bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computed tomography with view angle estimation using uncertainty quantification
Authors: Brogaard Riis Nicolai André , Dong Yiqiu , Hansen Per Christian 
Published: April 2021

Abstract
We consider computed tomography (CT) with uncertain measurement geometry, with a focus on the case where the view angles are uncertain and where estimation of these angles improves the reconstruction. We propose a new reconstruction model and a corresponding algorithm that has an additional view-angle estimation component, allowing us to determine the angles solely from the measured CT data. A key component of our approach is that we quantify the uncertainty of the view angles via a model-discrepancy formulation, allowing us to take the uncertainty into account in the image reconstruction. This approach generalizes in a straightforward way to other cases of uncertain geometry. Our method is computationally efficient since we can utilize a block-structure of the computational problem for estimation of both the CT image and the view angles under the assumption that the view angles are independent. The joint image/angle reconstruction problem is non-convex which leads to difficulties in recently proposed algorithms, and we demonstrate numerically that our method seems to avoid these difficulties. Simulations show that our method, with a total variation prior that reflects our phantoms, is able to achieve reconstructions whose quality is similar to ones obtained with the correct view angles (the ideal scenario).
Applicability of optical emission spectroscopy techniques for characterization of Ar and Ar/O2 discharges
Authors: Nikolić M , Sepulveda I , Gonzalez C , Khogeer N , Fernandez-Monteith M 
Published: April 2021

Abstract
Here we explore the accuracy and applicability of two readily—available, low cost techniques: (a) a branching fraction method and (b) an extended corona method (ECM). A three dimensional Monte Carlo simulation was developed to obtain the electron energy distribution function, a necessary parameter in the extended corona model, and we discuss its dependence on oxygen percentage and discharge pressure. The experiment was conducted with a 13.56 MHz radio-frequency capacitive discharge in Ar and Ar with 10% and 20% O2. Absolute densities of argon resonant 1 s4 and metastable 1 s5 energy levels were calculated at various pressures, powers, and positions inside the resulting plasma using both methods. The ECM was also used for calculation of electron temperature and electron density under the same plasma parameters. Results showed that in pure argon, both methods present a good, inexpensive choice for plasma characterization.
Application of machine learning for the estimation of electron energy distribution from optical emission spectra
Authors: Shojaei Kamran , Mangolini Lorenzo 
Published: April 2021

Abstract
This paper discusses the use of probabilistic deep neural networks for the prediction of the electron energy probability function in low-temperature non-thermal plasmas. The neural networks are trained using optical emission spectroscopy and Langmuir probe measurements, with the goal of providing a reliable estimate of the electron energy probability function solely from optical emission data. The performance of both non-Bayesian and Bayesian networks is evaluated. It is found that Bayesian models are preferable as they assign a higher level of uncertainty to their prediction especially when the dataset used to train them is small. This work describes one of the many potential applications of machine learning in plasma science and technology.
Temporal dynamics of femtosecond-TALIF of atomic hydrogen and oxygen in a nanosecond repetitively pulsed discharge-assisted methane–air flame
Authors: Ding Pengji , Ruchkina Maria , Del Cont-Bernard Davide , Ehn Andreas , Lacoste Deanna A , Bood Joakim 
Published: April 2021

Abstract
The temporal dynamics of the spatial distribution of atomic hydrogen and oxygen in a lean methane–air flame, forced by a nanosecond repetitively pulsed discharge-induced plasma, are investigated via femtosecond two-photon absorption laser-induced fluorescence technique. Plasma luminescence that interferes with the fluorescence from H and O atoms was observed to decay completely within 15 ns, which is the minimum delay required for imaging measurements with respect to the discharge occurrence. During discharge, H atoms in the excited state rather than the ground state, produced by electron-impact dissociation processes, are detected at the flame front. It was found that the temporal evolution of H and O fluorescence intensity during a cycle of 100 µs between two discharge pulses remains constant. Finally, the decay time of O-atoms produced by the discharge in the fresh methane–air mixture was about 2 µs, which suggests a faster reaction between O-atoms and methane than in air.
Bonding few-layered graphene via collision with high-speed fullerenes
Authors: Shi Jiao , Hu Chunwei , Sun Sreykeo , Song Bo , Qin Qing-Hua 
Published: April 2021

Abstract
Graphene, as a typical two-dimensional material, is popular in the design of nanodevices. The interlayer relative sliding of graphene sheets can significantly affect the effective bending stiffness of the few-layered graphene. For restricting the relative sliding, we adopted the atomic shot peening method to bond the graphene sheets together by ballistic C60 fullerenes from its two surfaces. Collision effects are evaluated via molecular dynamics simulations. Results obtained indicate that the fullerenes’ incident velocity has an interval, in which the graphene sheet can be bonded after collision while no atoms on the fullerenes escaping from the graphene ribbon after collision. The limits of the interval increase with the layer number. Within a few picoseconds of collision, a stable carbon network is produced at an impacted area. The graphene sheets are bonded via the network and cannot slide relatively anymore. Conclusions are drawn to show the way of potential applications of the method in manufacturing a new graphene-based two-dimensional material that has a high out-of-plane bending stiffness.
Flexible fiber-shaped supercapacitors based on graphene/polyaniline hybrid fibers with high energy density and capacitance
Authors: Wu Yuntao , Meng Zijie , Yang Junhe , Xue Yuhua 
Published: April 2021

Abstract
Fiber-shaped supercapacitors (FSCs) are promising energy storage devices for portable and wearable electronics due to their miniaturized size, flexibility, and knittability. Despite the significant progress in this area, it is still a challenge to develop large capacitance and high energy density FSCs for practical applications. In this work, a hybrid fiber composed of reduced graphene oxide and polyaniline nanoparticles (r-PANI-GOF) is synthesized via in situ synthesis of polyaniline nanoparticles both on the surface and inside of graphene fibers. The areal specific capacitance of a single r-PANI-GOF electrode is as large as 1755 mF cm−2 in the three-electrode system. The r-PANI-GOF hybrid fibers were also used as electrodes for making an all-solid-state FSCs. This whole device has a specific areal capacitance of up to 481 mF cm−2 and a high areal energy density of 42.76 μWh cm−2. The hybrid fiber electrodes with a high capacitance, and excellent flexibility may become new candidates for the development of fiber-shaped high-performance energy storage devices.
Brachytherapy treatment verification using gamma radiation from the internal treatment source combined with an imaging panel—a phantom study
Authors: Fonseca G P , van Wagenberg T , Voncken R , Podesta M , van Beveren C , van Limbergen E , Lutgens L , Vanneste B , Berbee M , Reniers B , Verhaegen F 
Published: April 2021

Abstract
Brachytherapy has an excellent clinical outcome for different treatment sites. However, in vivo treatment verification is not performed in the majority of hospitals due to the lack of proper monitoring systems. This study investigates the use of an imaging panel (IP) and the photons emitted by a high dose rate (HDR) 192Ir source to track source motion and obtain some information related to the patient anatomy. The feasibility of this approach was studied by monitoring the treatment delivery to a 3D printed phantom that mimicks a prostate patient. A 3D printed phantom was designed with a template for needle insertion, a cavity (‘rectum’) to insert an ultrasound probe, and lateral cavities used to place tissue-equivalent materials. CT images were acquired to create HDR 192Ir treatment plans with a range of dwell times, interdwell distances and needle arrangements. Treatment delivery was verified with an IP placed at several positions around the phantom using radiopaque markers on the outer surface to register acquired IP images with the planning CT. All dwell positions were identified using acquisition times ≤0.11 s (frame rates ≥ 9 fps). Interdwell distances and dwell positions (in relation to the IP) were verified with accuracy better than 0.1 cm. Radiopaque markers were visible in the acquired images and could be used for registration with CT images. Uncertainties for image registration (IP and planning CT) between 0.1 and 0.4 cm. The IP is sensitive to tissue-mimicking insert composition and showed phantom boundaries that could be used to improve treatment verification. The IP provided sufficient time and spatial resolution for real-time source tracking and allows for the registration of the planning CT and IP images. The results obtained in this study indicate that several treatment errors could be detected including swapped catheters, incorrect dwell times and dwell positions.
RF shielding materials for highly-integrated PET/MRI systems
Authors: Yin Laiyin , Schrank Franziska , Gross-Weege Nicolas , Schug David , Schulz Volkmar 
Published: April 2021

Abstract
Integration of magnetic resonance imaging (MRI) and positron emission tomography (PET) into a simultaneous device calls for adaptations of the radio frequency (RF) shielding concept. Conventional PET module housings fully encase the entire PET detector to reduce mutual interference. Excluding passive components, i.e. scintillators, from the housings, offers integration advantages, e.g. by reducing the overall housing volume or utilizing bigger scintillators. However, locating the scintillator outside of the RF shielding requires an optically transparent RF shielding interface between the scintillators and the photodetector to close the aperture. Therefore, a careful evaluation and selection of RF materials is essential to ensure an excellent PET/MRI system performance. To this end, we examined 10 materials (coated glasses, coated foils, meshes). The shielding effectiveness (SE) was evaluated at 100 and 300 MHz. PET performance was tested for single event registration and coincident events by integrating the material into the PET detector stack between the digital silicon photomultiplier photodetector array and one-to-one coupled scintillator. We determined photon attenuation (PA), energy resolution (dE/E), and coincidence resolving time (CRT) and compared to reference measurements for each material group. MRI compatibility was assessed by analyzing the material influence on the main magnetic field (B0) homogeneity. The coated glasses and foils exhibited SEs of up to 25 dB at 300 MHz. Both had a PA < 23% with dE/E and CRT comparable to the reference measurements, and no measurable impact on the B0 field was registered. The meshes exhibited higher SEs up to 56 dB, but also a PA > 58% with a higher impact on dE/E and CRT. Only one mesh affected B0 homogeneity. Overall, we recommend the coated foil HS 9400 for integration concepts as it exhibited a good performance with SE = 25 dB, PA = 22%, resulting in a PET performance of dE/E = 12% and CRT = 274 ps.
Living magnetorheological composites: from the synthesis to the in vitro characterization
Authors: Nardecchia Stefania , Chocarro-Wrona Carlos , Sánchez-Moreno Paola , Zambrano-Marín José Rafael , Marchal Juan Antonio , de Vicente Juan 
Published: April 2021

Abstract
A new type of magnetorheological (MR) material is reported that brings together conventional MR composites (MRCs) and biomaterials. Living MRCs based on carbonyl iron microparticles (CIPs) as magnetoactive filler, sodium alginate as elastomer and cells as biological components were prepared and characterized. The effect of CIPs concentration in isotropic alginate composites was examined by using thermogravimetric analysis, infrared spectroscopy, swelling and degradation tests in culture medium (Dulbecco’s Modified Eagle’s Medium, DMEM). To self-assemble the CIPs within the polymer matrix, the cross-linking process took place under an external magnetic field (24 mT). The cytotoxicity experiments were performed with human mesenchymal stem cells and human fibroblasts loaded inside of the hydrogel. It was demonstrated that the living MRCs supported cell survival and proliferation. The rheological response of the MRCs was evaluated in dynamic oscillatory tests in the absence and presence of magnetic fields. The viscoelastic response of the living MRCs improved when a magnetic field was applied. This work demonstrates the possibility to use CIPs in the fabrication of living composites with MR response. Results could be of interest in smart biomedical applications.
Trapping a magnetic field of 14.8 T using stacked coated conductors of 12 mm width
Authors: Suyama Masahiro , Pyon Sunseng , Iijima Yasuhiro , Awaji Satoshi , Tamegai Tsuyoshi 
Published: April 2021

Abstract
We fabricated a compact (13

×

12

×

12.5 mm3) trapped-field magnet by stacking 200 pieces of EuBa2Cu3O7 coated conductors (CCs) with BaHfO3 nanorods as artificial pinning centers. It was magnetized by field-cooling method using a 18 T superconducting magnet, and the maximum field of 14.8 T was trapped at 10 K at a field-ramp rate of 0.1 T min−1. At higher temperatures, although the trapped field was decreased, we could trap the field with much faster ramp rate. In order to understand these results, we also performed calculations of the trapped field based on

J

c

−
H

characteristics of the CC. The calculated trapped field value was larger than the experimental value at 10 K. This discrepancy can be understood by considering the reduction of the effective size of the stacked CCs due to the existence of extended regions of irregular flux penetration called ‘flux jets’.
Cascaded generation of isolated sub-10 attosecond half-cycle pulses
Authors: Shou Yinren , Hu Ronghao , Gong Zheng , Yu Jinqing , Chen Jia erh , Mourou Gerard , Yan Xueqing , Ma Wenjun 
Published: April 2021

Abstract
Sub-10 attosecond pulses (APs) with half-cycle electric fields provide exceptional options to detect and manipulate electrons in the atomic timescale. However, the availability of such pulses is still challenging. Here, we propose a method to generate isolated sub-10 attosecond half-cycle pulses based on a cascade process naturally happening in plasma. A backward AP is first generated by shooting a moderate overdense plasma with a one-cycle femtosecond pulse. After that, an electron sheet with the thickness of several nanometers is formed and accelerated forward by the electrostatic field. Then this electron sheet goes through unipolar perturbations driven by the tail of the first-stage AP instead of the initial laser pulse. As a result, a half-cycle sub-10 AP is cascadedly produced in the transmission direction. Two-dimensional particle-in-cell simulations indicate that an isolated half-cycle pulse with the duration of 7.3 attoseconds can be generated from the cascaded scheme. Apart from a one-cycle driving pulse, such a scheme also can be realized with a commercial 100 TW 25 fs driving laser by shaping the pulse with a relativistic plasma lens in advance.
Twisted light-induced spin–spin interaction in a chiral helimagnet
Authors: Goto Yutaro , Ishihara Hajime , Yokoshi Nobuhiko 
Published: April 2021

Abstract
We theoretically investigate how the orbital angular momentum of light can affect a chiral magnetic order. Here, we consider a metallic chiral helimagnet, which is under stationary radiation of a resonant optical vortex beam. We propose a novel interaction between local spins considering microscopic interactions between an optical vortex and electrons. This vortex-induced interaction modulates the chiral magnetic order in an entirely different way than an external magnetic field does. Our spin modulation technique may pave a route to create a unique topological or chiral structure for future opto-spintronics devices.
Bi-state switch based on two-dimensional guided-mode resonance
Authors: Taheri Atefe , Shokooh-Saremi Mehrdad 
Published: April 2021

Abstract
In this paper, a bi-state (on/off) switch is proposed utilizing a two-dimensional, all-dielectric periodic guided-mode resonance (GMR) structure. Employing a conceptual MEMS mechanism, switching is performed by modifying the Fourier series coefficients of the refractive index distribution. This switch operates in the visible region. In the ‘on’ state, the switch exhibits a narrow linewidth reflection resonance at λ = 541 nm; this resonance disappears in the ‘off’ state. In fact, in the ‘off’ state, the condition for supporting a GMR is lost. This element exhibits a reversible switching action and can be a potential candidate for narrowband optical switches, light modulators, and laser systems.
Factorization of radiative leptonic D-meson decay with sub-leading power corrections *
Authors: Lu Long-Sheng 
Published: April 2021

Abstract
In this work, we calculate the sub-leading power contributions to radiative leptonic

decay. For the first time, we provide the analytic expressions of next-to-leading power contributions and the error estimation associated with the power expansion of

. In our calculation, we adopt two different models of the D-meson distribution amplitudes

and

. Within the framework of QCD factorization as well as the dispersion relation, we evaluate the soft contribution up to the next-to-leading logarithmic accuracy and also consider the higher-twist contribution from the two-particle and three-particle distribution amplitudes. Finally, we find that all the sub-leading power contributions are significant at

MeV, and the next-to-leading power contributions lead to 143% in

and 120% in

corrections to leading power vector form factors with

GeV. As the corrections from the higher-twist and local sub-leading power contributions are enhanced with increasing inverse moment, it is difficult to extract an appropriate inverse moment of the D-meson distribution amplitude. The predicted branching fractions are

for

and

for

.
Compliant peripheral nerve interfaces
Authors: Paggi Valentina , Akouissi Outman , Micera Silvestro , Lacour Stéphanie P 
Published: April 2021

Abstract
Peripheral nerve interfaces (PNIs) record and/or modulate neural activity of nerves, which are responsible for conducting sensory-motor information to and from the central nervous system, and for regulating the activity of inner organs. PNIs are used both in neuroscience research and in therapeutical applications such as precise closed-loop control of neuroprosthetic limbs, treatment of neuropathic pain and restoration of vital functions (e.g. breathing and bladder management). Implantable interfaces represent an attractive solution to directly access peripheral nerves and provide enhanced selectivity both in recording and in stimulation, compared to their non-invasive counterparts. Nevertheless, the long-term functionality of implantable PNIs is limited by tissue damage, which occurs at the implant–tissue interface, and is thus highly dependent on material properties, biocompatibility and implant design. Current research focuses on the development of mechanically compliant PNIs, which adapt to the anatomy and dynamic movements of nerves in the body thereby limiting foreign body response. In this paper, we review recent progress in the development of flexible and implantable PNIs, highlighting promising solutions related to materials selection and their associated fabrication methods, and integrated functions. We report on the variety of available interface designs (intraneural, extraneural and regenerative) and different modulation techniques (electrical, optical, chemical) emphasizing the main challenges associated with integrating such systems on compliant substrates.
Driver Distraction Detection and Early Prediction and avoidance of accidents using Convolutional Neural Networks
Authors: Christy A. , Shyry Prayla , Meera Gandhi G. , Anto Praveena M.D. 
Published: April 2021

Abstract
In this fast-moving world, accidents in four wheeled vehicles occur due to the break failure or because of the carelessness or the fatigue of the driver. The driver pattern of the driver plays a major role in providing road safety as well as in fuel consumption. The distraction of drivers is found by installing various sensors which is used for gathering real time data. The behaviour of drivers under stress condition and their behavioural patterns for early detection and avoidance of accidents are found using convolutional neural networks. Convolutional Neural Networks are efficient classifiers in handling image processing and computer vision problem. The input dataset is a collection of driving behaviour of 10 different drivers collected from Kaggle. The behaviour of drivers under 7 distracted situations like texting, talking through phone, playing music, drinking, eating, doing make up and talking to passenger are considered. The batch normalization is used at the right of the input layer in order to avoid skewing of data at a direction. It is shown, the convolutional neural networks at 4 epochs have shown 99% accuracy.
Detecting Cardiac Arrest Based on Image Processing
Authors: Muthamreddy Veeranna Chowdary , Viji Amutha Mary A , Selvan Mercy Paul , Jancy  
Published: April 2021

Abstract
In the world, about 21 percent of death occurs in the age group of 28-72 years because of a cardiac arrest. Many people among us lose their life because of heart-attack. After the occurrence of heart-attack only, the patient can be monitored. To help our society from heart-attack, I am developing a system that helps to decrease the death rate and early detection of a heart attack. Thus, this system is used to save the life of many people. We detect the prior occurrence of heart-attack of a patient using their monitored lungs datasets using image processing along with IoT.
Research on Cosine Similarity and Pearson Correlation Based Recommendation Models
Authors: Mana Suja Cherukullapurath , Sasipraba T. 
Published: April 2021

Abstract
Recommendation models are based on data mining and machine learning techniques to suggest product and services to users. Advancement in the machine learning field results in the growth of more efficient recommendation models. Recommendation systems can contribute a lot to increase the business of internet based companies. Techniques for making recommendations generally fall into two categories namely collaborative filtering based models and content based recommendation models. The first techniques explores similarity based approaches like cosine similarity, Pearson correlation similarity etc. The second approaches uses predictions based on explicit and implicit ratings given by users. Recommendation systems try to suggest products to the users based on their previous purchases or general nature. A successful recommendation system is capable of improving the product sales to a large extend. This paper reviews about various recommendation models and performs a comparison of these models.