bluuebunny/crossref_metadata_2025 huggingface dataset:
Agreement between isokinetic eccentric hamstring strength, Nordic hamstring strength and Nordic break‐point angle in a sample of trained and healthy individuals
Authors: Miralles‐Iborra A. , Elvira J. L. L. , Urban T. , Calado A. , Del Coso J. , Moreno‐Pérez V.
Published: December 2021

Different eccentric strength assessments are used to identifying the risk of hamstring injury in athletes. However, there is scarce information to determine the association between Nordic‐based measurements and the gold standard measurement of eccentric hamstring strength in an isokinetic dynamometer. To investigate the relationship of different measures of eccentric hamstring strength (break‐point angle and eccentric strength during Nordic exercise) with eccentric hamstring peak torque measured with an isokinetic dynamometer. Forty‐six participants volunteered to participate in this study. Eccentric peak force in the Smart‐Nordic System and break‐point angle measured as trunk lowering at >20°/s and >150°/s2 during the Nordic exercise via high‐frequency video‐analysis were compared to eccentric hamstring peak torque in an isokinetic dynamometer set to produce knee extension at 30°/s. There was a moderate association between peak eccentric strength with the Smart‐Nordic and isokinetic eccentric hamstring peak torque (r = −0.65, p < 0.001, 95%CI = [−0.76‐(−0.50)]). The association between Nordic break‐point angle measured at 20°/s (r = 0.49, p < 0.001, 95%CI = [0.30–0.64]) and at 150°/s2 (r = 0.52, p < 0.001, 95%CI = [0.33–0.66]) presented statistically significant but lower associations with isokinetic eccentric hamstring peak torque. All Nordic‐based measurements presented acceptable associations with the gold standard isokinetic eccentric hamstring peak torque. However, peak eccentric force measured on the Smart‐Nordic device had a better agreement with eccentric peak torque measured with an isokinetic dynamometer than the video‐based measurements.

Highlights

Peak eccentric force measured on the isometric strain‐gauges device had a better agreement with eccentric hamstring peak torque measured with an isokinetic dynamometer than the break‐point angle.

The Nordic‐based measurements are an alternative cost‐effective method to assess eccentric muscle strength and weakness when the access to isokinetic dynamometry is not feasible.

Caution should be taken with certain variables such as participants body mass, hip position and movement speed when interpreting the results of Nordic‐based measurements.
IFT trains overcome an NPHP module barrier at the transition zone
Authors: Park Kwangjin , Leroux Michel R.
Published: December 2021

Cilia harbor diffusion barriers for soluble and membrane proteins within their proximal-most transition zone (TZ) region and employ an intraflagellar transport (IFT) system to form dynamic motile and signaling compartments. In this issue, De-Castro and colleagues (2021. J. Cell Biol.https://doi.org/10.1083/jcb.202010178) uncover a long-suspected role for the TZ in gating IFT particles.
Complex structures for Klein–Gordon theory on globally hyperbolic spacetimes
Authors: Much Albert , Oeckl Robert
Published: December 2021

We develop a rigorous method to parametrize complex structures for Klein–Gordon theory in globally hyperbolic spacetimes that satisfy a completeness condition. The complex structures are conserved under time-evolution and implement unitary quantizations. They can be interpreted as corresponding to global choices of vacuum. The main ingredient in our construction is a system of operator differential equations. We provide a number of theorems ensuring that all ingredients and steps in the construction are well-defined. We apply the method to exhibit natural quantizations for certain classes of globally hyperbolic spacetimes. In particular, we consider static, expanding and Friedmann–Robertson–Walker spacetimes. Moreover, for a huge class of spacetimes we prove that the differential equation for the complex structure is given by the Gelfand–Dikki equation.
Exploration and categorisation of pre-service physics teachers’ understanding of superconductivity and nanotechnology
Authors: Kriek Jeanne , Lemmer Miriam , Ojal John
Published: December 2021

Nanoscience and technology is a major field of scientific research and technological innovation but understanding concepts such as superconductivity and nanotechnology are not straightforward. To develop focused teaching strategies, it is necessary to categorise students’ prior understanding as different categories of prior ideas require different teaching strategies. An exploratory case study research design was followed to explore and categorise 21 pre-service physics teachers’ (PSPTs’) understanding of basic concepts of superconductivity and nanotechnology at a University in Oman. Self-compiled open ended questionnaires were used to elicit PSPT understanding of superconductivity and nanotechnology. Their understanding was categorised in epistemological and ontological categories. These six categories were: lateral alternative conceptions; ontological conceptions; naïve physics; phenomenological primitives; mixed conceptions; and loose ideas. Findings from this pre-instructional study indicated that naïve physics ideas and lateral alternative conceptions were dominant and that the PSPTs’ conceptions were diversified and inconsistent. These results could lead to the development of evidence-based pedagogy, which is fundamental to the advancement of an effective physics education curriculum for these two contemporary topics.
Simultaneous determination of mass parameter and radial marker in Schwarzschild geometry
Authors: Varela Victor , Leal Lorenzo
Published: December 2021

We show that mass parameter and radial marker values can be indirectly measured in thought experiments performed in Schwarzschild spacetime, without using the Newtonian limit of general relativity or approximations based on Euclidean geometry. Our approach involves different proper time quantifications as well as solutions to systems of algebraic equations, and aims to strengthen the conceptual independence of general relativity from Newtonian gravity.
Leidenfrost drop dynamics: a forgotten past and modern day rediscoveries
Authors: Stewart Seán
Published: December 2021

When drops of liquid are placed onto highly heated substrates at temperatures well above their boiling point, the drops float on a thin layer of vapour formed between the liquid and the hot surface. In a 290 year old phenomenon referred to as the Leidenfrost effect, drops freed from contact with the surface below can undergo a range of surprising and unexpected dynamical behaviour. In this paper we trace various early developments associated with the dynamics of Leidenfrost drops. By showing how many of the more recent discoveries found in the dynamic behaviour of Leidenfrost drops were either anticipated or antedated, we hope to draw attention to the long, rich, and largely overlooked history of the Leidenfrost effect and show there is much one can learn from its forgotten past.
New transform to project axisymmetric deflection fields along arbitrary rays
Authors: Sipkens T A , Grauer S J , Steinberg A M , Rogak S N , Kirchen P
Published: December 2021

Axisymmetric tomography is used to extract quantitative information from line-of-sight measurements of gas flow and combustion fields. For instance, background-oriented schlieren (BOS) measurements are typically inverted by tomographic reconstruction to estimate the density field of a high-speed or high-temperature flow. Conventional reconstruction algorithms are based on the inverse Abel transform, which assumes that rays are parallel throughout the target object. However, camera rays are not parallel, and this discrepancy can result in significant errors in many practical imaging scenarios. We present a generalization of the Abel transform for use in tomographic reconstruction of light-ray deflections through an axisymmetric target. The new transform models the exact path of camera rays instead of assuming parallel paths, thereby improving the accuracy of estimates. We demonstrate our approach with a simulated BOS scenario in which we reconstruct noisy synthetic deflection data across a range of camera positions. Results are compared to state-of-the-art Abel-based algorithms. Reconstructions computed using the new transform are consistently more stable and accurate than conventional reconstructions.
Alignment subdomain-based deep convolutional transfer learning for machinery fault diagnosis under different working conditions
Authors: Li Yibing , Wan Hu , Jiang Li
Published: December 2021

In recent years, transfer learning (TL) methods have been extensively used in machinery fault diagnosis under different working conditions. However, most of these TL methods perform poorly in the actual industrial applications, due to the fact that they mainly focus on the global distribution of different domains without considering the distribution of subdomains belonging to the same category in different domains. Therefore, we propose an alignment subdomain-based deep convolutional transfer learning (AS-DCTL) network for machinery fault diagnosis. First, continuous wavelet transform is used to transform the original vibration signal into a 2D time-frequency image. Then, AS-DCTL uses a convolutional neural network as the feature extractor to extract the features of the source and target domain samples and introduces maximum mean difference (MMD) to align the global distribution of the extracted features. Simultaneously, we use local MMD as a metric criterion to align the distribution of related subdomains, by adding weights to similar samples in the source domain and target domain. The experimental results of the two case studies show that the proposed AS-DCTL network can achieve higher recognition accuracy and classification effect, in comparison with the current mainstream TL methods.
Microstructure-dependent rate theory model of defect segregation and phase stability in irradiated polycrystalline LiAlO2
Authors: Hu Shenyang , Li Yulan , Shang Shunli , Liu Zi-Kui , Burkes Douglas , Senor David J
Published: December 2021

Gamma lithium aluminate (LiAlO2) is a breeder material for tritium and is one of key components in a tritium-producing burnable absorber rod (TPBAR). Dissolution and precipitation of second phases such as LiAl5O8 and voids are observed in irradiated LiAlO2. Such microstructure changes cause the degradation of thermomechanical properties of LiAlO2 and affect tritium retention and release kinetics, and hence, the TPBAR performance. In this work, a microstructure-dependent model of radiation-induced segregation (RIS) has been developed for investigating the accumulation of species and phase stability in polycrystalline LiAlO2 structures under irradiation. Three sublattices (i.e. [Li, Al, V]I [O, Vo]II [Lii, Ali, Oi, Vi]III), and concentrations of six diffusive species (i.e. Li; vacancy of Li or Al at [Li, Al, V]I sublattice, O vacancy at [O, Vo]II sublattice, and Li, Al and O interstitials at [Lii, Ali, Oi, Vi]III interstitial sublattices; are used to describe spatial and temporal distributions of defects and chemistry. Microstructure-dependent thermodynamic and kinetic properties including the generation, reaction, and chemical potentials of defects and defect mobility are taken into account in the model. The parametric studies demonstrated the capability of the developed RIS model to assess the effect of thermodynamic and kinetic properties of defects on the segregation and depletion of species in polycrystalline structures and to explain the phase stability observed in irradiated LiAlO2 samples. The developed RIS model will be extended to study the precipitation of LiAl5O8 and voids and tritium retention by integrating the phase-field method.
A generalizable machine learning potential of Ag–Au nanoalloys and its application to surface reconstruction, segregation and diffusion
Authors: Wang YiNan , Zhang LinFeng , Xu Ben , Wang XiaoYang , Wang Han
Published: December 2021

Owing to the excellent catalytic properties of Ag–Au binary nanoalloys, nanostructured Ag–Au, such as Ag–Au nanoparticles and nanopillars, has been under intense investigation. To achieve high accuracy in molecular simulations of Ag–Au nanoalloys, the surface properties must be modeled with first-principles precision. In this work, we constructed a generalizable machine learning interatomic potential for Ag–Au nanoalloys based on deep neural networks trained from a database constructed with first-principles calculations. This potential is highlighted by the accurate prediction of Au (111) surface reconstruction and the segregation of Au toward the Ag–Au nanoalloy surface, where the empirical force field (EFF) failed in both cases. Moreover, regarding the adsorption and diffusion of adatoms on surfaces, the overall performance of our potential is better than the EFFs. We stress that the reported surface properties are blind to the potential modeling in the sense that none of the surface configurations is explicitly included in the training database; therefore, the reported potential is expected to have a strong generalization ability to a wide range of properties and to play a key role in investigating nanostructured Ag–Au evolution, where accurate descriptions of free surfaces are necessary.
Curious behaviour of spinning coffee cups and other spinning objects
Authors: Cross Rod
Published: December 2021

If an empty coffee cup is spun on a horizontal surface about a vertical axis in an anti-clockwise direction, then the whole cup rotates slowly backwards, in a clockwise direction, about a vertical axis located outside the cup. Clues to this curious behaviour are presented by comparing it with other spinning objects.
Temperature measurement of intracranial cerebrospinal fluid using second-order motion compensation diffusion tensor imaging
Authors: Shibukawa Shuhei , Niwa Tetsu , Miyati Tosiaki , Ogino Tetsuo , Yoshimaru Daisuke , Kuroda Kagayaki
Published: December 2021

To reduce the determination errors of CSF pulsation in diffusion-weighted image (DWI) thermometry, we investigated whether applying second-order motion compensation diffusion tensor imaging (2nd-MC DTI) and fractional anisotropy (FA) processing improves the measurement of intracranial cerebrospinal fluid (CSF) temperature. In a phantom study, we investigated the relationship between temperature and FA in artificial CSF (ACSF) to determine the threshold for FA processing. The calculated temperatures of ACSF were compared with those of water. In a human study, 18 healthy volunteers were scanned using conventional DTI (c-DTI) and 2nd-MC DTI on a 3.0 T magnetic resonance imaging (MRI) system. A temperature map was created using diffusion coefficients from each DWI with/without FA processing. The temperatures of intracranial CSF were compared between each DTI image using Welch’s analysis of variance and Games–Howell’s multiple comparisons. In the phantom study, FA did not exceed 0.1 at any temperature. Consequently, pixels exceeding the threshold of 0.1 were removed from the temperature map. Intracranial CSF temperatures significantly differed between the four methods (p < 0.0001). The lowest temperature was 2nd-MC DTI with FA processing (mean, 35.62 °C), followed in order by c-DTI with FA processing (mean, 36.16 °C), 2nd-MC DTI (mean, 37.08 °C), and c-DTI (mean, 39.08 °C;p < 0.01 for each). Because the calculated temperature of ACSF was estimated to be lower than that of water, the temperature of 2nd-DTI with FA processing was considered reasonable. The method of 2nd-MC DTI with FA processing enabled determining intracranial CSF temperature with a reduction in CSF pulsation.
Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT
Authors: Iyer Aditi , Thor Maria , Onochie Ifeanyirochukwu , Hesse Jennifer , Zakeri Kaveh , LoCastro Eve , Jiang Jue , Veeraraghavan Harini , Elguindi Sharif , Lee Nancy Y , Deasy Joseph O , Apte Aditya P
Published: December 2021

Objective. Delineating swallowing and chewing structures aids in radiotherapy (RT) treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim to develop an accurate and efficient method to automate this process. Approach. CT scans of 242 head and neck (H&N) cancer patients acquired from 2004 to 2009 at our institution were used to develop auto-segmentation models for the masseters, medial pterygoids, larynx, and pharyngeal constrictor muscle using DeepLabV3+. A cascaded framework was used, wherein models were trained sequentially to spatially constrain each structure group based on prior segmentations. Additionally, an ensemble of models, combining contextual information from axial, coronal, and sagittal views was used to improve segmentation accuracy. Prospective evaluation was conducted by measuring the amount of manual editing required in 91 H&N CT scans acquired February-May 2021. Main results. Medians and inter-quartile ranges of Dice similarity coefficients (DSC) computed on the retrospective testing set (N = 24) were 0.87 (0.85–0.89) for the masseters, 0.80 (0.79–0.81) for the medial pterygoids, 0.81 (0.79–0.84) for the larynx, and 0.69 (0.67–0.71) for the constrictor. Auto-segmentations, when compared to two sets of manual segmentations in 10 randomly selected scans, showed better agreement (DSC) with each observer than inter-observer DSC. Prospective analysis showed most manual modifications needed for clinical use were minor, suggesting auto-contouring could increase clinical efficiency. Trained segmentation models are available for research use upon request via https://github.com/cerr/CERR/wiki/Auto-Segmentation-models. Significance. We developed deep learning-based auto-segmentation models for swallowing and chewing structures in CT and demonstrated its potential for use in treatment planning to limit complications post-RT. To the best of our knowledge, this is the only prospectively-validated deep learning-based model for segmenting chewing and swallowing structures in CT. Segmentation models have been made open-source to facilitate reproducibility and multi-institutional research.
Assessing cardiac stiffness using ultrasound shear wave elastography
Authors: Caenen Annette , Pernot Mathieu , Nightingale Kathryn R , Voigt Jens-Uwe , Vos Hendrik J , Segers Patrick , D’hooge Jan
Published: December 2021

Shear wave elastography offers a new dimension to echocardiography: it measures myocardial stiffness. Therefore, it could provide additional insights into the pathophysiology of cardiac diseases affecting myocardial stiffness and potentially improve diagnosis or guide patient treatment. The technique detects fast mechanical waves on the heart wall with high frame rate echography, and converts their propagation speed into a stiffness value. A proper interpretation of shear wave data is required as the shear wave interacts with the intrinsic, yet dynamically changing geometrical and material characteristics of the heart under pressure. This dramatically alters the wave physics of the propagating wave, demanding adapted processing methods compared to other shear wave elastography applications as breast tumor and liver stiffness staging. Furthermore, several advanced analysis methods have been proposed to extract supplementary material features such as viscosity and anisotropy, potentially offering additional diagnostic value. This review explains the general mechanical concepts underlying cardiac shear wave elastography and provides an overview of the preclinical and clinical studies within the field. We also identify the mechanical and technical challenges ahead to make shear wave elastography a valuable tool for clinical practice.
Simulation study on the performance of time-over-threshold based positioning in monolithic PET detectors
Authors: Thyssen Charlotte , Deprez Karel , Mollet Pieter , Van Holen Roel , Vandenberghe Stefaan
Published: December 2021

The vast majority of PET detectors in the field today are based on pixelated scintillators. Yet, the resolution of this type of detector is limited by the pixel size. To overcome this limitation, one can use monolithic detectors. However, this detector architecture demands specific and high-speed detector readout of the photodetector array. A commonly used approach is to integrate the current pulses generated by every pixel but such circuitry quickly becomes bulky, power consuming and expensive. The objective of this work is to investigate a novel readout and event positioning scheme for monolithic PET detectors, based on time-over-threshold (ToT). In this case, we measure the time that the pulse is above a certain threshold through a comparator. The pulse widths are used for event positioning using a mean nearest neighbour approach (mNN
ToT
). For energy determination one integrating multiplexed channel is foreseen. We evaluate the positioning accuracy and uniformity of such a ToT detector by means of Monte Carlo simulations. The impact of the threshold value is investigated and the results are compared to a detector using mean nearest neighbour with pulse-integration (mNN
int
), which has already proven to allow sub-mm resolution. We show minimal degradation in spatial resolution and bias performance compared to mNN
int
. The highest threshold results in the worst resolution performance but degradation remains below 0.1 mm. Bias is largely constant over different thresholds for mNN
ToT
and close to identical to mNN
int
. Furthermore we show that ToT performs well in terms of detector uniformity and that scattered photons can be positioned inside the crystal with high accuracy. We conclude from this work that ToT is a valuable alternative to pulse-integration for monolithic PET detectors. This novel approach has an impact on PET detector development since it has the advantage of lower power consumption, compactness and inherent amplitude-to-time conversion.
Enhanced confinement in diverted negative-triangularity L-mode plasmas in TCV
Authors: Coda S , Merle A , Sauter O , Porte L , Bagnato F , Boedo J , Bolzonella T , Février O , Labit B , Marinoni A , Pau A , Pigatto L , Sheikh U , Tsui C , Vallar M , Vu T
Published: December 2021

The favorable confinement properties of negative-triangularity (NT) tokamak configurations were discovered in the TCV tokamak in the late 1990s and were documented over the two following decades, through investigations of predominantly electron-heated plasmas in limited topologies. The most recent experimental campaign in TCV has marked a leap forward, characterized by the development of a variety of diverted NT shapes that are robustly stable with basic Ohmic heating. The application of auxiliary heating, directed now at both electrons and ions (using electron-cyclotron resonance heating as well as neutral-beam injection), has enabled the achievement of record performances for L-mode plasmas, with normalized β values reaching 2.8 transiently (as well as 2 in steady state, but reverting to a limited configuration) and with comparable ion and electron temperatures. The systematic confinement enhancement with NT is confirmed in these experiments. The L-mode existence space is broader than at positive triangularity, with only sporadic transitions to H-mode observed up to 1.4 MW heating power regardless of the magnetic-field-gradient direction relative to the X-point. These experiments are planned to be continued with even higher power following a heating-source upgrade.
High-performance narrow spectrum green phosphorescent top-emitting organic light-emitting devices with external quantum efficiency up to 38%
Authors: Li Xiaokang , Liu Wenxing , Chen Kai , Wu Ruixia , Liu Guojun , Zhou Liang
Published: December 2021

In this work, we have experimentally demonstrated the efficacy of micro-cavity effect in realizing high-performance top-emitting organic light-emitting diodes (TEOLEDs). By optimizing the thickness of top Yb/Ag electrode and cavity length, highly efficient green TEOLED with external quantum efficiency as high as 38% was achieved. A strong dependence of electroluminescent (EL) performances and spectrum on cavity length was observed, and there was also a significant angle dependence of EL spectrum. Ultimately, ultra-high current efficiency up to 161.17 cd A−1 (3.2 V) was obtained by the device with emission peak at 552 nm, which is 35 nm longer than the intrinsic emission peak (517 nm) of utilized green emitter. Interestingly, this device displayed narrow emission with full-width at half-maximum of less than 20 nm, which was obtained by increasing the Ag layer thickness.
In-situ monitoring of micro-tunnel geometry change based on distributed optical fiber strain sensing
Authors: Piccolo Arianna , Lecieux Yann , Leduc Dominique , Delepine-Lesoille Sylvie , Bumbieler Frédéric , Yven Béatrice
Published: December 2021

Underground radioactive waste disposal facilities must be monitored to guarantee their correct and safe exploitation during the early stage of their service life. This will be the case in Cigéo, the french industrial geological disposal facility for high-level and intermediate-level long-lived waste, which must be monitored for the first a hundred years at least. For this purpose optical fiber strain sensing cables can be chosen for their low intrusivity and resistance to harsh radiation environment. In this paper, a monitoring method able to follow shape evolution of the structure’s section, based on distributed strain sensing is tested on a high-level waste disposal cell mock-up, a steel lined micro-tunnel of 762 mm of outer diameter. The cell demonstrator is built in Meuse/Haute-Marne Underground Research Laboratory, in the same geological environment as the one envisaged for Cigéo but it is empty of waste. After 7 months of loading of the rock around the mock-up, a maximum of 2 mm of diameter reduction is observed with Rayleigh-scattering based strain sensing technique and 10 mm of spatial resolution around the circumference. This validation under realistic test conditions opens up to the use of the method in-situ for tunnel monitoring in harsh environment.
Improving the comprehensive performance of miniature MR rotary actuators using a lamellar excitation structure
Authors: Liu Ying , Zhu Tairong , Liao Yunlai , Li Jiaqi , Dai Jun
Published: December 2021

Miniaturization has increasingly become a crucial prerequisite in various magnetorheological (MR) drive application scenarios. Owing to their high controllability and low response time, MR rotary actuators are developed for numerous feasible actuation solutions. However, the incident low degradation efficiency in the miniaturization limits the application of MR rotary actuators. In addition to torque capacity, structural simplification and easy machinability are also essential for miniaturization. In this study, a novel lamellar excitation structure (LES), which is interleaved with induction coils and ring-shaped iron cores, is proposed to improve the comprehensive performance of a miniature MR rotary actuator. The optimisation of the magnetic field distribution is realised by adopting an equivalent magnetic modelling method. The miniature MR actuator is incorporated into a turbine generator to evaluate the torque capability of the proposed LES-incorporated MR actuator via a kinematic model of the rotating shaft. The LES-incorporated MR rotary actuator demonstrates more favourable deceleration efficiency and torque capacity than conventional MR rotary actuators. The speed reduction per unit power Δn/P can be increased by 500% at most. The torque enhancement ratio-to-volume ratio value of LES is approximately 80 times higher than that of other optimised structures. We believe that this study is significant in improving the comprehensive performance of miniature MR rotary actuators, expanding the applications of MR actuators in miniaturised scenarios.
A novel chain-cluster model of magnetorheological elastomer for the dynamic mechanical performance research
Authors: Fan Lili
Published: December 2021

The existing research on magnetorheological elastomer (MRE) mainly focused on the improvement of MRE formula and structural design of MRE devices. As to the microscopic mechanism, less research has been done. Based on the scanning electron micrograph of MRE, a novel chain-cluster model of MRE was constructed in this study. Particle size and particle distance were introduced simultaneously to the constitutive relation of MRE. The dynamic mechanical properties of MRE are studied theoretically and experimentally. Using the constructed chain-cluster model of MRE, the effect of magnetic field, particle volume fraction and strain on the magnetic-induced modulus of MRE were simulated. Rotating rheometer was adopted to test the magnetic response characteristics of MREs. Simulation and test results showed that the maximum magnetic-induced modulus tested experimentally was in good agreement with that calculated theoretically. Thus, the constructed chain-cluster model of MRE shows an important role in the field of intelligent vibration. It not only makes great sense in the prediction of MRE property but provides guidance on the property improvement of MRE.
Theory of multiple quantum coherence signals in dilute thermal gases
Authors: Ames Benedikt , Carnio Edoardo G , Shatokhin Vyacheslav N , Buchleitner Andreas
Published: December 2021

Manifestations of dipole–dipole interactions in dilute thermal gases are difficult to sense because of strong inhomogeneous broadening. Recent experiments reported signatures of such interactions in fluorescence detection-based measurements of multiple quantum coherence (MQC) signals, with many characteristic features hitherto unexplained. We develop an original open quantum systems theory of MQC in dilute thermal gases, which allows us to resolve this conundrum. Our theory accounts for the vector character of the atomic dipoles as well as for driving laser pulses of arbitrary strength, includes the far-field coupling between the dipoles, which prevails in dilute ensembles, and effectively incorporates atomic motion via a disorder average. We show that collective decay processes—which were ignored in previous treatments employing the electrostatic form of dipolar interactions—play a key role in the emergence of MQC signals.
Dual form of the phase-space classical simulation problem in quantum optics
Authors: Semenov A A , Klimov A B
Published: December 2021

In quantum optics, nonclassicality of quantum states is commonly associated with negativities of phase-space quasiprobability distributions. We argue that the impossibility of any classical simulations with phase-space functions is a necessary and sufficient condition of nonclassicality. The problem of such phase-space classical simulations for particular measurement schemes is analysed in the framework of Einstein–Podolsky–Rosen–Bell’s principles of physical reality. The dual form of this problem results in an analogue of Bell inequalities. Their violations imply the impossibility of phase-space classical simulations and, as a consequence, nonclassicality of quantum states. We apply this technique to emblematic optical measurements such as photocounting, including the cases of realistic photon-number resolution and homodyne detection in unbalanced, balanced, and eight-port configurations.
Quantum thermodynamics in the no-measurement scheme: driven two-level atom and harmonic oscillator
Authors: Moradian A , Kheirandish F
Published: December 2021

The two-point measurement and no-measurement schemes are reviewed briefly. The quantum thermodynamics of a driven harmonic oscillator and a two-level atom in an external light field are investigated in the framework of the no-measurement scheme. The work distribution functions and the modified quantum Jarzynski theorem are obtained and discussed.
The inflationary wavefunction from analyticity and factorization
Authors: Meltzer David
Published: December 2021

We study the analytic properties of tree-level wavefunction coefficients in quasi-de Sitter space.
We focus on theories which spontaneously break dS boost symmetries and can produce significant non-Gaussianities.
The corresponding inflationary correlators are (approximately) scale invariant, but are not invariant under the full conformal group.
We derive cutting rules and dispersion formulas for the late-time wavefunction coefficients by using factorization and analyticity properties of the dS bulk-to-bulk propagator.
This gives a unitarity method which is valid at tree-level for general n-point functions and for fields of arbitrary mass.
Using the cutting rules and dispersion formulas, we are able to compute n-point functions by gluing together lower-point functions.
As an application, we study general four-point, scalar exchange diagrams in the EFT of inflation.
We show that exchange diagrams constructed from boost-breaking interactions can be written as a finite sum over residues.
Finally, we explain how the dS identities used in this work are related by analytic continuation to analogous identities in Anti-de Sitter space.
Entanglement witnesses of four-qubit tripartite separable quantum states*
Authors: Xu Miao , Zhou Wei-Feng , Chen Feng , Jiang Li-Zhen , Chen Xiao-Yu
Published: December 2021

A quantum entangled state is easily disturbed by noise and degenerates into a separable state. Compared to the entanglement with bipartite quantum systems, less progress has been made for the entanglement with multipartite quantum systems. For tripartite separability of a four-qubit system, we propose two entanglement witnesses, each of which corresponds to a necessary condition of tripartite separability. For the four-qubit GHZ state mixed with a W state and white noise, we prove that the necessary conditions of tripartite separability are also sufficient at W states side.
A class of two-dimensional rational maps with self-excited and hidden attractors
Authors: Zhang Li-Ping , Liu Yang , Wei Zhou-Chao , Jiang Hai-Bo , Bi Qin-Sheng
Published: December 2021

This paper studies a new class of two-dimensional rational maps exhibiting self-excited and hidden attractors. The mathematical model of these maps is firstly formulated by introducing a rational term. The analysis of existence and stability of the fixed points in these maps suggests that there are four types of fixed points, i.e., no fixed point, one single fixed point, two fixed points and a line of fixed points. To investigate the complex dynamics of these rational maps with different types of fixed points, numerical analysis tools, such as time histories, phase portraits, basins of attraction, Lyapunov exponent spectrum, Lyapunov (Kaplan–Yorke) dimension and bifurcation diagrams, are employed. Our extensive numerical simulations identify both self-excited and hidden attractors, which were rarely reported in the literature. Therefore, the multi-stability of these maps, especially the hidden one, is further explored in the present work.
High-throughput computational material screening of the cycloalkane-based two-dimensional Dion–Jacobson halide perovskites for optoelectronics
Authors: Zhao Guoqi , Xie Jiahao , Zhou Kun , Xing Bangyu , Wang Xinjiang , Tian Fuyu , He Xin , Zhang Lijun
Published: December 2021

Two-dimensional (2D) layered perovskites have emerged as potential alternates to traditional three-dimensional (3D) analogs to solve the stability issue of perovskite solar cells. In recent years, many efforts have been spent on manipulating the interlayer organic spacing cation to improve the photovoltaic properties of Dion–Jacobson (DJ) perovskites. In this work, a serious of cycloalkane (CA) molecules were selected as the organic spacing cation in 2D DJ perovskites, which can widely manipulate the optoelectronic properties of the DJ perovskites. The underlying relationship between the CA interlayer molecules and the crystal structures, thermodynamic stabilities, and electronic properties of 58 DJ perovskites has been investigated by using automatic high-throughput workflow cooperated with density-functional (DFT) calculations. We found that these CA-based DJ perovskites are all thermodynamic stable. The sizes of the cycloalkane molecules can influence the degree of inorganic framework distortion and further tune the bandgaps with a wide range of 0.9–2.1 eV. These findings indicate the cycloalkane molecules are suitable as spacing cation in 2D DJ perovskites and provide a useful guidance in designing novel 2D DJ perovskites for optoelectronic applications.
A multi-step blind source separation approach for the attenuation of artifacts in mobile high-density electroencephalography data
Authors: Zhao Mingqi , Bonassi Gaia , Guarnieri Roberto , Pelosin Elisa , Nieuwboer Alice , Avanzino Laura , Mantini Dante
Published: December 2021

Objective. Electroencephalography (EEG) is a widely used technique to address research questions about brain functioning, from controlled laboratorial conditions to naturalistic environments. However, EEG data are affected by biological (e.g. ocular, myogenic) and non-biological (e.g. movement-related) artifacts, which—depending on their extent—may limit the interpretability of the study results. Blind source separation (BSS) approaches have demonstrated to be particularly promising for the attenuation of artifacts in high-density EEG (hdEEG) data. Previous EEG artifact removal studies suggested that it may not be optimal to use the same BSS method for different kinds of artifacts. Approach. In this study, we developed a novel multi-step BSS approach to optimize the attenuation of ocular, movement-related and myogenic artifacts from hdEEG data. For validation purposes, we used hdEEG data collected in a group of healthy participants in standing, slow-walking and fast-walking conditions. During part of the experiment, a series of tone bursts were used to evoke auditory responses. We quantified event-related potentials (ERPs) using hdEEG signals collected during an auditory stimulation, as well as the event-related desynchronization (ERD) by contrasting hdEEG signals collected in walking and standing conditions, without auditory stimulation. We compared the results obtained in terms of auditory ERP and motor-related ERD using the proposed multi-step BSS approach, with respect to two classically used single-step BSS approaches. Main results. The use of our approach yielded the lowest residual noise in the hdEEG data, and permitted to retrieve stronger and more reliable modulations of neural activity than alternative solutions. Overall, our study confirmed that the performance of BSS-based artifact removal can be improved by using specific BSS methods and parameters for different kinds of artifacts. Significance. Our technological solution supports a wider use of hdEEG-based source imaging in movement and rehabilitation studies, and contributes to the further development of mobile brain/body imaging applications.
Ultrasonic thalamic stimulation modulates neural activity of thalamus and motor cortex in the mouse
Authors: Wang Xingran , Yan Jiaqing , Zhang Huiran , Yuan Yi
Published: December 2021

Objective. Previous studies have demonstrated that ultrasound thalamic stimulation (UTS) can treat disorders of consciousness. However, it is still unclear how UTS modulates neural activity in the thalamus and cortex. Approach. In this study, we performed UTS in mice and recorded the neural activities including spike and local field potential (LFP) of the thalamus and motor cortex (M1). We analyzed the firing rate of spikes and the power spectrum of LFPs and evaluated the coupling relationship between LFPs from the thalamus and M1 with Granger causality. Main results. Our results clearly indicate that UTS can directly induce neural activity in the thalamus and indirectly induce neural activity in the M1. We also found that there is a strong connection relationship of neural activity between thalamus and M1 under UTS. Significance. These results demonstrate that UTS can modulate the neural activity of the thalamus and M1 in mice. It has the potential to provide guidance for the ultrasound treatment of thalamus-related diseases.
Effect of Undecided and Swing Voters on The Dynamics Voters Model in Presidential Elections
Authors: Yong B.
Published: December 2021

In this paper, we construct the NUS1S2A voters model of two political fanaticism figures which involves undecided and swing voters. We determine the equilibrium points and the threshold parameter of the voters model. We also perform a sensitivity analysis for the threshold number to determine the importance of model parameters. The results of the sensitivity analysis show that the rate of transfer from neutral voters to undecided and swing voters is not the most negative sensitive parameter of the model, even though an increase in its parameter will cause a decrease in voter interest in voting in the presidential elections.
Output Tracking of Some Class Non-Minimum Phase Nonlinear Systems via linearization Input-Output
Authors: Firman
Published: December 2021

We present an output tracking problem for a non-minimum phase nonlinear system. In this paper, the input control design to solve the output tracking problem is to use the input output linearization method. The use of the input output linearization method cannot be initiated from output causing the system to be non-minimum phase. Therefore the output of the system will be redefined such that the system will become minimum phase with respect to a new output.
Mixed Multivariate EWMA-CUSUM (MEC) Chart based on MLS-SVR Model for Monitoring Drinking Water Quality
Authors: Mashuri M , Khusna H , Wibawati  , Putri F D
Published: December 2021

Monitoring the quality of drinking water needs to be conducted considering the important role of water in human life. Mixed Multivariate EWMA-CUSUM (MEC) chart is a multivariate control chart developed for observing the mean process. Based on the previous studies, this chart has better performance in detecting a shift in the process mean. In this research, the MEC is applied to observe the grade of drinking water. However, there is autocorrelation in drinking water data which lead to more false alarm occurred. Therefore, the Multioutput Least Square Support Vector Regression (MLS-SVR) model is employed to reduce or even remove the autocorrelation in the data. Using the optimal hyperparameter, the MLS-SVR algorithm produces the residuals of phase I with no autocorrelation. Those residuals are then used to form the MEC control charts. When the MEC is used to monitor the residual in phase I, there is no signal of out-of-control found. Further, in phase II, out-of-control observations are detected. The MEC chart can detect more signals out of control compared to the conventional Hotelling’s T
2 and Multivariate Exponentially Moving Average (MEWMA) charts.
Statistical Inference on Nonparametric Spline Models and its Applications
Authors: Arifanti D R , Hidayat R
Published: December 2021

One of the components of the Human Development Index which is still a problem and concern in the world today is the Life Expectancy Rate (LER). United Nations Development Program (UNDP). United Nations Development Program (UNDP) uses the LER to measure community health status as well as a benchmark for development success. LER in Indonesia continues to increase almost throughout the year. That is, the hope of a newborn baby to be able to live longer is getting higher. LER data modelling with parametric regression is not necessarily suitable to be applied because the LER relationship pattern has a pattern that varies at certain age intervals. Spline regression is a regression method that can handle data whose pattern changes at certain intervals. Spline is one of the models in nonparametric regression that has a very special and very good visual statistical interpretation. In addition, splines are also able to handle data characters or functions that are smooth (smooth). This study aims to derive the form of the estimator and the shortest confidence interval for the quadratic spline model and model the LER data in Indonesia.
Comparison of Bayesian Spatio-temporal Models of Tuberculosis in Makassar, Indonesia
Authors: Sukarna  , Wahyuni Maya Sari , Syam Rahmat
Published: December 2021

South Sulawesi province ranks sixth-highest in tuberculosis (TB) in Indonesia. Makassar ranks the highest in South Sulawesi. Spatio-temporal modelling can identify the areas with high risk as well as the temporal relative risk of disease. We analysed the tuberculosis cases data from Makassar City Health Office for 15 districts over seven years from 2012 to 2018. Seven models of Bayesian Spatio-temporal (BST) Conditional Autoregressive (CAR) were applied by using the measures of goodness of fit (GOF) namely, DIC and WAIC. The results showed that BST CAR localised model with G = 3 has the lowest DIC and BST CAR adaptive has the lowest WAIC. Based on the preferred model (Bayesian ST CAR localised with G=3), Panakukang district had the highest relative risk of TB in 2012, 2013, and 2014, while Makassar district had the highest relative risk of TB in 2015, 2016, and 2017. Mamajang had the highest relative risk of TB in 2018.
Visualization of the gas flows that formed above the thin-film coatings under VUV radiation influence
Authors: Skriabin A S , Telekh V D , Pavlov A V , Chesnokov D A , Zhupanov V G , Novikov P A
Published: December 2021

The plasma focus of a magnetoplasma compressor is a unique source of high-brightness broadband VUV (with photon energy of 5 to 100 electron volt) radiation. When such radiation affects on the surfaces of materials, it is possible to generate rather complex gas-dynamic structures due to the evaporation of the material and ionization of its vapors. A separate task is to study the processes of a gas-dynamic response to the exposure of the specified radiation fluxes on the surface of interference antireflection and reflective multilayers, which are used in modern laser technology, high-power optoelectronics, etc. In this report, we used schlieren photography for studying the features of gas-dynamic structures that arise at irradiation of coatings. Radiation resistant (in the visible and near IR ranges) HfO2/SiO2 and ZrO2/SiO2 multilayer structures (with a total thickness of 140–3700 nanometers and a number of layers of from 2 to 24) were used as prototypes for testing their stability under the VUV exposure.
Application of the laser-induced fluorescence to study local characteristics of a gas-liquid flow in rectangular microchannel
Authors: Bartkus G V , Kuznetsov V V
Published: December 2021

The Laser-Induced Fluorescence (LIF) method was used to characterize liquid phase distribution in rectangular slit microchannel with cross-section 200×1205 μm for horizontal gas-liquid flow. Ethanol and nitrogen were used as working liquid and gas accordingly. The feature of this study is an application of hydraulic focusing cross-junction mixer for obtaining elongated bubble and transition flows in the microchannel with a high aspect ratio. Using LIF measurements for elongated bubble and transition flows the liquid film distributions were obtained for different distances from the bubble top and average liquid film thickness was compared with the prediction according to Taylor’s law.