bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive Model of Paraaortic Lymph Node Involvement in cN0 Locally Advanced Cervical Cancers: PET/CT Technology Matters
Authors: Hotton Judicael , Raimond Emilie , Reyal Fabien , Michel Sophie , Ceccato Vivien , Moubtakir Abdenasser , Papathanassiou Dimitri , Morland David
Published: November 2024

Background: The aim is to propose a model for predicting occult paraaortic lymph node (PALN) involvement in locally advanced cervical cancer (LACC) patients by including parameters such as reconstruction detection technology (use of time-of-flight) and parameters related to the primary tumor. This model will then be compared with the scores used in routine clinical practice; Methods: This retrospective observational cohort study included patients diagnosed with LACC who underwent 18F-FDG PET/CT prior to PALN surgical staging between February 2012 and May 2020. The following parameters were collected on PET/CT: tumor SUVmax, tumor MTV, number of common and distal pelvic node involvements. A multivariate regression analysis estimating the probability of PALN involvement was performed, with optimal thresholds determined via ROC curves; Results: In total, 71 patients met the inclusion criteria. Occult PALN involvement was detected in 12.7% of patients. A derived multivariate PET model selected four variables: number of common and distal iliac lymph nodes (OR 5.9 and 2.7, respectively), tumor-to-liver SUV ratio (OR 0.9) and the use of time-of-flight technology (OR 21.4 if no time-of-flight available). At the optimal threshold, a sensitivity of 77.8% and specificity of 88.7% was found. The model’s performances varied significantly between patients whose PET/CT used time-of-flight and those whose PET/CT did not. No significant differences were found between our model and the one used in clinical practice (p = 0.55); Conclusions: This study shows that PET/CT technology influences the ability to detect occult PALN involvement in LACC. This parameter should be considered in the regular revision of PET-based scores.
“Rosary Sign” at Somatostatin Receptor PET in a Case of Recurrent Meningioma
Authors: Iacovitti Cesare Michele , Bosetti Davide Giovanni , Muoio Barbara , Cuzzocrea Marco , Paone Gaetano , Treglia Giorgio
Published: November 2024

We present the case of a 60-year-old male with recurrent atypical meningioma in the right parietal lobe, previously treated with surgery and radiation therapy. Magnetic resonance imaging (MRI) performed 5 years after radiation therapy suggested a possible recurrence. A somatostatin receptor positron emission tomography/computed tomography (SR-PET/CT) scan with Gallium-68 DOTATATE was performed to confirm this suspicion. SR-PET/CT confirmed the presence of recurrent meningioma, showing a novel “rosary sign” with multiple adjacent areas of focal tracer uptake along the resection margins of the previous surgical site in the right parietal region. This novel imaging pattern improved diagnostic accuracy by detailing disease extent and identifying additional lesions not visible via MRI. Given the failure of prior treatments and high SR expression, peptide receptor radionuclide therapy (PRRT) was proposed as a therapeutic option for the patient.
Session-by-Session Prediction of Anti-Endothelial Growth Factor Injection Needs in Neovascular Age-Related Macular Degeneration Using Optical-Coherence-Tomography-Derived Features and Machine Learning
Authors: Ragni Flavio , Bovo Stefano , Zen Andrea , Sona Diego , De Nadai Katia , Adamo Ginevra Giovanna , Pellegrini Marco , Nasini Francesco , Vivarelli Chiara , Tavolato Marco , Mura Marco , Parmeggiani Francesco , Jurman Giuseppe
Published: November 2024

Background/Objectives: Neovascular age-related macular degeneration (nAMD) is a retinal disorder leading to irreversible central vision loss. The pro-re-nata (PRN) treatment for nAMD involves frequent intravitreal injections of anti-VEGF medications, placing a burden on patients and healthcare systems. Predicting injections needs at each monitoring session could optimize treatment outcomes and reduce unnecessary interventions. Methods: To achieve these aims, machine learning (ML) models were evaluated using different combinations of clinical variables, including retinal thickness and volume, best-corrected visual acuity, and features derived from macular optical coherence tomography (OCT). A “Leave Some Subjects Out” (LSSO) nested cross-validation approach ensured robust evaluation. Moreover, the SHapley Additive exPlanations (SHAP) analysis was employed to quantify the contribution of each feature to model predictions. Results: Results demonstrated that models incorporating both structural and functional features achieved high classification accuracy in predicting injection necessity (AUC = 0.747 ± 0.046, MCC = 0.541 ± 0.073). Moreover, the explainability analysis identified as key predictors both subretinal and intraretinal fluid, alongside central retinal thickness. Conclusions: These findings suggest that session-by-session prediction of injection needs in nAMD patients is feasible, even without processing the entire OCT image. The proposed ML framework has the potential to be integrated into routine clinical workflows, thereby optimizing nAMD therapeutic management.
Thoracic Lymphatic Perfusion Patterns Assessed by Magnetic Resonance Imaging and Late Fontan Failure
Authors: Ortega-Zhindón Diego B. , Meléndez-Ramírez Gabriela , Patrón-Chi Sergio A. , Rivera-Buendía Frida , Calderón-Colmenero Juan , García-Montes José A. , Pérez-Hernández Nonanzit , Rodríguez-Pérez José Manuel , Cervantes-Salazar Jorge L.
Published: November 2024

Background: Fontan circulation maintains an elevated venous pressure; this promotes venous and lymphatic congestion and may lead to late circuit failure. Our objective was to determine the association between thoracic lymphatic perfusion patterns assessed by magnetic resonance imaging and late Fontan failure. Methodology: A retrospective study was performed. We included patients who underwent the Fontan procedure between January 2005 and December 2019 and who were evaluated with lymphatic mapping using magnetic resonance imaging. Lymphatic abnormalities were classified into four types. The prevalence of late failure was determined, and logistic regression analysis was performed to establish the association between the variables of interest and the outcome. Results: Fifty-four patients were included with a mean age at surgery of 8.8 years ± 3.5 years; 42.6% (n = 23) were men. The most frequent diagnosis was tricuspid atresia (50%, n = 27), and the Fontan procedures were mainly performed using an extracardiac conduit (96.3%, n = 52). The prevalence of late Fontan failure was 35.2%. The lymphatic perfusion patterns observed were Type 1 in 25.9% (n = 14), Type 2 in 46.3% (n = 25), Type 3 in 25.9% (n = 14), and Type 4 in 1.8% (n = 1), with no differences in relation to late failure. (p = 0.42). The age at surgery was found to be a factor associated with the late Fontan failure (OR: 1.23; 95% CI: 1.02–1.48; p = 0.02). Conclusions: One-third of patients with Fontan circulation may experience late failure, not significantly associated with lymphatic changes, but when the total cavopulmonary connection is completed at an older age.
Control of a New Financial Risk Contagion Dynamic Model Based on Finite-Time Disturbance
Authors: Wei Yifeng , Xie Chengrong , Qing Xia , Xu Yuhua
Published: November 2024

With the widespread application of chaotic systems in many fields, research on chaotic systems is becoming increasingly in-depth. This article first proposes a new dynamic model of financial risk contagion based on financial principles and discusses some basic dynamic characteristics of the new chaotic system, such as equilibrium points, dissipativity, Poincaré diagrams, bifurcation diagrams, etc. Secondly, with the consideration of privacy during data transmission, the method was designed to protect the privacy of controlled systems in finite time based on perturbation. A controller designed for finite time was developed based on Lyapunov stability principles, which achieves system synchronization within a finite time and protects the privacy of the controlled system. The effectiveness was also verified by numerical simulations.
A Characterization of Optimal Prefix Codes
Authors: Congero Spencer , Zeger Kenneth
Published: November 2024

A property of prefix codes called strong monotonicity is introduced, and it is proven that for a given source, a prefix code is optimal if and only if it is complete and strongly monotone.
A Contemporary View on Carnot’s Réflexions
Authors: Meyn Jan-Peter
Published: November 2024

Entropy and energy had not yet been introduced to physics by the time Carnot wrote his seminal Réflexions. Scholars continue to discuss what he really had in mind and what misconceptions he might have had. Actually, his work can be read as a correct introduction to the physics of heat engines when the term calorique is replaced by entropy and entropy is used as the other fundamental thermal quantity besides temperature. Carnot’s concepts of falling entropy as an analogy to the waterfall, and the separation of real thermal processes into reversible and irreversible processes are adopted. Some details of Carnot’s treatise are ignored, but the principal ideas are quoted and assumed without modification. With only two thermal quantities, temperature and entropy, modern heat engines can be explained in detail. Only after the principal function of heat engines is developed is energy introduced as physical quantity in order to compare thermal engines with mechanical and electrical engines and, specifically, to calculate efficiency.
The Contribution of Linguistic Distance to L3 Learning Motivation: A Cross-L2 Comparison of University English as a Foreign Language Learners
Authors: Wang Xuan , Zhu Yilin
Published: November 2024

In this study, we respond to calls for more research on the motivation to learn a third language (L3), especially regarding how this motivation is influenced by linguistic distance in various second language (L2) contexts. We employed a comparative and mixed-method design to investigate whether L3 learners with a “longer L2–L3 linguistic distance” show significantly different L3 motivational constructs compared with L3 learners with a “shorter L2–L3 linguistic distance”. We recruited sixty university students majoring in English who were enrolled under same program curriculum in China, with half of them selecting French as their L3 and with the other half selecting Japanese. The French L3 group was labeled “shorter L2–L3 linguistic distance”, and the Japanese L3 group was labeled “longer L2–L3 linguistic distance”. We recruited learners from the same Chinese university to complete a Taguchi-based questionnaire on the L3 motivational system. The quantitative results revealed that the ideal L3 self, the ought-to L3 self, family influence and instrumentality promotion were significantly different between these two L3 groups. Qualitative results based on follow-up interviews with four participants showed that shorter L2–L3 linguistic distance contributed to higher instrumentality promotion, and family influence tended to be driven by practical concerns. These findings demonstrate how cross-linguistic factors may impact multilingual learners’ motivation and insights, which may be also of assistance to L3 acquisition and pedagogy.
Supporting the Cultural Identity Development of Indigenous Youth: Findings from an Indigenous Educators’ Community-Of-Practice
Authors: Lunda Angela , Frommherz Amber , Bolton William Gamaas , Cook Chelsee , Dude Barbara , Leask Naomi , Littlefield Roberta , McCarty Jennifer , Puustinen Shawna , Vaska Nastasia
Published: November 2024

Research reveals a positive impact on educational achievement for Indigenous students when their teachers are also Indigenous. The educational value of shared identity between students and teachers manifests in the form of increased student attendance rates, grades, and graduation rates. Fewer than 5% of public-school teachers in Alaska are Indigenous, while nearly 20% of students are Indigenous. Thus, it is unlikely that most Indigenous students in Alaska will experience a shared cultural identity with their teachers—nor would it be desirable, in this age of global mobility, for society to strive for teachers and students to share cultural identity in all instances. Yet it is important to discern what teaching practices and teacher dispositions support the cultural identity development (CID) of Indigenous children. This project brought together Indigenous educators from across Alaska to critically examine their practice as educators and to seek answers to the research question. Utilizing a collaborative autoethnographic framework, qualitative data were coded and analyzed to uncover answers to the research question. Key findings from this study indicate that teaching and using the local Indigenous language, shared cultural history documented in stories, and experiences related to the Land contribute to students’ CID. Furthermore, findings reveal that micro cultural validations, fleeting interactions between teachers and students, play a significant role in supporting the cultural identity development of Indigenous youth. Findings also suggest that Indigenous teachers are best positioned to discern the teaching practices that contribute to students’ cultural identity development.
Toward an Intersectional Leadership Identity Development Approach
Authors: De La Cruz Albizu Pedro J.
Published: November 2024

This paper introduces an intersectional leadership identity development framework to support both the leadership development of aspiring school leaders and the study of educational leadership. By combining aspects and insights from critical sensemaking, role identity, and intersectionality, this framework aims to expand the understanding of the flexible sensemaking of aspiring educational leaders, provide educational leadership preparation programs with necessary insights to better support the increasingly diverse cadre of aspiring leaders, and open new avenues of empirical research and practical application in the study of role identity and its influence on the preparation of successful school leaders.
Modeling of Collusion Behavior in the Electrical Market Based on Deep Deterministic Policy Gradient
Authors: Liu Yifeng , Chen Jingpin , Chen Meng , He Zhongshi , Guo Ye , Li Chenghan
Published: November 2024

The evolution of the electricity market has brought the issues of market equilibrium and collusion to the forefront of attention. This paper introduces the Deep Deterministic Policy Gradient (DDPG) algorithm on the IEEE three-bus electrical market model. Specifically, it simulates the behavior of market participants through reinforcement learning (DDPG), and Nash equilibrium and the collusive equilibrium of the power market are simulated by setting different reward functions. The results show that, compared with the Nash equilibrium, collusion equilibrium can increase the price of nodal marginal electricity and reduce total social welfare.
Analysis of Circuits Supplying Thomson Coil Actuator Operating in Vacuum Contact Units of DC and AC Ultra-Fast Circuit Breakers
Authors: Rodak Michal , Borkowski Piotr
Published: November 2024

The use of vacuum-hybrid DC circuit breaking methods allows the short-circuit current to be switched off in a shorter time, resulting in a reduction in the arc burning time. This requires the use of a drive, such as the Thomson Coil Actuator TCA, capable of providing a short response time for opening the vacuum interrupter VI, regardless of its rated current. The IDD is powered by a pre-charged capacitor, which, together with the drive coil, forms an LC oscillating circuit that, when switched on by a thyristor, generates a current pulse of several kA with a frequency above 1 kHz. The paper investigates the effect of modifying the basic IDD power supply circuit by adding semiconductor diodes to shape the current pulse and improve its performance. The authors also focused on exploring the impact of the connection quality and their length and the associated loss in drive force while proving that a circuit with a reverse diode on the IDD coil is most beneficial and that the effect of the circuit on the front of the current pulse can significantly slow down the drive.
Policy Perspectives of the Renewable Energy Landscape in Cameroon: Status, Drivers, Challenges and Enabling Frameworks
Authors: Ayuketah Yvan , Edimu Milton , Mwikirize Cosmas , Nsanyuy Wirnkar Basil , Ngole Ernest Belle
Published: November 2024

Cameroon, like most countries in sub-Saharan Africa, is grappling with inadequate electricity generation capacity and energy security issues amid an increasing energy demand and the goal to ensure 100% access to electricity and clean cooking for its citizens. The government has identified the uptake of renewable energy technologies (RETs) as instrumental to increasing electricity generation, as well as meeting its Nationally Determined Contributions (NDCs) commitments and overall long-term developmental goals. The nation’s strategies so far have yielded little results due to a combination of factors, ranging from financial to regulatory aspects. This study analyzes the existing renewable energy infrastructure, identifying the motivations and factors that influence the implementation of renewable energy policies and the challenges and barriers faced. It also explores the existing policy frameworks and regulatory mechanisms, provide insights into the policy gaps and suggests enabling mechanisms that will enable a more favorable environment for renewable energy investments and development in Cameroon. Although the policies posited are focused primarily for the energy system of Cameroon, they can be extended to sub-Saharan African countries and in the global context, provided that local conditions are accounted for. Adopting the recommended policy frameworks will stimulate, support and ensure the sustained development and deployment of renewable energy technologies in the nation and in the subregion.
Multi-Scale Graph Attention Network Based on Encoding Decomposition for Electricity Consumption Prediction
Authors: Huang Sheng , Que Huakun , Zeng Lukun , Yang Jingxu , Zheng Kaihong
Published: November 2024

Accurate electricity consumption forecasting is essential for power scheduling. In short-term forecasting, electricity consumption data exhibit periodic patterns, as well as fluctuations associated with production events. Traditional forecasting methods typically focus on sequential features of the data, which may lead to an over-smoothing issue for the fluctuations. In practice, the fluctuations of electricity consumption associated with these events tend to follow recognizable patterns. By emphasizing the impact of these experiential electricity consumption fluctuations on the current prediction process, we can capture the volatility variations to alleviate the over-smoothing problem. To this end, we propose an encoding decomposition-based multi-scale graph neural network (CMNN). The CMNN starts by decomposing the electricity data into various components. For the high-order components that exhibit approximate periodic behavior, the CMNN designs a Multi-scale Bi-directional Long Short-Term Memory (MBLSTM) network for fitting and prediction. For the low-order components that exhibit fluctuations, the CMNN transforms these components from one-dimensional time series into a two-dimensional low-order component graph to model the volatility of the low-order components, and proposes a Gaussian Graph Auto-Encoder to forecast the low-order components. Finally, the CMNN combines the predicted components to produce the final electricity consumption prediction. Experiments demonstrate that the CMNN enhances the accuracy of electricity consumption predictions.
Analysis of Wind Farm Productivity Taking Wake Loss into Account: Case Study
Authors: Zagubień Adam , Wolniewicz Katarzyna , Szwochertowski Jakub
Published: November 2024

Due to the growing demand for green energy, there is a shortage of land available for the location of wind farms. Therefore, the distances between turbines are being reduced, and the power of the turbines is being increased. This results in increased wake loss. The article describes a study of the impact of wind speed deficit and loss of wind turbine output due to wake loss on the decrease in energy efficiency of a wind farm. Two proposed wind farms, where the maximum number of turbines are located, were analyzed. The facilities were designed for implementation in Central Europe. The basic costs of construction and operation of the wind farms (WFs) were estimated. Based on the results of wind measurements and the performance characteristics of wind turbines, the productivity of the WFs was determined. The impact of removing individual turbines with the largest wake losses from the wind farm on the economic outcome of the project was studied. Evaluation criteria were proposed to quantify losses, which can serve as a benchmark for evaluating other wind farms. It was found that the higher the turbine’s power rating, the faster the payback resulting from the wake losses of a single turbine.
Optimising Flowback Strategies in Unconventional Reservoirs: The Critical Role of Capillary Forces and Fluid Dynamics
Authors: Nasriani Hamid Reza , Jamiolahmady Mahmoud
Published: November 2024

This study delves into the complexities of fluid cleanup processes post-hydraulic fracturing in unconventional gas deposits, focusing on the pivotal role of capillary pressure (Pc) correlations in tight and ultra-tight formations. Utilising Geo2Flow software, this research evaluates the efficacy of existing Pc models, identifying the Brooks and Corey model as notably precise for these formations, albeit recommending an adjustment to the pore size distribution index for a more accurate representation of rock behaviours. Further investigation centres on the cleanup process in multiple fractured horizontal wells, examining the impact of the Pc, matrix permeability, drawdown pressure, and fracturing fluid volume. A significant portion of this study addresses the influence of interfacial tension-reducing chemicals on post-fracturing production, highlighting their utility in ultra-tight formations, but advising against their use in tight formations due to environmental concerns and limited efficacy. The findings underscore the nuanced interplay between geological parameters and fracturing fluid dynamics, advocating for tailored fluid cleanup strategies that enhance the hydraulic fracturing efficiency while minimising the environmental impact. This comprehensive analysis offers valuable insights into optimising fracture cleanup and understanding the underlying physics, thereby contributing to more effective hydraulic fracturing practices.
Corrosion Rate Prediction of Buried Oil and Gas Pipelines: A New Deep Learning Method Based on RF and IBWO-Optimized BiLSTM–GRU Combined Model
Authors: Wang Jiong , Kong Zhi , Shan Jinrong , Du Chuanjia , Wang Chengjun
Published: November 2024

The corrosion of oil and gas pipelines represents a significant factor influencing the safety of these pipelines. The extant research on intelligent algorithms for assessing corrosion rates in pipelines has primarily focused on static evaluation methods, which are inadequate for providing a comprehensive dynamic evaluation of the complex phenomenon of corrosion in buried oil and gas pipelines. This paper proposes a novel approach to predicting the corrosion rate of buried oil and gas pipelines. The method is based on the combination of an improved Beluga Optimization algorithm (IBWO) and Random Forest (RF) optimization with BiLSTM and gated cycle unit (GRU), which are used to classify corrosion rates as high or low. Initially, a feature screening of corrosion factors was conducted via RF, whereby variables exhibiting a strong correlation were extracted. Subsequently, IBWO was employed to optimize the feature selection process, with the objective of identifying the optimal feature subset to enhance the model’s performance. Ultimately, the BiLSTM method was employed for the purpose of predicting the occurrence of low corrosion. A GRU method was employed for prediction in the context of high corrosion conditions. The RF–IBWO-BiLSTM–GRU model constructed in this paper demonstrates high prediction accuracy for both high and low corrosion rates. The verification of 100 groups of experimental data yielded the following results: the mean square error of this model is 0.0498 and the R2 is 0.9876, which is significantly superior to that of other prediction models. The combined model, which incorporates an intelligent algorithm, is an effective means of enhancing the precision of buried pipeline corrosion rate prediction. Furthermore, it offers a novel approach and insight that can inform subsequent research on the prediction of corrosion rates in buried oil and gas pipelines.
The Impact of Grid-Forming vs. Grid-Following Converters on Frequency Regulation: Comparing Centralised or Distributed Photovoltaic Generation
Authors: Tina Giuseppe Marco , Maione Giovanni , Stefanelli Domenico
Published: November 2024

Energy transition strategies point to energy systems that rely mostly on renewable sources, with photovoltaics being the most commonly used and emphasised. The transition from the past to the future of electrical system is characterised by the contrast between centralised and distributed generation, as well as the differences between synchronous machines and static converters and thus by their way to deliver services required for proper system operation, frequency regulation and transient stability. This paper compares the two converter control strategies, grid following and grid forming, for providing frequency regulation service while considering bulk photovoltaic generation at the HV level and MV-connected distributed by PV generation. The analyses reveal the equivalence between large plants and distributed resources for frequency regulation purposes, highlighting the relevance of grid-forming converter and their ability to supply inertia to the system. These results are obtained for the IEEE 14-bus system implemented in Dig Silent PowerFactory.
Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography
Authors: Stefaniak Barbara , Rymarczyk Tomasz , Wójcik Dariusz , Cholewa-Wiktor Marta , Cieplak Tomasz , Orzeł Zbigniew , Gudowski Janusz , Golec Ewa , Oleszek Michał , Kowalski Marcin
Published: November 2024

This paper presents an energy optimization approach to applying electrical impedance tomography (EIT) for medical diagnostics, particularly in detecting lung diseases. The designed Lung Electrical Tomography System (LETS) incorporates 102 electrodes and advanced image reconstruction algorithms. Energy efficiency is achieved through the use of modern electronic components and high-efficiency DC/DC converters that reduce the size and weight of the device without the need for additional cooling. Special attention is given to minimizing energy consumption during electromagnetic measurements and data processing, significantly improving the system’s overall performance. Research studies confirm the device’s high energy efficiency while maintaining the accuracy of the classification of lung disease using the LightGBM algorithm. This solution enables long-term patient monitoring and precise diagnosis with reduced energy consumption, marking a key step towards sustainable medical diagnostics based on EIT technology.
Optimization of Second-Generation Biodiesel Blends to Enhance Diesel Engine Performance and Reduce Pollutant Emissions
Authors: Gao Zhanbin , Xiao Yang , Mao Jin , Zhou Liang , Li Xinju , Li Zhiyong
Published: November 2024

In recent years, the global demand for energy has been continuously increasing. Biodiesel as a replacement for fossil fuels holds strategic importance for sustainable economic development, mitigating the environmental impact, and managing air pollution. The utilization of second-generation biodiesel has garnered significant research interest due to its physical and chemical characteristics that are comparable to diesel, its elevated cetane number, and its reduced viscosity. This study will transform the TBD234v6 fuel system, transforming the original diesel fuel system into a second-generation biodiesel/diesel hybrid fuel system. This study examined the impacts of second-generation biodiesel on combustion, performance, and emissions in diesel engines, as well as the influence of the deoxygenation rate on second-generation biodiesel. Grey decision-making was used to determine the optimal mixing ratio and deoxygenation rate. The results indicated that the optimal blend comprises 10% second-generation biodiesel and 90% diesel fuel. In dual-fuel mode at this blend ratio, there is a 3% increase in maximum pressure compared to running on pure diesel. Moreover, the fuel consumption rate decreases by approximately 5.6%. Nitrogen oxide (NOx) and soot emissions decreased by 4.7% and 4.9%, respectively.
Improving Photocatalytic Hydrogen Production with Sol–Gel Prepared NiTiO₃/TiO₂ Composite
Authors: Quispe Cohaila Alberto Bacilio , Sacari Sacari Elisban Juani , Lanchipa Ramos Wilson Orlando , Canahua Loza Hugo Benito , Tamayo Calderón Rocío María , Medina Salas Jesús Plácido , Gamarra Gómez Francisco , Mangalaraja Ramalinga Viswanathan , Rajendran Saravanan
Published: November 2024

This study presents a comprehensive investigation into the synthesis, characterization, and photocatalytic performance of NiTiO3/TiO2 nanocomposites for solar hydrogen production. Through a carefully optimized sol–gel method, we synthesized a heterojunction photocatalyst comprising 99.2% NiTiO3 and 0.8% anatase TiO2. Extensive characterization using XRD, Raman spectroscopy, FTIR, UV–visible spectroscopy, photoluminescence spectroscopy, and TEM revealed the formation of an intimate heterojunction between rhombohedral NiTiO3 and anatase TiO2. The nanocomposite demonstrated remarkable improvements in optical and electronic properties, including enhanced UV–visible light absorption and an 85% reduction in charge carrier recombination compared to pristine NiTiO3. Crystallite size analysis showed a reduction from 53.46 nm to 46.35 nm upon TiO2 incorporation, leading to increased surface area and active sites. High-resolution TEM confirmed the formation of well-defined interfaces between NiTiO3 and TiO2, with lattice fringes of 0.349 nm and 0.249 nm corresponding to their respective crystallographic planes. Under UV irradiation, the NiTiO3/TiO2 nanocomposite exhibited superior photocatalytic performance, achieving a hydrogen evolution rate of 9.74 μmol min−1, representing a 17.1% improvement over pristine NiTiO3. This enhancement is attributed to the synergistic effects of improved light absorption, reduced charge recombination, and efficient charge separation at the heterojunction interface. Our findings demonstrate the potential of NiTiO3/TiO2 nanocomposites as efficient photocatalysts for solar hydrogen production and contribute to the development of advanced materials for renewable energy applications.
Domain-Specific Modeling Language for Security Analysis of EV Charging Infrastructure
Authors: Motii Anas , El Hamlaoui Mahmoud , Basmadjian Robert
Published: November 2024

Electric vehicles (EVs) and their ecosystem have unquestionably made significant technological strides. Indeed, EVs have evolved into sophisticated computer systems with extensive internal and external communication capabilities. This interconnection raises concerns about security, privacy, and the expanding risk of cyber-attacks within the electric vehicle landscape. In particular, the charging infrastructure plays a crucial role in the electric mobility ecosystem. With the proliferation of charging points, new attack vectors are opened up for cybercriminals. The threat landscape targeting charging systems encompasses various types of attacks ranging from physical attacks to data breaches including customer information. In this paper, we aim to leverage the power of model-driven engineering to model and analyze EV charging systems at early stages. We employ domain-specific modeling language (DSML) techniques for the early security modeling and analysis of EV charging infrastructure. We accomplish this by integrating the established EMSA model for electric mobility, which encapsulates all key stakeholders in the ecosystem. To our knowledge, this represents the first instance in the literature of applying DSML within the electric mobility ecosystem, highlighting its innovative nature. Moreover, as our formalization based on DSML is an iterative, continuous, and evolving process, this approach guarantees that our proposed framework adeptly tackles the evolving cyber threats confronting the EV industry. Specifically, we use the Object Constraint Language (OCL) for precise specification and verification of security threats as properties of a modeled system. To validate our framework, we explore a set of representative threats targeting EV charging systems from real-world scenarios. To the best of our knowledge, this is the first attempt to provide a comprehensive security modeling framework for the electric mobility ecosystem.
A Comparative Study of the Environmental, Social, and Governance Impacts of Renewable Energy Investment on CO2 Emissions in Brazil, Russia, India, China, and South Africa
Authors: Bi Zhaoming , Khan Rabnawaz
Published: November 2024

The issue of climate change and global warming is rapidly intensifying due to the extensive emissions of CO2. In response to this, countries worldwide are implementing policies to enact decarbonization strategies through social and governance investing strategies. The current study examined the effects of environmental, social, and governance investing, eco-innovation, renewable energy production and consumption, and carbon taxes from 2004 to 2023. At the highest, middle, and lowest levels, this paper examines the environmental policies, social and governance economies, and energy of the BRICS nations. We investigate variable relationships through cross-sectional autoregressive distributed latency. The results suggest that Brazil’s focus on sustainability-driven innovation, along with its high renewable energy balance and middle-level status, is indicative of significant environmental initiatives. India’s higher-ups prioritize green finance, and their investments in environmental, social, and governance areas may demonstrate their commitment to sustainable development. China has made considerable progress in renewable energy and carbon trading despite its vast population and high emissions. At a lower level, Russia’s sustainability initiatives are undergoing evolution and have the potential to make significant strides. The nation’s difficulties require a coordinated, long-term strategy. The empirical findings imply that BRICS countries can achieve carbon neutrality by modifying their economic growth and globalization strategies and increasing their focus on renewable energy, as well as investment and policy regulations.
Ni/Al2O3/Foam Electric Heating Catalyst: Mitigating Carbon Emissions and Enhancing Reactor Temperature Uniformity
Authors: Ren Yanlun , Zhang Li , Xu Hong
Published: November 2024

Substituting the traditional fuel combustion heating mode in hydrogen production reactors with electric heating demonstrates a significant potential for reducing carbon dioxide emissions. An Ni/Al2O3/Ceramic Foam Electric Heating Catalyst was created using a replication template method and a slurry method. On a reactor with dimensions of Φ25 × 800 mm, the differences in the heating rate, axial temperature variance, radial temperature variance, and energy consumption between internal and external heating were analyzed. The results show that: (1) By optimizing the structure of the electric heating wires, the temperature uniformity in the catalyst is enhanced; (2) At 650 °C, 3000 h−1, and S/C = 3, compared to traditional granular catalysts, the internal electric heating reduces the axial temperature variance by 69.4% and the radial temperature variance by 95%; and (3) Achieving a temperature of 650 °C using electric heating only requires 23 min, resulting in a 56.82% reduction in energy consumption compared to external heating.
Research on Heat Transfer Characteristics of Plate Evaporators for Cold Storage
Authors: Xu Xun , Yuan Zhaokuo
Published: November 2024

A new type of plate evaporator suitable for cold storage refrigeration systems was designed. A mathematical model of the plate evaporator was established using Fluent14.0 software, and the effects of refrigerant mass flow rate and air velocity on the heat transfer characteristics of the plate evaporator were discussed. The numerical simulation results were verified through experiments. The research results show that in the design conditions of a refrigerant inlet dryness of 0.27, temperature of −5 °C, saturation pressure at this temperature, mass flow rate of 0.0187 kg/s, air inlet temperature of 6 °C, relative humidity of 80%, and flow rate of 3 m/s, the new plate evaporator had a cooling capacity of 3.13 kW, a refrigerant side pressure drop of 1.36 kPa, and an air side pressure drop of 495 Pa. By increasing the mass flow rate of the refrigerant or the air side flow rate, the cooling capacity of the evaporator increases linearly, but at the same time, the pressure drop on both the refrigerant and air sides increases rapidly.
Optimizing Techno-Economic Framework of REGs in Capacitive Supported Optimal Distribution Network
Authors: Srinivasan G. , Cheepati Kumar Reddy , Goud B. Srikanth , Alqarni Mohammed , Alamri Basem , Rami Reddy Ch.
Published: November 2024

This study describes the optimization of Distribution Network Structure (DNS) by altering sectionalizing and tie-switches with Reactive Power Injections (RPI) through optimal nodes under three load variations considering five different cases in Electric Distribution Networks (EDNs) to reduce Energy Loss (ELoss), thereby achieving Economic Benefit (EB), which is the first step process. This approach yields EBs only to some extent. To achieve a greater reduction in ELoss, enhancing bus voltage profile and to achieve additional EBs, this study examines the incorporation of Renewable Energy Generations (IREGs) into the optimal EDNs with reactive power support. The optimal energy has been purchased from the Independent Power Producers (IPPs). Besides, the Levy Flight Mechanism (LFM) integrated Seagull Optimization Algorithm (SOA) has been applied to solve the Economic Based Objective Function. The effectiveness of the developed methodology has been validated using IEEE 33-bus and a real 74-bus Myanmar EDN. The reductions in ELoss achieved by LFM-SOA have been compared with those of other existing methods in the literature for all the cases. The results reveals that the developed methodology efficiently achieves more EBs ($) for all the cases by optimizing DNSA with and without RPIs and IREGs.
Study on Electrical Characteristics Analysis and Electrical Circuit Model Design of Vanadium Redox Flow Battery Systems Based on Current and Flow Rate Conditions
Authors: Lee Seongjun , Jung Hyeonhong , Sung Yoon-Gyung
Published: November 2024

Recent research has focused on vanadium redox flow batteries (VRFBs) to address the short lifetimes and fire risks associated with lithium battery systems. While VRFBs offer advantages in safety, they suffer from low energy density and efficiency compared with lithium batteries. To improve VRFB performance, studies are exploring improvements in materials such as anodes, cathodes, and separators and optimizing operations by controlling electrolyte flow rates. However, the impact of current magnitude on VRFB efficiency has been less studied, with few analyses addressing both current and flow rate effects. This research proposes an experimental procedure to evaluate charge/discharge efficiency, energy efficiency, and system efficiency across varying current magnitudes and electrolyte flow rates, using a 40 W VRFB stack composed of four 10 W cells in series. In addition, we introduce a design method for an electrical equivalent circuit model that simulates the VRFB stack, reflecting experimental findings. The model’s accuracy was validated by comparing it with data from 11 full charge/full discharge cycle tests, which varied current and electrolyte amounts.
Underwater Noise Assessment in the Romanian Black Sea Waters
Authors: Mihailov Maria Emanuela , Chirosca Gianina , Chirosca Alecsandru Vladimir
Published: November 2024

The Black Sea, a unique semi-enclosed marine ecosystem, is the eastern maritime boundary of the European Union and holds significant ecological importance. The present study investigates anthropogenic noise pollution in the context of the Marine Strategy Framework Directive’s Descriptor 11, with a particular emphasis on the criteria for impulsive sound (D11C1) and continuous low-frequency sound (D11C2) in Romanian ports, which handle a substantial share of regional cargo traffic, and impact maritime activities and associated noise levels. The noise levels from shipping activity vary across Romanian waters, including territorial waters, the contiguous zone, and the Exclusive Economic Zone. These areas are classified by high, medium, and low ship traffic density. Ambient noise levels at frequencies of 63 Hz and 125 Hz, dominated by shipping noise, were established, along with their hydrospatial distribution for the 2019–2020 period. Furthermore, predictive modeling techniques are used in this study to assess underwater noise pollution from human sources. This modeling effort represents the first initiative in the region and utilizes the BELLHOP ray-tracing method for underwater acoustic channel modeling in shallow-water environments. The model incorporates realistic bathymetry, oceanography, and geology features for environmental input, allowing for improved prediction of acoustic variability due to time-varying sea variations in shallow waters. The study’s findings have important implications for understanding and mitigating anthropogenic noise pollution’s impact on the Black Sea marine ecosystem.
Elevational Effects of Climate Warming on Tree Growth in a Picea schrenkiana Forest in the Eastern Tianshan Mountains
Authors: He Jianing , Shen Zehao , Ning Caiwen , Zhang Wentao , Halik Ümüt
Published: November 2024

Considerable uncertainty exists regarding the overall effects of future climate change on forests in arid mountains, and the elevational range of drought-induced tree growth decline remains unclear. Tianshan is the largest mountain in arid regions globally. Here, we analyzed tree ring data of pure stands of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) in the Jiangbulake region in the eastern Tianshan Mountains along an elevational gradient (1800–2600 m a.s.l.). The radial growth of P. schrenkiana trees declined in three of the nine sample strips (1800–2100 m a.s.l.) over the last two decades. P. schrenkiana growth response (measured by the tree ring width index, RWI) to temperature significantly changed at an elevational “inflection point” at 2100–2200 m. RWI was significantly negatively correlated with temperature at low elevations, whereas the opposite was observed at high elevations. Precipitation and minimum temperatures in winter and spring and mean temperatures in spring and summer were the main drivers of P. schrenkiana growth, with the effect of maximum temperatures on tree growth concentrated in the spring. In addition to climate warming in the study area since the 1970s, tree growth (as measured by the basal area increment, BAI) at elevations below 2200 m initially increased and then decreased. Tree growth at higher elevations continues to increase. Since 2000, the average RWI at high elevations exceeded that at low elevations. The average BAI values at high and low elevations have gradually approached each other in recent decades, although lower elevations exhibited higher values in the past.
Dickson Quality Index of Cocoa Genotypes Under Water Deficit
Authors: Alonso Rogerio S. , Sodré George A. , Silva Delmira C.
Published: November 2024

The aim of this study was to identify patterns of morphological adjustments associated with the Dickson Quality Index (DQI) in Theobroma cacao L. genotypes subjected to water deficit (WD), as a criterion for the pre-selection of drought-tolerant genotypes. Rooted cuttings from seven genotypes were subjected to water deficit (WD). The data from the growth analysis and DQI were subjected to analysis of variance, tests of means, and multivariate analysis. A high correlation was identified between IQD and the variables root dry mass (RDM), leaf dry mass (LDM), stem diameter (SD), and total dry mass (TDM) independently for each genotype; these correlations are more evident in genotypes CP-49, PS-1319, and Cepec-2002. The multivariate analysis divided the genotypes into two major groups: one consisting of the Ipiranga-01, CCN-51, SJ-02, and PH-16 genotypes, and the other comprising the CP-49, Cepec-2002, and PS-1319 genotypes. By correlating the results of the growth analysis with DQI, we were able to identify genotypes CP-49, PS-1319, and Cepec-2002 as tolerant; Ipiranga-01 and CCN-51 as moderately tolerant; and SJ-02 and PH-16 as poorly tolerant to WD. However, it is important that other fields of science are considered to provide greater insights into adaptation to drought.
A Study on the Heterogeneity of Consumer Psychological Mechanisms of Dual Decision-Making Agents in Forest Educational Tourism: The Moderating Effect of Family Decision-Making Empowerment
Authors: Li Ying , Wang Wenlong , Liu Yuxin , Wang Chunyu
Published: November 2024

The consumption decision-making in educational tourism exhibits dual-agent characteristics, requiring alignment of consumption intentions between both agents to generate actual purchasing behavior. However, research on this characteristic is still relatively scarce. Understanding the psychological mechanisms and heterogeneity of consumption decision-making among students and parents in forest educational tourism is crucial for implementing precise consumer incentive strategies in related tourist attractions. This study constructs a theoretical model of the consumer psychological mechanism of dual decision-making agents in forest educational tourism, incorporating perceived value and perceived risk based on the Theory of Planned Behavior. A structural equation model is employed to validate the explanatory power and heterogeneity of this theoretical model, as well as to explore the moderating effect of family decision-making empowerment. The results indicate that the formation of the consumer psychological mechanism of dual decision-making agents in forest educational tourism is heterogeneous: the negative impact of perceived risk on perceived behavioral control and the positive impact of perceived behavioral control on consumption intention are only valid in the student group, not in the parent group; perceived behavioral control serves as a mediator only in the relationship between perceived value, perceived risk, and consumption intention for the student group, without any mediating effect for the parent group; family decision-making empowerment moderates certain paths in the consumer psychological influence mechanism of forest educational tourism decision-making agents. This study expands the Theory of Planned Behavior, enriching the research perspective on factors influencing consumption psychology, exploring the heterogeneity of dual decision-making agents in educational tourism, and examining the impact of family decision-making empowerment on consumer psychology. The findings provide relevant tourism enterprises and forest attractions with a deeper understanding of the consumption psychology of dual decision-making agents in forest educational tourism, offering a scientific basis for tourism enterprises and forest attractions to optimize marketing strategies, while also enhancing the consumption experience on the demand side.