bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interference between atomic Rb (5d
5/2–5p
3/2) and (5p
3/2–5s
1/2) coherences: observation of an exceptional point by quantum beating at ∼2.1 THz
Authors: Goldshlag W , Su R , Park S , Reboli T O , Eden J G 
Published: August 2021

Abstract
Coupled oscillators are prevalent in nature and fundamental to fields as disparate as astrophysics, photonics, the mechanical sciences, and geophysics. Theory has identified singularities in the response of coupled oscillators, known as exceptional points (EPs), that are associated with non-Hermitian operators and lie at the transition between weak and strong coupling of the oscillator. Although several EPs have been reported or predicted to exist in nanophotonic resonators and Feshbach resonances, for example, tuning the phase of two interfering atomic or molecular coherences near an EP has not been demonstrated previously. We report the observation of an EP associated with a pair of interfering atomic coherences in Rb, oscillating at 386.3 and 384.2 THz, and confirm the theoretical prediction of an abrupt phase shift of ∼π/4 as the EP is traversed by independently varying two experimental parameters. Pairs (and trios) of coupled coherences in thermal Rb atoms are established among the 7s
1/2, 5d
5/2, 5p
3/2, and 5s
1/2 states in pump–probe experiments with <200 fs laser pulses, and observed directly in the temporal and spectral domains through the ensuing quantum beating in the ∼2–36 THz interval. Interference between the (5d
5/2–5p
3/2) and (5p
3/2–5s
1/2) coherences is mediated by the 5p
3/2 state and detected through quantum beating in the vicinity of the (5d
5/2–5p
3/2)–(5p
3/2–5s
1/2) difference frequency of 2.11 THz which is monitored by a parametric four-wave mixing process. Phase of this composite atomic oscillator is first controlled by varying the mean Rb–Rb nearest neighbor distance (⟨R⟩) in a thermalized vapor. A discontinuous transition of (0.8 ± 0.2) ∼ π/4 radians in the phase of the coupled oscillator occurs when ⟨R⟩ is varied over the ∼80–90 nm interval, a phase shift associated with the transformation of a broadband, dissipative oscillator (characterized by a Fano interference window) into a strongly-coupled system resonant at 2.1 THz.
Coupled harmonic oscillator models for correlated plasmons in one-dimensional and quasi-one-dimensional systems
Authors: Khandelwal Aarushi , Mohammad Tashrif Shazed , Rusydi Andrivo 
Published: August 2021

Abstract
A new phenomenon of correlated plasmons was first observed in the insulating phase of the Sr1−x
Nb1−y
O3+δ
family (Asamara et al 2017 Nat. Commun.
8 15271). The correlated plasmons are tunable, have multiple plasmonic frequencies, and exhibit low loss—making them desirable in numerous plasmonic applications. However, their fundamental mechanism is yet to be explored. While conventional plasmons can be understood solely by considering long-range interactions, unconventional correlated plasmons arise in correlated electron systems and require consideration of the short-range interactions. Here, we report how the interplay of short-range and long-range interactions determines the correlated plasmon phenomena through a coupled harmonic oscillator model of both 1D and quasi-1D systems. In each system, the impact of various physical parameters like the number of oscillators, energy scale, free electron scattering parameter, quasi-particle concentration, charges, effective masses, and Coulomb interaction strengths are explored to gain an understanding of their impact on the complex dielectric function and loss function. We study both cases where the parameters are the same for all quasi-particles and where effective mass, Coulomb interaction strength, and charge are varied for individual quasi-particles. In an extended model of the quasi-1D system, we study both cases where the rung symmetry of all parameters is conserved and where it is broken. When rung symmetry is conserved, the overall trends in optical and plasmonic peaks are the same as the 1D model, though the peaks tend to shift to higher energies and amplitudes. When rung symmetry is broken, the quasi-1D behavior deviates significantly from the 1D model, including an increase in the maximum possible number of optical and plasmonic peaks. Overall, our results demonstrate the significance of the interplay of short-range and long-range interactions in determining the correlated plasmons and identifying how various parameters can be used to tune the resulting plasmons.
A reliable technique to fabricate superconducting joints between single grain, Y–Ba–Cu–O bulk superconductors
Authors: Congreve J V J , Dennis A R , Shi Y , Bumby C W , Druiff H , Cardwell D A , Durrell J H 
Published: August 2021

Abstract
The production of large (RE)Ba–Cu–O single grains ((RE)BCO), where RE = Y, Gd or Sm, of complex geometries is presently limited by the intrinsic slowness of the grain growth process. Additionally, the shapes achievable using established melt processing are constrained by the small number of post-processing techniques available. These materials are brittle and hard, which makes machining a difficult task and largely eliminates the possibility of producing highly intricate shapes. An alternative to this slow and inflexible growth process would be to join many small single grains to form one large composite grain, connected by high-performance superconducting joints. A reliable joining technique would also overcome the need for the careful and time-consuming post-growth machining processes. In this work we report on the use of single grain YBCO–Ag as an interface medium to achieve superconducting joints between (RE)BCO bulks. This joining technique is relatively quick and does not require tight process parameter control as there is no need to re-grow the interface joining material. We report on six joints produced from samples cut and joined in a variety of orientations. In addition, a joint was produced using bulk YBCO from two independent single grains. The trapped field properties of the resulting joined sample were measured and the microstructure at the joint was examined. We show that this simple but effective joining technique makes it possible to produce multiple composite grains with comparable superconducting properties to those of a single grain of the same size.
Probing inflation with precision bispectra
Authors: Clarke Philip , Shellard E.P.S. 
Published: August 2021

Abstract
Calculating the primordial bispectrum predicted by a model
of inflation and comparing it to what we see in the sky is very
computationally intensive, necessitating layers of approximations
and limiting the models which can be constrained. Exploiting the
inherent separability of the tree level in-in formalism using
expansions in separable basis functions provides a means by which to
obviate some of these difficulties. Here, we develop this approach
further into a practical and efficient numerical methodology which
can be applied to a much wider and more complicated range of
bispectrum phenomenology, making an important step forward towards
observational pipelines which can directly confront specific models
of inflation. We describe a simple augmented Legendre polynomial
basis and its advantages, then test the method on single-field
inflation models with non-trivial phenomenology, showing that our
calculation of these coefficients is fast and accurate to high
orders.
Quantitative evaluation of trunk function and the StartReact effect during reaching in patients with cervical and thoracic spinal cord injury
Authors: Castillo-Escario Yolanda , Kumru Hatice , Valls-Solé Josep , García-Alen Loreto , Jané Raimon , Vidal Joan 
Published: August 2021

Abstract

Objective. Impaired trunk stability is frequent in spinal cord injury (SCI), but there is a lack of quantitative measures for assessing trunk function. Our objectives were to: (a) evaluate trunk muscle activity and movement patterns during a reaching task in SCI patients, (b) compare the impact of cervical (cSCI) and thoracic (tSCI) injuries in trunk function, and (c) investigate the effects of a startling acoustic stimulus (SAS) in these patients. Approach. Electromyographic (EMG) and smartphone accelerometer data were recorded from 15 cSCI patients, nine tSCI patients, and 24 healthy controls, during a reaching task requiring trunk tilting. We calculated the response time (RespT) until pressing a target button, EMG onset latencies and amplitudes, and trunk tilt, lateral deviation, and other movement features from accelerometry. Statistical analysis was applied to analyze the effects of group (cSCI, tSCI, control) and condition (SAS, non-SAS) in each outcome measure. Main results. SCI patients, especially those with cSCI, presented significantly longer RespT and EMG onset latencies than controls. Moreover, in SCI patients, forward trunk tilt was accompanied by significant lateral deviation. RespT and EMG latencies were remarkably shortened by the SAS (the so-called StartReact effect) in tSCI patients and controls, but not in cSCI patients, who also showed higher variability. Significance. The combination of EMG and smartphone accelerometer data can provide quantitative measures for the assessment of trunk function in SCI. Our results show deficits in postural control and compensatory strategies employed by SCI patients, including delayed responses and higher lateral deviations, possibly to improve sitting balance. This is the first study investigating the StartReact responses in trunk muscles in SCI patients and shows that the SAS significantly accelerates RespT in tSCI, but not in cSCI, suggesting an increased cortical control exerted by these patients.
Research on Electrical Control System of CNC Machine Tool Based on Vector Control
Authors: Zhang Wei , Zhao Qingsong , Tuo Jianzhi 
Published: August 2021

Abstract
With the rapid development of science and technology, the society demands more and more diversification of products, which requires the cycle of product renewal to be shorter and shorter, which makes the proportion of multi-variety and small batch production increase obviously. CNC (Computer Numerical Control) machine tool is a very popular production machine in China’s industrial production, which is mainly composed of hardware circuit, mechanical part and lower computer software. CNC machine tools play an important role in solving the problem of precision or complex parts, and the data of CNC machine tools in mechatronics system are typical. Numerical control technology is related to a country’s position in international industry, so accelerating the development of advanced numerical control technology and strengthening the construction of numerical control equipment are important methods to improve a country’s position in international industry. Based on vector control technology, this paper discusses the design of electrical control system of CNC machine tools, and studies the methods to improve the safety, reliability, machining accuracy and productivity of CNC machine tools, in order to provide reference for the further application of vector control in CNC machine tools.
Regression analysis and prediction using LSTM model and machine learning methods
Authors: Tan Fangbi 
Published: August 2021

Abstract
In this paper, the LSTM model in deep learning is applied to regression analysis, and the LSTM model is used to solve the problems of nonlinearity and data interdependence in regression analysis, so as to improve the traditional regression analysis model. Through the actual modeling application experiment, on the one hand, the prediction accuracy of different model parameters is compared and analyzed, on the other hand, the effectiveness and practicability of LSTM model in multiple regression analysis and prediction are confirmed.
Overview of insulator state intelligent assessment in smart grid through fuzzy logic method
Authors: Luo Simin , Luan Le , Cui Yiping , Xu Shuo , Guo Quinten , Liu Tian 
Published: August 2021

Abstract
In the transmission system, the operating state of the line insulator is always a state quantity with both fuzziness and randomness. Fuzzy logic theory has certain advantages for evaluating such a system with both fuzziness and randomness. According to the theory of fuzzy logic in the field of insulator state evaluation development situation, this paper introduces four methods - weights fuzzy logic method, the multistage fuzzy logic judgment, variable weight fuzzy logic judgment and cloud theory. The paper also analyses the characteristics and advantages of four methods, the results show that the cloud theory and variable weight fuzzy logic method more engineering significance.
Generalized Control Algorithm and Artificial Intelligence Technology for Quadruped Walking Robot
Authors: Fei Guobiao , Liu Fenggang 
Published: August 2021

Abstract
Quadruped walking robot has superior adaptability and high adaptive mobility in various environments. These special advantages are particularly prominent in the mobile robot community. In this work, we introduce the omnidirectional gait and the rotational gait approach, which is a generalized control algorithm for executing any directional instruction. In addition, in order to improve the stability of the quadruped walking robot, we optimize the walking Angle and foot order. The proposed ideas were applied to the practical design of MRWallspect III, which was designed to examine large surfaces in industrial facilities. The effectiveness of the proposed method is verified by experiments on a robot.
Design and Implementation of Data Acquisition and Analysis System for Intelligent Meter in Smart Grid
Authors: Chen Jintao , Jiang Jianfeng , Shen Juan , Huang Liang , Sheng Qing , Zhou Qiang , Han Dongjun 
Published: August 2021

Abstract
Design a smart meter data acquisition and analysis system to collect and process electrical energy data, report remote data and collect electrical energy. The data collector of the smart meter supports multiple protocols and the collinear communication of the electric meters, and the collinear communication of the electric meters with different protocols, different models and different communication speeds is connected on the same communication line. The data is sent to the data collector through the RS-485 bus, and the data collector collects and processes the data and uploads it to the server through the WAN. The design of the smart meter data acquisition and analysis system effectively improves the scientific validity of electric energy billing.
RETRACTED: Analysis of the Impact of the Internet on Farmers’ Intelligent Selection under the Era of Big Data and Cloud Computing
Authors: Lu Youlan 
Published: August 2021

Abstract
With the advent of the era of big data, many industries have become deeply integrated with Internet technologies. Farmers using the Internet for entrepreneurship can promote the reform of agricultural development, optimize the entrepreneurial mode of farmers, drive farmers to increase their income, and inject new strength into the construction of the new socialist countryside. By reviewing relevant literature and data, this paper reviews the development trend and opportunities of farmers’ Internet entrepreneurship in the era of big data, analyzes the problems in the process of entrepreneurship and the corresponding solution strategies, in order to provide some reference value for the development of farmers’ Internet entrepreneurship.
Analysis and Construction of EEMD Smart Model and Fuzzy Forecasting through Improved Bayesian Estimation
Authors: Tang Liyao , Cui Zijian , Liu Kaishuo 
Published: August 2021

Abstract
Different portfolio models will have a great impact on the model rate of return. In order to meet the data needs of portfolio investment forecasting, a big data generation method based on incremental Bayesian network model is proposed. Firstly, the fuzzy interval number is constructed by using the global GM (1pare 1) prediction model, then the fuzzy Mmurv model is established based on the interval fuzzy number, and the model is optimized based on the midpoint, radius and acceptability of the interval number, thus a single objective programming model with parameters is obtained. The future data is partially generated by using the time series generation algorithm, and the Bayesian network model trained by historical data is updated with the newly generated data. So that the updated Bayesian network can reflect the relationship between the variables and the laws contained in the new and old financial data in this period of time. And use the model to predict the amount of foreign direct investment absorbed by China in 2020, test the robustness and analyze the impact of major random events to show the reliability of the prediction. The analysis is carried out on multiple scales. The results show that the integration of IMF1 and IMF2 components through the white noise test can be regarded as the random impact of external factors; the cycle length of IMF3 component is about 3 years, which can be regarded as the inventory cycle caused by the change of enterprise inventory; the cycle length of IMF4 component is 5 years, which can be regarded as political cycle; the cycle length of IMF5 component is about 20 years, which can be regarded as construction cycle. The set of portfolio paths is generated by path search algorithm in Bayesian network, and the big data set with real data characteristics is generated according to the probability distribution of each path. The experimental results show that the method is feasible and ensures a certain accuracy. The forecast results show that the amount of foreign direct investment in China will continue to fluctuate seasonally and in a trend in recent years.
Research on the Assessment of Qingdao Residents through Artificial Intelligence Algorithms and Grey Prediction Model
Authors: Shi Zhenqi , Lv Luyu 
Published: August 2021

Abstract
The model of health level system was constructed based on medical treatment, environment, policy, life and culture in Qingdao, the weight of each index was determined based on entropy method, and the impact of each index on residents’ health level was analyzed. Then the comprehensive score of health level was calculated according to the weight of each index. Finally, according to the grey prediction model, the comprehensive score is fitted and predicted, and relevant suggestions are provided according to the fitting and prediction conclusions.
Research and Application of Computer Artificial Intelligence Technology in Machine Pronunciation
Authors: Zhang Yisha 
Published: August 2021

Abstract
The traditional oral English training system uses a layered training strategy, which cannot meet the system performance design requirements. For this reason, the thesis designs a computer artificial intelligence system for oral English training based on human-computer interaction. The system hardware structure is composed of C8051F021 single chip microcomputer, LM317 chip, LM337 chip, A/D chip and IN5822 diode, which is used to reliably control the sampling frequency of the chip. At the same time, the paper introduces Sugeno points to realize the correct evaluation of spoken pronunciation. First, the randomness of natural language pronunciation and the instability of the speech processing system are modeled by fuzzy measure and credibility, and then they are integrated into the Sugeno integration framework to evaluate the language score instead of the specific score. The experimental results prove the credibility and stability of the evaluation model in closed and open tests.
The Application of Cloud Computing and Big Data Correlation Analysis to the Intelligent Evaluation Modeling
Authors: Xiao Yunxuan , Yang Leize 
Published: August 2021

Abstract
This passage gave an analyse big data collected from UNESCO and report from governments then give health index to countries and focus on Brazil to give some possible solutions to the problem. First, we aim to develop EHSIS model to assess the health of any national higher education system. We define the weight of the indexes by subjective weighting and objective weighting by using Analytic Hierarchy Process and Principal Component Analysis (AHP) to compare the importance of different weight and Entropy Method to get the weight from comparing the degree of dispersion of indicators. Then combine the weight and the normalized data to get the model to give scores to sample countries relying on the eight indexes. Then, we screened out several indicators with greater influence through Principal Component Analysis and correlation analysis of factors and extracted the recommended adjustable indicators to 3. We found that the proportion of foreign students has the greatest impact on the health and sustainability of higher education in the country, and it has a high correlation with QS excellent schools and UN News excellent schools, which are difficult to control. Other indicators that have a greater impact include the teacher-student ratio, employment rate, etc. Last, we forecast the changes of indexes without the policy by Grey prediction and use the memory-less of Markov Chain to predict the change after introducing new policies. In order to evaluate the effectiveness of our policy, we utilize EHSIS model to give the score and compare the score with and without the policy and find a significant increase in score. What’s more, we discuss the real-world influence and the hardness of achieving the goal.
Intelligent Promotion Mechanism of the Sustainable Aquaculture from the Perspective of Game Theory
Authors: Chang Zhao 
Published: August 2021

Abstract
China has always attached great attention to aquaculture development, but some inappropriate aquaculture modes have brought a series of marine resources waste and environment problems. In order to solve these problems more effectively and lead to a sustainable aquaculture mode, based on stakeholder analysis, this paper constructs evolutionary game models on both supply side and demand side of aquaculture, and puts forward some suggestions for sustainable aquaculture development. The results indicate that in initial stage of promoting sustainable aquaculture, mandatory control measures and economic subsidies of the government are needed to the promotion. After gradually forming a mature management mode, the market should play a decisive role in resource allocation, so as to realize the sustainable development of aquaculture with the tripartite win-win interests in the game.
Development and Research of Intelligent Testing Information System for Full Performance Test of Metrology Equipment
Authors: Ma Xiaofang , Ding Haili , Zhou Yuanfeng , Liu Pengyuan , Hu Tingting , Yan Shaokui 
Published: August 2021

Abstract
Aiming at the measurement laboratory with many types of testing equipment, many test items, low automation of instruments and equipment, inconsistent data interface standards, ineffective coordination of testing services, low level of laboratory testing resources and data sharing, and difficulty in achieving effective data and resources connection, etc. Problem, design and develop an intelligent detection system for full performance test of measurement equipment. The research and development of the full-performance test intelligent detection system replaces manual operation with standardized automatic operation, which improves the consistency, standardization and reliability of the full-performance test of the measurement equipment, and realizes the reproducibility and traceability of the test. The automatic collection of full performance test data has been realized, laying a solid foundation for the construction of the national industrial basic database.