bluuebunny/crossref_metadata_2025_split huggingface dataset:
Graph ‘texture’ features as novel metrics that can summarize complex biological graphs
Authors: Barker-Clarke R , Weaver D T , Scott J G 
Published: June 2023

Abstract

Objective. Image texture features, such as those derived by Haralick et al, are a powerful metric for image classification and are used across fields including cancer research. Our aim is to demonstrate how analogous texture features can be derived for graphs and networks. We also aim to illustrate how these new metrics summarize graphs, may aid comparative graph studies, may help classify biological graphs, and might assist in detecting dysregulation in cancer. Approach. We generate the first analogies of image texture for graphs and networks. Co-occurrence matrices for graphs are generated by summing over all pairs of neighboring nodes in the graph. We generate metrics for fitness landscapes, gene co-expression and regulatory networks, and protein interaction networks. To assess metric sensitivity we varied discretization parameters and noise. To examine these metrics in the cancer context we compare metrics for both simulated and publicly available experimental gene expression and build random forest classifiers for cancer cell lineage. Main results. Our novel graph ‘texture’ features are shown to be informative of graph structure and node label distributions. The metrics are sensitive to discretization parameters and noise in node labels. We demonstrate that graph texture features vary across different biological graph topologies and node labelings. We show how our texture metrics can be used to classify cell line expression by lineage, demonstrating classifiers with 82% and 89% accuracy. Significance. New metrics provide opportunities for better comparative analyzes and new models for classification. Our texture features are novel second-order graph features for networks or graphs with ordered node labels. In the complex cancer informatics setting, evolutionary analyses and drug response prediction are two examples where new network science approaches like this may prove fruitful.
Dosimetric comparison of autocontouring techniques for online adaptive proton therapy
Authors: Smolders A , Choulilitsa E , Czerska K , Bizzocchi N , Krcek R , Lomax A , Weber D C , Albertini F 
Published: June 2023

Abstract

Objective. Anatomical and daily set-up uncertainties impede high precision delivery of proton therapy. With online adaptation, the daily plan is reoptimized on an image taken shortly before the treatment, reducing these uncertainties and, hence, allowing a more accurate delivery. This reoptimization requires target and organs-at-risk (OAR) contours on the daily image, which need to be delineated automatically since manual contouring is too slow. Whereas multiple methods for autocontouring exist, none of them are fully accurate, which affects the daily dose. This work aims to quantify the magnitude of this dosimetric effect for four contouring techniques. Approach. Plans reoptimized on automatic contours are compared with plans reoptimized on manual contours. The methods include rigid and deformable registration (DIR), deep-learning based segmentation and patient-specific segmentation. Main results. It was found that independently of the contouring method, the dosimetric influence of using automatic OAR contours is small (<5% prescribed dose in most cases), with DIR yielding the best results. Contrarily, the dosimetric effect of using the automatic target contour was larger (>5% prescribed dose in most cases), indicating that manual verification of that contour remains necessary. However, when compared to non-adaptive therapy, the dose differences caused by automatically contouring the target were small and target coverage was improved, especially for DIR. Significance. The results show that manual adjustment of OARs is rarely necessary and that several autocontouring techniques are directly usable. Contrarily, manual adjustment of the target is important. This allows prioritizing tasks during time-critical online adaptive proton therapy and therefore supports its further clinical implementation.
Phase-tunable multiple Andreev reflections in a quantum spin Hall strip
Authors: Yang Xue , Burset Pablo , Lu Bo 
Published: June 2023

Abstract
A quantum spin Hall strip where different edges are contacted by s-wave superconductors with a phase difference φ supports Majorana bound states protected by time-reversal symmetry. We study signatures of these states in a four-terminal setup where two Josephson junctions are built on opposite edges of the strip and the phase difference between superconductors can be controlled by an external flux. Applying a voltage bias across the quantum spin Hall strip results in a sequence of conductance peaks from multiple Andreev reflections (MARs). We find that this so-called subharmonic gap structure is very sensitive to the phase difference and displays a phase-controlled even–odd effect, where all odd spikes disappear when the Majorana states are formed for

ϕ
=
π

. Moreover, the remaining even spikes split when the superconductors forming the junction have different gap size. We explain these features by showing that any midgap bound states enhance the transmission of the even order MARs, while the reduced density of states at the gap edges suppresses the odd order ones.
Coherent population transfer in the interaction of five-state nuclei with x-ray lasers using chain-STIRAP technique
Authors: Amiri Mehdi , Saadati-Niari Maghsoud 
Published: June 2023

Abstract
The complete population transfer from the first state to the fifth one in a five-state nuclear system that interacts with four x-ray laser pulses has been theoretically studied using the chain-STIRAP technique. In this scheme, it is assumed that the accelerated nucleus interacts with four x-ray laser pulses, and the relativistic factor is adjusted so that the resonance condition is established between the x-ray laser frequencies and the transition frequency of the nucleus. In this study, by establishing the adiabatic condition, the Hamiltonian of the system remains in the dark state. Therefore, the second and fourth states are not populated during the time evolution. Also, to eliminate the population of the third state during the interaction, the middle pulses are considered more significant compared to the first and last pulses. For the numerical study, 168Er is considered and, it is shown that the population is completely transferred from the first state to the fifth state.
Reconstructing the cosmological density and velocity fields from redshifted galaxy distributions using V-net
Authors: Qin Fei , Parkinson David , Hong Sungwook E. , Sabiu Cristiano G. 
Published: June 2023

Abstract
The distribution of matter that is measured through galaxy redshift and peculiar velocity surveys can be harnessed to learn about the physics of dark matter, dark energy, and the nature of gravity. To improve our understanding of the matter of the Universe, we can reconstruct the full density and velocity fields from the galaxies that act as tracer particles. In this paper, we use
the simulated halos as proxies for the galaxies. We use a convolutional neural network, a V-net, trained on numerical simulations of structure formation to reconstruct the density and velocity fields. We find that, with detailed tuning of the loss function, the V-net could produce better fits to the density field in the high-density and low-density regions, and improved predictions for the probability distribution of the amplitudes of the velocities. However, the weights will reduce the precision of the estimated β parameter. We also find that the redshift-space distortions of the halo catalogue do not significantly contaminate the reconstructed real-space density and velocity field. We estimate the velocity field β parameter by comparing the peculiar velocities of halo catalogues to the reconstructed velocity fields, and find the estimated β values agree with the fiducial value at the 68% confidence level.
Low-power blue LED and red laser effects on plasmid DNA, survival, and photolyase mRNA levels in Escherichia coli cultures
Authors: Ribeiro Rickson Souza , Rodrigues Juliana Alves , Mencalha Andre Luiz , da Fonseca Adenilson de Souza 
Published: June 2023

Abstract
Low-power lasers and light-emitting diodes (LEDs) are used for photobiomodulation therapy, but the photobiological effects on DNA repair mechanisms in bacteria cells are disputed yet. This work aimed to evaluate the induction of DNA damages in plasmids, bacterial survival and proliferation, and photolyase mRNA levels in E. coli cultures exposed to low-power blue LED and red laser, followed by ultraviolet c (UVC) radiation. Aliquots of pUC19 plasmids and E. coli C600 cultures were exposed to low-power blue LED (470 nm) and red laser (658 nm) at different fluences. Other E. coli C600 cultures were exposed to UVC radiation after exposure to low-power blue LED and red laser. After irradiations, plasmids were submitted to agarose gel electrophoresis to evaluate DNA damage, bacterial cultures were spread onto Petri dishes content rich medium and incubated to evaluate bacterial survival and proliferation, and photolyase mRNA levels in bacterial cells were evaluated by reverse transcription-quantitative polymerase chain reaction. The results suggest that exposure to blue and red lights emitted from low-power LEDs and lasers does not cause DNA strand breaks in bacterial plasmids and does not alter the survival and mRNA levels from photolyase gene in E. coli cells, but increases bacterial survival and proliferation in E. coli cultures exposed to UVC radiation depending on LED and laser fluences.
Disruption prediction on EAST with different wall conditions based on a multi-scale deep hybrid neural network
Authors: Guo B.H. , Chen D.L. , Rea C. , Wu M.Q. , Shen B. , Granetz R.S. , Zhang Z.C. , Huang Y. , Duan Y.M. , Zeng L. , Xiao B.J. 
Published: June 2023

Abstract
Plasma disruption is a very dangerous event for future tokamaks and fusion reactors. Therefore, predicting disruption is crucial for ensuring the safety and performance of reactors. In this study, the features of two deep learning algorithms are integrated to establish a multi-scale hybrid network disruption predictor. Firstly, 43 diagnostic signals are extracted by a convolutional neural network (CNN), and the time information is learned by a long short-term memory network. The predictor is trained and tested on a database containing

∼

10
4

non-all-metal wall discharges. Its area under the receiver operator characteristic curve (AUC), which is a common performance metric for deep learning algorithms, reaches 0.97, and the true positive rate is

∼

95.3
%

, while the false positive rate is

∼

8
%

. Since EAST was upgraded in 2020, the wall condition has been upgraded from non-all-metal to all-metal. To examine the robustness of the predictor, the EAST disruption predictor is migrated to the all-metal wall experiment for the first time. It is again tested under the all-metal wall experimental data, and its warning performance decreases significantly, with an AUC of only 0.79. To improve the robustness and sensitivity of the predictor against disruptions, the convolutional attention mechanism is introduced into the CNN. After training and testing with the same data set, the warning performance for the all-metal wall data is improved, with the AUC value increasing to 0.84. To further improve the robustness of the predictor, the t-distributed stochastic neighbor embedding algorithm is employed to explore the difference of the sample distribution before and after EAST upgradation, and the transfer learning algorithm is used to reduce this difference. By applying transfer learning to a small amount of discharges from the all-metal wall data, the warning performance in the all-metal wall experiment is further improved, and the AUC value increases to 0.93. Overall, the proposed data-driven predictor is promising for applications in future devices such as ITER.
The phase-space structure of a nonlinear ion diffusion tensor in ion-temperature-gradient-driven turbulence
Authors: Sun Shiqiao , Li Yuesong , Wang Zihao , Wang Shaojie 
Published: June 2023

Abstract
The phase-space structure of an ion diffusion tensor in ion temperature gradient (ITG)-driven turbulence is studied using the newly developed numerical code Numerical Diagnosis of Transport Matrix. The numerical results show that at both the linear and nonlinear stage, the diffusion tensor of ITG turbulence presents a typical ballooning structure in the poloidal direction and a magnetic drift resonance structure in velocity space. The D

rr
and D

rK
components of the diffusion tensor satisfy the Stokes–Einstein relation. It is found that the phase-space structure of the ion diffusion tensor at the linear stage is induced by the resonance between ions and ITG eigenmodes, while that at the nonlinear stage is induced by the resonance between ions and the daughter ballooning modes under the poloidal acceleration of nonlinear zonal radial electric fields.
Neon seeding effects on two high-performance baseline plasmas on the Joint European Torus
Authors: Gabriellini S. , Garzotti L. , Zotta V.K. , Bourdelle C. , Casson F.J. , Citrin J. , Frigione D. , Gatto R. , Giroud C. , Koechl F. , Lomas P. , Marin M. , Menmuir S. , Pucella G. , Rimini F. , van Eester D. 
Published: June 2023

Abstract
We present the JETTO-QuaLiKiz-SANCO fully predictive modelling of two JET-ILW high-performance baseline plasmas, a Ne seeded shot and an equivalent unseeded one. The motivation of the work lies in the experimental observation of a slightly higher confinement and performance of the Ne seeded shot with respect to the unseeded one, despite sharing the same main plasma parameters and heating powers. Moreover, the neon seeded shot shows a lower pedestal electron density and a higher core ion temperature with respect to the unseeded one. Integrated modelling is performed in order to understand if the cause of the improved confinement has to be ascribed to the improved pedestal parameters with neon seeding or if an impurity-induced turbulence stabilization is at play. The QuaLiKiz transport model is used for predicting the electron density, electron and ion temperatures and rotation in the core up to the pedestal top, while the pedestal is empirically modelled to reproduce the experimental kinetic profiles. The thermal diffusivities of the two shots, computed by QuaLiKiz, are compared, as well as the turbulence spectra, suggesting that the reduced transport found in the neon seeded shot is due in part to the stabilization of ion temperature gradient and electron temperature gradient modes. Further modelling is performed in order to disentangle the neon seeding effects, which are a direct effect on the turbulence stabilization and an indirect effect on the pedestal parameters. The results suggest that the improved performance with neon is due to a combination of turbulence stabilization and improved pedestal parameters.
The vibration of the double-plated structure containing the inner fluid and elastic connections
Authors: Wen Shitian , Chen Meixia 
Published: June 2023

Abstract
Analytical studies of the vibration characteristics of double-plated structure containing the inner fluid and elastic connections have been performed. An analytical model is first derived to predict the vibration characteristics of the double-plated structure. The transverse displacements of plate and the sound pressure of inner fluid are described by the improved Fourier series. Elastic connections are regarded as springs. In order to simulate arbitrary boundary conditions, the virtual spring technology is applied along each side of the plates. The vibration and sound pressure can be obtained by the Fourier coefficients which calculated by the Rayleigh-Ritz technique. Results from the finite element method (FEM) are well consistent with ones calculated by the analytical method. The effects of parameters on vibration are studied by analytical analyses. It is found that the inner air shows well vibration isolation, while inner water acts as a short circuit in vibration transmission. The stiffness of the elastic connection has significant effects only when the inner fluid is air. When the inner fluid is water, the effect of the spring will be greatly weakened.
Size dependence for mechanical properties of Ti/Cu multilayered nanowire with a semi-coherent interface
Authors: Liu Lanting , Wang Ruifeng , Su Mengjia , An Minrong , Wu Zhibo 
Published: June 2023

Abstract
Metallic multilayered nanowires have a wide application prospect in micro-nano devices because of their superior physical and chemical properties and microstructure designability. Size effects on the tensile behaviors of Ti/Cu multilayered nanowires are investigated by molecular dynamic simulations. Aspect ratios of 1:4, 1:3, 1:2, 1:1, 1:0.75, and 1:0.67 and sectional dimensions of 3, 4, 5, 6, and 7 nm are adopted to construct nanowires with different sizes. Simulation results indicate that the strength of Ti/Cu nanowires decreases with the decrease of aspect ratio in the large aspect ratio range (>1:2) and all simulated sectional dimension ranges, showing a reverse Hall-Petch effect. The Hall-Petch law can only be satisfied in a small aspect ratio range (<1:2). Deformation mechanism transition is found in the critical aspect ratio of 1:2. When the aspect ratio is larger than 1:2, crystalline phases of Ti and Cu layers dominate the plastic deformation of Ti/Cu nanowires. Crystal phases and interface both bear plastic deformation when the aspect ratio is smaller than 1:2. Interface is an important factor in the strength and deformation of Ti/Cu nanowires. The variation of interface fraction and interaction between interface and dislocation motion determine the tendency of strength variation for Ti/Cu nanowires.
A non-Fourier magneto-thermo-viscoelastic problem of a two-dimensional plate
Authors: Li Peng , Zhang Hui 
Published: June 2023

Abstract
Viscoelastic materials is a kind of damping materials which has been wildly applied in vibration control of ocean and civil engineering, and viscoelastic materials mostly work in a complex thermoelectric multi-field coupled environment. In this work, a two-dimensional viscoelastic plate is studied with stain relaxation time and viscoelastic relaxation time. The two-dimensional viscoelastic plate is placed in a magnetic field, and the upper surface is subjected to a thermal shock. The problem is investigated by a modified L-S thermo-viscoelastic model with stain, viscoelastic relaxation time, and magnetic field. Normal mode analysis is used to achieve exact analytical expressions of temperature distribution, displacement component and thermal stresses. Numerical computations are conducted for copper-like material and dimensionless results are illustrated graphically. Based on the results, the influence of magnetic field on the distributions of the nondimensional temperature, displacement and stresses are discussed.
The kinematics and deformation of bubbles when impacting the curved boundary with hydrophilicity and hydrophobicity
Authors: Tang Zijian , Wei Du , Li Guanghua , Du Peng , Hu Haibao , Chen Xiaopeng , Wen Jun , Xie Luo 
Published: June 2023

Abstract
Research on the behavior of bubble collision has always been one of the focuses in the scientific field. This work focuses on the kinematics and deformation of bubbles when impacting the curved boundary with hydrophilicity and hydrophobicity. The impact process of bubbles colliding with the curved wall was recorded by a high-speed camera. The effects of wettability and radius of curvature were analyzed. The results show that when the bubble collides with the hydrophilic curved wall, it will bounce many times until it leaves the wall. Aiming at the phenomenon of liquid film extrusion rupture, a theoretical model is established to deduce the prediction formula of liquid film induction time, which is mainly related to the thickness, the critical rupture thickness, and the compression speed of the liquid film. The prediction error is less than 5.0%.
Appearance of sexaquark in the core of neutron stars as a candidate of dark matter
Authors: Shahrbaf Mahboubeh 
Published: June 2023

Abstract
We study the appearance of sexaquark (uuddss) as a candidate of dark matter in the core of neutron stars while there has been no experimental evidence of this particle in laboratories so far. Regarding the observational constraints of supermassive pulsars as well as gravitational waves, we encounter a sexaquark dilemma for which we introduce a solution by quark deconfinement fulfilling all present constraints from multi-messenger astronomy, i.e., tidal deformability in accordance with GW170817 and maximum mass above the lower limit from PSR J0740+6620.
Can the MDCDW condensate withstand the heat of a cold neutron star?
Authors: Gyory W. 
Published: June 2023

Abstract
The correct description of strongly interacting matter at low temperatures and moderately high densities—in particular the conditions realized inside neutron stars—is still unknown. We review some recent results on the magnetic dual chiral density wave (MDCDW) phase, a candidate phase of quark matter for this region of the QCD phase diagram. We highlight the effects of magnetic fields and temperature on the condensate, which can be explored using a high-order Ginzburg-Landau (GL) expansion. We also explain how the condensate’s nontrivial topology, which arises due to the asymmetry in the lowest Landau level modes, affects its physical properties. Finally, we comment on the possible relevance of these results to neutron star applications. Over a wide range of densities and magnetic field strengths, MDCDW is preferred over the chirally symmetric ground state at temperatures consistent with typical cold neutron stars, and in some cases, even hot ones.
Polymer-mixed Sb2Te3/Te nanocomposites exhibiting p-type to n-type conduction reversal and thermal conductivity reduction
Authors: Meena Dilip Kumar , Bose Rapaka S C , Umarji A M , Babu D Arvindha 
Published: June 2023

Abstract
Sb2Te3-based materials are potential room-temperature thermoelectric materials. In the present work, we choose polycrystalline Sb2Te3/Te nanocomposites and utilize Poly Methyl Methacrylate (PMMA) to reduce the thermal conductivity of Sb2Te3 samples. PMMA and polycrystalline Sb2Te3/Te were well mixed using ball milling. Pellets have been made by the cold press method. Thermoelectric transport properties of Sb2Te3/Te nanocomposites: composition, microstructure, and analysis are found to be influenced by PMMA. With increasing PMMA concentration a p-type to n-type transition has been observed because there are fewer charge carriers or the composites have a higher resistance. It is also observed that the thermal conductivity of Sb2Te3/Te nanocomposites decreases as the PMMA increases. This research paves the way for making the best thermoelectric materials by reducing thermal conductivity through the use of polymers.