bluuebunny/crossref_metadata_2025_split huggingface dataset:
Propagation of waves in high Brillouin zones: Chaotic branched flow and stable superwires
Authors: Daza Alvar , Heller Eric J. , Graf Anton M. , Räsänen Esa 
Published: September 2021

Significance
Waves propagating through random media can accumulate in strong branches, intensifying fluctuations and powerful phenomena such as tsunamis. However, branched flow is not restricted to the large scale, and here, we find surprisingly that branched flow is not restricted to random media. We show that quantum waves living in the high Brillouin zones of periodic potentials also branch. Moreover, some of these branches do not decay as in random media but remain robust indefinitely, creating dynamically stable channels that we call superwires. The waves in these stable branches have enough energy to surmount the channel potential and go elsewhere, but classically, nonlinear dynamics keeps them confined within the channel. These results have direct experimental consequences for superlattices and optical systems.
Midbrain dopaminergic innervation of the hippocampus is sufficient to modulate formation of aversive memories
Authors: Tsetsenis Theodoros , Badyna Julia K. , Wilson Julianne A. , Zhang Xiaowen , Krizman Elizabeth N. , Subramaniyan Manivannan , Yang Kechun , Thomas Steven A. , Dani John A. 
Published: September 2021

Significance
The origin and mode of action of dopamine on hippocampus-dependent memory have been a matter of interest for many years. The latest research has pointed toward the locus coeruleus as the main source of hippocampal dopamine, while inputs from midbrain dopaminergic centers remain controversial and understudied. We provide anatomical evidence for a direct dopaminergic projection to the hippocampus from a distinct, identified midbrain population and report a bidirectional modulation of hippocampal-aversive learning by midbrain dopamine. Our data indicate that this modulation is sustained even in the absence of catecholamine release from the locus coeruleus. These results demonstrate that midbrain dopaminergic innervation of the dorsal hippocampus is significant and plays a functional role in the modulation of aversive memory formation.
Technical aspects of cardiorespiratory estimation using subspace projections and cross entropy
Authors: Morales John , Moeyersons Jonathan , Testelmans Dries , Buyse Bertien , Borzée Pascal , Van Hoof Chris , Groenendaal Willemijn , Van Huffel Sabine , Varon Carolina 
Published: September 2021

Abstract

Background. Respiratory sinus arrhythmia (RSA) is a form of cardiorespiratory coupling. Its quantification has been suggested as a biomarker to diagnose different diseases. Two state-of-the-art methods, based on subspace projections and entropy, are used to estimate the RSA strength and are evaluated in this paper. Their computation requires the selection of a model order, and their performance is strongly related to the temporal and spectral characteristics of the cardiorespiratory signals. Objective. To evaluate the robustness of the RSA estimates to the selection of model order, delays, changes of phase and irregular heartbeats as well as to give recommendations for their interpretation on each case. Approach. Simulations were used to evaluate the model order selection when calculating the RSA estimates introduced before, as well as three different scenarios that can occur in signals acquired in non-controlled environments and/or from patient populations: the presence of irregular heartbeats; the occurrence of delays between heart rate variability (HRV) and respiratory signals; and the changes over time of the phase between HRV and respiratory signals. Main results. It was found that using a single model order for all the calculations suffices to characterize RSA correctly. In addition, the RSA estimation in signals containing more than 5 irregular heartbeats in a period of 5 min might be misleading. Regarding the delays between HRV and respiratory signals, both estimates are robust. For the last scenario, the two approaches tolerate phase changes up to 54°, as long as this lasts less than one fifth of the recording duration. Significance. Guidelines are given to compute the RSA estimates in non-controlled environments and patient populations.
Shape resonances and the T

c
dependence on film thickness of Ni/Bi systems
Authors: Doria Mauro M , Liu Liying , Xing Yutao , Merino I L C , Litterst F J , Baggio-Saitovitch E 
Published: September 2021

Abstract
We report on the experimentally observed variation of the superconducting critical temperature (T

c
) of Ni/Bi systems as a function of the total deposited film thickness and on its explanation using a theoretical model. Two series of Ni/Bi systems have been analyzed which were obtained by depositions of Ni onto Bi in the proportions Ni3Bix (3 nm of Ni onto x nm of Bi) and NiyBi6y (y nm Ni onto 6 y nm of Bi). As shown recently, the formation of the superconducting compound NiBi3 at Ni/Bi interfaces in the resulting NiBi3-Bi films is thermodynamically favored by a volume contraction. Here we corroborate this result and estimate the thickness of the resulting NiBi3 and of the remaining Bi layers for the Ni3Bix and NiyBi6y series using the laws of mass and conservation of number of atoms. We consider the resulting film as being made up of two homogeneous and uniform layers of NiBi3 and Bi, respectively, and study this idealizing model using the Bogoliubov de Gennes (BdG) equations. It is assumed that superconductivity originates in the NiBi3 layer and penetrates the Bi layers via a potential barrier. Our theoretical calculations predict the dependence of T

c
with respect to the thicknesses of the NiBi3 and Bi layers, and also with the strength of the potential barrier that blocks the migration of electrons from the NiBi3 to the Bi layer. The calculations show that the superconducting gap also exists in Bi, although much weaker than in the NiBi3 layer. We compare the predicted T

c
values with the experimental data and find sufficient agreement to suggest that our model can explain the experimentally observed variation of T

c
with thickness. We interpret this dependence as shape resonance oscillations which are derived from the BdG theory applied to thin superconducting films.
Markovian dynamics in de Sitter
Authors: Mirbabayi Mehrdad 
Published: September 2021

Abstract
The equilibrium state of fields in the causal wedge of a dS observer is thermal, though realistic observers have only partial access to the state. To them, out-of-equilibrium states of a light scalar field appear to thermalize in a Markovian fashion. We show this by formulating a systematic expansion for tracing out the environment. As an example, we calculate the O(λ) correction to the result of Starobinsky and Yokoyama for the relaxation exponents of λϕ4 theory.
Latest results of Eurofusion plasma-facing components research in the areas of power loading, material erosion and fuel retention
Authors: Reinhart M. , Brezinsek S. , Kirschner A. , Coenen J.W. , Schwarz-Selinger T. , Schmid K. , Hakola A. , van der Meiden H. , Dejarnac R. , Tsitrone E. , Doerner R. , Baldwin M. , Nishijima D. , Team WP PFC 
Published: September 2021

Abstract
The interaction between the edge-plasma in a fusion reactor and the surrounding first-wall components is one of the main issues for the realisation of fusion energy power plants. The EUROfusion Work Package on plasma-facing components addresses the key areas of plasma-surface interaction in view of ITER and DEMO operation, which are mostly related to material erosion, surface damage and fuel retention. These aspects are both investigated experimentally (in tokamaks, linear plasma devices and lab experiments) and by modelling. Here, selective results regarding the main research topics are presented: in the area of tungsten (W) surface modifications, the interplay between W fuzz formation and W fuzz erosion depends strongly on the local plasma and surface conditions, as demonstrated by tokamak experiments. Complementary, experimental findings on the dependence of erosion on the surface structure in lab-scale experiments have led to the successful implementation of surface structure effects in numerical modelling. The qualification of ITER-like monoblocks at high fluences of up to 1031 D m−2 in linear plasma facilities has shown no visible damages at cold plasma conditions. However, experiments with simultaneous plasma and pulsed heat loading (edge-localized modes simulations) show that synergistic effects can lower the W damage thresholds. Additionally, fuel retention studies show that nitrogen as a plasma impurity increases the fuel retention in W, and that deuterium implanted in the surface of W is capable of stabilizing displacement damages caused by neutron damage. Finally, the implications of these results on ITER and DEMO operation are discussed and an outlook on follow-up experiments is given: the results indicate that there are possible impacts on the ITER divertor lifetime and tritium removal. Other areas like the divertor shaping and the erosion need additional investigations in the future to quantify the impact on ITER and DEMO operation.
The substitution of Mg2+with Mn2+/4+metal ions in chlorophyll structure isolated from Gliricidia sepium leaves
Authors: Selan O T E , Hawu H N , Poy L , Cunha T D , Darmakusuma D 
Published: September 2021

AbstractOne of the critical issues of using chlorophyll (Mg-Chl) as a dye photosensitizer in DSSC is related to a rapid decay of this material. Changing the alkali metal using transition metal ions could theoretically increase the stability of chlorophyll. In this research, the substitution of Mg2+with Mnn+ions (n = 2 and 4) in chlorophyll structure isolated fromGliricidia sepiumleaves had been carried out. The column chromatography technique was chosen to separate the chlorophyll followed by modifying the metal centre using two different compounds containing manganese, namely MnCl2and MnO2. The results show that there are differences in Rf values after substitutions, [0.90 (Mg-Chl), 0.81 (Mn2+-Chl), and 0.96 (Mn4+-Chl)]. The Soret bands experience a redshift from 330 to 338 nm for Mn2+-Chl and a blue shift from 411 to 401 nm for Mn4+-Chl while the Q band has a redshift from 665 to 668 nm for Mn2+-Chl but a blue shift from 665 to 526 nm for Mn4+-Chl. The obtained products have similar IR absorption patterns to Mg-Chl but differ only in its transmittance with slightly higher wavenumbers shifts. Shifting of UV-Visible and Infra-red characteristics indicate different molecular electronic nature of the obtained compounds. This implies successful substitution for the metal centre without damaging the structure of the chlorophyll.
Travelling salesman problem: Greedy single point crossover in ordinal representation
Authors: Fernandez B , Fanggidae A , Pandie E S Y , Mauko A Y 
Published: September 2021

AbstractGenetic Algorithm (GA) is a metaheuristic algorithm which has stages; coding, selection, crossover, and mutation. The crossover operator plays an important role in producing offspring to find solutions. Single Point Crossover (SPC) and Two Point Crossover (TPC) are classic crossover operators that are easy to apply to ordinal representation coding rather than path representation coding. The greedy algorithm is applied to the SPC operator to solve the Traveling Salesman Problem (TSP) to improve the performance of the genetic algorithm in the ordinal representation coding scheme. The results show that the proposed Greedy Single Point Crossover (GSPC) has higher performance in finding the global optimal solution for all population sizes and cities used, but it costs computation time.
The mapping of potential ground water using geoelectrical measurement of Schlumberger configuration method in Malata Village, Tana Righu Sub-District, West Sumba District, East Nusa Tenggara Province
Authors: Krisnasiwi I F 
Published: September 2021

Abstract
This study aims to analyze rock units containing aquifers in the location of investigation using geoelectrical measurements with Schlumberger configuration method of the MC OHM 2115 Resistivity Meter. The estimation was carried out in 12 measurement points with the length of each path was 150 m. The data analysis of the measurement was implemented using IP2WIN software and Corel Draw X6 software. The results of the interpretation of the 12 measurement points indicated that there were 5 rock units, namely the resistivity 0 ≤ 2 Ohm m which is interpreted as clay. Resistivity 2, 5 ≤ 10 Ohm m as marl. Species resistivity 10.5 ≤ 20 Ohm m as marl limestone, while resistivity ≥ 20.5 Ohm m as reef limestone. The aquifer belongs in the reef limestone unit with a specific resistance of 20.5 ≤ 100 Ohm m which ends with an impermeable layer such as clay or semi impermeable such as marl. Based on the interpretation, it is concluded that along the measurement area there are aquifers with varying depths which can be optimized by means of drilling at points 01, 03, 04, 06, and 09. The location that has the thickest aquifer is point 04 (± 29.3 m) and 09 (± 38 m).
Automatic Localization of Condylar Process Centre Based on Generalized Hough Transform from CBCT images
Authors: Wang Tingkang , Zhang Songze , Shi Hongjian 
Published: September 2021

Abstract
Cone Beam Computed Tomography (CBCT) is a technique for capturing maxillofacial images that provide tissue views with low radiation doses. In this paper, we propose an automatic method to locate the centre of the mandibular condylar process in CBCT images. The bone edges of the condylar process are extracted to detect the mandibular ramus in each slice based on the generalized Hough Transform. We propose an upward region-growing method to segment the condylar and coracoid processes. The centre of the condylar process is then determined as the centre of the condylar region in the axial slice with the maximum condyle area. The centre located by the proposed method was compared with the centre manually located by two experts. Our results indicate that the proposed method can accurately locate the condylar process centre.
Shuffling-SinGAN: Improvement on Generative Model from a Single Image
Authors: Zheng Ming , Zhang Pengyuan , Gao Yining , Zou Hang 
Published: September 2021

AbstractRecently, SinGAN takes the use of GANs into a new realm – unconditional generation learned from a single natural image. Following the SinGAN architecture, we propose Shuffling- SinGAN, an efficient unconditional generative model that trained on a single natural image for general image manipulation. Our new network includes a pyramid of fully convolutional GANs, in which each layer is responsible for learning the patch distribution at a different scale of the image. We can generate new samples with variability through our network, which have the function of maintaining the texture and global structure of the original image. New random image generated by the model after multiple training is different from the original image in detail. Inspired by sinIR, we decided to add random pixel shuffling to the network. After experimentation, we found that the changed model generated more random new samples. Shuffling-SinGAN allows generating new samples of arbitrary size and aspect ratio, that have significant variability, yet maintain both the global structure and the fine textures of the training image. User tests confirm that the generated samples are commonly confused to be real images. With quantitative evaluation, we show that Shuffling-SinGAN has competitive performance on random image generation.
Face feature matching based on semantic Information
Authors: Guo Jianlan , Chen Yuqiang , Li Jiaming , Xie Jiabao 
Published: September 2021

Abstract
Face feature matching problems have always been a very important research topic in the field of image processing. Face feature matching is always the most important part of common face recognition algorithms, but how to match features quickly and accurately is a quite essential and urgent problem to be solved. Therefore, we propose a face feature matching method which can effectively improve the matching efficiency and accuracy. For each feature point in the input image, face feature matching based on nearest neighbor ratio method requires global search for the best matching in the reference image. However, we find that such matching method can achieve better matching results, but it costs a lot of computing resources and time. Therefore, we use the feature vectors constructed by CNN convolution feature map to provide the local matching region based on semantic information for handcrafted descriptors after feature matching. Although two feature matching processes are used in this paper, the matching efficiency is improved several times compared with the traditional global search scheme. Experiments show that our proposed can be used as an important module of face recognition system to improve the accuracy of face recognition.
Correction of refractive and scattered image distortions in optical coherence tomography based on scalpel
Authors: Tang Ning , Fan Jinyu , Zhang Yunping , Shi Guohua 
Published: September 2021

Abstract
We describe a distortion correction algorithm for OCT images based on the scalpel. In this algorithm, the distorted OCT images are segmented into three parts depending on the seven customized fiducials. Image translation and image stitching are used to eliminate the majority of the distortions. After performing experiments with porcine eyes, we basically correct the optical distortions caused by the reflection and interlayer scattering effects. The correction error is less than 2%. Our algorithm could bring many potential applications in ophthalmic procedures.
Reliable Single-image Denoising for Adaptive Optics Scanning Laser Ophthalmoscopy
Authors: Chen Yiwei , He Yi , Wang Jing , Li Wanyue , Xing Lina , Gao Feng , Shi Guohua 
Published: September 2021

Abstract
A reliable single-image denoising method is presented for adaptive optics scanning laser ophthalmoscopy. This method firstly averaged multiple images and then used the averaged image as the reference to adjust the parameters of the filtering process that was subsequently applied to other individual images. Six filtering methods, including the mean, median, Gaussian, fast adaptive nonlocal synthetic aperture radar despeckling, K-single value decomposition, and block matching and three-dimensional filtering, were utilized. The effectiveness of our method was verified based on the comparison of sets of images without and with parameter adjustments. Furthermore, we applied the same parameter settings as those obtained from the filter adjustments of another adaptive optics scanning laser ophthalmoscope image acquired by the same instrument. The filtered images showed that the parameter-adjusted filters work well on other images, which is helpful for improving the image quality of adaptive optics scanning laser ophthalmoscope images.
Malware detection based on TF-(IDF&ICF) method
Authors: Qin Bin , Zhang Junpeng , Chen Hongyu 
Published: September 2021

Abstract
As the level of information technology continues to increase, information security problems caused by malware are becoming more and more serious. An important method to detect malware is to analyze software behavior information, such as permissions, API call sequences and system calls. In this paper, API call sequences are used as the research object for malware detection, and the traditional feature extraction methods are not ideal for API call sequences. In this paper, a TF-(IDF&ICF) feature extraction method is proposed by mathematical analysis, which combines document and category level features. Experiments show that using the feature extractor proposed in this paper, followed by training, the performance is improved in four different machine learning models, and the F1 can reach 0.979, while the system response time is significantly reduced, which has good practical value.
Visual gesture recognition based on hand key points
Authors: Chen Boxu , Yu Lixin , Meng Xiao , Hua Yang 
Published: September 2021

Abstract
In recent years, computers have become a part of people's daily life, and the interaction between people and computers has increasingly become a hot spot in the field of scientific research. Gesture recognition based on vision is an indispensable part of the new generation of human-computer interaction. This paper presents a visual gesture recognition method based on hand key points, which realizes the detection of hand key points in the current input image and the recognition of defined gestures. It provides a new technical scheme for human-computer interaction application. Compared with the current mainstream solutions that directly train the defined gestures and obtain the gestures in the input image through template comparison detection, this paper first uses the rigid characteristics of the palm to design a palm detection model instead of directly detecting the entire hand. After detecting the presence of hand in the picture, the hand key point model locates 21 3D hand key point coordinates in the previously detected hand area through direct coordinate prediction. Finally, the meaning of gestures in the input image is obtained through the positional relationship between the key nodes. This solution achieves 95.7% of the accuracy of detection, and improves the FPS from 21-23 to 30-31.
Target-oriented Opinion Words Extraction via graph convolutional network
Authors: Li BaoKai , Dai YueMing 
Published: September 2021

Abstract
Target-oriented opinion word extraction (TOWE) is a sequence labelling subtask of aspect-level sentiment analysis (ABSA), which aims to extract corresponding opinion words for a given sentence and opinion target. In view of the existing related work, the structural information of sentences is not fully considered. In this study, we explore the integration of neural network and dependency tree to handle the TOWE and propose a model based on graph convolution network (GCN). The model uses the long short-term memory network (LSTM) to learn the semantic features of sentences. On this basis, the model uses the GCN to model the sentence structure through dependency tree and capture the syntactic dependency relationship between the target word and the opinion word. The experimental results show that GCN can effectively improve the performance of TOWE. The F1 values of the model on the semeval-rest14 and semeval-laptop14 reached 82.60% and 74.45%.
Research on Building Chinese Blog Semantic Lexicon Based on Semantic Comprehension
Authors: Wen Bin , Dong Huihui , Ding Ling , Dai Wenhua 
Published: September 2021

Abstract
Nowadays, investigators of phrases and text sentimental orientation identification mainly divided into two ways: semantic comprehension and machine learning. Machine learning needs a lot of training corpus and also cannot handle general field words effectively, meanwhile, semantic comprehension cannot get high scores at precision and recall. Therefore, in this paper, we propose a new fusion method based on our semantic comprehension for judging phrases’ polarity. In this paper, firstly, we modify the knowledge of Hownet, on the basis of its four primitives, the fifth primitive—sentimental primitive was proposed by our research, and annotated it into Hownet manually; secondly, we propose a new phrase sentimental similarity calculation method to compute word’s sentimental value; at last, we integrate transductive learning into this method to identify phrases’ sentimental orientation. The performance of experiment show that, compared with SVM or traditional semantic comprehension, it can get better results.