bluuebunny/crossref_metadata_2025_split huggingface dataset:
A dynamic semantic segmentation algorithm with encoder-crossor-decoder structure for pixel-level building cracks
Authors: Chen Yuliang , Dong Shaojiang , Hu Bo , Liu Qingyi , Qu Yinghao 
Published: November 2023

Abstract
A large number of newly built infrastructures as well as those constructed in the early stage are faced with the problems of detection and maintenance. However, it is difficult to detect building cracks because of its small size and complex background noise. In this study, a crack segmentation network based on Encoder-Crossor-Decoder structure is innovatively proposed to solve the problems of small cracks and easy to be disturbed by background. Then, a loss function is proposed to address the problem of large differences in the ratio of cracks to background pixels in architectural crack segmentation. The experiments show that the loss function can effectively improve the training effect of the model and make the model obtain better semantic segmentation ability. Finally, according to the requirements of building crack detection, a large dataset of concrete pavement cracks is produced, which fills the gap of large dataset of semantic segmentation of cracks. The excellent effect of the model and loss function is verified with three datasets containing most of the major material and structural scenes. In addition, we compare the model with other deep learning segmentation models to validate its effectiveness. The results show that the mIoU of the model of this study reaches 84.04%, 77.56% and 87.38% in the bridge non-steel crack dataset, steel surface crack dataset and our concrete crack dataset, respectively. The accuracy reaches 99.14%, 98.62% and 99.37%. F1 reaches 0.911, 0.873 and 0.963 respectively. It outperforms other deep learning based segmentation methods.
Green fabrication of ultrafine N-Mo
x
C/CoP hybrids for boosting electrocatalytic water reduction
Authors: Yu Xiaomei , Shi Wei , Wei Jiajiao , Liu Tiantian , Li Yuanyuan , He Mengyuan , Wei Zhengyu , Ping Dehai , Sun Panfei , Zheng Jin You , Li Songjie 
Published: November 2023

Abstract
Developing non-noble-metal electrocatalysts for hydrogen evolution reactions with high activity and stability is the key issue in green hydrogen generation based on electrolytic water splitting. It has been recognized that the stacking of large CoP particles limits the intrinsic activity of as-synthesized CoP catalyst for hydrogen evolution reaction. In the present study, N-Mo
x
C/CoP-0.5 with excellent electrocatalytic activity for hydrogen evolution reaction was prepared using N-Mo
x
C as decoration. A reasonable overpotential of 106 mV (at 10 mA cm−2) and a Tafel slope of 59 mV dec−1 in 1.0 M KOH solution was achieved with N-Mo
x
C/CoP-0.5 electrocatalyst, which exhibits superior activity even after working for 37 h. Uniformly distributed ultrafine nanoclusters of the N-Mo
x
C/CoP-0.5 hybrids could provide sufficient interfaces for enhanced charge transfer. The effective capacity of the hydrogen evolution reaction could be preserved in the complex, and the enlarged electrocatalytic surface area could be expected to offer more active sites for the reaction.
Ca-AlN MOFs-loaded chitosan/gelatin scaffolds; a dual-delivery system for bone tissue engineering applications
Authors: Dousti Mahdi , Golmohamadpour Azadeh , Hami Zahra , Jamalpoor Zahra 
Published: November 2023

Abstract
Creating a scaffold for bone tissue engineering that is bioactive and capable of acting as a local-dual delivery system, releasing bioactive molecules and regulating the bone remodeling process to achieve balanced bone resorption and formation, is a significant challenge. The objective of this research is to create a composite scaffold using chitosan/gelatin (CHS/Gel) and the calcium (Ca)-alendronate (ALN) metal–organic frameworks (MOFs). The scaffold will act as a dual-delivery system, releasing Ca ions and ALN to regulate bone formation. Ca-ALN MOF nanoparticles (NPs) were prepared in mild conditions and studied by FTIR, XRD, FESEM, and TGA. Ca-ALN NPs-loaded CHS/Gel scaffolds were opportunely fabricated through freeze-drying approach. Physicochemical features of the scaffolds after incorporating NPs equated by CHS/Gel scaffold changed, therefore, the attendance of NPs caused a decreasing porosity, decreased swelling, and low rate of degradation. The release profile results showed that the NPs-loaded CHS/Gel scaffolds were able to simultaneously release ALN and Ca ions due to the decomposition of NPs. Additionally, the loading of NPs in the CHS/Gel scaffold led to an increment in alkaline phosphatase (ALP) activity and the quantity of deposited Ca along with osteogenesis gene markers. These findings suggest that the NPs-loaded CHS/Gel scaffold has the potential to enhance the differentiation of human adipose tissue-derived mesenchymal stem cells, making it a promising approach for bone repair.
Coherence of turbulent structures with varying drive in stellarator edge plasmas
Authors: Huslage P , Birkenmeier G , Shanahan B , Killer C 
Published: November 2023

Abstract
This work investigates the parallel coherence of plasma filaments through numerical simulations using the hot-ion two-fluid hermes-2 model within the BOUT++ framework. Realistic field lines in the scrape-off layer (SOL) of magnetic fusion devices, especially in stellarator configurations possess a highly varying curvature along the magnetic field line. A varying curvature creates a parallel

E

×

B

velocity gradient which might tear the filament apart. The main parameters controlling this process are the collisionality and the electron plasma beta. Simulations of realistic curvature variations along field lines in a circular ASDEX Upgrade-like tokamak and Wendelstein 7-X stellarator (W7-X) show the parallel displacement between different filament sections to correlate with the curvature. The rapidly varying W7-X curvature and the low average curvature drive reduce the propagation of the filament to only a few hundred meters per second. The effect of a finite ion temperature on filament propagation in a W7-X field line geometry is found to be a higher diamagnetic current resulting in stronger charge separation. This work supports simulations and experimental findings that filaments in W7-X are comparably slow due to the large major radius of the device. They do not perform ballistic motion and hence do not drive significant turbulence spreading in the SOL.
Quantum Goos-Hänchen switch in graphene junctions
Authors: Zhang Z B , Wang Rui , Wang Baigeng , Xing D Y 
Published: November 2023

Abstract
Goos-Hänchen (GH) shift, an interference phenomenon describing the lateral shift of the reflected beam along the interface during total internal reflection, has attracted great interests in the field of quantum transport in two-dimensional materials. In particular, the GH effect generates a novel pseudospin-dependent scattering effect in graphene, which in turn results in an

8

e

2

/

h

conductance step in the bipolar junctions. Here, we reveal that a barrier region with effective barrier strength χ can greatly enrich the GH effect in graphene junctions. In contrast to the conventional case where the negative shift is allowed only in the p-n junction, the thin barrier enables both negative and positive spatial shifts in pIn and nIn junctions, where I represents the barrier region. More interestingly, the lowest channel degeneracy can be efficiently varied by tuning χ in both the symmetric pInIp and the asymmetric pnIp junctions, leading to a highly controllable switch that switches the conductance between

8

e

2

/

h

and

4

e

2

/

h

. These results advance the knowledge of GH effects in electronic materials and suggest experimental avenues for its observation and manipulation.
Formation and evolution of multiple-core structures in laser-sustained plasmas
Authors: Liu Jinbao , Zhang Dongheyu , Fu Yangyang 
Published: November 2023

Abstract
We report on the formation of multiple-core structures in laser-sustained plasmas (LSPs) through the utilization of an improved two-dimensional laser-thermal-hydrodynamically coupled fluid model. Our findings reveal that steady-state LSPs exhibit various temperature structures, including single, double, and triple cores, as the input laser power increases incrementally. The spatiotemporal distributions of these multiple-core structures are demonstrated, and the presence of an LSP core is identified when the rate of enthalpy change becomes positive. This behavior is predominantly influenced by factors such as laser power absorption, radiation, and diffusion along the laser path. The obtained results provide explicit insights into the temperature structures within LSPs, thereby potentially contributing to the advancement of LSP-based light sources for optical wafer defect inspection in the semiconductor industry.
The two-loop power spectrum in redshift space
Authors: Taule Petter , Garny Mathias 
Published: November 2023

Abstract
We present the matter power spectrum in redshift space including two-loop corrections. We
follow a strictly perturbative approach incorporating all non-linearities entering both via the
redshift-space mapping and within real space up to the required (fifth) order, complemented by
suitable effective field theory (EFT) corrections. This approach can a priori be viable up to
scales of order 0.2h Mpc-1 beyond which power suppression related to the finger-of-God effect
becomes non-perturbatively strong. We extend a simplified treatment of EFT corrections at
two-loop order from real to redshift space, making sure that the leading UV-sensitivity of both
the single-hard and double-hard limit of the two-loop contributions to the power spectrum is
accounted for, and featuring two free parameters for each multipole. Taking also
infrared-resummation into account, we calibrate with and compare to Quijote N-body simulations
for the monopole and quadrupole at redshifts z = 0 and z = 0.5. We find agreement within sample
variance (at percent-level) up to 0.18h Mpc-1 at two-loop order, compared to 0.1h Mpc-1 at
one-loop. We also investigate the role of higher-derivative corrections.
Diurnal modulation of electron recoils from DM-nucleon scattering through the Migdal effect
Authors: Qiao Mai , Xia Chen , Zhou Yu-Feng 
Published: November 2023

Abstract
Halo dark matter (DM) particles could lose energy due to the scattering off nuclei within the Earth before reaching the underground detectors of DM direct detection experiments.
This Earth shielding effect can result in diurnal modulation of the DM-induced recoil event rates observed underground due to the self-rotation of the Earth.
For electron recoil signals from DM-electron scatterings, the current experimental constraints are very stringent such that the diurnal modulation cannot be observed for halo DM.
We propose a novel type of diurnal modulation effect: diurnal modulation in electron recoil signals induced by DM-nucleon scattering via the Migdal effect.
We set so far the most stringent constraints on DM-nucleon scattering cross section via the Migdal effect for sub-GeV DM using the S2-only data of PandaX-II and PandaX-4T with improved simulations of the Earth shielding effect.
Based on the updated constraints, we show that the Migdal effect induced diurnal modulation of electron events can still be significant in the low energy region, and can be probed by experiments such as PandaX-4T in the near future.
Spin-2 dark matter from inflation
Authors: Gorji Mohammad Ali 
Published: November 2023

Abstract
The seed of dark matter can be generated from light spectator fields during inflation through a similar mechanism that the seed of observed large scale structures are produced from the inflaton field. The accumulated energy density of the corresponding excited modes, which is subdominant during inflation, dominates energy density of the universe later around the time of matter and radiation equality and plays the role of dark matter. For spin-2 spectator fields, Higuchi bound may seem to prevent excitation of such light modes since deviation of the inflationary background from the exact de Sitter spacetime is very small. However, sizable interactions with the inflaton field breaks (part of) isometries of the de Sitter space in the inflationary background and relaxes the Higuchi bound. Looking for this possibility in the context of effective field theory of inflation, we suggest a dark matter model consisting of spin-2 particles that produce during inflation.
A topologically charged four-dimensional wormhole and the energy conditions
Authors: Ahmed Faizuddin 
Published: November 2023

Abstract
In this research work, our primary focus revolves around the examination of a specific category of traversable wormholes known as topologically charged generalized Schwarzschild-Simpson-Visser-type wormhole, ds
2 = -(1-(2M/√(x
2+b
2))) dt
2+(1-(2M/√(x
2+b
2)))-1 ·(dx
2/α2)+(x
2+a
2) (dθ
2+sin2
θ
dϕ
2). This wormhole is uniquely defined by a pair of key parameters including global monopole charge. A noteworthy outcome of our investigation is the observation that the energy-momentum tensor associated with this wormhole complies with both the weak energy condition (WEC) and the null energy condition (NEC). Furthermore, incorporation of global monopole charge introduces a substantial influence on the curvature properties of wormhole space-time and various associated physical quantities derived from this geometry.
Observation of local density increase during pellet homogenization on EAST
Authors: Huang J. , Zhang T. , Zhang J. , Liang Y.F. , Wang Y.M. , Liao L. , Hou J.L. , Han X. , Ye K.X. , Geng K.N. , Xiang H.M. , Wen F. , Zhong F.B. , Li G.S. , Wu M.F. , Zhou Z. , Yang S.Q. , Zhou Z.Q. , Yu L. , Liu H.Q. , Krämer-Flecken A. , Gao X. , Zhuang G. ,   the EAST Team
Published: November 2023

Abstract
By combining the X-mode polarized lower and upper cut-off reflections obtained from the density profile reflectometer, we have successfully attained a comprehensive density profile spanning from the edge to the core region in pellet injection (PI) experiments on EAST. During the homogenization process after PI on EAST, an innovative method was introduced to quantify the local density increase. This approach employed the distinctive ‘dual-reflection’ phenomenon observed in the EAST microwave reflectometer, encompassing measurements of both the X-mode lower and upper cut-off frequencies. Furthermore, experimental investigations were carried out on EAST to comprehensively explore the parallel and poloidal expansion of the high-density pellet cloud. Notably, this study marks the first instance of measuring expansion velocities of pellet materials in both parallel and poloidal directions on EAST. A comparative analysis was performed initially between these experimental measurements and simulation results obtained from the HPI2 code, marking a pivotal stride towards enhancing its applicability in EAST.
Intelligent Selection Method for Gravity-suitable Area Based on Improved Support Vector Machine by the Genetic Algorithm
Authors: He Chuangxin , Zhang Fengshuo , Yu Xiaoyou , Zheng Wei 
Published: November 2023

Abstract
The gravity-aided inertial navigation system (GAINS) can achieve precise positioning of underwater vehicles in a gravity-suitable area. However, there are generally shortcomings in the existing intelligent suitable area selection methods in terms of selecting gravity feature parameters and learning parameters. In this paper, an intelligent suitable area selection method is proposed based on an improved support vector machine by the genetic algorithm (GA-SVM) to address the aforementioned problems. Firstly, the genetic algorithm (GA) is utilized to independently pick out the optimal feature subset of 15 existing gravity feature parameters and obtain the optimal support vector machine (SVM) learning parameters while eliminating irrelevant redundant features, thus improving the classifier’s performance and generalization ability. Then, the SVM classifier is trained according to the optimal information output by GA, and the accuracy of the test set is 95.5%. Finally, the classifier is utilized to distinguish suitable and unsuitable areas in the application region to evaluate the proposed method’s performance. The TERCOM experiment in the suitable area resulted in an average positioning error of less than 170 m.
Robot path planning based on improved A* algorithm
Authors: Yu Jintao , Gao Zhenhua , Jiang Mingze , Hou Enqi 
Published: November 2023

Abstract
To address the issues of excessive polyline paths and the increased number of search nodes in the A* algorithm, a weighted WA* algorithm is proposed based on the A* algorithm. Firstly, a new distance function is introduced to reduce computational resource usage and improve search efficiency. Then, the heuristic function is improved by searching all feasible paths to find the shortest path. When the lengths of feasible paths are very similar, an additional value is added to the heuristic function along with weights to minimize frequent searches. Lastly, Bezier curves are introduced to enhance the smoothness of the global path. Simulation results show that the improved WA* algorithm reduces the number of turns, time consumption, search space, and turning angles by 25.0%, 65.4%, 53.5%, and 18.7%, respectively, compared to the A* algorithm. Compared to the bidirectional A* algorithm, these reductions are 7.6%, 34.4%, 43.5%, and 7.1%, respectively. In addition, the WA* algorithm uses Bezier curves to curve-fit the generated path points, making the path trajectory smoother.
Improved YOLOv7 Intelligent Environment Perception Algorithm Based on Loss Function
Authors: Ma Zingjing , Peng Tao 
Published: November 2023

Abstract
To address the difficulty of environment perception in unmanned driving technology, an improved intelligent environment perception model based on YOLOv7 loss function is proposed. Simultaneously, the algorithm of deep sort target tracking is added for the sake of perceiving the surrounding environment through the camera to ensure the safety of the driver. And by modifying the loss term of the aspect ratio to the distinction between the predicted width and the target width, the fitting speed of the model can be effectively improved. Focal Loss is introduced to optimize the problem with the sample imbalance inside the target bounding box regression and reduce the weight proportion of numerous anchor boxes with less overlap between the predicted target bounding box and the true target bounding one to the overall model, such that the model centers more upon overlapping targets. The data applied to this article is BDD100K. The map of this algorithm reaches 60.3 %, which reaches 2.2 percentage points exceeding the baseline. Tests indicate that the raised algorithm attains certain advancements in the intelligent perception model of unmanned driving.
Wildfire Smoke Detection Based on Swin Transformer
Authors: Wang Yue , Piao Yan 
Published: November 2023

Abstract
Wildfires have devastating consequences for ecosystems and human lives, and it is crucial to detect wildfires accurately for reducing losses. Most researchers detected wildfire smoke by traditional smoke detection algorithms, deep learning algorithms, or a combination of both, but this still has a high rate of false positive. To enhance the accuracy of wildfire smoke detection, we present an advanced algorithm based on the Swin Transformer architecture, which improves remote dependence of high-order feature maps in the convolutional neural network, thus reducing the false positive rate of smoke detection by introducing the STB module to the GoogLeNet. We approach the task of wildfire smoke detection as a classification problem, where we divide the dataset of 18, 000 real wildfire smoke images into two distinct sets: a training set and a testing set. The experimental results support the efficacy and practicality of the proposed algorithm, exhibiting a remarkable smoke detection accuracy rate of 95% while successfully reducing the false alarm rate to as low as 4%. These findings underscore the algorithm’s capability to accurately identify wildfire smoke instances while minimizing erroneous detections.
Design and Implementation of Environmental Monitoring System for Substation Based on Internet of Things
Authors: Li Songbai , Liu Yanlong , Chen Xiaoguang 
Published: November 2023

Abstract
At present, the environmental monitoring of the substation suffers from complex wiring, low intelligence, high staff work intensity, and a lack of information-based overall management. Moreover, the distribution of substations is relatively scattered, making it complex and costly to set up a dedicated communication network. In response to these problems, this paper combines modern communication technology, sensor technology, and mobile intelligent terminal development technology to study an overall information-based substation environmental monitoring system. The monitoring system proposed in this paper includes a main controller, a data collection terminal, and a mobile communication terminal. The environmental data collected by the main controller is sent to the server through the communication method of subscription and substation using wireless communication technology, and the interface of the mobile communication terminal can display indoor environmental monitoring data. When the environmental data of the Substation exceeds the set threshold value to issue an early warning alert, the user can control it remotely through the mobile communication terminal to improve the indoor environment of the Substation. The system has a simple operation interface, low power consumption, and strong expansion compatibility, which effectively realizes remote monitoring and control of the substation environment and has good engineering application value.
Fault detection of high-voltage insulator thermal images based on YOLOv5
Authors: Liu Xinyi , Miao Runzhong , Meng Yi , Sun Haonan , Wu Kaixin 
Published: November 2023

Abstract
In this paper, we propose a defect detection method based on YOLOv5 for thermal images of high-voltage insulators, in which a large number of insulator photographs are taken by a thermal imager, followed by a YOLOv5 model to detect the captured thermal images. The function Meta-ACON is proposed to replace the original activation function. Finally, the extracted features are used for insulator condition identification and defect detection. Experimental findings demonstrate the efficacy of the suggested approach in successfully accomplishing the feature extraction of insulator faults, thus improving the accuracy and efficiency of insulator fault diagnosis.
Self-supervised Learning for Expression Recognition on Small-scale Data Set
Authors: Li Songyang , Tsuchida Kensei , Goto Takaaki , Kirishima Tadaaki 
Published: November 2023

Abstract
In this paper, we propose a facial micro-expression recognition method utilizing self-supervised learning and Vision Transformer. We employ a contrast learning approach for self-supervision and extract image features using an attention mechanism. Various data augmentation techniques were utilized, and we specifically designed an enhancement method for facial recognition. By combining the strengths of the Vision Transformer and CNN models for feature extraction, our approach achieves improved recognition accuracy, even with limited labeled data. Experimental evaluation shows that our proposed method has good results in facial micro-expression recognition tasks.