bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vagal Nerve Stimulation in the Pediatric Population and Correlation between Family and Treatment Team Perspectives: Single-Center Experience
Authors: Alnaami Ibrahim , Algarni Abdullah , Alqahtani Saeed A. , Alqahtani Rawan M. , Jabbar Imtinan Al , Alhadi Wajd , Alnujaymi Bayan M. , Alahmari Seham A. , Asiri Dina , AlQahtani Asma M. , Otaif Mansour Y. 
Published: June 2024

Abstract
Background Vagal nerve stimulation (VNS) is an adjunctive therapy to pharmacologic treatment in patients with drug-resistant epilepsy. This study aimed to assess the efficacy of VNS therapy for seizure frequency reduction and improving the quality-of-life (QOL) measures in children with refractory epilepsy and to evaluate the correlation between the perspectives of families and those of the treating team.
Methods This was a prospective cohort study conducted at Abha Maternity and Children's Hospital, Saudi Arabia, from 2018 to 2022. A total of 21 pediatric patients who completed 1 year of follow-up after VNS implantation were included. Patients were aged between 2 and 14 years, with a mean age of 8.14 ± 3.92 years; 11 (52.4%) patients were females. Family and physician assessments were collected blinded to each other using the Clinical Global Impression of Improvement (CGI-I) scores and QOL assessments to evaluate the correlation between the families' and treating team's perspectives on VNS outcomes.
Results In this study, VNS showed significant efficacy in reducing the frequency of seizures. VNS significantly reduced the number of seizures per week from a baseline median of 35 to a median of 0.25 at the end of the follow-up period, representing a dramatic reduction of 99.3% (p < 0.001). The number of emergency department visits per year decreased from a baseline median of 12 to a median of 2, a reduction of 83.3% (p < 0.001), while the number of hospital admissions per year decreased from a baseline median of 3 to a median of 1, a 66.7% decrease (p < 0.001). The number of antiepileptic medications taken decreased from a median of four to three (p < 0.001). Notably, 28.57% of the patients achieved complete seizure freedom, and 38% exhibited significant improvement, with at least 50% reduction in seizure frequency. Importantly, none of the patients experienced an increase in seizure frequency following VNS treatment. The family and physician assessments showed varying degrees of alignment in perceptions, with “concentration” exhibiting a significant positive correlation (r = 0.498, p = 0.022), indicating noteworthy agreement, whereas verbal communication did not show a substantial correlation (r = − 0.062, p = 0.791), indicating a divergence of views.
Conclusion VNS is a promising and well-tolerated therapy for individuals with intractable seizures, offering clinical benefits and potential enhancements in various aspects of QOL. The varying perceptions between family and physician assessments highlight the importance of considering multiple perspectives when evaluating treatment outcomes.
68Ga-FAPI PET/CT versus 18F-FDG PET/CT: Differentiating Metastatic Disease and Reactive Lymph Nodes in a Case of Carcinoma of Breast/Acquired Immunodeficiency Syndrome
Authors: Gunasekaran Gopinathraj , Amalachandran Jaykanth 
Published: June 2024

AbstractGallium-68 (68Ga)-fibroblast activation protein inhibitor (FAPI) positron emission tomography (PET) images the cancer-associated fibroblast that forms a vital component of the tumor microenvironment. It is known that 68Ga-FAPI PET can aid in differentiating reactive lymph nodes from metastatic lymph nodes. 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) is still the most commonly used PET radiopharmaceutical in the evaluation of a wide range of malignancies including breast carcinoma. Reactive lymph nodes may also show FDG uptake which can hinder optimal assessment for metastatic involvement. We report an interesting case of invasive ductal carcinoma of the right breast with associated World Health Organization clinical stage I acquired immunodeficiency syndrome for which 18F-FDG PET/CT and 68Ga-FAPI PET/CT were done.
Studying the rotational dynamics of a meter stick using the Arduino board and 3D printed parts
Authors: Oliveira Vitor , Brazil Gustavo , Rodrigues Paulo , Almeida Pedro 
Published: June 2024

Abstract
We present a low-cost experimental apparatus designed for studying the rotational dynamics of a meter stick. This apparatus uses everyday laboratory supplies, 3D printed parts, and an Arduino board for data acquisition. It consists of a common bearing fixed to a vertical axle, connected to the meter stick through a 3D printed spindle adapter. A thread attached to a hanging weight and winded around the spindle applies a constant external torque to the stick. The moment of inertia of the apparatus may be changed by incorporating weights into the apparatus through 3D printed adapters. An Arduino board records the time interval between consecutive half turns of the stick, allowing the calculation of the angular displacement over time. The data collected from experiments is compared with theoretical models. Among others, the effect of the applied torque, air resistance and moment of inertia of the stick is studied. This experimental apparatus is particularly suitable for undergraduate students enrolled in a classical mechanics course, offering them a practical, hand-on experience while remaining cost-effective.
MIM waveguide refractive index sensor with graphene enhanced three-ring nested resonator Fano resonance
Authors: Qi Yunping , Wu Qilong , Su Mingrui , Li Hao , Wang Xiangxian 
Published: June 2024

Abstract
In this paper, a metal-insulator-metal (MIM) waveguide featuring a three-ring nested cavity structure is proposed. We enhance and optimize this design by integrating graphene nanostructures into the ferrule resonance cavity, resulting in a hybrid graphene-MIM waveguide structure. The transmission spectra and electric fields generated by the structure are analyzed by using the finite element method (FEM), shedding light on the formation mechanism of various Fano resonance peaks. The validity of our theoretical analysis is confirmed using multimode interference coupled mode theory (MICMT), and the simulation results are largely aligning with the theoretical verification results. Next, by manipulating the chemical potential of graphene, the Fano resonance can be tuned across a wide range of wavelength bands. And this capability enables the realization of a dynamically tunable refractive index sensor for transmission spectroscopy. Under optimized parameter settings, the refractive index sensor achieves a maximum sensitivity of

1266.67

nm
/
RIU
,

and a maximum figure of merit (FOM) value of

199.67

RIU

−
1

.

Compared with conventional MIM waveguide devices, this design overcomes the difficulty of conventional MIM waveguide structures that cannot be dynamically tunable. Notably, the wavelength of the Fano resonance formed by the transmission spectrum can be dramatically altered when the refractive index of the medium in the surrounding environment is slightly changed. Therefore, this structure expands the repertoire of integrated optical devices with potential applications, particularly in the field of optical sensors.
Feature engineering mediated machine learning prediction of high-frequency property of soft magnetic thin films
Authors: Mehmood Nasir , Wang Jianbo , Liu Qingfang 
Published: June 2024

Abstract
High-frequency applications including magnetic write heads, inductors, transformers and sensors etc, demand thin films with tremendous soft magnetic properties. In this regard, the resonance frequency of the soft magnetic thin films is of crucial importance which has a direct relation with material properties. Meanwhile, machine learning (ML) has recently evolved as an efficient tool for material designing tasks including material-property relationship. For an ML algorithm to efficiently perform such tasks, feature engineering is implemented, in which a set of descriptors is designed that can best represent the data. Here, we employ the ML technique, combined with data augmentation and feature engineering, for the estimation of the resonance frequency (f
r) value of thin films for high-frequency applications from different sets of theoretical and experimental features. Among the selected experimental features, when anisotropy field is combined with saturation magnetization, the ML model’s performance is improved, which is in line with the Kittel’s expression for f
r estimation. Finally, it is shown that the data augmentation can improve the training score, and reduce the mean squared error as well as bias of the models. The outcomes of this work are of key importance in paving the way for ML implementation in material-property analysis and time and cost-effective high-frequency device designing.
Recess-free enhancement-mode AlGaN/GaN RF HEMTs on Si substrate
Authors: Luan Tiantian , Huang Sen , Jing Guanjun , Fan Jie , Yin Haibo , Gao Xinguo , Zhang Sheng , Wei Ke , Li Yankui , Jiang Qimeng , Wang Xinhua , Hou Bin , Yang Ling , Ma Xiaohua , Liu Xinyu 
Published: June 2024

Abstract
Enhancement-mode (E-mode) GaN-on-Si radio-frequency (RF) high-electron-mobility transistors (HEMTs) were fabricated on an ultrathin-barrier (UTB) AlGaN (<6 nm)/GaN heterostructure featuring a naturally depleted 2-D electron gas (2DEG) channel. The fabricated E-mode HEMTs exhibit a relatively high threshold voltage (V
TH) of +1.1 V with good uniformity. A maximum current/power gain cut-off frequency (f
T/f
MAX) of 31.3/99.6 GHz with a power added efficiency (PAE) of 52.47% and an output power density (P
out) of 1.0 W/mm at 3.5 GHz were achieved on the fabricated E-mode HEMTs with 1-µm gate and Au-free ohmic contact.
Phase-locked single-mode terahertz quantum cascade lasers array
Authors: Xu Yunfei , Li Weijiang , Ma Yu , Lu Quanyong , Zhang Jinchuan , Zhai Shenqiang , Zhuo Ning , Liu Junqi , Liu Shuman , Cheng Fengmin , Wang Lijun , Liu Fengqi 
Published: June 2024

Abstract
We demonstrated a scheme of phase-locked terahertz quantum cascade lasers (THz QCLs) array, with a single-mode pulse power of 108 mW at 13 K. The device utilizes a Talbot cavity to achieve phase locking among five ridge lasers with first-order buried distributed feedback (DFB) grating, resulting in nearly five times amplification of the single-mode power. Due to the optimum length of Talbot cavity depends on wavelength, the combination of Talbot cavity with the DFB grating leads to better power amplification than the combination with multimode Fabry−Perot (F−P) cavities. The Talbot cavity facet reflects light back to the ridge array direction and achieves self-imaging in the array, enabling phase-locked operation of ridges. We set the spacing between adjacent elements to be 220 μm, much larger than the free-space wavelength, ensuring the operation of the fundamental supermode throughout the laser's dynamic range and obtaining a high-brightness far-field distribution. This scheme provides a new approach for enhancing the single-mode power of THz QCLs.
Complementary memtransistors for neuromorphic computing: How, what and why
Authors: Chen Qi , Zhou Yue , Xiong Weiwei , Chen Zirui , Wang Yasai , Miao Xiangshui , He Yuhui 
Published: June 2024

Abstract
Memtransistors in which the source−drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing. On the other side, it is known that the complementary metal-oxide-semiconductor (CMOS) field effect transistors have played the fundamental role in the modern integrated circuit technology. Therefore, will complementary memtransistors (CMT) also play such a role in the future neuromorphic circuits and chips? In this review, various types of materials and physical mechanisms for constructing CMT (how) are inspected with their merits and need-to-address challenges discussed. Then the unique properties (what) and potential applications of CMT in different learning algorithms/scenarios of spiking neural networks (why) are reviewed, including supervised rule, reinforcement one, dynamic vision with in-sensor computing, etc. Through exploiting the complementary structure-related novel functions, significant reduction of hardware consuming, enhancement of energy/efficiency ratio and other advantages have been gained, illustrating the alluring prospect of design technology co-optimization (DTCO) of CMT towards neuromorphic computing.
Surface modification of W–Ta–V–Cr multi-component alloy after low-energy He plasma irradiation
Authors: Yin Chao , Gao Zeshi , Li Yangyang , Wang Zhaofan , Li Long , Chen Ze , Sun Xia , Mao Shifeng , Ye Minyou 
Published: June 2024

Abstract
This study explores a hypothetical scenario where low-activation refractory multi-component alloys (RMCAs) are considered for use as divertor target materials in fusion reactors. To investigate the surface modifications under divertor service conditions, a multi-phase W–Ta–V–Cr RMCA is irradiated with low-energy helium (He) plasma at varying temperatures to approximately 5.0 × 1025 He·m−2. The W-rich and Cr-rich phases in the multi-phase RMCA mimic the mono-phase W–Ta–V–Cr RMCA and segregation at grain boundaries, respectively. Following irradiation, fuzz layer formation is observed for all phases at temperatures lower than pure W requires. Additionally, nano He bubbles are identified in the fuzz tendrils at 920 °C. The modified layers exhibit reduced V and Cr content with increasing temperature, transitioning into W-Ta binary alloys at 920 °C. Notably, the fuzz layer on the W-rich phase is thinner than that on pure W at 920 °C. While a thinner fuzz layer suggests the alloy’s potential as a divertor target material, challenges include a lower fuzz formation temperature and potential high V and Cr sputtering yield, raising concerns for plasma contamination during fusion reactor operation. This dual perspective highlights both the promise and challenges of utilizing RMCAs as divertor target materials in severe fusion reactor environments.
Current and Future Trends of Electricity Service in South Sudan
Authors: Amogpai Ater Y. 
Published: June 2024

Abstract
Electricity service is the main driver for social and economic development. Readers and decision-makers need access to reliable and accurate data in this sector. South Sudan is one of the eastern African countries with the least access to electricity globally. Four sites in the central equatoria state where the Capital City Jubal is located were identified to develop large hydropower plants (LHP) to improve the country’s poor access to electricity. However, the initial cost of the LHP is high and takes many years to build; thus, small hydropower plants (SHP) are introduced as they can be made in a shorter time and can urgently deliver electricity to needed locations. Solar energy systems can also be utilized to electrify rural and urban areas. This paper aims to provide the reader and decision-makers with information about electricity services in South Sudan. The paper explains the current and future status of the electricity service and contributes to sustainable development in the country’s electricity supply reliability. The paper further recommends that decision-makers in the field of electricity better implement the proper practices and avoid malpractices in the electricity service.
Feasibility and Techno-Economic Assessment of a 128kWp Grid-Tied SPV System using HOMER Pro
Authors: Khan Akhlaque Ahmad , Minai Ahmad Faiz , Siddiqui Mohammad Atif 
Published: June 2024

Abstract
A substantial amount of the world’s annual CO2 emissions are attributable to the continued consumption of electricity from the grid that is generated from burning fossil fuels. Renewable energy sources could strengthen grid reliability and lessen their effect on the environment, especially in high-demand regions prone to power failures. Investigating the viability of erecting solar power plants in a subtropical area to provide the necessary electricity for an educational building that operates mainly during daylight hours is the main intent of the present study. The purpose of this investigation is to demonstrate and validate a model for enormous-scale commercial HRES applications (such as an educational institution) utilising the HOMER programme to figure out the optimal size. Minimising emissions of carbon dioxide, the main greenhouse gas responsible for accelerating global warming, is also of the utmost importance. Based on the simulation findings, the optimal system configuration consisted of a 120 kW converter and 400 PV arrays (each with 320 Wp = 128 kWp). For regional power generation, the most cost-effective choice is still a combination of solar panels and the grid. Findings show that a HRES can be economically feasible for installation in educational institutions at an initial capital cost of USD $0.068 million with annual operating expenses of USD $0.0447 million—a reduction of 44.11% compared to the existing system. The expected payback for this endeavour is five years. Other locations with identical climates could benefit from these results when considering the deployment of comparable technology. In order to help achieve a zero-carbon target, financial rewards could encourage governments to adopt similar schemes.
Research on distribution network restoration based on ant colony algorithm
Authors: Yuan Jianxiang , Yi Xin , Zeng Weihe , Wang Zicheng , Li Xin 
Published: June 2024

Abstract
Distribution automation is a necessary means and shortcut to improve the reliability, safety, and service quality of power supply in distribution networks, improve work efficiency, and reduce operating costs. This article uses the ant colony algorithm to study the problem of distribution network fault recovery strategy and proposes a distribution network fault recovery strategy algorithm based on the ant colony algorithm. Established a mathematical model for fault recovery in distribution networks; Using random spanning tree theory to control ants to search within feasible solution domains, and the ant routing rules and pheromone update strategies were provided, and the correctness of the method was verified through simulation.
Safety and energy saving dispatching method of large power grid considering demand response
Authors: Zhao Yulin , Li Lanqing , Wang Bolun , Wang Yuyang , Lv Xingyue 
Published: June 2024

Abstract
To improve the energy-saving effect of power grids, a safe and energy-saving dispatching method for large power grids considering demand response is proposed. From the perspective of grid load, power generation capacity, transmission capacity, and energy supply, the demand response of grid energy-saving dispatching is analyzed. This paper also conducts research on energy-saving dispatch of the power grids based on the analysis results and from the perspective of loss control. The experimental results show that the operation efficiency of the distribution network has been significantly improved after the dispatching method in this paper, which shows that the large power grid security and energy-saving dispatching method considering demand response has high practicability.
A method for detecting the status of secondary pressing plate in substation based on electrical analog quantity and rule library
Authors: Zeng Hongyu , Guo Haisheng , Wu Junfeng , Xu Tao , Zhang Yong , Xia Hui 
Published: June 2024

Abstract
A method for detecting the status of secondary pressure plates in substations based on electrical analog quantities and rule libraries is proposed to address the issues of time-consuming and erroneous manual verification during secondary pressure plate status detection. By using Hall sensors, the electrical analog quantity of the secondary pressure plate is collected in real time and then input into the secondary pressure plate state detection model based on confidence rule library inference. This model takes the electrical analog quantity status of the secondary pressure plate as the result attribute. It aims to calculate and merge the reference level confidence of each state in the result attribute and prerequisite attribute, and complete the detection of the pressure plate status. The gradient descent method is introduced to optimize the model by setting confidence rule weight coefficients, prerequisite attribute weight coefficients, and inference confidence of the pressure plate state, which can minimize the error between the pressure plate state detection results and the expected results to optimize the detection performance of the model. After verification, this method is embedded in the intelligent pressure plate management system and can complete 120 pressure plate status detection tasks in just 0.1 hours, with accurate pressure plate status detection.
Feature extraction and clustering of electricity market data based on GCN and graph filtering
Authors: Huang Longda , Xu Pan , Weng Liguo 
Published: June 2024

Abstract
As the power grid undergoes transformation and the Internet’s influence grows, the electricity market is evolving towards informatization. Traditional power marketing methods struggle to cope with the vast and intricate data of the modern power market. To address this challenge, this study employs random forest and PBF models for processing electricity market data. Additionally, it introduces the spectral clustering algorithm for a comprehensive analysis. The experimental results successfully extract diverse electricity consumption characteristics. This approach aids in advancing the informatization of power grid enterprises, boosting their capacity to perceive power data, and furnishing decision-makers with dependable support.
The Method for smart grid false data injection attack detection based on multilevel fingerprint identity authentication
Authors: He Wei , Wen Chenglin , Liu Weifeng 
Published: June 2024

Abstract
With the rapid development of Cyber-Physical Systems (CPS), security concerns have increasingly garnered attention. This paper focuses on the security threats faced by smart grid systems, particularly false data injection (FDI) attacks, and proposes a multilevel fingerprint identity authentication method to provide effective security for the operation of smart grids. Firstly, we construct a mathematical model of the smart grid by using harmonics and direct current attenuation components to establish a foundation for subsequent feature extraction and matching authentication. Secondly, a multi-granularity feature approach is utilized to represent the model in multiple levels and extract feature information granularity, thereby enhancing the system’s ability to detect attack signals. In addition, we employ the gap measurement method to perform multi-scale matching of the granularity information of sensor data with that of the data security repository, to detect attack signals. Finally, experimental results confirm that this method effectively detects FDI attacks, improves detection accuracy while ensuring real-time detection, and realizes the safe and reliable operation of smart grid systems.