Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Management Science from 1991 to 2021: Review of Publications Indexed in WoS

Management is a discipline that has existed for as long as humans have, but its theoretical underpinnings are relatively new. There was already evidence of the creation and use of management ideas since 2900 BC, when Egypt was deploying over ten thousand people to build the pyramids. During the Middle Ages, the Greek, Roman, and Chinese empires all created their own versions of management theory. Modern management throughs were a 20th-century phenomenon, and management was only recognized as a formal study since the late 19th century. In this paper, the development background, thoughts and schools, existing problems, research methodology, discipline branches, and functions of management as a social science are systematically discussed and elaborated. A systematic review approach was used to summarize and analyze the 2,772,999 publications included in the Web of Science from 1991 to 2021 to find out the overall trend of publication, the published organization or institution, and the high-frequency research areas.
Integrand reduction for two-loop scattering amplitudes through multivariate polynomial division

We describe the application of a novel approach for the reduction of scattering amplitudes, based on multivariate polynomial division, which we have recently presented. This technique yields the complete integrand decomposition for arbitrary amplitudes, regardless of the number of loops. It allows for the determination of the residue at any multiparticle cut, whose knowledge is a mandatory prerequisite for applying the integrand-reduction procedure. By using the division modulo Gr\"obner basis, we can derive a simple integrand recurrence relation that generates the multiparticle pole decomposition for integrands of arbitrary multiloop amplitudes. We apply the new reduction algorithm to the two-loop planar and nonplanar diagrams contributing to the five-point scattering amplitudes in $\mathcal{N}=4$ super Yang-Mills and $\mathcal{N}=8$ supergravity in four dimensions, whose numerator functions contain up to rank-two terms in the integration momenta. We determine all polynomial residues parametrizing the cuts of the corresponding topologies and subtopologies. We obtain the integral basis for the decomposition of each diagram from the polynomial form of the residues. Our approach is well suited for a seminumerical implementation, and its general mathematical properties provide an effective algorithm for the generalization of the integrand-reduction method to all orders in perturbation theory.
Structural damage detection of old ADA steel truss bridge using vibration data

This study proposes a statistical‐based detection method that is responsive to damage and not to environmental and operational conditions. The method serves as a damage recognition system for structural health monitoring using field measurements from real bridges. Vehicle‐induced bridge and ambient vibration measurements collected from the benchmark Old ADA steel truss bridge situated in Japan were utilized to validate the proposed method. The steel truss members in the bridge were subjected to five different damage scenarios to represent common potential problems in structural health monitoring of real‐life applications. The collected measurements have been completely published and made available online. A combination of principal component analysis (PCA) and linear discriminant analysis (LDA) transformation is utilized as a statistical‐based recognition technique. Vibration data representing power spectral density (PSD) functions were tested as damage‐sensitive features from identified condition sources. The proposed combination of the PCA‐LDA transformation system outperforms the popular PCA transformation as a statistical model for classification of state conditions. Although the first two principal components of PCA hold 50–85% of the variation in data, the first two components from PCA‐ LDA hold about 95% of the total variation. As a result, the three PCs, of PCA‐LDA, visualization successfully managed to classify the five structural damage scenarios into their five individual subgroups.
Modeling and Quality Analysis of Algorithms for Formation of Panoramic Images for Different

The issues of image formation in the technical vision system are considered, the sources of primary information in which are video cameras installed in such a way that each controlled area is located in the field of view of two cameras. Modeled and researched results of applying different panning algorithms at different angles tilt of video cameras relative to the vertical axis. The process of railway rolling stock moving through a station or sorting hill is selected as the object of observation. The results of the experiment were compared according to such criteria as speed (task completion time) and quality of the resulting image (estimates of the deviation of the obtained result from the standard).
The scalar bi-spectrum during preheating in single field inflationary models

In single field inflationary models, preheating refers to the phase that immediately follows inflation, but precedes the epoch of reheating. During this phase, the inflaton typically oscillates at the bottom of its potential and gradually transfers its energy to radiation. At the same time, the amplitude of the fields coupled to the inflaton may undergo parametric resonance and, as a consequence, explosive particle production can take place. A priori, these phenomena could lead to an amplification of the super-Hubble scale curvature perturbations which, in turn, would modify the standard inflationary predictions. However, remarkably, it has been shown that, although the Mukhanov-Sasaki variable does undergo narrow parametric instability during preheating, the amplitude of the corresponding super-Hubble curvature perturbations remain constant. Therefore, in single field models, metric preheating does not affect the power spectrum of the large scale perturbations. In this article, we investigate the corresponding effect on the scalar bi-spectrum. Using the Maldacena's formalism, we analytically show that, for modes of cosmological interest, the contributions to the scalar bi-spectrum as the curvature perturbations evolve on super-Hubble scales during preheating is completely negligible. Specifically, we illustrate that, certain terms in the third order action governing the curvature perturbations which may naively be expected to contribute significantly are exactly canceled by other contributions to the bi-spectrum. We corroborate selected analytical results by numerical investigations. We conclude with a brief discussion of the results we have obtained.
Detection of skin defects in loquats based on grayscale features combined with reflectance, absorbance, and Kubelka–Munk spectra

Skin defects are one of the main problems that occur during postharvest grading and processing of loquat, leading to deterioration of loquat, reducing the economic value of the commodity, and causing food quality and safety problems. Improving the identification rate of skin defects in loquat can reduce the economic loss caused by transportation and storage. In this paper, hyperspectral imaging technology was used to collect the reflectance (R), absorbance (A), and Kubelka–Munk (KM) spectra of loquat with skin defects for classification of defects types. Principal component analysis (PCA) was used to obtain the characteristic wavelength images. Competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), uninformative variables elimination (UVE), and Monte Carlo combined with uninformative variables elimination (MCUVE) were used to reduce the dimension of spectral data to obtain the characteristic wavelength. The spectral data and grayscale features were used to establish the spectral model (SPEC) and grayscale features combined with spectral model (MIX). Extreme learning machine (ELM), least squares support vector machine (LS‐SVM), and k‐nearest neighbors (KNN) algorithm were applied to establish a classification model for skin defects in loquat. Comparing the model classification results of the three spectral parameters combined image features, it was found that the A‐CARS‐MIX‐ELM model had the highest accuracy, with a classification accuracy of 98.18%. The number of selected characteristic spectra was 37, accounting for 21.02% of the total spectral number of the whole band. In the online detection process of a large number of fruits, we usually need to improve the detection speed on the premise of high‐precision detection. In this case, the R‐SPA‐MIX‐ELM model can be selected, and the classification accuracy is 94.55%. The number of selected spectra is 10, accounting for 5.68% of the number of wavelengths in the whole band. Consequently, it also provides a theoretical reference for the rapid, nondestructive, and high‐precision fruit online detection technology in the future.
Self-Competitive Learning for Solving Math Word Problem

Math word problem (MWP) aims to automat-001 ically solve mathematical questions given in 002 texts. Most previous MWP models tend to 003 ﬁt the sole ground-truth solution provided by 004 the dataset, without considering the diverse 005 but equivalent solution expressions. To miti-006 gate this issue, we propose a s elf-c ompetitive 007 l earning framework (called SCL), which at-008 tempts to get different predictions and improve 009 the generalization ability of the model by co-010 operatively learning a source network and a 011 pruned competitor network. The competitor 012 network is created by pruning a source net-013 work, which perturbs the source network’s 014 structure and is conducive to generate diverse 015 solutions. The source network and the com-016 petitor network learn collaboratively and teach 017 each other throughout the training process. Ex-018 tensive experiments on two large-scale bench-019 marks demonstrate that our model substan-020 tially outperforms the strong baseline meth-021 ods. In particular, our method improves the 022 best performance (accuracy) by 8.4% (78.4% 023 → 86.8%) for Math23k and 6.2% (70.5% → 024 76.7%) for Ape210K. 025
The Adiabatic Phase Mixing and Heating of Electrons in Buneman Turbulence

The nonlinear development of the strong Buneman instability and the associated fast electron heating in thin current layers with $\Omega_e/\omega_{pe} <1$ are explored. Phase mixing of the electrons in wave potential troughs and a rapid increase in temperature are observed during the saturation of the instability. We show that the motion of trapped electrons can be described using a Hamiltonian formalism in the adiabatic approximation. The process of separatrix crossing as electrons are trapped and de-trapped is irreversible and guarantees that the resulting electron energy gain is a true heating process.
Experimental Study on Characteristics of Plasma Synthetic Jet Actuators With Different Insulating Materials

Plasma synthetic jet actuator (PSJA) has a wide application prospect in the high-speed flow control field for its high jet velocity. In this article, Nylon and Teflon were selected as the insulation materials of synthetic jet actuators to make use of the ionization ablation properties of thermoplastic materials to improve the actuator performance. The performance differences between these actuators and traditional ceramic synthetic jet actuator are obtained. Based on electrical measurement and high-speed schlieren image system, the electrical characteristics and jet performance of the three kinds of actuators at different air pressures are studied. The discharge voltage, current waveform, discharge efficiency, and discharge energy of the three kinds of actuators were almost the same under different pressures. However, Nylon and Teflon materials will be ablated after ionization, resulting in higher jet velocity and longer jet duration time than traditional actuator of ceramic. The ablation of Teflon was most serious. The Teflon actuator had the maximum jet velocity up to 447.51 m/s at 20-kPa pressure. Based on the schlieren image processing method, the affected area of the actuator was calculated. It was found that the maximum affected area of the Teflon actuator was 144.84% larger than that of the ceramic actuator at 100 kPa. The synthetic jet actuator of Teflon had larger affected area and higher jet velocity than other actuators, so it has great application value in high-speed flow field control.
Dijet Azimuthal Decorrelations in pp Collisions at √s=7 TeV

Measurements of dijet azimuthal decorrelations in pp collisions at √s=7 TeV using the CMS detector at the CERN LHC are presented. The analysis is based on an inclusive dijet event sample corresponding to an integrated luminosity of 2.9 pb^(-1). The results are compared to predictions from perturbative QCD calculations and various Monte Carlo event generators. The dijet azimuthal distributions are found to be sensitive to initial-state gluon radiation.
LIKELY MEMBERS OF THE β PICTORIS AND AB DORADUS MOVING GROUPS IN THE NORTH

We present first results from follow-up of targets in the northern hemisphere β Pictoris and AB Doradus moving group candidate list of Schlieder et al. We obtained high-resolution, near-infrared spectra of 27 candidate members to measure their radial velocities and confirm consistent group kinematics. We identify 15 candidates with consistent predicted and measured radial velocities, perform analyses of their six-dimensional (UVWXYZ) Galactic kinematics, and compare to known group member distributions. Based on these analyses, we propose that seven β Pic and eight AB Dor candidates are likely new group members. Four of the likely new β Pic stars are binaries, one a double-lined spectroscopic system. Three of the proposed AB Dor stars are binaries. Counting all binary components, we propose 22 likely members of these young, moving groups. The majority of the proposed members are M2 to M5 dwarfs, the earliest being of type K2. We also present preliminary parameters for the two new spectroscopic binaries identified in the data, the proposed β Pic member and a rejected β Pic candidate. Our candidate selection and follow-up has thus far identified more than 40 low-mass, likely members of these two moving groups. These stars provide a new sample of nearby, young targets for studies of local star formation, disks and exoplanets via direct imaging, and astrophysics in the low-mass regime.
Security evaluation techniques of Cognitive Radio Network status and challenges

Security model is a protection scheme has a different security service to protect network information against malicious nodes. Its aim to specify and enforce security policies, access rights or any encryption algorithm in the network. There are several cryptography methods and modulation techniques on different locations within the security of communications system use to protect entirely network transmission. Cognitive radio networks (CRN) are intended for utilizing radio spectrum effectively. The network formed by cognitive radio devices achieves dynamic spectrum access by sensing the environment and adapting to the frequencies. But due to its enormous applications in wireless networks demands good security methods to be incorporated in CRN. This paper is reviewed the security evaluation of wireless network in general and cognitive radio network in private case by used Fuzzy Logic method for secure cryptography system cognitive radio network architecture.
Running head: GENDER DIFFERENCES IN ACHIEVEMENT EMOTIONS 1 GENDER DIFFERENCES IN ACHIEVEMENT EMOTIONS: A CONTROL-VALUE THEORY APPROACH by

The current study examines whether there are gender differences in general academic contexts within three achievement emotions: prospective outcome emotions, retrospective outcome emotions and activity emotions. I combined Pekrun’s control-value theory with the Achievement Emotion Questionnaire (AEQ) to assess participants’ achievement emotions. Discriminant function analysis revealed statistically and practically significant gender differences in prospective outcome emotions and activity emotions, but not in retrospective outcome emotions. Moreover, females scored higher on three achievement emotions: prospective outcome emotions, retrospective outcome emotions, and activity emotions than males in this study. The current study filled in the gap of prior studies which have not explored gender differences in three achievement emotions: prospective outcome emotions, retrospective outcome emotion and activity emotions, in general domains. Future studies could replicate the current study and explore if other factors would influence the impact of gender on achievement emotions, for example, culture and age. Additionally, researchers could try to apply achievement emotions to improve students’ academic performance.
The physics of randomness and regularities for languages (lifetimes, family trees, and the second languages); in terms of random matrices

The physics of randomness and regularities for languages (mother tongues) and their lifetimes and family trees and for the second languages are studied in terms of two opposite processes; random multiplicative noise [1], and fragmentation [2], where the original model is given in the matrix format. We start with a random initial world, and come out with the regularities, which mimic various empirical data [3] for the present languages.
Advantages of Taguchi Method compared to Response Surface Methodology for achieving the Best Surface Finish in Wire Electrical Discharge Machining (WEDM)

Design of Experiments is a method to predict the optimum conditions of a process to reduce the time and number of experiments to be conducted with limited resources. In this paper, a comparative work on design and analysis of experiments between Taguchi method and response surface methodology is carried out in predicting the set of optimal conditions for obtaining the best surface roughness of commercially pure titanium powder metallurgy component using wire electrical discharge machining process. With surface roughness of the Titanium as the response and pulse on time, pulse off time, and sintering temperature of the wire electrical discharge machining process as the affecting factors, the optimum conditions for the surface roughness of the material have been predicted and analysed. Analysis of variance is used to identify the significant factors affecting the system. Both methods gave the same results and the Taguchi approach requires less number of experiments compared to response surface methodology and the predicted surface roughness of the components with the Taguchi method is 2.4 µm, whereas it is between 2.41-3.04 µm with the Response Surface Methodology. The factor Pulse on Time (N) shows a significant effect on the response of the system.
How experience value affect user stickiness? An empirical research on booking tourism application

This study with a view to explore the influencing factors of user stickiness of booking tourism applications’ users. Conducting surveys on samples from China online, this study analyzes the impact of different levels of user experience value, user satisfaction, and perceived risk on user stickiness by using SPSS 23.0 and AMOS 23.0. Results of correlation analysis and structural equation modeling indicate that both functional experience value and user satisfaction significantly positive influence user stickiness, while neither emotional experience value nor perceived risk have significant impact on user stickiness. In addition, user satisfaction is found an important mediator in the relationship between experience value and user stickiness. In exploring the moderating effect of perceived risk, results find that as perceived risk deepens, both the positive impacts of functional experience value and emotional experience value on user satisfaction are weaken, and the positive influence of functional experience value on user stickiness is decline.
Harvesting Mature Relation Extraction Models from Limited Seed Knowledge: A Self-Development Framework for DS Rule Expansion

Distantly-supervised relation extraction 001 (DSRE) is an effective method to scale relation 002 extraction (RE) to large unlabeled corpora 003 with the utilization of knowledge bases (KBs), 004 but suffers from the scale of KBs and the 005 introduced noise. 006 To alleviate the above two problems, we 007 propose a novel framework called S elf-008 devel O pment r U le ex P ansion ( SOUP ), which 009 starts from limited amount of labeled data 010 and continuously produces low-noise labels on 011 large-scaled unlabeled data by a growing learn-012 able logical rules set. 013 Specifically, SOUP achieves a mutual enhance-014 ment of RE model and logical rules set, first 015 a RE model is trained on the labeled data to 016 summarize the knowledge, then the knowledge 017 is utilized to explore candidate rules from unla-018 beled data, finally high-quality candidates are 019 selected in a graph-based ranking manner to ex-020 tend the logical rules set and new rule-labeled 021 data are provided for better RE model training. 022 Experiments on wiki20 dataset demonstrate 023 that, with limited seed knowledge from small-024 scaled manually labeled data, SOUP achieves 025 significant improvement compared to baselines 026 by producing continuous growth of both logical 027 rules and the RE model, and that labeling noise 028 of SOUP is much less than DS. Furthermore, 029 RE model enhanced by SOUP with 1.6k logical 030 rules learned from prior knowledge could pro-031 duce an equivalent performance to the model 032 trained on data labeled in DS manner by 72k 033 relational facts of KBs. 034
Thin-Torus Limit of Fractional Topological Insulators

We analytically and numerically analyze the one-dimensional "thin-torus" limit of Fractional Topological Insulators in a series of simple models exhibiting exactly flat bands with local hopping. These models are the one-dimensional limit of two dimensional Chern Insulators, and the Hubbard-type interactions projected into their lowest band take particularly simple forms. By exactly solving the many-body interacting spectrum of these models, we show that, just like in the Fractional Quantum Hall effect, the zero modes of the thin-torus limit are CDW states of occupation numbers satisfying generalized Pauli principles. As opposed to the FQH where the thin-torus CDW appear in orbital space, in the thin-torus FCI states, the CDW states are in real-space. We show the counting of the quasihole excitations in the energy spectrum cannot distinguish between a CDW state and a FQH state. However, by exactly computing the entanglement spectrum for the thin-torus states, we show that it can qualitatively and quantitatively distinguish between a CDW and a fractional topological state such as the FCI. We then discover a previously unknown separation of energy scales of the full FQH energy spectrum in the thin torus limit and find that Chern insulator models exhibiting strong isotropic FCI states have a similar structure in their thin-torus limit spectrum. We close by numerically computing the evolution of energy and entanglement spectra from the thin-torus to the isotropic limit. Our results can also be interpreted as an analysis of one-body, 1-dimensional topological insulators stabilized by inversion symmetry in the presence of interactions.