bluuebunny/crossref_metadata_2025_split huggingface dataset:
A method for analyzing the state of double-column horizontal rotary isolation switch based on image processing
Authors: Li Fupeng 
Published: September 2024

Abstract
When the operating status of electrical equipment in a substation or the operating mode of the power system changes, a series of electrical equipment tripping operations need to be carried out. For traditional substations, personnel need to visually verify the opening and closing status of isolation switches during tripping operations and electrical equipment inspections. This manual operation mode has disadvantages such as low automation level, high labor intensity, and long operation time. The method of indirectly detecting the opening and closing status of isolation switches by installing auxiliary switches on the operating mechanism of control isolation switches also has the drawback of low accuracy. Currently, most inspection robots deployed in substations are used to detect the infrared temperature of electrical equipment and determine if there is an overheating defect, but they cannot automatically identify the opening and closing status of isolation switches and other electrical equipment.
Measurement error prediction of CVT based on DenseNet-GRU network
Authors: Chen Xu , Zhang Chao , Zhang Haomiao , Cheng Zhiqiang , Xu Yinzhe , Yan Yu , Su Yingchun , Ou Long 
Published: September 2024

Abstract
Capacitor voltage transformer (CVT) out-of-tolerance is one of the main factors causing power metering losses. In order to accurately predict CVT errors and avoid losses caused by CVT out-of-tolerance in a timely manner, this paper proposes a CVT error prediction algorithm based on the DenseNet-GRU network. This method uses CVT historical error data and environmental parameters as data samples to establish DenseNet-GRU Error prediction model achieves accurate prediction of CVT errors. In order to verify the effectiveness of the model, experimental comparisons were conducted with error prediction models established by similar algorithms. The results showed that the average absolute percentage error, root mean square error, and coefficient of determination of the prediction results of the DenseNet-GRU model were optimal and had higher prediction performance. The accuracy and robustness provide ideas and support for subsequent CVT error prediction research work.
Numerical modeling of borehole thermal energy storage in unsaturated soils
Authors: Meng Boyan , Luo Wenxing , Chen Guifan , Zhang Xiaoxiao 
Published: September 2024

Abstract
Borehole Thermal Energy Storage (BTES) in unsaturated soils offers advantages such as enhanced heat storage efficiency and widespread accessibility. However, the complex heat and mass transfer mechanisms and their impact on BTES performance necessitate further investigation. In this study, a componential two-phase heat transfer and fluid flow model was employed to examine the key mechanisms impacting the heat storage performance of a soil BTES system. Simulated results reveal that changes in soil thermal and hydraulic properties due to heat injection may significantly affect the heat transfer mechanisms and heat storage performance of the system. In particular, strong convective heat transfer may cause a reduction in heat storage efficiency. Comparison with results from the heat conduction model demonstrates the effectiveness of the modeling approach, especially when drying out occurs. The findings of this study can inform the design of soil BTES systems.
Simulation study of CCFL phenomenon in downcomer during refilling stage based on two-fluid three-field model
Authors: Zhou Fanfan , Zhang Hao , Chen Lin , Yang Yanhua 
Published: September 2024

Abstract
This study adopts a two-fluid three-field model instead of a traditional CCFL model to study hydraulic behavior in downcomers during a refilling stage. UPTF Test 6, a cold leg injection experiment, is simulated by the subchannel program cosSUBC. Results show that the flow field distribution in the downcomer is non-uniform. Coarser node divisions cannot simulate the actual flow field in the downcomer. The effectiveness of the interphase friction model in cosSUBC is verified by comparing simulated and experimental results. Compared with the simulation results of the CCFL model, cosSUBC has a smaller error and can predict the CCFL phenomenon in downcomers more accurately.
Algebraic discrete quantum harmonic oscillator with dynamic resolution scaling
Authors: May Michael Q , Qin Hong 
Published: September 2024

Abstract
We develop an algebraic formulation for the discrete quantum harmonic oscillator (DQHO) from the Hamiltonian for two, coupled QHOs and provide a physical picture for the Kravchuk function eigenstates of the oscillator. The familiar

su

(
2
)

structure of the coupled QHO Hamiltonian divides its spectrum into sets corresponding to the DQHO at different resolutions. In addition to energy ladder operators, the formulation allows for the introduction of resolution ladder operators connecting all DQHOs with different resolutions, thus enabling the dynamic scaling of the resolution of finite degree-of-freedom quantum simulations. The coherent state of the DQHO is constructed, and its expected position is proven to oscillate as a classical harmonic oscillator. The DQHO coherent state recovers that of the quantum harmonic oscillator at large resolution.
Verifiable quantum homomorphic encryption based on garbled evaluation
Authors: He Renke , Chen Lingli , Li Qin , Tan Xiaoqing , Chen Lv 
Published: September 2024

Abstract
Quantum homomorphic encryption (QHE) can allow directly computation on the encrypted data without need to decrypt it in advance. It is also necessary to provide another property of verifiability that the client should verify whether the evaluation result is correct. However, most existing QHE schemes did not consider it and only assumed servers to be honest. In this paper, we propose a verifiable QHE (vQHE) scheme by using different types of circuits indistinguishable to the server, where the client can detect whether the server is honest or not by verifying the results of test circuits. Furthermore, by designing the gadgets to implement and test T gates and H gates in a non-interactive way for the used circuits, the proposed vQHE scheme does not require interaction during the process of evaluation. Thus the proposed vQHE scheme has the potential to make clients prefer to use it for protecting their private data in future quantum cloud environments.
Estimating the Ebro river discharge at 1 km/daily resolution using indirect satellite observations
Authors: Pellet Victor , Aires Filipe , Baez Villa Nueva Oscar , Filippucci Paolo 
Published: September 2024

Abstract
Estimating river discharge Q at global scale from satellite observations is not yet fully satisfactory in part because of limited space/time resolution. Furthermore, on highly anthropized basins, it is essential to anchor the analysis to reliable Q measurements. Gauge networks are however very sparse and limited in time, and SWOT (Surface Water Ocean Topography) river discharge estimates at global scale are not yet available. The method proposed here is able to obtain continuous daily Q estimates at 1 km/daily resolution, using indirect satellite data and ground-based estimates. We focus here on the Ebro. Over such an anthropized basin (e.g. change of land use, irrigation), the exploitation of 205 available gauges at their nominal resolution (i.e., daily point measurements) is a necessity. The hydrological Continuum model is used to help interpolate spatially and temporally the observations into our optimal interpolation scheme. The proposed Q-mapping is similar to an assimilation scheme were Earth observations (precipitation, evapotranspiration and total water storage change) and model simulations are constrained by in situ gauge measurements. The Q estimates are evaluated using a rigorous leave-one-out experiment, showing a good agreement with the in situ data: a correlation of 0.72 (median), and a 75th percentile of Nash-Sutcliffe Efficiency up to 0.62. Our spatio-temporal continuous Q estimates at high spatial/temporal resolution can describe complex continental water dynamics, including extreme events. SWOT estimates will soon be available, at the global scale but with irregular space/time sampling: our method should help exploit them to obtain a regular space-temporal description of the water cycle at high resolution.
ETLoViT: an acne diagnose approach using vision-transformers and model ensembling
Authors: Paluri Krishna Veni , Gupta Ashish 
Published: September 2024

Abstract
Acne, a widespread skin condition predominantly affecting teenagers, presents intricate challenges in its diagnosis. Recent advances in deep learning, machine learning, and image processing methods have made it possible to diagnose acne automatically and effectively. However, achieving higher acne classification accuracy is still one of the concerns with these methods. Therefore, this paper introduces a group of trained models based on transfer learning that is applied to Vision Transformer extracted features (ETLoViT). These models are trained using two innovative deep-learning methods: the Vision Transformer (ViT) and model ensembling for acne image classification. The ViT approach harnesses the power of the attention module to extract acne features efficiently. These extracted features are subsequently run through different transfer learning models, such as MobileNetV2, VGG16, and InceptionResNetV2. The predicted results were subsequently combined for classification. The proposed model (ETLoViT) is compared with standing deep learning models, and the outcomes demonstrate that the proposed (ETLoViT) model consistently performs better, achieving an astounding 96% classification accuracy.
Multi-fidelity Gaussian process surrogate modeling for regression problems in physics
Authors: Ravi Kislaya , Fediukov Vladyslav , Dietrich Felix , Neckel Tobias , Buse Fabian , Bergmann Michael , Bungartz Hans-Joachim 
Published: September 2024

Abstract
One of the main challenges in surrogate modeling is the limited availability of data due to resource constraints associated with computationally expensive simulations. Multi-fidelity methods provide a solution by chaining models in a hierarchy with increasing fidelity, associated with lower error, but increasing cost. In this paper, we compare different multi-fidelity methods employed in constructing Gaussian process surrogates for regression. Non-linear autoregressive methods in the existing literature are primarily confined to two-fidelity models, and we extend these methods to handle more than two levels of fidelity. Additionally, we propose enhancements for an existing method incorporating delay terms by introducing a structured kernel. We demonstrate the performance of these methods across various academic and real-world scenarios. Our findings reveal that multi-fidelity methods generally have a smaller prediction error for the same computational cost as compared to the single-fidelity method, although their effectiveness varies across different scenarios.
Accelerating cavity fault prediction using deep learning at Jefferson Laboratory
Authors: Rahman Md M , Carpenter A , Iftekharuddin K , Tennant C 
Published: September 2024

Abstract
Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.
Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium
Authors: Carnazza Francesco , Carollo Federico , Andergassen Sabine , Martius Georg , Klopotek Miriam , Lesanovsky Igor 
Published: September 2024

Abstract
We develop a machine learning algorithm to infer the emergent stochastic equation governing the evolution of an order parameter of a many-body system. We train our neural network to independently learn the directed force acting on the order parameter as well as an effective diffusive noise. We illustrate our approach using the classical Ising model endowed with Glauber dynamics, and the contact process as test cases. For both models, which represent paradigmatic equilibrium and nonequilibrium scenarios, the directed force and noise can be efficiently inferred. The directed force term of the Ising model allows us to reconstruct an effective potential for the order parameter which develops the characteristic double-well shape below the critical temperature. Despite its genuine nonequilibrium nature, such an effective potential can also be obtained for the contact process and its shape signals a phase transition into an absorbing state. Also, in contrast to the equilibrium Ising model, the presence of an absorbing state renders the noise term dependent on the value of the order parameter itself.
Fanny Hensel, born Fanny Mendelssohn-Bartholdy (1805–1847)
Authors: Wilson Miranda 
Published: September 2024

Abstract
The nineteenth century was the golden age of the cello-piano sonata. The Romantic composers Hensel, Mendelssohn, Chopin, Farrenc, Brahms, and Smyth, all of whom were pianists, found ways to showcase the lyrical qualities of the cello alongside piano parts of concerto-level difficulty. While Beethoven’s blueprint for the cello-piano sonata influenced all these composers, they also created innovations to the form through their use of harmonically rich, dramatically expressive Romantic language. Nineteenth-century developments to virtuoso technique also made it possible to write increasingly difficult material in cello parts. The dedicatees of several of the sonatas in this chapter—Count Mateusz Wielhorski for Mendelssohn, Auguste Franchomme for Chopin, and Julius Klengel for Smyth—were among the celebrity virtuosos of their day.
‘The King[’s] Courts as the fountain of justice’ and the supremacy of ordinary law: implications for English arbitration
Authors: Clover Alcolea Lucas 
Published: September 2024

Abstract
English arbitration law is predicated on a uniquely close relation between the courts and arbitration with, historically, substantial interference and review by the former over the latter, although in recent decades statutory reform and ‘judicial legislation’ have curtailed this. Nevertheless, English arbitration law is almost unique among leading arbitration jurisdictions in permitting appeals on points of law, as well as emphasizing the importance of the law of the seat, and a consequent trenchant rejection of the possibility of delocalized arbitration. This article suggests that these idiosyncrasies flow from the twin English constitutional principles that ‘The King is the fountain of justice’ (although in practice this means the King’s Courts) and the supremacy of ordinary law and tribunals. These principles entail a concomitant individual right to petition the King’s Courts to remedy injustice and the subjection of everyone, no matter how rich or powerful, to the same law and courts. This, in turn, explains English reluctance to permit ousters of the Court’s jurisdiction, which persists even under the current pro-arbitration regime as regards vulnerable parties, and a rejection of the idea of ‘freedom from law’ whether on the part of state authorities or private parties such as arbitral tribunals.
Hidden hurts: life with lichen sclerosus – a patient’s perspective
Authors: Galentine Elena , Powers Camille M , McAleer Leah , Rivera Dixon Sydney , Mauskar Melissa M 
Published: September 2024

Teaser text
A patient with vulvar lichen sclerosus bravely shares her experiences living with this hidden, painful, life-altering and potentially stigmatizing vulvar condition. Complemented by a clinician’s perspective on the complexities of managing such patients, this piece aims to illuminate the many psychosocial challenges posed by lichen sclerosus. Through this dual narrative, we seek to deepen providers’ knowledge of the impact lichen sclerosus has on patients’ lives and the nuanced care required to support them.
Brain glycogen build-up measured by magnetic resonance spectroscopy in classic infantile Pompe disease
Authors: Najac Chloé , van der Beek Nadine A M E , Boer Vincent O , van Doorn Pieter A , van der Ploeg Ans T , Ronen Itamar , Kan Hermien E , van den Hout Johanna M P 
Published: September 2024

Abstract
Classic infantile Pompe disease is caused by abnormal lysosomal glycogen accumulation in multiple tissues, including the brain due to a deficit in acid α-glucosidase. Although treatment with recombinant human acid α-glucosidase has dramatically improved survival, recombinant human acid α-glucosidase does not reach the brain, and surviving classic infantile Pompe patients develop progressive cognitive deficits and white matter lesions. We investigated the feasibility of measuring non-invasively glycogen build-up and other metabolic alterations in the brain of classic infantile Pompe patients. Four classic infantile patients (8–16 years old) and 4 age-matched healthy controls were scanned on a 7 T MRI scanner. We used T2-weighted MRI to assess the presence of white matter lesions as well as 1H magnetic resonance spectroscopy and magnetic resonance spectroscopy imaging to obtain the neurochemical profile and its spatial distribution, respectively. All patients had widespread white matter lesions on T2-weighted images. Magnetic resonance spectroscopy data from a single volume of interest positioned in the periventricular white matter showed a clear shift in the neurochemical profile, particularly a significant increase in glycogen (result of acid α-glucosidase deficiency) and decrease in N-acetyl-aspartate (marker of neuronal damage) in patients. Magnetic resonance spectroscopy imaging results were in line and showed a widespread accumulation of glycogen and a significant lower level of N-acetyl-aspartate in patients. Our results illustrate the unique potential of 1H magnetic resonance spectroscopy (imaging) to provide a non-invasive readout of the disease pathology in the brain. Further study will assess its potential to monitor disease progression and the correlation with cognitive decline.
Investigating recovery after a spontaneous intracerebral haemorrhage in zebrafish larvae
Authors: Crilly Siobhan , Shand Isabel , Bennington Abigail , McMahon Emily , Flatman Daisy , Tapia Victor S , Kasher Paul R 
Published: September 2024

Abstract
Intracerebral haemorrhage is a debilitating stroke sub-type with high morbidity and mortality rates. For survivors, rehabilitation is a long process, and with no available therapeutics to limit the immediate pathophysiology of the haemorrhage, recovery is dependent on individual neuroplasticity. We have previously shown that zebrafish larvae can be used to model spontaneous brain haemorrhage. Zebrafish exhibit innate recovery mechanisms and are often used as a model system for investigation into regeneration after injury, including injury to the nervous system. Here, we investigate the spontaneous and immediate recovery in zebrafish larvae following an intracerebral haemorrhage at 2 days post-fertilisation, during pre-protected stages and over the first 3 weeks of life. We have shown that following the onset of bleed at ∼2 days post-fertilisation zebrafish are capable of clearing the haematoma through the ventricles. Brain cell damage associated with intracerebral haemorrhage is resolved within 48 h, and this recovery is associated with survival rates equal to wildtype and non-haemorrhaged sibling control animals. Larvae express more nestin-positive neural progenitor cells 24 h after injury when the most damage is observed, and through mass spectrometry analysis, we have determined that these cells are highly proliferative and may specially differentiate into oligodendrocytes. This study provides an insight into the haematoma resolution processes in a live, intact organism, and may suggest potential therapeutic approaches to support the recovery of intracerebral haemorrhage patients.
The Effects of Vaccination Status and Age on Clinical Characteristics and Severity of Measles Cases in the United States in the Postelimination Era, 2001–2022
Authors: Leung Jessica , Munir Naeemah A , Mathis Adria D , Filardo Thomas D , Rota Paul A , Sugerman David E , Sowers Sun B , Mercader Sara , Crooke Stephen N , Gastañaduy Paul A 
Published: September 2024

Abstract

Background
Despite high vaccine effectiveness, wild-type measles can occur in previously vaccinated persons. We compared the clinical presentation and disease severity of measles by vaccination status and age in the postelimination era in the United States.

Methods
We included U.S. measles cases reported from 2001 to 2022. Breakthrough measles was defined as cases with ≥1 documented dose of measles-containing vaccine, classic measles as the presence of rash, fever, and ≥1 symptoms (cough, coryza, or conjunctivitis), and severe disease as the presence of pneumonia, encephalitis, hospitalization, or death. Vaccinated cases with low- and high-avidity immunoglobulin G were classified as primary (PVF) and secondary (SVF) vaccine failures, respectively.

Results
Among 4056 confirmed measles cases, 2799 (69%) were unvaccinated, 475 (12%) were breakthrough infections, and 782 (19%) had unknown vaccination; 1526 (38%), 1174 (29%), and 1355 (33%) were aged &lt;5, 5–19, and ≥20 years, respectively. We observed a general decline in classic presentation and severe disease with an increase in the number of doses and fewer complications among children aged 5–19 years compared to other age groups. Among 93 breakthrough cases with avidity results, 11 (12%) and 76 (82%) were classified as PVF and SVF, respectively, with a higher proportion of PVFs having a classic measles presentation and severe disease than SVFs.

Discussion
Breakthrough measles cases tended to have milder disease with less complications. A small proportion of breakthrough infections were due to PVF than SVF. It is critical to maintain high measles-mumps-rubella vaccination coverage in the United States to prevent serious measles illnesses.