bluuebunny/crossref_metadata_2025 huggingface dataset:
Epitranscriptomics in the Glioma Context: A Brief Overview
Authors: Santamarina-Ojeda Pablo , Fernández Agustín F. , Fraga Mario F.
Published: February 2025

Epitranscriptomics, the study of chemical modifications in RNA, has emerged as a crucial field in cellular regulation, adding another layer to the established landscape of DNA- and histone-based epigenetics. A wide range of RNA modifications, including N6-methyladenosine, pseudouridine, and inosine, have been identified across nearly all RNA species, influencing essential processes such as transcription, splicing, RNA stability, and translation. In the context of brain tumors, particularly gliomas, specific epitranscriptomic signatures have been reported to play a role in tumorigenesis. Despite growing evidence, the biological implications of various RNA modifications remain poorly understood. This review offers an examination of the main RNA modifications, the interplay between modified and unmodified molecules, how they could contribute to glioma-like phenotypes, and the therapeutic impact of targeting these mechanisms.
Non-Coding RNAs in Cancer: Structure, Function, and Clinical Application
Authors: Márton Éva , Varga Alexandra , Domoszlai Dóra , Buglyó Gergely , Balázs Anita , Penyige András , Balogh István , Nagy Bálint , Szilágyi Melinda
Published: February 2025

We are on the brink of a paradigm shift in both theoretical and clinical oncology. Genomic and transcriptomic profiling, alongside personalized approaches that account for individual patient variability, are increasingly shaping discourse. Discussions on the future of personalized cancer medicine are mainly dominated by the potential of non-coding RNAs (ncRNAs), which play a prominent role in cancer progression and metastasis formation by regulating the expression of oncogenic or tumor suppressor proteins at transcriptional and post-transcriptional levels; furthermore, their cell-free counterparts might be involved in intercellular communication. Non-coding RNAs are considered to be promising biomarker candidates for early diagnosis of cancer as well as potential therapeutic agents. This review aims to provide clarity amidst the vast body of literature by focusing on diverse species of ncRNAs, exploring the structure, origin, function, and potential clinical applications of miRNAs, siRNAs, lncRNAs, circRNAs, snRNAs, snoRNAs, eRNAs, paRNAs, YRNAs, vtRNAs, and piRNAs. We discuss molecular methods used for their detection or functional studies both in vitro and in vivo. We also address the challenges that must be overcome to enter a new era of cancer diagnosis and therapy that will reshape the future of oncology.
What We Know and Do Not Yet Know About the Canine Model of Lymphoma in Human Medicine—The Current State of Knowledge
Authors: Będkowska Daria , Al-Ameri Sara , Wieczorek Agnieszka , Bubak Joanna , Miszczak Marta
Published: February 2025

This review comprehensively compares lymphoma in humans and dogs, highlighting the canine model’s utility in translational research. Canine lymphoma (cL), predominantly diffuse large B-cell lymphoma (DLBCL), mirrors human non-Hodgkin’s lymphoma (NHL) in its clinical presentation, including lymphadenopathy, systemic symptoms (e.g., fever, weight loss), and hematological abnormalities. Morphologically, cL and NHL share similarities in DLBCL subtypes (centroblastic, immunoblastic, anaplastic), although some variations exist, such as the presence of macronuclear medium-sized cells in canine polymorphonuclear centroblastic lymphoma, not observed in humans. Canine and human lymphomas share molecular mechanisms, including the activation of key pathways like NF-κB and mTOR, and genetic and epigenetic alterations. The tumor microenvironment influences tumor growth and immune evasion in both species. Both species exhibit similar responses to chemotherapy, primarily CHOP-based protocols, although canine lymphoma often progresses more rapidly, offering advantages for shorter clinical trials. Molecular targeted therapy is emerging as a promising treatment, with human therapies like rituximab and chimeric antigen receptor T-cell therapy showing efficacy, and canine treatments still developing. Epidemiological data reveal overlapping risk factors, including exposure to environmental carcinogens (e.g., household chemicals, pollution) and the potential influence of sex hormones, although the role of sex hormones requires further investigation in canines. While staging systems differ slightly (Lugano modification of Ann Arbor for humans, WHO system for dogs), both consider disease extent and systemic involvement. Prognostic factors, such as lactate dehydrogenase (LDH) levels, are relevant in human NHL but have not shown consistent utility in cL. This study concludes that the spontaneous development of cL in immunocompetent dogs, coupled with its clinical, histological, and therapeutic similarities to human NHL, makes the canine model invaluable for preclinical research, accelerating the development of novel diagnostic tools and therapies for both human and canine lymphoma. The shared environmental risk factors and shorter disease progression in dogs further enhance the translational potential of this model, promoting a One Health approach to cancer research.
Multimodal Imaging of Osteosarcoma: From First Diagnosis to Radiomics
Authors: Cè Maurizio , Cellina Michaela , Ueanukul Thirapapha , Carrafiello Gianpaolo , Manatrakul Rawee , Tangkittithaworn Phatthawit , Jaovisidha Suphaneewan , Fuangfa Praman , Resnick Donald
Published: February 2025

Osteosarcoma is a primary malignant bone tumor characterized by the production of an osteoid matrix. Although histology remains the definitive diagnostic standard, imaging plays a crucial role in diagnosis, therapeutic planning, and follow-up. Conventional radiography serves as the initial checkpoint for detecting this pathology, which often presents diagnostic challenges due to vague and nonspecific symptoms, especially in its early stages. Today, the integration of different imaging techniques enables an increasingly personalized diagnosis and management, with each contributing unique and complementary information. Conventional radiography typically initiates the imaging assessment, and the Bone Reporting and Data System (Bone-RADS) of the Society of Skeletal Radiology (SSR) is a valuable tool for stratifying the risk of suspicious bone lesions. CT is the preferred modality for evaluating the bone matrix, while bone scans and PET/CT are effective for detecting distant metastases. MRI reveals the extent of the lesion in adjacent soft tissues, the medullary canal, and joints, as well as its relationship to neurovascular structures and the presence of skip lesions. Advanced techniques such as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion-weighted imaging (DWI), and perfusion MRI help characterize the tumor environment and assess treatment response. Osteosarcoma comprises a range of subtypes with differing clinical and imaging characteristics, some of which are particularly distinctive, such as in the case of telangiectatic osteosarcoma. Knowledge of these variants can guide radiologists in the differential diagnosis, which includes both central and surface forms, ranging from highly aggressive to more indolent types. In this review, we present a wide range of representative cases from our hospital case series to illustrate both typical and atypical imaging presentations. Finally, we discuss recent advancements and challenges in applying artificial intelligence approaches to the imaging of osteosarcoma.
Endobronchial Ultrasound Access to Pulmonary Vasculature in Thoracic Malignancy
Authors: Koukaki Evangelia , Anagnostopoulos Nektarios , Bakiri Aikaterini , Zaneli Stavroula , Stratakos Grigorios
Published: February 2025

Endobronchial ultrasound (EBUS) has evolved beyond conventional applications in mediastinal staging and central pulmonary tumor diagnosis. It encompasses the assessment of pulmonary vasculature in patients with thoracic malignancies. EBUS can visualize major vessels and allow assessment of pulmonary embolism, differential diagnosis of endovascular lesions, and T staging. Additionally, EBUS-guided transvascular needle aspiration (TVNA) has proven valuable for sampling lesions behind vessels and diagnosing conditions such as pulmonary artery sarcoma and tumor embolism, with low complication rates reported. The PubMed and SCOPUS databases were searched up to November 2024 for articles in the English language reporting the use of EBUS for pulmonary vasculature assessment. References were also searched for relevant articles. The integration of EBUS with other modalities enhances staging and diagnostic capabilities in thoracic malignancies. Despite promising findings, limitations include suboptimal image quality and challenges in extensively assessing all the vasculature. Safety concerns, particularly with transvascular biopsy, remain minimal with expert handling, although further studies are needed to assess specific risks like hematogenous tumor seeding. EBUS continues to evolve, suggesting its potential to become the cornerstone in advanced thoracic diagnostics and treatment planning. This review systematically explores the feasibility, safety, and diagnostic utility of EBUS in pulmonary vasculature assessment, highlighting its potential as an indispensable tool in thoracic diagnostics and treatment planning.
Deep Learning in Thoracic Oncology: Meta-Analytical Insights into Lung Nodule Early-Detection Technologies
Authors: Wang Ting-Wei , Wang Chih-Keng , Hong Jia-Sheng , Chao Heng-Sheng , Chen Yuh-Min , Wu Yu-Te
Published: February 2025

Background/Objectives: Detecting lung nodules on computed tomography (CT) images is critical for diagnosing thoracic cancers. Deep learning models, particularly convolutional neural networks (CNNs), show promise in automating this process. This systematic review and meta-analysis aim to evaluate the diagnostic accuracy of these models, focusing on lesion-wise sensitivity as the primary metric. Methods: A comprehensive literature search was conducted, identifying 48 studies published up to 7 November 2023. The pooled diagnostic performance was assessed using a random-effects model, with lesion-wise sensitivity as the key outcome. Factors influencing model performance, including participant demographics, dataset privacy, and data splitting methods, were analyzed. Methodological rigor was maintained through the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tools. Trial Registration: This review is registered with PROSPERO under CRD42023479887. Results: The meta-analysis revealed a pooled sensitivity of 79% (95% CI: 72–86%) for independent datasets and 85% (95% CI: 83–88%) across all datasets. Variability in performance was associated with dataset characteristics and study methodologies. Conclusions: While deep learning models demonstrate significant potential in lung nodule detection, the findings highlight the need for more diverse datasets, standardized evaluation protocols, and interventional studies to enhance generalizability and clinical applicability. Further research is necessary to validate these models across broader patient populations.
Solid-Phase Activation During the Degradation of Tetracycline by Modified Activated Carbon–Persulfate Composite
Authors: Ding Shihu , Tan Peng , Meng Nuo , Zhang Xiguo , Ma Lin , Zhou Minghua , Wang Wei
Published: February 2025

In this study, the novel composite materials of activated carbon (AC) and persulfate (PS) doped by nitrogen (N) and sulfur (S) were successfully synthesized through one-step mechanical ball milling. Different from the previous liquid-phase activation process of PS, the direct in situ solid-phase activation of PS was achieved through the newly generated chemical bonds between AC and PS. The increased crystal surface exposure and highly electronegative atoms provided more reactive sites for the modified composites, enabling them to extract electrons from the pollutant. Compared to S doping, the N-doped composite exhibited a higher oxidative degradation ability, with a removal rate of 93.6% for tetracycline (TC, 40 mg/L) within 40 min. The interactions between AC and PS that occur in the interior of the composite avoid the limitations of mass transfer between the solid–liquid interface, thus expanding the pH application range of the catalytic reaction and minimizing the interference of other components in the solution. The synergistic effect between active oxygen species and electron transfer is the main mechanism for promoting pollutant degradation. This research puts forward a new insight into the activation approach of PS and proposes a feasible method for the advanced treatment of TC wastewater.
Eugenol Promotes Apoptosis in Leukemia Cells via Targeting the Mitochondrial Biogenesis PPRC1 Gene
Authors: Al-Harbi Sayer , Alkholiwy Elham M. A. , Ali Ahmed Syed Osman , Aljurf Mahmoud , Al-Hejailan Reem , Aboussekhra Abdelilah
Published: February 2025

Acute myeloid leukemia (AML) is a highly heterogenous and aggressive myeloid neoplasm. To sustain growth and survival, AML cells, like other neoplasms, require energy. This process is orchestrated by mitochondria and is under the control of several genes, such as PPRC1 (PRC), a member of the PGC-1 family, which is a key player in the transcription control of mitochondrial biogenesis. We have shown here that eugenol inhibits cell growth and promotes apoptosis through the mitochondrial pathway in AML cell lines as well as in cells from AML patients but not in cells from healthy donors. Similar effects were also observed on cytarabine-resistant AML cells. Interestingly, eugenol downregulated PPRC1 at both the protein and mRNA levels and reduced mitochondrial membrane potential in AML cells. We have also shown that PPRC1 expression is higher in cancer cells from blood, breast, and other types of cancer relative to normal cells, and high PPRC1 levels correlate significantly with short overall survival (OS). In addition, PPRC1 gene mutations significantly correlate with short OS and/or disease-free survival in several cancers. PPRC1 mutations also correlated significantly with poor OS (p < 0.0001) when tested in a total of 23,456 cancer patients. These findings suggest an oncogenic role of PPRC1 in various types of cancer and the possible eugenol-targeting of this gene for the treatment of AML patients, especially those exhibiting resistance to cytarabine.
Correction: Dwivedi et al. SERS-Driven Ceftriaxone Detection in Blood Plasma: A Protein Precipitation Approach. Chemosensors 2024, 12, 213
Authors: Dwivedi Aradhana , Ryabchykov Oleg , Liu Chen , Farnesi Edoardo , Schmidt Michael Stenbæk , Bocklitz Thomas , Popp Jürgen , Cialla-May Dana
Published: February 2025

The blood-based samples for the original publication [...]
High-Performance Data Throughput Analysis in Wireless Ad Hoc Networks for Smart Vehicle Interconnection
Authors: Dafhalla Alaa Kamal Yousif , Ahmed Amira Elsir Tayfour , Sid Ahmed Nada Mohamed Osman , Filali Ameni , Alhomed Lutfieh S. , Ali Fawzia Awad Elhassan , Eldeen Asma Ibrahim Gamar , Elobaid Mohamed Elshaikh , Adam Tijjani
Published: February 2025

Vehicular Ad Hoc Networks play a crucial role in enabling Smart City applications by facilitating seamless communication between vehicles and infrastructure. This study evaluates the throughput performance of different routing protocols, specifically AODV, AODV:TOM, AODV:DEM, GPSR, GPSR:TOM, and GPSR:DEM, under various city and highway scenarios in complex networks. The analysis covers key parameters including traffic generation, packet sizes, mobility speeds, and pause times. Results indicate that TOM and DEM profiles significantly improve throughput compared to traditional AODV and GPSR protocols. GPSR:TOM achieves the highest throughput across most scenarios, making it a promising solution for high-performance data transmission in Smart Cities. For instance, GPSR:TOM achieves an average throughput of 3.2 Mbps in city scenarios compared to 2.8 Mbps for GPSR, while in highway scenarios, the throughput increases to 3.6 Mbps. Additionally, AODV:DEM records a throughput of 3.4 Mbps for high traffic generation, outperforming AODV:TOM at 3.1 Mbps and baseline AODV at 2.7 Mbps. The findings highlight the importance of optimizing data throughput to ensure reliability and efficiency in complex vehicle interconnection systems, which are critical for traffic management, accident prevention, and real-time communication in smart urban environments.
Detecting the Endangered San Joaquin Kit Fox (Vulpes macrotis mutica) and Other Canine Species in Kern County, CA: Applying a Non-Invasive PCR-Based Method to Four Case Study Sites
Authors: Lauer Antje , Alame Sarah , Calvillo Julian A. , Gaytan Mario E. , Juarez Jonathan R. , Lopez Jocelyne J. , Medina Kayla , Owens Isaac , Romero Alejandro , Sheppard Jarred
Published: February 2025

The endangered San Joaquin kit fox (SJKF) (Vulpes macrotis mutica), which is endemic to the San Joaquin Valley in California, has lost most of its natural habitat due to urban sprawl and change in land use over time. Many studies have been conducted to restore and protect the remaining habitat, involving presence/absence surveys prior to urban development using camera monitoring, tracking dogs, tracking plates, spotlighting, and trapping. While these traditional methods work well, they can be invasive, expensive, labor-intensive, and require permits to perform. In our study, we used a non-invasive method based on DNA extraction from scat collected in the environment, followed by a diagnostic Polymerase Chain Reaction (PCR)-based approach on mitochondrial DNA fragments and investigated the presence of the SJKF on four case study sites that shared a high SJKF habitat suitability index but are under the threat of development. We found that the diagnostic PCR was able to accurately differentiate between different canids present at the sites, in a time- and cost-effective manner. Including this non-invasive method in the Department of Fish and Wildlife’s standardized recommendations for survey methods would help to improve future environmental assessments for SJKF populations in the Central Valley of California.
Toward an Understanding of Cancer as an Issue of Social Justice: Perspectives and Implications for Oncology Nursing
Authors: Horrill Tara C. , Beck Scott M. , Wiens Allison
Published: February 2025

Within the fields of oncology practice and research, cancer has historically been and continues to be understood as primarily biologically produced and physiologically driven. This understanding is rooted in biomedicine, the dominant model of health and illness in the Western world. Yet, there is increasing evidence of inequities in cancer that are influenced by social and structural inequities. In this article, we propose that cancer-related inequities ought to be seen as issues of social justice, and, given nursing’s longstanding commitments to social justice, they ought to be a priority for oncology nurses. Using a social justice lens, we highlight potential social injustices in the form of inequities in cancer outcomes and access to cancer care across the cancer continuum. Our intention is not to provide an exhaustive review of evidence, but to provide our perspective, adding to the dialogue surrounding health equity and cancer while shifting the narrative away from an understanding of cancer inequities as stemming from “lifestyle” and “behavioural” choices. We conclude by exploring the implications of considering cancer inequities as social injustices for nursing practice.
Optimizing Air Pollution Forecasting Across Temporal Scales: A Case Study in Salamanca, Mexico
Authors: Moreno-Vazquez Francisco-Javier , Trujillo-Romero Felipe , Violante Gavira Amanda Enriqueta
Published: February 2025

Air pollution forecasting is essential for understanding environmental patterns and mitigating health risks, especially in urban areas. This study investigates the forecasting of criterion pollutants—CO,O3,SO2,NO2,PM2.5, and PM10—across multiple temporal frames (hourly, daily, weekly, monthly) in Salamanca, Mexico, utilizing temporal, meteorological, and pollutant data from local monitoring stations. The primary objective is to identify robust models capable of short- and mid-term predictions, despite challenges related to data inconsistencies and missing values. Leveraging the low-code PyCaret framework, a benchmark analysis was conducted to identify the best-performing models for each pollutant. Statistical evaluations, including ANOVA and Tukey HSD tests, were employed to compare model performance across different time frames. The results reveal significant variations in prediction accuracy depending on both the pollutant and temporal windows, with stronger predictive performance observed in the weekly and monthly frames. The research indicates that the incorporation of temporal and environmental variables enhances forecast accuracy and highlights the value of low-code AutoML tools, such as PyCaret, in streamlining model selection and improving overall forecasting efficiency.
Optimizing Multiclass Classification Using Convolutional Neural Networks with Class Weights and Early Stopping for Imbalanced Datasets
Authors: Razali Muhammad Nazim , Arbaiy Nureize , Lin Pei-Chun , Ismail Syafikrudin
Published: February 2025

Multiclass classification in machine learning often faces significant challenges due to unbalanced datasets. This situation leads to biased predictions and reduced model performance. This research addresses this issue by proposing a novel approach that combines convolutional neural networks (CNNs) with class weights and early-stopping techniques. The motivation behind this study stems from the need to improve model performance, especially for minority classes, which are often neglected in existing methodologies. Although various strategies such as resampling, ensemble methods, and data augmentation have been explored, they frequently have limitations based on the characteristics of the data and the specific model type. Our approach focuses on optimizing the loss function via class weights to give greater importance to minority classes. Therefore, it reduces bias and improves overall accuracy. Furthermore, we implement early stopping to avoid overfitting and improve generalization by continuously monitoring the validation performance during training. This study contributes to the body of knowledge by demonstrating the effectiveness of this combined technique in improving multiclass classification in unbalanced scenarios. The proposed model is tested for oil palm leaves analysis to identify deficiencies in nitrogen (N), boron (B), magnesium (Mg), and potassium (K). The CNN model with three layers and a SoftMax activation function was trained for 200 epochs each. The analysis compared three scenarios: training with the imbalanced dataset, training with class weights, and training with class weights and early stopping. The results showed that applying class weights significantly improved the classification accuracy, with a trade-off in other class predictions. This indicates that, while class weight has a positive overall impact, further strategies are necessary to improve model performance across all categories in this study.
Methane Emissions from Mining in the European Union
Authors: Zięba Magdalena , Smoliński Adam
Published: February 2025

Methane emissions from coal mining remain a significant environmental challenge in the European Union, particularly in the context of climate change commitments and the ongoing transformation of the energy sector. This article analyses methane emissions from surface and underground coal mining, distinguishing between emissions from mining activities, abandoned underground mines, and post-mining activities. A key aspect of the analysis is the methane emissions per 1000 tonnes of lignite and hard coal mined, which allows a comparison of emission intensities between different mining methods. Between 2009 and 2021, methane emissions from coal mining in the EU decrease, with reductions of 2436 kt CO2 eq. (87 kt CH4) from surface mining and 16,518 kt CO2 eq. (590 kt CH4) from underground mining. However, total methane emissions in 2021 still amount to 25,414 kt CO2 eq. (908 kt CH4), with underground mining contributing 84.7% of the emissions. Discrepancies in national emissions reporting and the lack of transparent data on methane emissions from imported coal make accurate assessments difficult. Strengthening international cooperation, improving data transparency, and exploring methane recovery for energy use are essential steps towards achieving the EU’s climate change objectives.
Numerical Investigation on the Effect of Passive Jet Control on the Performance of a Vortex Induced Vibration Energy Harvester System
Authors: Ravi Dineshkumar , Litak Grzegorz , Waśkowicz Mateusz , Fronc Marcin
Published: February 2025

The present study investigates the effect of the passive jet control system on the performance of a vibration energy harvester system (VIVEHS). The shape of a bluff body plays a crucial role in determining the vortex shedding mechanism, while the passive jet control system influences the dynamic behavior of these vortices, either enhancing or suppressing the bluff body’s oscillatory performance. This study introduces key innovations, including the incorporation of perforations in the bluff body, variations in outlet angles, and different inlet and outlet configurations. In this regard, a two-dimensional numerical investigation has been carried out to understand and optimize the dynamic response from the bluff body and its effect on beam deflection. The validation of the numerical code has been carried out for a cylindrical shaped bluff body using ANSYS Fluent 23.2 numerical modelling software. Upon validation, the effects of a single inlet and a symmetrical dual outlet with different outlet angles are numerically analyzed under various flow conditions to assess their impact on the dynamic behavior of the system. The outlet angle varies between 30 degrees and 120 degrees with intervals of 30 degrees. The contours of vorticity and the bluff body dynamic characteristics were observed and plotted for various flow conditions ranging between 1 m/s and 8 m/s with intervals of 1 m/s. The results of this numerical study are crucial for designing passive jet control systems in practical energy harvesting applications. The optimization of outlet configurations and control strategies can significantly enhance both the efficiency and stability of energy harvesting systems.
Composite Power Management Strategy for Hybrid Powered Compound-Wing Aircraft in Level Flight
Authors: An Siqi , Peng Xu , Gan Yuantao , Yang Jingyu , Xiang Guofei , Dian Songyi
Published: February 2025

A composite strategy is proposed to address the optimal power management for a hybrid powered compound-wing aircraft, which integrates bang–bang regulation with optimal demand chasing regulation. The electro-gasoline hybrid power system enhances the overall flight endurance of vertical take-off and landing compound-wing aircraft. The power consumption in level flight appears to be much lower than that in hovering, enabling the hybrid power system to simultaneously energize and charge the battery pack. In order to minimize fuel consumption and battery pack degradation during level cruise flight, a power management strategy that serves for both battery charging and thrust energizing is worthy of careful consideration. To obtain the desired features and design the regularity strategy of the power system, linear and nonlinear models are established based on the configuration of an electro-gasoline series hybrid power system installed in the proposed aircraft, with mathematical modelling of key components and units. A notable feature of semi-fixing for battery voltage and engine rotational speed has been qualitatively identified and subsequently quantitatively validated on the testbench. After conducting simulations and comparing with other strategies, the composite strategy demonstrates appropriate fuel consumption and battery degradation, effectively achieving cost minimization. Testbench evaluation confirms the effectiveness of this proposed power management strategy. Furthermore, the practicality of the hybrid power system and its associated level flight composite power management strategy are validated by tests conducted on a 30 kg aircraft prototype, thereby showcasing the potential to enhance flight performance.
The Impact of Design Modifications on the Effectiveness of Energy Storage Construction in a Salt Cavern According to Enhanced Technology Based on Laboratory Tests
Authors: Chromik Mariusz , Korzeniowski Waldemar
Published: February 2025

This article presents findings from ongoing research on improving the efficiency of leaching salt caverns for brine production and creating storage spaces for gases or fuels. Previous studies of the authors highlighted the potential of modifying conventional technology by employing a high-pressure water jet to carve niches in salt rock. Current research aims to define precise niche parameters using innovative and enhanced Jet Cavern Technology (JCT). Our research identified improvements in leach efficiency across various configurations and quantities of niches. By analyzing three salt types—pink, spiz, and crystalline—it was demonstrated that creating a niche perpendicular to the well axis significantly reduces the time to achieve saturated brine by approximately 38%, particularly during the initial construction phase. Further adjustments in niche dimensions, spacing, or spatial positioning can improve cavern construction rates by up to 20% over standard methods. This study quantified the correlation between the advancement of the process and the rate of increase in the salt content in the brine. Accelerated brine saturation facilitates cavern construction and mitigates environmental concerns associated with the discharge of unsaturated brine. The adoption of this new technology is crucial for the expansion of renewable energy sources and the associated storage requirements.
Software Package for Optimization of Burner Devices on Dispersed Working Fluids
Authors: Fedorov Ruslan V. , Shepelev Igor I. , Malyoshina Mariia A. , Generalov Dmitry A. , Sherkunov Vyacheslav V. , Sapunov Valeriy V.
Published: February 2025

Taking into account the approaches to ecology and social policy, the development of technologies for optimizing the combustion process for thermal power plants, one of the key sources of greenhouse gas emissions, is relevant. This article analyzes approaches that improve the combustion process efficiency in thermal power plants, as well as speed up the development of various operating modes. Particular attention is paid to the control of fuel composition and geometric parameters of a burner device. Optimal settings of these parameters can significantly impact the reduction in harmful emissions into the atmosphere, though finding such parameters is a labor-intensive process and requires the use of modern automation and data processing tools. Nowadays, the main methods to analyze and optimize various characteristics are machine learning methods based on artificial neural networks (ANNs), which are used in this work. These methods also demonstrate the efficiency in combination with the optimization method. Thus, the use of approaches based on the combustion process optimization can significantly improve the environmental footprint of thermal power plants, which meets modern environmental requirements. The obtained results show that the most significant effect on the NOX content has the mass flow rate change of primary air and fuel with a change in geometric parameters. The decrease in NOX concentration in comparison with the calculation results with basic values is about 15%.
Concept and Implementation of Innovative Scalable Wind Turbine Emulator with Doubly Fed Asynchronous Machine
Authors: Rink Robert , Małkowski Robert , Gawin Bartłomiej , Janiga Klara
Published: February 2025

This paper presents the design of an innovative scalable wind turbine emulator. The system’s hardware and software components are described in detail including test results, demonstrating the research potential of the proposed design. The uniqueness of the proposed solution lies in its scalability, achieved despite the use of physical devices with fixed parameters. This scalability allows for the flexible shaping of the system’s structure and parameters, allowing it to emulate both individual wind turbines with a capacity ranging from kilowatts to megawatts as well as aggregated models of entire wind farms. The emulator was developed using the hardware-in-the loop (HIL) concept and consists of a digital part including aerodynamic and mechanical models (wind, rotor, shaft models, disturbances, etc.) and control systems for mechanical and electrical devices within the wind turbine. The digital component has a modular structure, which allows for the replacement of any module of the native control system with the user’s custom designed one and testing its properties over a broad range of parameters. The test results presented in the article demonstrate a satisfactory level of accuracy of the developed emulator.
The Effect of Facade Orientation on the Electrical Performance of a BIPV System: A Case Study in João Pessoa, Brazil
Authors: Gomes Michelli Mayara de Medeiros , Cavalcante Renan Douglas Lopes da Silva , Ando Junior Oswaldo Hideo , Pero Claudio Del , Lima João Alves de , Lago Taynara Geysa Silva do
Published: February 2025

Photovoltaic solar energy has emerged as a vital solution in energy transition, especially in buildings with building-integrated photovoltaic (BIPV) systems. This study evaluated a BIPV system in João Pessoa, Brazil, using PVsyst 7.4 software for simulations in 2023 and experimental tests in 2024 to compare real and simulated energy values injected into the grid. The experiments were conducted in April, June, July, and August, covering seasonal variations. The east and west orientations showed the best performance, with annual production of 65.5 and 81.6 kWh, respectively, due to the balanced solar irradiance. Conversely, the north and south orientations generated less electricity, with 51.3 and 42.1 kWh, respectively, due to lower direct solar exposure. The average injected energy was 0.2445 to 0.2530 kWh/day in April, 0.2851 to 0.2470 kWh/day in June, 0.2816 to 0.2400 kWh/day in July, and 0.1556 to 0.1700 kWh/day in August. Performance ratios were 44.3% for the north, 44.4% for the south, 47.4% for the east, and 56.8% for the west, highlighting the impact of orientation. It is concluded that the east and west facades are more suitable for BIPV systems in João Pessoa, emphasizing the importance of local factors in optimizing urban energy efficiency.
Comparative Study of Voltage and Control Characteristics of Two-Core and Single-Core Step-Up/Down Thyristor-Controlled Phase-Shifting Transformers
Authors: Zhang Ningyu , Li Huarui , Jin Xiaokuan , Bi Chongze , Wang Jianhua
Published: February 2025

The thyristor-controlled phase-shift transformer (TCPST) is an effective means of controlling power flow, exhibiting a simple structure and a long operating life. However, conventional TCPSTs are limited in their ability to regulate the phase-shifting angle, necessitating the matching of the step-up/down transformer to control the amplitude of voltages. Therefore, this paper puts forth two distinct structures of TCPSTs, each of which is capable of regulating both the phase-shifting angle and the amplitude of voltages: the two-core step-up/down thyristor-controlled phase-shifting transformer (TCSUD-TCPST) and the single-core step-up/down thyristor-controlled phase-shifting transformer (SCSUD-TCPST). Moreover, a comparison was conducted between the topology structure and the thyristor-controlled strategies of the TCSUD-TCPST and the SCSUD-TCPST. The coupling relationship and the limitations of the phase-shifting angle and the amplitude of voltages are illustrated, indicating that the SCSUD-TCPST appears to be a more suitable option for power transmission. Furthermore, the considerable static and dynamic characteristics of the TCSUD-TCPST and the SCSUD-TCPST were investigated through the PLECS simulation platform, which was also employed to further verify the aforementioned conclusions.
Fault Diagnosis of Photovoltaic Array Based on Improved Honey Badger Optimization Algorithm
Authors: Guo Zhuo , Chang Yuanyuan , Fang Yanhong
Published: February 2025

A photovoltaic array fault diagnosis method based on an improved honey badger optimization algorithm is proposed to improve the accuracy of photovoltaic array fault diagnosis. Firstly, analyze the current and power output characteristic curves of the photovoltaic array under different states, and construct a preliminary set of 10 dimensional fault feature vectors. Secondly, the feature vector set is ranked in importance using the random forest algorithm, and then input into support vector machines, long short-term memory, and bidirectional long short-term memory neural networks to obtain the optimal combination of the base model and the number of features. Then, the honey badger optimization algorithm was improved by combining Tent chaotic mapping column measurement, improved control factors, and pinhole imaging strategy, and compared with other optimization algorithms to demonstrate its effectiveness in optimization ability, stability, and convergence speed. Finally, by combining the improved honey badger optimization algorithm with the optimal base model and number of features, the problem of hyperparameter setting in the base model was effectively solved. The experimental results show that the fault diagnosis accuracy of the proposed photovoltaic array fault diagnosis model is 97.1014%, which is superior to other models and verifies the effectiveness of the proposed method.
Integrated Phase-Change Materials in a Hybrid Windcatcher Ventilation System
Authors: Eso Olamide , Darkwa Jo , Calautit John
Published: February 2025

Windcatchers are effective passive ventilation systems, but their inability to actively reduce and stabilize supply air temperatures reduces indoor cooling performance. This study addresses this limitation by integrating encapsulated phase-change material tubes (E-PCM-Ts) into a solar fan-assisted, multidirectional windcatcher. The novelty lies in the vertical placement of E-PCM-Ts within the windcatcher’s airstreams, enhancing heat transfer and addressing challenges related to temperature stabilization and cooling. Using computational fluid dynamics (CFD) under hot outdoor conditions, the ventilation, cooling, and PCM thermal storage performance are evaluated based on two different E-PCM-T arrangements. Results showed a maximum air temperature drop of 2.28 °C at a wind speed of 1.88 m/s and wind angle of 0°. This offers an optimal temperature reduction that achieved a 6.5% reduction for up to 7 h of air temperature stabilization. Placing E-PCM-Ts in all airstreams improved the thermal storage performance of the windcatcher. A 50% increase in hybrid ventilation efficiency was also achieved when wind angles increased from 0° to 30°. Overall, the proposed system demonstrated superior performance compared to that of traditional windcatchers, delivering improved thermal energy storage and cooling efficiency and adequate hybrid ventilation with supply air velocities of 0.37–0.60 m/s.
System Analysis and Comparison Between a 2 MW Conventional Liquid Cooling System and a Novel Two-Phase Cooling System for Fuel Cell-Powered Aircraft
Authors: van Gerner Henk Jan , Luten Tim , Resende William , Mühlthaler Georg , Buntz Marcus-Benedict
Published: February 2025

Hydrogen-powered fuel cells are the preferred energy source for electric aircraft. However, for aircraft applications, it is of upmost importance to reduce the mass of the fuel cell system. A considerable amount of the total system mass is due to the fuel cell cooling system. In this paper, the analysis of a 2 MW cooling system for fuel cell-powered aircraft is discussed. A detailed comparison is made between a conventional liquid cooling system with ethylene glycol–water (EGW) and a novel two-phase cooling system that uses the evaporation of a liquid to remove waste heat from the fuel cells. For this novel two-phase cooling system, several refrigerants were analyzed, and methanol resulted in the lowest system mass. The mass of a liquid EGW system is 35% higher than for two-phase methanol with accumulator and 2.4 times higher than for two-phase methanol without accumulator. Because of this large mass benefit, a demonstrator for a two-phase methanol cooling system without accumulator with a capacity of 200 kW is currently being built.
A Study on the Impact of Energy Diplomacy on China’s Crude Oil Trade
Authors: Li Boyuan , Ren Zhongyuan , Gao Ping
Published: February 2025

Based on the information of China’s bilateral energy diplomacy with 43 countries from 2000 to 2023, this study analyzes the impact of different diplomatic forms on China’s crude oil trade. A fixed-effects model is reconstructed to analyze the impact of various aspects of energy diplomacy on China’s crude oil trade based on panel data. These aspects include diplomacy frequency, frequency of visits, first or regular visits by heads of state, changes in diplomatic relationship levels, whether oil or energy is involved in joint public statements, and the nature of diplomacy (bilateral or multilateral). This study provides a reference for strategic decision-making in China’s energy diplomacy and indicates that frequent meetings of heads of state and proactive “going out” strategies in energy diplomacy significantly promote crude oil trade cooperation between two countries and ensure national energy security. Bilateral energy diplomacy is more effective in fostering crude oil trade cooperation with resource countries compared to multilateral diplomacy, with particularly notable effects in neighboring countries and those that belong to the Belt and Road Initiative (BRI). The Chinese government could increase the frequency of energy diplomacy, appropriately increase the frequency of overseas visits, and be more proactive in “going out” for energy diplomacy. There should be a greater focus on bilateral energy diplomacy with key resource countries, including neighboring countries such as Russia and Kazakhstan, as well as BRI countries such as Saudi Arabia, Iraq, the UAE, and Indonesia. It is also crucial to enhance the discourse power and influence of China in the global energy governance system. If the outcome documents of diplomatic activities involve crude oil or energy cooperation, they may invite competition from other resource countries or intervention from external forces. It is recommended that the principle of “do more, say less” is upheld. Any sensitive or controversial topics that would cause external interferences should be avoided, and not be included or actively mentioned. Based on practical cooperation with potential partner countries, the entire industry chain of energy investment, trade, technical services, and engineering equipment will be strengthened.
Identifying Harmonic Sources by Profiling Discrete Harmonic Cycle Time
Authors: Hjertberg Tommy , Rönnberg Sarah K.
Published: February 2025

Harmonic emissions cause power quality issues in electrical systems, making source identification necessary to determine the best way of remedying them. Existing methods rely on measuring variations in harmonic amplitude, angle, and phase which require multiple measurement points or extensive system knowledge. We identified a methodological research gap because Discrete Harmonic Cycle Time (DHCT) has not been evaluated as a measuring principle for harmonic source identification. We propose a method using DHCT to enable single point measurements to profile harmonic sources. To determine the cycle length, we used a combination of sifting, a filter bank of cascaded high-pass and notch filters, and zero-crossing detection. For comparing the devices, we extracted motifs from the time series of discrete cycle lengths and applied principal component analysis. While it has previously been known in other contexts that harmonics can have varying cycle lengths, our laboratory results show that this is also true for the emissions of power electronic devices and that the differentiation can be used to identify the devices, thus bridging this knowledge gap. This method is independent of system impedance and topology. While further validation in more complex environments is needed, our results suggest that devices can be identified using this measurement principle. Since the measuring principle is orthogonal to other methods, it has potential as a complementary tool in harmonic source identification.
Supercritical CO2 Injection-Induced Fracturing in Longmaxi Shales: A Laboratory Study
Authors: Zhang Xiufeng , Song Xuehang , Li Xingyu , Liu Shuyuan , Wang Jiangmei , Wei Junjie , Zhang Min
Published: February 2025

Although supercritical CO2 (SC-CO2) fracturing has shown promise in oil and gas development with demonstrated potential, its application in shale gas extraction remains in its infancy globally. In this study, fracturing experiments were conducted with water, liquid CO2 (L-CO2), and SC-CO2, as well as SC-CO2 at varying pump rates. The results reveal that SC-CO2 fracturing produces a highly complex fracture network characterized by fractures of varying numbers, deflection angles, and tortuosity. Analysis of CO2 temperature and pressure data showed a sharp drop in injection pressure and temperature at breakdown, followed by fluctuations until injection stopped. Acoustic emission (AE) monitoring demonstrated that energy released during main fracture initiation significantly exceeded that from CO2 phase transition-driven fracture extension, underscoring the dominant role of main fractures in energy dissipation. Compared to hydraulic fracturing, SC-CO2 fracturing created a seepage area 2.2 times larger while reducing the breakdown pressure by 37.2%, indicating superior stimulation performance. These findings emphasize the potential of SC-CO2 to form intricate fracture networks, offering a promising approach for efficient shale gas extraction.
Analysis and Suppression of Thrust Ripple in a Permanent Magnet Linear Synchronous Motor—A Review
Authors: Chen Siwen , Liu Yang , Zhang Qian , Tan Jiubin
Published: February 2025

Nowadays, Permanent Magnet Synchronous Linear Motors (PMLSMs) are widely applied as direct drive mechanisms in the industrial manufacturing sector, which can fulfill the requirements for high precision and high production rates. However, PMLSMs are characterized by significant thrust ripple issues, including cogging force, ripple force, and end force, which severely deteriorate the operational accuracy. This paper provides a review of analysis and suppression of the thrust ripple characteristics in PMLSM, aiming to offer guidance on how to mitigate the thrust ripples, and hence, enhancing the operational accuracy of PMLSM system. Firstly, the structural features and operating principles of PMLSMs are analyzed to understand the causes of thrust ripples. Then, strategies for mitigating the PMLSM thrust ripples are elaborated upon, respectively, from two main perspectives: structural optimization and control strategies. Finally, a summary and outlook are presented.