bluuebunny/crossref_metadata_2025 huggingface dataset:
Role and Diagnostic Significance of Apolipoprotein D in Selected Neurodegenerative Disorders
Authors: Kolanek Agata , Cemaga Roman , Maciejczyk Mateusz
Published: December 2024

The World Health Organization in 2021 ranked Alzheimer’s disease and other dementias as the seventh leading cause of death globally. Neurodegenerative disorders are progressive, intractable, and often fatal diseases. Early diagnosis may allow patients to enjoy prolonged survival with attenuated symptomatology because of early intervention. Hence, further research on finding non-invasive biomarkers of neurodegenerative diseases is warranted. Apolipoprotein D (ApoD) is a glycoprotein involved in lipid metabolism, oxidative stress regulation, and inflammation. It is expressed in various body fluids and regions of the central nervous system. ApoD’s roles in neuroprotection, lipid transport, and anti-inflammatory processes are crucial as far as the prevention of neurodegenerative pathologies is concerned. This review aims to summarize the background knowledge on ApoD, and it covers studies indexed in the PubMed, Scopus, and Web of Science databases. It discusses the evidence for the multifaceted roles of ApoD in the mechanisms and pathogenesis of multiple sclerosis, Alzheimer’s disease, and Parkinson’s disease. ApoD may be a specific, sensitive, easily obtained, cost-effective biomarker for neurodegenerative diseases and its applications in diagnostic practices, treatment strategies, and advancing neurodegenerative disorders’ management.
Intrauterine Adhesion-Induced Septated Amniotic Cavity: Ultrasonographic Findings in Second and Third Trimesters
Authors: Huang Jo-Ting , Chen Yu-Ming , Tsai Ching-Chang , Cheng Hsin-Hsin , Lai Yun-Ju , Lee Pei-Fang , Hsu Te-Yao , Huang Kun-Long
Published: December 2024

A 40-year-old woman who had obstetric history of one vaginal delivery and two surgical abortions to terminate early pregnancy received regular prenatal care without any systemic maternal diseases. During the detailed second trimester ultrasound, a homogenous adhesion-induced pseudocystic lesion of 8.6 × 7.4 cm was found between the inlet of the endocervix and the uterine cavity in the lower segment of the uterus. There was a clear septum with an inlet of about 2.6 cm near the right lower segment of the uterus. Transvaginal sonography showed a cervical length of 3.29 cm without dilatation. No gross fetal anomalies were found. Sometimes, the fetal head or limbs moved into this cystic space. At 36 3/7 weeks of gestation, a cesarean section was arranged for fetal breech presentation and pre-labor rupture of the membrane. After the delivery of the baby and its placenta, there was no obvious septum in the uterine cavity but only a very short fibrous tissue from the posterior wall of uterus, which could be destroyed when the baby was delivered. No adverse outcomes for the mother or the neonate were observed.
Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT)
Authors: Dierksen Fiona , Sommer Jakob K. , Tran Anh T. , Lin Huang , Haider Stefan P. , Maier Ilko L. , Aneja Sanjay , Sanelli Pina C. , Malhotra Ajay , Qureshi Adnan I. , Claassen Jan , Park Soojin , Murthy Santosh B. , Falcone Guido J. , Sheth Kevin N. , Payabvash Seyedmehdi
Published: December 2024

Background: Intracerebral hemorrhages (ICH) and perihematomal edema (PHE) are respective imaging markers of primary and secondary brain injury in hemorrhagic stroke. In this study, we explored the potential added value of PHE radiomic features for prognostication in ICH patients. Methods: Using a multicentric trial cohort of acute supratentorial ICH (n = 852) patients, we extracted radiomic features from ICH and PHE lesions on admission non-contrast head CTs. We trained and tested combinations of different machine learning classifiers and feature selection methods for prediction of poor outcome—defined by 4-to-6 modified Rankin Scale scores at 3-month follow-up—using five different input strategies: (a) ICH radiomics, (b) ICH and PHE radiomics, (c) admission clinical predictors of poor outcomes, (d) ICH radiomics and clinical variables, and (e) ICH and PHE radiomics with clinical variables. Models were trained on 500 patients, tested, and compared in 352 using the receiver operating characteristics Area Under the Curve (AUC), Integrated Discrimination Index (IDI), and Net Reclassification Index (NRI). Results: Comparing the best performing models in the independent test cohort, both IDI and NRI demonstrated better individual-level risk assessment by addition of PHE radiomics as input to ICH radiomics (both p < 0.001), but with insignificant improvement in outcome prediction (AUC of 0.74 versus 0.71, p = 0.157). The addition of ICH and PHE radiomics to clinical variables also improved IDI and NRI risk-classification (both p < 0.001), but with a insignificant increase in AUC of 0.85 versus 0.83 (p = 0.118), respectively. All machine learning models had greater or equal accuracy in outcome prediction compared to the widely used ICH score. Conclusions: The addition of PHE radiomics to hemorrhage lesion radiomics, as well as radiomics to clinical risk factors, can improve individual-level risk assessment, albeit with an insignificant increase in prognostic accuracy. Machine learning models offer quantitative and immediate risk stratification—on par with or more accurate than the ICH score—which can potentially guide patients’ selection for interventions such as hematoma evacuation.
Simulation of an Orthodontic System Using the Lingual Technique Based on the Finite Element Method
Authors: Hazem Abbas , Mărășescu Felicia Ileana , Țuculină Mihaela Jana , Popa Dragoș Laurențiu , Geonea Ionuț Daniel , Iliescu Alexandru , Mărășescu Petre , Gheorghe Ioan Ovidiu , Pitru Alma Roxana , Tieranu Eugen Nicolae , Dascălu Ionela Teodora
Published: December 2024

Backgrounds/Objectives: The finite element method (FEM) is an advanced numerical technique that can be applied in orthodontics to study tooth movements, stresses, and deformations that occur during orthodontic treatment. It is also useful for simulating and visualizing the biomechanical behavior of teeth, tissues, and orthodontic appliances in various clinical scenarios. The objective of this research was to analyze the mechanical behavior of teeth, tissues, and orthodontic appliances in various clinical scenarios. Materials and Methods: For this study, we utilized a model derived from a set of CBCT scans of a 26-year-old female patient who underwent fixed orthodontic treatment using the lingual technique. Through a series of programs based on reverse engineering, we constructed a three-dimensional reconstruction of the teeth and their internal structures. Using the finite element method (FEM), we obtained six simulations of an orthodontic system utilizing the fixed lingual technique, in which we employed brackets made of chrome–nickel or gold, and archwires made of nitinol, gold, or stainless steel. Results: The study reveals that although the deformation of the archwires during orthodontic treatment is the same, the forces generated by the three types of archwires on brackets differ. The variation in forces applied to the brackets in the fixed lingual orthodontic technique is essential for customizing orthodontic treatment, as these forces must be precisely controlled to ensure effective tooth movement and prevent overloading of the dental structures. Conclusions: The FEM analysis allows for the identification of ideal combinations between the materials used for orthodontic archwires and the materials used for brackets. This ensures that the optimal intensity of forces applied during the fixed lingual orthodontic technique results in desired tooth movements without causing damage to the enamel, dentin, or pulp of the teeth.
Hydroxyapatite from Mollusk Shells: Characteristics, Production, and Potential Applications in Dentistry
Authors: Muntean Florin Lucian , Olariu Iustin , Marian Diana , Olariu Teodora , Petrescu Emanuela Lidia , Olariu Tudor , Drăghici George Andrei
Published: December 2024

Modern dentistry is turning towards natural sources to overcome the immunological, toxicological, aesthetic, and durability drawbacks of synthetic materials. Among the first biomaterials used as endosseous dental implants, mollusk shells also display unique features, such as high mechanical strength, superior toughness, hierarchical architecture, and layered, microporous structure. This review focusses on hydroxyapatite—a bioactive, osteoconductive, calcium-based material crucial for bone healing and regeneration. Mollusk-derived hydroxyapatite is widely available, cost-effective, sustainable, and a low-impact biomaterial. Thermal treatment coupled with wet chemical precipitation and hydrothermal synthesis are the most common methods used for its recovery since they provide efficiency, scalability, and the ability to produce highly crystalline and pure resulting materials. Several factors, such as temperature, pH, and sintering parameters, modulate the size, purity, and crystallinity of the final product. Experimental and clinical data support that mollusk shell-derived hydroxyapatite and its carbonated derivatives, especially their nanocrystaline forms, display notable bioactivity, osteoconductivity, and osteoinductivity without causing adverse immune reactions. These biomaterials are therefore highly relevant for specific dental applications, such as bone graft substitutes or dental implant coatings. However, continued research and clinical validation is needed to optimize the synthesis of mollusk shell-derived hydroxyapatite and determine its applicability to regenerative dentistry and beyond.
Perturbational Decomposition Analysis for Quantum Ising Model with Weak Transverse Fields
Authors: Li Youning , Huang Junfeng , Zhang Chao , Li Jun
Published: December 2024

This work presents a perturbational decomposition method for simulating quantum evolution under the one-dimensional Ising model with both longitudinal and transverse fields. By treating the transverse field terms as perturbations in the expansion, our approach is particularly effective in systems with moderate longitudinal fields and weak to moderate transverse fields relative to the coupling strength. Through systematic numerical exploration, we characterize parameter regimes and evolution time windows where the decomposition achieves measurable improvements over conventional Trotter decomposition methods. The developed perturbational approach and its characterized parameter space may provide practical guidance for choosing appropriate simulation strategies in different parameter regimes of the one-dimensional Ising model.
Sleep Stage Classification Through HRV, Complexity Measures, and Heart Rate Asymmetry Using Generalized Estimating Equations Models
Authors: Biczuk Bartosz , Żurek Sebastian , Jurga Szymon , Turska Elżbieta , Guzik Przemysław , Piskorski Jarosław
Published: December 2024

This study investigates whether heart rate asymmetry (HRA) parameters offer insights into sleep stages beyond those provided by conventional heart rate variability (HRV) and complexity measures. Utilizing 31 polysomnographic recordings, we focused exclusively on electrocardiogram (ECG) data, specifically the RR interval time series, to explore heart rate dynamics associated with different sleep stages. Employing both statistical techniques and machine learning models, with the Generalized Estimating Equation model as the foundational approach, we assessed the effectiveness of HRA in identifying and differentiating sleep stages and transitions. The models including asymmetric variables for detecting deep sleep stages, N2 and N3, achieved AUCs of 0.85 and 0.89, respectively, those for transitions N2–R, R–N2, i.e., falling in and out of REM sleep, achieved AUCs of 0.85 and 0.80, and those for W–N1, i.e., falling asleep, an AUC of 0.83. All these models were highly statistically significant. The findings demonstrate that HRA parameters provide significant, independent information about sleep stages that is not captured by HRV and complexity measures alone. This additional insight into sleep physiology potentially leads to a better understanding of hearth rhythm during sleep and devising more precise diagnostic tools, including cheap portable devices, for identifying sleep-related disorders.
A Low-Cost Data Acquisition System Design for Multifunctional Test Equipment in Electronics Laboratories
Authors: Atcı Ahmet , Ünal Emin , Akgöl Oğuzhan
Published: December 2024

There are various commercially available multifunctional electronics laboratory test equipment on the market that integrates an oscilloscope, signal generator, and logic analyzer. The price point for all these devices typically exceeds USD 250. To lower this cost to around USD 100, the data acquisition components of these devices need to be re-evaluated. In this paper, we present the design of an analog front-end (AFE) for low-cost multifunctional laboratory equipment, mainly for electronics students. The primary objective was to meet student requirements while ensuring minimal cost, maximum functionality, and high robustness. Through our research, we optimized our AFE design to achieve these objectives effectively. Our approach addresses key limitations found in existing designs, as we developed four-stage attenuation and three-stage op-amp gain architecture. This arrangement optimizes signal clarity and achieves high bandwidth while maintaining a cost-effective framework suitable for educational applications. With this study, a 20 MHz bandwidth, ±40 V input voltage range, volt/div range from 5 mV to 10 V, and minimum amplitude resolution of 9.7 µV were achieved in the design of the analog front-end and data acquisition unit. The achieved bandwidth and linearity enable designed AFE to accommodate applications such as ultrasonic discrete TGC (Time Gain Compensation).
Carbon-Aware Demand Response for Residential Smart Buildings
Authors: Zou Jiamin , Liu Sha , Ouyang Luxia , Ruan Jiaqi , Tang Shuoning
Published: December 2024

The stability and reliability of a smart grid are challenged by the inherent intermittency and unpredictability of renewable energy as its integration into the smart grid increases. This places enormous pressure on the smart grid to manage high loads and volatility. To effectively mitigate the impact of new energy integration on smart grids, demand response (DR) can be altered to the demand-side burdens. Using residential smart buildings (RSBs) in Shanghai, this study proposes a carbon-aware demand response (CADR) model that is predicated on the coordination of power carbon intensity and real-time electricity prices. In order to accomplish a more comprehensive reduction in overall electricity consumption costs, we conducted real-time scheduling of a building’s electrical devices using a greedy algorithm. In addition, a model of an optimal charging and discharging scheme for household electric vehicles was established, which is based on various charging modes, taking into account the electrification of the transportation sector. The cost of EV charging is reduced by an average of 23.18% and 33.2% under the two common charging modes, while the integrated cost of the total annual electricity consumption of household devices is reduced by 8.69%, as indicated by the simulation results.
Statistical Analysis of Intermediate Frequency Underwater Acoustic Communication Channel Characteristics in Deep-Sea Sound Channel Axis
Authors: Li Yunfei , Jia Ning , Han Ruigang , Qu Suna , Liu Yufei , Guo Zhongyuan , Guo Shengming
Published: December 2024

Based on experimental data from the deep-sea sound channel axis in the Western Pacific, the statistical distribution law of cluster structure and channel delay spread characteristics are analyzed for three typical receiving depths near the sound channel axis in this paper. A ray theory-based underwater acoustic channel model is used to explain the variations in channel parameters over time and the receiving depth. The results indicate that the underwater acoustic communication channel at the channel axis depth over a 20-km range exhibits a clustered structure that depends on the emission angles of sound rays. For the amplitude characteristics, the amplitude of each cluster follows an inverse Gaussian distribution, with the maximum average amplitude observed when the receiver and transmitter depths are similar. The amplitude of each cluster fluctuation decreases as the receiving depth increases. Regarding delay spread characteristics, the delay spread of each cluster, as well as the maximum and root mean square delay spread of the channel, conform to a Gaussian mixture distribution. The mean and fluctuation of the delay spread parameters increase with the receiving depth. Variations in the cluster structure and channel delay spread characteristics above are primarily attributed to the time-varying sound speed along the propagation paths of sound rays emitted at small upward angles.
Enhanced Kalman Filter with Dummy Nodes and Prediction Confidence for Bipartite Graph Matching in 3D Multi-Object Tracking
Authors: Sun Shaoyu , Wang Chunyang , Xiao Bo , Liu Xuelian , Shi Chunhao , Sun Rongliang , Han Ruijie
Published: December 2024

Kalman filter (KF)-based methods for 3D multi-object tracking (MOT) in autonomous driving often face challenges when detections are missed due to occlusions, sensor noise, or objects moving out of view. This leads to data association failures and cumulative errors in the update stage, as traditional Kalman filters rely on linear state estimates that can drift significantly without measurement updates. To address this issue, we propose an enhanced Kalman filter with dummy nodes and prediction confidence (KDPBTracker) to improve tracking continuity and robustness in these challenging scenarios. First, we designed dummy nodes to act as pseudo-observations generated from past and nearby frame detections in cases of missed detection, allowing for stable associations within the data association matrix when real detections were temporarily unavailable. To address the uncertainty in these dummy nodes, we then proposed a prediction confidence score to reflect their reliability in data association. Additionally, we modified a constant acceleration motion model combined with position-based heading estimation to better control high-dimensional numerical fluctuations in the covariance matrix, enhancing the robustness of the filtering process, especially in highly dynamic scenarios. We further designed bipartite graph data association to refine Kalman filter updates by integrating geometric and motion information weighted by the prediction confidence of the dummy nodes. Finally, we designed a confidence-based retention track management module to dynamically manage track continuity and deletion based on temporal and reliability thresholds, improving tracking accuracy in complex environments. Our method achieves state-of-the-art performance on the nuScenes validation set, improving AMOTA by 1.8% over the baseline CenterPoint. Evaluation on the nuScenes dataset demonstrates that KDPBTracker significantly improves tracking accuracy, reduces ID switches, and enhances overall tracking continuity under challenging conditions.
High-Altitude Operation of a Commercial 100 kW PEM Fuel Cell System
Authors: Willich Caroline , Frank Daniel , Graf Tobias , Wazlawik Stefan , Brandao Samara , Bauer Christiane
Published: December 2024

A commercially available 100 kW PEM fuel cell system designed for efficient operation on ground-level was tested at low ambient pressures between 750 mbar and 940 mbar in a low-pressure chamber. The current–voltage characteristics at 940 mbar and 900 mbar showed only small differences, while the system performed worse at lower ambient pressures. To enable operation at these low pressures, an additional current-limiting strategy had to be implemented, as it was found that the compressor could not deliver sufficient mass flow at ambient pressures below 867 mbar to reach the maximum current allowed by the system (420 A). The results show that the fuel cell system, which was designed for ground-level applications, can be operated at lower pressures if the proposed current-limiting strategy is implemented, although at the cost of a lower maximum current output at low ambient pressures. Based on the results, suggestions for further hardware measures to optimise the system for flight conditions are made.
A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy
Authors: Zhan Hua , Jiang Changxu , Lin Zhen
Published: December 2024

The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. Furthermore, few scholars in the existing research on distribution network (DN) reconfiguration have considered the graph structure information, resulting in the loss of critical topological information and limiting the effect of optimization. Therefore, this paper proposes an ADNDR approach based on the graph convolutional network deep deterministic policy gradient (GCNDDPG). Firstly, a nonlinear stochastic optimization mathematical model for the ADNDR is constructed, taking into account the uncertainty of sources and loads. Secondly, a loop-based encoding method is employed to reduce the action space and complexity of the ADNDR. Then, based on graph theory, the DN structure is transformed into a dynamic network graph model, and a GCNDDPG-based ADNDR approach is proposed for the solution. In this method, graph convolutional networks are used to extract features from the graph structure information, and the state of the DN, and the deep deterministic policy gradient is utilized to optimize the ADNDR decision-making process to achieve the safe, stable, and economic operation of the DN. Finally, the effectiveness of the proposed approach is verified on an improved IEEE 33-bus power system. The simulation results demonstrate that the method can effectively enhance the economy and stability of the DN, thus validating the effectiveness of the proposed approach.
Oil Cooling Method for Internal Heat Sources in the Outer Rotor Hub Motor of ElectricVehicle and Thermal Characteristics Research
Authors: Guo Fulai , Zhang Chengning
Published: December 2024

The heat dissipation of wheel hub motors is difficult due to the limited installation space and harsh working environment, which will lead to an increase in the operating temperature of the motor. Excessive motor temperature will limit the further increase in the power density and torque density of the motor. Taking the outer rotor hub motor as the research object, a heat dissipation structure is designed by passing oil through the stator core, slot wedge, and the motor end, mainly the cooling stator core, slot winding, and the end winding from inside of the motor. The internal heat is mainly carried away through lubricating oil by convective heat transfer and heat conduction. The heat distribution model of the motor based on the new cooling structure is established using the centralized parameter heat network method. The Motor-CAD software is used to build the motor 3d model and simulate the motor temperature field, and the temperature distribution in the motor under the rated working condition is analyzed. The temperature rising test of the motor prototype are performed on a bench built in the laboratory. The experimental results are consistent with the simulation results of the temperature field, which verify the rationality of the model.
Interline Power Flow Controller Allocation for Active Power Losses Enhancement Using Whale Optimization Algorithm
Authors: Alshannaq Ahmed M. , Haj-ahmed Mohammed A. , Aldwaik Mais , Abualnadi Dia
Published: December 2024

Transmission networks face continuous electrical and mechanical stresses due to increasing system challenges and power losses. Transmission networks require special focus and detailed studies each time a load or a generator emerges to the grid. The interline power flow controller (IPFC) is a relatively new scheme that is implemented in the transmission network to improve transmission efficiency, decrease transmission losses, and enhance voltage profile. In this paper, the interline power flow controller’s impact on transmission network performance is investigated as it is implemented within the IEEE 5-bus, 14-bus, and IEEE 57-bus systems. In addition, the whale optimization algorithm (WOA) is used to optimize the interline power flow controller locations within the system to achieve optimal transmission system performance. WOA performance is also compared to genetic algorithm (GA) and particle swarm optimization (PSO) algorithms, and the superiority of the proposed WOA-based control is proved. The robustness of the optimized system against load variations is investigated and the results introduced affirm the capability of the interline power flow controller to enhance transmission network efficiency.
Performance Analysis of a Solar-Powered Pulverizing Aerator
Authors: Osuch Andrzej , Osuch Ewa , Rybacki Piotr
Published: December 2024

The global energy crisis is associated with the need to search for low-energy technical solutions. Such solutions are also introduced in the field of protection and restoration of surface waters. The aim of this work was to determine the efficiency of the AS15000 pulverizing aerator powered by solar energy. The innovative solutions of the aerator presented in this manuscript are subject to a patent application. A simulation was carried out taking into account the efficiency of the aerator pump and the sunlight conditions for the indicated location. The analysis was carried out for the location of an artificial reservoir—Zalew Średzki in Środa Wielkopolska (Poland). The simulation showed that during 6515 h of aerator operation, the pulverizing system pumped as much as 97,725 m3 of lake water. The amount of pure oxygen introduced into the water during the operation of the device can be as much as 1074.98 kg. The minimum daily value of sunlight enabling continuous operation of the device (24 h a day) with maximum efficiency is 1.43 kW/m2. Deoxygenated water in the pulverizing aeration process is taken from the bottom zone, transported to the surface and sprayed in the atmospheric air. Oxygenated water is intercepted and discharged to the bottom zone. Developing artificial aeration methods for lakes in combination with renewable energy sources is very important for improving water quality. The use of solar power allows the device to be used when it is far from the power infrastructure. This also allows the installation of aerators in the middle of the lake. In accordance with the Water Framework Directive, we should strive to improve the water quality of many European lakes as quickly as possible.
Maximizing the Total Profit of Combined Systems with a Pumped Storage Hydropower Plant and Renewable Energy Sources Using a Modified Slime Mould Algorithm
Authors: Kien Le Chi , Pham Ly Huu , Duong Minh Phuc , Phan Tan Minh
Published: December 2024

This paper examines the effectiveness of a pumped storage hydropower plant (PSHP) when combined with other plants. System 1 examines the contribution of the PSHP to reducing fuel costs for thermal power plants. System 2 examines the optimization of operations for power systems with energy storage and uncertain renewable energies to maximize total profit based on four test system cases: Case 1: neglect the PSHP and consider wind and solar certainty; Case 2: consider the PSHP and wind and solar certainty; Case 3: neglect the PSHP and consider wind and solar uncertainty; and Case 4: consider the PSHP and wind and solar uncertainty. Cases 1 and 2 focus on systems that assume stable power outputs from these renewable energy sources, while Cases 3 and 4 consider the uncertainty surrounding their power output. The presence of a PSHP has a key role in maximizing the system’s total profit. This proves that Case 2, which incorporates a PSHP, achieves a higher total profit than Case 1, which does not include a PSHP. The difference is USD 17,248.60, representing approximately 0.35% for a single day of operation. The total profits for Cases 3 and 4 are USD 5,089,976 and USD 5,100,193.80, respectively. Case 4 surpasses Case 3 by USD 10,217.70, which is about 0.2% of Case 3’s total profit. In particular, the PSHP used in Cases 2 and 4 is a dispatching tool that aims to achieve the highest profit corresponding to the load condition. The PSHP executes its storage function by using low-price electricity at off-peak periods to store water in the reservoir through the pumping mode and discharge water downstream to produce electricity at periods with high electricity prices using the generating mode. As a result, the total profit increases. A modified slime mould algorithm (MSMA) is applied to System 2 after proving its outstanding performance compared to the jellyfish search algorithm (JS), equilibrium optimizer (EO), and slime mould algorithm (SMA) in System 1.
The Impact of Renewable Energy Development on Economic Growth
Authors: Dirma Virgilijus , Neverauskienė Laima Okunevičiūtė , Tvaronavičienė Manuela , Danilevičienė Irena , Tamošiūnienė Rima
Published: December 2024

The development of renewable energy resources significantly impacts economic growth, various aspects of which can be assessed. First, the sector contributes to job creation, as new technologies and projects require specialists in various fields, from engineering to installation. Second, investments in renewable energy drive economic growth as the private and public sectors increasingly invest in innovation and infrastructure. In addition, developing renewable energy sources can lower energy prices for consumers, increase market competition, and reduce dependence on imported resources. However, there are also challenges related to initial investment costs, technological barriers and required political support. To ensure the successful development of renewable energy sources, it is necessary to create a favorable legal and regulatory environment, as well as to promote education and training in this area. In conclusion, the development of renewable energy resources can become an important driver of economic growth but requires a balanced approach and strategic planning. This work aims to evaluate the impact of the use of renewable resources on the economy after examining theories of economic growth. The following methods are used: analysis of theoretical and practical statements, comparative analysis, and panel data analysis. The research rejects hypotheses which suggest that transitioning to renewable energy sources slows economic growth. The development and adoption of renewable energy resources are essential for reducing greenhouse gas emissions, improving air quality, and ensuring sustainable development in the European Union. Despite initial costs and the hypothesis that transitioning to renewable energy slows economic growth, research shows that renewable energy sources (RES) do not hinder growth in the long term. Instead, they drive economic growth through technological advancements, job creation, and attracting significant investments, ultimately contributing to environmental protection and energy stability.
Analysis of an Axial Field Hybrid Excitation Synchronous Generator
Authors: Yu Junyue , Zhu Shushu , Liu Chuang
Published: December 2024

An axial field hybrid excitation synchronous generator (AF-HESG) is proposed for an independent power supply system, and its electromagnetic performance is studied in this paper. The distinguishing feature of the proposed generator is the addition of static magnetic bridges at both ends to place the field windings and the use of a sloping surface to increase the additional air-gap cross-sectional area. The advantage of the structure is that it achieves brushless excitation and improves the flux-regulation range. The structure and magnetic circuit characteristics are introduced in detail. Theoretical analysis of the flux-regulation principle is conducted by studying the relationship between field magnetomotive force, rotor reluctance, and air-gap flux density. Quantitative calculation is performed using a magnetomotive force (MMF)-specific permeance model, and the influence of the main parameters on the air-gap flux density and flux-regulation range is analyzed. Subsequently, magnetic field, no-load, and load characteristics are investigated through three-dimensional finite element analysis. The loss distribution is analyzed, and the temperature of the generator under rated conditions is simulated. Finally, a 30 kW, 1500 r/min prototype is developed and tested. The test results show good flux-regulation capability and stable voltage output performance of the proposed generator.
Experimental Investigation of the Dynamic Deformation of Wind Turbine Blades Based on 3D-Digital Image Correlation
Authors: Zhang Liru , Jia Jing , Shao Shibing , Gao Wei , Niu Dachuan
Published: December 2024

A wind turbine is a rigid–flexible coupling system, and its blades will be deformed under the action of aerodynamic force, inertia force, and elastic force. To monitor the deformation of the blades, this paper builds a dynamic deformation measurement system for wind turbine blades based on 3D-DIC and directly measures the three-dimensional displacement distribution of different blades under different operating conditions to obtain the dynamic deformation of the blades. The experimental results show that the dynamic waving deformation of the blade shows the trend of increasing and then decreasing with the increase in wind turbine rotational speed and incoming wind speed, and when the rotational speed reaches 500 r/min and the incoming wind speed reaches 9 m/s, the blade deformation reaches the maximum value; the dynamic waving deformation of wind turbine blade decreases with the increase in the elastic modulus of the blade and the degree of the decrease decreases gradually; the dynamic deformation of is predicted by the multiple displacement distribution of different blades under different operating conditions, and is obtained by the fitting of the experimental data. This paper develops a 3D-DIC-based dynamic testing system for wind turbine blades, conducts experimental studies to verify and prove the practicality of the system, and finally obtains the prediction polynomials for the dynamic deformation of wind turbine blades under different operating conditions.
Numerical Simulation and Analysis of Semi-Industrial Retrofit for Tangentially Fired Boilers with Slag-Tap Technology
Authors: Wu Qinglong , Fang Fan , Guan Jingyu , Zhu Lingkun , Chen Yang , Deng Lei
Published: December 2024

High-alkali Zhundong coal presents significant challenges for power generation, due to its propensity for fouling and slagging. This study investigates a retrofit of a 300 MW tangentially fired boiler with the integration of a slag-tap chamber to improve combustion performance. Computational fluid dynamics (CFD) simulations are employed to examine the influence of this modification on combustion dynamics and the effects of Zhundong coal blending ratios on heat and mass transfer. The results demonstrate that the retrofit facilitates stable airflow recirculation, optimizing combustion efficiency with a peak temperature of 2080 K in the combustion chamber. The flue gas temperature decreases to approximately 1650 K upon exit, which can be attributed to the slag catcher cooling. The integration of the liquid slagging chamber significantly mitigates slag formation, while enhancing oxygen and CO2 distribution throughout the furnace. As the blending ratio of Zhundong coal increases, oxygen concentrations rise in the bottom burner region, indicating improved air–fuel mixing. With a 30% Zhundong coal ratio, the combustion chamber temperature increases by 3%, and flow velocity in the upper and middle furnace sections decreases by 15%, leading to enhanced combustion intensity. This retrofit demonstrates substantial improvements in combustion stability, slagging control, and the efficient utilization of high-alkali coal.
Research on Self-Recovery Ignition Protection Circuit for High-Voltage Power Supply System Based on Improved Gray Wolf Algorithm
Authors: Zhu Jingyi , Zhu Wanlu , Wei Haifeng , Zhang Yi
Published: December 2024

In order to solve the problems of traditional high-voltage power supply ignition protection circuits, such as non-essential start–stop power supply, a slow response speed, the system needing to be restarted manually, and so on, a high-voltage power supply system self-recovery ignition protection circuit was designed using an IGWO (improved grey wolf optimization) and PID control strategy designed to speed up the response speed, and improve the reliability and stability of the system. In high-voltage power supply operation, the firing discharge phenomenon occurs. Current transformers fire signal into a current signal through the firing voltage value and Zener diode voltage comparison to set the safety threshold; when the threshold is exceeded, the fire protection mechanism is activated, reducing the power supply voltage output to protect the high-voltage power supply system. When the ignition signal disappears, based on the IGWO-PID control of the ignition self-recovery circuit according to the feedback voltage, the DC supply voltage of the high-voltage power supply is adjusted, inhibiting the ignition discharge and, according to the ignition signal, “segmented” to restore the output of the initial voltage. MATLAB/Simulink was used to establish a system simulation model and physical platform test. The results show that the protection effect of the designed scheme is an improvement, in line with the needs of practical work.
Mitigating Mode Switching Oscillation in a One-Motor-One-Pump Motor-Controlled Hydraulic Cylinder via System Pressure Control: Simulation Study
Authors: Zhao Wei , Ebbesen Morten Kjeld , Hansen Michael Rygaard , Andersen Torben Ole
Published: December 2024

This study focuses on a hydraulic cylinder that is directly connected to a fixed-displacement hydraulic pump driven by an electric servo motor. This particular setup is referred to as a one-motor-one-pump motor-controlled hydraulic cylinder (MCC). This paper presents a new approach to address mode switching oscillation (MSO) in MCCs by incorporating system pressure control capabilities. It conducts a detailed investigation into the factors that contribute to MSO in standard MCCs and thoroughly evaluates the effectiveness of the proposed system in mitigating MSO. The simulation results demonstrate the successful suppression of MSO. In conclusion, the proposed MCC with system pressure control capabilities is validated and, furthermore, it shows great potential for practical applications involving small loads and rapid retraction.
Co-Movement Among Electricity Consumption, Economic Growth and Financial Development in Portugal, Italy, Greece, and Spain: A Wavelet Analysis
Authors: Magazzino Cosimo , Naqvi Syed Kafait Hussain , Giolli Lorenzo
Published: December 2024

The aim of this paper is to examine the connections among time-frequency dependencies associated with electrical power consumption (EPC), economic growth, and financial development (FD) in Portugal, Italy, Greece, and Spain during the period 1970–2014. Using monthly data collected from the World Bank (WB) and Federal Reserve Bank of St. Louis (FRED), the wavelet analysis is applied, which allows for assessing the co-movement between these variables. As a first step, a classical time-domain approach is used to alternatively test the connection, including unit-root tests and cointegration. To achieve a comprehensive understanding of the relationships between EPC, economic growth, and FD, we employ Wavelet Transform Coherency (WTC) and Partial Wavelet Coherency (PWC) to explore both their temporal and phase-based dynamics. The main findings show that EPC leads FD, but in the short term, and periods dominated by economic stagnations and political crises. Otherwise, FD drives EPC in the medium term, under economic expansion periods. In both cases, economic growth is crucial, being a strong binding force of the interaction between EPC and FD. The difference in the applied results provides alternative policy implications, justifying the use of the wavelet approach.
Fragility Analysis of Power Transmission Tower Subjected to Wind–Sand Loads
Authors: Ma Xiaoqian , Lu Jun , Li Benliang , Tian Weiguang , Zhang Yaxiao , Zhang Peng
Published: December 2024

With the increasing construction of power transmission towers in desert regions for the transportation of wind or solar energy, structural safety under wind and sand loads has become critical. Current design codes primarily account for wind loads on these towers, overlooking the effects of sand impact. This study presents a new model to simulate sand–steel interactions and evaluates the fragility of transmission towers under both wind-only and combined wind–sand loads. The impact model is grounded in Hertz contact theory, with equations of motion derived for the interaction between wind-driven sand particles and structural members, solved via the central difference method. A parametric study investigates the effects of wind speed and sand particle mass: (1) impact forces and maximum deformations increase with wind speed, with impact duration initially decreasing up to 20 m/s and then gradually increasing; (2) an increase in sand particle mass leads to greater impact deformation, force, and duration. Fragility analysis, using incremental dynamic analysis, reveals that sand particles significantly amplify the tower’s response at high wind speeds and increase failure probability across all wind attack angles. These findings highlight the importance of incorporating sand-impact effects in the design and assessment of power transmission towers in desert environments to ensure structural safety and reliable operation of critical energy infrastructure.
Pasteurization and the Potential Anti-Obesity Function of Fermented Beverages: A Significant Increase in Nitrogen-Containing Aromatic Heterocyclic Compound Content
Authors: Wu Xiurong , Wang Ting , Nie Xiangzhen , Wu Yanglin , Wang Jinghan , Wang Haoming , Dai Rui , Liu Ronghan , Cui Yingying , Su Miaoting , Qiu Yang , Yan Xiantao
Published: December 2024

Obesity is a chronic disease that profoundly impacts human health, and the role of plant-based formulas (PBFs) in combating obesity has garnered significant interest. Studies have revealed that fermentation significantly enhances the taste, aroma, quality, and health benefits of PBF water extract, with pasteurization being the preferred sterilization technology. However, few studies have investigated the effects of pasteurization on the active components and potential functions of PBF water extract fermentation broth. To examine the impact of pasteurization on fermented water extract of Millettia speciosa Champ (FH08F) and its potential anti-obesity properties, the components of FH08F and thermal-pasteurized FH08F (FH08FS) were analyzed in this study. The analysis revealed a substantial rise in ester content following sterilization. This can be attributed to the acidic environment that promotes the esterification reaction during the heating phase. Network pharmacology was employed to thoroughly examine seven active components of upregulated compounds (URCs) with potential obesity targets, which constituted 92.97% of the total URC content, and four of them were nitrogen-containing aromatic heterocyclic compounds (NAHCs), which accounted for 90.33% of the total URC content. Upregulated NAHCs appear to actively contribute to efficacy against obesity. Molecular docking analyses have shown that theophylline, an NAHC, has the strongest binding affinity with the obesity-related target PTGS2 (Prostaglandin G/H synthase 2, 5FLG). These results imply that theophylline may directly activate PKA/PKG-mediated phosphorylated hormone-sensitive lipase (p-HSL), thereby promoting lipolysis through the cAMP signaling pathway and stimulating the catabolism of triglycerides (TGs) to combat obesity. In conclusion, pasteurization substantially alters the composition of FH08F, and NAHCs are likely to play a significant role in its potential anti-obesity function. These findings provide a scientific foundation for the potential therapeutic effect of FH08FS on obesity and associated metabolic diseases.
Evaluation of a Novel Potentially Probiotic/Pediococcus acidilactici ORE5 in Lactic Acid Fermentation of Cornelian Cherry Juice: Assessment of Nutritional Properties, Physicochemical Characteristics, and Sensory Attributes
Authors: Mantzourani Ioanna , Daoutidou Maria , Terpou Antonia , Plessas Stavros
Published: December 2024

The present research survey aimed to investigate the effect of a novel, potentially probiotic strain Pediococcus acidilactici ORE5 on the fermentation of Cornelian cherry for 24 h at 30 °C, followed by cold storage for 4 weeks. Two fermentation systems were established, differing in the form of P. acidilactici ORE5 applied as starter culture of (i) free cells and (ii) immobilized cells in delignified wheat bran. A high lactic acid fermentation rate was recorded, especially in the case of immobilized cell application, since lactic acid levels were determined at 184.8 mg/100 mL and acetic acid at 12.7 mg/100 mL. High probiotic load was observed throughout all studied periods, even at the fourth week of cold storage for both fermentation systems (above 8 log cfu/mL). The total phenolics content (TPC) of the fermented juices was high elevated compared to the unfermented one in all studied periods. When immobilized cells were applied, the TPC of the fermented juice attained the highest values (224.4.5–285.1 mg GAE/100 mL) compared to the juice fermented with free cells (204.5–258.4 mg GAE/100 mL) and the unfermented juice (140.5–165.8 mg GAE/100 mL). Improvements in the sensorial features of the fermented juice compared to the unfermented were also recorded during cold storage. Overall, the results of the present research demonstrated that P. acidilactici ORE5 can be successfully applied in lactic acid fermentation of Cornelian cherry juice, leading to a functional product with increased nutritional value, high probiotic load, and improved sensorial features.
The Effect of a Leaf Fertilization Method Using Humic Acids on the Minerality and Chemical Composition of Sauvignon Blanc Wine from the Slovak Wine Region
Authors: Bartkovský Martin , Semjon Boris , Regecová Ivana , Baričičová Viera , Očenáš Peter , Šuľáková Lucia , Marcinčák Slavomír
Published: December 2024

The objective of this study was to analyze the minerals transferred to Sauvignon blanc must and wine as an effect of foliar fertilizer application. The mineral composition was determined via atomic absorption spectroscopy. Experimental leaf and berry samples were examined during the phenological grapevine growth phases. A foliar fertilizer mixture (0.5 L/hL) with humic acids (8.51%) and B (0.031 kg) was applied. It was observed that the application of humic acids and boron significantly influenced the quality of Sauvignon blanc wine samples. During the blooming period, there was a statistically significant increase (p < 0.05) in P, K, and B in the experimental group. The results showed that using HAs and B in foliar fertilizer significantly (p < 0.05) increased the concentration of minerals in the experimental group. However, P and Fe content in the leaves decreased after veraison. After processing the berries in the vinification process, the levels of B in the must (0.71 ± 0.06 mg/kg) and, subsequently, in the wine (0.61 ± 0.06 mg/kg) were significantly (p < 0.05) higher in the experimental group. Data showed that the foliar fertilizer significantly increased the concentration of N (176.24 ± 0.02 mg/L) in the experimental must. These changes were also observed in wine samples. In wine, a statistically significant decrease in Ca (82.86 ± 0.29 mg/kg) was observed.