bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel flexible hydrogel electrode with a strong moisturizing ability for long-term EEG recording
Authors: Shen Gencai , Gao Kunpeng , Zhao Nan , Yi Zhiran , Jiang Chunpeng , Yang Bin , Liu Jingquan 
Published: December 2021

Abstract

Objective. A novel flexible hydrogel electrode with a strong moisturizing ability was prepared for long-term electroencephalography (EEG) monitoring. Approach. The hydrogel was synthesized by polymerizing the N-acryloyl glycinamide monomer. And a proper amount of glycerin was added to the hydrogel to increase the moisture retention ability of the electrodes. The hydrogel shows high mechanical properties, and the liquid in the hydrogel produces a hydrating effect on the skin stratum corneum, which could decrease the contact impedance between skin and electrode. In addition, the installation of hydrogel electrode is very convenient, and the skin of the subject does not need to be abraded. Main results. Scanning electron microscope images show that there are a large number of micropores in the hydrogel, which provide storage space for water molecules. The average potential drift of the hydrogel electrode is relatively low (1.974 ± 0.560 µV min−1). The average contact impedance of hydrogel electrode in forehead region and hair region are 6.43 ± 0.84 kΩ cm2 and 13.15 ± 3.72 kΩ cm2, respectively. The result of open/closed paradigm, steady-state visual evoked potentials, and P300 visual evoked potential show that hydrogel electrode has excellent performance. Compared with the hydrogel without glycerin, the moisture retention ability of hydrogel containing glycerin was greatly improved. Significance. Compared with standard Ag/AgCl wet electrode, hydrogel electrode is more convenient to install and has strong moisture retention ability, which makes it have great potential in daily life for long-term EEG recording.
Magnetic properties of CrFeCoNi based high entory alloy
Authors: Yin Junqi , Eisenbach Markus , Daene Makrus , Malcolm Stocks G. 
Published: December 2021

Abstract
Monte Carlo simulations are performed on three high entropy alloys: Cr0.25Fe0.25Co0.25Ni0.25, Cr0.2Fe0.2Co0.2Ni0.2Pd0.2, and Cr0.2Mn0.2Fe0.2Co0.2Ni0.2, with exchange interactions extracted from The ab initio Korringa-Kohn-Rostoker method combined with the coherent potential approximation calculations. Using finite size scaling analyses, we estimate the magnetic phase transition temperature for the four component alloy to be 108(2) K, and although the individual critical exponents are different from 3D Heisenberg universality class, the reduced exponent follows Suzuki weak universality. With the additional Palladium component, the transition temperature elevates to about 200 K. In contrast, we find no magnetic order for the five component alloy with Manganese at any finite temperatures.
Design and Optimization of Star Recognition Algorithm Based on Hierarchical CNN
Authors: Lu Wentao , Hua Gengxin , Zhao Yunfu , Zhou Jiantao 
Published: December 2021

Abstract
With the rapid-development of AI technology, artificial intelligence algorithms for the aerospace applications have shown very good simulation performance in many areas. Among the spaceborne application fields, star identification can be seen as a typical pattern recognition process. It’s also the key part of attitude determination of the satellites, which requires the algorithm to be robust and efficient due to the limited computing and storing resources of the spaceborne computers. Nevertheless, most of the previous algorithms are not possible to be applied in practical due to the reasons above. This article proposes a strategy of constructing ‘net-structure’ images of stars to build the datasets for training and testing. Besides, a hierarchical convolutional neural network(CNN) with a small size is also designed. It performs good results on robustness and efficiency in the experiments. In the end, a method of fusing the Conv layers and the batch normalization (BN)layers is also adopted to further accelerate the algorithm.
Single object tracking algorithm in occlusion scene based on improved ECO
Authors: Xie Guorong , Jiang Rongqi , Qu Yi 
Published: December 2021

Abstract
To alleviate the occlusion problem in a single object tracking scene, this paper proposes an ECO-MHDU object tracking algorithm with a more powerful anti-occlusion performance based on the ECO tracker. The algorithm first uses the pre-trained MobileNetV3 lightweight backbone network on the ImageNet dataset to replace the ResNet network in the ECO to increase the speed of the algorithm to obtain the shallow and deep feature information of the image, while effectively using the attention mechanism in the MobileNetV3 network to strengthen the algorithm’s ability to extract target features; secondly, use the DropBlock operation on the acquired feature map to generate a random continuous mask on the feature map channel to improve the algorithm’s learning of the global robust spatial structure information; finally, a confidence update strategy is introduced into the GMM sample generation space. To improve the quality of training samples, unreliable tracking states such as confidence detection and occlusion are designed to avoid updating the sample space with damaging information. Compared with the ECO algorithm, the ECO-MHDU algorithm proposed in this paper has a success rate of 68.0% on the occlusion attributes of the OTB100 dataset, which is 2.3% higher than the ECO algorithm, and the ECO-MHDU algorithm also showed the best performance on the entire dataset sequence, with a success rate of 69.3%.
Vehicle and pedestrian target detection in auto driving scene
Authors: Yu Wanbo , Ren Pengjie 
Published: December 2021

Abstract
To improve the target detection accuracy and speed of autonomous driving in various weather environments and small target traffic senarios,an improved YOLOV4 target detection model based on CSPDarknet45_G backbone network is proposed in this paper.By adding a new DBG module which consists of DArknetConv2D + BN + GELU activation function,this model is enhanced in generalization ability and accuracy. We also improved Res unit residual module to enhance shallow features fusing with deep feathers and reduced the number of neurons in the CSP module to simplify the module structure.The K-Means++ clustering algorithm is introduced to obtain the size of the prior box used for target detection to satisfy the data set in this paper. In the captured target vehicle image data set, the model detection result shows that the improved YOLOV4 model achieve an average detection accuracy of 90.45%, a recall of 94.37%, and an FPS of 50 frames per second when the IOU is taken as 0.5, which meet the real-time and accuracy of the detection task in this paper.
Tumor imaging diagnosis analysis based on improved KNN algorithm
Authors: Wang Cailing , Li LeiChao , He SuQiang , Zhang Jing 
Published: December 2021

Abstract
As a simple, effective and non-parameter analysis method, knn is widely used in text classification, image recognition, etc. [1]. However, this method requires a lot of calculations in practical applications, and the uneven distribution of training samples will directly lead to a decrease in the accuracy of tumor image classification. To solve this problem, we propose a method based on dynamic weighted KNN to improve the accuracy of classification, which is used to solve the problem of automatic prediction and classification of medical tumor images based on image features and automatic abnormality detection. According to the classification of tumor image characteristics, it can be divided into two categories: benign and malignant. This method can assist doctors in making medical diagnosis and analysis more accurately. The experimental results show that this method has certain advantages compared with the traditional KNN algorithm.
Fractional strong matching preclusion of some Cartesian product graphs
Authors: Zhu Bo , Zhang Shumin , Ye Chenfu 
Published: December 2021

Abstract
The fractional strong matching preclusion number of a graph is the minimum number of edges and vertices whose deletion leaves the resulting graph without a fractional perfect matching. In this paper, we obtain the fractional strong matching preclusion number for the Cartesian product of a graph and a cycle. As an application, the fractional strong matching preclusion number for torus networks is also obtained.
The influence of color temperature mismatch in star simulator on positioning accuracy and magnitude measurement by star sensor
Authors: Wang Zhiyong , Liu Shishen , Sun Hao , Zhang Jingjing , Li Ruyou , Liu Chen 
Published: December 2021

Abstract
During the calibrating of star sensor, the calibration accuracy is greatly affected by the mismatch between the color temperature of the light and the to-be-measured star, which further affects the attitude measurement accuracy. This paper studied the near-infrared spectra of stars with different color temperatures, and analyzed the errors on star positioning and magnitude measurement of star sensor due to the color temperature mismatch. The results showed that in the central field of view, the spot centroid deviation caused by spectral mismatch is smaller than that in the edge field of view.And the defocus of the imaging surface also affects the spot centroid deviation. Besides, when calibrating with 6000K color temperature light, the maximum measurement error can reach -1.9126 magnitude.
Error factors of AC-DC conversion circuits accuracy
Authors: Jia Dongyu , Yan Ming , Feng Rongwei , Li Shuangyu 
Published: December 2021

Abstract
Voltage standard source is an important basic instrument in the electrical measurement and testing field, and it has important guarantee significance for many industries. AC voltage standard source is based on AC-DC conversion technology to achieve output function of high precision AC voltage. In order to get a better effect of AC-DC conversion, the three factors—operational amplifier, resistance and diode—that have a greater impact on the accuracy of the rectifier output were taken the research object, and their impacts on the circuit error were analyzed respectively. The output result was compared with the output of full wave precision rectification circuit under ideal state, and the scheme of reducing error in the precision rectifier circuit was summarized, which provides a reference for improving the accuracy of AC-DC conversion in the design of full wave rectifier circuit.
Damage Degree analysis of storage failure modes for plastic encapsulated microelectronic devices
Authors: Ju Hang , Liu Shuang 
Published: December 2021

Abstract
After long-term storage, plastic sealing devices must have good performance when installed on the whole machine. Identifying the risk of failure mode and taking preventive measures before failure can effectively improve storage reliability. To ensure the quality of military products, this paper studies the storage failure modes of plastic sealed micro-electronic devices, and uses the method of FMECA to calculate the damage degree of each failure mode and determine the key failure modes. The case analysis shows that the damage degree of failure mode is ranked as external lead corrosion, aging of packaging material, chip corrosion and bonding ball corrosion. The evaluation result accords with the actual situation of the method. The improved FMECA model can better deal with the relative importance of risk factors, improve the accuracy of risk ranking, and quantify risks more reasonably.
Lateral/Directional Control Law Design for Civil Airplane Based on Eigen Structure Assignment
Authors: Li Bingbing , Xu Dongguang , Zheng Xiaohui , Zheng Bowen 
Published: December 2021

Abstract
Considering disadvantages of lateral/directional mode characteristics of civil aircraft, design requirements are thus presented and the P-Beta control law architecture is adopted for the lateral/directional control law. Meanwhile, the practical application of eigen structure assignment in the design of lateral/directional control law is studied. By eigen structure assignment the closed loop is designed, and the decoupling of roll channel and yaw channel is realized. Through the design of feed-forward command channel, the pilot’s stick control roll rate and pedal control sideslip angle are realized. Simulation results show that the designed lateral/directional flight control law could meet design requirements.
Research on Dynamic Characteristics of Constant Power Control of Plunger Pump Variable Regulator
Authors: Dong Haoming , Jin Xiajie , Xing Keli 
Published: December 2021

Abstract
This article takes K3VDT63 variable plunger pump original regulator as the research object, establishes its dynamic motion equation, uses matlab simulation software to establish its simulation model on the basis of this equation, and the dynamic characteristics of the simulation model under different physical parameters Experiment, and get the dynamic response curve and result of variable regulator constant power control under the influence of various factors.
Physical characterization of biopolymers with starch from potato and cassava organic wastes polymerized in water
Authors: Quintana D N , Sanabria D P , Castro H F , Roa K L , Paredes R A , Vargas Y C 
Published: December 2021

Abstract
During the last decades, the use of plastic has become indispensable for the daily life of people; the global production of these materials reaches approximately more than 200 million tons per year. For this reason, research has been carried out to manufacture substitute materials that have similar physical properties, such as starch-based biopolymers; in this research we initially characterized the physical properties of a biopolymer based on starch polymerized in water, without plasticizers, and also to find an optimal proportion between starch and water; in this way an experimental design is generated where the proportion of these two varies, in which starch extracted from potato and cassava wastes was used. These biopolymers were characterized for linear shrinkage, density, and hardness properties. The results of the characterizations showed that the proportions lower than 1:5 starch-water present difficulty to process and deficiency in the homogeneity of the mixture, while the proportions higher than 1:5 presented a linear shrinkage higher than 82. 69% and a loss in weight higher than 74.45%; on the other hand, the hardness analysis showed an average of 79 points on the shore A scale and density with an average of 1.055 g/cm3, the results determined that the most adequate proportion is 1:6.5 starch-water.
Statistical analysis of cutting tool wear in machining centers
Authors: Arévalo-Ruedas J H , Espinel-Blanco E , Florez-Solano E 
Published: December 2021

Abstract
Cutting tools have great use in the industry for their great effectiveness at the time of use, but it is important to know what the proper use is, because the misuse or constant use of such tools, can cause excessive wear and tear that will reduce tool life. There are different methods and equations to measure the useful life of the tool, it is important to know its state so that at the time of being used in a machining process does not cause irreversible damage to the part. One of the most well-known equations is the Taylor equation where they relate useful lifetime to cutting speed. This project was developed in order to demonstrate, by means of equations and graphs, the lifetime and wear of the cutting tools, as well as the application of statistical equations that allow the analysis of the results obtained in the laboratory; a statistical study was able to evaluate the wear on the cutting tool, obtaining statistically the useful life of the tool in each machining process and calculate in the same way the total useful life of the tool.
Low energy event classification in IceCube using boosted decision trees
Authors: Leonard DeHolton K. 
Published: December 2021

Abstract
The DeepCore sub-array within the IceCube Neutrino Observatory is a densely instrumented region of Antarctic ice designed to observe atmospheric neutrino interactions above 5 GeV via Cherenkov radiation. An essential aspect of any neutrino oscillation analysis is the ability to accurately identify the flavor of neutrino events in the detector. This task is particularly difficult at low energies when very little light is deposited in the detector. Here we discuss the use of machine learning to perform event classification at low energies in IceCube using a boosted decision tree (BDT). A BDT is trained using reconstructed quantities to identify track-like events, which result from muon neutrino charged current interactions. This new method improves the accuracy of particle identification compared to traditional classification methods which rely on univariate straight cuts.
Embedded software developments in KM3NeT phase I
Authors: van Beveren V. , Real D. , Chiarusi T. , Calvo D. , Mastroianni S. , Musico P. , Pellegrini G. , Jansweijer P. , Colonges S. , Bozza C. , Filippini F. , Nicolau C. , Díaz A. 
Published: December 2021

Abstract
The KM3NeT collaboration has already produced more than one thousand acquisition boards, used for building two deep-sea neutrino detectors at the bottom of the Mediterranean Sea, with the aim of instrumenting a volume of several cubic kilometers with light sensors to detect the Cherenkov radiation produced in neutrino interactions. The so-called digital optical modules, house the PMTs and the acquisition and control electronics of the module, the central logic board, which includes a Xilinx FPGA and embedded soft processor. The present work presents the architecture and functionalities of the software embedded in the soft processor of the central logic board.
Demonstrating a single-block 3D-segmented plastic-scintillator detector
Authors: Boyarintsev A. , De Roeck A. , Dolan S. , Gendotti A. , Grynyov B. , Kose U. , Kovalchuk S. , Nepokupnaya T. , Rubbia A. , Sgalaberna D. , Sibilieva T. , Zhao X.Y. 
Published: December 2021

Abstract
Three-dimensional finely grained plastic scintillator
detectors bring many advantages in particle detectors, allowing a
massive active target which enables a high-precision tracking of
interaction products, excellent calorimetry and a sub-nanosecond
time resolution. Whilst such detectors can be scaled up to
several-tonnes, as required by future neutrino experiments, a
relatively long production time, where each single
plastic-scintillator element is independently manufactured and
machined, together with potential challenges in the assembly,
complicates their realisation. In this manuscript we propose a novel
design for 3D granular scintillator detectors where
O(1 cm3) cubes are efficiently glued in a single block of
scintillator after being produced via cast polymerization, which can
enable rapid and cost-efficient detector construction. This work
could become particularly relevant for the detectors of the
next-generation long-baseline neutrino-oscillation experiments, such
as DUNE, Hyper-Kamiokande and ESSnuSB.
Modeling of U-shaped composite detectors
Authors: Chakraborty A. , Kshetri R. , Patra A.S. 
Published: December 2021

Abstract
We have investigated the basic operation of a composite
detector comprising of elements arranged in the shape of an U-shaped
rectangular well. Considering an isotropic scattering of gamma-rays
and partial energy absorptions in up to four detector modules,
expressions for the addback factor and the peak-to-total ratio have
been obtained in terms of only one probability amplitude. We have
compared the performance of two U-shaped detectors having different
geometries and observed negligible gain in addback due to the longer
arms. For completeness, comparisons have been made with composite
detectors like the two element stacked detector and the two level
pyramidal detector, both being embedded inside the U-shaped
detector. Our pen-on-paper approach could be used to understand the
operation of modern arrays having detector elements arranged in
various sophisticated ways.
A review of the importance of mineral nitrogen cycling in the plant-soil-microbe system of permafrost-affected soils—changing the paradigm
Authors: Ramm Elisabeth , Liu Chunyan , Ambus Per , Butterbach-Bahl Klaus , Hu Bin , Martikainen Pertti J , Marushchak Maija E , Mueller Carsten W , Rennenberg Heinz , Schloter Michael , Siljanen Henri M P , Voigt Carolina , Werner Christian , Biasi Christina , Dannenmann Michael 
Published: December 2021

Abstract
The paradigm that permafrost-affected soils show restricted mineral nitrogen (N) cycling in favor of organic N compounds is based on the observation that net N mineralization rates in these cold climates are negligible. However, we find here that this perception is wrong. By synthesizing published data on N cycling in the plant-soil-microbe system of permafrost ecosystems we show that gross ammonification and nitrification rates in active layers were of similar magnitude and showed a similar dependence on soil organic carbon (C) and total N concentrations as observed in temperate and tropical systems. Moreover, high protein depolymerization rates and only marginal effects of C:N stoichiometry on gross N turnover provided little evidence for N limitation. Instead, the rather short period when soils are not frozen is the single main factor limiting N turnover. High gross rates of mineral N cycling are thus facilitated by released protection of organic matter in active layers with nitrification gaining particular importance in N-rich soils, such as organic soils without vegetation. Our finding that permafrost-affected soils show vigorous N cycling activity is confirmed by the rich functional microbial community which can be found both in active and permafrost layers. The high rates of N cycling and soil N availability are supported by biological N fixation, while atmospheric N deposition in the Arctic still is marginal except for fire-affected areas. In line with high soil mineral N production, recent plant physiological research indicates a higher importance of mineral plant N nutrition than previously thought. Our synthesis shows that mineral N production and turnover rates in active layers of permafrost-affected soils do not generally differ from those observed in temperate or tropical soils. We therefore suggest to adjust the permafrost N cycle paradigm, assigning a generally important role to mineral N cycling. This new paradigm suggests larger permafrost N climate feedbacks than assumed previously.