bluuebunny/crossref_metadata_2025 huggingface dataset:
A chloric polycation binder enables rapid ionic transport in thick electrodes of high-energy aluminum-ion batteries
Authors: Li Jingwen , Ma Chengyun , Geng Xinle , Tuo Yongxiao , Sun Ruoxuan , Du Huiping , Lin Meng-Chang , Cai Mian
Published: April 2023

A chloric polycation binder, which can facilitate fast AlCl4−transport, is investigated for thick cathode of aluminum-ion battery, achieving improved area-specific capacity, rate capability, energy efficiency, and long-term cycling stability.
Revealing the underlying solvent effect on film morphology in high-efficiency organic solar cells through combinedex situandin situobservations
Authors: Ma Ruijie , Jiang Xinyu , Fu Jiehao , Zhu Tao , Yan Cenqi , Wu Kexin , Müller-Buschbaum Peter , Li Gang
Published: April 2023

Here the aggregation behavior differences induced by solvent–material and material–material interactions are clearly revealed by the combinedex situandin situmorphology characterization studies on representative high-efficiency OPV systems.
Hydrothermal synthesis of zeolites using silica extracted from tropical volcanic ash
Authors: Otieno Stephen O. , Kengara Fredrick O. , Kowenje Chrispin O. , Mokaya Robert
Published: April 2023

Tropical volcanic ash is a cheap and sustainable source of high purity silica for the synthesis of zeolites; the zeolite type, whether Na–X, Na–P or hydroxysodalite, depends on the amount of SiO2and Na2O in the synthesis hydrogels.
Photo-assisted electrochemical CO2reduction at a boron-doped diamond cathode
Authors: Iwai Goki , Fiorani Andrea , Du Jinglun , Einaga Yasuaki
Published: April 2023

A photo-assisted electrochemical system converting CO2into formic acid by photoelectrochemical water oxidation at TiO2nanotubes coupled with electrochemical CO2reduction at boron-doped diamond.
A symmetric adaptive visibility graph classification method of orthogonal signals for automatic modulation classification
Authors: Bai Haihai , Yang Jingjing , Huang Ming , Li Wenting
Published: April 2023

Visibility graph methods allow time series to mine non‐Euclidean spatial features of sequences by using graph neural network algorithms. Unlike the traditional fixed‐rule‐based univariate time series visibility graph methods, a symmetric adaptive visibility graph method is proposed using orthogonal signals, a method applicable to in‐phase and quadrature (I/Q) orthogonal signals for adaptive graph mapping for radio modulated signals in automatic modulation classification tasks. The method directly models the intra‐channel and inter‐channel graph relations of I/Q signals using two different types of convolutional kernels. It captures non‐Euclidean spatial feature information of I/Q signals using a graph neural network combining graph sampling aggregation and graph differentiable pooling as a feature extractor. Extensive experimental results on two benchmark datasets and a simulated dataset containing channel fading show that the proposed Quadrature Signal Symmetric Adaptive Visibility Graph (QSSAVG) method in this paper outperforms the benchmark method in terms of classification accuracy and is also more robust against channel fading and noise variations.
Cross‐class pest and disease vegetation detection based on small sample registration
Authors: Jiayao Liu , Linfeng Wang , Yunsheng Wang , MingMing An , Wenfei Jiang , Shipu Xu
Published: April 2023

This paper introduces few‐shot anomaly detection (FSAD), a practical and less anomaly detection (AD) method, which can provide a limited number of normal images for each class during training. So far, studies on FSAD have been carried out according to each model, and there is no discussion of commonalities between different types. Depending on how people detect unusual lies, the problematic images are compared to the normal ones. The image alignment method based on different classifications is used to train the target detection model independent of classification, and performed ablation experiments on the pest and disease datasets in different environments for verification. This is the first time the FSAD method has been used to train a single scalable model without the need to train new classifications or adjust parameters. The experimental results show that the application of AUC based on vegetation disease data set and vegetation pest data set in FSAD algorithm is improved by 19.5% compared with the existing algorithm.
A multiple spatio‐temporal features fusion approach for short‐term passenger flow forecasting in urban rail transit
Authors: Yu Qian , Zhang Yadong , Guo Jin , Ma Wengang , Liu Ruiqi , Lai Pei
Published: April 2023

Timely and precise short‐term passenger flow forecasting (STPFF) is a key to intelligent urban rail transit (URT) operation. The uncertainty of passenger travel behaviors leads to passenger flow data showing high nonlinearities and complex spatio‐temporal correlation. Therefore, the ability to capture such correlations determines the prediction performance of the model. However, current methods either consider only the physical topology of URT network or lack the ability to model global spatial dynamics, making it difficult to obtain satisfactory predictions. Therefore, a Multiple Spatio‐Temporal Features Fusion (MSTFF) network is proposed for STPFF in URT networks. Specifically, the connectivity and passenger flow similarity relationships in URT networks are encoded as physical adjacency graph and virtual functional similarity graph, respectively, and then these two complementary graphs are input into two designed Residual Graph Convolutional Gated Recurrent Unit (RGCGRU) modules to extract their spatio‐temporal features. Second, an Attention‐based Gated Recurrent Unit (AGRU) module is designed to capture global dynamic evolutionary trends in both spatial and temporal dimensions. Finally, a fully connected neural network is used to fuse these features. Experiments on two real passenger flow datasets of URT show that MSTFF performs well on various prediction tasks (15, 30, 45, and 60 min).
Driver distraction detection via multi‐scale domain adaptation network
Authors: Wang Jing , Wu ZhongCheng
Published: April 2023

Distracted driving is the leading cause of road traffic accidents. It is essential to monitor the driver's status to avoid traffic accidents caused by distracted driving. Current research on detecting distracting behaviours focuses on analysing image features using convolutional neural networks (CNNs). However, the generalisation ability of the current distracted driving models is limited. This paper aims to improve the generalisation ability of distracted driving models that are affected by factors such as the driver himself, the background, the monitoring angle, and so on. A new driver distraction detection method, which is referred to as multi‐scale domain adaptation network (MSDAN), was proposed to improve model adaptability. The method consists of three stages: first, multi‐scale convolution was introduced to build a new backbone to accommodate better the valuable feature of the target on different scales. Secondly, the authors designed the domain adaptation network to improve the model's adaptability to the difference in data sources through adversarial training. Finally, dropout is added to the fully connected layer to increase the model's generalisation ability. The comparison results on the large‐scale driver distraction detection dataset show that the authors’ method can accurately detect driver distraction and has good generalisation performance, with an accuracy improvement in the cross‐driver and cross‐dataset experiments.
A generalized space shift keying modulation for molecular MIMO systems
Authors: Ahuja Muskan , Bhatnagar Manav R.
Published: April 2023

Index modulation utilizes spatial dimensions for transmission of information in multiple‐input multiple‐output (MIMO) molecular communication systems. Molecular space shift keying (MSSK) is an IM‐based technique that modulates information in the antenna index and efficiently combats both intersymbol interference and interlink interference in molecular MIMO systems. In this paper, generalized form of the MSSK scheme, that is, generalized MSSK (GMSSK) is proposed which activates a fixed number of antennas for information transmission. The antenna constellation is selected judiciously to minimize the chances of errors in the proposed GMSSK strategy. Design guidelines are provided for the GMSSK antenna constellation for the case of two activated antennas at the transmitter side. Exploiting an additional degree of freedom, the presented GMSSK scheme is shown to achieve reasonably close or better error performance with a smaller antenna array size as compared to the traditional MSSK scheme.
Understanding the trans-Neptunian Solar System
Authors: Shannon Andrew , Doressoundiram Alain , Roques Françoise , Sicardy Bruno , Kral Quentin
Published: April 2023

The most pristine remnants of the Solar System planet formation epoch orbit the Sun beyond Neptune. These are the small bodies of the trans-Neptunian object populations. The bulk of the mass is distributed in ~100 km objects, but objects at smaller sizes have undergone minimum collisional processing. The New Horizons mission recently revealed that the body (486958) Arrokoth, with its effective diameter of ~20 km, appears to be a primordial body and not a collisional fragment. This indicates that bodies at these (and perhaps smaller) sizes retain a record of how they were formed, and they are the most numerous record of this epoch. However, it is impractical to find these bodies with optical surveys because their brightnesses are very low. Their presence can be inferred from the observed cratering record of Pluto and Charon, and it can be directly measured by serendipitous stellar occultations. These two methods produce contradicting results: occultations measure roughly ten times the number of about kilometer-size bodies as are inferred from the cratering record. We used numerical models to explore how these observations can be reconciled with evolutionary models of the outer Solar system. We find that models in which the initial size of the bodies decreases with increasing semimajor axis of formation and models in which the surface density of the bodies increases beyond the 2:1 mean-motion resonance with Neptune can produce both sets of observations, but a comparison to various observational tests favours the former mechanism. We discuss how the astrophysical plausibility of these solutions can be evaluated, and we conclude that extended serendipitous occultation surveys with a broad sky coverage are the most practical approach.
Contribution des résidus de culture à la réduction du déficit alimentaire des troupeaux de ruminants dans l’Ouémé Supérieur au Bénin
Authors: Djohy Gildas Louis , Sounon Bouko Boni , Djohy Georges , Dossou Paulin Jésutin , Yabi Jacob Afouda
Published: April 2023

L’utilisation de la biomasse des résidus de cultures présents sur les exploitations agricoles après les récoltes est importante pour alimenter les animaux durant la saison sèche. La présente étude vise d’une part à estimer la biomasse des résidus au champ, et d’autre part à analyser la capacité de charge qui en résulte dans l’Ouémé Supérieur au Bénin. Des enquêtes ont été réalisées auprès d’agriculteurs et d’éleveurs, ainsi que des mesures de biomasses de résidus. Trois cents éleveurs ont été interrogés sur l’importance, la durée d’utilisation et les modes d’accès aux résidus. Puis, 350 placettes de 5 × 5 m ont été installées dans une sélection de champs, dont 175 en 2020 et 175 en 2021. Les résultats montrent que les quantités de résidus disponibles à l’hectare varient selon les cultures et les années. En 2020, les quantités mesurées sont les suivantes : 5,3 t de Matière Sèche/ha pour le maïs ; 6,7 t MS/ha pour le sorgho ; 3,4 t MS/ha pour le riz ; 2,3 t MS/ha pour le niébé ; 2,0 t MS/ha pour le soja ; 1,0 t MS/ha pour l’arachide ; 1,0 t MS/ha pour le voandzou. En 2021 : 4,4 t MS/ha pour le maïs ; 5,3 t MS/ha pour le sorgho ; 3,2 t MS/ha pour le riz ; 2,1 t MS/ha pour le niébé ; 2,0 t MS/ha pour le soja ; 1,1 t MS/ha pour l’arachide ; 1,1 t MS/ha pour le voandzou. Le bilan entre la capacité de charge calculée à partir des résidus et la charge animale réelle est négatif sur les deux années d’étude. Les résidus ont couvert potentiellement 77 % (2020) et 66 % (2021) des besoins alimentaires du bétail entre décembre et février. La prise en compte de ces résultats dans l’élaboration des politiques agricoles et pastorales contribuerait à mieux gérer l’ensemble des ressources fourragères disponibles pour le bétail.
REactor Safety Analysis ToolboX RESA-TX
Authors: Cuesta Alejandra , Palazzo Simone , Wenzel Stefan , Kerner Alexander
Published: April 2023

The REactor Safety Analysis ToolboX RESA-TX is a software and data package in development that combines the automatisation of all established procedures for deterministic safety analysis (DSA), the integration of expert know-how and a large database including the most relevant information required for conducting a DSA. In the current state of the art, DSA is a complex and thus error-prone process that is highly time-consuming and repetitive. The reliability of the result is strongly dependent on the availability of plant data and expert know-how. The idea of developing the RESA-TX toolbox arose at GRS to cope with these conditions. The innovative approach proposes an automated and standardised procedure, supported by a large database of plant design characteristics, plant behaviour, regulatory rules and DSA expert knowledge incorporated within the tool. Its application allows the end user to automatically generate and verify an input deck, as well as conduct design basis accident (DBA) calculations for a certain design with highly reduced manual intervention. The databases can be extended depending on available information or other boundary conditions. A heuristic approach is integrated into the model generation process, where users often suffer from a lack of information about the facility under consideration. These heuristics can be replaced when higher information quality is available or enhanced over time, which can lead to more reliable results with increasing usage of the tool. As a result, the application of RESA-TX could highly increase the efficiency of the DSA process, reducing both repetitiveness as well as user-induced errors. This in return will lead to an improvement in the quality of the analysis and reliability of the results. In consequence, RESA-TX will allow for a DSA to be conducted more frequently in situations where time or budget was a limitation before, thereby contributing to an increase in reactor safety.
Iatrogenic Complications and Management of Biliary Interventions
Authors: Martens Spencer , Karani Kunal , Navuluri Rakesh
Published: April 2023

Iatrogenic complications can result from both diagnostic and therapeutic hepatobiliary interventions such as percutaneous transhepatic cholangiography, percutaneous biliary drain placement, percutaneous liver biopsy, transarterial liver-directed therapies for malignancy, and liver transplantation. In many of these procedures, the proximity of the biliary ductal system to the hepatic arteries and portal veins predisposes to injury. In other procedures, compromised arterial supply to the biliary system, errors related to complexity of the procedures, or the fragility of the structures themselves may be the root cause. Understanding the etiology of these iatrogenic complications as well as the management options is essential for a multidisciplinary team tasked with managing patients with complex hepatobiliary diseases.
A supranational solidaristic space? Comparative appraisal of determinants of individual support for European solidarity in the COVID-19 era
Authors: Russo Luís
Published: April 2023

COVID-19 created profound shockwaves across the Union, pushing supranational crisis policymaking to the forefront of European politics and fostering an unprecedented expansion in fiscal solidarity with which to support the economic recovery ahead. This development lends pertinence to a contemporary reappraisal of the main determinants underlying individual support for European solidarity and its implications to the consolidation of a political basis for a supranational solidaristic space. Using an original large-N survey dataset and employing a fixed-effects linear regression analysis, this paper empirically reviews ideal-type theoretical predictions for individual support for European solidarity by conducting a comparative assessment of their correlates' explanatory power in the new pandemic context. First, I contend individuals reason in supranational terms as key political attitudes driving individual support for cross-border solidarity are informed directly at the supranational level, consubstantiating the claim that European redistribution operates as a distinct legitimate space for solidarity in its own right. Second, I argue that utilitarian motivations linked to expectations of material amelioration are better predictors of support for solidarity than cultural explanations emphasising national identity or attitudes towards immigration. Third, I suggest that preferences concerning European solidarity are better captured by political divides over economic redistribution rather than over cultural concerns, but only among more cosmopolitan-oriented individuals. In any event, cultural factors are still relevant predictors of support for solidarity, particularly among nationalists. The final section interprets these findings by discussing how the correspondence between public expectations and institutional supply of supranational redistributive instruments to respond to the pandemic may contribute to strenghten political support for European solidarity and the EU polity itself.
Prediction method of blast load on underground structure surface based on neural network
Authors: Liu Fei , Zhang Zhao , Gao Yonghong , Xin Kai , Yan Minhua , Huang Xu , Duan Yapeng , Huang Chaoyuan
Published: April 2023

The dynamic load in the soil directly leads to the damage of underground structures upon explosions. In this study, a method to predict blast load on underground structure surface based on the neural network was developed to study the load distribution under close-in detonation. First, taking the underground utility tunnel as the experimental structure, 52 groups of field blast tests were conducted on the surface load mechanism, and the surface load data samples were obtained. Second, the key influencing parameters of the reflected blast load were obtained through the dimensional analysis method, and the backpropagation neural network model was constructed based on the test data using the Levenberg–Marquardt algorithm to train and optimize the neural network. Finally, the accuracy of load prediction results was compared and evaluated among the neural network, empirical formula, and nonlinear regression analysis (NRA) methods. It is found that the input parameters of combined variables can further improve the prediction accuracy of the neural network compared with the input parameters of single physical variables. Compared with the empirical formula method and the NRA method, the neural network model with input parameters of combined variables provided the most accurate prediction. The load distribution under typical conditions calculated by the neural network showed that the explosive setting parameters impact the uneven shape of blast load on the structure surface. The increase in explosive equivalent and depth reduces the nonuniformity of load distribution, while the decrease in explosion distance increases the nonuniformity of load distribution.
Three orders of magnitude enhancement of second and third harmonic generation in the visible and ultraviolet ranges from plasmonic gold nanogratings
Authors: Mukhopadhyay S. , Rodriguez-Suné L. , Cojocaru C. , Vincenti M. A. , Hallman K. , Leo G. , Belchovski M. , de Ceglia D. , Scalora M. , Trull J.
Published: April 2023

We report experimental observations and numerical simulations of second and third harmonic generation from a gold nanograting, which exhibits a plasmonic resonance in the near infrared. The resonance is tunable, with a spectral position that depends on the angle of incidence. All things being equal, the enhancement of nonlinear optical processes produced by the field localization in the nanograting when compared with a flat gold mirror manifests itself dramatically from the ultraviolet to the visible range: second harmonic generation conversion efficiencies increase by more than three orders of magnitude, while we report a third harmonic generation conversion efficiency enhancement factor of 3200, both in excellent agreement with our theoretical predictions. The clear inferences one may draw from our results are that our model describes the dynamics with unprecedented accuracy and that much remains to be revealed in the development of nonlinear optics of metals at the nanoscale.
Broadband phase-modulated metasurface based on vanadium dioxide patches in microwave band
Authors: Ma Y. L. , Wan W. P. , Wang Z. B. , Chen Q. , Zheng Y. J. , Guo T. T. , Shuai C. Y. , Fu Y. Q.
Published: April 2023

Phase-modulated metasurfaces (PMMs) have attracted considerable attention because of their widespread application in many fields. However, the most existing PMMs are only available in a relatively narrow band. In this paper, we propose a design of a broadband PMM based on vanadium dioxide (VO2) patches. The unit cell of the proposed PMM is composed of a surface layer supported by a 0.5 mm F4B with a dielectric constant of εr = 2.65, and a dielectric layer with a metal ground on its back. The surface layer consists of two opposite T-shaped metal patches connected by a VO2 patch. The VO2 patch can be used as an active element due to the insulator-to-metal transition of VO2. The process of phase transition is achieved by direct heating with a heating plate, without additional feeders affecting the performance of the PMM. The designed PMM can achieve a broadband phase difference within 180° ± 37° from 6.94 to 20.84 GHz, with a fractional bandwidth of 100%. Both full wave simulation and measurement results show that the proposed metasurface presents a good phase reconstruction performance over a wideband frequency range.
Non-volatile logic-in-memory ternary content addressable memory circuit with floating gate field effect transistor
Authors: Cho Sangki , Kim Sueyeon , Choi Insoo , Kang Myounggon , Baik Seungjae , Jeon Jongwook
Published: April 2023

Due to the limitations of the currently widely used von Neumann architecture-based computing system, research on various devices and circuit systems suitable for logic-in-memory computing applications has been conducted. In this work, the silicon-based floating gate memory cell transistor structure, which has been attracting attention as a memory to replace the dynamic random access memory or NAND Flash technology, was newly recalled, and its applicability to logic-in-memory application was confirmed. This floating gate field effect transistor (FGFET) has the advantage that the compatibility of the existing silicon-based complementary metal–oxide–semiconductor (CMOS) process is far superior to that of logic-in-memory application devices to which materials with new memory characteristics are applied. At the 32 nm technology node, which is the front node to which the planar MOSFET structure is applied, an analysis environment that can simultaneously analyze the device and circuit of the FGFET was established. For a seamless connection between FGFET-based devices and circuit analysis, the compact model of the FGFET was developed, which is applied to logic-in-memory ternary content addressable memory (TCAM) circuit design. It was verified that the two types of logic-in-memory TCAM circuits to which FGFETs are applied are superior to a conventional CMOS FET-based TCAM circuit in the number of devices used (=circuit area) and power/energy efficiency.
The microstructure and mechanical properties of 2219 alloy during ultrasonic treatment
Authors: Li An-qing , Jiang Ri-peng , Li Rui-qing , Zhang Li-hua
Published: April 2023

High-intensity ultrasonic melt treatment technique plays a key role in improving the performance of large-scale 2219 alloy ingot (Φ630 mm × 4500 mm). In this current paper, ultrasonic treatment-assisted casting techniques were developed and applied to manufacture large-scale 2219 aluminium (Al) alloy ingot in direct chill casting (DC). The industry-level experiments revealed that the α-Al grains of the ingot with ultrasonic (USDC) were refined, the area fraction of the coarse Al2Cu eutectic phase showed a decreasing trend, and the mechanical properties were lightly improved than without ultrasonic ingot (DC). Based on the present results and previous proposed hypotheses, the synergistic effects of cavitation and acoustic streaming were considered as the dominant mechanisms of USDC.
Age-related alterations in meningeal immunity drive impaired CNS lymphatic drainage
Authors: Rustenhoven Justin , Pavlou Georgios , Storck Steffen E. , Dykstra Taitea , Du Siling , Wan Zhengpeng , Quintero Daniel , Scallan Joshua P. , Smirnov Igor , Kamm Roger D. , Kipnis Jonathan
Published: April 2023

The meningeal lymphatic network enables the drainage of cerebrospinal fluid (CSF) and facilitates the removal of central nervous system (CNS) waste. During aging and in Alzheimer’s disease, impaired meningeal lymphatic drainage promotes the buildup of toxic misfolded proteins in the CNS. Reversing this age-related dysfunction represents a promising strategy to augment CNS waste clearance; however, the mechanisms underlying this decline remain elusive. Here, we demonstrate that age-related alterations in meningeal immunity underlie this lymphatic impairment. Single-cell RNA sequencing of meningeal lymphatic endothelial cells from aged mice revealed their response to IFNγ, which was increased in the aged meninges due to T cell accumulation. Chronic elevation of meningeal IFNγ in young mice via AAV-mediated overexpression attenuated CSF drainage—comparable to the deficits observed in aged mice. Therapeutically, IFNγ neutralization alleviated age-related impairments in meningeal lymphatic function. These data suggest manipulation of meningeal immunity as a viable approach to normalize CSF drainage and alleviate the neurological deficits associated with impaired waste removal.
Simulating noisy quantum channels via quantum state preparation algorithms
Authors: Zanetti Marcelo S , Pinto Douglas F , Basso Marcos L W , Maziero Jonas
Published: April 2023

In Xinet al(2017Phys. Rev.A96062303) and Weiet al(2018Sci. China Phys. Mech. Astron.6170311), the authors reported an algorithm to simulate, in a circuit-based quantum computer, a general quantum channel (QC). However, the application of their algorithm is limited because it entails the solution of intricate non-linear systems of equations in order to obtain the quantum circuit to be implemented for the simulation. Motivated by this issue, in this article we identify and discuss a simple way to implement the simulation of QCs on anyd-level quantum system through quantum state preparation algorithms, that have received much attention in the quantum information science literature lately. We exemplify the versatility of our protocol applying it to most well known qubit QCs, to some qudit QCs, and to simulate the effect of Lorentz transformations on spin states. We also regard the application of our protocol for initial mixed states. Most of the given application examples are demonstrated using IBM’s quantum computers.
Rogue wave solutions of (3+1)-dimensional Kadomtsev-Petviashvili equation by a direct limit method
Authors: Sun Yujie , Wu Jiaojiao , Li Biao
Published: April 2023

On the bases of N-soliton solutions of Hirota’s bilinear method, high-order rogue wave solutions can be derived by a direct limit method. In this paper, a (3+1)-dimensional Kadomtsev-Petviashvili equation is taken to illustrate the process of obtaining rogue waves, that is, based on the long-wave limit method, rogue wave solutions are generated by reconstructing the phase parameters of N-solitons. Besides the fundamental pattern of rogue waves, the triangle or pentagon patterns are also obtained. Moreover, the different patterns of these solutions are determined by newly introduced parameters. In the end, the general form of N-order rogue wave solutions are proposed.
High-performance chiral all-optical OR logic gate based on topological edge states of valley photonic crystal
Authors: Wang Xiaorong , Fei Hongming , Lin Han , Wu Min , Kang Lijuan , Zhang Mingda , Liu Xin , Yang Yibiao , Xiao Liantuan
Published: April 2023

For all-optical communication and information processing, it is necessary to develop all-optical logic gates based on photonic structures that can directly perform logic operations. All-optical logic gates have been demonstrated based on conventional waveguides and interferometry, as well as photonic crystal structures. Nonetheless, any defects in those structures will introduce high scattering loss, which compromises the fidelity and contrast ratio of the information process. Based on the spin-valley locking effect that can achieve defect-immune unidirectional transmission of topological edge states in valley photonic crystals (VPCs), we propose a high-performance all-optical logic OR gate based on a VPC structure. By tuning the working bandwidth of the two input channels, we prevent interference between the two channels to achieve a stable and high-fidelity output. The transmittance of both channels is higher than 0.8, and a high contrast ratio of 28.8 dB is achieved. Moreover, the chirality of the logic gate originated from the spin-valley locking effect allows using different circularly polarized light as inputs, representing “1” or “0”, which is highly desired in quantum computing. The device’s footprint is 18 μm × 12 μm, allowing high-density on-chip integration. In addition, this design can be experimentally fabricated using current nanofabrication techniques and will have potential applications in optical communication, information processing, and quantum computing.
Design, fabrication and optimization of electromagnetic absorption metamaterials
Authors: Lou 娄 Qi 琦 , Zhang 张 Xu-Dong 旭东 , Xia 夏 Ming-Gang 明岗
Published: April 2023

For decades, the rapid development of wireless communication has provided people a smarter way of living. However, a significant increase in electromagnetic pollution is an unavoidable consequence. Evading radar detection in modern warfare has also become an important prerequisite for survival on the battlefield. This review provides a comprehensive overview of the current status and types of electromagnetic absorption metamaterials, especially their design and preparation methods. Moreover, this review focuses on the strategies used to optimize the absorber absorption performance. Finally, this review presents a viewpoint on future research on electromagnetic absorption metamaterials, the main challenges that need to be addressed and the possible solutions.
Recent progress on deep learning-based disruption prediction algorithm in HL-2A tokamak
Authors: Yang Zongyu , Liu Yuhang , Zhu Xiaobo , Chen Zhengwei , Xia Fan , Zhong Wulyu , Gao Zhe , Zhang Yipo , Liu Yi
Published: April 2023

Disruption prediction and mitigation is a crucial topic, especially for future large-scale tokamaks, due to disruption’s concomitant harmful effects on the devices. On this topic, disruption prediction algorithm takes the responsibility to give accurate trigger signal in advance of disruptions, therefore the disruption mitigation system can effectively alleviate the harmful effects. In the past 5 years, a deep learning-based algorithm is developed in HL-2A tokamak. It reaches a true positive rate of 92.2%, a false positive rate of 2.5% and a total accuracy of 96.1%. Further research is implemented on the basis of this algorithm to solve three key problems, i.e., the algorithm’s interpretability, real-time capability and transferability. For the interpretability, HL-2A’s algorithm gives saliency maps indicating the correlation between the algorithm’s input and output by perturbation analysis. The distribution of correlations shows good coherence with the disruption causes. For the transferability, a preliminary disruption predictor is successfully developed in HL-2M, a newly built tokamak in China. Although only 44 shots are used as the training set of this algorithm, it gives reasonable outputs with the help of data from HL-2A and J-TEXT. For the real-time capacity, the algorithm is accelerated to deal with an input slice within 0.3 ms with the help of some adjustments on it and TFLite framework. It is also implemented into the plasma control system and gets an accuracy of 89.0% during online test. This paper gives a global perspective on these results and discusses the possible pathways to make HL-2A’s algorithm a more comprehensive solution for future tokamaks.
Deep learning framework for time series classification based on multiple imaging and hybrid quantum neural networks
Authors: Xie 谢 Jianshe 建设 , Dong 董 Yumin 玉民
Published: April 2023

Time series classification (TSC) has attracted a lot of attention for time series data mining tasks and has been applied in various fields. With the success of deep learning (DL) in computer vision recognition, people are starting to use deep learning to tackle TSC tasks. Quantum neural networks (QNN) have recently demonstrated their superiority over traditional machine learning in methods such as image processing and natural language processing, but research using quantum neural networks to handle TSC tasks has not received enough attention. Therefore, we proposed a learning framework based on multiple imaging and hybrid QNN (MIHQNN) for TSC tasks. We investigate the possibility of converting 1D time series to 2D images and classifying the converted images using hybrid QNN. We explored the differences between MIHQNN based on single time series imaging and MIHQNN based on the fusion of multiple time series imaging. Four quantum circuits were also selected and designed to study the impact of quantum circuits on TSC tasks. We tested our method on several standard datasets and achieved significant results compared to several current TSC methods, demonstrating the effectiveness of MIHQNN. This research highlights the potential of applying quantum computing to TSC and provides the theoretical and experimental background for future research.
Accelerator-mode islands and superdiffusion in double-kicked rotor
Authors: Wang Fengdi , Fang Ping
Published: April 2023

This paper presents a theoretical investigation of the presence of acceleration islands in the phase space of double-kicked rotor (DKR) systems, which can lead to superdiffusive behavior. We establish the conditions for the existence of period-1 acceleration centers and subsequently calculate the stability conditions for both period-1 and period-2 accelerate mode islands. A detailed analysis of local and global diffusion in the vicinity of the islands and the stickiness regions is provided. It is demonstrated that the mean stickiness time decays exponentially when the phase point is located in the interior of the island. Moreover, the phase point undergoes a power-law decay with a power equal to approximately 5 when entering the sticky region. These findings offer a foundation for future exploration of quantum dynamics in the DKR system.
The Year-scale X-Ray Variations in the Core of M87
Authors: Cheng Yu-Lin , Xiang Fei , Yu Heng , Jia Shu-Mei , Li Xiang-Hua , Li Cheng-Kui , Chen Yong , Feng Wen-Cheng
Published: April 2023

The analysis of light variation of M87 can help us understand the disk evolution. In the past decade, M87 has experienced several short-term light variabilities related to flares. We also find that there are year-scale X-ray variations in the core of M87. Their light variability properties are similar to clumpy-ADAF. By re-analyzing 56 Chandra observations from 2007 to 2019, we distinguish the “non-flaring state” from “flaring state” in the light variability. After removing flaring state data, we identify four gas clumps in the nucleus and all of them can be well fitted by the clumpy-ADAF model. The average mass accretion rate is ∼0.16M
⊙ yr−1. We analyze the photon index (Γ)–flux (2–10 keV) correlation between the non-flaring state and flaring state. For the non-flaring states, the flux is inversely proportional to the photon index. For the flaring states, we find no obvious correlation between the two parameters. In addition, we find that the flare always occurs at a high mass accretion rate, and after the luminosity of the flare reaches the peak, it will be accompanied by a sudden decrease in luminosity. Our results can be explained as that the energy released by magnetic reconnection destroys the structure of the accretion disk, thus the luminosity decreases rapidly and returns to normal levels thereafter.
Probing the Internal Physics of Neutron Stars through the Observed Braking Indices and Magnetic Tilt Angles of Several Young Pulsars
Authors: Hu Fang-Yuan , Cheng Quan , Zheng Xiao-Ping , Wang Jia-Qian , Yan Yu-Long , Wang Jia-Yu , Luo Tian-Yu
Published: April 2023

The braking indices of pulsars may contain important information about the internal physics of neutron stars (NSs), such as neutron superfluidity and internal magnetic fields. As a subsequent paper of Cheng et al., we perform the same analysis as that done in the previous paper to other young pulsars with a steady braking index, n. Combining the timing data of these pulsars with the theory of magnetic field decay, and using their measured magnetic tilt angles, we can set constraints on the number of precession cycles, ξ, which represents the interactions between superfluid neutrons and other particles in the NS interior. For the pulsars considered in this paper, the results show that ξ is within the range of a few ×103 to a few ×106. Interestingly, for the Crab and Vela pulsars, the constraints on ξ obtained with our method are generally consistent with that derived from modeling of the glitch rise behaviors of the two pulsars. Furthermore, we find that the internal magnetic fields of pulsar with n < 3 may be dominated by the toroidal components. Our results may not only help to understand the interactions between the superfluid neutrons and other particles in the interior of NSs but also be important for the study of continuous gravitational waves from pulsars.
Neutrino Mass Constraints from Reconstructing the Large-scale Structure: Systematic Uncertainty
Authors: Chung Chok Lap , Inman Derek , Wang Xin , Shang Erhao , Zhuang Zi , Yuan Fucheng , Pen Ue-Li
Published: April 2023

We examine the possibility of applying the baryonic acoustic oscillation reconstruction method to improve the neutrino mass Σm

ν
constraint. Thanks to the Gaussianization of the process, we demonstrate that the reconstruction algorithm could improve the measurement accuracy by roughly a factor of two. On the other hand, the reconstruction process itself becomes a source of systematic error. While the algorithm is supposed to produce the displacement field from a density distribution, various approximations cause the reconstructed output to deviate on intermediate scales. Nevertheless, it is still possible to benefit from this Gaussianized field, given that we can carefully calibrate the “transfer function” between the reconstruction output and theoretical displacement divergence from simulations. The limitation of this approach is then set by the numerical stability of this transfer function. With an ensemble of simulations, we show that such systematic error could become comparable to statistical uncertainties for a DESI-like survey and be safely neglected for other less ambitious surveys.
Substantiating parameters of short-delay blasting and seismic safety while constructing the inclined tunnel
Authors: Petrenko Volodymyr , Bondarenko Nataliia , Miroshnyk Vitalii , Burskyi Maksym , Konoval Volodymyr
Published: April 2023

Implementation of blasting works in mining engineering and underground construction requires new effective blasting technologies in conducting an explosion. Short-delay blasting is a technology that requires scientific substantiation of its parameters. The application of explosion technology with increased blast intervals between charges is characterized as successful. However, the degree of reduction of seismic action and, accordingly, an increase in seismic safety needs clarification of the parameters of short-delay blasting. The scientific paper analyzes the delay time of the blast of charges and the classification of the degree of damage to buildings and structures. Seismic safety parameters for the inclined tunnel “Skhidnyi” while tunneling at the quarry of the Inhulets Ore Mining and Processing Plant (in the city of Kryvyi Rih) have been substantiated. The functional dependence of the maximum vibration velocity on the seismically safe distance has been obtained, as well as the dependence of the coefficient, the value of which characterizes the mass of the explosive. This allows for a quick evaluation of seismic safety parameters when calculating the parameters of blasting operations in the case of short-delay blasting.
Results of research on the stability of mine workings, fixed by arched supports made of composite materials, in the conditions of the Pokrovske Mine Administration
Authors: Bondarenko Volodymyr , Kovalevska Iryna , Sheka Ivan , Sachko Roman
Published: April 2023

The paper provides a detailed analysis of innovative technologies for maintaining mine workings at great depths. The possibility of using composite materials (in particular, carbonfiber-reinforced plastic) as fastening elements is of special attention. It has been conducted a comparative analysis of the physical-mechanical properties of carbon fiber-reinforced plastic and low-alloy steel, traditionally used for the manufacture of frame support. To conduct a comparative analysis of the stress-strain state, a series of models has been developed and computer modelling has been performed by the finite element method using the Ansys Mechanical software product. In mining-geological conditions Pokrovske Mine Administration, three types of supports, namely, basic, composite with variable section and composite with constant section, have been studied. The initial and boundary conditions, as well as the assumptions and idealization of the model, have been substantiated. A comparative analysis of the stress intensity confirms the advantage of the proposed frame supports made of composite materials in terms of limiting the zones with maximum values. Laboratory research, conducted on a 3D-printer, testifies to the adequacy of conducted modelling. The reliability of the obtained values makes it possible to recommend an innovative support using carbon fiber-reinforced plastic for conducting a mine experiment.
Fuzzy logic methods for risk management at mining enterprises
Authors: Slashchova Olena , Yalanskyi Oleksii , Slashchov Ihor , Kurinnyi Volodymyr , Kulbach Andrii
Published: April 2023

To prevent emergencies at mining enterprises, a model of controlling stability of geotechnical system by fuzzy logic methods was developed based on the data fuzzification, inference and defuzzification. The main principles were formulated for the identification of specific features of dangerous production facilities in mining industry. To determine the input parameters for the fuzzy logic model, the systematization of uncontrolled (mining and geological) and controlled (technical and technological) parameters, the presence or change of which affects the stability of the rock massif and roadways, was carried out. The application of such methods as aggregation, implication, defuzzification was substantiated for processing input signals. An algorithm of fuzzy logic inference was formed to control parameters of a geotechnical system. The model differs by its ability to adapt to the specifics of controlling the geotechnical system “support - rock massif” and to select logical rules depending on the established criteria.
Drones as elements of remote control of the state of geophysical objects
Authors: Ihor Krasovskyi
Published: April 2023

Control of the state of geophysical objects is one of the key components of their further safe operation. But some geophysical objects have areas that cannot be successfully inspected for various reasons. Such missed areas can be in critical condition and significantly affect the final results of the examination. It is possible to solve this issue by implementing methods and means of remote operational non-destructive control of the state of geophysical objects. One such solution is implementation of unmanned aerial vehicles, commonly known as drones. The goal of the work is to find out the possibility of using drones as an element of remote control of the state of geophysical systems in order to eliminate inaccessible areas during the inspection of both on-ground and underground objects and to establish the key parameters of drones for their implementation in the specified role. Drones and areas of their application were used as objects for this research. Two categories of remote control of the state of geophysical objects by drones were defined, followed by technical requirements for drones for each category.
The use of steel and injection rock bolts to support mine workings when crossing tectonic faults
Authors: Krukovskyi Oleksandr , Krukovska Viktoriia , Kurnosov Serhii , Demin Vladimir , Korobchenko Vladyslav , Zerkal Volodymyr
Published: April 2023

Using the method of numerical modeling, the stability of mine working under difficult conditions of crossing a tectonic fault was studied as well as effectiveness of using steel rock bolts in combination with injection rock bolts. It was shown that steel and injection rock bolts complemented each other very well, increasing the stability of the mine working and reducing permeability of the host rocks. Injection rock bolts exclude the possibility of destruction of host rocks and more effectively reduce permeability of disturbed rocks in the zone of the tectonic fault. At the same time, steel rock bolts better restrain the expansion of the zone of high difference of the stress tensor components. Therefore, in case of heavily watered rocks or a high probability of methane breakthroughs into the mine working, it is better to install injection rock bolts as close to the mine face as possible. Then a water- and gas-proof shell arch around the mine working will be created in the immediate vicinity of the mine face. If there is no such threat and the priority is to maintain the long-term stability of the mine working, then first of all it is necessary to install steel bolts.
Statistical analysis of Samara River pollution impact on the population morbidity rate in Western Donbas (Ukraine)
Authors: Kovrov Oleksandr , Kulikova Daria , Pavlychenko Artem
Published: April 2023

The anthropogenic load on natural environment has reached a level that threatens the population health. The main causes of water sources pollution are the discharge of untreated or insufficiently treated wastewaters by industrial enterprises. These and other reasons lead to the spread of various types of diseases among the population. A cause-and-effect relationship between the qualitative and quantitative state of the surface waters of the Samara River and certain diseases of the population living in the Western Donbas region has been established. The method of statistical analysis based on Pearson correlation has been applied. Reliable correlation between the pollutants content in surface waters of Samara River and the increase of the population diseases in the investigated territory has been proven. With high degree of probability, the following diseases are closely related to water quality: diseases of the blood, hematopoietic organs and disorders of immune system; diseases of endocrine system, digestive and metabolic disorders; circulatory system and digestion diseases; diseases of the skin and subcutaneous tissues. The obtained results indicate the need for further research taking into consideration the regional specificity of conditions and factors of environmental pollution, development of advanced water treatment to reduce the morbidity rate of the population.