bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gender stereotypes about interests start early and cause gender disparities in computer science and engineering
Authors: Master Allison , Meltzoff Andrew N. , Cheryan Sapna 
Published: November 2021

Significance
Societal stereotypes that girls are less interested than boys in computer science and engineering are endorsed by children and adolescents in a large and socioeconomically diverse sample, across multiple racial/ethnic and gender intersections, and as early as age six (first grade). Gender-interest stereotypes may contribute to subsequent gender disparities in the pursuit of these societally important fields. Addressing interest stereotypes may help improve educational equity.
Exploring the signaling space of a GPCR using bivalent ligands with a rigid oligoproline backbone
Authors: Romantini Nina , Alam Shahidul , Dobitz Stefanie , Spillmann Martin , De Foresta Martina , Schibli Roger , Schertler Gebhard F. X. , Wennemers Helma , Deupi Xavier , Behe Martin , Berger Philipp 
Published: November 2021

SignificanceG protein–coupled receptors (GPCRs) are major players in cellular signal transmission. In this work, we have used rigid oligoproline backbones derivatized with two ligands at defined distances to induce GPCR dimer formation as a way to alter its signaling profile. We show that bivalent ligands at distances of 20 and 30 Å induce dimers of the GRPR receptor with different signaling responses. In addition, a nondimer–inducing bivalent ligand (with 10-Å distance between agonists) also induces different signaling patterns, most likely due to allosteric effects. These findings identify bivalent ligands with a stiff oligoproline backbone as tools to explore the natural signaling space of GPCRs.
Past insecticide exposure reduces bee reproduction and population growth rate
Authors: Stuligross Clara , Williams Neal M. 
Published: November 2021

Significance
Global insect declines are profoundly concerning, especially for groups like bees that provide important services to humanity. However, we do not know the extent to which recognized drivers of decline, like pesticides, may produce carryover effects that influence reproduction and population dynamics over time. We reveal that pesticide exposure, both directly to foraging bees and via carryover effects from past exposure, dramatically reduced bee reproduction, which reduced population growth. Carryover effects reduced bee reproduction by 20% beyond current impacts on foraging bees, exacerbating the negative impact on population growth rates. This indicates that bees may require multiple generations to recover from a single pesticide exposure; thus, carryover effects must be considered in risk assessment and conservation management.
Light-driven dynamic surface wrinkles for adaptive visible camouflage
Authors: Ma Tianjiao , Bai Jing , Li Tiantian , Chen Shuai , Ma Xiaodong , Yin Jie , Jiang Xuesong 
Published: November 2021

SignificanceCamouflage has broad applications in nature, engineering, and the military. This work demonstrated a feasible strategy for adaptive visible camouflage based on light-driven dynamic surface wrinkles. The multiwavelength light–driven dynamic surface wrinkles based on photothermal effect–induced thermal expansion of the substrate could tune the light scattering and the visibility of the film interference color. Consequently, the color captured by the observer could switch between the exposure state that is distinguished from the background and the camouflage state that is similar to the surroundings, demonstrating the adaptive camouflage. This system is simple to configure, easy to operate, versatile, and exhibits in situ dynamic characteristics without any external sensors and extra stimuli, which provided an alternative strategy for adaptive camouflage.
Warming winters in lakes: Later ice onset promotes consumer overwintering and shapes springtime planktonic food webs
Authors: Hébert Marie-Pier , Beisner Beatrix E. , Rautio Milla , Fussmann Gregor F. 
Published: November 2021

Significance
Freshwater ice is being lost at an accelerating rate with global warming. Yet the ecological implications of shortening ice-covered seasons remain largely unexplored due to a historical lack of freshwater research in winter. We provide an innovative experimental study that realistically reproduces warming effects on the timing of ice onset to address the consequences for lake food webs. We find that later ice-on sustains photosynthesis longer, permitting greater accumulation of high-quality fat reserves in primary consumers, and likely facilitating winter survival. Further, we show that a greater prevalence of overwintering consumers shapes springtime food webs via an increased top-down control of the spring algal bloom. Broadly, this study demonstrates that warmer winters can have cross-seasonal cascading effects on ecological processes.
Interactional gestures as soccer celebrations
Authors: Heliasz-Nowosielska Celina 
Published: November 2021

Abstract
The article presents a variety of gesture types used as celebrations during or after soccer matches and explains
the forms, meaning, reference and functions of the gestures as a semiotic phenomenon. The qualitative analysis of media images and
comments on celebratory performances shows that pre-planned, creative celebrations, including trademarks or signatures, which have
recently overshadowed spontaneous, conventionalized displays of affect, take the form of interactional gestures of different
types: performatives, regulators, pointing, icons, metaphors, pantomime, emblems or signs, as well as the form of compositions of
gestures, such as icons and pointing. During the match, gestures of all the above types serve to display affects and take on other
new functions. Also, even gestures like regulators, identified in literature as conversational ones, are used without the
accompanying speech. A disintegrated speech context for the interpretation of the meaning and reference of celebratory gestures is
provided in after-match media discourse.
Exploring the parameter space of modified supergravity for double inflation and primordial black hole formation
Authors: Ishikawa Ryotaro , Ketov Sergei V 
Published: November 2021

Abstract
We study the parameter space of the effective (with two scalars) models of cosmological inflation and primordial black hole (PBH) formation in the modified (R + R
2) supergravity. Our models describe double inflation, whose first stage is driven by Starobinsky’s scalaron coming from the R
2 gravity, and whose second stage is driven by another scalar belonging to the supergravity multiplet. The ultra-slow-roll regime between the two stages leads a large peak (enhancement) in the power spectrum of scalar perturbations, which results in efficient PBH formation. Both inflation and PBH formation are generic in our models, while those PBH can account for a significant part or the whole of dark matter. Some of the earlier proposed models in the same class are in tension (over 3σ) with the observed value of the scalar tilt n
s, so that we study more general models with more parameters, and investigate the dependence of the cosmological tilts (n
s, r) and the scalar power spectrum enhancement upon the parameters. The PBH masses and their density fraction (as part of dark matter) are also calculated. A good agreement (between 2σ and 3σ) with the observed value of n
s requires fine tuning of the parameters, and it is only realized in the so-called δ-models. Our models offer the (super)gravitational origin of inflation, PBH and dark matter together, and may be confirmed or falsified by future precision measurements of the cosmic microwave background radiation and PBH-induced gravitational waves.
Enhance your smartphone with a Bluetooth arduino nano board
Authors: Bouquet F , Creutzer G , Dorsel D , Vince J , Bobroff J 
Published: November 2021

Abstract
Using smartphones in experimental physics teaching offers many advantages in terms of engagement, pedagogy and flexibility. But it presents drawbacks such as possibly endangering the device and also facing the heterogeneity of available sensors on different smartphones. We present a low-cost alternative that preserves the advantages of smartphones: using a microcontroller equipped with a large variety of sensors that transmits data to a smartphone using a Bluetooth low-energy protocol. This device can be lent to students with little risk and used to perform a wide range of experiments. It opens the way to new types of physics teachings.
The role of resonance radiation in the propagation of a positive pre-breakdown ionization wave in long discharge tubes
Authors: Siasko A V , Golubovskii Yu B , Valin S V 
Published: November 2021

Abstract
The work is devoted to calculating the flux of resonance photons towards the boundary of a cylindrical discharge tube of a finite size during the propagation of a pre-breakdown ionization wave of positive polarity. A cylindrical discharge tube of finite dimensions with argon at the pressure of p = 1 Torr is considered. The propagation mechanisms of metastable and resonance atoms are compared. For the considered discharge conditions, the space-time distributions of metastable and resonance atoms are calculated. The manuscript presents a technique for calculating the flux of resonance photons onto the discharge tube wall with the account of the radiation trapping. It is shown that for the studied conditions the photon flux density towards the longitudinal boundary of the tube ahead of the ionization wave can reach 1013 cm−2 s−1. The obtained results allow us to describe the appearance of seed electrons ahead of the positive ionization wavefront during their propagation due to the electron photoemission from the discharge tube wall.
Impact of Joule heating and multiple slips on a Maxwell nanofluid flow past a slendering surface
Authors: Ahmad Shafiq , Khan Muhammad Naveed , Nadeem Sohail , Rehman Aysha , Ahmad Hijaz , Ali Rifaqat 
Published: November 2021

Abstract
This manuscript presents a study of three-dimensional magnetohydrodynamic Maxwell nanofluid flow across a slendering stretched surface with Joule heating. The impact of binary chemical reactions, heat generation, thermal radiation, and thermophoretic effect is also taken into consideration. The multiple slip boundary conditions are utilized at the boundary of the surface. The appropriate similarity variable is used to transfer the flow modeled equations into ODEs, which are numerically solved by the utilization of the MATLAB bvp4c algorithm. The involved parameter’s impact on the concentration, velocity, and temperature distribution are scrutinized with graphs. The transport rates (mass, heat) are also investigated using the same variables, with the results reported in tabulated form. It is seen that the fluid relaxation, magnetic, and wall thickness characteristics diminish the velocities of fluid. Further, the velocity, concentration, and temperature slip parameters reduce the velocities of fluid, temperature, and concentration distribution. The results are compared to existing studies and shown to be in dependable agreement.
Comparison of JET-C DD neutron rates independently predicted by the ASCOT and TRANSP Monte Carlo heating codes
Authors: Weisen H. , Sirén P. , Varje J. , JET Contributors  
Published: November 2021

Abstract
Simulations of the DD neutron rates predicted by the ASCOT and TRANSP Monte Carlo heating codes for a diverse set of JET-C (JET with carbon plasma facing components) plasmas are compared. A previous study (Weisen et al 2017 Nucl. Fusion
57 076029) of this data set using TRANSP found that the predicted neutron rates systematically exceeded the measured ones by factors ranging between 1 and 2. No single explanation for the discrepancies was found at the time despite a large number of candidates, including anomalous fast ion loss mechanisms, having been examined. The results shed doubt on our ability to correctly predict neutron rates also in the deuterium–tritium plasmas expected in the JET D–T campaign (DTE2). For the study presented here the calculations are independently repeated using ASCOT with different equilibria and independent mapping of the profiles of temperature and density to the computational grid. Significant differences are observed between the results from the investigations with smaller systematic differences between neutron rates measurements and predictions for the ones using ASCOT. These are traced back not to intrinsic differences between the ASCOT and TRANSP codes, but to the differences in profiles and equilibria used. These results suggest that the discrepancies reported in reference (Weisen et al 2017 Nucl. Fusion
57 076029) do not require invoking any unidentified plasma processes responsible for the discrepancies and highlight the sensitivity of such calculations to the plasma equilibrium and the necessity of a careful mapping of the profiles of the ion and electron densities and temperatures.
Environmental testing for reliable battery management system in electric vehicle
Authors: Raharjo J , Wikarta A , Sidharta I , Yuniarto M N , Firdaus M I , Zulhaimi M F B 
Published: November 2021

Abstract
The Battery management system (BMS) is a main component in the battery pack system for electric vehicles (EV). The function of BMS is to monitor battery cells such as; cell voltage, cell temperature, and current in the battery pack. Moreover BMS also able to balance the voltage of the cells so the difference in voltage of the cells can be minimized. By having many of these functions, BMS can identify battery health based on these parameters. With such an important function, in this paper, BMS was tested to determine its reliability. The standard testing for BMS reliability is the Environment test. In the environment test, some things that are conducted in the environment test are initial temperature cycling. From the environment, the test can be generated information to assess the quality of the BMS following its function. Furthermore, it can reduce the cost to inspect every battery cells in the packs. With the environment test as a basis for BMS reliability tester, hopefully, good quality is obtained. Future development in BMS reliability testing can also be conducted to improve reliability.
Research on 3D Reconstruction Technology of Power Line Based on Image Semantic Segmentation
Authors: Li Xionggang , Zhang Feng , Li Guoqiang , Xiang Dongwei , Yang Chengcheng 
Published: November 2021

Abstract
Because it was difficult to distinguish the characteristics of the power lines by the traditional methods of extracting the power lines, which led to the current situation of incomplete reconstruction and a large number of noise in the process of rebuilding the power lines only by the inclined photographing. In this paper, the power line information in the image is segmented pixel by pixel by introducing in-depth learning semantics segmenting neural network. The three-dimensional coordinates of the power line are calculated by the principle of multi-view three-dimensional reconstruction. Finally, the power line is fitted by the catenary equation to complete the incomplete power line reconstruction. The results show that the fitted power line model has high accuracy and meets the requirements of power related applications. Based on the traditional three-dimensional reconstruction, a new idea for power line reconstruction is proposed.
Research on Deterministic Measurement Matrix of Power Line Carrier Compressed Sensing
Authors: Jin Jiliang , Xing Liyun , Yang Miao , Shen Jianqiang , Dong Yuqi 
Published: November 2021

Abstract
To verify the advantages of deterministic matrix applied to power line carrier communication (PLCC) based on compressed sensing (CS). This article analyzed the research status of commonly used deterministic measurement matrices, and made simulation comparison. It is found that different types of deterministic measurement matrices generated based on chaotic mapping had higher reconstruction accuracy and higher reconstruction efficiency than Gaussian random matrix. Then, according to simulation results and the characteristics of PLCC signal, the Chebyshev sparse circulant (CSC) measurement matrix was designed by combining eighth-order Chebyshev chaotic and the idea of sparse and circulant. Actual circuit measurement shows that when compression rate was 40% and 60%, the reconstruction loss of CSC is 0.72dB and 0.49dB higher than that of Chebyshev chaotic measurement matrix and Chebyshev circulate measurement matrix, respectively. Obviously, the CSC measurement matrix designed in this paper can effectively improve the reconstruction accuracy.
Research on Optimization of Power System Regulation Capacity Based on New Energy Installed Capacity
Authors: Zhu Yibing , Zhang Jing , Hu Yuou , Cui Fubo , Chu Wenjia 
Published: November 2021

Abstract
As the proportion of new energy continues to increase, the safty and stability of the power system faces severe challenges. Many a flexible resource should be established to ensure that the regulating ability of the power system is enough, so as to cope with the load fluctuations caused by the gird-connected new energy. This article analyses the technical characteristics of various flexible resources, and which aspect that each flexible resource can contribute to the regulating ability of the power system. On this basis, this paper proposes a quantitative analysis method of the improvement of power system regulating ability based on the consumption model of new energy, using the addition of new energy grid-connected capacity as a quantitative indicator to evaluate the improvement of system regulating ability contributed by each type of flexible resource. Combined with calculation examples, a quantitative analysis of usual flexibility resources is carried out.
Simulation and Optimization of Body Structure of Electric Vehicles with Offset Collision
Authors: Hu Yuanhe , Yang Kun , Chen Hao , Wang Jiangbo 
Published: November 2021

Abstract
In recent years, as the rapid growth of the number of electric vehicles, people have more and more requirements on the safety performance of vehicles. However, compared with fuel vehicles, the structure of electric vehicles has its own particularity which makes the safety design of body structure more difficult. Thus, improving the passive safety of electric vehicles and protecting the passengers from injury in the collision to the greatest extent have become important issues for the automotive industry. This paper simulates the frontal offset impact simulation analysis of a certain type of SUV, and analyzes the safety performance of the vehicle from the perspective of member protection. The front side member structure and impact energy absorption which affect the passive safety of the whole vehicle are optimized and improved. The finite element model of the whole vehicle is rebuilt, and the frontal offset impact simulation test is carried out to verify the effectiveness of the optimization scheme.
Acoustic Simulation of the Electric Vehicle Motor
Authors: Li Huibin , Xu Peiyun , Cao Cheng , Hu Dongmei , Yan Xiaojun , Song Zhihuan 
Published: November 2021

Abstract
People pay more and more attention to NVH (N-noise, V-vibration, and H-harshness) characteristics of electric vehicles and motors. The vibration and noise of the electric vehicle motor is a complex multi physical field problem, related to electromagnetic, mechanical, structural and sound fields. In this paper, firstly, the Maxwell electromagnetic field analysis software is used to build the electromagnetic simulation model of PMSM(Permanent magnet synchronous motor) motor, and then the electromagnetic excitation is calculated. Then, the magnetic solid coupling analysis is carried out by using the Maxwell module and harmonic response module of ANSYS Workbench, and the harmonic response of the motor structure under the action of electromagnetic excitation is simulated. After the simulation of magnetic solid coupling is completed, the BEM(Boundary element method) simulation of the permanent magnet synchronous motor is carried out with the acoustic simulation software LMS Virtual Lab. The acoustic simulation of the permanent magnet synchronous motor shows that the sound pressure level at three measurement points have obvious peak value at 3700Hz, 4500Hz, 5400Hz and 6400Hz respectively. The acoustic simulation results lay the foundation for the vibration and noise reduction of the motor.
Constrained Spacecraft Attitude Optimal Control via Successive Convex Optimization
Authors: Wang Jiayao , Shang Haibin 
Published: November 2021

Abstract
Rapid attitude path planning is the key technique in autonomous spacecraft operation missions. An efficient method is proposed for energy-optimal spacecraft attitude control in presence of constraints. Firstly, Gauss pseudospectral method is utilized to discretize and transcribe the primal continuous problem to a nonlinear programming problem. Then a set of convexification techniques are used to convexity the nonlinear programming problem to a series of second-order cone programming problems, which can be solved iteratively by the interior-point method. A solution to the nonlinear programming problem is obtained as the iteration converges. Numerical results show the method could obtain a valid energy-optimal attitude control plan more rapidly than traditional methods.
Automated Classification of High-resolution Rock Image Based on Residual Neural Network
Authors: Cai Weibo , Deng Juncan , Lu Qirong , Lu Kengdong , Luo Kaiqing 
Published: November 2021

Abstract
The identification and classification of high-resolution rock images are significant for oil and gas exploration. In recent years, deep learning has been applied in various fields and achieved satisfactory results. This paper presents a rock classification method based on deep learning. Firstly, the high-resolution rock images are randomly divided into several small images as a training set. According to the characteristics of the datasets, the ResNet (Residual Neural Network) is optimized and trained. The local images obtained by random segmentation are predicted by using the model obtained by training. Finally, all probability values corresponding to each category of the local image are combined for statistics and voting. The maximum probability value and the corresponding category are taken as the final classification result of the classified image. Experimental results show that the classification accuracy of this method is 99.6%, which proves the algorithm’s effectiveness in high-resolution rock images classification.
A Deep Learning Based Automatic Interference Avoidance Resource Allocation Scheme for SCMA Systems
Authors: Yang Peng , Wang Wei , Mao Weimin , Zhang Guoyi , Cai Jie , Hong Danke , Zhu Hailong , Zhang Jianhui , Chen Shengli 
Published: November 2021

Abstract
Sparse code multiple access (SCMA) is able to provide high spectral efficiency and massive connectivity, hence it is considered as a promising scheme for the fifth generation (5G) systems. This paper proposed a radio resource allocation scheme based on deep learning for SCMA systems, with the aim to automatically avoid the inter-cell interference. A long short term memory (LSTM) network is adopted to learn the past interference characteristics and predict the interference power in the current subframe. Radio resource blocks with less predicted interference power are then selected for users to transmit signals. Simulation results show that the proposed scheme outperforms the moving average prediction method and has significant gains over the random radio resource block allocation in terms of achievable bit error rate in SCMA systems.