bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailoring the optical properties of dilute nitride semiconductors at the nanometer scale
Authors: Pettinari Giorgio , Marotta Gianluca , Biccari Francesco , Polimeni Antonio , Felici Marco 
Published: January 2021

Abstract
We report on the innovative approaches we developed for the fabrication of site-controlled semiconductor nanostructures [e.g. quantum dots (QDs), nanowires], based on the spatially selective incorporation and/or removal of hydrogen in dilute nitride semiconductor alloys [e.g. Ga(AsN) and (InGa)(AsN)]. In such systems, the formation of stable nitrogen-hydrogen complexes removes the effects nitrogen has on the alloy properties, which in turn paves the way to the direct engineering of the material’s electronic—and, thus, optical—properties: not only the bandgap energy, but also the refractive index and the polarization properties of the system can indeed be tailored with high precision and in a reversible manner. Here, lithographic approaches and/or plasmon-assisted optical irradiation—coupled to the ultra-sharp diffusion profile of hydrogen in dilute nitrides—are employed to control the hydrogen implantation and/or removal process at a nanometer scale. This results in a highly deterministic control of the spatial and spectral properties of the fabricated nanostructures, eventually obtaining semiconductor nanowires with controlled polarization properties, as well as site-controlled QDs with an extremely high control on their spatial and spectral properties. The nanostructures fabricated with these techniques, whose optical properties have also been simulated by finite-element-method calculations, are naturally suited for a deterministic coupling in optical nanocavities (i.e. photonic crystal cavities and circular Bragg resonators) and are therefore of potential interest for emerging quantum technologies.
Regulating the core/shell electric structure of Co3O4@Ni–Co layered double hydroxide on Ni foam through electrodeposition for a quasi-solid-state supercapacitor
Authors: Zhang Yuqiang , Wang Yan , Zhu Jiahui , Zhang Xubin , Cai Wangfeng 
Published: January 2021

Abstract
A flower-like structured electrode material of Co3O4@Ni–Co layered double hydroxide (LDH) grown on Ni foam (Co3O4@Ni–Co LDH/NF) was prepared via an in situ growth, annealing and electrodeposition process. The Co3O4@Ni–Co LDH/NF electrode was prepared with the optimized conditions of annealing temperature 300 °C, deposition time 20 min and Ni/Co ratio 1:1. The results showed that the as-prepared electrode material exhibited an excellent specific capacitance and great cycling stability. Furthermore, an quasi-solid-state supercapacitor was assembled using the prepared Co3O4@Ni–Co LDH/NF as the positive electrode and activated carbon on Ni foam (AC/NF) as the negative electrode. The as-assembled device presented a high energy density and power density.
Termination points and homoclinic glueing for a class of inhomogeneous nonlinear ordinary differential equations
Authors: Keeler J S , Blyth M G , King J R 
Published: January 2021

Abstract
Solutions u(x) to the class of inhomogeneous nonlinear ordinary differential equations taking the form

u

″

+

u

2

=
α
f

(

x

)

for parameter α are studied. The problem is defined on the x line with decay of both the solution u(x) and the imposed forcing f(x) as |x| → ∞. The rate of decay of f(x) is important and has a strong influence on the structure of the solution space. Three particular forcings are examined primarily: a rectilinear top-hat, a Gaussian, and a Lorentzian, the latter two exhibiting exponential and algebraic decay, respectively, for large x. The problem for the top hat can be solved exactly, but for the Gaussian and the Lorentzian it must be computed numerically in general. Calculations suggest that an infinite number of solution branches exist in each case. For the top-hat and the Gaussian the solution branches terminate at a discrete set of α values starting from zero. A general asymptotic description of the solutions near to a termination point is constructed that also provides information on the existence of local fold behaviour. The solution branches for the Lorentzian forcing do not terminate in general. For large α the asymptotic analysis of Keeler, Binder and Blyth (2018 J. Fluid Mech.
832 73–96) is extended to describe the behaviour on any given solution branch using a method for glueing homoclinic connections.
Students’ understanding of gravity using the rubber sheet analogy: an Italian experience
Authors: Postiglione A , De Angelis I 
Published: January 2021

Abstract
General relativity (GR) represents the most recent theory of gravity, on which all modern astrophysics is based, including some of the most astonishing results of physics research. Nevertheless, its study is limited to university courses, while being ignored at high-school level. To introduce GR in high school, one of the approaches that can be used is the so-called rubber sheet analogy (RSA), i.e. comparing space-time to a rubber sheet that deforms under a weight. In this paper, we analyse the efficacy of an activity for high-school students held at the Department of Mathematics and Physics of Roma Tre University that adopts the RSA to address several topics related to gravity. We present the results of the questionnaires we administered to over 150 Italian high-school students to investigate their understanding of the topics treated.
Robust optimization for HDR prostate brachytherapy applied to organ reconstruction uncertainty
Authors: van der Meer Marjolein C , Bosman Peter A N , Niatsetski Yury , Alderliesten Tanja , Pieters Bradley R , Bel Arjan 
Published: January 2021

Abstract

Purpose. Recently, we introduced a bi-objective optimization approach based on dose-volume indices to automatically create clinically good HDR prostate brachytherapy plans. To calculate dose-volume indices, a reconstruction algorithm is used to determine the 3D organ shape from 2D contours, inevitably containing settings that influence the result. We augment the optimization approach to quickly find plans that are robust to differences in 3D reconstruction. Methods. Studied reconstruction settings were: interpolation between delineated organ contours, overlap between contours, and organ shape at the top and bottom contour. Two options for each setting yields 8 possible 3D organ reconstructions per patient, over which the robust model defines minimax optimization. For the original model, settings were based on our treatment planning system. Both models were tested on data of 26 patients and compared by re-evaluating selected optimized plans both in the original model (1 organ reconstruction, the difference determines the cost), and in the robust model (8 organ reconstructions, the difference determines the benefit). Results. Robust optimization increased the run time from 3 to 6 min. The median cost for robust optimization as observed in the original model was −0.25% in the dose-volume indices with a range of [−0.01%, −1.03%]. The median benefit of robust optimization as observed in the robust model was 0.93% with a range of [0.19%, 4.16%]. For 4 patients, selected plans that appeared good when optimized in the original model, violated the clinical protocol with more than 1% when considering different settings. This was not the case for robustly optimized plans. Conclusions. Plans of high quality, irrespective of 3D organ reconstruction settings, can be obtained using our robust optimization approach. With its limited effect on total runtime, our approach therefore offers a way to account for dosimetry uncertainties that result from choices in organ reconstruction settings that is viable in clinical practice.
A comparison of Monte Carlo dropout and bootstrap aggregation on the performance and uncertainty estimation in radiation therapy dose prediction with deep learning neural networks
Authors: Nguyen Dan , Sadeghnejad Barkousaraie Azar , Bohara Gyanendra , Balagopal Anjali , McBeth Rafe , Lin Mu-Han , Jiang Steve 
Published: January 2021

Abstract
Recently, artificial intelligence technologies and algorithms have become a major focus for advancements in treatment planning for radiation therapy. As these are starting to become incorporated into the clinical workflow, a major concern from clinicians is not whether the model is accurate, but whether the model can express to a human operator when it does not know if its answer is correct. We propose to use Monte Carlo Dropout (MCDO) and the bootstrap aggregation (bagging) technique on deep learning (DL) models to produce uncertainty estimations for radiation therapy dose prediction. We show that both models are capable of generating a reasonable uncertainty map, and, with our proposed scaling technique, creating interpretable uncertainties and bounds on the prediction and any relevant metrics. Performance-wise, bagging provides statistically significant reduced loss value and errors in most of the metrics investigated in this study. The addition of bagging was able to further reduce errors by another 0.34% for

D

m
e
a
n

and 0.19% for

D

max

,

on average, when compared to the baseline model. Overall, the bagging framework provided significantly lower mean absolute error (MAE) of 2.62, as opposed to the baseline model’s MAE of 2.87. The usefulness of bagging, from solely a performance standpoint, does highly depend on the problem and the acceptable predictive error, and its high upfront computational cost during training should be factored in to deciding whether it is advantageous to use it. In terms of deployment with uncertainty estimations turned on, both methods offer the same performance time of about 12 s. As an ensemble-based metaheuristic, bagging can be used with existing machine learning architectures to improve stability and performance, and MCDO can be applied to any DL models that have dropout as part of their architecture.
An end-to-end assessment on the accuracy of adaptive radiotherapy in an MR-linac
Authors: Axford A , Dikaios N , Roberts D A , Clark C H , Evans P M 
Published: January 2021

Abstract

Purpose. To develop and demonstrate an end-to-end assessment procedure for adaptive radiotherapy (ART) within an MR-guided system. Methods and materials. A 3D printed pelvic phantom was designed and constructed for use in this study. The phantom was put through the complete radiotherapy treatment chain, with planned internal changes made to model prostate translations and shape changes, allowing an investigation into three ART techniques commonly used. Absolute dosimetry measurements were made within the phantom using both gafchromic film and alanine. Comparisons between treatment planning system (TPS) calculations and measured dose values were made using the gamma evaluation with criteria of 3 mm/3% and 2 mm/2%. Results. Gamma analysis evaluations for each type of treatment plan adaptation investigated showed a very high agreement with pass rates for each experiment ranging from 98.10% to 99.70% and 92.60% to 97.55%, for criteria of 3%/3 mm and 2%/2 mm respectively. These pass rates were consistent for both shape and position changes. Alanine measurements further supported the results, showing an average difference of 1.98% from the TPS. Conclusion. The end-to-end assessment procedure provided demanding challenges for treatment plan adaptations to demonstrate the capabilities and achieved high consistency in all findings.
Wakefield decay in a radially bounded plasma due to formation of electron halo
Authors: Spitsyn R I , Lotov K V 
Published: January 2021

Abstract
There is a new effect that can limit the lifetime of a weakly non-linear wakefield in a radially bounded plasma. If the drive beam is narrow, some of the plasma electrons fall out of the collective motion and leave the plasma radially, forming a negatively charged halo around it. These electrons repeatedly return to the plasma under the action of the charge separation field, interact with the plasma wave and cause its damping. The lowest-energy halo electrons take the energy from the wave more efficiently, because their trajectories are bent by the plasma wave towards the regions of the strongest acceleration. For correct accounting of the wave damping in simulations, it is necessary to take the simulation window at least twice as wide as the plasma.
Dim and bright void regimes in capacitively-coupled RF complex plasmas
Authors: Pikalev A , Semenov I , Pustylnik M , Räth C , Thomas H 
Published: January 2021

Abstract
We demonstrate experimentally that the void in capacitively-coupled RF complex plasmas can exist in two qualitatively different regimes. The ‘bright’ void is characterized by bright plasma emission associated with the void, whereas the ‘dim’ void possesses no detectable emission feature. The transition from the dim to the bright regime occurs with an increase of the discharge power and has a discontinuous character. The discontinuity is manifested by a kink in the void size power dependencies. We reproduce the bright void (mechanically stabilized due to the balance of ion drag and electrostatic forces) by a simplified time-averaged 1D fluid model. To reproduce the dim void, we artificially include the radial ion diffusion into the continuity equation for ions, which allows to mechanically stabilize the void boundary due to very weak electrostatic forces. The electric field at the void boundary occurs to be so small that it, in accordance with the experimental observation, causes no void-related emission feature.
Computational intelligence of Levenberg-Marquardt backpropagation neural networks to study the dynamics of expanding/contracting cylinder for Cross magneto-nanofluid flow model
Authors: Shah Z , Raja M A Z , Chu Yu-Ming , A Khan W , Abbas S Z , Shoaib M , Irfan M 
Published: January 2021

Abstract
In the present investigation, design of integrated numerical computing through Levenberg-Marquardt backpropagation neural network (LMBNN) is presented to examine the fluid mechanics problems governing the dynamics of expanding and contracting cylinder for Cross magneto-nanofluid flow (ECCCMNF) model in the presence of time dependent non-uniform magnetic force and permeability of the cylinder. The original system model ECCCMNF in terms of PDEs is converted to nonlinear ODEs by introducing the similarity transformations. Reference dataset of the designed LMBNN methodology is formulated with Adam numerical technique for scenarios of ECCCMNF by variation of thermophoresis temperature ratio parameter, Brownian motion, suction parameters as well as Schmidt, Prandtl, local Weissenberg and Biot numbers. To calculate the approximate solution for ECCCMNF for different scenarios, the training, testing, and validation processes are conducted in parallel to adapt neural network by reducing the mean square error (MSE) function through Levenberg-Marquardt backpropagation. The comparative studies and performance analyses based on outcomes of MSE, error histograms, correlation and regression demonstrate the effectiveness of designed LMBNN technique.
Fabrication of a green and sensitive quantum dots based fluorescent probe for determination of sparfloxacin in biological samples and drug formulations
Authors: Muhammad Mian , Ara Behisht , Ali Faiz , Ullah Ikram 
Published: January 2021

Abstract
A simple and fast spectrofluorimetric method for determination of sparfloxacin (SPAR) based on fluorescence quenching of colloidal water soluble TGA caped, Mn doped ZnS quantum dots (QDs) has been described. The QDs having characteristic fluorescence spectra with maximum emission at 632 nm (Excitation at 315 nm) were characterized using Energy Dispersive x-ray and x-ray Diffraction techniques. The effect of various parameters such as concentration of QDs, time, pH, common excipients and metal ions on the quenching phenomenon was investigated. Fluorescence quenching was found to be maximum with 10 μg ml−1 of QDs at pH 7 with fluorescence intensity remaining constant upto 60 min. The Stern-Volmer calibration plot of F0/F as a function of sparfloxacin concentration was found to be linear in the range of 0.2–2.2 μg ml−1 with r2 = 0.995. Under optimal experimental conditions the method was found to be interference free. The percent relative standard deviation of the proposed method calculated against method blank was found to be 1.67%. The limit of detection and the limit of quantitation for SPAR (n = 3 and 10 respectively) were calculated to be 0.07 and 0.21 μg ml−1 respectively. Average percent recoveries (±SD) obtained were found to be 89.16 ± 0.03 to 94.44 ± 0.15 μg ml−1 for serum and 85.00 ± 0.10 to 97.77 ± 0.37 μg ml−1 for urine samples. In case of commercial formulations sparaxcin and spar, the maximum % recovery was found to 89.33 ± 0.54% while in case of Quspar the % recovery obtained was less than 71.83 ± 0.14%. The proposed method was statistically compared with reported chromatographic method and no significant difference was observed.
DBS electrode localization and rotational orientation detection using SQUID-based magnetoencephalography
Authors: Yalaz Mevlüt , Sohail Noor M , McIntyre Cameron C , Butz Markus , Schnitzler Alfons , Deuschl Günther , Höft Michael 
Published: January 2021

Abstract

Objective. The aim of the present study was to investigate the accuracy of localization and rotational orientation detection of a directional deep brain stimulation (DBS) electrode using a state-of-the-art magnetoencephalography (MEG) scanner. Approach. A directional DBS electrode along with its stimulator was integrated into a head phantom and placed inside the MEG sensor array. The electrode was comprised of six directional and two omnidirectional contacts. Measurements were performed while stimulating with different contacts and parameters in the phantom. Finite element modeling and fitting approach were used to compute electrode position and orientation. Main results. The electrode was localized with a mean accuracy of 2.2 mm while orientation was determined with a mean accuracy of 11∘. The limitation in detection accuracy was due to the lower measurement precision of the MEG system. Considering an ideal measurement condition, these values represent the lower bound of accuracy that can be achieved in patients. Significance. However, a future magnetic measuring system with higher precision will potentially detect location and orientation of a DBS electrode with an even greater accuracy.
Development of the Learning Instruction Based on Problem Based Learning Models Oriented with Mitigation of Mount Eruption and Lava Floods on the Mathematical Reasoning Ability of Class VIII Students of SMP / MTs
Authors: Badri R , Yerizon  
Published: January 2021

Abstract
During 2019, the National Disaster Management Agency (BNPB) noted that there had been 3622 disasters in Indonesia, one of which was natural disasters such as volcanic eruptions and cold lava floods. In terms of volcanoes, Indonesia is the most active volcanoes location in the world and it have many tectonic plates that have the potential to cause volcanic eruptions, tsunamis, and earthquakes. Therefore, the Indonesia Government recommends providing education on natural disaster mitigation in schools. The goal of this study was to determine the mathematical reasoning abilities of students and the knowledge and attitudes of students towards mitigating natural disasters. This research is a development research, the development model used in this research is the Plomp model which consists of three phases, namely preliminary research, prototyping phase, and assessment phase. The instruments used during the research were observation sheets, interview guides, questionnaires, validation sheets for learning devices, and tests of students' mathematical reasoning abilities. From this research, it is proven that about 71.4% of MTsN 6 Agam students stated that there has been no learning about natural disaster mitigation. Based on the results of the mathematical reasoning ability test, there was an increase to 72.7% from the initial test result of 25.47%. Natural disaster mitigation knowledge does not have to be provided to students in specific subjects, but can be integrated into existing subjects, one of which is mathematics.
The Development of Geometrical Learning Devices Based On Rumah Gadang Ethnomathematics for Grade VII Junior High School
Authors: Setiawan H , Fauzan A , Arnawa I M 
Published: January 2021

Abstract
Based on the observations, interviews and preliminary analysis conducted in several schools, it showed that the learning devices used so far have not been linked to the culture around the students. Besides, the students’ learning outcomes were also still low. This was caused by (1) the learning resources that were still general in nature and not yet associated with the students' daily lives, (2) the student worksheet (LKPD) used so far did not contain sufficient activities for learning mathematics, (3) the LKPD contained problems that were difficult for the students to imagine, and (4) the activities in the lesson plan did not show the activities that lead the students to be active and can find their own mathematical concepts. Based on these problems, the researcher developed the Rumah Gadang ethnomathemic-based geometrical learning devices in form of lesson plan (RPP) and LKPD. This study was a research and development conducted with the Plomp development model. The result of the study show that RPP and LKP was valid and practical.
The Development of Mathematics Learning Devices Based On Problem Based Learning and Geogebra-Assisted for Junior High School Students
Authors: Priyatno N , Arnawa I M , Bakar N N 
Published: January 2021

Abstract
Based on observations, interviews, and preliminary analysis conducted, it showed that students' mathematical problem-solving skills were still not satisfying. This was caused by the teaching materials used by teachers in teaching have not helped students a lot in understanding mathematical concepts and properties. Based on these problems, the main objective of this research is to produce a practical mathematics learning devices in the form of RPP and LKPD for junior high school students based on problem based learning (PBL) and geogbra-assisted. This study was research and development (R&D) conducted with the Plomp development model. The subjects of this study were the student's grade viii SMP Negeri 25 Padang. Based on the R & D that has been carried out, it obtained that the learning devices (RPP and LKPD) were valid and practical.
The Effect of Blended Learning on Student Learning Outcomes in Calculus Vector Course
Authors: Tasman F , Ahmad D , Rifandi R , Sari W W 
Published: January 2021

Abstract
Rapid development of technology has become an inseparable part of life. This poses a challenge for the world of education to be able to take advantage of technological developments in achieving educational goals. However, switching from a direct learning model to technology-based learning requires a lot of effort and money. However, this can be started with the Blended Learning Model. This study aims to analyse whether student learning outcomes are better with the application of Blended Learning using e-learning and to describe how student learning activities with the Blended Learning model. This type of research is a combination of quasy-experiment and descriptive research. The research data are the value of the midterm exam and the final semester test scores after the implementation of the learning Blended Learning model which will be analysed. Therefore, it can be compared students’ learning outcomes using the Blended Learning model with student learning outcomes with the conventional learning model. Based on the results of data analysis, it can be concluded that the N-gain test results obtained from the control class are better than the experimental class, which means that the use of the Blended Learning model is less effective in improving student learning outcomes in vector calculus subjects.