bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing hybrid and regular COVID-19 vaccine-induced immunity against the Omicron epidemic
Authors: Huang Lei , Lai Francisco Tsz Tsun , Yan Vincent Ka Chun , Cheng Franco Wing Tak , Cheung Ching Lung , Chui Celine Sze Ling , Li Xue , Wan Eric Yuk Fai , Wong Carlos King Ho , Hung Ivan Fan Ngai , Lau Chak Sing , Wong Ian Chi Kei , Chan Esther Wai Yin 
Published: December 2022

AbstractEvidence on the effectiveness of COVID-19 vaccines among people who recovered from a previous SARS-CoV-2 infection is warranted to inform vaccination recommendations. Using the territory-wide public healthcare and vaccination records of over 2.5 million individuals in Hong Kong, we examined the potentially differential risk of SARS-CoV-2 infection, hospitalization, and mortality between those receiving two homologous doses of BNT162b2 or CoronaVac versus those with a previous infection receiving only one dose amid the Omicron epidemic. Results show a single dose after a SARS-CoV-2 infection is associated with a lower risk of infection (BNT162b2: adjusted incidence rate ratio [IRR] = 0.475, 95% CI: 0.410–0.550; CoronaVac: adjusted IRR = 0.397, 95% CI: 0.309–0.511) and no significant difference was detected in the risk of COVID-19-related hospitalization or mortality compared with a two-dose vaccination regimen. Findings support clinical recommendations that those with a previous infection could receive a single dose to gain at least similar protection as those who received two doses without a previous infection.
A proof-of-concept study on the genomic evolution of Sars-Cov-2 in molnupiravir-treated, paxlovid-treated and drug-naïve patients
Authors: Alteri Claudia , Fox Valeria , Scutari Rossana , Burastero Giulia Jole , Volpi Sara , Faltoni Matteo , Fini Vanessa , Granaglia Annarita , Esperti Sara , Gallerani Altea , Costabile Valentino , Fontana Beatrice , Franceschini Erica , Meschiari Marianna , Campana Andrea , Bernardi Stefania , Villani Alberto , Bernaschi Paola , Russo Cristina , Guaraldi Giovanni , Mussini Cristina , Perno Carlo Federico 
Published: December 2022

AbstractLittle is known about SARS-CoV-2 evolution under Molnupiravir and Paxlovid, the only antivirals approved for COVID-19 treatment. By investigating SARS-CoV-2 variability in 8 Molnupiravir-treated, 7 Paxlovid-treated and 5 drug-naïve individuals at 4 time-points (Days 0-2-5-7), a higher genetic distance is found under Molnupiravir pressure compared to Paxlovid and no-drug pressure (nucleotide-substitutions/site mean±Standard error: 18.7 × 10−4 ± 2.1 × 10−4 vs. 3.3 × 10−4 ± 0.8 × 10−4 vs. 3.1 × 10−4 ± 0.8 × 10−4, P = 0.0003), peaking between Day 2 and 5. Molnupiravir drives the emergence of more G-A and C-T transitions than other mutations (P = 0.031). SARS-CoV-2 selective evolution under Molnupiravir pressure does not differ from that under Paxlovid or no-drug pressure, except for orf8 (dN > dS, P = 0.001); few amino acid mutations are enriched at specific sites. No RNA-dependent RNA polymerase (RdRp) or main proteases (Mpro) mutations conferring resistance to Molnupiravir or Paxlovid are found. This proof-of-concept study defines the SARS-CoV-2 within-host evolution during antiviral treatment, confirming higher in vivo variability induced by Molnupiravir compared to Paxlovid and drug-naive, albeit not resulting in apparent mutation selection.
A regime beyond the Hall–Petch and inverse-Hall–Petch regimes in ultrafine-grained solids
Authors: Zhang Huijun , Liu Feng , Ungar Goran , Zheng Zhongyu , Sun Qingping , Han Yilong 
Published: December 2022

AbstractThe strength of polycrystal increases as the grain diameter l decreases, i.e. the Hall–Petch behaviour. This trend reverses at about 3 < l < 15 nm, i.e. the inverse-Hall–Petch behaviour. How the grain size affects material’s strength at l < 3 nm (~12 particles) remains unclear. Here our simulations use mixtures of soft and hard particles so that compression can continuously reduce l to merely a few particles, resulting in ultrafine-grained solids termed as glass-crystal composites. Beyond the conventional Hall–Petch strengthening and inverse-Hall–Petch softening, we observe a power-law strengthening at l < 14 particles as a result of the blockage of shear-banding by crystalline grains. Amorphous and crystalline regions accommodate shear strains via bond-breaking and collective rotation, respectively. Moreover, a polycrystal–glass transition occurs at l = 14 particles featured with peaks of various quantities, which deepens the understanding on softening–strengthening transition.
Data-Driven Optimization of Energy Storage Allocation for Stable Outward Delivery in Wind and Solar Enrichment Region-A Case Study of Provincial Power Grid
Authors: Wang Bangyan , Wang Xiuli , Zhang Likai , Yuan Shengqi , Wang Shuai , Xin Chaoshan 
Published: December 2022

Abstract
The volatility and uncertainty of renewable energy sources aggravate the difficulties of power consumption balance in the new power system. One practical approach is to equip the grid with sufficient energy storage to reduce the operation risk. This paper focuses on a provincial grid with a heavy power outward delivery burden and its storage allocation problem. First, the optimization model with minimum storage allocation is established. Scenarios are constructed based on the typical set and the validation set. Second, a data-driven method is applied to build the typical set by k-means++. To describe the tolerance of wind and solar curtailed and delivery shedding, a chance-constrained approach is established and converted to linear constraints by big-M. The case study shows the power system needs considerable energy storage to ensure renewable energy consumption and delivery. With the lower tolerance, the allocated storage capacity will increase, and the lowest feasible tolerance is limited by scenarios with poor renewable output.
Research on Torque Current Error Control of PMSM Based on Model Predictive Control
Authors: Yan Hongliang , Zhang Kui , Xu Yuhao 
Published: December 2022

AbstractTo solve the problem that the torque pulsation is serious due to the large current error in the period when the duty cycle is calculated by the deadbeat method in the duty cycle dual-vector model predictive current control method, a vector switching method is proposed. The control objective of the proposed method is not to equate the predicted torque current with the reference value under the dead-beat idea, but to reduce the torque current control error by changing the switching time of the voltage vector and ensuring the symmetry of the positive and negative current errors. By deducing the duty cycle, the maximum current errors in a single control cycle before and after vector switching is compared and analyzed. The vector switching method is verified on the Simulink simulation platform and compared with the duty cycle double vector method. The results show that the vector switching method can effectively reduce the intra-cycle torque current tracking error and realize the optimal process control in each cycle.
Power Loss Analysis and Suggestions for Efficiency Improvement of Roof Distributed Photovoltaic System
Authors: Yang Guojin , Xue Yi , Wang Meng , Lv Junzhang , Yu Guangwen , Zhang Wei 
Published: December 2022

Abstract
With the gradual depletion of traditional fossil energy and the increasingly prominent environmental problems caused by it, China has proposed carbon peaking and carbon neutrality goals to promote the transformation of the energy structure. Solar energy is one of the important renewable energy sources, and roof-distributed photovoltaic power generation technology has a broad market prospect. Given the efficiency analysis of the roof-distributed photovoltaic power generation system, this paper first establishes an analysis model of the roof-distributed photovoltaic power generation system, analyzes the factors affecting the power loss of each link in detail, and further clarifies the distribution characteristics of the power loss of the system through simulation. Finally, some suggestions are put forward for the efficiency promotion of the roof-distributed photovoltaic power generation system.
Capacity Configuration Strategy of Hybrid Energy Storage System Considering Photovoltaic Power Fluctuation Suppression and Operation Optimization
Authors: Cui Shaofeng , Li Wei , Sui Hailin , Xu Yibin , Wang Baoxiang , Qi Weiping , Sun Shaoyang , Li Guo 
Published: December 2022

Abstract
Photovoltaic (PV) is becoming popular in many countries. However, due to the influence of weather, the PV output power often fluctuates greatly in a short time, and its intermittence makes it difficult to meet the load demand. The Hybrid energy storage system (HESS) can smooth the PV power fluctuation and optimize the operation of the whole system. Therefore, this paper proposes a capacity configuration strategy for the HESS composed of a battery and super capacitor. The strategy aims to minimize the construction and operation costs. It contains a two-layer optimization model. The upper layer configures the capacity and output power of the HESS, and the lower model optimizes the operation of the PV-HESS system and solves the model through deep reinforcement learning. Finally, a PV demonstration project in Shandong Province, China, is taken as an example to verify the effectiveness of the HESS capacity configuration strategy.
Condition Assessment Method of Electronic Transformer Based on High-dimensional Random Matrix
Authors: Liu Cencen , Xia Tian , Tuo Jing , Chen Zechun , Zhao Cong 
Published: December 2022

Abstract
The operation status of the transformer in the substation is changeable, and the evaluation index can not be determined, which leads to an increase in evaluation error. The evaluation method of the electronic transformer based on a high-dimensional random matrix is studied and analyzed. A comprehensive evaluation of the needs and standards and analysis of the evaluation characteristics are targeted to clear the evaluation index and calculate the threshold, build a high-dimensional random matrix state assessment model, and use the wide-area measurement processing method to achieve state assessment. The test results show that the final evaluation error of the method is only 0.82, which is well controlled below 1. It indicates that in the process of practical application, the evaluation speed is fast, the accuracy is high, and the links are simplified, which has practical application value.
Reliability Evaluation of Distribution Networks Considering the Randomness of Wind Turbine Outputs
Authors: Zheng Xin , Liu Jing , Peng Ganrong , Liu Chaonan , Pan Zhiyuan , Wang Jing 
Published: December 2022

Abstract
With more and more distributed generators integrated into the distribution networks, the uncertain outputs of distributed generators make the reliability evaluations of distribution networks harder to be handled. However, the existing studies such as the analytical method and simulation method cannot take into account the accuracy and calculation efficiency at the same time in a real time operation. So this paper proposes a reliability evaluation method for distribution networks considering the randomness of WT outputs. Firstly, based on the probability level of the WT outputs in different scenarios by prediction error of wind speed, the island division method under multi-scenario conditions is proposed. Then, the reliability of the distribution network with WTs is evaluated by the improved minimal path method. Finally, numerical simulations on the IEEE-RBTS 6 bus system show the superiority of the proposed algorithm over existing methods.
Spin-wave directional coupler based on the Bloch-type magnetic domain walls
Authors: Zhang Xiao , Zhang Chen , Zhao Jia 
Published: December 2022

Abstract
Domain walls (DWs) as waveguides of spin waves (SWs) have been used to study SWs propagation properties in ferromagnetic thin films. In this work, we present a spin-wave (SW) directional coupler based on two Bloch-type DWs for the first time with micromagnetic simulations. The distance between the DWs is 40 nm, and the magnetization orientation is is parallel at the central positions of the two magnetic DWs. Under the dipolar interaction, the lowest-width SW mode is split into symmetric and antisymmetric modes, and the SW coupling length L is characterized to be 469nm.
Research on Grid Information Model (GIM) Technology of Transmission Line Based on Full-area Feature Weight Template Matching Recognition
Authors: Liu Qi , Zhao Jian , You Poyu , Wu Sirui , Wang Di 
Published: December 2022

Abstract
Aiming at the problems of low efficiency, poor spatial location and incomplete attribute information in current transmission line modeling methods, a refined modeling method for transmission lines based on full area feature weighted template matching is proposed. First, collect the point cloud of the scary line, and extract the point cloud data of the tower and power line; Secondly, statistical outlier filter is used to denoise point cloud data; Finally, the GIM model of the transmission line is constructed by using the whole region feature weighted template matching method, which realizes the integrity and lightweight of the geometric, appearance and semantic information of the three-dimensional model of the transmission line, improves the efficiency of the transmission line modeling, and is verified by taking a 500kV transmission line as an example.
Icing Detection Method of Transmission Line Based on Machine Vision
Authors: Dai Linfeng 
Published: December 2022

Abstract
The conventional icing detection method is mainly based on the manual detection of icing status. The texture correlation characteristics of icing are variables, which lead to large errors in the icing edge detection and affect the subsequent maintenance of transmission lines. Therefore, the transmission line icing detection method based on machine vision is designed in this paper. The method comprises the following steps of extracting the icing texture feature of the transmission line, namely extracting the correlation feature of an icing image, identifying an icing area by using machine vision technology, carrying out edge detection on the transmission line and finally obtaining the icing thickness of the transmission line to realize the accurate detection on the icing of the power transmission line. The comparative experimental results show that the detection error of this method is small, the detection accuracy is high, and it can be applied to real life.
Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Constrained Particle Swarm Optimization
Authors: Chen Shuai , Kan Zhe 
Published: December 2022

Abstract
When the particle swarm is active, the robustness of the system is quite great, which is very useful for solving ill-conditioned problems like picture reconstruction. In the reconstructed image, however, the large number of pixels results in the large dimension of particles, making it harder for particles to attain the ideal solution during the optimization process. A constraint condition is applied to the position of particles to solve this problem. The image reconstruction algorithm regularized by Tikhonov is used as the particle position reference to constrain the particles to search within a certain range of the algorithm, and the penalty function is used to solve the problem to improve the particle search speed. For the inertia weight of particle swarm, this paper uses linear decreasing weight to realize its adaptive dynamic adjustment, which improves the flexibility of the algorithm. When chaos operator is added to the particle swarm location search process, if the particle is trapped in a local optimum, the chaos variable will fluctuate within a certain range, thus reducing the error rate of the optimal solution. The experimental comparison results illustrate that the modified particle swarm optimization technique for the image reconstruction of Electrical Capacitance Tomography outperforms the classic LBP and Tikhonov algorithms in terms of accuracy and efficiency.
Design concepts of a new imaging system for a high-intensity XUV source beam by colour centres excitation in lithium fluoride crystals
Authors: Al-Juboori Haider M. , Danylyuk Serhiy 
Published: December 2022

AbstractStable colour centre production in lithium fluoride (LiF) crystals can employ as a high-spatial-resolution imaging tool for extreme ultraviolet (XUV) irradiation, as well as the possibility for images of the unfocused beam and the beam focused by a multi-layer mirror.The LiF crystal sensitivity has sufficient to impress high-contrast photo-luminescent patterns with XUV single-pulse irradiation on an area up to 40mm2. The suggested imaging technique, using LiF as a detector, can contribute to reducing the lack of sufficient knowledge for XUV beam characterization and profile featurization which can open a very wide range of XUV metrology and tomography applications.The experimental results explain the concepts of detection of high-intensity source at13.5nm using a YAG:Ce scintillator crystal embedded with a CMOS camera, additionally using LiF as a 2D high-resolution detector, and the work shows investigations outcomes and improvement procedure and analysis.The results demonstrate the potential of LiF crystals as a sub-micrometre resolution two-dimensional imaging tool for XUV irradiation applications. Moreover, the research study explains the optimization sequences of the new imaging technique that will play an important role to predict the achievable spot size, geometry, beam profile and intensity distribution, as well as the characterization complexity of XUV source features.
Development of a Low-Cost Interrogation System Using a MEMS Fabry-Pérot Tunable Filter
Authors: Araújo João C. C. , Dias Bernardo , dos Santos Paulo S. S. , de Almeida J. M. M. M. , Coelho Luís C. C. 
Published: December 2022

Abstract
The interrogation of optic fiber sensors usually relies in complex and costly equipment with low portability due to their size such as Optical Spectrum Analyzers (OSA) or high-resolution spectrometers. Because of this, micro spectrometer devices, such as Micro-Electromechanical Systems (MEMS) with Fabry-Pérot tunable filters, are emerging as simpler and compact alternatives capable of being used to acquire spectral information in a wide wavelength band. In this work it is described the development of an interrogation system capable of infrared spectroscopy using a MEMS Fabry-Pérot Interferometer (MEMS-FPI) with a spectral response in the 1350nm to 1650nm range. Its performance is tested with the interrogation of long period fiber gratings both as a refractive index sensor and as a temperature sensor. Deconvolution techniques such as Wiener filtering are used to reduce the impact of the tunable filter’s impulse response in the measured signal. Results are comparable to those obtained using a typical OSA which shows the system’s potential as a cheaper and more transportable alternative.
Impact of Sm ions on microstructure and magneto-optical effects of Y2O3 ceramics obtained by arc plasma melting
Authors: Kruk Andrzej 
Published: December 2022

Abstract
Faraday materials based on transparent ceramics are regarded for high power magneto-optical isolators. Pure yttria ceramics with high transmittance were prepared using the raw oxide powders. To enhance the magneto–optical performance of the ceramics, samarium oxide were introduced to yttrium oxide matrix as a paramagnetic ions. The Sm-Y2O3 Faraday ceramic was melted above 2700 °C for 10 min. It is noted that as-prepared ceramic presents the highest in-line transmittance above 61.0% at the high spectrum range of wavelengths from 350 to 1110 nm. Physicochemical properties of the sample were characterized by means of numerous techniques. No secondary phase was detected from the sample using X-ray diffraction. The Verdet constant of Sm-Y2O3 ceramic at 532 nm is as high as 20 rad/m*T, which is higher than that of pure Y2O3 ceramic. The good optical quality and magneto-optical properties make Sm-Y2O3 ceramic an attractive magneto-optical material.
Listening plasmas in Laser-Induced Breakdown Spectroscopy
Authors: Cavaco Rafael , Rodrigues Pedro , Lopes Tomás , Capela Diana , Ferreira Miguel F. S. , Jorge Pedro A. S. , Silva Nuno A. 
Published: December 2022

Abstract
Apart from radiation, which constitutes the primary source of information in laser-induced breakdown spectroscopy, the process is accompanied by secondary processes such as shock wave generation and sound emission. In this manuscript, we explore the possibility of relating plasma properties with the sound from the shock waves in multiple materials, from metals to minerals. By analyzing the behavior of shock wave sound from homogeneous reference metallic targets, we investigate the relation between plasma properties and sound signal, demonstrating that distinct materials and plasma characteristics correspond to distinct plasma sound fingerprints.
Drying Patterns of Cerebrospinal Fluid as Indicator for Alzheimer’s Disease by a Machine Learning Framework
Authors: Arévalo Laura A. , O’Brien Stephen A. , Antonova Olga , Seifert Andreas 
Published: December 2022

Abstract
Cerebrospinal fluid contains specific biomarkers of Alzheimer’s disease that include amyloid beta peptides and tau proteins. In this work, we present for the first time possible evidence that the formation of the constituents of cerebrospinal fluid during drying is related with Alzheimer’s. We use machine learning to examine optical microscope images of dried cerebrospinal fluid patterns from patients with Alzheimer’s and healthy controls to create a diagnostic model. To analyze the images, the histogram of oriented gradients is used as a feature descriptor. Each image is mapped into the corresponding feature space, and principal component analysis is applied for dimensionality reduction. A machine-learning prediction model with a sensitivity of 82% was built. These promising preliminary results show great potential for new rapid and low-cost diagnostic pathways in the detection of Alzheimer’s disease.
Development of an Escherichia coli optical biosensor with computational validation
Authors: Dante A , Silva P H , Lopes R , Allil A , Sbano A , Esteves M E , Silva M , Werneck M , Allil R 
Published: December 2022

Abstract
The biosensor consists of an optical sensing system and an optoelectronic data acquisition system. The sensor’s optical system consists of a biochemically functionalized polymer optical fiber (POF-Plastic Optical Fiber) based on Field Evanescent technology. The Evanescent Field technique has been widely adopted in sensing and in this project, it was obtained by bending the fiber in a “U” shape, aiming to increase the sensitivity of the biosensor, through the contact of the curved sensor part with the sample biological. A data acquisition system was developed through an optoelectronic project aiming to increase the sensitivity when compared to a commercial equipment acquisition system. This work presents a biosensor for the detection of Escherichia coli based on an evanescent field with a polymer optical fiber linked to the analog signal acquisition system through an optoelectronic system developed. The interaction investigation of antibodies and antigens in Escherichia coli for computational methods was carried out in order to obtain information about the action of the antibody and in future steps applied in the validation of the diagnostic method.