bluuebunny/crossref_metadata_2025_split huggingface dataset:
Organizational cultural strength as the negative cross-entropy of mindshare: a measure based on descriptive text
Authors: Marchetti Arianna , Puranam Phanish 
Published: April 2022

AbstractThe strength of an organization’s culture is an important property that may have implications for organizational structure, performance, diversity, and inclusion, independent of its content. However, progress on conceptualizing and measuring cultural strength has been restricted so far. We propose a novel measure of an organization’s cultural strength as the negative average cross-entropy of its members’ mindshare distributions, defined on a support comprising a set of firm-specific cultural elements. Using descriptive text data produced by 2.9 million individuals in about 95 thousand US firms from the employee review website Glassdoor.com, we calculate our measure of organizational cultural strength using topic modeling and show that it behaves as theoretically expected: older, smaller, and more geographically concentrated firms have stronger organizational cultures. We also note some intriguing associations between organizational cultural strength, role differentiation, and gender imbalance within firms. Finally, we discuss opportunities for using this new measure to understand how organizations work more generally.
Strong increase of correlations in liquid glycerol observed by nonlinear dielectric techniques
Authors: Thoms Erik , Matyushov Dmitry V. , Richert Ranko 
Published: April 2022

Nonlinear dielectric measurements are an important tool to access material properties and dynamics concealed in their linear counterparts, but the available data are often intermittent and, on occasion, even contradictory. Employing and refining a recently developed technique for high ac field dielectric measurements in the static limit, we ascertain nonlinear effects in glycerol over a wide temperature range from 230 to 320 K. We find that the temperature dependence of the Piekara factor a, which quantifies the saturation effect, changes drastically around 290 K, from ∂a/∂T = +1.4 to −130 in units of 10−18 V2 m−2 K−1. These high values of |a| quantify not only elevated dielectric saturation effects but also indicate a temperature driven increase in higher-order orientational correlations and considerable correction terms with respect to the central limit theorem. No signature of this feature can be found in the corresponding low field data.
An empirical study of Chinese university student advisors’ dynamic identity construction in the context of individual consultation
Authors: Chen Jing , Zhao Xin 
Published: April 2022

Abstract
While extensive research has been done on pragmatic identity construction in various contexts by various social groups, little is known about how and why university student advisors may dynamically construct their pragmatic identity in their interaction with their students. Based on the analysis of naturally-occurring data about 5 student advisors’ consultation, this article explores the various pragmatic identities constructed by Chinese university student advisors as well as their underlying motivations. It finds that the identities constructed by the student advisors can be non-professional (such as a student, an individual, a friend, and a family member) and professional (such as an administrator, a tutor and a teacher). It suggests that their pragmatic identity construction may signify their effort to balance their various communicative needs in the educational contexts. Such balance may serve to meet their goal of constructing a new type of Chinese advisor-student relation characterized by equality, democracy, and harmony.
A novel superhard boron nitride polymorph with monoclinic symmetry
Authors: Fan Qing-Yang , Li Chen-Si , Zhao Ying-Bo , Song Yan-Xing , Yun Si-Ning 
Published: April 2022

Abstract
In this work, a new superhard material named Pm BN is proposed. The structural properties, stability, mechanical properties, mechanical anisotropy properties, and electronic properties of Pm BN are studied in this work. Pm BN is dynamically and mechanically stable, the relative enthalpy of Pm BN is greater than that of c-BN, and in this respect, and it is more favorable than that of T-B3N3, T-B7N7, tP24 BN, Imm2 BN, NiAs BN, and rocksalt BN. The Young’s modulus, bulk modulus, and shear modulus of Pm BN are 327 GPa, 331 GPa, and 738 GPa, respectively, and according to Chen’s model, Pm BN is a novel superhard material. Compared with its original structure, the mechanical anisotropy of Young’s modulus of Pm BN is larger than that of C14 carbon. Finally, the calculations of the electronic energy band structure show that Pm BN is a semiconductor material with not only a wide band gap but also an indirect band gap.
The masking condition for the quantum state in two-dimensional Hilbert space
Authors: Wang Mei-yi , Zhang Su-juan , Bai Chen-ming , Liu Lu 
Published: April 2022

Abstract
This paper focuses on quantum information masking for the quantum state in two-dimensional Hilbert space. We present a system of equations as the condition of quantum information masking. It is shown that quantum information contained in a single qubit state can be masked, if and only if the coefficients of the quantum state satisfy the given system of equations. By observing the characteristics of non-orthogonal maskable quantum states, we obtain a related conclusion, namely, if two non-orthogonal two-qubit quantum states can mask a single qubit state, they have the same number of terms and the same basis. Finally, for maskable orthogonal quantum states, we analyze two special examples and give their images for an intuitive description.
Phase equilibrium and microstructure of topological AdS black holes in massive gravity *
Authors: Liu Fang , Du Yun-Zhi , Zhao Ren , Li Huai-Fan 
Published: April 2022

Abstract
In order to clearly understand the gravitational theory through the thermal properties of the black hole, it is important to further investigate the first-order phase transition of black holes. In this paper, we adopt different conjugate variables (

,

,

, and

) and apply Maxwell's equal-area law to study the phase equilibrium of a topological black hole in massive gravity. The condition and latent heat of phase transition are displayed as well as the coexistent curve of

. The result shows that the phase transition of this system is the high/low electric potentials one, not only the large/small black holes one. We also analyze the effect of the model's parameters on phase transition. Furthermore we introduce a new order parameter to probe the microstructure of this system. This work will provide the theoretical basis to study the phase structure of topological black holes in massive gravity and to further explore the gravitational theory.
The effect of mental schema evolution on mental workload measurement: an EEG study with simulated quadrotor UAV operation
Authors: Gu Heng , Yao Qunli , Chen He , Ding Zhaohuan , Zhao Xiaochuan , Liu Huapeng , Feng Yunduo , Li Chen , Li Xiaoli 
Published: April 2022

Abstract

Objective. Mental workload is the result of the interactions between the demands of an operation task, the environment in which the task is performed, and the skills, behavior and perception of the performer. Working under a high mental workload can significantly affect an operator’s ability to choose optimal decisions, judgments and motor actions while operating an unmanned aerial vehicle (UAV). However, the effect of mental schema, which reflects the level of expertise of an operator, on mental workload remains unclear. Here, we propose a theoretical framework for describing how the evolution of mental schema affects mental workload from the perspective of cognitive processing. Approach. We recruited 51 students to participate in a 10-day simulated quadrotor UAV flight training exercise. The EEG power spectral density (PSD)-based metrics were used to investigate the changes in neural responses caused by variations in the mental workload at different stages of mental schema evolution. Main results. It was found that the mental schema evolution influenced the direction and change trends of the frontal theta PSD, parietal alpha PSD, and central beta PSD, which are EEG indicators of mental workload. Initially, before the mental schema was formed, only the frontal theta PSD increased with increasing task difficulty; when the mental schema was initially being developed, the frontal theta PSD and the parietal alpha PSD decreased with increasing task difficulty, while the central beta PSD increased with increasing task difficulty. Finally, as the mental schema gradually matured, the trend of the three indicators did not change with increasing task difficulty. However, differences in the frontal PSD became more pronounced across task difficulty levels, while differences in the parietal PSD narrowed. Significance. Our results describe the relationship between the EEG PSD and the mental workload of UAV operators as the mental schema evolved. This suggests that EEG activity can be used to identify the mental schema and mental workload experienced by operators while performing a task, which can not only provide more accurate measurements of mental workload but also provide insights into the development of an operator’s skill level.
Fast parametric curve matching (FPCM) for automatic spike detection
Authors: Kleeva Daria , Soghoyan Gurgen , Komoltsev Ilia , Sinkin Mikhail , Ossadtchi Alexei 
Published: April 2022

Abstract

Objective. Epilepsy is a widely spread neurological disease, whose treatment often requires resection of the pathological cortical tissue. Interictal spike analysis observed in the non-invasively collected EEG or MEG data offers an attractive way to localize epileptogenic cortical structures for surgery planning purposes. Interictal spike detection in lengthy multichannel data is a daunting task that is still often performed manually. This frequently limits such an analysis to a small portion of the data which renders the appropriate risks of missing the potentially epileptogenic region. While a plethora of automatic spike detection techniques have been developed each with its own assumptions and limitations, none of them is ideal and the best results are achieved when the output of several automatic spike detectors are combined. This is especially true in the low signal-to-noise ratio conditions. To this end we propose a novel biomimetic approach for automatic spike detection based on a constrained mixed spline machinery that we dub as fast parametric curve matching (FPCM). Approach. Using the peak-wave shape parametrization, the constrained parametric morphological model is constructed and convolved with the observed multichannel data to efficiently determine mixed spline parameters corresponding to each time-point in the dataset. Then the logical predicates that directly map to verbalized text-book like descriptions of the expected interictal event morphology allow us to accomplish the spike detection task. Main results. The results of simulations mimicking typical low SNR scenarios show the robustness and high receiver operating characteristic AUC values of the FPCM method as compared to the spike detection performed using more conventional approaches such as wavelet decomposition, template matching or simple amplitude thresholding. Applied to the real MEG and EEG data from the human patients and to rat ECoG data, the FPCM technique demonstrates reliable detection of the interictal events and localization of epileptogenic zones concordant with independent conclusions made by the epileptologist. Significance. Since the FPCM is computationally light, tolerant to high amplitude artifacts and flexible to accommodate verbalized descriptions of an arbitrary target morphology, it is likely to complement the existing arsenal of means for analysis of noisy interictal datasets.
A Nonlinear Correction Method on Elastic Lift Coefficient for Civil Aircraft
Authors: Liu Xiaoyan , Chen Kai , Cheng Pan , Sun Yuchen 
Published: April 2022

Abstract
Aerodynamic lift coefficient is nonlinear for an elastic aircraft flying at a high transonic speed, varying with Mach number and dynamic pressure. The common industry practice is that the correction on slope and intercept for linear segment of data curve of wind tunnel test, which is incapable of meeting increasing design requirements whereas aerodynamic coefficients are characterized by nonlinear nature. The nonlinear correction method for elastic lift coefficient is introduced by using equivalent angle of attack. Based on wind tunnel test data of rigid designed aircraft shape, elastic lift coefficient used for load and control analysis is directly obtained, which is applicable to different flight deformation state of a civil aircraft within the flight envelope. The wind tunnel test model was selected as a validation illustration. The analysis shows that the results obtained through the proposed correction method and the elastic test data are in a good agreement. The developed method takes into consideration both the computational efficiency and the precision.
Development of a Horizontal Pneumatic Test System for Shock Response Spectrum
Authors: Zhiqiang Shen , Tingfei Yan , Chuang Liu , Anchao Jiao , Fei Gu 
Published: April 2022

Abstract
Pendulum impact test equipment cannot meet the high magnitude test demand of large products. This paper designed a pneumatic impact test which can make a high-magnitude impact test, giving the design principle of the pneumatic impact test system, introducing the design methods of the pneumatic test system. The test results show that the technical indexes of the system meet the design requirements. The pneumatic impact test system with a 1.25 m× 1.25 m table based on the shock response spectrum principle can realize the inflection frequency adjustable from 500 to 1500 Hz and the slope adjustable from +6 to +9 dB. And it can realize the shock response spectrum test of 5000g magnitude at full load. The test system can meet the current test magnitude and test requirements of spacecraft products. The method proposed in this paper can serve as a reference for the design of this kind of impact test systems.
Barium 5-nitriminotetrazolate - A Powerful Primary Explosive with Resistance High Temperature Properties
Authors: Ni Debin , Liu Jiang , Yuxin Jia , Yang Bing , Yu Guoqiang 
Published: April 2022

Abstract
The primary explosive of barium 5-nitriminotetrazolate was obtained by dehydrating the crystal waters of barium 5-nitriminotetrazolate dihydrate under high temperature, which was shown high decomposition temperature of 384 °C by differential scanning calorimeter (DSC). The preparation route of barium 5-nitriminotetrazolate was relatively safe through using the potassium 5-nitriminotetrazolate as raw material. Barium 5-nitriminotetrazolate could easily initiate hexanitrostilbene (HNS) in combination with long-time stability and low sensitivities, which was promised to apply in high temperature initiator of military and civilian.
Intelligent analysis method for transient stability of power distribution system
Authors: Jia-long Li , Wei Zhang , Lin-lin Ge 
Published: April 2022

Abstract
According to the principle of transient stability of power distribution system, this paper establishes the evaluation model of system transient stability, and studies a new intelligent analysis method of transient stability of power distribution system. Improve the process of power system transient stability analysis through wavelet transform. The experimental results show that the intelligent analysis method of transient stability of power distribution system based on wavelet transform can effectively shorten the analysis time and improve the accuracy.
Solving degree constrained minimum spanning tree problem based on improved fireworks algorithm
Authors: Gao Zunhai , Gui Chengpeng , Liu Yi 
Published: April 2022

Abstract
In the iterative process of fireworks algorithm, an improved algorithm is proposed to improve the local search ability of optimal fitness value and make it more suitable for solving discrete problems, so as to obtain a method to find degree constrained minimum spanning tree. Firstly, the corresponding mathematical model is constructed by analyzing the degree constrained minimum spanning tree, then the explosion operator and the corresponding fitness function are established according to the model, and finally the algorithm is improved to adapt to the discrete fireworks algorithm, so as to achieve the purpose of seeking the degree constrained minimum spanning tree. The example calculation shows that the improved fireworks algorithm can reduce the number of iterations and achieve high accuracy.
Log filtering method based on user behaviors
Authors: Wu Nan , Tang Xueming , Pan Ying 
Published: April 2022

Abstract
In the big data environment, various websites on the Internet have generated more and more user behaviors. Designing a universal log filtering method based on user behaviors is the current research trend. However, the current log filtering technology has disadvantages such as low filtering accuracy and low efficiency. In this paper, we propose a log filtering method based on user behaviors. First, divide user behaviors into multiple sub-behaviors and assign corresponding weights. Obtain and store log information of user behaviors through distributed log collection tools, and the log information of corresponding sub-behaviors below the weight threshold is filtered. Then, the log information of the retained sub-behaviors is processed in parallel through the utility function. The utility function establishes the mapping relationship between user interest degree and sub-behavior indicators. The corresponding log information of the sub-behaviors below the user interest degree threshold is deleted, and the log information of the user’s preferred sub-behaviors is retained, forming an optimized data source for recommendation results, and stored in the data cluster. This method can perform secondary filtering of the massive log information, respond to users’ current requirements and interesting information promptly, improving processing efficiency.
Ontology-based task planning for autonomous unmanned system: framework and principle
Authors: Pang Weijian , Gu Wenguan , Li Hui 
Published: April 2022

Abstract
Operational knowledge is an important factor to improve the autonomy of unmanned systems. How to store and represent operational knowledge semantically and normatively, so that unmanned systems can autonomously accomplish task planning according to the high-level order of humans, carry out re-planning, and make decisions has been a new topic in the autonomous unmanned system field. This paper reviews several typical robot ontologies, as well as modeling and representation methods of uncertain information, proposes the concept of Ontology-based Task Planning(OTP) for the unmanned system, and introduces the principles of ontology construction. Finally, the application of ontology in unmanned combat systems are discussed.
Visual Analysis of Urban Block Risk Based on Bayesian Network——Taking Traffic as an Example
Authors: Yin Shuqi , Yan Xu , Yin Mengzi , Zhang Luming 
Published: April 2022

Abstract
In order to improve urban safety and resilience, this paper focuses on urban traffic and public health emergencies, integrates disaster related data, constructs Bayesian network reasoning model, and uses spatial analysis technology to visualize risk information on dynamic map, analyze the disaster chain risk in different places in the same time period, and then form decision support options to realize reasoning visualization, distribute control of disaster chain evolution, minimize the loss caused by disaster chain effect, and promote urban disaster prevention and reduction.
3D Vehicle Surround View Algorithm for Embedded Platform
Authors: Liang Zuowei , Chen Lei , An Fengwei 
Published: April 2022

Abstract
Although surround view systems have been widely used in advanced automotive, processing speed is still a bottleneck for the embedded system. This paper presents a 3D surround-view algorithm suitable for embedded platforms. Using methods such as extracting regions of interest (ROI) and HSV color screening to improve the efficiency of image registration, there is no need to manually select feature points, which reduces the difficulty of operation. In addition, we designed a bowl-shaped three-dimensional model to be used as a projection surface. In terms of optimization, methods such as look-up table (LUT) and hardware acceleration significantly reduce computational time.
Multi-scene small object detection with modified YOLOv4
Authors: Ziming Cao , Han Yu , Lingjun Kong , Dapeng Zhang 
Published: April 2022

Abstract
Applications of small object detection exist in many different scenarios of our daily life, and this topic is also one of the most difficult issues in studying object detection and recognition. Therefore, improving small object detection accuracy is not only important in theory, but also significant in practice. However, current detection relevant algorithms are inefficient in this task; therefore in this study, a type of generalized improved algorithm based on YOLOv4 model is proposed. After the “ADD” and “Concat” layers of the conventional cross stage partial network (CSPNet), a type of mixed attention module (MA) is added to strengthen the spatial and channel feature information of the object; the dilated convolution module (DC) is then used to expand the receptive field information around the peripheries of target small objects. Several numerical experiments show that this modified model associated with its algorithms achieves higher mean average precision of the tests on the Pascal VOC and the VISDRONE data sets (mAP@0.5). Compared with YOLOv4, these performance assessment indices increase by 3.23% and 2.88% respectively. After refining the YOLOv4 network structure with the condition that the size of input images set as 416*416, the average accuracies of the model can reach 87.58% on Pascal VOC data set and 26.12% on VISDRONE data set. These results present the apparent better performance of this method than the original detection algorithm on recognizing small objects without affecting the real-time performance.