bluuebunny/crossref_metadata_2025_split huggingface dataset:
An anomaly detector as a clinical decision support system for parotid gland delineations
Authors: Papaconstadopoulos Pavlos , González Patrick , Carbaat Casper , Simões Rita , Beemster Herbert , Koetsveld Folkert , Remeijer Peter , Janssen Tomas 
Published: April 2021

Abstract

Purpose. Auto-contouring (AC) is rapidly becoming standard practice for OAR contouring. However, in clinical practice, clinicians still need to manually check and correct contours. Anomaly detection systems (ADS) can aid the clinical decision process by suggesting which structures require corrections or not, greatly enhancing the value of AC. The purpose of this work is to develop and evaluate a decision support system for detecting anomalies in the case of parotid gland delineations. Methods. Head and neck parotid gland delineations (1037 right, 1038 left), were retrieved from the Netherlands Cancer Institute (NKI) database. Morphological and image-based features were extracted from each patient’s CT and structure set. An isolation forest model was initially trained on 70% of the data, of which 10% had synthetically generated anomalies and validated on the remaining 30% of clinical data. The ADS was tested on an independent set of 250 patients (Normal: 174, Anomalies: 76) and on a clinical autocontouring software. Results. Applied to the validation set, the ADS system resulted in area under the curve (AUC) values of 0.93 and 0.94 for the parotid left and right respectively. Image features appeared more important than morphological, but using all features resulted marginally in the best model. Applied to the test set the ADS system reached an accuracy level of 0.83 and 0.81 for the parotid left and right respectively. The ADS was particularly sensitive to uniform expansions/contractions, misplacements, extra/missing slices and anisotropic over-contouring. Conclusion. Anomaly detection can serve as a powerful contour quality assurance tool, especially for cases of organ misplacement and over-contouring.
Smooth plasma etching of GeSn nanowires for gate-all-around field effect transistors
Authors: Eustache E , Mahjoub M A , Guerfi Y , Labau S , Aubin J , Hartmann J M , Bassani F , David S , Salem B 
Published: April 2021

Abstract
We report on the nanopatterning of horizontal and vertical germanium-tin (Ge1−x
Sn
x
or GeSn) nanowires by inductively coupled plasma reactive ion etching for gate-all-around field effect transistors. First, a chlorine based chemistry has been investigated and optimal conditions identified for GeSn 6% alloys. Then, plasma etching was optimized to etch high Sn content GeSn alloys (up to 15%) with a high anisotropy, smooth sidewalls and a high selectivity versus a hydrogen silsesquioxane hard mask. We have shown that, in order to obtain smooth surfaces after plasma etching, a HCl pre-treatment was mandatory to eliminate the native Sn and Ge oxides. This behavior was even more pronounced for high Sn contents. Finally, we succeeded in patterning 20 nm wide suspended beams from GeSn layers with Sn concentrations up to 15%.
Modeling and characterization for straight twisted polymer fiber actuators in blocked torsion: effect of radial thermal expansion
Authors: Takagi Kentaro , Iwai Hiroki , Oiwa Chihaya , Irisawa Toshihira , Shioya Masatoshi , Masuya Ken , Tahara Kenji , Sakurai Daichi , Watanabe Haruhiko , Asaka Kinji 
Published: April 2021

Abstract
This paper discusses a new model and experimental characterization for thermal responses of straight twisted polymer fiber (TPF) actuators in blocked torsion. The proposed model is derived from combining the fiber stiffness matrix with Shafer’s model of free torsion. The derived model predicts that the blocking torque increases as the initial twist increases. Although it is not widely recognized, the tension of a straight TPF decreases as the initial torsion increases, and this paper explains this fact. The proposed model predicts the decrease in tension by using Shafer’s kinematic model that considers the effect of radial thermal expansion. Experimental characterization and model verification are performed using nylon 6 (polyamide 6) fiber samples with ten different initial twists, ranging from weak to strong. The results indicate that as the initial twist increases, the torque increases and the tension decreases. The tension fluctuates with respect to time. The experimental results show that the shear modulus increases as the initial twist increases. The predictions of the proposed model are reasonably consistent with the experimental thermal responses of straight TPFs in blocked torsion when the constants obtained by experimental characterization are used.
Multiple plasmon-induced transparency with extra-high FOM based on a MIM waveguide composed of stubs
Authors: Hao Xiangxiang , Huo Yiping , He Qian , Guo Yiyuan , Niu Qiqiang , Cui Pengfei , Wang Yunyan , Song Meina 
Published: April 2021

Abstract
A plasmon structure based on a metal-insulator-metal (MIM) waveguide composed of three stubs (TSs) is proposed, and its transmission characteristics are studied numerically by the finite element method (FEM). The simulation results show that multiple plasmon-induced transparencies (PITs) with high transmission can be produced in the structure and can be tuned effectively. By adjusting the structure parameters, more high-order PITs with narrower window are generated. Furthermore, the proposed MIM waveguide is sensitive to the environment and the maximum values of refractive index sensitivity and figure of merit (FOM) are 1340 nm R−1IU−1 and 251/RIU, respectively. Multiple, adjustable and narrow PITs with high FOM can be induced in the proposed structure, which can be used in the fields of multi-channel filters, optical switches, storages, sensors, and so on.
Diffraction of vortex Gaussian beams from a two-dimensional Raman-induced grating
Authors: Arkhipkin V G , Myslivets S A 
Published: April 2021

Abstract
In this paper, we study diffraction of a vortex Gaussian probe beam on a two-dimensional (2D) Raman-induced diffraction grating. Both near- and far-field diffraction of a vortex beam is considered. In the near field, quasi-Talbot images occur at specific distances from the grating, which corresponds to the classical Talbot length. Diffraction patterns in the Talbot planes are a periodic 2D array of ring-like vortex beamlets with topological charges (TCs) equal to the illuminating probe beam’s charge. The lateral (off-axis) beamlets consist of several overlapping vortices with the TCs l = 1 and l =−1, and their centers (singular points) are offset relative to each other. It is shown that in the near field the TC is conserved, and the total diffraction field represents a single (global) vortex with an effective TC equal to the charge of the vortex probe beam. In the far field, diffraction patterns are also a 2D array of ring-like local vortices with a period depending on the z coordinate. Their TCs are equal to the charge of the probe field. It is shown that in a far field, the diffracted field’s total TC is also equal to that of the probe field. We demonstrate that by choosing the pump field parameters, one can effectively control the intensity of diffraction orders.
Design of Dynamic Evaluation Algorithm for Classroom Mathematics Teaching
Authors: Cai Wenhuan 
Published: April 2021

Abstract
With the reform and development of education, there is a clear gap between our country’s current evaluation theories, methods and systems and the requirements of quality education, which has become a bottleneck restricting the overall implementation of quality education. Therefore, explore and try to change the evaluation function, evaluation method, evaluation technology and other content, establishing a developmental mathematics teaching evaluation system that embodies the theory of quality education is an objective requirement for the overall implementation of quality education. The purpose of this article is to research and design the dynamic evaluation algorithm of classroom mathematics teaching. This article takes the city’s key teaching reform subject “Research and Practice on the Dynamic Evaluation Method of Classroom Mathematics Teaching” as the research background to develop a classroom math teaching quality evaluation system. On the basis of inheriting the original, feasible and effective classroom mathematics teaching evaluation methods and means, this paper establishes a set of classroom mathematics teaching evaluation system structure, and uses the network-based computer evaluation system as a tool to complete the collection and arrangement of evaluation data And analysis process, provide a random evaluation platform for each evaluator, record all evaluation activities and evaluation results of the evaluator, and provide it to the evaluators for evaluation information query. This article gives a comprehensive evaluation method for teachers’ mathematics teaching effect, which can be both quantitative and qualitative. It can give a comprehensive evaluation of the combination of quantity and sex to each link of teacher’s mathematics teaching according to the change of evaluation information. Experimental research shows that teachers with a Ph.D. degree in language behavior are about 12% higher than those with a master’s degree, and the proportion of classroom silence and technology usage is lower than that of teachers with a master’s degree.
Keywords of Search Engine Optimization based on Corpus
Authors: Li Runtao 
Published: April 2021

Abstract
With the development of network, keywords have become an important way of retrieval, which is the window for academic papers to enter circulation and citation. Therefore, the selection of keywords is very important to improve the retrieval rate. Based on this, this paper carries out a corpus based search engine optimization keyword research. Based on one million English corpora, this paper analyzes and studies 3933 key words from the definition and function of keywords, the characteristics of keywords, selection methods, arrangement order, composition, quantity and writing format. It also analyzes the algorithm and ranking principle of search engine, discusses the optimization of website structure, keywords and single page, the punishment of search engine and the rescue method after being punished by search engine. According to the statistical research on the frequency of key words, the number of keywords is mainly 1-2 words, accounting for 90% of the total number. It can be seen that the search engine optimization technology used in the research of keyword optimization in the website can improve the website ranking and realize the value of the website.
Computer Network Security under the Background of Big Data
Authors: Chen Fei 
Published: April 2021

Abstract
With the advent of the era of big data, data has exploded. This paper mainly studies the analysis of computer network security under the background of big data. In order to make these data intuitively reflect the network security situation, this paper uses the method of weight allocation to normalize the five groups of data, and allocates a larger weight to the security problems with high network security threat and a small weight to the security problems with low network security threat. In this paper, 3603 sample data are randomly selected as evaluation data according to the proportion of the type of data set unchanged. After setting the parameters, you can train and test. According to the risk level, take corresponding control measures to control the system risk at an acceptable level. The data shows that a certain number of attacks are carried out on the protected network in the 5th, 12th, 20th, 28th, 36th, 44th and 52nd minutes, and the scale of each attack is twice that of the last attack. The results show that the construction and deduction method of network security event scenarios can provide effective support for the research of network security incident coping strategies.
Data Transmission Security in Computer Network Communication
Authors: Chen Fei 
Published: April 2021

Abstract
In recent years, computer network communication technology has made considerable progress and development, and its scale has now covered all aspects of society and people’s lives. However, while computer network technology promotes social development and improves the convenience of people’s lives, there are still many security problems, especially the difficulty of ensuring the security of user data, which has become a prominent problem in the further development and improvement of communication technology. This article takes the network communication security technology as an entry point, and analyzes its technical types with the aid of data encryption technology, and then analyzes and studies its security in computer network communication data transmission according to the specific points proposed. Through the substantial technical analysis of the computer network security system, the possibility of the system being attacked can be reduced to a certain extent, and the security of network data can be improved. Through the analysis of the integrity of the network system, the overall framework of a distributed network security early warning system based on the network is established, and various structures of the system are analyzed. The network load analysis module is responsible for using key performance index data, such as user traffic, number of users and wireless utilization, and analyzes and classifies the network cell load by combining the partial least square method and BP neural network, so that the key cell performance analysis module is mainly Analyze key performance index data of key communities, obtain early warning thresholds through clustering algorithms, and implement a dynamic early warning system to provide guidance for network planning and mining in key small areas. The database module is responsible for storing all performance data and performance analysis results; the performance query module is responsible for querying and analyzing performance data and static warnings, and presents them to users in the form of text and graphics. Experimental research results show that in this information age, the development of computer networks plays a very important role in the development of our country. Computer network operators make full use of cluster analysis, data mining, encryption algorithms, and early warning systems to conduct research to fully improve the security performance of data in network communications.
Innovative Application of Artificial Intelligence Technology in College Physical Education
Authors: Wen Jiao 
Published: April 2021

Abstract
Against the background of the new era, the birth of artificial intelligence technology opened a new chapter in human development. Artificial intelligence technology has been developed in many places. The report discusses the application and innovation of artificial intelligence technology in college sports. The first thing people think of artificial intelligence is robots. In fact, it can be said that artificial intelligence can replace human labor. Artificial intelligence is a product of modern technology and cannot be understood unilaterally. For example, the various means of transportation used in people’s daily travel is an artificial intelligence that can replace people’s walking. Another example is that elevators can replace people on stairs. It is also a type of artificial intelligence, which is not an advanced technology. Product, it is also seen everywhere in people’s daily life. Artificial intelligence is a synthesis of scientific and intelligent technology created by human beings. It is a scientific technology including computer science, cognition, logic, etc., formed through mutual intersection and integration. In recent years, artificial intelligence has achieved considerable development, but there are still a series of unsolved problems, and the development of artificial intelligence is still very long. This article studies what artificial intelligence has facilitated and changed the physical education in colleges and universities, and what changes have taken place in the teaching mode are all worthy of our thinking. As a result, artificial intelligence technology is convenient for teachers and students in teaching. Let’s take a look at how to innovate.
Variational Quantum Algorithm and Its Application on Non-Linear Equations
Authors: Yang Yihang , Shan Zheng , Zhao Bo , Xu Le 
Published: April 2021

Abstract
Quantum algorithms of factoring problem have been paid more and more attention since Shor’s algorithm was proposed. Combining the current quantum computer hardware level and integer factorization quantum algorithms, this paper proposes a “classical + quantum” hybrid solution. This scheme first adopts classical methods and corresponding rules in the preprocessing step to simplify the nonlinear equations, which is used to reduce the number of qubits needed for the cost Hamiltonian. Then the variational quantum algorithm is used to find the approximate ground state of the cost Hamiltonian, which encodes the solution of the nonlinear equations. The program was verified on the IBM QX4 quantum machine, and the results showed that this hybrid solution can effectively reduce the quantum resources required to solve the nonlinear equations.
Hierarchical Attention Maps for Super Resolution
Authors: Zhang Zhiqin , Zhang Bo 
Published: April 2021

Abstract
Recent state-of-the-art super-resolution methods have achieved impressive performance on ideal datasets. However, these methods always fail in balance between spatial details and high-level perceptual information. Most of them adopt downsampling step to construct Low-Resolution (LR) and High-Resolution (HR) training which may lose local spatial details. To address this issue, we focus on designing a hierarchical attention maps mechanism for recovering both local spatial details and global perceptual information. By using our novel Hierarchical attention module, we can acquire better High-Resolution (HR) predicted images. Finally, we propose a hierarchical multiple scale feature concatenation module aiming at better perception. Extensive experiments on real-world images demonstrate that our method achieved better visual quality both for perception and quantitative estimation.
RETRACTED: A Feasibility Study on Improving the Quality of Sports Competitions Based on Big Data Analysis
Authors: Li Guangjian 
Published: April 2021

Abstract
With the development of China’s sports power development strategy, the quality of sports competitions also needs to be further improved. Only in this way can we better play its role in promoting sports and sports. The application of big data technology is an important way to improve the quality of sports competitions. Big data technology can not only comprehensively mine and collect sports competition data, but also perform objective, comprehensive and efficient analysis and processing of massive technologies. This will not only provide better protection for athletes, but also provide spectators with a better watching experience, thus laying a good foundation for comprehensively improving the quality of sports competitions.
Environmental and political implications of underestimated cropland burning in Ukraine
Authors: Hall Joanne V , Zibtsev Sergiy V , Giglio Louis , Skakun Sergii , Myroniuk Viktor , Zhuravel Oleksandr , Goldammer Johann Georg , Kussul Nataliia 
Published: April 2021

Abstract
Open burning is illegal in Ukraine, yet Ukraine has, on average, 300 times more fire activity per year (2001–2019) than most European countries. In 2016 and 2017, 47% of Ukraine was identified as cultivated area, with a total of 70% of land area dedicated to agricultural use. Over 57% of all active fires in Ukraine detected using space-borne Visible Infrared Imaging Radiometer Suite (VIIRS) during 2016 and 2017 were associated with pre-planting field clearing and post-harvest crop residue removal, meaning that the majority of these fires are preventable. Due to the small size and transient nature of cropland burns, satellite-based burned area (BA) estimates are often underestimated. Moreover, traditional spectral-based BA algorithms are not suitable for distinguishing burned from plowed fields, especially in the black soil regions of Ukraine. Therefore, we developed a method to estimate agricultural BA by calibrating VIIRS active fire data with exhaustively mapped cropland reference areas (42 958 fields). Our study found that cropland BA was significantly underestimated (by 30%–63%) in the widely used Moderate Resolution Imaging Spectroradiometer-based MCD64A1 BA product, and by 95%–99.9% in Ukraine’s National Greenhouse Gas Inventory. Although crop residue burns are smaller and emit far less emissions than larger wildfires, reliable monitoring of crop residue burning has a number of important benefits, including (a) improving regional air quality models and the subsequent understanding of human health impacts due to the proximity of crop residue burns to urban locations, (b) ensuring an accurate representation of predominantly smaller fires in regional emission inventories, and (c) increasing awareness of often illegal managed open burning to provide improved decision-making support for policy and resource managers.
Characterising stochastic motion in heterogeneous media driven by coloured non-Gaussian noise
Authors: Mutothya Nicholas Mwilu , Xu Yong , Li Yongge , Metzler Ralf 
Published: April 2021

Abstract
We study the stochastic motion of a test particle in a heterogeneous medium in terms of a position dependent diffusion coefficient mimicking measured deterministic diffusivity gradients in biological cells or the inherent heterogeneity of geophysical systems. Compared to previous studies we here investigate the effect of the interplay of anomalous diffusion effected by position dependent diffusion coefficients and coloured non-Gaussian noise. The latter is chosen to be distributed according to Tsallis’ q-distribution, representing a popular example for a non-extensive statistic. We obtain the ensemble and time averaged mean squared displacements for this generalised process and establish its non-ergodic properties as well as analyse the non-Gaussian nature of the associated displacement distribution. We consider both non-stratified and stratified environments.
Compressive Strength of a Prescribed Control Mix for High Performance Self-compacting Concrete
Authors: Mark O G , Ede A N , Arum C , Bamigboye G O , Oyebisi S O , Jolayemi K J 
Published: April 2021

Abstract
Another way of improving concrete production involves incorporating the unique features of high performance concrete with the special properties of self-compacting concrete, resulting in another type of concrete called high performance self-compacting concrete (HPSCC). Many researchers have developed diverse designed control mix for HPSCC which were obtained through several and rigorous designed trial mixes. Yet, little work has been done on prescribed control mix for HPSCC. The purpose of this paper is to establish a prescribed control mix ratio for HPSCC and to test by conducting compressive strength test. Review of the various designed control mix ratios is done in this paper. A logical prescribed control mix ratio of 1:1.02:0.95 has been established for an HPSCC with 0.36 w/c proportion, 0.02 superplasticizer/cement proportion. The compressive strength gave 36.10 MPa at 7 days curing age, 41.76 MPa at 14 days curing age and 57.29 MPa at 28 days curing age. This strength result satisfied the strength criteriaa of HPSCC, according to EFNARC It is therefore recommended that a prescribed control mix of 1:1.02:0.95 be used if the minimum crushing strength value expected at 28 days is 40 N/mm2 for an HPSCC.