bluuebunny/crossref_metadata_2025 huggingface dataset:
Endoscopic In Vivo Hyperspectral Imaging for Head and Neck Tumor Surgeries Using a Medically Approved CE-Certified Camera with Rapid Visualization During Surgery
Authors: Bali Ayman , Bitter Thomas , Mafra Marcela , Ballmaier Jonas , Kouka Mussab , Schneider Gerlind , Mühlig Anna , Ziller Nadja , Werner Theresa , von Eggeling Ferdinand , Guntinas-Lichius Orlando , Pertzborn David
Published: November 2024

Background: In vivo visualization of malignant tumors remains the main challenge during head and neck cancer surgery. This can result in inadequate tumor margin assessment and incomplete tumor resection, adversely affecting patient outcomes. Hyperspectral imaging (HSI) is a promising approach to address this issue. However, its application in surgery has been limited by the lack of medically approved HSI devices compliant with MDR regulations, as well as challenges regarding the integration into the surgical workflow. Methods: In this feasibility study, we employed endoscopic HSI during surgery to visualize the tumor sites of 12 head and neck cancer patients. We optimized the HSI workflow to minimize time required during surgery and to reduce the adaptation period needed for surgeons to adjust to the new workflow. Additionally, we implemented data processing to enable real-time classification and visualization of HSI within the intraoperative setting. HSI evaluation was conducted using principal component analysis and k-means clustering, with this clustering validated through comparison with expert annotations. Results: Our complete HSI workflow requires two to three minutes, with each HSI measurement—including evaluation and visualization—taking less than 10 s, achieving an accuracy of 79%, sensitivity of 72%, and specificity of 84%. Medical personnel became proficient with the HSI system after two surgeries. Conclusions: This study presents an HSI workflow for in vivo tissue differentiation during head and neck cancer surgery, providing accurate and visually accessible results within minimal time. This approach enhances the in vivo evaluation of tumor margins, leading to more clear margins and, consequently, improved patient outcomes.
A Hybrid Deep Learning and Machine Learning Approach with Mobile-EfficientNet and Grey Wolf Optimizer for Lung and Colon Cancer Histopathology Classification
Authors: Ochoa-Ornelas Raquel , Gudiño-Ochoa Alberto , García-Rodríguez Julio Alberto
Published: November 2024

Background: Lung and colon cancers are among the most prevalent and lethal malignancies worldwide, underscoring the urgent need for advanced diagnostic methodologies. This study aims to develop a hybrid deep learning and machine learning framework for the classification of Colon Adenocarcinoma, Colon Benign Tissue, Lung Adenocarcinoma, Lung Benign Tissue, and Lung Squamous Cell Carcinoma from histopathological images. Methods: Current approaches primarily rely on the LC25000 dataset, which, due to image augmentation, lacks the generalizability required for real-time clinical applications. To address this, Contrast Limited Adaptive Histogram Equalization (CLAHE) was applied to enhance image quality, and 1000 new images from the National Cancer Institute GDC Data Portal were introduced into the Colon Adenocarcinoma, Lung Adenocarcinoma, and Lung Squamous Cell Carcinoma classes, replacing augmented images to increase dataset diversity. A hybrid feature extraction model combining MobileNetV2 and EfficientNetB3 was optimized using the Grey Wolf Optimizer (GWO), resulting in the Lung and Colon histopathological classification technique (MEGWO-LCCHC). Cross-validation and hyperparameter tuning with Optuna were performed on various machine learning models, including XGBoost, LightGBM, and CatBoost. Results: The MEGWO-LCCHC technique achieved high classification accuracy, with the lightweight DNN model reaching 94.8%, LightGBM at 93.9%, XGBoost at 93.5%, and CatBoost at 93.3% on the test set. Conclusions: The findings suggest that our approach enhances classification performance and offers improved generalizability for real-world clinical applications. The proposed MEGWO-LCCHC framework shows promise as a robust tool in cancer diagnostics, advancing the application of AI in oncology.
Unlocking Potential: A Comprehensive Overview of Cell Culture Banks and Their Impact on Biomedical Research
Authors: Weiskirchen Sabine , Monteiro Antonio M. , Borojevic Radovan , Weiskirchen Ralf
Published: November 2024

Cell culture banks play a crucial role in advancing biomedical research by providing standardized, reproducible biological materials essential for various applications, from drug development to regenerative medicine. This opinion article presents a comprehensive overview of cell culture banks, exploring their establishment, maintenance, and characterization processes. The significance of ethical considerations and regulatory frameworks governing the use of cell lines is discussed, emphasizing the importance of quality control and validation in ensuring the integrity of research outcomes. Additionally, the diverse types of cell culture banks—primary cells, immortalized cell lines, and stem cells—and their specific contributions to different fields such as cancer research, virology, and tissue engineering are examined. The impact of technological advancements on cell banking practices is also highlighted, including automation and biobanking software that enhance efficiency and data management. Furthermore, challenges faced by researchers in accessing high-quality cell lines are addressed, along with proposed strategies for improving collaboration between academic institutions and commercial entities. By unlocking the potential of cell culture banks through these discussions, this article aims to underline their indispensable role in driving innovation within biomedical research and fostering future discoveries that could lead to significant therapeutic breakthroughs.
Small and Long Non-Coding RNA Analysis for Human Trophoblast-Derived Extracellular Vesicles and Their Effect on the Transcriptome Profile of Human Neural Progenitor Cells
Authors: Kinkade Jessica A. , Singh Pallav , Verma Mohit , Khan Teka , Ezashi Toshihiko , Bivens Nathan J. , Roberts R. Michael , Joshi Trupti , Rosenfeld Cheryl S.
Published: November 2024

In mice, the fetal brain is dependent upon the placenta for factors that guide its early development. This linkage between the two organs has given rise to the term, the placenta–brain axis. A similar interrelationship between the two organs may exist in humans. We hypothesize that extracellular vesicles (EVs) released from placental trophoblast (TB) cells transport small RNA and other informational biomolecules from the placenta to the brain where their contents have pleiotropic effects. Here, EVs were isolated from the medium in which human trophoblasts (TBs) had been differentiated in vitro from induced pluripotent stem cells (iPSC) and from cultured iPSC themselves, and their small RNA content analyzed by bulk RNA-seq. EVs derived from human TB cells possess unique profiles of miRs, including hsa-miR-0149-3p, hsa-302a-5p, and many long non-coding RNAs (lncRNAs) relative to EVs isolated from parental iPSC. These miRs and their mRNA targets are enriched in neural tissue. Human neural progenitor cells (NPCs), generated from the same iPSC, were exposed to EVs from either TB or iPSC controls. Both sets of EVs were readily internalized. EVs from TB cells upregulate several transcripts in NPCs associated with forebrain formation and neurogenesis; those from control iPSC upregulated a transcriptional phenotype that resembled glial cells more closely than neurons. These results shed light on the possible workings of the placenta–brain axis. Understanding how the contents of small RNA within TB-derived EVs affect NPCs might yield new insights, possible biomarkers, and potential treatment strategies for neurobehavioral disorders that originate in utero, such as autism spectrum disorders (ASDs).
Wear and Corrosion Resistance of ZrN Coatings Deposited on Ti6Al4V Alloy for Biomedical Applications
Authors: Rabadzhiyska Stanislava , Dechev Dimitar , Ivanov Nikolay , Ivanova Tatyana , Strijkova Velichka , Katrova Vesela , Rupetsov Velko , Dimcheva Nina , Valkov Stefan
Published: November 2024

Zirconium nitrides films were synthesized on Ti6Al4V substrates at a bias voltage of −50 V, −80 V, −110 V and −150 V by the direct current (DC) reactive magnetron sputtering technique. The as-deposited coatings were characterized by X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) and atomic force microscopy (AFM). The wear and corrosion resistance of the obtained ZrN coatings were evaluated to determine the possibility for their implementation in modern biomedical applications. It was found that the intensity of the diffraction peak of the Zr-N phase corresponding to the (1 1 1) crystallographic plane rose as the bias voltage increased, while the ZrN coatings’ thickness reduced from 1.21 µm to 250 nm. The ZrN films’ surface roughness rose up to 75 nm at −150 V. Wear tests showed an increase in the wear rate and wear intensity as the bias voltage increased. Corrosion studies of the ZrN coatings were carried out by three electrochemical methods: open circuit potential (OCP), cyclic voltammetry (polarization measurements) and electrochemical impedance spectroscopy (EIS). All electrochemical measurements confirmed that the highest protection to corrosion is the ZrN coating, which was deposited on the Ti6Al4V substrate at a bias voltage of −150 V.
Review of Power-to-Liquid (PtL) Technology for Renewable Methanol (e-MeOH): Recent Developments, Emerging Trends and Prospects for the Cement Plant Industry
Authors: Marques Luísa , Vieira Maria , Condeço José , Sousa Henrique , Henriques Carlos , Mateus Maria
Published: November 2024

The cement industry is a significant contributor (around 8%) to CO2 global emissions. About 60% of the industry’s emissions come from limestone calcination, which is essential for clinker production, while 40% are the result of fuel combustion. Reducing these emissions is challenging due to limestone’s role as the primary raw material for cement. Cement plants are required to achieve carbon neutrality by 2050, as outlined in the 13th United Nations Sustainable Goals. One strategy to achieve this goal, involves Carbon Capture and utilization (CCU). Among the options for CO2 utilization, the Power-to-Liquid (PtL) strategy offers a means to mitigate CO2 emissions. In PtL, the CO2 captured from cement industrial flue gas is combined with the hydrogen generated by renewable electrolysis (green hydrogen) and is catalytically converted into renewable methanol (e-MeOH). In this sense, this review provides a comprehensive overview of the worldwide existing pilot and demonstration units and projects funded by the EU across several industries. It specifically focuses on PtL technology worldwide within cement plants. This work covers 18 locations worldwide, detailing technology existent at plants of different capacities, location, and project partners. Finally, the review analyses techno-economic assessments related to e-MeOH production processes, highlighting the potential impact on achieving carbon neutrality in the cement industry.
From Fossil Fuels to Renewables: Clustering European Primary Energy Production from 1990 to 2022
Authors: Kosowski Piotr
Published: November 2024

This study examines the structural shifts in primary energy production across European countries from 1990 to 2022, focusing on changes in energy sources and their implications for energy security and sustainability. Set against a backdrop of evolving geopolitical landscapes, economic pressures, and climate policies, including significant recent impacts such as the conflict in Ukraine, this research highlights the critical importance of a stable and diversified energy supply. The analysis utilizes the k-means clustering method, examining countries for which data are available in the Eurostat database and considering primary energy sources as defined by the Standard International Energy Product Classification (SIEC), including solid fossil fuels, natural gas, crude oil, nuclear energy, renewable energy sources, peat, and non-renewable waste. By categorizing European nations into clusters based on their energy production profiles, the study reveals substantial transitions from fossil fuel-based systems to those increasingly dominated by renewable energy sources. While some countries have made significant progress in integrating renewables, others remain heavily dependent on traditional energy sources such as coal and natural gas. The findings underscore the growing role of natural gas as a bridge fuel and the relatively stable contribution of nuclear energy in certain regions. A key outcome is the observed disparity between energy production and consumption across Europe, with many large economies facing a persistent deficit in domestic energy production, resulting in a high reliance on energy imports, particularly of natural gas and oil. This dependency poses significant challenges to energy security, especially given recent geopolitical disruptions and market fluctuations. The paper also discusses the environmental implications of these energy trends, emphasizing the vital role of renewable energy in achieving the European Union’s decarbonization goals.
Flow Separation Control and Aeroacoustic Effects of a Leading-Edge Slat over a Wind Turbine Blade
Authors: Bouterra Sami , Belamadi Riyadh , Djemili Abdelouaheb , Ilinca Adrian
Published: November 2024

To enable wind energy to surpass fossil fuels, the power-to-cost ratio of wind turbines must be competitive. Increasing installation capacities and wind turbine sizes indicates a strong trend toward clean energy. However, larger rotor diameters, reaching up to 170 m, introduce stability and aeroelasticity concerns and aerodynamic phenomena that cause noise disturbances. These issues hinder performance enhancement and social acceptance of wind turbines. A critical aerodynamic challenge is flow separation on the blade’s suction side, leading to a loss of lift and increased drag, ultimately stalling the blade and reducing turbine performance. Various active and passive flow control techniques have been studied to address these issues, with passive techniques offering the advantage of no external energy requirement. High-lift devices, such as leading-edge slats, are promising in improving aerodynamic performance by controlling flow separation. This study explores the geometric parameters of slats and their effects on wind turbine blades’ aerodynamic and acoustic performance. Using an adequate turbulence model at Re = 106 for angles of attack from 14° to 24°, 77 slat configurations were evaluated. Symmetric slats showed superior performance at high angles of attack, while slat chord length was inversely proportional to aerodynamic improvement. A hybrid method was employed to predict noise, revealing slat-induced modifications in eddy topology and increased low- and high-frequency noise. This study’s main contribution is correlating slat-induced aerodynamic improvements with their acoustic effects. The directivity reveals a 10–15 dB reduction induced by the slat at 1 kHz, while the slat induces higher noise at higher frequencies.
Evaluation Method of Water Injection Development Effects in Fractured Vuggy Carbonate Reservoirs: Case Study of FI7 Strike-Slip Fault Zone
Authors: Geng Jie , Xiao Long , Yue Ping , Xiao Yun , Yang Hongnan , Qu Simin , Wang Xia
Published: November 2024

As the main method of secondary development, water injection has been widely used in fractured vuggy carbonate reservoirs. By using an evaluation index system combined with an integrated approach to objectively evaluate and support targeted and operational adjustments of water injection development effects in fractured vuggy carbonate reservoirs, a comprehensive evaluation method is established in this study. The CRITIC method is used as the main approach, and the analytic hierarchy process, the entropy weight method, and the coefficient of variation method are used as sub-methods. Additionally, the clustering centres are divided using the clustering method to reduce the error caused by the irrational distribution of the relevant evaluation index data. The method is used to evaluate and analyse the effects of water injection development, using the FI7 fault zone of the Halahatang oilfield as an example. The application results show that the evaluation method is feasible and effective for cases with small data volume, fewer computational resources, and less time. This study has a certain reference significance for the evaluation of the effect of water injection development in similar fractured vuggy reservoirs.
Research on the Internal Flow and Cavitation Characteristics of Petal Bionic Nozzles Based on Methanol Low-Pressure Injection
Authors: Zhu Yuejian , Wang Yanxia , Wang Yannian
Published: November 2024

This paper aims to discuss the internal flow and cavitation characteristics of petal bionic nozzle holes under different injection pressures to improve the atomization effect of methanol. The FLUENT (v2022 R1) software is used for simulation. The Schnerr-Sauer cavitation model in the Mixture multiphase flow model is adopted, considering the evaporation and condensation processes of methanol fuel to accurately simulate cavitation and internal flow performance. The new nozzle hole is compared with the ordinary circular nozzle hole for analysis to ensure research reliability. The results show that the cavitation of the petal bionic nozzle hole mainly occurs at the outlet, which can enhance the atomization effect. In terms of turbulent kinetic energy, the internal turbulent kinetic energy of the petal bionic nozzle hole is greater under the same pressure. At 1 MPa, its outlet turbulent kinetic energy is 38.37 m2/s2, which is about 2.3 times that of the ordinary circular nozzle hole. When the injection pressure is from 0.2 MPa to 1 MPa, the maximum temperature of the ordinary circular nozzle hole increases by about 33.4%, while that of the petal bionic nozzle hole only increases by 12.3%. The intensity of internal convection and vortex is significantly reduced. The outlet velocity and turbulent kinetic energy distribution of the petal bionic nozzle hole are more uniform. In general, the internal flow performance of the petal bionic nozzle hole is more stable, which is beneficial to the collision and fragmentation of droplets and has better uniformity of droplet distribution. It has a positive effect on improving the atomization effect of methanol injection in the intake port of methanol-diesel dual-fuel engines.
Electric Vehicles for a Flexible Energy System: Challenges and Opportunities
Authors: Micari Salvatore , Napoli Giuseppe
Published: November 2024

As the adoption of Electric Vehicles (EVs) accelerates, driven by increasing urbanization and the push for sustainable infrastructure, the need for innovative solutions to support this growth has become more pressing. Vehicle-to-Grid (V2G) technology presents a promising solution by enabling EVs to engage in bidirectional interactions with the electrical grid. Through V2G, EVs can supply energy back to the grid during peak demand periods and draw power during off-peak times, offering a valuable tool for enhancing grid stability, improving energy management, and supporting environmental sustainability. Despite its potential, the large-scale implementation of V2G faces significant challenges, particularly from a technological and regulatory standpoint. The success of V2G requires coordinated efforts among various stakeholders, including vehicle manufacturers, infrastructure providers, grid operators, and policymakers. In addition to the technical barriers, such as battery degradation due to frequent charging cycles and the need for advanced bidirectional charging systems, regulatory frameworks must evolve to accommodate this new energy paradigm. This review aims to provide a comprehensive analysis of V2G technology, focusing on different perspectives—such as those of users, vehicles, infrastructures, and the electricity grid. This study will also explore ex ante, ex post, and ongoing assessment studies, alongside the experiences of pioneer cities in implementing V2G.
Comparative Approaches to Energy Transition: Policy Guideline for Enhancing Thailand’s Path to a Low-Carbon Economy
Authors: Kanchana Kamonphorn
Published: November 2024

Thailand’s transition to a low-carbon economy faces significant challenges, including a dependency on fossil fuels, fluctuating energy costs, and limited policy clarity. This study conducts a comparative analysis of energy transition policies in Germany, Japan, Australia, Malaysia, and Singapore to derive actionable lessons that can be adapted to Thailand’s socio-economic and energy contexts. Using the Integrated National Energy Planning (INEP) framework and Network Governance Theory, the research identifies key strategies, such as setting clear and achievable renewable energy targets, establishing robust legal frameworks, fostering multi-stakeholder engagement, and encouraging decentralized governance. The findings highlight the importance of long-term vision, inclusive governance, and targeted investments in renewable technologies to accelerate energy transitions. This paper presents policy guidelines to enhance Thailand’s energy security and contribute to its climate goals by promoting public awareness and strengthening institutional capacities. By adapting these strategies, Thailand can align with global energy trends, reduce its reliance on fossil fuels, and advance toward a resilient and sustainable energy system, aligned with global energy trends while addressing its unique socio-economic context.
Life Cycle Assessment and Process Optimization of Precipitated Nanosilica—A Case Study in China
Authors: Gu Shan , Yang Li , Liang Xiaoye , Zhou Jingsong
Published: November 2024

To mitigate environmental emissions in the industrial nanosilica sector and promote its sustainable development, the life cycle assessment (LCA) method is employed to evaluate the environmental impacts throughout the life cycle of industrial precipitated nanosilica. This LCA spans from the acquisition and transportation of raw materials to the production of nanosilica. By identifying the critical contributing factors, effective optimization strategies have been proposed to enhance the environmental performance of the nanosilica life cycle. The effects of electricity, alkalis, acids, and steam on the life cycle emission factors of nanosilica were examined. The results indicate that substituting traditional coal power and steam with cleaner alternatives like wind energy, hydroelectric power, and solar power (both photovoltaic and thermal), as well as biogas steam, can lead to a significant reduction in the life cycle emission factors of nanosilica, ranging from 50% to 90%. Notably, the types of acids and alkalis used only significantly reduce certain environmental factors. These findings provide valuable theoretical insights and practical guidance for the industrial nanosilica sector, particularly in the areas of energy conservation, emission reduction, and the transition towards a lower-carbon economy.
High-Precision Rotor Position Fitting Method of Permanent Magnet Synchronous Machine Based on Hall-Effect Sensors
Authors: Qu Kaining , Pang Pengfei , Hua Wei
Published: November 2024

The high-performance vector control technology of permanent magnet synchronous machines (PMSMs) relies on high-precision rotor position. The Hall-effect sensor has the advantages of low cost, simple installation, and strong anti-interference ability. However, it can only provide six discrete rotor angles in an electrical cycle, which makes high-precision vector control of PMSMs difficult. Hence, to obtain the necessary rotor position of PMSMs, a rotor position fitting method combining the Hall signal and machine flux information is proposed. Firstly, the rotor position signal output by the Hall-effect sensors is used to calibrate and update the stator flux obtained under pure integration. Then, based on the corrected stator flux and its relationship with current and angle, the rotor position and speed are obtained. Experimental verification shows that the rotor position observer combining Hall signal and flux information can reduce the initial value bias and integral drift caused by traditional average speed method hysteresis and pure integration method calculation of flux and can quickly and accurately track and estimate the rotor position, achieving high-performance vector control of PMSMs.
Modeling of Lithium-Ion Batteries for Electric Transportation: A Comprehensive Review of Electrical Models and Parameter Dependencies
Authors: Graber Giuseppe , Sabatino Simona , Calderaro Vito , Galdi Vincenzo
Published: November 2024

The power and transportation sectors contribute to more than 66% of global carbon emissions. Decarbonizing these sectors is critical for achieving a zero-carbon economy by mid-century and mitigating the most severe impacts of climate change. Battery packs, which enable energy storage in electric vehicles, are a key component of electrified transport systems. The production of these batteries has significantly increased in recent years to meet rising demand, and this trend is expected to continue. However, current traction batteries exhibit lower energy density compared to fossil fuels. As a result, accurate battery models that balance computational complexity and precision are essential for designing high-performance energy storage systems. This paper provides a comprehensive review of the most used electrical models for lithium-ion batteries in traction applications, as reported in the technical literature. By exploring the strengths and limitations of different modeling approaches, this paper aims to offer valuable insights into their practical applicability for the electrification of transportation systems. Additionally, this paper discusses the primary methods employed to derive the values of the electrical components within these models. Finally, it examines the key parameters—such as temperature, state of charge, and aging—that significantly influence the component values. Ultimately, it guides researchers and practitioners in selecting the most suitable modeling approach for their specific needs.
Simulators for Conversing Power to Thermal on Green Data Centers: A Review
Authors: Li Danyang , Song Jie , Liu Hui , Jiang Jingqing
Published: November 2024

This paper aims to help data center administrators choose thermal simulation tools, which manage thermal conduction from power for energy savings. When evaluating and suggesting data center thermal simulators for users, questions such as “What are the simulator’s differences? Are they easy to use? Which is the best choice?” are frequently asked. To answer these questions, this paper reviews the thermal simulation works for data centers in the last ten years. After that, it proposes the versatility and dexterity metrics for these simulators and discovers that it is difficult to choose them despite their similar design purpose and functions. Empowered by the survey, we claim that the widespread practice simulators still need more enhancement in data center scenarios. We back up our claim by comparing typical simulators and propose improvements to thermal simulators for future studies.
Wind Farm Layout Optimization/Expansion of Real Wind Turbines with a Parallel Collaborative Multi-Objective Optimization Algorithm
Authors: Bouchekara Houssem R. E. H. , Ramli Makbul A. M. , Javaid Mohammad S.
Published: November 2024

The objective of this paper is to study the Wind Farm Layout Optimization/expansion problem. This problem is formulated here as a Multi-Objective Optimization Problem considering the total power output and net efficiency of Wind Farms as objectives along with specific constraints. Once formulated, this problem needs to be solved efficiently. For that, a new approach based on a combination of five Multi-Objective Optimization algorithms, which is named the Parallel Collaborative Multi-Objective Optimization Algorithm, is developed and implemented. This technique is checked on seven test cases; for each case, the goal is to find a set of optimal solutions called the Pareto Front, which can be exploited later. The acquired solutions were compared with other approaches and the proposed approach was found to be the better one. Finally, this work concludes that the proposed approach gives, in a single run, a set of optimal solutions from which a designer/planner can select the best layout of a designed Wind Farm using expertise and applying technical and economic constraints.
Energy Sources and Battery Thermal Energy Management Technologies for Electrical Vehicles: A Technical Comprehensive Review
Authors: Afia Sara El , Cano Antonio , Arévalo Paul , Jurado Francisco
Published: November 2024

Electric vehicles are increasingly seen as a viable alternative to conventional combustion-engine vehicles, offering advantages such as lower emissions and enhanced energy efficiency. The critical role of batteries in EVs drives the need for high-performance, cost-effective, and safe solutions, where thermal management is key to ensuring optimal performance and longevity. This study is motivated by the need to address the limitations of current battery thermal management systems (BTMS), particularly the effectiveness of cooling methods in maintaining safe operating temperatures. The hypothesis is that immersion cooling offers superior thermal regulation compared to the widely used indirect liquid cooling approach. Using MATLAB Simulink, this research investigates the dynamic thermal behaviour of three cooling systems, including air cooling, indirect liquid cooling, and immersion cooling, by comparing their performance with an uncooled battery. The results show that immersion cooling outperforms indirect liquid cooling in terms of temperature control and safety, providing a more efficient solution. These findings challenge the existing literature, positioning immersion cooling as the optimal BTMS. The main contribution of this paper lies in its comprehensive evaluation of cooling technologies and its validation of immersion cooling as a superior method for enhancing EV battery performance.
A LiDAR-Based Active Yaw Control Strategy for Optimal Wake Steering in Paired Wind Turbines
Authors: Mahmoodi Esmail , Khezri Mohammad , Ebrahimi Arash , Ritschel Uwe , Kamandi Majid
Published: November 2024

In this study, we investigate a yaw control strategy in a two-turbine wind farm with 3.5 MW turbines, aiming to optimize power management. The wind farm is equipped with a nacelle-mounted multi-plane LiDAR system for wind speed measurements. Using an analytical model and integrating LiDAR and SCADA data, we estimate wake effects and power output. Our results show a 2% power gain achieved through optimal yaw control over a year-long assessment. The wind predominantly blows from the southwest, perpendicular to the turbine alignment. The optimal yaw and power gain depend on wind conditions, with higher turbulence intensity and wind speed leading to reduced gains. The power gain follows a bell curve across the range of wind inflow angles, peaking at 1.7% with a corresponding optimal yaw of 17 degrees at an inflow angle of 12 degrees. Further experiments are recommended to refine the estimates and enhance the performance of wind farms through optimized yaw control strategies, ultimately contributing to the advancement of sustainable energy generation.
Numerical Simulation of Seepage in Shale Oil Reservoirs Under Hydraulic Fracturing: From Core-Scale Experiment to Reservoir-Scale Modeling
Authors: Gao Yanfang , Wang Di , Chen Zupeng , Li Yanchao , Shen Shijie , Li Dengke , Liang Xuelin , Huang Zhi
Published: November 2024

In this study, finite element software was used to simulate seepage at the core scale, the stress sensitivity of the shale core of the stripe layer and fractures was evaluated, and the production optimization design of reservoir C in block B of the oilfield under different fracturing parameters and wellbore parameters was simulated. The coupled finite element model of reservoir seepage stress was established; the pore elasticity model was used to determine the reservoir deformation; the seepage followed Forchheimer’s law and Darcy’s law; and finally, the liquid production was calculated to optimize the production plan. The results showed that the permeability under the same stress conditions increased nonlinearly with the increase in the striatal angle at the core scale, the permeability under the same effective stress conditions decreased gradually with the increase in the shale/fringe thickness ratio, and the elastic modulus and Poisson’s ratio of the proppant decreased. The permeability stress sensitivity was stronger. In the reservoir-scale model, the production pressure difference was the most significant factor affecting shale oil production, followed by the number of fractures and the length of the horizontal zone wellbore, and the elastic modulus of the proppant and Poisson’s ratio had the least impact on production.
Synergistic Effects of Energy Storage Systems and Demand-Side Management in Optimizing Zero-Carbon Smart Grid Systems
Authors: Almutairi Zeyad A. , Eltamaly Ali M.
Published: November 2024

The urgent need to mitigate climate change and reduce reliance on fossil fuels has driven the global shift towards renewable energy sources (RESs). However, the intermittent nature of RESs poses significant challenges to the widespread adoption of Zero-Carbon Smart Grids (ZCSGs). This study proposes a synergistic framework to address this hurdle. It utilizes energy storage systems (ESSs) by comparing Vanadium redox flow batteries (VRFBs) and Lithium ion batteries (LIBs) to identify the most suitable option for ZCSGs, with precise models enabling robust performance evaluation. Moreover, an accurate demand-side management (DSM) strategy considering power elasticity to manage discrepancies between electricity load, RES generation, and ESS availability is introduced for estimating fair, dynamic tariffs. An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. Simulations demonstrate significant reductions in carbon footprint, peak power demand, and reliance on fossil fuels. The study finds that VRFBs outperform LIBs in cost and security, and dynamic tariffs based on accurate DSM significantly reduce energy costs. This work explores the challenges and opportunities of this integrated approach, offering policy recommendations and future research directions for truly optimized ZCSG implementation.
Study on Windage Response Suppression of Large-Span Transmission Tower-Line System Using a Spring-Pendulum Dynamic Vibration Absorber
Authors: Song Peng , Lang Xujun , Zhang Sixiang , Yang Bo , Zhang Siyao , Rong Kunjie , Tian Li
Published: November 2024

Insulators and conductors in transmission line systems are susceptible to wind-induced movements, especially when insulators are closely positioned to transmission towers, potentially leading to electrical discharge. To address this issue, this study proposes a spring-pendulum dynamic vibration absorber (SPDVA) for windage suppression in transmission line systems. Using a finite element model based on an actual transmission line project, the study investigates SPDVA’s effectiveness in mitigating windage responses under varying wind speeds. The analysis considers mass and stiffness parameters to elucidate SPDVA’s suppression mechanism. The results indicate that SPDVA outperforms the additional heavy hammer method in suppressing insulator windage responses and also affects the peak acceleration response at the insulator’s bottom. Increasing stiffness initially enhances SPDVA’s suppression effectiveness on both peak and mean square deviation windage angle responses, peaking at 10 kN/m stiffness, while increasing the mass of the mass block also enhances suppression effectiveness.
Fault Section Identification for Hybrid Transmission Lines Considering the Weak-Feed Characteristics of Floating Photovoltaic Power Plant Inverters
Authors: Ye Huiqiang , Zhu Lifeng , Xu Weifeng , Liu Fangzhou , Liu Xinbo , Xu Yi , Wang Qianggang
Published: November 2024

The overhead line (OHL)–cable hybrid transmission line, which connects floating photovoltaic (PV) power plants, needs to be considered regarding whether to block reclosing operations or not. However, due to the weak-feed characteristics of PV inverters, existing methods are difficult to apply in this scenario. This paper proposes a criterion for fault section identification in the transmission lines of floating PV power plants based on traveling wave power and the zero-sequence impedance angle. Firstly, the fault current characteristics of photovoltaic inverters under dual-vector control are analyzed, and the applicability of the sequence component impedance directional criterion in this scenario is discussed. Then, the transmission, refraction, and reflection processes of traveling waves in OHL–cable hybrid lines are analyzed, and a traveling wave energy criterion is designed to determine the fault section. Finally, based on the scope of application of the zero-sequence impedance angle and traveling wave energy criterion, a fault section identification method for the hybrid lines of floating PV power plants is established. A deployment method for the proposed method, based on feeder terminal units (FTUs) at the connection points between the OHL and cable is proposed. This method identifies fault sections through traveling waves and zero-sequence impedance angles, which are unaffected by PV week feed characteristics, can be applied to all the AC fault types, and do not rely on multi-terminal synchronous sampling. The proposed method is verified on a 1MW PV system built in the PSCAD.
The Effects of Localized Heating and Ethephon Application on Cambial Reactivation, Vessel Differentiation, and Resin Canal Development in Lacquer Tree, Toxicodendron vernicifluum, from Winter to Spring
Authors: Tiyasa Novena Puteri , Rahman Md Hasnat , Nakaba Satoshi , Funada Ryo
Published: November 2024

Resin canals serve as a natural feature with the function of a defense system against fungi, bacteria, and insects. Trees can form these canals in response to mechanical injury and ecological disturbance. Factors, such as plant hormones and temperature, influence cambial activity and cell differentiation. This study examined the effects of increased temperature and plant hormones on cambial reactivation, vessel formation, and resin canal formation using localized heating and the application of the ethylene generator ethephon to dormant stems of the Toxicodendron vernicifluum seedlings. Localized heating was achieved by wrapping an electric heating ribbon around dormant stems, while ethephon was applied to the bark surface. Treatment was initiated on 29 January 2021, including control, heating, ethephon, and a combination of heating and ethephon. Cambial reactivation and resin canal formation were monitored using light microscopy, and bud growth was recorded with a digital camera. Localized heating induced earlier phloem reactivation, cambial reactivation, and xylem differentiation, increasing the number of vessels. The application of exogenous ethylene delayed these processes. The combination of localized heating and exogenous ethylene application resulted in smaller vessels and larger resin canals. These results suggest that increased temperature plays a significant role in cambial reactivation and vessel formation in ring-porous hardwood and that ethylene affects vessel differentiation and resin canal development.
Combining LiDAR, SAR, and DEM Data for Estimating Understory Terrain Using Machine Learning-Based Methods
Authors: Huang Jiapeng , Zhang Yue , Ding Jianhuang
Published: November 2024

Currently, precise estimation of understory terrain faces numerous technical obstacles and challenges that are difficult to overcome. To address this problem, this paper combines LiDAR, SAR, and DEM data to estimate understory terrain. The high multivariable-precision spaceborne LiDAR ICESat-2 data, validated by the NEON, are divided into training and validation sets. The training dataset is used as a dependent variable, the SRTM DEM and Sentinel-1 SAR data are regarded as independent variables, a total of 13 feature parameters with high contributions are extracted to construct a Multiple Linear Regression model (MLR), BAGGING model, Random Forest model (RF), and Long Short-Term Memory model (LSTM). The results indicate that the RF model exhibits the highest accuracy among the four models, with R2 = 0.999, RMSE = 0.701 m, and MAE = 0.249 m. Then, based on the RF model, the understory terrain at the regional scale is generated, and an accuracy assessment is performed using the validation dataset, yielding R2 = 0.999, RMSE = 0.847 m, and MAE = 0.517 m. Furthermore, this paper quantitatively analyzes the effects of slope, vegetation coverage, and canopy height on the estimation accuracy of understory terrain. The results show that as slope, and canopy height increase, the estimation accuracy of the RF model for understory terrain gradually decreases. The accuracy of the understory terrain estimated by the RF model is relatively stable and not easily affected by slope, vegetation coverage, and canopy height. The research on the estimation of understory terrain holds significant practical implications for forest resource management, ecological conservation, and biodiversity protection, as well as natural disaster prevention.
Approaches to Identifying Emotions and Affections During the Museum Learning Experience in the Context of the Future Internet
Authors: Fominska Iana , Di Tore Stefano , Nappi Michele , Iovane Gerardo , Sibilio Maurizio , Gelo Angela
Published: November 2024

The Future Internet aims to revolutionize digital interaction by integrating advanced technologies like AI and IoT, enabling a dynamic and resilient network. It envisions emotionally intelligent systems that can interpret and respond to human feelings, creating immersive, empathy-driven learning experiences. This evolution aspires to form a responsive digital ecosystem that seamlessly connects technology and human emotion. This paper presents a computational model aimed at enhancing the emotional aspect of learning experiences within museum environments. The model is designed to represent and manage affective and emotional feedback, with a focus on how emotions can significantly impact the learning process in a museum context. The proposed model seeks to identify and quantify emotions during a visitor’s engagement with museum exhibits. To achieve this goal, we primarily explored the following: (i) methods and techniques for assessing and recognizing emotional responses in museum visitors, (ii) feedback management strategies based on the detection of visitors’ emotional states. Then, the methodology was tested on 1000 cases via specific questionnaire forms, along with the presentation of images and short videos, and the results of data analysis are reported. The findings contribute toward establishing a comprehensive methodology for the identification and quantification of the emotional state of museum visitors.
Rhegmatogenous Retinal Detachment Secondary to Type I Stickler Syndrome: Diagnosis, Treatment and Long-Term Outcomes
Authors: Chen Xin , Ju Yuqiao , Gao Fengjuan , Zong Yuan , Zhang Ting , Li Ruiwen , Chang Qing , Huang Xin
Published: November 2024

Objective: This study aimed to clarify the genetic diagnosis of rhegmatogenous retinal detachment (RRD) secondary to type I Stickler syndrome (STL1) and evaluate the anatomical and functional outcomes of surgical treatment. Methods: This retrospective study included 11 patients with RRD secondary to STL1. Familial and sporadic cases of STL1 were diagnosed at the Eye & ENT Hospital, Fudan University, between 2017 and 2023. To clarify the genetic diagnosis, next-generation sequencing was performed in suspected STL1 cases. Further, standard ocular examinations and surgical treatment were performed. Results: Nine variants of COL2A1, including four novel mutations (c.394G>T, c.2977G>T, c.3003+2dup, and c.3853G>C), were screened and identified. The pathogenicity of all variants was conclusively demonstrated. Among patients who underwent vitrectomy, the mean age at RRD was 11.5 years, and the mean follow-up was 32.9 months. The average number of surgical procedures required during the follow-up was two; 90.9% of eyes achieved final attachment, and best corrected visual acuity (BCVA) significantly improved in 81.8% of the eyes, with a middle postoperative logMAR BCVA of 0.52 compared with the preoperative value (p = 0.0148). High intraocular pressure (81.8%) and cataract (72.7%) were the most common complications. Conclusions: Our study expands the spectrum of COL2A1 mutations and provides a novel diagnostic strategy for STL1. By combining clinical manifestations with genetic testing, STL1 could be accurately diagnosed. With proper surgical treatment and long-term follow-up, the prognosis of RRD in patients with STL1 could be improved.
Epigenetic Regulation of Anthocyanin Biosynthesis in Betula pendula ‘Purple Rain’
Authors: Gu Chenrui , Xu Huan , Yuan Qihang , Huang Jinbo , Yuan Kunying , Zhao Yihan , Liu Guifeng , Zhang Qingzhu , Jiang Jing
Published: November 2024

Betula pendula ‘Purple Rain’ is characterized by its purple leaves and has ornamental applications. A green mutant line NL, which was mutated by line NZ of B. pendula ‘Purple Rain’ during tissue culture, shows green leaves instead of the typical purple color of B. pendula ‘Purple Rain’. This study quantified the leaf color traits of NL and a normal B. pendula ‘Purple Rain’ line NZ, and uncovered differentially expressed genes involved in flavonoid biosynthesis pathway genes in NL through RNA-Seq analysis. Compared to NZ, reduced levels of six anthocyanins contained in NL were revealed via flavonoids-targeted metabolomics. Sequence mutations in transcription factors that could explain NL’s phenotype failed to be screened via whole-genome resequencing, suggesting an epigenetic basis for this variant. Therefore, a key gene, BpMYB113, was identified in NL via the combined analysis of small RNA sequencing, whole-genome methylation sequencing, and transcriptomics. In NL, this gene features a hyper CHH context methylation site and a lower transcription level compared to NZ, disrupting the expression of downstream genes in the phenylalanine metabolism pathway, and thereby reducing flavonoid biosynthesis. Our study elucidates an epigenetic mechanism underlying color variation in variegated trees, providing pivotal insights for the breeding and propagation of colored-leaf tree species.