bluuebunny/crossref_metadata_2025_split huggingface dataset:
High quality factor, protein-based microlasers from self-assembled microcracks
Authors: Nguyen Tam Trong , Mai Hanh Hong , Pham Thin Van , Nguyen Thau Xuan , Ta Van Duong 
Published: March 2021

Abstract
In the last decade, microlasers with biological origin have shown their great potential in biosensing and bioimaging. Several micro-structures have been developed for high quality (Q) factor biolasers including Fabry–Pérot, distributed feedback and whispering gallery mode cavities. However, the fabrication of these lasers is generally complicated and their operation is strongly affected by cavity defects. In this work, we demonstrate random protein-based microlasers fabricated by a simple one-step self-assembled method. The lasing can be achieved from microcracks with random structures. The lasing threshold is around 14 mJ cm−2 and the quality factor of lasing modes can be up to

3
×

10
3

which are comparable with other conventional biolasers. Our work opens a new possibility for the fabrication of high Q factor microlasers from biocompatible materials, with great potential for biosensing and biomedical applications.
Error propagation dynamics of velocimetry-based pressure field calculations (2): on the error profile
Authors: Faiella Matthew , Grant Jeon Macmillan Corwin , Whitehead Jared P , Pan Zhao 
Published: March 2021

Abstract
A recent study investigated the propagation of error in a velocimetry-based pressure (V-pressure) field reconstruction problem by directly analyzing the properties of the pressure Poisson equation (Pan et al 2016 Meas. Sci. Technol.
27 084012). In the present work, we extend these results by quantifying the effect of the error profile in the data field (shape/structure of the error in space) on the resultant error in the reconstructed pressure field. We first calculate the mode of the error in the data that maximizes error in the pressure field, which is the most dangerous error (called the worst error in the present work). This calculation of the worst error is equivalent to finding the principle mode of, for example, an Euler–Bernoulli beam problem in one-dimension and the Kirchhoff–Love plate in two-dimensions, thus connecting the V-pressure problem from experimental fluid mechanics to buckling elastic bodies from elastic mechanics. Taking advantage of this analogy, we then analyze how the error profile (e.g. spatial frequency of the error and the location of the most concentrated error) in the data field coupled with fundamental features of the flow domain (i.e. size, shape, and dimension of the domain, and the configuration of boundary conditions) significantly affects the error propagation from data to the reconstructed pressure. Our analytical results lend to practical applications in two ways. First, minimization of error propagation can be achieved by avoiding low frequency error profiles in data similar to the worst case scenarios and error concentrated at sensitive locations. Second, small amounts of the error in the data, if the error profile is similar to the worst error case, can cause significant error in the reconstructed pressure field; such a synthetic error can be used to benchmark V-pressure algorithms.
Male pelvic CT multi-organ segmentation using synthetic MRI-aided dual pyramid networks
Authors: Lei Yang , Wang Tonghe , Tian Sibo , Fu Yabo , Patel Pretesh , Jani Ashesh B , Curran Walter J , Liu Tian , Yang Xiaofeng 
Published: March 2021

Abstract
The delineation of the prostate and organs-at-risk (OARs) is fundamental to prostate radiation treatment planning, but is currently labor-intensive and observer-dependent. We aimed to develop an automated computed tomography (CT)-based multi-organ (bladder, prostate, rectum, left and right femoral heads (RFHs)) segmentation method for prostate radiation therapy treatment planning. The proposed method uses synthetic MRIs (sMRIs) to offer superior soft-tissue information for male pelvic CT images. Cycle-consistent adversarial networks (CycleGAN) were used to generate CT-based sMRIs. Dual pyramid networks (DPNs) extracted features from both CTs and sMRIs. A deep attention strategy was integrated into the DPNs to select the most relevant features from both CTs and sMRIs to identify organ boundaries. The CT-based sMRI generated from our previously trained CycleGAN and its corresponding CT images were inputted to the proposed DPNs to provide complementary information for pelvic multi-organ segmentation. The proposed method was trained and evaluated using datasets from 140 patients with prostate cancer, and were then compared against state-of-art methods. The Dice similarity coefficients and mean surface distances between our results and ground truth were 0.95 ± 0.05, 1.16 ± 0.70 mm; 0.88 ± 0.08, 1.64 ± 1.26 mm; 0.90 ± 0.04, 1.27 ± 0.48 mm; 0.95 ± 0.04, 1.08 ± 1.29 mm; and 0.95 ± 0.04, 1.11 ± 1.49 mm for bladder, prostate, rectum, left and RFHs, respectively. Mean center of mass distances was within 3 mm for all organs. Our results performed significantly better than those of competing methods in most evaluation metrics. We demonstrated the feasibility of sMRI-aided DPNs for multi-organ segmentation on pelvic CT images, and its superiority over other networks. The proposed method could be used in routine prostate cancer radiotherapy treatment planning to rapidly segment the prostate and standard OARs.
Spatial characteristics of luminous hydrocarbon pellet clouds in the large helical device
Authors: Sharov I A , Sergeev V Yu , Miroshnikov I V , Tamura N , Sudo S 
Published: March 2021

Abstract
This study analyzes the dependences of the size of the luminous region of hydrocarbon pellet cloud on the ablation rate, as well as on the ambient plasma electron density and temperature. The data were obtained in a series of experiments where spherical solid polystyrene pellets with a diameter of ≈900 μm at a speed of ≈450 m s−1 were injected into hydrogen plasma of the large helical device. The ambient plasma with an electron temperature of 0.5–1.5 keV and a density of (1–7) × 1019 m−3 was maintained by injection of neutral atom beams with total the heating power of 3–14 MW. A scaling law was derived for determining the transverse size of the cloud’s luminous region from the known values of the pellet’s current radius as well as the values of the density and temperature of the ambient plasma at the place of image acquisition. The interdependencies between various dimensions of the luminous region obtained in the line spectrum are established. The presence of such dependences makes it possible to describe the dimensions of the luminous region comprehensively by means of the scaling law for its transverse size.
Modeling active control of resistive wall mode with power saturation and sensor noise on HL-2M
Authors: Wang S , Liu Y Q , Xia G L , Song X M , Hao G Z , Li L , Li B , Zhang N , Dong G Q , Bai X , Zheng G Y 
Published: March 2021

Abstract
The resistive wall mode (RWM) control on the HL-2M tokamak is simulated with the MARS-F code (Liu et al 2000 Phys. Plasmas
7 3681), aiming at quantifying control current and voltage requirements when more realistic issues are taken into account, i.e. the control power saturation and the sensor signal noise. The fluid model predicts a narrow stability region for the n = 1 RWM without magnetic feedback, in the 2D parameter space of the plasma pressure versus the toroidal flow speed. Magnetic feedback can fully stabilize the RWM on HL-2M. Without considering the voltage limitation and the sensor signal noise, it is found that plasma flow helps active control of the mode, by reducing the required critical feedback gain for both flux-to-current and flux-to-voltage control schemes. In the absence of the sensor signal noise, the lowest control voltage saturation level, below which the RWM control is lost, is found to roughly satisfy a linear relation to the plasma flow frequency, indicating that subsonic plasma flow is effective in relaxing the control power requirement for the RWM feedback stabilization. The presence of the sensor signal noise substantially modifies the feedback results. A statistical study finds that the sensor signal noise, with the standard deviation of 0.1 G on HL-2M, roughly doubles the required control voltage for successful mode control. The synergistic stabilization effect due to plasma flow is somewhat weakened by the presence of the sensor signal noise. At a given rotation, the tolerable voltage limit generally increases with increasing feedback gain due to the sensor signal noise.
2D particle-in-cell simulations of geometrically asymmetric low-pressure capacitive RF plasmas driven by tailored voltage waveforms
Authors: Wang Li , Hartmann Peter , Donkó Zoltán , Song Yuan-Hong , Schulze Julian 
Published: March 2021

Abstract
The effects of the simultaneous presence of two different types of plasma asymmetry, viz, geometric and electrical, on low-pressure capacitively coupled argon discharges are studied by 2D3V graphics-processing-unit-based particle-in-cell/Monte Carlo simulations. The geometric asymmetry originates from the different powered vs grounded electrode surface areas, while the electrical asymmetry is established by applying peaks/valleys and sawtooth-up/-down driving voltage waveforms. While in geometrically symmetric discharges, the {peaks ↔ valleys} and the {sawtooth-down ↔ sawtooth-up} switching of the waveforms is equivalent to exchanging the powered and grounded electrodes, this transformation is violated when the geometric symmetry is broken. Under such conditions, the plasma characteristics and the DC self-bias generation behave differently, compared to the geometrically symmetric case. This leads to different sheath dynamics and, therefore, strongly influences the electron power absorption dynamics. For identical peak-to-peak voltages, the plasma density obtained for such tailored voltage waveforms is found to be higher compared to the classical single-frequency waveform case. Reduced plasma densities are found in the valleys- and sawtooth-down waveform cases, compared to the peaks- and sawtooth-up waveforms. By including realistic energy and material-dependent secondary electron emission (SEE) coefficients in the simulations, the electron-induced SEE is found to be reduced in the valleys- and sawtooth-down waveform cases, which explains the behaviour of the plasma density. Using such tailored waveforms in geometrically asymmetric discharges is also found to lead to the formation of different charged particle energy distributions at the boundary surfaces, compared to those in geometrically symmetric plasma sources.
Structure of DC magnetron sputtering discharge at various gas pressures: a two-dimensional particle-in-cell Monte Carlo collision study
Authors: Ryabinkin A N , Serov A O , Pal A F , Mankelevich Yu A , Rakhimov A T , Rakhimova T V 
Published: March 2021

Abstract
We report the results of a particle-in-cell Monte-Carlo collision simulation of an axially symmetric DC magnetron discharge with a 5 cm diameter flat cathode in argon at pressures from 1 to 10 mTorr at a constant discharge current of about 0.5 A. Calculations show that the cathode region, where almost the entire discharge voltage drops, consists of a cathode sheath 0.1–0.2 mm wide and a presheath about 2 cm wide, where most of the ionizations occur, separated by a region 0.25–0.35 mm wide, where the plasma potential remains almost unchanged and the plasma density reaches its maximum value. Most of the discharge voltage drops in the presheath at low gas pressure, and in cathode sheath at high pressure. The ratio of sheath to presheath voltages increases linearly with pressure. The distribution of the ionization rate has two maxima: near the cathode sheath and in the presheath. The fraction of ionizations near the cathode sheath increases with pressure. The electron energy distribution function (EEDF) is generally a two-temperature function. At low pressures at a distance of less than 1 cm from the cathode, the EEDF becomes one-temperature. A high-energy tail is observed on the EEDF near the cathode; the fraction of electrons in the tail (in the order of tenths of a percent at 10 mTorr) and their energy, determined by the sheath voltage, increase with pressure. The electron temperature decreases with pressure due to a decrease of the electric field in the presheath, which leads to a decrease of energetically accessible regions of collisionless electron motion and to a corresponding decrease in the energy that electrons can obtain in these regions. The dependence of the discharge voltage on the gas pressure has a minimum at about 3 mTorr, which occurs due to the competition of two processes on pressure increase: a decrease in the electron temperature and a decrease in the fraction of electrons returning back to the cathode. Plasma density waves are observed in the presheath region at pressures of 1–3 mTorr.
Genuine monogamy relations in no-signaling theories—a geometric approach
Authors: Ryu Junghee , Lee Daemin , Lee Jinhyoung , Kurzyński Paweł , Kaszlikowski Dagomir 
Published: March 2021

Abstract
Quantum correlations are subject to certain distribution rules represented by so-called monogamy relations. Derivation of monogamy relations for multipartite systems is a non-trivial problem, as the multipartite correlations reveal their behaviors in a way different from bipartite systems. We here show that simple geometric properties of probabilistic spaces, in conjunction with no-signaling principle, lead to genuine monogamy relations for a large class of Bell type inequalities for many qubits. The term of ‘genuine’ implies that only one out of N Bell inequalities exhibits a quantum violation. We also generalize our method to qudits. Using the similar geometric approach with a quasi-distance employed, we derive Svetlichny–Zohren–Gill type Bell inequalities for d-dimensional tripartite systems, and show their monogamous nature.
Redshift-space distortions in Lagrangian perturbation theory
Authors: Chen Shi-Fan , Vlah Zvonimir , Castorina Emanuele , White Martin 
Published: March 2021

Abstract
We present the one-loop 2-point function of biased tracers
in redshift space computed with Lagrangian perturbation theory,
including a full resummation of both long-wavelength (infrared)
displacements and associated velocities. The resulting model
accurately predicts the power spectrum and correlation function of
halos and mock galaxies from two different sets of N-body
simulations at the percent level for quasi-linear scales, including
the damping of the baryon acoustic oscillation signal due to the
bulk motions of galaxies. We compare this full resummation with
other, approximate, techniques including the moment expansion and
Gaussian streaming model. We discuss infrared resummation in detail
and compare our Lagrangian formulation with the Eulerian theory
augmented by an infrared resummation based on splitting the input
power spectrum into “wiggle” and “no-wiggle” components. We
show that our model is able to recover unbiased cosmological
parameters in mock data encompassing a volume much larger than what
will be available to future galaxy surveys. We demonstrate how to
efficiently compute the resulting expressions numerically, making
available a fast Python code capable of rapidly computing these
statistics in both configuration and Fourier space.
Optimization of the computation of total and local radiated power at ASDEX Upgrade
Authors: David P. , Bernert M. , Pütterich T. , Fuchs C. , Glöggler S. , Eich T. , the ASDEX Upgrade Team  
Published: March 2021

Abstract
Radiation losses are measured as a line integrated quantity from the plasma, on ASDEX Upgrade using foil bolometers. Based on these measurements, the computation of the radiated power from either the whole volume or any sub region requires post processing including key assumptions. A new algorithm to improve this computation was recently developed and benchmarked. The algorithm is based on a routinely used tomography method and allows for local radiative events to be properly taken into account. It is compared to two other methods used at ASDEX Upgrade: the generic one based on flux tube symmetry and a more specific method using a 1D fit to compute the radiation excluding the divertor. In benchmarks with phantom radiation distributions, the new method shows a significantly better accuracy of −2.9 ± 5.2% in comparison to the previous algorithm accuracy of −27.8 ± 21.4% (average ± standard deviation on all test cases of the benchmark). The new code also allows the systematic computation of the radiated power from four sub regions, such as the divertor, the main chamber and inside the separatrix.
Modification of favorable average curvature effect by changing parallel sound wave behavior in tokamak plasmas
Authors: Bai Xue , Liu Yueqiang , Hao Guangzhou 
Published: March 2021

Abstract
The favorable average curvature effect, also known as the GGJ effect (Glasser et al 1975 Phys. Fluids
18 875), is intrinsically associated with parallel sound wave propagation in a tokamak plasma. This work investigates how the GGJ effect is modified by changing the parallel sound wave behavior. Two physics models beyond the standard single fluid theory, i.e. an anisotropic thermal transport model and a parallel sound wave damping model, are employed to change parallel sound waves in a toroidal plasma, and the consequence on the GGJ effect is demonstrated for two important classes of problems, i.e. the resistive plasma response to the applied resonant magnetic perturbation and the stability of the tearing mode. Toroidal modeling reveals that the GGJ effect is significantly altered by both of the aforementioned physics effects. Compared to the thermal transport physics, which completely removes the GGJ effect, the sound wave damping effect only offers partial mitigation. The differences between these two models are further illustrated in terms of the radial structure of the shielding current and the eigenfunction of the tearing instability. In particular, a fundamental reason for complete suppression of the GGJ effect by the thermal transport is identified as an extra toroidal coupling of the poloidal harmonics.
Comparison of Colorectal Cancer Classification between K-Nearest Neighbors (K-NN) and Neural Network
Authors: Zhafarina F , Rustam Z , Amalia Y , Wirasati I 
Published: March 2021

Abstract
Machine learning is one of the technologies used in medicine. Machine learning can help detect various kinds of problems in the medical field and enables a process to be faster and more efficient. Cancer is one of the most dangerous diseases in the world. Machine learning is widely used in bioinformatics and particularly in cancer diagnosis. One of the most popular methods is K-nearest neighbors (K-NN) and Neural Network. There are supervised learning methods. Using K-NN, the quality of the results depends largely on the distance and the value of the parameter “k” which represents the number of the nearest neighbors. This research is explains the classification of colorectal cancer by using K-NN with different k values and Neural Network Classification. Our work will be performed on the Colorectal Cancer dataset obtained by the Al-Islam Hospital, Bandung, Indonesia and it consists of benign cases 163 and malignant cases 47 samples. Thus, the final result indicates better performance for K-nearest neighbors’ accuracy is 0.786 in K-parameter equal to 7, 9, 11 has the same accuracy with 60% data training and Neural Network reached 0.904 with 90% of data training.
Mathematical model of schistosomiasis with health education and molluscicide intervention
Authors: Nur W , Trisilowati  , Suryanto A , Kusumawinahyu W M 
Published: March 2021

Abstract
In this article, a mathematical model is developed to study the impact of health education and molluscicide intervention on the spread of schistosomiasis. The model constructed consists of seven ordinary differential equations that describe susceptible human, latent human, infectious human, susceptible snail, infected snail, miracidia and cercarie. After analyzing non-negativity and boundedness of solutions of the model, we determine the disease free equilibrium point and the endemic equilibrium point as well as their existence conditions. The basic reproduction number is determined using the next generation matrix approach. The local stability condition of the disease-free equilibrium point is proved by using linearization and Descartes’ sign rule.. The Center Manifold Theory is used to prove the local stability condition of the endemic equilibrium point and to identify the existence of bifurcation. We constructed Lyapunov function to show that the disease-free equilibrium point is globally asymptotically stable under sufficient condition. We present numerical simulations to support our theoretical study. Numerical simulations show that health education and molluscicide intervention are able to reduce schistosomiasis cases in human and snail populations. Molluscicide intervention is a very effective method to control the spread of schistosomiasis.
An epidemic model with age structured of rubella virus: threshold and stability
Authors: Abadi  , Artiono Rudianto , Prawoto Budi Priyo 
Published: March 2021

Abstract
This study aimed to explore the dynamic behaviour of rubella virus model which considers age-structured. It was not only to figure out the stability analysis of the model but also the judgement of the result through numerical simulation. Firstly, we constructed model for the disease spread based on the characteristic of rubella virus. The basic model of the disease spread (SEIR) had been used as a fundamental model. In the beginning, human population have been divided into two age groups; children and adults. Furthermore, based on the characteristic of rubella, we separated each group into four sub populations, i.e., Susceptible, Exposed, Infected, and Recovered. The transmission routes of the disease were formulated mathematically based on the real problem. In the second step, two disease equilibrium points had been obtained. There were a disease-free equilibrium and an endemic equilibrium. Moreover, by using Next Generation Matrix method, the basic reproduction number also had been determined. Finally, stability analysis had been done to explore the persistence of the disease. This results also had been supported by the numerical simulation.
About the Creation of Sensor of New Firefighting, Devices Based on Nanostructures for Determination of Carbon Monoxide and Carbon Dioxide Components
Authors: Boroznin S V , Zaporotskova I V , Boroznina N P 
Published: March 2021

Abstract
The article is devoted to the study of methods of detecting CO2 molecules using boroncarbon nanotubes of type BC5. The article also compares the mechanisms of attachment of the molecule CO2 to the surface of the modified carboxyl group of the nanotube. The main method used in the work is the density functional theory (DFT) method within the B3LYP functional. As a result of the work, the most likely method of catching carbon dioxide molecules using boroncarbon nanotubes was established and the physicochemical characteristics of these phenomena were determined
Numerical Simulation of Stratified Values of the Vertical Gravity Gradient Generated by a Pair of Closely Spaced Isolated Inhomogeneities with Excessive Density
Authors: Chashchin O N , Podoinikov D A 
Published: March 2021

Abstract
In the article is presented a mathematical model and a computational algorithm for solving the inverse problem of gravity gradiometry – a problem of localization (separability) of a pair of gravitational inhomogeneities – isolated ore bodies (oil and gas domes) with excessive positive (negative) density based on the gravitational anomalies generated by them. Anomalies are empirical data for solving the inverse problem, which is relevant for geological exploration, monitoring and geophysical support of developed fields, as well as for practical problems of engineering geology.