bluuebunny/crossref_metadata_2025_split huggingface dataset:
A plasma loss to sidewall model for 1D PIC/MCC simulation for plasma transport estimation
Authors: Yang Jinghan , Li Dong , Chen Peng , Li Zengshan , Jiang Wei , Chen Dezhi 
Published: September 2022

Abstract
A plasma loss to sidewall model is used for one-dimensional (1D) particle-in-cell (PIC) with Monte Carlo collision (MCC) simulation to calculate plasma transport through a transverse magnetic field in a negative ion source chamber. The presented 1D model includes plasma radial loss treatment when calculating the plasma transport in the axial direction. It does not cost computation effort as much as a 2D or 3D model and can be used to estimate the plasma transport process quickly. The conventional 1D kinetic model calculates particle motion only in the ‘x’-direction. The sidewall loss in the ‘y’ ‘z’ direction is not included, leading to unusual plasma distribution. Especially when applying a transverse magnetic field, the motion and loss of electrons along the magnetic field line to the sidewall are ignored. Thus electrons are completely constrained by the magnetic field, resulting in abnormal plasma density accumulation. The sidewall loss estimation method uses Bohm velocity calculated from plasma parameters as radial loss velocity to obtain the plasma flux to the sidewall. And the sidewall loss rate can be obtained from the flux combined with chamber geometry. This method is integrated into a self-developed 1D PIC–MCC program to examine its effect. Several verification cases are performed separately for the PIC, MCC, and the sidewall loss treatment module, and the results exhibit good reliability. Simulations are then carried out to study plasma transport across the magnetic field under similar conditions to actual experiments. Simulation results agree with the experiment, which indicates that the 1D sidewall loss model is useful when dealing with plasma transport in the source chamber.
Power characteristics of vibration-based piezoelectric energy harvesters: the effect of piezoelectric material nonlinearity
Authors: Lan Chunbo , Qian Feng , Liao Yabin , Zuo Lei 
Published: September 2022

Abstract
Piezoelectric energy harvesting has received tremendous interests in the past two decades as a viable solution to self-powered electronics and devices. Recently, significant emphasis has been given to nonlinear energy harvesters driven by the desire for broadband, high-performance energy harvesting. Numerous efforts have been devoted to the understanding and modeling of the electromechanical coupling and the effect of nonlinearities introduced by mechanical and electrical aspects of the system. However, very few works in the literature considered the effect of piezoelectric material nonlinearity on the system power performance. Nevertheless, it has been found that piezoelectric nonlinearity is significant even at low to moderate excitation level. This paper is motivated to study the power behavior of piezoelectric energy harvesters with piezoelectric nonlinearity, most importantly, the power limit and electromechanical coupling. For this purpose, an approximate model is developed from the nonlinear model in the literature to derive the closed-form expressions of important power characteristics. Analytical analysis shows that the effect of piezoelectric material nonlinearity results in a nonlinear damping term and a nonlinear stiffness term in the approximate model. The approximate solutions of optimal load resistance, maximum power, power limit, and critical electromechanical coupling are obtained and validated by numerical simulations first. The induced nonlinear damping reduces the power limit of the system compared to its linear counterpart. Interestingly, a harvester that exhibits strong electromechanical coupling under small excitation could become weakly coupled under large excitation. The analytical analysis and numerical results are validated by experiments.
Superconducting properties of pseudobinary telluride Chevrel phase Mo4Re2Te8
Authors: Kataria A , Agarwal T , Sharma S , Ali A , Singh R S , Singh R P 
Published: September 2022

Abstract
Unconventional superconductivity in the Chevrel phase (CP) offers a wide structural aspect to understand the superconducting ground state. A detailed investigation of the superconducting properties of Re-based pseudobinary telluride CP Mo4Re2Te8 is reported. It crystallizes in a trigonal structure, with the space group

R

3
ˉ

H

having a superconducting transition temperature at

T
C

=
3.26
(
3
)

K with a fully gapped superconducting state in the moderate electron–phonon coupling limit.
Mottness induced superfluid phase fluctuation with increased density
Authors: Lang Zi-Jian , Yang Fan , Ku Wei 
Published: September 2022

Abstract
Recent observation of diminishing superfluid phase stiffness upon increasing carrier density in cuprate high-temperature superconductors is unexpected from the quantum density-phase conjugation of superfluidity. Here, through analytic estimation and verified via variational Monte Carlo calculation of an emergent Bose liquid, we point out that Mottness of the underlying carriers can cause a stronger phase fluctuation of the superfluid with increasing carrier density. This effect turns the expected density-increased phase stiffness into a dome shape, in good agreement with the recent observation. Specifically, the effective mass divergence due to ‘jamming’ of the low-energy bosons reproduces the observed nonlinear relation between phase stiffness and transition temperature. Our results suggest a new paradigm, in which unconventional superconductivity in some strongly correlated materials is described by physics of bosonic superfluidity, as opposed to pairing-strength limited Cooper pairing.
DFT calculation of structures and electronic characteristic of VOPO4 polymorphs
Authors: Zheng Lei , Yang Xiaojun , Li Jian , Yang Ruhui , Qu Hengze , Guo Xiangyu , Huang Shiping , Zhang Shengli 
Published: September 2022

Abstract
Vanadyl Phosphate (VOPO4) is an attractive candidate for catalytic materials. Previous works by S. C. Lim, R. Gautier, N. Dupre, et al,have reported that VOPO4 co-exists in seven polymorphs including α
Ι-, α
Ι′-, α
II-, β-, γ-, δ-, ε-, and ω-VOPO4. However, there is no systematic investigation on these seven polymorphs. Here, based on density functional theory (DFT) calculations, all these structures, stability and the differences of band structures are compared in detail. The results show that α
Ι-, α
Ι′-, α
II-, β-, γ-, and ε-VOPO4 are indirect bandgap semiconductors, while δ-VOPO4 exhibits a direct band structure and ω-VOPO4 belongs to insulators. Our work can shed light on the perspective of the application of VOPO4.
Constraints on self-dual black hole in loop quantum gravity with S0-2 star in the galactic center
Authors: Yan Jian-Ming , Wu Qiang , Liu Cheng , Zhu Tao , Wang Anzhong 
Published: September 2022

Abstract
One of remarkable features of loop quantum gravity (LQG) is that it can provide resolutions to both the black hole and big bang singularities. In the mini-superspace approach based on the polymerization procedure in LQG, a quantum corrected black hole metric is constructed. This metric is also known as self-dual spacetime since the form of the metric is invariant under the exchange r ⟶ a
0/r with a
0 being proportional to the minimum area in LQG and r is the standard radial coordinate at asymptotic infinity. It modifies the Schwarzschild spacetime by the polymeric function P, purely due to the geometric quantum effects from LQG. Here P is related to the polymeric parameter δ which is introduced to define the paths one integrates the connection along to define the holonomies in the quantum corrected Hamiltonian constraint in the polymerization procedure in LQG. In this paper, we consider its effects on the orbital signatures of S0-2 star orbiting Sgr A* in the central region of our Milky Way, and compare it with the publicly available astrometric and spectroscopic data, including the astrometric positions, the radial velocities, and the orbital precession for the S0-2 star. We perform Monte Carlo Markov Chain (MCMC) simulations to probe the possible LQG effects on the orbit of S0-2 star. No significant evidence of the self-dual spacetime arisIng from LQG is found. We thus place an upper bounds at 95% confidence level on the polymeric function P < 0.043 and P < 0.056, for Gaussian and uniform priors on orbital parameters, respectively.
Driver awareness collision/proximity detection system for heavy vehicles based on deep neural network
Authors: Anwar Qaiser , Hanif Muhammad , Shimotoku Daisuke , Kobayashi Hill H. 
Published: September 2022

Abstract
Heavy vehicles are essentially used to perform several critical tasks in construction industry. These heavy vehicles are different in shape and structure according to their capabilities and needs on the construction sites. Bigger size and different design of these vehicles result in extended blind spot compare to the normal vehicles, thus risking the equipment and workers operating around them. Each year, a large number of incidents are reported involving human injuries or loss of life due to improper handling of blind spots in heavy vehicles. In this paper we developed a deep learning based collision detection and driver assistance methodology by removing the blind spots in haul truck. In the proposed methodology, vision sensor data is used for automatic detection and classification of objects, employing the YOLO-v5 network architecture. For distance measurement of the objects we used stereo imaging camera Intel RealSense D455. The proposed algorithm detects and classify the object around the vehicle and provide the captioning to describe the nature of object to the driver. In addition, the algorithm also measures the distance of objects from the vehicle. The experimental results validate the performance of our proposed methodology in real time.
Mobile robot path planning based on fusion of improved A* algorithm and adaptive DWA algorithm
Authors: Zhenyang Xu , Wei Yuan 
Published: September 2022

Abstract
For mobile robot autonomous navigation, path planning algorithm matters. For the reason that traditional A* algorithm is unable to achieve the global path planning perfectly and avoid unknown obstacles at the same time, the mobile robot algorithm combining improved A* with adaptive DWA was proposed for path planning. Firstly, safe distance judgment is added in A* algorithm to avoid the problem that the path crosses the vertex of obstacle diagonally. Secondly, the dynamic tangential method is used to smooth the path of A* algorithm, which is more consistent with the actual motion curve of mobile robot. Then, the path key points explored by improved A* algorithm are extracted as intermediate target points of the velocity adaptive DWA algorithm. Unknown obstacles avoidance based on the optimal global path planning is realized. Finally, the proposed fusion algorithm’s feasibility is verified through mobile robot ROS simulation.
Integrated planning of UAV 3D trajectory based on ant colony algorithm
Authors: Qihan Deng 
Published: September 2022

Abstract
To address the problem of UAV trajectory planning optimality, a dynamic multi-objective optimal path model is established based on satisfying the basic conditions of UAV flight constraints, taking into account the time window restricted area and radio interference threat, etc. comprehensively. Based on the characteristics of the complex environment, an ant colony algorithm with reduced adaptive step size is constructed based on the theory of ant colony algorithm to quickly plan the best safe UAV trajectory in the complex dynamic environment. Simulation results show that the model can meet the complex airspace conditions of UAV missions, while the algorithm can find shorter trajectories and shorten the search time.
Research on the key technology of course ontology construction
Authors: Chen Yue , Chen Zhiyun 
Published: September 2022

Abstract
Education Information and smart education is the future trend of education. Education ontology is an important tool and means to realize education information and smart education. In the traditional method, the ontology is basically constructed manually, which will consume huge labor and time costs, and the automatically constructed ontology is often of low quality. The previous semi-automatic construction method is also aimed at the ontology of the subject area. Due to the wide range of subject areas and many concepts, the direct construction requires the cooperation of many people and takes several months to complete. Therefore, starting from the construction of curriculum ontology, this paper puts forward an efficient, accurate and low-cost method of constructing course ontology. This method takes “China University MOOC”, “XuetangX” and “cnblog” as data sources, making full use of structured data, semi-structured data and unstructured data to integrate technologies such as web crawler technology, text matching, active learning and deep learning. Applying these methods to the course “Data Structure”, the experimental results show that the scale coefficient of the number of concepts in the course ontology constructed by this method in the standard set is as high as 0.92, and the attribute coverage reaches 1.21, which proves the effectiveness and accuracy of the method.
iDREAM: industrial Detector of REactor Antineutrinos for Monitoring at Kalinin nuclear power plant
Authors: Abramov A. , Chepurnov A. , Etenko A. , Gromov M. , Konstantinov A. , Kuznetsov D. , Litvinovich E. , Lukyanchenko G. , Machulin I. , Murchenko A. , Nemeryuk A. , Nugmanov R. , Obinyakov B. , Oralbaev A. , Rastimeshin A. , Skorokhvatov M. , Sukhotin S. 
Published: September 2022

Abstract
The paper is devoted to the description of the iDREAM
detector and its systems. iDREAM is a prototype detector designed to
demonstrate the feasibility of antineutrino detectors for remote
reactor monitoring and safeguard purposes. Antineutrinos are
detected with a 1 ton liquid scintillator via inverse beta decay on
protons. In order to suppress cosmic muons, gamma and neutron
background, the detector is housed in a dedicated shielding. The
detector is installed at the Kalinin nuclear power plant (Russia),
20 m from the 3 GWth reactor core.
Commutativity and the emergence of classical objectivity
Authors: Ryan Eoghan , Carolan Eoin , Campbell Steve , Paternostro Mauro 
Published: September 2022

Abstract
We examine how the ability of a system to redundantly proliferate relevant information about its pointer states is affected when it is coupled to multiple baths. To this end, we consider a system in contact with two baths: one—termed the accessible environment —which, on its own, induces a pure dephasing mechanism on the state of the system and satisfies the conditions for classical objectivity to be established. The second environment, which we dub as inaccessible, affects the system in two physically relevant ways. Firstly, we consider an interaction that commutes with the Hamiltonian describing the interaction between system and accessible bath. It thus also gives rise to dephasing of the system, albeit on different time scales. Secondly, we consider a thermalising interaction, which does not commute with the system-accessible environment Hamiltonian. While the former still allows the system to redundantly encode its state into the accessible environment, the latter degrades the correlations, eventually destroying them in the long-time limit, and thus leads to a loss of the conditions necessary for classical objectivity to be established. This sheds light on the role that commutativity between the various system-bath interaction terms plays when establishing the conditions for classical objectivity to be supported.
Critical factors for photoelectrochemical and photocatalytic H2 evolution from gray anatase (001) nanosheets
Authors: Qin Shanshan , Denisov Nikita , Zhou Xin , Zdražil Lukáš , Fehn Dominik , Hwang Imgon , Bruns Mark , Kim Hyesung , Meyer Karsten , Schmuki Patrik 
Published: September 2022

Abstract
In recent years, the defect engineering of titania via reduction treatments has shown a high potential for enabling efficient and co-catalyst-free photocatalytic H2 generation from methanol/water solutions. However, defect engineering simultaneously alters several properties of TiO2. Here, we use pristine (white) and hydrogenated (gray) anatase nanosheets with dominant (001) facets. By comparing electrical conductivity, photocurrent spectra, transient photocurrent response, and photocatalytic H2 evolution, we show that the increased conductivity or broad visible light absorption of gray titania is not responsible for its increased activity. Instead, the true bottleneck is the hole transfer rate that is significantly accelerated while using gray instead of white modification. Moreover, the hole transfer reaction causes the accumulation of the reaction products in pure water, hindering the photocatalytic H2 evolution over time. These combined factors explain the superior performance of gray titania over white titania in photoelectrochemical or photocatalytic water splitting.
Modified HSE06 functional applied to anatase TiO2: influence of exchange fraction on the quasiparticle electronic structure and optical response
Authors: S B Sruthil Lal , D Murali , Posselt Matthias , Sasikala Devi Assa Aravindh , Sharan Alok 
Published: September 2022

Abstract
The influence of non-interacting Kohn–Sham Hamiltonian on the non-self consistent GW(G
0
W
0) quasiparticle gap and Bethe–Salpeter-equation (BSE) optical spectra of anatase TiO2 is systematically evaluated. G
0
W
0 and BSE calculations are carried out starting with HSE06 (Heyd–Scuseria–Ernzerhof) type functionals containing 20%, 25% and 30% exact Hartree–Fock exchange. The results are also compared against G
0
W
0 + BSE calculations starting from semi-local (PBE) functionals. Our results indicate that the G
0
W
0 and BSE calculations of anatase TiO2 depend critically on the mean-field starting point, wherein its dependence is mainly introduced through the dielectric screening evaluated at the intermediate G
0
W
0. We find that the band dispersion, density of states, and consequently the oscillator strengths of optical excitation and spatial localization of excitons are insensitive to the starting points while the quasiparticle gap, optical gap and exciton binding energies are strongly affected. G
0
W
0 quasiparticle gap of anatase TiO2 computed over hybrid functional starting points is typically overestimated compared to measured values. However, by varying the amount of exact exchange, the dielectric screening can be tuned, and thus the quasiparticle gap. Exciton binding energy is shown to increase in proportion to the increase of the amount of exact exchange. A simple extrapolation of the calculated data leads to the exact match with the recently measured value with 13% of the exact exchange. Systematic analysis of G
0
W
0 + BSE calculation starting from screened hybrid functionals provided in this study forms a reference for all such future calculations of pristine anatase TiO2 and its derivatives.
Nanoparticles of metal/metal oxide embedded fabrics to impart antibacterial activity to counteract hospital acquired infections
Authors: Antinate Shilpa S , Subbulakshmi M S , Hikku G S 
Published: September 2022

Abstract
The spread of infectious diseases by the bacterial cells through hospital-acquired infections (HAIs) has become a major threat throughout the world. Fabrics used in the healthcare sector such as bedsheets, healthcare uniforms, and patient gowns can act as growing substrates for infectious bacterial cells and have become one of the causes of the spread of HAIs. The development of MDR by the bacterial cells further makes the situation worse. However, the metal ion toxicity and generation of reactive oxygen species by the metal/metal oxide-based nanoparticles (NPs) have the ability to counteract the proliferation of MDR bacterial strains. In this context, several NPs have been synthesized and functionalized over fabric to impart antibacterial activity. This process could hinder bacterial growth and biofilm formation over fabrics and thus, can prevent the spread of HAIs through contaminated fabrics. Therefore, the present review focuses on the types of NPs that are utilized to develop antibacterial fabrics.
Subaging in underparametrized deep neural networks
Authors: Herrera Segura Carolina , Montoya Edison , Tapias Diego 
Published: September 2022

Abstract
We consider a simple classification problem to show that the dynamics of finite–width Deep Neural Networks in the underparametrized regime gives rise to effects similar to those associated with glassy systems, namely a slow evolution of the loss function and aging. Remarkably, the aging is sublinear in the waiting time (subaging) and the power–law exponent characterizing it is robust to different architectures under the constraint of a constant total number of parameters. Our results are maintained in the more complex scenario of the MNIST database. We find that for this database there is a unique exponent ruling the subaging behavior in the whole phase.
Keystone structures maintain forest function for Canada lynx after large-scale spruce beetle outbreak
Authors: Squires John R , Ivan Jacob S , Paolini Kelsey E , Olson Lucretia E , Jones Gavin M , Holbrook Joseph D 
Published: September 2022

Abstract
Central to species conservation in an era of increased disturbance from climate change is understanding the primary mechanisms that facilitate how forest-dependent species respond to changes in forest structure and composition. Here, we leveraged a natural experiment to investigate how changed forest structure and function pre-spruce-beetle (Dendroctonus rufipennis) and post-beetle disturbance influenced the regional distribution of Canada lynx (Lynx canadensis) at their southern range periphery. We compared the distribution of Canada lynx that were reintroduced into Colorado, USA from 1999–2006 to the current (2015–2017) distribution following a spatial large-scale spruce beetle outbreak from 2007 to 2016. Canada lynx did not substantially alter their distribution following the wide-spread alteration of forest structure and composition following the insect outbreak. We used the Bhattacharyya’s affinity metric to document that core (50% isopleth) and overall population ranges (95% isopleth) overlapped significantly at 50% and 77% respectively. In addition, areas of low and high relative use remained similar after the bark beetle outbreak and mapped onto one another in nearly a 1:1 fashion (Spearman rank correlation = 0.92, p < 0.01). The low impact of forest change on distribution was due to the keystone habitat elements (high horizontal forest cover, snowshoe hares) that remained functional. Thus, our results highlight that conservation scientists should increase their focus to understand the underlying mechanisms that impact wildlife distributions as climate-related disturbances becomes ever more amplified.
Photochemical reactions and the self-depuration of sunlit freshwaters
Authors: Vione Davide 
Published: September 2022

Abstract
Reactions induced by sunlight (direct photolysis and indirect photochemistry) are important ecosystem services that aid freshwater bodies in removing contaminants, although they may also exacerbate pollution in some cases. Without photoinduced reactions, pollution problems would be considerably worse overall. The photochemical reaction rates depend on seasonality, depth, water chemistry (which also significantly affects the reaction pathways), and pollutant photoreactivity. Photochemical reactions are also deeply impacted by less studied factors, including hydrology, water dynamics, and precipitation regimes, which are key to understanding the main impacts of climate change on surface-water photochemistry. Climate change is expected in many cases to both exacerbate freshwater pollution, and enhance photochemical decontamination. Therefore, photochemical knowledge will be essential to understand the future evolution of freshwater environments.