bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of 6 weeks of very low‐volume high‐intensity interval training on oral glucose‐stimulated incretin hormone response
Authors: Hindsø Morten , Kuhlman Anja Birk , Dohlmann Tine Lovsø , Lund Michael Taulo , Hartmann Bolette , Holst Jens Juul , Larsen Steen , Helge Jørn Wulff 
Published: January 2021

ABSTRACTIntroduction: Decreased fasting and oral glucose‐stimulated incretin hormone concentrations following moderate‐intensity continuous endurance training interventions have been reported in glucose‐tolerant people, however results are conflicting. The effect of more time‐efficient, very low‐volume, high‐intensity interval training (HIT) on circulating incretin hormone levels has never been studied.Materials and methods: Ten sedentary and overweight‐to‐obese participants (4 women and 6 men; age 43 ± 6 years (mean ± SD); BMI 30.2 ± 3.2 kg∙m−2; HbA1c 35 ± 5.1 mmol∙mol−1 (5.3 ± 0.3%); VO2max 30 ± 5 ml∙min−1∙kg−1) from the Copenhagen cohort of the METAPREDICT trial underwent 6 weeks of supervised low‐volume HIT (3 sessions per week: 7 × 1 min at ∼100% VO2max separated by 1 min of active recovery). We measured glucose, insulin, C‐peptide, glucagon, GLP‐1 and GIP concentrations during a frequently sampled 75 g oral glucose tolerance test as well as VO2max and body composition before and after the intervention.Results: Training compliance was 100%. Relative VO2max improved after the intervention (median 2.69 ml∙min−1∙kg−1, IQR [0.43; 3.14], p = 0.037) while there were no significant effects on body weight and composition. No significant effects on oral glucose‐stimulated glucose and hormone responses or estimates of insulin sensitivity and β‐cell function were observed.Conclusion: Low‐volume HIT improved aerobic fitness, but neither affected glucose tolerance nor oral glucose‐stimulated incretin hormone responses in sedentary and overweight‐to‐obese people.Highlights
Ten sedentary, overweight‐to‐obese, glucose‐tolerant participants underwent 6 weeks of supervised, very low‐volume HIT.
Aerobic fitness improved.
Fasting and oral glucose‐stimulated incretin hormone concentrations were not affected.
Plenty of soliton solutions to the DNA Peyrard-Bishop equation via two distinctive strategies
Authors: Ouahid Loubna 
Published: January 2021

Abstract
Here, the Deoxyribo-Nucleic Acid (DNA) dynamic equation that arises from the oscillator chain named the Peyrard-Bishop model for plenty of solitary wave solutions is presented. The efficacy of newly designed algorithms are investigated, namely, the extended Auxiliary equation method and Kudryashov expansion method for constructing the new solitary wave solutions of the DNAdynamic Peyrard-Bishop model with beta-derivative. Here, the proposed methods contribute to a range of accurate solutions for soliton, including light, dark, and other solutions are obtained. In addition, some results are also clarified by computer simulations demonstrating the uniqueness of our work relative to the existing literature on the classic Peyrard-Bishop model. These solutions lead to the issue of the possibility to expand the method to deal with other non-linear equations of fractional space-time derivatives in non-linear science. It is noted that the newly proposed approach is accurate and is used to create new general closed-form solutions for all other fractional NPDEs.
The new physics of dust in plasmas
Authors: Mamun A A 
Published: January 2021

Abstract
The new physics of dust, which arises due to dust-plasma interaction in space environments and laboratory devices, is presented. The new research horizons (different new fields of physics involving many challenging research problems and open issues) introduced by this new physics of dust in plasmas are explained. The basic features of dust-plasma interaction, particularly, basic characteristics of dust in plasmas, and typical dusty plasma parameters for different space and laboratory conditions are presented. The complexity and the diversity of the field of the new physics of dust in plasmas are briefly discussed. The theoretical and experimental discoveries of dust associated linear waves, nonlinear structures, and some other important phenomena are mentioned. The basic features of dust associated nonlinear structures (viz. solitary waves, shock structures, and Mach cones) obtained from our recent published works are briefly discussed.
Doping and disorder dependent isotope exponent in hole doped cuprates
Authors: Islam R S , Naqib S H 
Published: January 2021

Abstract
The nature of the variation of oxygen isotope exponent (IE) with the number of doped holes, p, in the CuO2 planes has been a source of considerable debate. The large IE over certain range of hole concentrations always casts a shadow over any proposal where non-phononic mechanism is invoked to describe pairing in cuprates. On the other hand, existing theoretical schemes, based on electron-phonon interactions, cannot describe the anomalous features shown by the IE as a function of hole concentration/disorder, either quantitatively or qualitatively. Based on an experiment relating the possibility of Fermi-surface reconstruction to the thermoelectric transport measurements (Laliberté et al. Nature Commun. 2, 432 (2011)), we propose here a simple scenario where isotope substitutions affect the charge/spin stripe state via the coupling to the underlying lattice and thereby change the superconducting Tc
. In this picture, significant part of the IE, over an extended p-range, actually originates from the isotope induced stripe modulation and is not directly related to the characteristic energy scale of the phonons mediating the Cooper pairing. This proposal qualitatively explains all the disorder- and p-dependent features of the IE seen in hole doped high-Tc
cuprates. We also provide with an outline of some experiments that can verify the degree of validity of the proposed scheme.
Non-monotonic potential description of the cross-section, vector and tensor analyzing powers of the 6Li+12C elastic scattering at 30 and 50 MeV†
Authors: Nilima Athoy , Hossain S , Azad M M B , Billah M M , Tariq A S B , Uddin M A , Bhattacharjee S , Azizur Rahman M , Basak A K 
Published: January 2021

Abstract
This work illustrates, for the first time, the analysis of tensor analyzing powers (T
20, T
21, T
22) along with the differential cross-section (CS) and the vector analyzing power iT
11 for the 6Li+12C elastic scattering at 30 and 50 MeVwithin the framework of an optical model (OM) using microscopic shallow non-monotonic (NM) potentials. The NM potential is generated from the energy density functional formalism (EDF) [Brueckner et al., Phys. Rev., 168 (1968) 1184] using a realistic two-nucleon interaction incorporating Pauli Exclusion principle. The shallow NM potential can describe the experimental angular distributions of CS and analyzing powers of the elastic scattering data. The OM analysis of the data at this energy does not indicate their sensitivity on the nuclear matter incompressibility K.
Using X-ray Fluorescence Technique Propagation of Chromium (Cr) from Poultry Feeds to Different Parts of Chicken including her Eggs†
Authors: Rajib Arifuzzaman , Tariqur Rahman Md. , Md. Ismail Abu Bakar 
Published: January 2021

Abstract
This paper presents the detection and propagation of heavy metals, particularly Chromium (Cr), in poultry in the Rajshahi area using the X-ray fluorescence (XRF) technique. The investigation was done to assess the possible transfer of heavy metals from poultry feeds to chicken meat. The study was carried out in the Rajshahi including collection feeds to chicken. It was found that a considerable amount of Cr was confirmed in all four locally produced poultry feeds and also assured that the Cr contained in chicken propagates to the chicken meat and egg. Among the four most widely used feeds in the Rajshahi region, “Adorsho Feed (Pabna)” shows a maximum Cr concentration of 17.3 ppm. Six different parts of the chicken for different ages which were grown by “Adorsho Feed” were considered for further study. About 4.3 ppm of Cr was found in Yolk whereas a little small about 2.7 ppm was found in the albumin. The average value of Cr in six parts of chicken remains almost the same, which is 3.74 ppm, irrespective of age. It is found that about 21.6% of Cr was propagated from the poultry feed to chicken flesh and also about 90% of Cr was propagated from the chicken to egg. The experimental results indicate that the investigation of the transmission of heavy metals like Cr from feed to egg and poultry is efficiently evaluated by using X-ray Fluorescence Technique.
A Multi-Layers Perceptron for predicting weekly learner commitment in MOOCs
Authors: Mourdi Youssef , Sadgal Mohammed , El Kabtane Hamada , El Abdallaoui Hasna El Alaoui 
Published: January 2021

Abstract
Since they were first set up in 2008, MOOCs have continued to integrate very deeply into the distance learning field. They have been adopted by a very large number of universities in order to complement face-to-face learning and thus remedy the massive number of students that the infrastructures can no longer support. In spite of the investments made for their development, MOOCs suffer from a huge drop-out rate of around 90%. This problem creates a number of difficulties for the instructors, including monitoring learners and group formation. In order to help the instructors to identify learners at risk of dropping out, this paper presents a model based on Multi-Layer Perceptron (MLP) that provides weekly predictions of each learner's engagement based on their behaviour. Our model has been tested on a data set of 3585 learners and has shown a high ability to identify this type of learner with an average accuracy of 90.3%.
Numerical estimation of log-GARCH model with relaxed moment assumptions
Authors: Settar Abdeljalil , Fatmi Nadia Idrissi , Badaoui Mohammed 
Published: January 2021

AbstractThis paper provides algorithms for the numerical estimation of the log-GARCH model parameters with no assumptions on the existence of the log-moment orders greater than one. Our approach is based on the quasi-maximum likelihood estimation combined with the information filter. The proposed estimation is employed for two aims. The first is to treat the zero returns considered as missing values through an EM imputation algorithm. The second is to compute the kurtosis of the log-GARCH process by the so-called, right and left measures. A Monte Carlo simulation is performed to investigate the potential of the proposed algorithms to improve the accuracy of the quasi-maximum likelihood for the parameter estimation and the treatment of zero returns as well as to check the robustness of the used kurtosis measures.
A coupled Meshless-FEM method based on strong form of Radial Point Interpolation Method (RPIM)
Authors: El Kadmiri R. , Belaasilia Y. , Timesli A. , Kadiri M. S. 
Published: January 2021

Abstract
In this present work, we are implementing a novel hybrid method based on the coupling of RPIM in strong form and Finite Element Method (FEM). The basic idea is to ensure the coupling between the two methods through the collocation technique based on RPIM interpolation. This technique is used to evaluate the local equations of the problem at the interface between FEM and RPIM regions. We can avoid numerical integrations of a big part of nodes using the strong form of RPIM. Numerical studies show that this method gives reasonably accurate results consistent with the theory.
Application and Typical Case of Unmanned Aerial Vehicles Combined with Building 3D Modeling
Authors: Li Minhui , Yin Hang , Cheng Dongji , Xu Xinli , He Ya 
Published: January 2021

Abstract
With the development of unmanned aerial vehicle (UAV) technology, the application of UAV is becoming more and more extensive, including the application of UAV in building 3D modeling. This paper introduces the composition of commonly used related equipment and some key UAV technologies combined with building 3D modeling: 3D laser scanning technology, Photogrammetry, Multi-view 3D reconstruction technology and Seismic disaster prevention technology. This paper also studies practical applications and related cases. On the one hand, UAV can be used in the protection of ancient building heritage. Combined with photography, measurement, modeling technology, UAVs can rapid and efficient access to relevant building three-dimensional information, including building damage and overall configuration, then provide important information and reference for building heritage protection. On the other hand, UAVs can also carry out multi-faceted evaluation and survey of modern buildings, collect topography, guide seismic planning and post-disaster reconstruction, and save project costs.
Technology Application Base on ASP.NET Model View Controller
Authors: Liu Yuanchun , Zhu Heyi 
Published: January 2021

Abstract
The Music Mall System is developed by ASP.NET model view controller technology. It realizes the functions of registration and login, song search, playing songs, collecting and commenting, shopping mall and so on. This paper firstly introduces the function design, the database design of the music mall system, secondly describes the architecture and finally elaborates the implementation codes of the specific modules. Using this system, users can quickly search and listen to relevant music, buy related music peripheral products. Through reasonable page layout and detailed user experience, users can feel happy and satisfied.
RobotDrlSim: A Real Time Robot Simulation Platform for Reinforcement Learning and Human Interactive Demonstration Learning
Authors: Sun Te , Gong Liang , Li Xvdong , Xie Shenghan , Chen Zhaorun , Hu Qizi , Filliat David 
Published: January 2021

Abstract
Deep reinforcement learning (DRL) techniques give robotics research an AI boost in many applications. In order to simultaneously accommodate the complex robotic behaviour simulation and DRL algorithm verification, a new simulation platform, namely the RobotDrlSim, is proposed.
First, we design a standardized API interfacing mechanism for coordinating diverse environments on RobotDrlSim platform, where PyBullet simulator is equipped with an API to form a physical engine for robotics simulation. Second, benchmark DRL models are included in the baseline library for evaluation. Third, real-time human-robot interactions can be captured and imported to drive the RobotDrlSim tasks, which provide big data-stream for reinforcement learning. Experimentations show that cutting-edge DRL algorithms developed in python can be seamlessly deployed to the robots, and human interactions can be availed in training the robots. RobotDrlSim is valid for efficiently developing DRL algorithms for artificial intelligence models of robots, and it is especially suitable for the robot educational purposes.
Optimal Model and Algorithm of Cross-layer Dynamic Resource Allocation based on Multi-Period and Utility
Authors: Shao Qing , Su Yang 
Published: January 2021

Abstract
An optimal model and algorithm for dynamic resource allocation in satellite communication systems is proposed to further promote the system throughput and fairness based on user satisfaction. It takes the parameters of application layer, data link layer and physical layer into consideration and constructs a new kind of utility function by using the cross-layer design strategy and converts the resource allocation problem into a utility maximization model. The optimal solution of the model is solved by the combination of the Lagrange multiplier method and the Greedy algorithm, which maximizes the utility and ensures the optimal resources allocation of the satellite communication system in the multiple periods. The simulation results show that the proposed optimal model and algorithm effectively promote the throughput and fairness based on user satisfaction on the premise of ensuring service quality, therefore it can meet the requirements of the variety and the dynamic change of the service in the satellite communication system.
Adaptive Conflict Detection Algorithm Based on Rochester Software Transactional Memory
Authors: Liu Ying , Liu Junting , Gao Fuxiang 
Published: January 2021

Abstract
When the transactional memory system detects conflicts, the more read-write addresses are, the higher the false positive rate of this algorithm is. This paper studies the problem and proposes a new signature based optimization algorithm, adaptive increase signature algorithm (AISA). The algorithm can calculate the saturation value of the number of read-write addresses, and dynamically adjust the size of bit string through the calculated saturation value, thus greatly reducing the false positive rate. The experimental results show that AISA can control the false positive rate at a low level on the basis of considering the space cost, and its effect is almost the same as that of 6 times of space, which will improve the performance of transactional memory system greatly.
Structured Data Extraction Method of Hazard Description Text Based on Strong Part-of-speech Matching
Authors: Zhou Yi , Chen Cheng , Zhang Peng , Wu Aizhi , Ai Xinbo 
Published: January 2021

Abstract
In the field of work safety, the hazard description text is an important basis for accident investigation. However, because the text is unstructured, it causes a lot of inconvenience for subsequent analysis and processing, so it’s necessary to extract structured information from hazard description text. At present, there are few corpus and annotated data of hazard description text, cause it’s difficult to extract structured information based on machine learning models. To solve this problem, we proposed a new method based on strong part-of-speech pattern matching This method is based on the short length and relative simplicity of the hazard description text, matching predefined patterns through the part-of-speech sequences of the text, and then extract structured information of hazard entity and entity description. The method achieved 86.2% accuracy with text processing speed 5514 iters/s when only a small amount of annotated data required.
Extended LDA Based Topic Analysis for Big Sentiment Data
Authors: Xie Shengzhen , Sui Ling , Li Jiaxin , Kou Kaiqi , Wang Zhiqiong 
Published: January 2021

Abstract
Owing to the massive emergence of multi-modal data related to big sentiment events, the topic analysis of the text cannot accurately reflect the topic distribution of the whole data set. There are some problems such as semantic deficiency and difficulty in integration. Therefore, the extended LDA(eLDA) based topic analysis for big sentiment data is posed. Firstly, the semantic analysis of text and image data is carried out by probability generation method respectively. The semantic correlation between multi-modal data is used for visual topic learning, a visual topic model is established, and the mapping between visual data and text topics is realized. Furthermore, the fusion of text, audio, video and image data is realized, and multimodal theme analysis is carried out accordingly. The experimental results show that the multimodal topic analysis method can effectively obtain the subject words related to the semantics of big sentiment data. The effect of the subject words tracked by the multi-modal data analysis method is better than that of the single text subject words extraction, which can provide basis for emotional analysis of big sentiment events.
Study on Denoising Algorithm for Power Quality Disturbances Based on Variational Mode Decomposition
Authors: Li Yan , Li Kaicheng , Liu Chang , Xiao Xiangui , Chen Xiya , Wang Menghao 
Published: January 2021

Abstract
The power quality signals are always mixed with noise, which will influence the accurate measurement and characteristic extraction. Therefore, it’s important to denoise for the signal processing. This paper puts forward a novel denoising algorithm for power quality disturbances (PQDs) based on variational mode decomposition (VMD) and the truth that the energy density times the average period of each intrinsic mode function (IMF) is a constant. Firstly, the VMD algorithm is used to decompose the white noise into several IMF components. Then, the average period energy product of each IMF component is calculated, and some of the IMF components are selected for reconstruction according to the judgment criterion to obtain the denoised signal. The simulation results show that the proposed algorithm can greatly improve the signal-to-noise ratio (SNR), and the denoising effect is better than that of wavelet threshold and ensemble empirical mode decomposition (EEMD) algorithm.
Part of the Unipotency of Free Group Generated by Two Elements Whose Maximum Jordan Matrix Does Not Exceed 8 Times
Authors: Zhen Chaoran , Yang Xinsong 
Published: January 2021

Abstract
Intelligent calculations can already assist in the completion of mathematical proofs. We have completed a partial verification of an important theory with data calculation as the main method. When the dimension is ten, free group generated by two elements with linear representation is unipotent when the primitive elements are unipotent and the maximum Jordan block does not exceed the eighth order, at the same time there is a primitive element with the maximum Jordan block not exceeding the second order.
Optimization Study on Emergency Communication in the Great East Japan Earthquake
Authors: Guo Jia , Xu Zhen , Zhao Yu 
Published: January 2021

Abstract
Emergency communication is a special communication mechanism used for disaster rescue. The article took the Great East Japan Earthquake as the research object. It was found that mobile communication was the main way in general communication and social media played an important role in emergency communication. The causes of traffic congestion were studied to provide strategies for PSTN and mobile communication. Unitary management system in Japan for the restoration of services was studied, too. At last, the development of satellite communication in Japan and its needs for emergency communication were researched to provide references for emergency communication in China.
Bullet Engraving Automated Comparison Optimization Method Based on Second Moment Invariant
Authors: He Chenggang , Ding Chris H. Q. , Chen Sibao , Wang Jiaxin , Tan Shicheng 
Published: January 2021

Abstract
In the research of bullet engraving comparison method at home and abroad, the traditional method is through visual observation by microscope, comparing line-type engraving of two bullets to distinct whether the line match, which is inefficient and having big error. In this paper we proposed method based on moment invariant to identify the bullet engraving, which eliminate the actual measurement error (translation error and rotation error). Finally we get the high performance result of bullet engraving identifying based on second moment invariant.
Quantile S-N Curve and its Application based on Tukey’s g-and-h Distribution and Whale Optimization Algorithm
Authors: Zhang Jinbao , Zhang Aiju , Wang Min , Wei Yuhu , Gui Peng 
Published: January 2021

Abstract
Tukey’s g-and-h distribution is a generalized implicit distribution based on the transformation of normal distribution, which has a stronger fault-tolerant capability for the fitting of life data distribution. In this paper, the P-S-N curve is modelled through its corresponding location-scale model with quantile expression, so as to improve the life prediction accuracy of mechanical parts in reliability design. Two groups of life experiment data concerning G20CrNi2Mo bearing steel and 104 rolling bearing are used to verify the proposed model. The mean square error (MSE) of experimental data and simulation data is taken as the objective function, and the parameter estimation of the model is realized with the whale optimization algorithm (WOA). The results show that the proposed approach could accurately express the trend of life varying with different loads, and the quantile expression of life data can be realized conveniently.