bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variational embedding of protein folding simulations using Gaussian mixture variational autoencoders
Authors: Ghorbani Mahdi , Prasad Samarjeet , Klauda Jeffery B. , Brooks Bernard R. 
Published: October 2021

Conformational sampling of biomolecules using molecular dynamics simulations often produces a large amount of high dimensional data that makes it difficult to interpret using conventional analysis techniques. Dimensionality reduction methods are thus required to extract useful and relevant information. Here, we devise a machine learning method, Gaussian mixture variational autoencoder (GMVAE), that can simultaneously perform dimensionality reduction and clustering of biomolecular conformations in an unsupervised way. We show that GMVAE can learn a reduced representation of the free energy landscape of protein folding with highly separated clusters that correspond to the metastable states during folding. Since GMVAE uses a mixture of Gaussians as its prior, it can directly acknowledge the multi-basin nature of the protein folding free energy landscape. To make the model end-to-end differentiable, we use a Gumbel-softmax distribution. We test the model on three long-timescale protein folding trajectories and show that GMVAE embedding resembles the folding funnel with folded states down the funnel and unfolded states outside the funnel path. Additionally, we show that the latent space of GMVAE can be used for kinetic analysis and Markov state models built on this embedding produce folding and unfolding timescales that are in close agreement with other rigorous dynamical embeddings such as time independent component analysis.
The ratio of heart rate to heart rate variability reflects sympathetic activity during incremental cycling exercise
Authors: Tanoue Yukiya , Komatsu Tomohiro , Nakashima Shihoko , Matsuda Takuro , Michishita Ryoma , Higaki Yasuki , Uehara Yoshinari 
Published: October 2021

ABSTRACTA low‐frequency to a high‐frequency component ratio (LF/HF) in heart rate variability (HRV) may not accurately reflect sympathetic nervous activity during exercise. Thus, a valid HRV‐based index of sympathetic nervous activity is needed. Therefore, the heart rate to LF ratio (Heart rate/LF) was evaluated as sympathetic nervous activity index which is reflected by catecholamine levels during incremental exercise. In this study, 15 healthy adults performed an incremental exercise test using a cycle ergometer. HRV was derived from electrocardiography and HRV components related to the autonomic nervous system were obtained using frequency analysis. Heart rate/LF was calculated using the heart rate and LF component produced by HRV analysis. Catecholamine, blood lactate levels and respiratory gas were also measured throughout the exercise test. While LF/HF did not increase with increasing exercise intensity, Heart rate/LF non‐linearly increased during the incremental exercise test, as did noradrenaline and blood lactate. Interestingly, Heart rate/LF values were positively correlated with noradrenaline (ρ = 0.788, p < 0.05) and blood lactate (ρ = 0.802, p < 0.05) levels and carbon dioxide production (ρ = 0.903, p < 0.05) from at rest through the exercise stages. Heart rate/LF reflects sympathetic nervous activity and metabolic responses during incremental cycling exercise and has potential as an HRV index of sympathetic nervous activity during exercise.Trial registration: UMIN Japan identifier: UMIN000039639.
NRPyCritCol & SFcollapse1D: an open-source, user-friendly toolkit to study critical phenomena
Authors: Werneck Leonardo R , Etienne Zachariah B , Abdalla Elcio , Cuadros-Melgar Bertha , Pellicer CE 
Published: October 2021

Abstract
We present a new open-source, user-friendly toolkit of two codes—SFcollapse1D and NRPyCritCol—to study critical phenomena in the context of gravitational collapse. SFcollapse1D is a C/C++ tool designed to solve the problem of gravitational collapse of massless, spherically symmetric scalar fields with the ADM formalism in spherical-like coordinates. NRPyCritCol is a collection of Python modules that leverage the NRPy+ infrastructure to generate a highly optimized C-code for evolving massless scalar fields within a covariant BSSN formalism. The toolkit was developed with user-friendliness and code efficiency in mind, enabling the exploration of critical phenomena with consumer-grade computers. We present a study of critical phenomena from the collapse of massless scalar fields in spherical symmetry, using only these two codes and a laptop computer.
Carroll limit of four-dimensional gravity theories in the first order formalism
Authors: Guerrieri Amanda , Sobreiro Rodrigo F 
Published: October 2021

Abstract
We explore the ultra-relativistic (UR) limit of a class of four dimensional gravity theories, known as Lovelock–Cartan (LC) gravities, in the first order formalism. First, we review the well known limit of the Einstein–Hilbert (EH) action. A very useful scale symmetry involving the vierbeins and the boost connection is presented. Moreover, we explore the field equations in order to find formal solutions. Some remarkable results are obtained: Riemann and Weitzenböck like manifolds are discussed; Birkhoff’s theorem is verified for the torsionless case; an explicit solution with non-trivial geometry is discussed; a quite general solution in the presence of matter is obtained. Latter, we consider the UR limit of the more general LC gravity. The previously scale symmetry is also discussed. The field equations are studied in vacuum and in the presence of matter. In comparison with the EH case, a few relevant results are found: Birkhoff’s theorem is also verified for the torsionless case; a quite general solution in the presence of matter is obtained. This solution generalizes the previous case; Riemann and Weitzenböck like manifolds are derived in the same lines of the EH case.
Electromotive force (emf) for the confused
Authors: Ho Timothy , Toh Dylan , Ricardo Bernard 
Published: October 2021

Abstract
The electromotive force (emf) is a topic that is introduced in high school and undergraduate physics courses, but the numerous expressions for this quantity in different scenarios often lead to confusion among students. In addition, emf and potential difference are often treated as the same concept when being taught to students, and several misconceptions may arise from not distinguishing between the two. This paper aims to demonstrate the difference between the two quantities from their definitions and through the use of several examples, including the conceptual challenges when it comes to voltmeter measurements. This is expected to be of great interest to educators and students alike, as proper teaching of the topic will allow students to have a more thorough understanding of the effects of electromagnetic fields.
Approximation error method for imaging the human head by electrical impedance tomography*
Authors: Candiani V , Hyvönen N , Kaipio J P , Kolehmainen V 
Published: October 2021

Abstract
This work considers electrical impedance tomography imaging of the human head, with the ultimate goal of locating and classifying a stroke in emergency care. One of the main difficulties in the envisioned application is that the electrode locations and the shape of the head are not precisely known, leading to significant imaging artifacts due to impedance tomography being sensitive to modeling errors. In this study, the natural variations in the geometry of the head and skull are modeled based on a library of head anatomies. The effect of these variations, as well as that of misplaced electrodes, on (absolute) impedance tomography measurements is in turn modeled by the approximation error method. This enables reliably reconstructing the conductivity perturbation caused by the stroke in an average head model, instead of the actual head, relative to its average conductivity levels. The functionality of a certain edge-preferring reconstruction algorithm for locating the stroke is demonstrated via numerical experiments based on simulated three-dimensional data.
Ultra-low power signal conditioning system for effective biopotential signal recording
Authors: Thakur Diksha , Sharma Kulbhushan , Kapila Sonal , Sharma Rajnish 
Published: October 2021

Abstract
Design of Low-power signal conditioning system comprising of biopotential amplifier (BPA) and low pass Filter (LPF) remains one of the most critical block of system on chips (SoCs) targeted for wearable non-invasive and semi-invasive biomedical applications like electroencephalography and electrocorticography. Design of the same is a challenging task owing to noise-power trade-off in BPA and dependency of process voltage and temperature variations on the filter circuit. We report the design of a signal conditioning system comprising of a capacitively coupled capacitive feedback (CC-CF) BPA and composite p-channel metal oxide semiconductor (PMOS) based complementary source-follower LPF. The results obtained in Cadence with standard 0.18 µm technology and BSIM3V3 MOS models for the proposed signal conditioning system provide a DC-gain value of 36.76 dB, bandwidth of 280 mHz–174 Hz, power consumption of 24.54 µW, supply current of 24.54 µA, area consumption of 0.212826 mm2 from

±

0.5 V supply voltage. Robustness of this signal conditioning system has been checked by performing 200 runs of monte carlo simulations. The statistical results obtained for gain of (CC-CF) BPA, complementary source follower (CSF-C) LPF and signal conditioning system show mean (µ) values of 39.93 dB, −3.92 dB and 35.96 dB as well as standard deviation (

σ

) of 135.433 mdB, 1.90 dB, and 2.00 dB respectively. The CC-CF BPA architecture, CSF-C LPF and complete signal conditioning system are expected to be used in SoCs targeted for various low-power biomedical applications.
Oblique drive tolerance of elliptical skyrmions moving in perpendicularly magnetized nanowire
Authors: Kaiya Yuki , Nishiyama Shota , Honda Syuta , Itoh Hiroyoshi , Ohsawa Tomokatsu 
Published: October 2021

Abstract
A magnetic skyrmion is stabilized via the Dzyaloshinskii–Moriya interaction in a perpendicularly magnetized thin nanowire. When the skyrmion is driven by a spin-transfer torque due to spin currents flowing through the wire, the skyrmion approaches the wire edge owing to the skyrmion Hall effect. In other words, the skyrmion moves obliquely along the longitudinal direction of the wire. The skyrmion often breaks or disappears because of this oblique motion. In this study, we propose an elliptical skyrmion to prevent this disappearance. We simulated the current-induced motion of an elliptical skyrmion produced in a wire through a micromagnetic approach. The elliptical skyrmion was also moved obliquely to the longitudinal direction of the wire. When a small current flowed through the wire, the skyrmion moved in the longitudinal direction of the wire after it approached the wire edge. When a larger current flowed through the wire, the skyrmion disappeared after it approached the wire edge. The elliptical skyrmion can be driven over a long distance with a larger current compared to a circular skyrmion. The motion of the skyrmion approaching the wire edge was analyzed using Thiele’s equation, with an external force. We estimated the external force from the simulation results of the skyrmion motion. The external force was proportional to the distance between the skyrmion edge and the wire edge. The results of this study indicate that using the elliptical skyrmion as a binary digit in a magnetic memory, such as a skyrmion-based racetrack memory, can be advantageous in term of the stability of the binary digit.
Construction and application of knotted acoustic fields with intensity maxima
Authors: Liu Ya , Zhang Weixuan , Zhang Xiangdong 
Published: October 2021

Abstract
Knots have always played an important role in the life sciences because of their complex topology. Some previous investigations have shown that an optical field can be modulated into knot structures, and a knotted trap formed by light beams has also been demonstrated. Very recently, it has also been demonstrated that an acoustic vortex field with phase singularities can be tied into a knotted structure. However, for knotted tweezers, we need to use the relative maximum points of the amplitude distribution to construct the knotted field (although it is still not known how to create such a knotted line acoustic field) which is beneficial for particle trapping into knotted shapes. In this work we propose a method to generate acoustic fields with knotted intensity maxima in three dimensions. Based on the finite element method and angular spectrum theory, we prove that both Hopf link and trefoil knot lines in acoustic fields can be generated by the designed holograms. Furthermore, under particle tracking simulation in the time domain, we demonstrate that the knotted line acoustic fields can be used to capture particles into different topologies in three dimensions.
Constraining the density dependence of the symmetry energy: the isospin transport ratio revisited
Authors: Mallik S , Gulminelli F , Gruyer D 
Published: October 2021

Abstract
The isospin diffusion of the quasi-projectile formed in the

Ni

64
,
58

on

Ni

64
,
58

reactions in the Fermi energy domain is investigated in the framework of the Boltzmann–Uehling–Uhlenbeck transport model. The well known isospin transport ratio observable is revisited, with the aim of insuring an optimal comparison between experimental data and theoretical calculations and reducing the present uncertainties in the extraction of empirical equation of state parameters. We show that isospin transport ratios are sensitive to all the low order isovector parameters (E
sym, L
sym and K
sym, but the quantitative results depend on the choice of the isospin sensitive observable. We demonstrate that realistic models of the equation of state, covering the uncertainty that presently affects the theoretical description of neutron stars static observables, can be effectively discriminated by isospin diffusion experiments, provided the neutron to proton ratio of the projectile remnant is precisely measured as a function of centrality.
Emerging technologies in brachytherapy
Authors: Song William Y , Robar James L , Morén Björn , Larsson Torbjörn , Carlsson Tedgren Åsa , Jia Xun 
Published: October 2021

AbstractBrachytherapy is a mature treatment modality. The literature is abundant in terms of review articles and comprehensive books on the latest established as well as evolving clinical practices. The intent of this article is to part ways and look beyond the current state-of-the-art and review emerging technologies that are noteworthy and perhaps may drive the future innovations in the field. There are plenty of candidate topics that deserve a deeper look, of course, but with practical limits in this communicative platform, we explore four topics that perhaps is worthwhile to review in detail at this time. First, intensity modulated brachytherapy (IMBT) is reviewed. The IMBT takes advantage ofanisotropicradiation profile generated through intelligent high-density shielding designs incorporated onto sources and applicators such to achieve high quality plans. Second, emerging applications of 3D printing (i.e. additive manufacturing) in brachytherapy are reviewed. With the advent of 3D printing, interest in this technology in brachytherapy has been immense and translation swift due to their potential to tailor applicators and treatments customizable to each individual patient. This is followed by, in third, innovations in treatment planning concerning catheter placement and dwell times where new modelling approaches, solution algorithms, and technological advances are reviewed. And, fourth and lastly, applications of a new machine learning technique, called deep learning, which has the potential to improve and automate all aspects of brachytherapy workflow, are reviewed. We do not expect that all ideas and innovations reviewed in this article will ultimately reach clinic but, nonetheless, this review provides a decent glimpse of what is to come. It would be exciting to monitor as IMBT, 3D printing, novel optimization algorithms, and deep learning technologies evolve over time and translate into pilot testing and sensibly phased clinical trials, and ultimately make a difference for cancer patients. Today’s fancy is tomorrow’s reality. The future is bright for brachytherapy.
Comparison between the results of a recently-developed biological weighting function (V79-RBE10 BWF) and the in vitro clonogenic survival RBE10 of other repair-competent asynchronized normoxic mammalian cell lines and ions not used for the development of the model
Authors: Parisi Alessio , Struelens Lara , Vanhavere Filip 
Published: October 2021

Abstract
728 simulated microdosimetric lineal energy spectra (26 different ions between 1H and 238U, 28 energy points from 1 to 1000 MeV/n) were used in combination with a recently-developed biological weighting function (Parisi et al 2020 Phys. Med. Biol. 1361–6560) and 571 published in vitro clonogenic survival curves in order to: (1) assess prediction intervals for the in silico results by deriving an empirical indication of the experimental uncertainty from the dispersion in the in vitro hamster lung fibroblast (V79) data used for the development of the biophysical model; (2) explore the possibility of modeling the relative biological effectiveness (RBE) of the 10% clonogenic survival of asynchronized normoxic repair-competent mammalian cell lines other than the one used for the development of the model (V79); (3) investigate the predictive power of the model through a comparison between in silico results and in vitro data for 10 ions not used for the development of the model. At first, different strategies for the assessment of the in silico prediction intervals were compared. The possible sources of uncertainty responsible for the dispersion in the in vitro data were also shortly reviewed. Secondly, also because of the relevant scatter in the in vitro data, no statistically-relevant differences were found between the RBE10 of the investigated different asynchronized normoxic repair-competent mammalian cell lines. The only exception (Chinese Hamster peritoneal fibroblasts, B14FAF28), is likely due to the limited dataset (all in vitro ion data were extracted from a single publication), systematic differences in the linear energy transfer calculations for the employed very-heavy ions, and the use of reference photon survival curves extracted from a different publication. Finally, the in silico predictions for the 10 ions not used for the model development were in good agreement with the corresponding in vitro data.
Uncovering low frequency band gaps in electrically resonant metamaterials through tuned dissipation and negative impedance conversion
Authors: Callanan J , Willey C L , Chen V W , Liu J , Nouh M , Juhl A T 
Published: October 2021

Abstract
A new class of electromechanically coupled metamaterial is presented which relies on magnetic field interactions between the host structure and a local resonator circuit to realize novel vibration control capabilities. The metamaterial chain exhibits a highly tunable vibration band gap which can be easily placed at a desired frequency using the resonant circuit parameters, providing a robust mechanism to independently alter the band gap width, depth, and frequency of maximum attenuation. In its dissipative form, the electromechanical metamaterial is shown to exhibit electrical metadamping as a function of the local resonance circuit resistance. The impact of the damping ratio as a function of the electrical resistance is characterized in frequency and time domains, and related to the infinite system dynamics. A robust experimental realization of the system is constructed which achieves electromechanical coupling through a moving coil and magnet system. The apparatus is used to show that the band gap location and depth can be readily tuned with the circuit elements. The presented metamaterial has potential for meaningful vibroacoustic practical applications in addition to revealing fundamentally new properties of damped electrically-resonant structures.
In situ embedded PZT sensor for monitoring 3D concrete printing: application in alkali-activated fly ash-slag geopolymers
Authors: Kocherla Amarteja , Kamakshi Tippabhotla A , Subramaniam Kolluru V L 
Published: October 2021

Abstract
An embedded PZT sensor is developed for in situ monitoring of 3D-printed materials formed by extrusion-based layer deposition. The PZT sensor with a two-layer protection coating is embedded in the material during the layer deposition, and continuous measurements are obtained through the post-printing period. The PZT sensor is used to detect the physio-chemical changes in the alkali-activated fly ash-slag geopolymer with time. The effect of the added weight of each layer of print is sensitively reflected in the electrical impedance (EI) measurement obtained from the PZT sensor. The changes in EI measurements obtained from the embedded PZT sensor are compared with the measurements on the material related to the changes in the rheological behavior, reaction kinetics assessed using calorimetry, and setting behavior in the material. The build-up of the internal structure within the material, which allows buildability, is assessed from the conductance signature of the embedded PZT sensor. The changes produced by the chemical reactions within the binder, which bring about irreversible changes leading to the setting of the printed structure, are also sensitively detected in the EI measurements from the embedded PZT sensor. The amplitude of conductance is sensitive to the setting of the material. The frequency changes from the recorded EI signature reflect the continuous increase in the material stiffness with time.
Sensitivity analysis and machine learning modelling for the output characteristics of rotary HTS flux pumps
Authors: Wen Zezhao , Zhang Hongye , Mueller Markus 
Published: October 2021

Abstract
High temperature superconducting (HTS) rotatory flux pump, or so called HTS dynamo, can output none-zero time-averaged DC voltage and charge the rest of the circuit if a closed loop has been formed. This type of flux pump is often employed together with HTS coils, where the HTS coils can potentially work in persistent current mode, and act like electromagnets with considerable magnetic field, having wide range of applications in industry. The output characteristics of HTS rotary flux pumps have been extensively explored through experiments and finite element method (FEM) simulations, yet the work on constructing statistical models as an alternative approach to capture key characteristics has not been studied and published. A 2D FEM program has been used to model the HTS rotatory flux pumps and evaluate the effects of different factors upon the output voltage through parameter sweeping and analysis of variance. Typical design considerations, including operation frequency, air gap, HTS tape width and remanent flux density have been investigated, in particular the bilateral effect of HTS tape width has been explained by looking at the averaged integration of the electric field over the tape. Based on the data obtained from various simulations, regression analysis has been conducted through a collection of machine learning methods and demonstrated that the output voltage of a rotary flux pump can be obtained promptly with satisfactory accuracy via Gaussian process regression, aiming to provide a novel approach for future research and powerful design tool for industrial applications using HTS rotary flux pump devices.