bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of the Mechanical and Corrosion Resistance of Alloy 625 through Aging Treatments
Authors: Rivolta Barbara , Gerosa Riccardo , Panzeri Davide , Nazim Arsalan
Published: January 2024

In the as-annealed condition, the nickel-based Alloy 625 has excellent mechanical and corrosion properties compared to those of common stainless steels. This peculiarity enables its exploitation in several industrial fields at cryogenic and high temperatures and in the presence of severely corrosive atmospheres. However, in this alloy, when high-temperature plastic deformation processes and heat treatments are not carefully optimized, the occurrence of excessive grain coarsening can irremediably deteriorate the mechanical strength, possibly leading to incompatibility with the standard requirements. Therefore, this research work investigated the possibility of adopting single- and double-aging treatments aimed at improving such strength loss. Their optimization involved identifying the best compromise between the hardening effect and the loss in corrosion resistance induced by the simultaneous formation of intergranular chromium-rich carbides during aging. The investigation of the aging treatments was performed using hardness, tensile and intergranular corrosion tests considering different time–temperature combinations in a range from 621 °C to 732 °C. Double aging resulted in a considerable acceleration in the hardening response compared to single aging. However, even after its optimization in terms of both temperature and time, the intergranular corrosion resistance remained a critical aspect. Among all the tested conditions, only single aging at 621 °C for 72 h was acceptable in terms of both mechanical and corrosion properties. The influence of longer exposures will be investigated in a future study.
Synthesis, Crystal Structure, and Electrochemistry of Mono- and Bis-Homoannular Ferrocene Derivatives
Authors: Pokharel Uttam R. , Daigle Derek P. , Naquin Stone D. , Engeron Gwyneth S. , Lo Mary A. , Fronczek Frank R.
Published: January 2024

Two ferrocene derivatives, namely, 1,2-(tetramethylene)-ferrocene and 1,2,1′,2′-bis(tetramethylene)-ferrocene, were synthesized in a four-step reaction sequence starting from ferrocene. Friedel–Crafts acylation of ferrocene using succinic anhydride gave mono- or bis(3-carboxypropinoyl)-ferrocene depending on the stoichiometry of succinic anhydride. The reduction of the keto groups to methylene followed by ring-closing using trifluoroacetic anhydride gave 1,2-(α-ketotetramethylene)-ferrocene or 1,2,1′,2′-bis(α-ketotetramethylene)-ferrocene. The diastereomeric mixture of the latter diketones was separated using column chromatography, characterized via single-crystal X-ray analysis, and assigned its stereochemistry. Reduction of the keto groups to methylene under Clemmensen conditions gave homoannular mono- or bis(tetramethylene)-ferrocene derivatives. The molecular structure of 1,2-(tetramethylene)-ferrocene revealed that the ipso carbon atoms of the cyclopentadienyl group are 0.023(3) Å farther away from Fe(II) compared to the remaining three carbon atoms. Both complexes exhibit lower half-wave oxidation potentials than ferrocene, possibly due to the electron-releasing effects of the tetramethylene bridges.
Novel Four-Way Variant Translocation, t(1;9;22;16)(q21;q34;q11.2;q24), in a Patient with Chronic Myeloid Leukemia
Authors: Son Han Joon , Lee Jong Ho
Published: January 2024

Chronic myeloid leukemia (CML) is characterized by the Philadelphia (Ph) chromosome resulting from the translocation of t(9;22)(q34;q11), producing the BCR::ABL1 fusion gene. Variant Ph chromosome translocations, involving rearrangements in chromosomes other than 9 and 22, occur in 5–10% of CML cases. Herein, we report a unique case of a 36-year-old male with a four-way variant Ph chromosome. Conventional chromosomal analysis performed on bone marrow aspirate samples showed 46, XY, t(1;9;22;16)(q21;q34;q11.2;q24). Nested RT-PCR of the BCR::ABL1 gene revealed a major BCR::ABL rearrangement. The treatment with nilotinib achieved a complete hematologic, cytogenetic, and molecular response after 12 months.
Intestinal Obstruction as Initial Presentation of Idiopathic Portal and Mesenteric Venous Thrombosis: Diagnosis, Management, and Literature Review
Authors: Stancu Bogdan , Chira Alexandra , Coman Horațiu F. , Mihaileanu Florin V. , Ciocan Razvan , Gherman Claudia D. , Andercou Octavian A.
Published: January 2024

It is quite common for portal vein thrombosis to occur in subjects who present predisposing conditions such as cirrhosis, hepatobiliary malignancies, infectious or inflammatory abdominal diseases, or hematologic disorders. The incidence of idiopathic portal vein thrombosis in non-cirrhotic patients remains low, and despite the intensive workup that is performed in these cases, in up to 25% of cases, there is no identifiable cause. If portal vein thrombosis is untreated, complications arise and include portal hypertension, cavernous transformation of the portal vein, gastroesophageal and even small intestinal varices, septic thrombosis, or intestinal ischemia. However, intestinal ischemia develops as a consequence of arterial thrombosis or embolism, and the thrombosis of the mesenteric vein accounts for about 10% of cases of intestinal ischemia. Although acute superior mesenteric vein thrombosis can cause acute intestinal ischemia, its chronic form is less likely to cause acute intestinal ischemia, considering the possibility of developing collateral drainage. Ileus due to mesenteric venous thrombosis is rare, and only a small number of cases have been reported to date. Most patients experience a distinct episode of acute abdominal pain due to ischemia, and in the second phase, they develop an obstruction/ileus. Acute superior mesenteric venous thrombosis is a rare condition that is still associated with a high mortality rate. The management of such cases of superior mesenteric venous thrombosis is clinically challenging due to their insidious onset and rapid development. A prompt and accurate diagnosis followed by a timely surgical treatment is important to save patient lives, improve the patient survival rate, and conserve as much of the patient’s bowel as possible, thus leading to fewer sequelae.
Incremental Coding for Real-Time Remote Control over Bandwidth-Limited Channels and Its Applications in Smart Grids
Authors: Qiu Yiyu , Wu Junjie , Chen Wei
Published: January 2024

Remote control over communication networks with bandwidth-constrained channels has attracted considerable recent attention because it holds the promise of enabling a large number of real-time applications, such as autonomous driving, smart grids, and the industrial internet of things (IIoT). However, due to the limited bandwidth, the sub-packets or even bits have to be transmitted successively, thereby experiencing non-negligible latency and inducing serious performance loss in remote control. To overcome this, we introduce an incremental coding method, in which the actuator acts in real time based on a partially received packet instead of waiting until the entire packet is decoded. On this basis, we applied incremental coding to a linear control system to obtain a remote-control scheme. Both its stability conditions and average linear-quadratic-Gaussian-(LQG) cost are presented. Then, we further investigated a multi-user remote-control method, with a particular focus on its applications in the demand response of smart grids over bandwidth-constrained communication networks. The utility loss due to the bandwidth constraint and communication latency are minimized by jointly optimizing the source coding and real-time demand response. The numerical results show that the incremental-coding-aided remote control performed well in both single-user and multi-user scenarios and outperformed the conventional zero-hold control scheme significantly under the LQG metric.
Academic Third Mission through Community Engagement: An Empirical Study in European Universities
Authors: Spânu Paulina , Ulmeanu Mihaela-Elena , Doicin Cristian-Vasile
Published: January 2024

Community engagement is fundamental for tertiary education, as it allows universities to connect with external stakeholders, create social impact, and improve the development of strategies for public engagement. The current study aims to evaluate the level of community engagement in tertiary education, assess the level of sustainable practices, and identify areas for improvement. The research employed a survey method, using a standardized questionnaire to gather data from 44 respondents, representing 35 European universities from nine countries. The survey covered various aspects of community engagement, such as university commitment, documentation, public awareness, investments, incentives, training, and stakeholder engagement. Quantitative analysis was employed using ANOVA and AHP to analyze the data collected from 20 questions. The results revealed that universities have a clear commitment to public engagement and have well-documented policies in place. However, there were areas identified for improvement, such as increasing investments to encourage public engagement and offering more training activities to support it. Additionally, the universities were found to have a limited target group for their community engagement activities and insufficient communication of the results of impact assessments. The findings of this study will be used to improve the development of strategies and enhance public engagement in tertiary education through the Academic Third Mission.
Techno-Economic Assessment of Solar–Grid–Battery Hybrid Energy Systems for Grid-Connected University Campuses in Kenya
Authors: Katche Musong L. , Makokha Augustine B. , Zachary Siagi O. , Adaramola Muyiwa S.
Published: January 2024

This paper presents the techno-economic feasibility of using grid-connected PV hybrid systems to supply power in large grid-dependent academic institutions. The study was conducted using the administration building of Moi University in Kenya. The power consumption profile of the building was collected using a PCE-360 power analyzer. The peak load demand was found to be 60 kW. Using random variability constants of 4% for day-to-day and 4% time-step load variability, a peak demand of 70.58 kW was obtained, which was used in our simulation. The solar radiation and temperature data for this site were collected from the weather station of the university. The hybrid system was simulated using HOMER Pro software. It was found from the simulation results that the optimal system was the solar PV/grid without battery storage, which had a levelized cost of energy (LCOE) of KSH 8.78/kWh (USD 0.072), net present cost (NPC) of KSH 27,974,492 (USD 230,813), capital expenditure (CAPEX) of KSH 26,300,000 (USD 216,997), and a simple payback period (SPBP) of 5.08 years for a 25-year life span. This system, when compared to the existing grid, showed an 83.94% reduction in the annual electricity bill of the administration building. These results demonstrate a reduction in energy cost by a renewable energy fraction of 67.1%.
FedScrap: Layer-Wise Personalized Federated Learning for Scrap Detection
Authors: Zhang Weidong , Deng Dongshang , Wang Lidong
Published: January 2024

Scrap steel inspection is a critical entry point for connecting the smelting process to the industrial internet, with its security and privacy being of vital importance. Current advancements in scrap steel inspection involve collecting scattered data through the industrial internet, then utilizing them to train machine learning models for distributed classification. However, this detection method exposes original scrap steel data directly to the industrial internet, making it susceptible to interception by attackers, who can potentially obtain sensitive information. This paper presents a layer-wise personalized federated framework for scrap steel detection, termed FedScrap, which leverages federated learning (FL) to coordinate decentralized and heterogeneous scrap steel data while ensuring data privacy protection. The key challenge that FedScrap confronts is the heterogeneity of scrap steel data distributed across the network, which complicates the task of effectively integrating these data into a single detection model constructed via FL. To address this challenge, FedScrap employs a self-attention mechanism to aggregate personalized models for each layer of every client, focusing on the most relevant models to their specific data. By assigning higher attention scores to more relevant models, it achieves more accurate aggregation weights during the model aggregation process. To validate the efficacy of the proposed method, a dataset of scrap images was collected from a steel mill, and the results demonstrate that FedScrap achieves accurate classification of distributed scrap data with an impressive accuracy rate of 90%.
Efficient EM Scattering Modeling from Metal Targets Coated with Anisotropic Thin Layers
Authors: Hua Mengbo , He Siyuan
Published: January 2024

To address the challenges posed by composite targets composed of an anisotropic medium and metal in electromagnetic (EM) scattering calculations, this paper introduces an innovative hybrid algorithm tailored for simulating the EM scattering characteristics of such complex targets. Utilizing impedance boundary condition (IBC), the method employs surface impedance vectors to precisely depict the EM properties of the medium. By harnessing the distinct advantages of the Method of Moments (MoMs) at low frequency and Physical Optics (POs) at high frequency, the algorithm ensures both accuracy and efficiency in the EM simulation of composite targets. By transforming the EM scattering problem of targets coated with a thin-layered medium into an equivalent radiation problem of EM currents on impedance surfaces, this research has achieved rapid and high-precision calculations of the Radar Cross Section (RCS) for complex targets with anisotropic medium coatings. To assess the performance of the algorithm, three target models—square plates, simplified aircraft, and complex satellites—are selected as test cases. The dual metrics of RCS and surface current distribution are utilized as evaluation benchmarks, and comparisons are made against the Method of Moments–Finite Element Method (MoM-FEM) hybrid numerical method. The comparative results demonstrate that the proposed method meets the engineering standards in terms of both the root mean square error (RMSE) of RCS and the relative error in surface current distribution, while also achieving a significant improvement of over 50% in computational efficiency, thereby validating its superior accuracy and practical utility.
Multi-Objective Prediction of the Sound Insulation Performance of a Vehicle Body System Using Multiple Kernel Learning–Support Vector Regression
Authors: Sun Ping , Dai Ruxue , Li Haiqing , Zheng Zhiwei , Wu Yudong , Huang Haibo
Published: January 2024

The sound insulation performance of an electric vehicle’s body system serves as a critical metric for evaluating the noise, vibration, and harshness (NVH) quality of the vehicle. The accurate and efficient prediction of sound insulation performance is foundational for undertaking noise reduction design and optimization. Current engineering practices predominantly rely on Computer-Aided Engineering (CAE) methodologies to address this challenge. However, inherent shortcomings such as low modeling efficiency and difficulty in ensuring prediction accuracy often characterize these approaches. In an effort to overcome these limitations, we propose a decomposition framework for predicting the sound insulation performance of the electric vehicle body system. This framework is established based on a comprehensive analysis of the noise transmission paths within the system. Subsequently, the support vector regression (SVR) method is introduced to construct a machine learning model specifically designed for predicting the sound insulation performance of the body system. This approach aims to mitigate the inherent weaknesses associated with the conventional CAE processes using a ‘data-driven’ paradigm. Furthermore, the Multiple Kernel Learning (MKL) method is used to enhance the processing efficacy of the SVR model. The proposed method is validated using practical application and testing on a specific electric vehicle. The results demonstrate commendable performance in terms of prediction accuracy and robustness. This research contributes to advancing the field by presenting a more effective and reliable approach to predicting the sound insulation performance of electric vehicle body systems, offering valuable insights for noise reduction strategies and optimization efforts in the automotive industry.
Development of an Automated Moderator for Deliberative Events
Authors: Bonechi Simone
Published: January 2024

Online communication platforms have revolutionized interpersonal interactions by transcending geographical barriers. While facilitating connectivity, these platforms have introduced challenges such as overcoming linguistic differences and preventing spam and offensive content diffusion. This is particularly pertinent in the context of deliberative events, where online platforms could be used to extend the inclusion of citizens in democratic decision-making. In traditional deliberative events, human moderators and translators were used to facilitate conversation; however, the need for these figures imposed a limit on both the number of deliberative events that could be organized and the number of participants. In response, this paper proposes an automated moderator for deliberative events. The moderator is developed in Python for the online communication platform Discord and can be used, thanks to the integrated AI (Artificial Intelligence) tools, to automatically manage conversation agendas, prevent spam and inappropriate language, analyze the sentiment of the conversation, and translate messages into multiple languages. In particular, three classifiers, based on a pre-trained BERT (Bidirection Encoder Representations from Transformers), were fine-tuned for spam detection, toxic comments classification, and sentiment analysis. These allow the moderator to automatically detect and remove spam and offensive messages in different languages, send warnings to users, alert administrators, and, after repeated warnings, impose bans. Additionally, a built-in translator, based on Meta’s No Language Left Behind NLLB model, translates messages into five languages (Italian, English, French, German, and Polish). The developed bot was tested in a simulated deliberative event on a Discord server, demonstrating its ability to manage conversations and prevent linguistic abuse.
A Novel Three-Dimensional Sigma–Delta Modulation for High-Switching-Frequency Three-Phase Four-Wire Active Power Filters
Authors: Lumbreras David , Zaragoza Jordi , Lamich Manel , Berbel Néstor , Romero-Cadaval Enrique
Published: January 2024

This article presents a new modulation technique called three-dimensional sigma–delta (3D-ΣΔ) modulation for high-frequency three-leg four-wire voltage source converters (VSCs) that use wide-bandgap (WBG) semiconductors. These WBG devices allow for the use of high switching frequencies with a greater efficiency than silicon devices. The proposed 3D-ΣΔ technique enables operation at a variable switching frequency, resulting in a significant reduction in switching losses compared to classical pulse-width modulation (PWM) techniques. Moreover, the 3D-ΣΔ technique uses a fast-processing 3D quantiser that simplifies implementation and considerably reduces computational costs. The behaviour of the 3D-ΣΔ modulation is analysed using MATLAB/Simulink and PLECS. The experimental results performed on an active power filter that uses silicon carbide (SiC) MOSFETs demonstrate an improvement in converter efficiency compared to the conventional SPWM technique. Additionally, the experimental results show how 3D-ΣΔ allows for the compensation of harmonics and homopolar currents, thereby balancing the electrical grid currents. The experiments also show that the proposed 3D-ΣΔ modulation outperforms an SPWM technique in terms of power quality, since the former achieves a larger reduction in the harmonic content of the power grid. In conclusion, the proposed modulation technique is an attractive option for improving the performance of four-wire converters in active power filter applications.
Analysis of Minimal Channel Electroencephalography for Wearable Brain–Computer Interface
Authors: Suwannarat Arpa , Pan-ngum Setha , Israsena Pasin
Published: January 2024

Electroencephalography (EEG)-based brain—computer interface (BCI) is a non-invasive technology with potential in various healthcare applications, including stroke rehabilitation and neuro-feedback training. These applications typically require multi-channel EEG. However, setting up a multi-channel EEG headset is time-consuming, potentially resulting in patient reluctance to use the system despite its potential benefits. Therefore, we investigated the appropriate number of electrodes required for a successful BCI application in wearable devices using various numbers of EEG channels. EEG multi-frequency features were extracted using the “filter bank” feature extraction technique. A support vector machine (SVM) was used to classify a left/right-hand opening/closing motor imagery (MI) task. Nine electrodes around the center of the scalp (F3, Fz, F4, C3, Cz, C4, P3, Pz, and P4) provided high classification accuracy with a moderate setup time; hence, this system was selected as the minimal number of required channels. Spherical spline interpolation (SSI) was also applied to investigate the feasibility of generating EEG signals from limited channels on an EEG headset. We found classification accuracies of interpolated groups only, and combined interpolated and collected groups were significantly lower than the measured groups. The results indicate that SSI may not provide additional EEG data to improve classification accuracy of the collected minimal channels. The conclusion is that other techniques could be explored or a sufficient number of EEG channels must be collected without relying on generated data. Our proposed method, which uses a filter bank feature, session-dependent training, and the exploration of many groups of EEG channels, offers the possibility of developing a successful BCI application using minimal channels on an EEG device.
Development of Software for 3D Well Visualization Modeling Using Acoustic, Gamma, Neutron and Density Logging for Fossil Energy Sources Sustainable Production
Authors: Abu-Abed Fares , Pivovarov Kirill , Zhironkin Sergey
Published: January 2024

Achieving the UN Sustainable Development Goals is impossible without sustainable oil and gas production, both in terms of ensuring equal access to cheap energy and preserving the environment, as well as caring for non-renewable fossil energy sources. This actualizes the need for the digital 3D modeling of wells, which allows one to assess their current condition and predict their future condition as well as determine the feasibility of investing in their reconstruction and the expansion of the well network. This is possible due to the fact that the visualization of a well, reflecting its physical and technical parameters, gives engineers, designers and ecologists the opportunity to recognize the defects of the well (cracks, cavities, behind casing and interlayer leaks, etc.) and predict their appearance and proliferation on which the service life, hydrocarbon flow rate, pollution, operating and capital costs directly depend. The software required for this must be versatile enough to cover different types of logging and fit different operating systems. The goal of the study is to develop a software for creating visual 3D models of wells based on acoustic and various types of radioactive logging data, capable of integrating drilling rig parameters and geophysical survey data with modern 3D modeling and programming methods. The developed software meets the requirements of various operating systems and the specifics of different types of logging, which is designed to help in increasing the productivity of oil and gas wells, save energy consumption and reduce groundwater pollution from chemicals used in hydrocarbon production. This is achievable by ensuring trouble-free execution and the operation of well systems, minimizing the risks of collapses and the destruction of well walls through accurate monitoring and forecasting their dynamic condition in real time using 3D models, which is not available for static 2D models.
Production of Coconut Oil Bioturbosine without Water by Using Ultrasound as a Source of Energy and Ion Exchange for Its Purification
Authors: Esquerre Verastegui Jorge Eduardo , López López Andres , González Domínguez Roberto Adrián , Zamora Antuñano Marco Antonio , Dávila Ignacio Carlos Vidal , García García Raúl
Published: January 2024

Jet fuel production is a key element in the aviation industry’s strategy to reduce operating costs and environmental impacts. Alternatives are required, and bioturbosine obtained from biomass can replace significant amounts of jet fuel. In this investigation, the properties of the production of bioturbosine from coconut oil and mixtures of B5, B10, B20, B1OO, bottom, and jet fuel were measured according to the ASTM standards. A transesterification reaction between coconut oil and methanol was carried out using ultrasound, resulting in 99.93% conversion of triglycerides into bioturbosine at room temperature for 10 min, with a 6:1 molar ratio of methanol and oil. The catalyst concentration was 1.0 g/100 g of oil, and purification was carried out without water using an ion-exchange resin to remove impurities. The results obtained for density and viscosity were within the regulations. The temperature of the clogging point for a cold filter in the mixtures was up to −30 °C. The average caloric values of mixtures B5, B10, and B20 were 45,042, 44,546, and 43,611 MJ/Kg, respectively. In a copper corrosion test, the result for all samples was class 1A. It is expected that the results of this research may influence the use of bioturbosine in the aviation industry.
Comprehensive Modulation Strategies for Synchronous Reluctance Motor Drives Used in Weak Grids
Authors: Wang Shuo , Prystupa Dmytro , Bao Yuli , Varvolik Vasyl , Buticchi Giampaolo , Zhang He , Degano Michele
Published: January 2024

Synchronous reluctance machines are considered a cost-effective solution for several industrial applications and present potential efficiency benefits compared to induction motors. In industrial applications, power supply oscillations can lead to short-term disturbances that can affect the drive operation; therefore, the control must be robust to guarantee high efficiency and service continuity. The focus of this study was to identify the speed boundaries considering different values of applied DC-link voltage, taking into account the highly nonlinear magnetic behavior of the machine and its cross-coupling characteristics. In addition, a comprehensive carrier-based implementation of a pulse width modulation strategy was proposed to achieve optimal efficiency in both the machine and converter, which is essential in the presence of “weak” grids. The proposed technique was demonstrated to meet the desired reference torque and rated speed, even during DC-link voltage drops (up to 7.4% of the rated voltage). The proposed methodology was experimentally validated on a 90 kW SynRM drive with a broader modulation range and higher efficiency. This work considered several different supply voltage levels to assess the stability and continuity of torque output and further proved the proposed method.
Waste to H2 Sustainable Processes: A Review on H2S Valorization Technologies
Authors: Spatolisano Elvira , Restelli Federica , Pellegrini Laura A. , de Angelis Alberto R.
Published: January 2024

In the energy transition from fossil fuels to renewables, the tendency is to benefit from ultra-sour natural gas reserves, whose monetization was previously considered unviable. The increasing H2S content together with the growing concern about emissions that are harmful to the environment, make necessary the development of efficient strategies for pollutants management. Although large-scale H2S conversion is well-established through the Claus process, novel technologies for H2S valorization could be a reliable alternative for waste-to-valuable chemicals, following the circular economy. In this perspective, technologies such as Hydrogen Sulfide Methane Reformation (H2SMR), non-thermal plasma, photocatalytic decomposition, decomposition through cycles and electrolysis are analyzed for the H2 production from H2S. They represent promising alternatives for the simultaneous H2S valorization and H2 production, without direct CO2 emissions, as opposite to the traditional methane steam reforming. The various H2S conversion routes to H2 are examined, highlighting the advantages and disadvantages of each of them. This review focuses in particular on the most promising technologies, the H2SMR and the non-thermal plasma, for which preliminary process scheme and techno-economic analysis are also reported. Finally, the major research gaps and future developments necessary to unlock the full potential of hydrogen sulfide valorization as a sustainable pathway for hydrogen production are discussed.
Age Estimation of Transmission Line Using Statistical Health Index and Failure Probability Curve-Fitting Method
Authors: Suwanasri Cattareeya , Yongyee Ittiphong , Suwanasri Thanapong
Published: January 2024

The aging process of transmission lines has a direct impact on the reliability and safety of the power grid. Therefore, an accurate age estimation method is imperative for effective maintenance planning and infrastructure investment. This paper introduces a systematic methodology for estimating the age of overhead transmission lines, utilizing the percentage statistical health index (%SHI) and the failure probability curve-fitting (FPCF) method. The %SHI, employing a scoring and weighting approach derived from test results and inspections, is used to assess the actual condition of transmission line equipment. Additionally, the FPCF approach is applied to illustrate the connection between the SHI and the likelihood of failure, facilitating the assessment of transmission line age by fitting failure probability curves to the SHI data. This age is directly associated with the probability of experiencing a failure. The evaluation was conducted on 924 towers situated along four transmission lines connecting the 115 kV substations S1–S2, S3–S4, S5–S6, and S7–S8. These transmission lines are in four regions with diverse terrain and environments such as mountains, rice fields, and more. In the SHI calculation, practical testing results and historical failure data were applied. The results clearly indicate that there were notable disparities in the age estimations for transmission lines in diverse geographical regions of Thailand when compared to their actual ages. These discrepancies can be attributed to various factors, including the local environment, such as rainfall, flooding, and salt-laden air as well as specific geographical features like mountainous and coastal terrain. To mitigate the deterioration of transmission lines in all regions, it is essential to implement a proactive maintenance strategy. This strategy should involve more frequent inspections, the use of advanced monitoring technologies, and the establishment of robust maintenance procedures, with which it would become possible to enhance the accuracy of equipment condition assessments, ultimately resulting in an overall improvement in the reliability of transmission lines.
A Comprehensive Review on Voltage Stability in Wind-Integrated Power Systems
Authors: Malik Farhan , Khan Muhammad , Rahman Tauheed , Ehtisham Muhammad , Faheem Muhammad , Haider Zunaib , Lehtonen Matti
Published: January 2024

The fast growth of the world’s energy demand in the modernized world has stirred many countries around the globe to focus on power generation by abundantly available renewable energy resources. Among them, wind energy has attained significant attention owing to its environment-friendly nature along with other fabulous advantages. However, wind-integrated power systems experience numerous voltage instability complexities due to the sporadic nature of wind. This paper comprehensively reviews the problems of voltage instability in wind-integrated power systems, its causes, consequences, improvement techniques, and implication of grid codes to keep the operation of the network secure. Thorough understanding of the underlying issues related to voltage instability is necessary for the development of effective mitigation techniques in order to facilitate wind integration into power systems. Therefore, this review delves into the origin and consequences of voltage instability, emphasizing its adverse impacts on the performance and reliability of power systems. Moreover, it sheds light on the challenges of integrating wind energy with existing grids. This manuscript provides a comprehensive overview of the essential features required for critical analysis through a detailed examination of Voltage Stability Indices (VSIs). To address voltage stability issues in wind-integrated power systems, this review examines diverse techniques proposed by researchers, encompassing the tools utilized for assessment and mitigation. Therefore, in the field of power system operation and renewable energy integration, this manuscript serves as a valuable resource for researchers by comprehensively addressing the complexities and challenges associated with voltage instability in wind-integrated power systems.
Anti-Freezing Study of High-Level Water-Collecting Natural Draft Wet-Cooling Tower Based on Its Water Temperature Distribution Characteristics
Authors: Wang Zhonghua , Yue Zenggang , Wang Wei , Ma Chenghui , Li Xiaoguang , Guo Changmin , Zhao Yuanbin
Published: January 2024

Thermal power units play a crucial role in the deep peak regulation of power generation. During deep peak regulation, the load of the unit changes significantly, causing fluctuations in the inlet water temperature of the cooling tower and the water temperature in the filler. Therefore, in cold regions in winter, cooling towers have a high risk of freezing, which threatens the economic and safe operation of the unit. This paper establishes a three-dimensional numerical model based on constant heat dissipation and explores the average and minimum water temperatures at the bottom of filler under different water distribution methods, crosswind velocities, and ambient temperatures. The results show that the water distribution method has a significant impact on the water temperature at the filler bottom. Reducing the water distribution area can significantly increase the minimum water temperature at the filler bottom and reduce the risk of freezing. Although the presence of crosswind is not conducive to the cooling performance of the cooling tower, the higher the crosswind velocity, the higher the minimum outlet water temperature at the filler bottom and the lower the risk of freezing. The minimum water temperature at the filler bottom is approximately linearly related to the ambient temperature and is less affected by the unit load at the same temperature.
Myopia, Sodium Chloride, and Vitreous Fluid Imbalance: A Nutritional Epidemiology Perspective
Authors: Brown Ronald B.
Published: January 2024

Theories of myopia etiology based on near work and lack of outdoor exposure have had inconsistent support and have not prevented the rising prevalence of global myopia. New scientific theories in the cause and prevention of myopia are needed. Myopia prevalence is low in native people consuming traditional diets lacking in sodium chloride, and nutritional epidemiological evidence supports the association of rising myopia prevalence with dietary sodium intake. East Asian populations have among the highest rates of myopia associated with high dietary sodium. Similar associations of sodium and rising myopia prevalence were observed in the United States in the late 20th century. The present perspective synthesizes nutritional epidemiology evidence with pathophysiological concepts and proposes that axial myopia occurs from increased fluid retention in the vitreous of the eye, induced by dietary sodium chloride intake. Salt disturbs ionic permeability of retinal membranes, increases the osmotic gradient flow of fluid into the vitreous, and stretches ocular tissue during axial elongation. Based on the present nutritional epidemiology evidence, experimental research should investigate the effect of sodium chloride as the cause of myopia, and clinical research should test a very low-salt diet in myopia correction and prevention.
Exploring the Potential of Roadside Plantation for Carbon Sequestration Using Simulation in Southern Quebec, Canada
Authors: Srour Nour , Thiffault Evelyne , Boucher Jean-François
Published: January 2024

Afforestation of urban lands can play an important role in increasing carbon sequestration and mitigating the effects of climate change. This study aimed to evaluate the potential for carbon sequestration and storage in plantations on roadsides in southern Quebec, Canada. We used the Carbon Budget Model of the Canadian Forester Sector 3 (CBM-CFS3) to simulate the carbon sequestration capacity over 100 years of plantations established following afforestation with different species mixtures based on local needs and aspirations. We then compared the carbon sequestration potential of simulated plantations with the carbon storage of natural vegetation of reference roadsides with different histories of land use. Our findings suggested that plantations on roadsides subjected to high anthropogenic pressure, such as road rights-of-way, may provide carbon sequestration benefits relative to baseline conditions (i.e., no plantation). For instance, 15 years after afforestation, the additional carbon sequestration potential of plantations on road rights-of-way varied between 25 and 32 Mg ha−1, depending on the afforestation scenario. However, allowing roadsides classified as abandoned agricultural lands to undergo natural succession could promote higher carbon storage on roadsides than planting, irrespective of species mixtures. Our results indicated that the carbon storage of vegetation resulting from the abandonment of agriculture 35 to 45 years ago showed a range of 260 to 290 Mg ha−1, which exceeded the carbon stocks predicted with afforestation models for 60 to 84 years after planting. Indeed, reference roadsides used for agriculture in the past, but that have otherwise not been subjected to other anthropogenic degradation, appeared to naturally evolve toward forest vegetation with higher carbon stocks than simulated plantations.
Intention to Hack? Applying the Theory of Planned Behaviour to Youth Criminal Hacking
Authors: Aiken Mary P. , Davidson Julia C. , Walrave Michel , Ponnet Koen S. , Phillips Kirsty , Farr Ruby R.
Published: January 2024

Adolescents are currently the most digitally connected generation in history. There is an ever-growing need to understand how typical adolescent risk-taking intersects with the vastly criminogenic potential of digital technology. Criminal hacking in older adolescents (16–19-year-olds) was assessed using an adapted Theory of Planned Behaviour (TPB) model, a cohesive theoretical framework that incorporates cognitive processes and human drivers (informed by psychology, cyberpsychology, and criminology theory). In 2021, a large-scale anonymous online survey was conducted across nine European countries. Criminal hacking was assessed using data from 3985 participants (M = 1895, 47.55%; F = 1968, 49.39%). This study formulated a powerful predictive model of youth hacking intention (accounting for 38.8% of the variance) and behaviour (accounting for 33.6% of the variance). A significant minority, approximately one in six (16.34%), were found to have engaged in hacking, and approximately 2% reported engaging in hacking often or very often. Increased age, being male, and offline deviant behaviour were significant predictors of hacking behaviour. In line with the TPB, intention was the strongest individual predictor of hacking behaviour, which in turn was significantly predicted by cognitive processes accounted for by TPB constructs: subjective norms of family and peers, attitudes towards hacking, and perceived behavioural control. These TPB constructs were found to be significantly associated with human factors of risk-taking, toxic online disinhibition, offline deviant behaviour, and demographic variables of age and gender. Implications for future research, interventions, policy, and practice are discussed.
Bifurcation Analysis of Time-Delayed Non-Commensurate Caputo Fractional Bi-Directional Associative Memory Neural Networks Composed of Three Neurons
Authors: Wang Chengqiang , Zhao Xiangqing , Mai Qiuyue , Lv Zhiwei
Published: January 2024

We are concerned in this paper with the stability and bifurcation problems for three-neuron-based bi-directional associative memory neural networks that are involved with time delays in transmission terms and possess Caputo fractional derivatives of non-commensurate orders. For the fractional bi-directional associative memory neural networks that are dealt with in this paper, we view the time delays as the bifurcation parameters. Via a standard contraction mapping argument, we establish the existence and uniqueness of the state trajectories of the investigated fractional bi-directional associative memory neural networks. By utilizing the idea and technique of linearization, we analyze the influence of time delays on the dynamical behavior of the investigated neural networks, as well as establish and prove several stability/bifurcation criteria for the neural networks dealt with in this paper. According to each of our established criteria, the equilibrium states of the investigated fractional bi-directional associative memory neural networks are asymptotically stable when some of the time delays are less than strictly specific positive constants, i.e., when the thresholds or the bifurcation points undergo Hopf bifurcation in the concerned networks at the aforementioned threshold constants. In the meantime, we provide several illustrative examples to numerically and visually validate our stability and bifurcation results. Our stability and bifurcation theoretical results in this paper yield some insights into the cause mechanism of the bifurcation phenomena for some other complex phenomena, and this is extremely helpful for the design of feedback control to attenuate or even to remove such complex phenomena in the dynamics of fractional bi-directional associative memory neural networks with time delays.
A Bound-Preserving Numerical Scheme for Space–Time Fractional Advection Equations
Authors: Gao Jing , Chen Huaiguang
Published: January 2024

We develop and analyze an explicit finite difference scheme that satisfies a bound-preserving principle for space–time fractional advection equations with the orders of 0<α and β≤1. The stability (and convergence) of the method is discussed. Due to the nonlocal property of the fractional operators, the numerical method generates dense coefficient matrices with complex structures. In order to increase the effectiveness of the method, we use Toeplitz-like structures in the full coefficient matrix in a sparse form to reduce the costs of computation, and we also apply a fast evaluation method for the time–fractional derivative. Therefore, an efficient solver is constructed. Numerical experiments are provided for the utility of the method.
Identification of Volatile Compounds and Terpene Synthase (TPS) Genes Reveals ZcTPS02 Involved in β-Ocimene Biosynthesis in Zephyranthes candida
Authors: Wei Guo , Xu Yang , Xu Mengmeng , Shi Xinwei , Wang Jianwen , Feng Liguo
Published: January 2024

Zephyranthes candida is a frequently cultivated ornamental plant containing several secondary metabolites, including alkaloids, flavonoids, and volatile organic compounds (VOCs). However, extensive research has been conducted only on non-VOCs found in the plant, whereas the production of VOCs and the molecular mechanisms underlying the biosynthesis of terpenes remain poorly understood. In this study, 17 volatile compounds were identified from Z. candida flowers using gas chromatography–mass spectrometry (GC-MS), with 16 of them being terpenoids. Transcriptome sequencing resulted in the identification of 17 terpene synthase (TPS) genes; two TPS genes, ZcTPS01 and ZcTPS02, had high expression levels. Biochemical characterization of two enzymes encoded by both genes revealed that ZcTPS02 can catalyze geranyl diphosphate (GPP) into diverse products, among which is β-ocimene, which is the second most abundant compound found in Z. candida flowers. These results suggest that ZcTPS02 plays a vital role in β-ocimene biosynthesis, providing valuable insights into terpene biosynthesis pathways in Z. candida. Furthermore, the expression of ZcTPS02 was upregulated after 2 h of methyl jasmonate (MeJA) treatment and downregulated after 4 h of the same treatment.
Towards Real-Time 3D Terrain Reconstruction from Aerial Imagery
Authors: Wang Qiaosong
Published: January 2024

We present a near real-time solution for 3D reconstruction from aerial images captured by consumer UAVs. Our core idea is to simplify the multi-view stereo problem into a series of two-view stereo matching problems. Our method applies to UAVs equipped with only one camera and does not require special stereo-capturing setups. We found that the neighboring two video frames taken by UAVs flying at a mid-to-high cruising altitude can be approximated as left and right views from a virtual stereo camera. By leveraging GPU-accelerated real-time stereo estimation, efficient PnP correspondence solving algorithms, and an extended Kalman filter, our system simultaneously predicts scene geometry and camera position/orientation from the virtual stereo cameras. Also, this method allows for the user selection of varying baseline lengths, which provides more flexibility given the trade-off between camera resolution, effective measuring distance, flight altitude, and mapping accuracy. Our method outputs dense point clouds at a constant speed of 25 frames per second and is validated on a variety of real-world datasets with satisfactory results.