Published: October 2024

The article contains a numerical analysis of the effects of electromagnetic wave propagation in an area containing a non-ideal, non-uniform, and absorbing dielectric. The analysis concerned the influence of the structure of the building material and its electrical parameters on the electric field intensity. The analysis took into account the variability of the number of hollows in the brick, the width of hollows, as well as the arrangement of these hollows relative to each other using the example of two types of bricks. The article also provides the most commonly used values of electrical parameters for building materials (brick, plaster). For this reason, the article includes results for different values of conductivity (0–0.2 S/m). The FDTD (Finite Difference Time Domain) method was used for multivariate analysis. The aim was to verify the correctness of the numerical assumptions adopted. Using the example of the most commonly used wall structure in construction, the results obtained using the FDTD method were compared with values obtained using another numerical method, the finite element method (FEM). The influence of an additional layer of plaster on the considered wall on the electric field was also checked. The analysis showed that a symmetrical arrangement of bricks results in higher values of the electric field by an average of 20%. Of course, this depends on the length of the hollows and the number of holes. The highest field values occur at low conductivities (0–0.04 S/m). A brick wall with a larger number of hollows and a symmetrical brick arrangement shows the highest electric field intensity, especially for hollow sizes (0.009–0.015 m).
Correction: Wang et al. Studies on the Experimental Measurement of the Low-Frequency Aerodynamic Noise of Large Wind Turbines. Energies 2024, 17, 1609
Authors: Wang Wenjie , Yan Yan , Zhao Yongnian , Xue Yu
Published: October 2024

In the original publication [...]
Optical Fiber Technology for Efficient Daylighting and Thermal Control: A Sustainable Approach for Buildings
Authors: Udhwani Lokesh , Soni Archana , Cuce Erdem , Kumarasamy Sudhakar
Published: October 2024

Different direct solar harvesting systems for daylighting are being explored to achieve high uniform illumination deep within buildings at minimal cost. A promising solution to make these systems cost-effective is the use of plastic optical fibers (POFs). However, heat-related issues with low-cost POFs need to be addressed for the widespread adoption of efficient daylighting technologies. Previous studies have explored solutions for this overheating problem, but their effectiveness remains uncertain. This study proposes a low-cost fiber optic daylighting system integrated with a newly patented mechanical component designed to secure the fiber optic bundle at the focal point, providing three levels of heat filtration while ensuring uniform illumination. Our methodology involves selecting a small area, installing the setup, and measuring both heat and light readings, followed by validation through software simulations. The operational principle of this technology is explained, and experimental tests using lux meters and infrared thermometers were conducted to investigate the system’s characteristics. The three-level heat filtration device reduces temperature by approximately 35 °C at the surface of the optical fiber, and the average illumination of the room is around 400 lux. These results were further verified using RELUX simulation software. The findings demonstrate the promising potential of this new device in solar heat filtration and achieving uniform illumination. Recommendations for mitigating overheating damage and exploring heat filtering possibilities in new parabolic solar daylighting systems for further research are also provided.
Plant Diversity Research in Shangqiu Yellow River Ancient Course National Forest Park, China
Authors: Wang Xiaofang , Song Yiming , Zhang Xiangju , Hou Heping , Li Yongsheng
Published: October 2024

The Shangqiu Yellow River Ancient Course National Forest Park, the only national forest park in China created entirely from man-made forests, plays a critical role in ecological conservation. Our research employed plot surveys and quantitative ecological methods, including a diversity index analysis and importance value analysis, to investigate the diversity of arboreal, shrub, and herbaceous plants. This study revealed the composition and distribution of plant communities and analyzed invasive species. It identified dominant plant families, genera, and species and evaluated the types, distribution, and characteristics of invasive plants. We documented 70 families, 177 genera, and 254 species, highlighting that local environmental factors and human activities significantly affect the composition and distribution of plant communities. The presence of 29 invasive plant species poses a risk to the ecosystem. We constructed a phylogenetic tree of the plant community based on rbcL (ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit) gene sequences, revealing the evolutionary relationships among species, and evaluated the community’s stability using the NTI (nearest taxon index) and NRI (net relatedness index). This research aims to provide a scientific foundation for conserving plant diversity and promoting sustainable development, and it can inform ecological protection and biodiversity studies in similar regions.
Innovative Approaches to Camembert Cheese: Optimizing Prebiotics and Coagulation Conditions for Enhanced Quality and Nutrition
Authors: Benahmed Djilali Adiba , Metahri Mohammed Said , Lakabi Lynda , Tahraoui Hichem , Benseddik Abdelouahab , Besombes Colette , Allaf Karim
Published: October 2024

The objective of this study is to investigate how different factors, such as lactic acid bacteria, prebiotics (flaxseed powder, watercress seed powder, okra mucilage), and coagulation temperature influence the final quality of curd by conducting three optimization experiments and implementing a structured experimental plan. In the first phase, milk coagulation was assessed at 45 °C with various combinations of lactic acid bacteria (probiotics) and prebiotics (powdered flaxseed and watercress). In the second investigation phase, the effects of lowered probiotic and prebiotic (powdered flaxseed and watercress) concentrations were examined at the coagulation temperature of 38 °C. We investigated the concentration of lactic acid bacteria at 3 mg/mL of milk and the effects of temperature and prebiotics (okra mucilage and flaxseed powder). We observed short milk clotting time (2 s) using the optimized mixture (0.18 mg of probiotics, 1.5 mg of flaxseed powder, and 1.147 mg of watercress powder) per 10 mL of milk. It contrasts with the classical coagulation way optimized at (5.9 and 9.5 s), which were generated at optimal temperatures of 45 and 45.7 °C, respectively. Our new mixture improves the fermentation process of camembert cheese at 38 °C. This cheese had a high flavonoid content, fewer lactic bacteria and molds, a homogeneous texture, and no outer crust, and exceptional sensory attributes such as a creamy and fluid paste. These attributes suggest its potential benefits as a dairy product for individuals with cardiovascular and gastrointestinal conditions.
A Performance Benchmark for the PostgreSQL and MySQL Databases
Authors: Salunke Sanket Vilas , Ouda Abdelkader
Published: October 2024

This study highlights the necessity for efficient database management in continuous authentication systems, which rely on large-scale behavioral biometric data such as keystroke patterns. A benchmarking framework was developed to evaluate the PostgreSQL and MySQL databases, minimizing repetitive coding through configurable functions and variables. The methodology involved experiments assessing select and insert queries under primary and complex conditions, simulating real-world scenarios. Our quantified results show PostgreSQL’s superior performance in select operations. In primary tests, PostgreSQL’s execution time for 1 million records ranged from 0.6 ms to 0.8 ms, while MySQL’s ranged from 9 ms to 12 ms, indicating that PostgreSQL is about 13 times faster. For select queries with a where clause, PostgreSQL required 0.09 ms to 0.13 ms compared to MySQL’s 0.9 ms to 1 ms, making it roughly 9 times more efficient. Insert operations were similar, with PostgreSQL at 0.0007 ms to 0.0014 ms and MySQL at 0.0010 ms to 0.0030 ms. In complex experiments with simultaneous operations, PostgreSQL maintained stable performance (0.7 ms to 0.9 ms for select queries during inserts), while MySQL’s performance degraded significantly (7 ms to 13 ms). These findings underscore PostgreSQL’s suitability for environments requiring low data latency and robust concurrent processing capabilities, making it ideal for continuous authentication systems.
Spatiotemporal Analysis of Open Biomass Burning in Guangxi Province, China, from 2012 to 2023 Based on VIIRS
Authors: He Xinjie , Huang Qiting , Yang Dewei , Yang Yingpin , Xie Guoxue , Yang Shaoe , Liang Cunsui , Qin Zelin
Published: October 2024

Open biomass burning has significant adverse effects on regional air quality, climate change, and human health. Extensive open biomass burning is detected in most regions of China, and capturing the characteristics of open biomass burning and understanding its influencing factors are important prerequisites for regulating open biomass burning. The characteristics of open biomass burning have been widely investigated at the national scale, with regional studies often focusing on northeast China, but few studies have examined regional discrepancies in spatiotemporal variations over a long timescale in Guangxi province. In this study, we used the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), combined with land cover data and high-resolution remote sensing images, to extract open biomass burning (crop residue burning and forest fire) fire points in Guangxi province from 2012 to 2023. We explored the spatial density distribution and temporal variation of open biomass burning using spatial analysis methods and statistical methods, respectively. Furthermore, we analyzed the driving forces of open biomass burning in Guangxi province from natural (topography, climate, and plant schedule), policy, and social (crop production and cultural customs) perspectives. The results show that open biomass burning is concentrated in the central, eastern, and southern parts of the study area, where there are frequent agricultural activities and abundant forests. At the city level, the highest numbers of fire points were found in Baise, Yulin, Wuzhou, and Nanning. The open biomass burning fire points exhibited large annual variation, with high levels from 2013 to 2015 and a remarkable decrease from 2016 to 2020 under strict control measures; however, inconsistent enforcement led to a significant rebound in fire points from 2021 to 2023. Forest fires are the predominant type of open biomass burning in the region, with forest fires and crop residue burning accounting for 76.82% and 23.18% of the total, respectively. The peak period for crop residue burning occurs in the winter, influenced mainly by topography, planting schedules, crop production, and policies, while forest fires predominantly occur in the winter and spring, primarily influenced by topography, climate, and cultural customs. The results indicate that identifying the driving forces behind spatiotemporal variations is essential for the effective management of open biomass burning.
Driving Innovation Through Regulatory Design and Corporate Behaviour: A Case Study of Functional Food Industry in Japan
Authors: Sato Keigo , Kodama Kota , Sengoku Shintaro
Published: October 2024

This study addresses the critical need for innovation in the healthcare sector, particularly in Japan’s functional food industry, amid rising chronic diseases and healthcare costs. It explores the complex relationship between regulatory design and corporate behaviour, focusing on how companies’ compliance strategies influence their research and development (R&D) investments. A mixed-method approach was used, analysing data from 15 major dietary supplement companies and 74 products under Japan’s Foods with Function Claims (FFCs) regulation. The study reveals a correlation between companies’ engagement in the FFCs system and their preference for conducting in-house clinical trials, indicative of higher R&D investments (R = 0.66, p = 0.007), and that between the latter variable and average product sales, which is a measure of returns on regulatory compliance (R = 0.66, p = 0.008). Companies actively complying with FFCs regulations tend to conduct R&D and accumulate knowledge in-house, to innovate and differentiate their products, gaining competitive advantages. The study also highlights the role of a company’s size, market presence, and industry origins in shaping regulatory strategies, with firms from other industries using FFCs regulations to explore new business opportunities. The research underscores the importance of flexible regulatory frameworks that encourage R&D investment, leading to innovation and competitive advantages in the healthcare sector.
Chemical Composition and Crystallization Behavior of Oil and Fat Blends for Spreadable Fat Applications
Authors: Gerlei Maureen , Pierson Hugo , Ponçot Marc , Kahn Cyril J. F. , Linder Michel
Published: October 2024

To meet the expectations of European consumers, who prioritize agro-environmental factors and local resources, the substitution of fats (palm, coconut, shea) and achieving a balanced fatty acid profile in spreadable fats are gaining more attention. The crystallization at 4 °C of a lipid blend composed of rapeseed oil, anhydrous dairy fats, and emulsifiers was studied using a multi-scale approach (DSC and X-ray diffraction techniques) to understand the emergence of polymorphic structures. Although the addition of PUFA from rapeseed oil reduces the atherogenicity and thrombogenicity indices in the blend, controlling the cooling kinetics influences the shapes (needles and spherulites) and sizes of the crystalline structures (small crystals form at a cooling rate of 1 °C min−1, while larger crystals form at higher rates of 5 and 10 °C min−1). The crystallization behavior revealed differences in polymorphic forms at 4 °C in the blend, with a transition to different forms occurring more rapidly compared to dairy fat (stop-and-return method). The study shows crystalline coexistence (α, β′, and β) in a 2L lamellar structure, with the β′ form being predominant. This structure is ideal for formulating a spreadable product, offering good spreadability (SFC < 32% at 10 °C), mouthfeel, and nutritional benefits compared to butter.
Effect of Tree Density on Yield and Fruit Quality of the Grafted Hazelnut Cultivar ‘Tonda Francescana®’
Authors: Portarena Silvia , Proietti Simona , Moscatello Stefano , Zadra Claudia , Cinosi Nicola , Traini Chiara , Farinelli Daniela
Published: October 2024

Optimizing planting density is crucial for balancing resource competition, light penetration, and tree productivity in orchard systems. This study investigateed the impact of planting density on the yield and fruit quality of the hazelnut cultivar ‘Tonda Francescana®’ grafted onto Corylus colurna L. rootstocks. The research aimed to assess how different planting densities influenced light penetration, canopy volume, yield, and the nutritional profile of hazelnuts during their sixth growing season. Three planting densities were tested: 625, 1250, and 2500 trees per hectare (low, medium, and high density, respectively). The results show that medium-density planting provided the best balance between light availability, canopy development, and yield efficiency. The synthesis of monounsaturated fatty acids (MUFA) and α-tocopherol (vitamin E) was more prominent in the medium-density system (80.2% and 10.3%, respectively), suggesting a favorable metabolic response to moderate competition for resources. In contrast, high-density planting yielded the most per hectare (2898 kg/ha) but exhibited lower individual tree productivity (1.16 kg). Low-density planting had the highest light penetration (53%) but lower overall yield (822 kg/ha) and quality, with greater starch accumulation in the fruit. In general, medium-density planting optimized both yield and kernel quality, with potential implications for orchard management and breeding strategies to enhance hazelnut production and nutritional value.