bluuebunny/crossref_metadata_2025 huggingface dataset:
CO2 Emission from Caves by Temperature-Driven Air Circulation—Insights from Samograd Cave, Croatia
Authors: Buzjak Nenad , Gabrovšek Franci , Perșoiu Aurel , Pennos Christos , Paar Dalibor , Bočić Neven
Published: November 2024

Opposite to atmospheric CO2 concentrations, which reach a minimum during the vegetation season (e.g., June–August in the Northern Hemisphere), soil CO2 reaches a maximum in the same period due to the root respiration. In karst areas, characterized by high rock porosity, this excess CO2 seeps inside caves, locally increasing pCO2 values above 1%. To better understand the role of karst areas in the carbon cycle, it is essential to understand the mechanisms of CO2 dynamics in such regions. In this study, we present and discuss the spatial and temporal variability of air temperature and CO2 concentrations in Samograd Cave, Croatia, based on three years of monthly spot measurements. The cave consists of a single descending passage, resulting in a characteristic bimodal climate, with stable conditions during summer (i.e., stagnant air inside the cave) and a strong convective cell bringing in cold air during winter. This bimodality is reflected in both CO2 concentrations and air temperatures. In summer, the exchange of air through the cave’s main entrance is negligible, allowing the temperature and CO2 concentration to equilibrate with the surrounding rocks, resulting in high in-cave CO2 concentrations, sourced from enhanced root respiration. During cold periods, CO2 concentrations are low due to frequent intrusions of fresh external air, which effectively flush out CO2 from the cave. Both parameters show distinct spatial variability, highlighting the role of cave morphology in their dynamics. The CO2 concentrations and temperatures have increased over the observation period, in line with external changes. Our results highlight the role of caves in transferring large amounts of CO2 from soil to the atmosphere via caves, a process that could have a large impact on the global atmospheric CO2 budget, and thus, call for a more in-depth study of these mechanisms.
Assessing the Role of Climate Transition Bonds in Advancing Green Transformations in Japan
Authors: Zhao Zhiying , Huang Rong , Zhang Yanwu , Shiga Yuki , Shaw Rajib
Published: November 2024

This study investigates the potential of Climate Transition Bonds as strategic financial instruments in promoting green transformations within Japan’s carbon-intensive sectors. Through a qualitative case study approach, we assess four prominent bond issuances—Japan Government Bonds, MUFG Bonds, TEPCO Bonds, and SMBC Bonds—focusing on their contributions to emissions reduction, renewable energy expansion, and technological innovation. The analysis reveals that these bonds play a pivotal role in enabling Japan to advance its carbon neutrality goals by financing key decarbonization projects. However, significant challenges persist, including the limited scalability of emerging technologies, disparities in economic benefits across sectors, and governance inefficiencies that may hinder optimal outcomes. The findings underscore the necessity of refining collaborative governance frameworks to enhance transparency, stakeholder inclusivity and regulatory oversight in the deployment of these bonds. This paper contributes to the discourse on sustainable finance by elucidating the policy implications of climate transition bonds, proposing avenues for improved governance, and highlighting the structural adjustments required to align these financial mechanisms with Japan’s long-term sustainability objectives.
Biomarkers of Creatine Metabolism in Humans: From Plasma to Saliva and Beyond
Authors: Nedeljkovic David D. , Ostojic Sergej M.
Published: November 2024

The literature on creatine biomarkers in various bodily fluids remains limited. The purpose of this review is to explore the available data regarding the presence of molecules considered biomarkers of creatine metabolism—namely creatine, guanidinoacetate, and creatinine—across different bodily fluids and matrices. In addition to providing reference values for each biofluid, the paper reports concentrations of these biomarkers in different pathologies. The impairment of creatine metabolism is most extensively studied in creatine deficiency syndromes, which are characterized by genetic deficiencies in either the enzymes involved in creatine biosynthesis or creatine transport. However, other conditions may also influence creatine metabolism to some extent. Our paper also focuses on the transport pathways of these metabolites from their originating tissues to various bodily fluids, typically mediated by the creatine transporter (SLC6A8), with evidence suggesting the involvement of other transporters as well. Gas and liquid chromatography have replaced traditional methods for the analytical detection of biomarkers of creatine metabolism and are now commonly used for this purpose. The paper also discusses the differences and variations between these analytical methods.
Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care
Authors: Haykal Diala
Published: November 2024

Objectives: Artificial intelligence (AI) is transforming aesthetic dermatology, introducing new opportunities for personalized, predictive, and adaptive approaches in skin diagnostics, treatment planning, and patient management. This review examines AI’s evolving role in enhancing diagnostic precision, individualizing treatments, and supporting dynamic patient care, with a focus on practical implementation in clinical settings. Results: This piece highlights how AI-based imaging and predictive tools enable more precise diagnostics and tailored treatment protocols, leading to improved patient outcomes and satisfaction. Some of the key benefits of AI in aesthetic dermatology include the ability to detect subtle skin changes, simulate treatment outcomes, and adjust interventions in real time. However, this manuscript also addresses significant challenges that practitioners face, such as technical constraints, data privacy concerns, algorithmic biases, and financial barriers, which impact the accessibility and efficacy of AI across diverse patient populations. Conclusions: While AI holds significant potential to enhance aesthetic dermatology, its responsible integration requires addressing these challenges through clinician training, ethical guidelines, and robust data security measures. Effective use of AI will depend on collaboration between technology developers, clinicians, and regulatory bodies. Perspectives: Looking forward, the development of diverse, inclusive datasets and transparent, patient-centered AI models will be essential to ensure that AI’s benefits reach all patients equitably and safely. By prioritizing these factors, AI-driven technologies would become a reliable, accessible, and transformative element of aesthetic dermatology practice.
Primary Central Nervous System Lymphoma (PCNSL) Following Thyroid Cancer Surgery: A Case Report of Misdiagnosed Brain Metastasis and Literature Review
Authors: Li Yilin , Liang Tingyu , Xing Hao , Wang Yu , Wang Kuanyu , Ma Wenbin
Published: November 2024

Objectives: This article reports a rare case of primary central nervous system lymphoma (PCNSL) found in a patient with thyroid cancer after surgery. Methods: The patient was initially misdiagnosed with brain metastases, and the diagnosis of PCNSL was later confirmed by pathology. Results: The analysis of this case and review of the relevant literature explores the possible mechanisms of the coexistence of thyroid cancer and PCNSL, as well as their diagnostic, differential diagnostic, and therapeutic challenges. Conclusions: The article suggests a possible correlation between the coexistence of multiple cancers and autoimmune diseases and emphasizes that disease cannot be only considered in a monolithic way.
Atypical Presentation of Spindle Cell Lipoma in a Young Male with a History of Malignant Melanoma
Authors: Theriot Ty , Cattar John David , Falgout Lacey , Culotta Nicholas , Haas Christopher
Published: November 2024

Spindle cell lipoma (SCL) is a benign adipocytic tumor usually found in the subcutis of the posterior neck, upper back, and shoulder, predominantly in middle-aged males. This case report describes an atypical presentation of SCL in a 26-year-old male with a history of malignant melanoma. The patient presented with an erythematous plaque with central hyperpigmentation on the right upper arm, an uncommon location and presentation for SCL. Histopathological examination revealed an atypical myxoid spindle cell neoplasm with CD34 positivity and an overlying mildly atypical compound melanocytic nevus. The unusual clinical and histological features, combined with the patient’s melanoma history, complicated the differential diagnosis, which included dermatofibrosarcoma protuberans (DFSP) and solitary fibrous tumors (SFTs). A wide local excision with 2 cm margins was performed, and subsequent pathology confirmed clear margins, supporting the diagnosis of SCL. This case highlights the importance of including SCL in the differential diagnosis of CD34-positive spindle cell tumors, even when clinical and histological presentations are atypical, and underscores the need for thorough histopathological evaluation and a broad differential diagnosis in patients with a history of melanoma.
Substance Use and Mental Health in Emerging Adult University Students Before, During, and After the COVID-19 Pandemic in Mexico: A Comparative Study
Authors: Hernandez-Fuentes Gustavo A. , Romero-Michel Jessica C. , Guzmán-Sandoval Veronica M. , Diaz-Martinez Janet , Delgado-Enciso Osiris G. , Garcia-Perez Ruth R. , Godínez-Medina Monserrat , Zamora-Barajas Vicente , Hilerio-Lopez Angel G. , Ceja-Espiritu Gabriel , Toro-Equihua Mario Del , Martinez-Fierro Margarita L. , Garza-Veloz Idalia , Rodriguez-Sanchez Iram P. , Sanchez-Ramirez Carmen A. , Ramirez-Flores Mario , Delgado-Enciso Ivan
Published: November 2024

Background: The COVID-19 pandemic significantly impacted mental health and substance use patterns, particularly among young adults. Objective: This study aimed to assess changes in anxiety, depression, self-esteem, and substance use among university students in Mexico before, during, and after the pandemic. Methods: Using a repeated cross-sectional design, this study was conducted with university students in Mexico across three periods: pre-pandemic (2017 and 2019); during the pandemic (2021); and post-pandemic (2023). A total of 2167 students were interviewed during one of the three periods. Standardized scales measured anxiety, depression, self-esteem, Erotic Response and Sexual Orientation Scale (EROS), and substance use. Results: showed a marked and significant increase in the proportion of students with anxiety (40.0%, 71.7%, and 79.6%) and depression (14.4%, 61.9%, and 62.6%) during the pre-pandemic, pandemic, and post-pandemic periods, respectively. Self-esteem significantly decreased during and after the pandemic, compared to pre-pandemic, particularly among females. The proportion of students categorized as moderate/high-risk for their substance use changed over time, showing a reduction in alcohol use (from 29.9% to 20.2%) and tobacco use (from 26.0% to 18.2%) but an increase in sedative use (from 7.1% to 11.7%), before vs after the pandemic, respectively. Multivariate analysis revealed that anxiety, low self-esteem, and increased sedative use were consistently linked to a heightened risk of depression during and after the pandemic. Notably, anxiety and depression levels remained in a proportion significantly elevated even in the post-pandemic period. Conclusions: These findings underscore the enduring impact of the COVID-19 pandemic on the mental health of university students, highlighting the urgent need for targeted interventions, early detection strategies, and customized educational programs to effectively support students’ mental well-being in the ongoing post-pandemic era.
The Thermodynamics of the Van Der Waals Black Hole Within Kaniadakis Entropy
Authors: Kaczmarek Adam Z. , Sekhmani Yassine , Szczȩśniak Dominik , Rayimbaev Javlon
Published: November 2024

In this work, we have studied the thermodynamic properties of the Van der Waals black hole in the framework of the relativistic Kaniadakis entropy. We have shown that the black hole properties, such as the mass and temperature, differ from those obtained by using the the Boltzmann–Gibbs approach. Moreover, the deformation κ-parameter changes the behavior of the Gibbs free energy via introduced thermodynamic instabilities, whereas the emission rate is influenced by κ only at low frequencies. Nonetheless, the pressure–volume (P(V)) characteristics are found independent of κ and the entropy form, unlike in other anti-de Sitter (AdS) black hole models. In summary, the presented findings partially support the previous arguments of Gohar and Salzano that, under certain circumstances, all entropic models are equivalent and indistinguishable.
Prospects of Agrotourism Development in the Region
Authors: Safarov Bahodirhon , Amirov Akmal , Mansurova Nargiza , Hassan Thowayeb H. , Hasanov Habibullo , Pereș Ana Cornelia , Bilalov Bahadur , Turdibekov Khasan
Published: November 2024

For every nation, the era of transition to a market economy is marked by a severe lack of financial resources. Bringing in sectors of the economy that yield the fastest and most efficient returns is one strategy to develop and overcome this issue. Agrotourism, which is seen as a new trend in the tourism business, is one of these industries. The Samarkand region is used as an example to examine the scientific and theoretical underpinnings of agrotourism as well as its geographical characteristics in this article. Furthermore, an agrotourism map of the region was created by evaluating each location’s potential for agrotourism, classifying the regions based on how desirable they are for agrotourism, and identifying the facilities and resources available for agrotourism. Factors affecting the market of tourist services in the area were studied, and forecast values of the volume of tourist services were determined.
Convergence and Divergence Tendencies in the European Union: New Evidence on the Productivity/Institutional Puzzle
Authors: Borović Zoran , Radicic Dragana , Ritan Vladana , Tomaš Dalibor
Published: November 2024

The World Bank (WB) has described the European Union (EU) as a convergence machine, and the real and institutional convergence has been achieved for a long period of time, and EU’s cohesion policy, alongside the Recovery and Resilience Facility (RRF), remains crucial for driving reforms and fostering investments that promote growth. But, in the last two decades this convergence machine has stopped working, and the convergence process has turned in the divergence. The divergence process poses a great risk for the smooth functioning of the EU, and it increases vulnerability of the EU to negative economic shocks. Productivity and institutional convergence are a necessary precondition for the smooth functioning of the EU, reducing differences in standards of living, increasing resilience, and achieving environmental sustainability. In the present paper, we will apply log t-test over the period 2003–2023 to investigate the formation of productivity and institutional convergence clusters. Our goal is to identify which countries belong to the poor productivity/institutional clubs, and to provide the necessary policy implications. Results indicate the existence of multiple steady states, which means that EU is vulnerable to external economic shocks
The Effect of Governance on the Relationship Between Research and Development Expenditure and Economic Growth in South Africa
Authors: Chagwiza Clarietta , Owusu-Sekyere Emmanuel , Kapfudzaruwa Farai
Published: November 2024

This study analyzes the effects of governance on the relationship between research and development expenditure and economic growth in South Africa using annual data from 1997 to 2022 using an autoregressive distributed lag (ARDL) model. The calculated F-tests for the two models in the ARDL bounds testing approach to cointegration revealed a long-run relationship between the series. In the model without a mediating factor, an insignificant impact of research and development (R&D) expenditure on economic growth is reported. However, when R&D interacted with governance, a positive and significant impact was observed. This implies that for R&D to have a positive impact on economic growth, there is a need for strong and quality governance to provide a conducive productive environment. Furthermore, given the ambiguous relationship between governance and economic growth, the Granger causality test results showed that governance granger-causes economic growth and not the other way round. The findings presented in this paper are expected to provide some useful insights for policymakers in South Africa and the African continent. The findings demonstrate the important role that governance plays in enhancing the developmental performance of critical macro-economic growth factors. The study potentially generates new dimensions (by including governance as a mediating factor) in the understanding of how the impact of R&D and other macroeconomic parameters on economic growth can be promoted.
Promoting Teaching and Learning Through Research-Informed Professional Development: The Leadership for Learning Programme in Australia and China
Authors: Siraj Iram , Huang Runke
Published: November 2024

The fragmented provision of training for early childhood educators has highlighted the imperative need for research-informed professional development (PD) programmes to enhance educator professionalism. This study evaluates the effectiveness of a research-informed in-service PD programme—“Leadership for Learning”—through cluster randomised controlled trials in Australia and China. In Australia, the study involved 83 early-years services, and 1346 4–5-year-old children. In China, the study adapted the PD programme both educationally and culturally, involving 24 preschools, 95 classrooms, 202 educators, and 547 children aged 3–5 years. The comparative findings revealed that the PD programme significantly improved scores on the ECERS-E and SSTEW classroom quality rating scales in both Australia and China. Regarding children’s outcomes, the Australian PD programme significantly enhanced children’s numeracy development, social–emotional development, and expressive language, but not vocabulary, while the Chinese adaptation improved literacy development but not numeracy. This study has important implications for the implementation of PD programmes and cross-cultural educational research, highlighting the need for context-specific adaptations to maximise the effectiveness of PD interventions.
The Mediating Role of Generative AI Self-Regulation on Students’ Critical Thinking and Problem-Solving
Authors: Zhou Xue , Teng Da , Al-Samarraie Hosam
Published: November 2024

Within the rapid integration of AI into educational settings, understanding its impact on essential cognitive skills is crucial for developing effective teaching strategies and improving student outcomes. This study examines the influence of generative artificial intelligence (GenAI) on students’ critical thinking and problem-solving skills in higher education. Our research specifically investigates how the perceived ease of use, usefulness, and learning value of GenAI tools might influence students’ critical thinking and problem-solving skills, and whether self-regulation serves as a mediator in this relationship. Utilising a quantitative approach, we surveyed 223 students and analysed their responses using a structural equation modelling method. The results reveal that the ease of use of GenAI significantly enhances self-regulation, which in turn positively impacts both the critical thinking and problem-solving abilities of students. However, the perceived usefulness and learning value of GenAI were not found to significantly influence these skills through self-regulation. These findings suggest that, while AI tools can offer an environment conducive to developing higher-order cognitive skills, this might not necessarily translate to the enhancement of students’ skills. This research contributes to the ongoing literature on the role of technology in education by highlighting the importance of designing GenAI tools that support self-regulated learning. Furthermore, it calls for educators and developers to focus not just on the functionality of AI, but also on how these tools can be integrated into curricula to effectively support critical thinking and problem-solving. The practical implications of our research highlight the need for AI tools that are user-friendly and aligned with educational goals, enhancing their adoption and effectiveness in improving student outcomes. It is crucial for educators to integrate strategies that promote self-regulation within AI-enhanced learning environments to maximise their impact on student learning.
Dedicated HVAC Technology in the Renovation of Historic Buildings on the Example of the Marshal Pilsudski Manor in Sulejówek
Authors: Gleń Piotr , Wrana Jan , Struzik Wojciech , Jaromin-Gleń Katarzyna
Published: November 2024

The article investigates HVAC (heating, ventilation, and air conditioning) technologies aimed at mitigating Primary Energy (PE) consumption in renovated buildings. This research is part of a broader initiative focused on enhancing air quality and reducing the carbon footprint within the fields of architecture and urban planning. Conducted since 2018 by a team from the Institute of Architectural Design at the Department of Contemporary Architecture, Faculty of Civil Engineering and Architecture, University of Technology in Lublin, the study exemplifies the application of these technologies at the historic Marshal Piłsudski’s “Milusin” Manor House in Sulejówek, near Warsaw. The primary objective of this research is to present HVAC solutions, particularly a free cooling and heating system, which are specifically tailored for the renovation of historic structures. This technology effectively recovers thermal energy from groundwater, achieving low energy consumption levels while simultaneously minimizing CO2 emissions.
Correction: Enescu, D. Heat Transfer Mechanisms and Contributions of Wearable Thermoelectrics to Personal Thermal Management. Energies 2024, 17, 285
Authors: Enescu Diana
Published: November 2024

The temperature t noted in the original publication [...]
Analysis of Energy Effort in Terms of Changes in Stiffness and Damping of Tire Wheels and Low Car Speed
Authors: Zuska Andrzej , Jackowski Jerzy
Published: November 2024

This paper presents the results of a study on the effects of low car speeds and the elastic-damping properties of tires on steering effort. “Steering effort” is a measure of the demand/energy consumption of the power steering system that limits the force applied by the driver to the steering wheel. Low driving speeds, on the other hand, are characteristic of urban traffic, where we would like to see as many electric cars moving as possible. An increase in “driver effort” means a higher electricity consumption and shorter car range. In this study, energy intensity was evaluated for a typical maneuver such as a double lane change. For this purpose, measurements were made of the torque on the steering wheel, the speed of the car, and the lateral accelerations acting on the car. A torque wheel, an optoelectronic sensor for measuring the components of the car’s motion, and an acceleration sensor were used for the study. The test subjects were two passenger cars with hydraulic power steering systems. The tests were carried out for four values of air pressure in the tires. This made it possible to determine four work charts for each wheel. The work charts made it possible to identify the stiffness and damping coefficients of the tires for the tested cars. The values of the coefficients were used to determine the correlation between the directional coefficient of the regression lines of the skeletal axes of the elastic and damping characteristics and the index determining steering effort.
Wind Turbine Wake Regulation Method Coupling Actuator Model and Engineering Wake Model
Authors: Ma Kuichao , Zou Jiaxin , Fan Qingyang , Wang Xiaodong , Zhang Wei , Fan Wei
Published: November 2024

The wake effect is one of the main factors affecting the power generation of wind farms. Wake regulation is often used to reduce the wake interference between wind turbines. Accurate assessment of the wake flow of wind turbine is essential to wake regulation. Engineering wake models are widely used for rapid evaluation of the wake at present due to lower computational resource cost. However, the selection of empirical parameters of the wake model has significant influence on the prediction accuracy, especially in the case of yaw. The actuator model based on CFD simulation has less dependence on empirical parameters and higher simulation accuracy. However, the computational cost is too high for wake regulation for large wind farms. This paper proposed an improved wake regulation method that combines the advantages of the actuator line model (ALM) method and the engineering wake mode. The simulation results of the ALM is used to calibrate the empirical parameters of the engineering wake model. The calibrated wake model can be used to optimize the yaw angle of wind turbines during wake regulation. The accuracy of two models is compared using wind tunnel experimental data. The ALM results give better agreement to the experimental data. The Horns Rev wind farm case is used for the coupled method verification. The power generation increase using the engineering wake model is obviously greater than that of the ALM. After calibrating the wake model, the gap between the two power predictions is greatly narrowed, which proves the effectiveness of the proposed method. The proposed coupling method can be used to improve the credibility of the wake regulation with affordable computational cost.
Multiscale Pore Architecture and Its Influence on Porosity, Permeability, and Fluid Flow in Tight Gas Reservoirs of the Shihezi H8 Formation, Ordos Basin
Authors: Adnan Muhammad Toseef , Zhang Guishan , Chang Bin , Wei Hu , Peng Ren , Chang Wang , Wang Liang
Published: November 2024

Characterizing pore network morphology and its influence on critical reservoir properties such as porosity, permeability, and fluid flow pathways is imperative for maximizing production from tight gas sandstone reservoirs. This study integrated petrographic and pore-scale analyses to investigate diagenetic effects on the Shihezi H8 Formation, Ordos Basin, China. Sixty core plug samples spanning depositional facies from wells were analyzed using thin-section petrography, scanning electron microscopy, laser grain size analysis, mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR), and porosity–permeability measurements. Thin-section observations indicated that formation primarily comprises litharenite and sub-litharenite sandstones deposited in fluvial–deltaic environments composed primarily of quartz and feldspar grains. Diagenesis caused significant porosity reduction through initial mechanical compaction, 3–13% quartz cementation, and localized dissolution, resulting in secondary porosity of up to 5%. Three diagenetic facies were differentiated based on variations in mineralogy and diagenetic alterations. MICP classified pore networks into three reservoir types defined by mean throat radii ranging from 0.091 to 0.270 μm. NMR distinguished pore architectures as uniformly microporous, bimodally micro–mesoporous, and heterogeneously distributed multiscale pores. Larger throat radii correlated positively with higher porosity (up to 8.6%), gas porosity (10.5%), and permeability (0.1911 mD). Grain size analysis demonstrated a positive correlation between mean detrital grain diameter (>2.6 φ, 0.18 mm, (180 µm)), and significantly elevated average porosity (5–8%) compared to finer lithologies, implying depositional energy and sorting regimes. Integrating depositional features, diagenetic alterations, and multiscale pore architecture characterization quantitatively and qualitatively enhanced predictions of heterogeneity in hydrocarbon flow behavior amongst these tight reservoirs. The optimized insights from this integrated study provide a framework to guide development strategies and field appraisal methods for maximizing recovery from unconventional tight gas formations.
A GWO-Based Indirect IMC-PID Controller for DC-DC Boost Converter
Authors: Choubey Ashish , Jain Sachin Kumar , Padhy Prabin Kumar
Published: November 2024

A PID controller design using an internal model control (IMC) approach is a well-established method for controller tuning in a DC-DC boost converter. This study introduces an innovative implementation of a novel indirect Internal Model Control (IMC) strategy for PID controller design, tailored specifically for a DC-DC boost converter. While the indirect IMC approach has been documented in prior research, its application to boost converters signifies a substantial contribution to the field. The proposed method simplifies the tuning process by focusing exclusively on the plant shifting parameter ψ, thereby eliminating the need for an IMC filter. Optimal tuning is achieved through the Grey Wolf Optimization (GWO) method, which enhances the controller’s stability, robustness, and transient response in the presence of disturbances commonly encountered in boost converter operation. Extensive simulations are performed in a MATLAB Simulink environment to compare the performance of the GWO-based indirect IMC-PID controller with traditional PID and IMC-PID designs. Performance is assessed based on transient response parameters and performance indices, such as IAE, ISE, ITAE, and ITSE. Results reveal that the GWO-optimized indirect IMC-PID controller significantly outperforms conventional controllers, demonstrating enhanced servo and regulatory behaviors.
Chemistry of Ammonia/Hydrogen and Ammonia/n-Heptane Fuels: Reaction Mechanism Updating and Chemical Kinetic Analysis
Authors: Chen Qihang , Lyu Lin , Huang Yongzhong , Yang He , Liang Junjie , Zhu Neng
Published: November 2024

For spark ignition and compression ignition ammonia engines, a typical approach to ensure stable operation involves the blending of ammonia with hydrogen and diesel, respectively. For the ammonia/hydrogen fuel, in this study a comprehensive comparison was conducted firstly for the differences among existing chemical mechanisms according to the experimental data of ignition, oxidation, and flame propagation. The result indicates that the current reaction mechanisms for ammonia/hydrogen fuel exhibit high prediction accuracy only within limited condition ranges. Subsequently, considering the completeness of combustion reaction pathways for ammonia/hydrogen fuel, a chemical mechanism of ammonia and ammonia/hydrogen fuel was developed and optimized in this study, and the comprehensive validation demonstrates the accuracy of the developed mechanism. On this basis, the ammonia mechanism was integrated with the detailed n-heptane mechanism to derive a mechanism for ammonia/diesel fuel that includes 1351 species and 6227 reactions. The good performance of this mechanism was demonstrated in terms of the experimental data of ignition and oxidation. In addition, the ignition sensitivity and reaction pathways of ammonia/hydrogen fuel were investigated based on the constructed mechanism, and the significance of C3–C7/N reactions was also analyzed for the ammonia/diesel fuel ignition process.
A Comprehensive Analysis of the Influencing Factors of Interharmonics on a Distributed PV Grid-Connected Power Generation System
Authors: Mao Mingxuan , Ni Xiaoyu , Xu Zhao , Sun Haojin , Yin Chengqi
Published: November 2024

In this paper, a detailed mathematical model for the interharmonic current in a distributed grid-connected photovoltaic (PV) system is proposed and the factors affecting its output characteristics are analyzed comprehensively. First of all, a transfer function approach is used to build a mathematical model for the interharmonic current in grid-connected PV systems. Then, the equation of the PV generator output characteristics is linearized. Furthermore, a real-time calculation method of the amplitude of interharmonic current is introduced based on the established mathematical model. Moreover, a series of comparative tests are conducted, and how various factors such as the MPPT parameters, the main circuit parameters and the environmental factors affect the interharmonic current are investigated. Finally, a series of simulation and experimental tests are conducted to verify the accuracy of the mathematical model for the interharmonic current and the real-time calculation method. The results show that the proposed model is useful for improving the performance of grid-connected PV systems in terms of the behavior of the interharmonic current. Moreover, the mathematical model and the analysis of the influencing factors provide valuable insights for improving system efficiency and reliability in practical applications.
The Impact of Green Finance and Technological Innovation on Corporate Environmental Performance: Driving Sustainable Energy Transitions
Authors: Chen Sonia Chien-i , Xu Xinlei , Own Chung-Ming
Published: November 2024

As global sustainability imperatives increase, understanding how green finance policies and technological innovation influence corporate environmental performance has become a relevant issue. This study examines the impact of green finance on corporate environmental practices, particularly focusing on how innovation enhances sustainable energy transitions. A difference-in-differences (DID) approach was employed. This research compares corporate environmental performance before and after the implementation of green finance policies across treated and control groups. This method allows for isolating the effect of green finance by controlling for temporal and individual factors, providing robust insights into policy efficacy. Our findings indicate a statistically significant improvement in environmental performance, particularly among larger, state-owned enterprises in China’s eastern regions. The findings also underscore the moderating role of innovation in optimizing green finance outcomes. Finally, important implications for policymakers aiming to drive corporate sustainability are offered.
Research of Heat Transfer Characteristics of Supercritical CO2 in Spiral Tube Heat Exchangers
Authors: Cheng Jian , Wang Wendong , Yu Jianyang , Jiang Huadong , Gao Jianmin , Xu Dan
Published: November 2024

The spiral tube heat exchanger has the advantages of stable structure, high space utilization rate, and strong heat transfer ability. Supercritical carbon dioxide (s-CO2) has the advantages of high thermal conductivity, high specific heat capacity, and low viscosity. When the spiral tube heat exchanger uses supercritical carbon dioxide as the heat transfer medium, the two complement each other’s advantages and can further improve the heat transfer efficiency and optimize the space utilization rate. However, under the coupling influence of factors such as centrifugal force and buoyancy force, the heat transfer process of s-CO2 in the spiral tube is extremely complex. At present, there is no design criterion or empirical correlation with strong universality in the industrial field. Based on this, this paper mainly uses ANSYS FLUENT, a numerical simulation software suitable for numerical simulation, to study the influence of internal vortex field and secondary flow intensity on the thickness of thermal boundary layers through a combination of numerical simulation and theoretical analysis. At the same time, by changing various operating and structural parameters, the heat transfer characteristics of supercritical s-CO2 in the spiral tube heat exchanger are analyzed and summarized. In addition, we also established a new buoyancy factor, Fu, and tested that when Fu < 1.6 × 10−5, the effect of the buoyancy lift in the pipeline disappeared. At the same time, a correlation formula for predicting the heat transfer performance of spiral tube heat exchangers with a Nu number error less than 20% is established in this paper, which can provide solid theoretical guidance for industrial application.
Correlating Sediment Erosion in Rotary–Stationary Gaps of Francis Turbines with Complex Flow Patterns
Authors: Acharya Nirmal , Gautam Saroj , Chitrakar Sailesh , Iliev Igor , Dahlhaug Ole Gunnar
Published: November 2024

Secondary flows in Francis turbines are induced by the presence of a gap between guide vanes and top–bottom covers and rotating–stationary geometries. The secondary flow developed in the clearance gap of guide vanes induces a leakage vortex that travels toward the turbine downstream, affecting the runner. Likewise, secondary flows from the gap between rotor–stator components enter the upper and lower labyrinth regions. When Francis turbines are operated with sediment-laden water, sediment-containing flows affect these gaps, increasing the size of the gap and increasing the leakage flow. This work examines the secondary flows developing at these locations in a Francis turbine and the consequent sediment erosion effects. A reference Francis turbine at Bhilangana III Hydropower Plant (HPP), India, with a specific speed (Ns = 85.4) severely affected by a sediment erosion problem, was selected for this study. All the components of the turbine were modeled, and a reference numerical model was developed. This numerical model was validated with numerical uncertainty measurement and experimental results. Different locations in the turbine with complex secondary flows and the consequent sediment erosion effects were examined separately. The erosion effects at the guide vanes were due to the development of leakage flow inside the guide vane clearance gaps. At the runner inlet, erosion was mainly due to a leakage vortex from the clearance gap and leakage flow from rotor–stator gaps. Toward the upper and bottom labyrinth regions, erosion was mainly due to the formation of secondary vortical rolls. The simultaneous effects of secondary flows and sediment erosion at all these locations were found to affect the overall performance of the turbine.
Challenges of Artificial Intelligence Development in the Context of Energy Consumption and Impact on Climate Change
Authors: Pimenow Sergiusz , Pimenowa Olena , Prus Piotr
Published: November 2024

With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for enhancing energy efficiency and mitigating the impacts of climate change. However, their implementation has a dual character: on one hand, AI facilitates sustainable solutions, including energy optimization, renewable energy integration and carbon reduction; on the other hand, the training and operation of large language models (LLMs) entail significant energy consumption, potentially undermining carbon neutrality efforts. Key findings include an analysis of 237 scientific publications from 2010 to 2024, which highlights significant advancements and obstacles to AI adoption across sectors, such as construction, transportation, industry, energy and households. The review showed that interest in the use of AI and ML in energy efficiency has grown significantly: over 60% of the documents have been published in the last two years, with the topics of sustainable construction and climate change forecasting attracting the most interest. Most of the articles are published by researchers from China, India, the UK and the USA, (28–33 articles). This is more than twice the number of publications from researchers around the rest of the world; 58% of research is concentrated in three areas: engineering, computer science and energy. In conclusion, the review also identifies areas for further research aimed at minimizing the negative impacts of AI and maximizing its contribution to sustainable development, including the development of more energy-efficient AI architectures and new methods of energy management.
Techno-Economic Analysis of Territorial Case Studies for the Integration of Biorefineries and Green Hydrogen
Authors: Giuliano Aristide , Stichnothe Heinz , Pierro Nicola , De Bari Isabella
Published: November 2024

To achieve sustainable development, the transition from a fossil-based economy to a circular economy is essential. The use of renewable energy sources to make the overall carbon foot print more favorable is an important pre-requisite. In this context, it is crucial to valorize all renewable resources through an optimized local integration. One opportunity arises through the synergy between bioresources and green hydrogen. Through techno-economic assessments, this work analyzes four local case studies that integrate bio-based processes with green hydrogen produced via electrolysis using renewable energy sources. An analysis of the use of webGIS tools (i.e., Atlas of Biorefineries of IEA Bioenergy) to identify existing biorefineries that require hydrogen in relation to territories with a potential availability of green hydrogen, has never been conducted before. This paper provides an evaluation of the production costs of the target products as a function of the local green hydrogen supply costs. The results revealed that the impact of green hydrogen costs could vary widely, ranging from 1% to 95% of the total production costs, depending on the bio-based target product evaluated. Additionally, hydrogen demand in the target area could require an installed variable renewable energy capacity of 20 MW and 500 MW. On the whole, the local integration of biorefineries and green hydrogen could represent an optimal opportunity to make hydrogenated bio-based products 100% renewable.
The Design and Implementation of an Intelligent Carbon Data Management Platform for Digital Twin Industrial Parks
Authors: Wang Lingyu , Wang Hairui , Li Yingchuan , Yan Xingyun , Wang Min , Guo Meixing , Fang Mingzhu , Kong Yue , Hu Jie
Published: November 2024

In the face of increasing environmental challenges, carbon emissions from industrial parks have become a global focal point, particularly as electricity consumption serves as a major source of carbon emissions that requires effective management. Despite proactive efforts by governments and industry stakeholders to transition industrial parks toward cleaner production methods, traditional energy management systems exhibit significant limitations in data collection, real-time monitoring, and intelligent analysis, making it difficult to meet the urgent demands for carbon reduction. To address these challenges, this study proposes a carbon data management approach for industrial parks based on digital twin technology and develops an intelligent system that integrates monitoring, environmental surveillance, energy management, and carbon emission monitoring. The system supports efficient energy-saving and carbon-reducing decision making by real-time collection of energy consumption data. By incorporating Building Information Modeling (BIM) and Internet of Things (IoT) technologies, the system facilitates the integration and visualization of multi-source data, significantly enhancing the transparency of carbon data. The results of the carbon reduction validation system demonstrate that the application of this platform and its associated facilities can significantly reduce carbon emissions in the park, providing robust support for the transition of industrial parks toward low-carbon and sustainable development.
Modeling of Habitat Suitability Using Remote Sensing and Spatio-Temporal Imprecise In Situ Data on the Example of Red Deer
Authors: Kenna Amelie Mc , Schultz Alfred , Neumann Matthias , Lausch Angela , Borg Erik
Published: November 2024

This paper presents a streamlined approach to describing potential habitats for red deer (Cervus elaphus) in situations where in situ data collected through observations and monitoring are absent or insufficient. The main objectives of this study were as follows: (a) to minimize the negative effects of limited in situ data; (b) to identify landscape features with a functional relationship between habitat quality and landscape structure; and (c) to use imprecise in situ data for statistical analyses to specify these relationships. The test area was located in the eastern part of Mecklenburg-Western Pomeriania (Germany). For this area, remotely sensed forest maps were used to determine landscape metrics as independent variables. Dichotomous habitat suitability was determined based on hunting distances over a five-year period. Ecological and biological habitat requirements of red deer were derived from suitable landscape measures, which served as model inputs. Correlation analysis identified the most relevant independent landscape metrics. Logistic regression then tested various metric combinations at both class and landscape levels to assess habitat suitability. Within the model variants, the contagion index, edge density, and percentage of forested area showed the largest relative impact on habitat suitability. The approach can also be applied to other mammals, provided there are appropriate structural preferences and empirical data on habitat suitability.
Immediate Response of Carabids to Small-Scale Wildfire Across a Healthy-Edge-Burnt Gradient in Young Managed Coniferous Forest in Central Europe
Authors: Zumr Václav , Remeš Jiří , Nakládal Oto
Published: November 2024

Wildfire is a type of disturbance that plays a critical role in affecting forest ecosystems. Wildfires also have a significant effect on shaping arthropods communities. Carabids (family Carabidae) are often used as a bioindicator group of altered biocenoses. Methods: For carabid sampling, pitfall traps were used in three habitats, healthy-edge-burnt, fifteen days after the suppression of wildfire. Seven traps were evenly placed on each transect. In total, twenty-one traps were used for the study. Aim of the study: (i) evaluate the overall diversity of carabids, (ii) sex change and distribution within the studied habitats, (iii) dynamics of pyrophilous carabids. Results: In total, 1051 individuals within 42 species were recorded. The total number of species was higher in the edge and burnt habitats and differed from the healthy habitat. The abundance of carabids did not differ significantly across the three habitats. However, the healthy habitat exhibited both lower species numbers and abundance. Communities, species richness, and diversity indices were similar in the edge and burnt habitats, while the healthy habitat had lower species richness, diversity indices, and more homogenized communities. The overall sex ratio was nearly equal, with females comprising 519 individuals (49.4%) and males 532 individuals (50.6%), showing nonsignificant differences among study habitats. Among the nine most dominant species, a general trend of female dominance was observed. Many species showed different patterns in sex distribution in relation to the study habitats. Pyrophilous species accounted for the majority of individuals, comprising 55% of all carabids in the burnt habitat, predominantly represented by Pterostichus quadrifoveolatus. The rare species Sericoda quadripunctata was observed infrequently with only twenty-three individuals recorded. These two species are highly correlated, potentially indicating their near-habitat requirements. Males of pyrophilous species in general colonize the area in the earliest post-fire period. Conclusions: The immediate response of carabids to forest wildfire is significant, primarily influencing species richness and communities. While wildfire did not affect overall sex distribution, it shaped interspecies sex distribution across the study habitats.