bluuebunny/crossref_metadata_2025_split huggingface dataset:
YOLOv7-based insulator defect detection with progressive feature fusion and DFC attention
Authors: You Xilai , Ma Jianqiao 
Published: November 2024

Abstract
With the development of smart grids, drones have been widely used for inspecting power transmission lines, generating a large amount of insulator image data. Relying on manual inspection for this task results in a huge workload and the risk of missed detections due to human fatigue. Here, we propose an improved model based on YOLOv7-Tiny. First, we replace the activation function with the funnel activation function to optimize the activation domain dynamically. Second, we introduce a lightweight DFC attention mechanism. Experimental results show that the improved model achieves a detection accuracy and recall rate of 96.4% and 92.5%, respectively.
A new DC bus voltage control strategy for energy routers based on distributed coordination optimization
Authors: Chen Shiwei , Lei Shi , Xia Xuhua 
Published: November 2024

Abstract
The types of power ports of energy routers at the side of the distribution network platform are complex and have different characteristics, which makes the operation conditions of energy routers complex and changeable. Although many pieces of literature have proposed more relevant control strategies to effectively realize the efficient and stable operation of energy routers under the two basic working conditions of grid-connected and isolated islands. However, when considering various complex operating conditions such as start-up, overload/overcharge, sudden failure of distribution network, grid-connected, and inter-island switching, the reliable operation of the existing energy routers is still faced with great challenges. In this paper, a DC bus voltage control strategy based on distributed coordination optimization is proposed for typical operating conditions of energy routers. Simulation results show that this strategy can effectively achieve the DC bus voltage control performance of energy routers under various burst operating conditions and strengthen the robustness of output voltage of energy routers under isolated islands.
Refined transmission line ice-cover prediction model and optimization study
Authors: Tian Maojie , Yang Guozhu , Sun Shirui , Sun Huamin , Liu Jingru 
Published: November 2024

Abstract
This study aims to develop a fine-grained transmission line ice-cover prediction model and conduct an optimization study. Ice cover is one of the important factors leading to transmission line accidents, so accurately predicting the ice cover of transmission lines is crucial to ensure the safe operation of power grids. In this paper, an efficient ice-cover prediction model is constructed based on advanced machine learning algorithms and optimization methods and is validated and optimized with a large amount of experimental data. The results show that the proposed model has high accuracy and prediction capability in ice cover prediction, which provides important support for the safe operation of transmission lines.
Force analysis and improvement of main transformer bushing terminal structure
Authors: Duan Ruofei , Pei Hao , Shi Kaiyuan , Wang Dayong , Yu Haiyang , Wang Yuping , Zhong Haoxin 
Published: November 2024

Abstract
After investigation, it was found that due to natural environmental conditions such as rain and snow temperature, equipment such as down conductor above the terminals, and natural swings of wires, the terminal blocks of the down conductor bushing on the high voltage side of the main transformer of a 500kV substation will deteriorate and deform. Following the force analysis and experiment on the down conductor bushing terminal block on the high voltage side of the main transformer, it is found that the weak structure of the bushing terminal block lies in the vertical orientation of the terminal and the connection point of the transverse structure, and its horizontal external force limit value is 1.91KN. In this paper, it was finally decided to improve the terminal structure by erecting diagonal supports between the vertical and transverse structures of the terminals. The improved terminal block can be subjected to an external force of 5KN horizontally, and the terminal shape is within the safe range. It can ensure the safety and stability of the main transformer bushing terminal block.
Improved sparrow algorithm to optimize kernel extreme learning machines for lithium battery status of health estimation on incremental capacity curve
Authors: Ni Yiwei , Ding Xuqiang , Wang Qi 
Published: November 2024

Abstract
The advancement of new energy vehicles and energy storage devices has increasingly demanded a more accurate state of health estimation for lithium batteries. Data-driven models are gradually widely used but still have the problems of long iteration time, low accuracy, and unreliable selection of feature factors. Thus, to promote the application of data-driven models in estimating the health state of lithium batteries, this paper proposes a multi-method improved sparrow algorithm optimized kernel extreme learning machine framework for lithium battery health state estimation. To improve the speed and accuracy issues of the data-driven model, this paper selects the kernel extreme learning machine as the network model and the improved sparrow algorithm using chaotic mapping and self-designed exponential weight factors as the optimization algorithm for automatic parameter search to achieve high accuracy and speed. Secondly, to strengthen the reliability of data feature factor selection, multiple feature factors are selected in the incremental capacity curve to improve the stability of feature factors. Finally, the rapidity and reliability of the proposed model on the SOH prediction of lithium batteries are verified by experiments, which provides an effective way to manage lithium batteries healthily.
Research progress on topology and energy management of fuel cell hybrid power ships
Authors: Tian Chenglong , Zhang Li , Zou Liang , Liu Xingdou 
Published: November 2024

Abstract
With the increasing awareness of environmental protection, the maritime industry is moving towards green and low-carbon development. Fuel cells, due to their pollution-free and high-efficiency characteristics, are one of the key technologies driving the green transformation of traditional ships. However, fuel cells have relatively soft output characteristics and often require other energy storage components to provide supplementary power. This paper reviews the types, advantages, and disadvantages of the topologies of fuel cell hybrid power ships, analyses the current development status of energy management goals and methods, and finally provides an outlook on the development of fuel cell hybrid power ships.
Design of a two-stage photovoltaic grid-connected system with dual closed-loop control
Authors: Niu Jianfeng 
Published: November 2024

Abstract
This paper designs a two-stage photovoltaic grid-connected system with dual closed-loop control, cascading the topological structures of photovoltaic cells, boost chopper circuits, and inverter circuits. The front-stage boost chopper circuit control utilizes the incremental conductance method to achieve maximum power point tracking control. The rear-stage inverter circuit employs a dual closed-loop control system with an outer voltage loop and an inner current loop, incorporating a proportional-integral controller, to ensure stable DC-side voltage and unity power factor for grid connection. A simulation model of the two-stage photovoltaic grid-connected system designed in this paper was constructed and analyzed through simulation runs. The firmness of the DC-side voltage and the achievement of unity power factor during grid connection confirmed the operability and resultiveness of the cascaded topology and the control method.
A distributed photovoltaic short-term power forecasting model based on lightweight AI for edge computing
Authors: Fan Yuanliang , Wu Han , Lin Jianli , Li Zewen , Li Lingfei , Huang Xinghua , Chen Weiming , Chen Beibei 
Published: November 2024

Abstract
In recent years, an immense amount of distributed photovoltaics are integrated into low-voltage distribution network, producing a substantial volume of operational data. The centralized cloud data center cannot process massive amounts of data precisely and promptly. Therefore, the operational status of distributed photovoltaic systems in low-voltage distribution network becomes difficult to predict. However, edge computing in the distribution network enables local data processing to improve the forecasting service’s real-time reliability. In this regard, this paper proposes a distributed photovoltaic short-term power forecasting model based on lightweight AI algorithms. Firstly, based on the Pearson correlation coefficient method, an analysis is conducted on the historical operational data in the network to extract important meteorological features correlated with the photovoltaic power output. Secondly, a distributed photovoltaic power forecasting model for the distribution network is constructed based on the Xception and attention mechanism. Finally, the model is trained using pruning, which removes redundant parts of the model, resulting in a compact and efficient forecasting model. By validating real-world datasets, the results demonstrate that the model presented in this article has a smaller size and higher forecasting accuracy than other state-of-the-art forecasting models.
Voltage control strategy of output bus of grid-connected port of energy router based on energy feedback
Authors: Chen Shiwei , Shen Ying , Xia Xuhua 
Published: November 2024

Abstract
The remaining power conversion ports are equivalent to constant power loads for the grid-connected port of the voltage source. The negative impedance characteristics of the constant power loads will worsen the voltage source characteristics of the grid-connected port and even cause system instability. According to the influence mechanism of constant power load on the DC bus voltage control performance during grid-connection, a new voltage control strategy based on energy feedback is proposed in this paper. The simulation results show that the proposed control strategy can more effectively reduce the negative impedance characteristics of the energy router’s constant power load and improve the bus voltage’s control performance compared with the existing control strategies.
The Fabrication of BiVO4/WO3/GaN Heterojunction and its Enhanced Water Splitting Performance
Authors: Xi Xin , Suo Zhaojun , Li Tuo , Yu Zhiguo , Liu Kai , Zou Xiaofeng , Wang Changhong 
Published: November 2024

Abstract
GaN has garnered significant attention for water splitting due to its excellent light absorption, carrier transport properties, and chemical inertness. However, its bandgap of 3.4 eV restricts absorption to the ultraviolet range. To address this limitation, narrow-bandgap semiconductors BiVO4 and WO3 were deposited on the GaN surface using the sol-gel method. Photoelectrochemical water-splitting tests revealed that the saturated photocurrent densities of GaN/BiVO4 and GaN/BiVO4/WO3 under full-spectrum illumination were 1.42 and 1.86 times greater than that of GaN alone, respectively. This improvement is attributed to the smaller bandgaps of BiVO4 and WO3, which significantly extend the spectral absorption range of GaN. Additionally, BiVO4 and WO3 form heterojunctions through energy alignment, and the built-in electric field at the heterojunctions accelerates the separation of photo-generated carriers, further enhancing energy conversion efficiency. The study also found that the BiVO4 and WO3 films exhibit a 2D flake morphology, providing larger surface areas that enhance light absorption and carrier transport, thereby improving water-splitting efficiency. Our research paves a new path for the application of GaN in water splitting.
Priority directions for increasing production volumes in the regional livestock industry
Authors: Yu Gusev A 
Published: November 2024

Abstract
The efficiency of agricultural production is determined by one of key parameters, namely, the production volume, which directly affects the earning power and profitability of the agricultural sector. The current level of development of the agricultural sector, both in the country as a whole and in most regions, indicates two trends in the development of the livestock industry and production, namely, processes of an intensive and extensive nature, thanks to which production volumes are also growing. At the same time, their influence on the scale of production activity is multidirectional. With the further development of technical and technological modernization, the introduction of modern technologies, the digital transformation of the livestock industry, processes related to the intensification of agricultural production should become priority methods for stimulating the growth of volumes, which will significantly and rapidly increase production volumes, ensure a significant increase in labor productivity, increase the level of its intellectualization.
Imagining a net-zero Teesside: actors, networks, and expectations in industrial decarbonisation megaprojects
Authors: Herman Kyle S , Iskandarova Marfuga , Sovacool Benjamin K 
Published: November 2024

Abstract
Decarbonising industrial clusters is critical to achieving the UK’s net-zero industrial strategy. This study focuses on Teesside, an industrial cluster in Northeast England, analysing its transition through the framework of the Sociology of Expectations (SoE). The research investigates the role of public and private stakeholders in driving decarbonisation efforts, concentrating on a limited set of technologies and large-scale megaprojects, especially carbon capture, hydrogen production, CO2 and hydrogen transport. The study highlights the challenges of deploying these first-of-a-kind technologies, which are not yet commercially viable in the UK. Our analysis identifies both opportunities and significant risks in Teesside’s approach, particularly the potential over-reliance on a narrow range of technologies. The findings raise concerns about the assumed reductions in costs and carbon emissions, questioning the feasibility of scaling these technologies for long-term industrial sustainability. The main implication is that, should the technologies currently favoured by incumbent industry fail to perform, the expectations could play a double and contradictory role in net-zero transitions—by both motivating actors to legitimise decarbonisation technologies, yet blinding others to the significant challenges that lie ahead.
Research on temperature rise prediction model for circuit breaker based on numerical Laplace transform
Authors: Zhang Yihe , Zhang Xu , Qu Xiaomin , Wang Songtao , Liu Xiaozhi , Zhang Jiang 
Published: November 2024

Abstract
The temperature rise in circuit breakers’ thermal paths is a critical indicator influencing their tripping characteristics, directly affecting response speed, reliability, and safety. Existing models for predicting circuit breaker temperature rise are often structurally limited, lack generality, and exhibit low predictive accuracy. Addressing this issue, this paper investigates an efficient, precise, and widely applicable theoretical model for predicting circuit breaker temperature rise. This model focuses on the thermal conduction mechanisms within small-scale circuit breakers, establishing a fundamental numerical heat transfer model based on Newton’s cooling formula and Fourier’s heat conduction law. By applying numerical Laplace transformation, the model is simplified into the complex frequency domain, and employing residue theorem for solving, it is transformed back into the time domain using Laplace inverse transformation to derive the predictive model. Experimental validation using a 32 A rated current circuit breaker demonstrates the model’s high predictive accuracy, suitability across various circuit breaker structures, with an average deviation below the permissible deviation in industry standards. This research holds significant implications for enhancing the thermal tripping characteristics of circuit breakers.
Ethical implications of artificial intelligence in skin cancer diagnostics: use-case analyses
Authors: Shah Syed F H , Arecco Daniel , Draper Heather , Tiribelli Simona , Harriss Eli , Matin Rubeta N 
Published: November 2024

Abstract

Background
Skin cancer is the most common cancer worldwide. Early diagnosis is crucial to improving patient survival and morbidity. Artificial intelligence (AI)-assisted smartphone applications (apps) for skin cancer potentially offer accessible, early risk assessment of suspicious skin lesions. However, the integration of novel technologies into dermatology pathways raises ethical concerns. Although ethical principles for AI governance are well known, how these principles should be applied to real-life AI apps readily available for public use is less well understood.

Objectives
To conduct an ethical use-case analysis of commercially available skin cancer apps, to better understand the ethical issues arising from their development and use in a real-world context.

Methods
Established methods for the ethical analysis of clinical AI applications were applied to two popular skin cancer apps in the UK: SkinVision and Scanoma. Systematic searches of published literature, regulatory documents and websites were conducted to review the evidence regarding app development, effectiveness and use. Screening for inclusion was undertaken by two researchers independently. Ethical concerns were identified with reference to previously described ethical concerns and principles for AI-assisted healthcare.

Results
By conceptualizing ethical principles within the use-context of skin cancer apps, we identified specific ethical issues arising throughout the AI lifecycle of both apps. One company provided extensive detail regarding algorithm development and decision-making; this information was insufficiently reported for the other app. Other concerns identified were related to number, quality and consistency of studies assessing algorithm efficacy. Limited efforts to address potential skin tone biases and the exclusion of individuals with darker skin tones as target users by one app risks perpetuating existing inequalities. Inadequate regulatory oversight was identified.

Conclusions
Findings from our ethical use-case analysis of two patient-facing AI-assisted skin cancer apps suggest inadequate incorporation of bioethical norms such as justice, responsibility and transparency into the development and deployment of both apps. Improved regulation should increase accountability. Ensuring ethics by design through integration between technology developers, dermatologists, ethicists and the public is urgently needed to prevent the potential benefits of AI-assisted skin cancer apps being overshadowed by potential ethical harms.
AAV1.tMCK.NT-3 gene therapy improves phenotype in Sh3tc2−/− mouse model of Charcot–Marie–Tooth Type 4C
Authors: Ozes Burcak , Tong Lingying , Moss Kyle , Myers Morgan , Morrison Lilye , Attia Zayed , Sahenk Zarife 
Published: November 2024

Abstract
Charcot–Marie–Tooth Type 4C (CMT4C) is associated with mutations in the SH3 domain and tetratricopeptide repeats 2 (SH3TC2) gene, primarily expressed in Schwann cells (SCs). Neurotrophin-3 (NT-3) is an important autocrine factor for SC survival and differentiation, and it stimulates neurite outgrowth and myelination. In this study, scAAV1.tMCK.NT-3 was delivered intramuscularly to 4-week-old Sh3tc2−/− mice, a model for CMT4C, and treatment efficacy was assessed at 6-month post-gene delivery. Efficient transgene production was verified with the detection of NT-3 in serum from the treated cohort. NT-3 gene therapy improved functional and electrophysiological outcomes including rotarod, grip strength and nerve conduction velocity. Qualitative and quantitative histopathological studies showed that hypomyelination of peripheral nerves and denervated status of neuromuscular junctions at lumbrical muscles were also improved in the NT-3-treated mice. Morphometric analysis in mid-sciatic and tibial nerves showed treatment-induced distally prominent regenerative activity in the nerve and an increase in the estimated SC density. This indicates that SC proliferation and differentiation, including the promyelination stage, are normal in the Sh3tc2−/− mice, consistent with the previous findings that Sh3tc2 is not involved in the early stages of myelination. Moreover, in size distribution histograms, the number of myelinated axons within the 3- to 6-µm diameter range increased, suggesting that treatment resulted in continuous radial growth of regenerating axons over time. In conclusion, this study demonstrates the efficacy of AAV1.NT-3 gene therapy in the Sh3tc2−/− mouse model of CMT4C, the most common recessively inherited demyelinating CMT subtype.
Prognostic implications and reversibility of pulmonary vascular resistance derived by echocardiography in patients undergoing tricuspid annuloplasty
Authors: Zhang Jingnan , Flachskampf Frank A , Zhu Ching-Yan , Chen Yan , Wu Meizhen , Ren Qingwen , Huang Jiayi , Guo Ran , Gu Wenli , Hung Yik-Ming , Böyük Ferit , Fang Fang , Zhang Gejun , Pan Xiangbin , Chan Yap-Hang , Chan Tai-Leung , Yiu Kai-Hang 
Published: November 2024

Abstract

Aims
Pulmonary vascular resistance (PVR) intimately correlates with right ventricular afterload and the development of secondary tricuspid regurgitation (sTR). We sought to investigate the prognostic roles of PVR derived by echocardiography in patients with sTR undergoing tricuspid annuloplasty (TA).

Methods and results
Data from 322 TA patients [median age (inter-quartile range): 65.0 (59.0–70.0) years; 35.7% males] were obtained from a prospective registry to determine the impact of PVR on the composite outcome [including all-cause mortality and heart failure (HF) hospitalization]. PVR was calculated by dividing the peak TR velocity by time–velocity integral of the right ventricular outflow tract followed by adding 0.16. During a median follow-up of 5.2 years, 108 adverse events occurred including 48 deaths and 60 HF readmissions. Baseline PVR ≥ 2 WU was independently associated with a higher risk of composite outcome (HR: 1.674, 95% CI: 1.028–2.726, P = 0.038). Baseline PVR outperforms both pulmonary artery systolic pressure (PASP) and the ratio of tricuspid annulus plane systolic excursion to PASP in terms of outcome prediction, with pronounced improvement of global model fit, reclassification, and discrimination. In 150 patients who received short-term echocardiograms after surgery, the presence of post-operative PVR ≥ 2 WU (n = 20, 13.3%) was independently associated with the composite outcome (HR: 2.621, 95% CI: 1.292–5.319, P = 0.008).

Conclusion
PVR derived by echocardiography is an independent determinant of outcomes in patients undergoing TA for sTR. The inclusion of non-invasive PVR may provide valuable information to improve patient selection and post-operative management in this population.