bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of chamber pressure and Si-doping on the surface morphology and electrical properties of homoepitaxial (100) β-Ga2O3thin films grown by MOVPE
Authors: Bin Anooz S , Grüneberg R , Chou T-S , Fiedler A , Irmscher K , Wouters C , Schewski R , Albrecht M , Galazka Z , Miller W , Schwarzkopf J , Popp A 
Published: September 2020

AbstractThe influence of chamber pressure and Si-doping on the growth rate, surface morphology and Hall mobility was investigated forβ-Ga2O3thin films homoepitaxially grown by metalorganic vapor phase epitaxy on Mg-dopedβ-Ga2O3(100) substrates with 4° miscut. Transitions from step-bunching to step-flow to 2D island growth modes were achieved by varying the chamber pressure from 10 mbar to 40 mbar and/or by varying the O2/Ga ratio. High-qualityβ-Ga2O3homoepitaxial thin films with a high electron mobility of 153 cm2Vs−1have been obtained at a chamber pressure of 25 mbar and a growth rate of 3.6 nm min−1. The Si-doped films show electron concentrations in the range of 1 × 1017to 2 × 1019cm−3. When increasing the chamber pressure to 40 mbar step-flow growth mode and high charge carrier mobility can only be preserved by adjusting the O2/Ga ratio and increasing the Ar push gas flow. Secondary ion mass spectrometry and Hall measurements for Si and electron concentration, respectively, revealed Si compensation at higher tetraethyl orthosilicate flux.
Nonadiabatic quasiparticle description of rotation-particle coupling in triaxial odd–odd nuclei
Authors: Siwach Pooja , Arumugam P , Modi S , Ferreira L S , Maglione E 
Published: September 2020

Abstract
A large wealth of data and a variety of models led to significant progress in understanding the spectra of deformed nuclei. However, a robust theoretical approach, which is less reliant on adjustable parameters is still elusive. Due to the scarcity of data, this drawback gets more pronounced while studying the exotic nuclei. With the motive to overcome this difficulty, we have developed the nonadiabatic quasiparticle approach for the description of rotational states in triaxial deformed odd–odd nuclei. The rotation-particle coupling is carried out utilizing an appropriate basis transformation such that the matrix elements of the odd–odd system can be written in terms of the rotor energies. This provides the advantage of studying the role of core more efficiently as compared to the conventional particle rotor model. The residual interaction between the valence proton and neutron is incorporated in two reliable ways, namely, the constant potential form and the zero-range interaction.
An equation of state for expanded metals
Authors: Schirmacher W , Pilgrim W-C , Hensel F 
Published: September 2020

Abstract
We present a model equation of states for expanded metals, which contains a pressure term due to a screened-Coulomb potential with a screening parameter reflecting the Mott–Anderson metal-to-nonmetal transition. As anticipated almost 80 years ago by Zel’dovich and Landau, this term gives rise to a second coexistence line in the phase diagram, indicating a phase separation between a metallic and a nonmetallic liquid.
A new dose quantity for evaluation and optimisation of MV photon dose distributions when using advanced algorithms: proof of concept and potential applications
Authors: Jurado-Bruggeman Diego , Muñoz-Montplet Carles , Vilanova Joan C 
Published: September 2020

Abstract
Advanced algorithms used in MV photon radiotherapy model radiation transport in any media. They represent a step forward but introduce new uncertainties and questions, including whether to report the doses to water (Dw,m) or medium (Dm,m) voxels, and the impact of fluence changes introduced by surrounding media. These aspects can compromise consistency between both reporting modes and with previous algorithms in which clinical experience is based. This study introduces a new dose quantity, the dose-to-reference-like medium, to overcome the aforementioned shortcomings. It is linked to a reference medium, water in this study (Dw,m*), and defined as the absorbed dose in a voxel of this reference medium surrounded by a reference-like medium with the same radiation transport characteristics as the original one. We propose to derive Dw,m* distributions by post-processing Dw,m or Dm,m applying a correction factor (CF) to each voxel which depends on its composition. We present and justify a simple and straightforward method to obtain CFs that only involves two phantoms with the same density: one with the considered composition and the other with that of the reference medium. A proof of concept was performed in a clinical environment for Acuros XB (AXB) advanced algorithm and 6 MV photon beams. The CFs were derived for the tissues characterised in Acuros. Dw,m* was compared to Dw,m, Dm,m, and Dw,w from AAA analytical algorithm for some virtual and clinical cases. All the previous quantities presented limitations that can be solved by Dw,m*. This new quantity allows the applicability of evaluation parameters, traceability to clinical experience, and isolation of heterogeneity effects to identify optimum plans, offering useful characteristics for plan evaluation and optimisation in clinical practice. Additionally, it also has potential applications in automated treatment planning and multi-centre activities such as clinical trials, audits, benchmarking, and shared models for automation.
RegQCNET: Deep quality control for image-to-template brain MRI affine registration
Authors: Denis de Senneville Baudouin , Manjón José V , Coupé Pierrick 
Published: September 2020

Abstract
Affine registration of one or several brain image(s) onto a common reference space is a necessary prerequisite for many image processing tasks, such as brain segmentation or functional analysis. Manual assessment of registration quality is a tedious and time-consuming task, especially in studies comprising a large amount of data. Automated and reliable quality control (QC) becomes mandatory. Moreover, the computation time of the QC must be also compatible with the processing of massive datasets. Therefore, automated deep neural network approaches have emerged as a method of choice to automatically assess registration quality.
In the current study, a compact 3D convolutional neural network, referred to as RegQCNET, is introduced to quantitatively predict the amplitude of an affine registration mismatch between a registered image and a reference template. This quantitative estimation of registration error is expressed using the metric unit system. Therefore, a meaningful task-specific threshold can be manually or automatically defined in order to distinguish between usable and non-usable images.
The robustness of the proposed RegQCNET is first analyzed on lifespan brain images undergoing various simulated spatial transformations and intensity variations between training and testing. Secondly, the potential of RegQCNET to classify images as usable or non-usable is evaluated using both manual and automatic thresholds. During our experiments, automatic thresholds are estimated using several computer-assisted classification models (logistic regression, support vector machine, Naive Bayes and random forest) through cross-validation. To this end we use an expert’s visual QC estimated on a lifespan cohort of 3953 brains. Finally, the RegQCNET accuracy is compared to usual image features such as image correlation coefficient and mutual information.
The results show that the proposed deep learning QC is robust, fast and accurate at estimating affine registration error in the processing pipeline.
Emitter-site specificity of hard x-ray photoelectron Kikuchi-diffraction
Authors: Fedchenko O , Winkelmann A , Chernov S , Medjanik K , Babenkov S , Agustsson S Y , Vasilyev D , Hoesch M , Elmers H-J , Schönhense G 
Published: September 2020

Abstract
High-resolution full-field imaging of (k

x
, k

y
) photoelectron distributions (k-resolution 0.03 Å−1, angular resolution 0.03° at 6.7 keV) in a large field of view (up to 16 Å−1 dia.) allows to observe fine details in Kikuchi-type diffractograms. Alongside with the element specificity via core-level spectra, this method opens a new avenue to structural analysis using hard x-ray photoelectron diffraction (hXPD). Here we present a theoretical study of the emitter-site specificity by simulating hXPD patterns for arbitrary positions of emitter atoms in the unit cell. Using the Bloch wave approach to photoelectron diffraction from lattice planes, the diffraction patterns from a number of positions in the unit cell can be obtained simultaneously exploiting the reciprocity theorem. Simulations for dopant atoms and dopant multimers (dimers, trimers, clusters) in the Si lattice at various positions in the unit cell reveal a strong site-sensitivity in terms of dramatic changes in the diffraction patterns with emitter-atom position. The results are compared with measurements for Si hyperdoped with Te.
O-GlcNAcylation inhibits the oligomerization of alpha-synuclein by declining intermolecular hydrogen bonds through a steric effect
Authors: Wu Kai , Li Dechang , Xiu Peng , Ji Baohua , Diao Jiajie 
Published: September 2020

Abstract
Toxic abnormal aggregation of α-synuclein (α-Syn) is a feature of Parkinson’s disease. Several biochemical and biophysical studies have demonstrated that many post-translational modifications (PTM) of α-Syn could distinctly alleviate its oligomerization-mediated toxicity. Recently, a compelling link is emerging between the PTM O-GlcNAcylation (O-GlcNAc) and protein aggregation, yet the underlying molecular mechanism remains unclear. Based on the all-atom molecular dynamics simulations, we found that O-GlcNAc modifications can suppress the process of oligomerization of α-Syn aggregates via a steric effect—the additional O-linked glycosyl group disrupts the formation of hydrogen bonds (H-bonds) between α-Syn monomers. Besides, we proposed a theoretical model to further capture the physical mechanism of α-Syn aggregation/disaggregation in the absence/presence of O-GlcNAc-modified α-Syn. Our findings unveil the molecular mechanism of the O-GlcNAc-induced inhibition of α-Syn oligomerization, which may help to understand how O-GlcNAc prevents the oligomerization of other proteins and provides the guideline for the development of O-GlcNAc-based therapeutic strategies in neurodegenerative diseases.
Thermodynamics in rotating anti-de Sitter black holes with massive scalar field in three dimensions *
Authors: Gwak Bogeun 
Published: September 2020

Abstract
We investigated the tendency in the variations of CFT2 when a rotating AdS3 black hole changes because of the fluxes transferred by the scattering of a massive scalar field according to the anti-de Sitter (AdS)/conformal field theory (CFT) correspondence. The conserved quantities of the black hole are definitely constrained by the extremal condition. Moreover, the laws of thermodynamics provide a direction for the changes in the conserved quantities. Therefore, the black hole cannot be extremal under the scattering; this is naturally preferred. According to the relationship between the rotating AdS3 black hole and dual CFT2, we find that such changes in the black hole constrain thevariations in the eigenstates of dual CFT2. Furthermore, the tendency in the variations is closely related to the laws of thermodynamics.
A Bayesian-neural-network prediction for fragment production in proton induced spallation reaction *
Authors: Ma Chun-Wang , Peng Dan , Wei Hui-Ling , Wang Yu-Ting , Pu Jie 
Published: September 2020

Abstract
Fragment production in spallation reactions yields key infrastructure data for various applications. Based on the empirical SPACS parameterizations, a Bayesian-neural-network (BNN) approach is established to predict the fragment cross sections in proton-induced spallation reactions. A systematic investigation has been performed for the measured proton-induced spallation reactions of systems ranging from intermediate to heavy nuclei systems and incident energies ranging from 168 MeV/u to 1500 MeV/u. By learning the residuals between the experimental measurements and SPACS predictions, it is found that the BNN-predicted results are in good agreement with the measured results. The established method is suggested to benefit the related research on nuclear astrophysics, nuclear radioactive beam sources, accelerator driven systems, proton therapy, etc.
Surface functionalization of PEEK with silicon nitride
Authors: Boschetto Francesco , Marin Elia , Ohgitani Eriko , Adachi Tetsuya , Zanocco Matteo , Horiguchi Satoshi , Zhu Wenliang , McEntire Bryan J , Mazda Osam , Bal B Sonny , Pezzotti Giuseppe 
Published: September 2020

Abstract
Surface roughness, bioactivity, and antibacterial properties are desirable in skeletal implants. We hot-pressed a mix of particulate sodium chloride (NaCl) salt and silicon nitride (β-Si3N4) onto the surface of bulk PEEK. NaCl grains were removed by leaching in water, resulting in a porous PEEK surface embedded with sim15 vol% β-Si3N4 particles. This functionalized surface showed the osteogenic and antibacterial properties previously reported in bulk silicon nitride implants. Surface enhancement of PEEK with β-Si3N4 could improve the performance of spinal fusion cages, by facilitating arthrodesis and resisting bacteria.
A map of roadmaps for zero and low energy and carbon buildings worldwide
Authors: Mata É , Korpal A K , Cheng S H , Jiménez Navarro J P , Filippidou F , Reyna J , Wang R 
Published: September 2020

Abstract
Formulation of targets and establishing which factors in different contexts will achieve these targets are critical to successful decarbonization of the building sector. To contribute to this, we have performed an evidence map of roadmaps for zero and low energy and carbon buildings (ZLECB) worldwide, including a list and classification of documents in an on-line geographical map, a description of gaps, and a narrative review of the knowledge gluts. We have retrieved 1219 scientific documents from Scopus, extracted metadata from 274 documents, and identified 117 roadmaps, policies or plans from 27 countries worldwide. We find that there is a coverage bias towards more developed regions. The identified scientific studies are mostly recommendations to policy makers, different types of case studies, and demonstration projects. The geographical inequalities found in the coverage of the scientific literature are even more extreme in the coverage of the roadmaps. These underexplored world regions represent an area for further investigation and increased research/policy attention. Our review of the more substantial amount of literature and roadmaps for developed regions shows differences in target metrics and enforcement mechanisms but that all regions dedicate some efforts at national and local levels. Roadmaps generally focus more on new and public buildings than existing buildings, despite the fact that the latter are naturally larger in number and total floor area, and perform less energy efficiently. A combination of efficiency, technical upgrades, and renewable generation is generally proposed in the roadmaps, with behavioral measures only reflected in the use of information and communication technologies, and minimal focus being placed on lifecycle perspectives. We conclude that insufficient progress is being made in the implementation of ZLECB. More work is needed to couple the existing climate goals, with realistic, enforceable policies to make the carbon savings a reality for different contexts and stakeholders worldwide.
How have surface NO2 concentrations changed as a result of the UK’s COVID-19 travel restrictions?
Authors: Dacre H F , Mortimer A H , Neal L S 
Published: September 2020

Abstract
Restrictions as a result of the COVID-19 pandemic have led to fewer vehicles on UK roads. Since fuel combustion is responsible for a large fraction of UK emissions it is expected that surface NO2 concentrations would reduce as a result. However, over parts of the UK, surface NO2 concentrations have increased following the implementation of travel restrictions. NO2 measurements from 142 Automatic Urban and Rural Network sites are combined with meteorological data from the Met Office high-resolution weather prediction model to build site specific models. These models predict NO2 concentrations given no change in emissions. It is found that both meteorological and emission changes contribute to the observed changes in NO2 concentrations. Given no change in emissions, changes in meteorology between pre- and post-lockdown periods would have led to a mean increase in NO2 concentrations of +6%. Conversely, changes in emissions would have led to a mean reduction in NO2 concentrations of -18%, resulting in the observed total change in NO2 concentrations of −12%. However at some sites the reduction in emissions is smaller than the increase in NO2 concentrations due to meteorology. The largest increases associated with changes in the meteorology are seen at rural sites (+20%) where NO2 measurements are representative of large areas and thus dominated by the regional advection of secondary NO2 from Europe. Conversely, the largest decreases associated with reduced emissions are found at urban traffic and urban background sites (−27% and −14% respectively) where NO2 concentrations are representative of local areas and thus dominated by local reduction in emissions from vehicles. As lockdown measures are relaxed, NO2 concentrations are likely to return to pre-COVID levels, but these results demonstrate that changes in our behaviour can result in positive impacts on air quality and illustrate the effectiveness of travel-reducing strategies in urban areas.
Electron in bilayer graphene with magnetic fields leading to shape invariant potentials
Authors: Fernández C David J , García M Juan D , O-Campa Daniel 
Published: September 2020

Abstract
The quantum behavior of electrons in bilayer graphene with applied magnetic fields is addressed. By using second-order supersymmetric quantum mechanics the problem is transformed into two intertwined one dimensional stationary Schrödinger equations whose potentials are required to be shape invariant. Analytical solutions for the energy bound states are obtained for several magnetic fields. The associated spectrum is analyzed, and the probability and current densities are determined.
Nanoindentation study and mechanical property analysis of nickel-based single crystal superalloys
Authors: Zhang Zhongkui , Wen Zhixun , Yue Zhufeng 
Published: September 2020

Abstract
Based on uniaxial tensile and compressive creeps, the mechanical properties of the third generation nickel-based single crystal superalloy were studied via the combination of nanoindentation, crystal plasticity theory, and finite element analysis. The Young’s moduli and hardness of γ, γ′ and the topologically close-packed (TCP) phases are related to chemical composition and applied stress. The maximum values of the Von Mises equivalent stress and damage are at the tip of the TCP phase. These values are inversely proportional to the distance to the TCP phase. Furthermore, the rafting of the γ′ phase can be predicted according to the distribution of the TCP phase and stress.
Mobility and threshold voltages comparison of zinc nitride-based thin-film transistor fabricated on Si and glass
Authors: Surve Sachin , Banerjee M K , Sachdev Kanupriya 
Published: September 2020

Abstract
The present work reports the fabrication and characterization of high mobility thin-film transistors, where zinc nitride is used as the active layer (∼100 nm thick). For the TFT, the active layer was deposited at room temperature on different substrates (Si-p type and glass) by RF magnetron sputtering method and annealed at 350 °C post-fabrication and HfO2 was used as the gate insulation layer (∼50 nm thick). The obtained value of field-effect mobility was greater than 5 cm2 Vs−1, with optical bandgap ∼3.07 eV. The two MIS (metal insulator semiconductor) structures were analyzed using I–V and C–V measurements. It is demonstrated that Zinc Nitride is a potential candidate to be used as an active layer in TFT fabrication. The threshold voltages of the device built on Si and glass substrates were obtained as 0.8 volts and 2.6 volts respectively.
Preparation a three-dimensional hierarchical graphene/stearic acid as a phase change materials for thermal energy storage
Authors: Wang Xiuli , Cheng Xiaomin , Li Dan , Li Yuanyuan , Li Ruguang , Gong Shengqin , Zhong Hao 
Published: September 2020

Abstract
Three-dimensional hierarchical graphene (3DHG) was compounded with stearic acid (SA) to obtain SA/3DHG composite phase change materials (PCMs). The specific surface area and pore volume of 3DHG are 393 m2 g−1 and 0.57 m3 g−1. The phase-transition temperatures of SA/3DHG composites keep at 69 ± 1 °C with different adding amounts of 3DHG, meanwhile SA/3DHG-3 possesses the melting enthalpy of 189.7 J·g−1 and solidifying enthalpy of 188.8 J·g−1. 3DHG shows significant enhancement on the thermal properties and shape stability of SA. The thermal conductivity of SA/3DHG-3 reaches to 0.93 W·m−1·K−1, which is as high as 2.8 times of pure SA (0.33 W·m−1·K−1). The investigations of XRD and FTIR indicate that no chemical but physical combination occurs between SA and graphene. 3DHG has substantial meso-porous/macro-porous structure for packaging SA to form the irregular core–shell structure. The hierarchical pores are also beneficial to the graded thermal transfer inside SA/3DHG composite PCMs. The efficiency of heating process from 25 °C to 90 °C was improved by about 57%. Furthermore, the 3D network skeleton built up by graphene sheets can form an effective and connected heat transfer paths for SA, thus improves the endothermic and exothermic efficiency of SA/3DHG composite PCMs. This work emphasizes the 3D hierarchical structure of graphene and provides a promising way to prepare composite PCMs with high large storage density and heat transfer efficiency.
Mode rolling effects in nitride laser diodes
Authors: Kuhn E , Uhlig L , Wachs M , Schwarz U T , Thränhardt A 
Published: September 2020

Abstract
Due to their small separation of longitudinal modes, Fabry-Pérot type laser diodes show rich mode competition effects. We present streak camera measurements of two nitride laser diodes with different cavity lengths and model them using a fully dynamic model based on the semiconductor Bloch equations, obtaining good agreement. Both theory and experiment show that the different mode spacing has a large influence on the interactions between longitudinal modes. In contrast to rate-equation type models, our approach includes the detailed density distribution as well as the derivation of the relevant parameters, e.g. broadening, from standard material quantities, thus setting a milestone on the way towards a fully predictive laser model.
Deep reinforcement learning for optical systems: A case study of mode-locked lasers
Authors: Sun Chang , Kaiser Eurika , Brunton Steven L , Nathan Kutz J 
Published: September 2020

Abstract
We demonstrate that deep reinforcement learning (deep RL) provides a highly effective strategy for the control and self-tuning of optical systems. Deep RL integrates the two leading machine learning architectures of deep neural networks and reinforcement learning to produce robust and stable learning for control. Deep RL is ideally suited for optical systems as the tuning and control relies on interactions with its environment with a goal-oriented objective to achieve optimal immediate or delayed rewards. This allows the optical system to recognize bi-stable structures and navigate, via trajectory planning, to optimally performing solutions, the first such algorithm demonstrated to do so in optical systems. We specifically demonstrate the deep RL architecture on a mode-locked laser, where robust self-tuning and control can be established through access of the deep RL agent to its waveplates and polarizers. We further integrate transfer learning to help the deep RL agent rapidly learn new parameter regimes and generalize its control authority. Additionally, the deep RL learning can be easily integrated with other control paradigms to provide a broad framework to control any optical system.