bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental assessment of impedance-based structural health monitoring in radioactive environment
Authors: de Souza Campos Fernando , Albuquerque de Castro Bruno , Luiz Taveira de Assis Helder , Zeituni Carlos Alberto , Covolan Ulson José Alfredo , Baptista Fabricio Guimarães 
Published: April 2023

Abstract
This work presents an experimental study of the influence of radiation on structural health monitoring systems based on the electromechanical impedance method using low-cost piezoelectric diaphragms. For application of the method, the baseline was obtained without radiation and then compared by damage indices after application of radiation. Considering applications in nuclear power plants, the irradiation and calculation of damage indices were performed in the range of 10 kGy–60 kGy at 10 kGy intervals. Impedance measurements were performed in seven frequency bands between 0 and 65 kHz. The results show that, due to the change in the impedance signatures, the damage indices values increase according to the total applied radiation dose, which may indicate a false indication of damage. Besides, results indicate that there are frequency bands less sensitive to radiation and a threshold can be defined to distinguish radiation from structural damage.
Dynamic state estimation of power systems considering maximum correlation entropy and quadratic function
Authors: Chen Tengpeng , Liu Fangyan , Sun Lu , Amaratunga Gehan A J , Zeng Nianyin 
Published: April 2023

Abstract
Uncertainties such as abnormal system inputs, strong model nonlinearities, outliers and impulsive noise unavoidably exist in the power system dynamic state estimation (SE) (DSE). The existing Kalman filter-based DSE methods cannot deal with the uncertainties well and can be improved further. In this paper, a robust DSE method based on the maximum correlation entropy (MCE), quadratic function (QF) and the cubature Kalman filter is proposed to reduce the effects caused by the uncertainties. The MCE-QF based estimator is robust and can alleviate the influence of uncertainties. A new SE error covariance is derived by using the robust statistical tool, influence function. The robustness and estimation precision of the proposed DSE method is demonstrated by conducting simulations on a synchronous generator under different cases.
An interval SLAM algorithm for leg–arm mobile robots based on a CBMeMBer filter with Gaussian indicator box-particles
Authors: Luo Jingwen , Qin Shiyin 
Published: April 2023

Abstract
During the implementation of SLAM methods based on probability hypothesis density with sequential Monte Carlo (SMC), it is necessary to generate a relatively large number of particles for mapping and to cluster particles for target state extraction, which brings about heavy computing requirements and difficulty in enhancing the estimation accuracy. Along these lines, in this work, an interval SLAM algorithm for a leg–arm mobile robot (LA-MR) is presented, which is based on cardinality-balanced multi-target multi-Bernoulli filter (CBMeMBer) with Gaussian indicator box-particles (GIBPs). First, an effective strategy for improving the selection criterion of subdivision box-particles is given via the indicator subdivision resampling to provide more reliable box-particles. In addition, mixtures of Gauss distributions with box supports were developed to fit the posterior probability, i.e. GIBP. Then, the GIBP filter was employed to implement the CBMeMBer filter and thus the particle numbers were significantly reduced to decrease the computational complexity compared with the SMC-CBMeMBer filter. In this way, the feature map learning is considered as a multi-target tracking problem, whereas a kind of SLAM algorithm for LA-MR was also designed and implemented through the GIBP-CBMeMBer filter, in which the GIBP filter is used to realize simultaneous localization and the GIBP-CBMeMBer filter is utilized to build a map. A series of experiments and a case study clearly illustrated the performance superiority of the proposed algorithms.
Effects of spring gripper configuration and forming temperature on the thermo-stamping of a carbon-fiber woven-fabric/polyphenylene sulfide composite sheet
Authors: Yildirim Halil , Uren Nazli , Ozturk Fahrettin 
Published: April 2023

Abstract
Although thermo-stamping is one of the fastest and most cost-effective processes in the production of fabric-reinforced thermoplastic composite parts used in aerospace and automotive industries, it is quite prone to result in many defects. In particular, wrinkling is a frequently encountered defect in the production of doubly curved parts and is very sensitive to process parameters. Finite element analysis is an effective tool for estimating defects that can occur during the thermo-stamping process. In this study, effects of spring configurations in spring-based holders and forming temperature on wrinkling and shear deformation are investigated experimentally and numerically by using two different spring configurations and three different forming temperatures. Non-isothermal and isothermal approaches used in thermo-stamping simulations are compared in terms of wrinkling estimation and shear angle distribution. The results reveal that while the wrinkle predictions obtained by the non-isothermal approach are in good agreement with the experimental results, the isothermal approach cannot predict any of the wrinkles obtained in the experiment. Furthermore, the obtained results confirm that spring gripper configurations and forming temperature have a significant effect on wrinkling and shear angle distribution.
High-sensitivity biosensor based on SERS integrated with dendrimer-assisted boronic acid-functionalized magnetic nanoparticles for IL-6 detection in human serum
Authors: Wang Ying , Guan Ming , Hu Cunming , Mi Fang , Geng Pengfei , Li Yingjun 
Published: April 2023

Abstract
High-sensitivity quantitative analysis of sepsis disease markers in circulating blood is essential for sepsis early diagnosis, rapid stratification, and interventional treatment. Herein, a high-sensitivity biosensor combining surface-enhanced Raman spectroscopy (SERS) and functionalized magnetic materials was developed to quantitatively detect interleukin-6 (IL-6), a glycoprotein disease marker closely related to sepsis. First, boronic acid-functionalized magnetic nanomaterials with high adsorption performance were synthesized by utilizing the branched polyethyleneimine to provide many binding sites for boronic acid. Under antibody-free conditions, dendrimer-assisted boronic acid-functionalized magnetic nanomaterials selectively capture glycoproteins in complex biological samples as bio-capture element. Then, a core–shell bimetallic material with plenty of ‘hot spots’ was designed and synthesized as the enhancement substrate. The 4-Mercaptobenzonitrile (4-MP) with a characteristic peak at 2224 cm−1 (Raman-silent region) was embedded as the Raman reporter to form a SERS immune probe with highly efficient electromagnetic enhancement effect, achieving specific recognition and high-sensitivity detection of IL-6 on bio-capture elements. Using this strategy for quantitative analysis of IL-6, a wide detection range (0.5–5000 pg ml−1) and a low detection limit (0.453 pg ml−1) were obtained. Moreover, this method exhibited excellent detection performance for IL-6 in human serum samples, demonstrating its potential promise in screening clinically relevant diseases. The biosensor presented here not only provides a novel and universally applicable sensing strategy for the enrichment and detection of trace glycoprotein disease markers, but also the application of a portable Raman spectrometer provides a more reliable experimental basis for the diagnosis and treatment of major diseases in the clinic or remote and deprived areas.
Data-driven adaptive needle insertion assist for transperineal prostate interventions
Authors: Bernardes Mariana C , Moreira Pedro , Mareschal Lisa , Tempany Clare , Tuncali Kemal , Hata Nobuhiko , Tokuda Junichi 
Published: April 2023

Abstract

Objective. Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150–200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients. Approach. In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not require a priori information about needle or tissue properties. The method was evaluated in experiments with both in vitro and ex vivo phantoms. Main results. The experiments in ex vivo tissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction. Significance. Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.
Positional sleep apnea phenotyping using machine learning and digital oximetry biomarkers
*
Authors: Ben Sason Yuval , Levy Jeremy , Oksenberg Arie , Sobel Jonathan , Behar Joachim A 
Published: April 2023

Abstract

Study Objectives. To examine the feasibility of using digital oximetry biomarkers (OBMs) and body position to identify positional obstructive sleep apnea (POSA) phenotypes. Methods. A multiclass extreme gradient boost (XGBoost) was implemented to classify between three POSA phenotypes, i.e., positional patients (PP), including supine-predominant OSA (spOSA), and supine-isolated OSA (siOSA), and non-positional patients (NPP). A total of 861 individuals with OSA from the multi ethnic study of atherosclerosis (MESA) dataset were included in the study. Overall, 43 OBMs were computed for supine and non-supine positions and used as input features together with demographic and clinical information (META). Feature selection, using mRMR, was implemented, and nested cross validation was used for the model’s performance evaluation. Results. The best performance for the multiclass classification yielded a median weighted F1 of 0.79 with interquartile range (IQR) of 0.06. Binary classification between PP to NPP achieved weighted F1 of 0.87 (0.04). Conclusion. Using OBMs computed in PP and NPP with OSA, it is possible to distinguish between the different phenotypes of POSA. This data-driven algorithm may be embedded in portable home sleep tests.
Application of de-shape synchrosqueezing to estimate gait cadence from a single-sensor accelerometer placed in different body locations
Authors: Wu Hau-Tieng , Harezlak Jaroslaw 
Published: April 2023

Abstract

Objective. Commercial and research-grade wearable devices have become increasingly popular over the past decade. Information extracted from devices using accelerometers is frequently summarized as ‘number of steps’ (commercial devices) or ‘activity counts’ (research-grade devices). Raw accelerometry data that can be easily extracted from accelerometers used in research, for instance ActiGraph GT3X+, are frequently discarded. Approach. Our primary goal is proposing an innovative use of the de-shape synchrosqueezing transform to analyze the raw accelerometry data recorded from a single sensor installed in different body locations, particularly the wrist, to extract gait cadence when a subject is walking. The proposed methodology is tested on data collected in a semi-controlled experiment with 32 participants walking on a one-kilometer predefined course. Walking was executed on a flat surface as well as on the stairs (up and down). Main results. The cadences of walking on a flat surface, ascending stairs, and descending stairs, determined from the wrist sensor, are 1.98 ± 0.15 Hz, 1.99 ± 0.26 Hz, and 2.03 ± 0.26 Hz respectively. The cadences are 1.98 ± 0.14 Hz, 1.97 ± 0.25 Hz, and 2.02 ± 0.23 Hz, respectively if determined from the hip sensor, 1.98 ± 0.14 Hz, 1.93 ± 0.22 Hz and 2.06 ± 0.24 Hz, respectively if determined from the left ankle sensor, and 1.98 ± 0.14 Hz, 1.97 ± 0.22 Hz, and 2.04 ± 0.24 Hz, respectively if determined from the right ankle sensor. The difference is statistically significant indicating that the cadence is fastest while descending stairs and slowest when ascending stairs. Also, the standard deviation when the sensor is on the wrist is larger. These findings are in line with our expectations. Conclusion. We show that our proposed algorithm can extract the cadence with high accuracy, even when the sensor is placed on the wrist.
Charged-particle transport models for global models
Authors: Alves L L , Tejero-del-Caz A 
Published: April 2023

Abstract
This work analyses the influence of different charged-particle transport models on the global modeling of low-temperature plasmas. The simulations use the LisbOn KInetics simulation tool, calculating the charged-particle loss frequency due to transport with various formulations, categorized into two large groups: ambipolar-based and h-factor transport models. The models are applied to the description of (i) a DC discharge in oxygen (as example of an electronegative multi-ion plasma), at low to intermediate pressures, adopting a validated kinetic scheme as reference model; (ii) a microwave discharge in helium (as example of an electropositive multi-ion plasma), from low to atmospheric pressures, proposing and validating an updated kinetic scheme that bridges two previous models, adjusted separately for low to intermediate pressures and for atmospheric pressure. The analysis shows that using different charged-particle transport models can result in uncertainties of 20%–60% and 8%–115% in the discharge characteristics of oxygen and helium, respectively, with larger dispersion at low pressure and low electron density. The spreading in the results is observed also in the densities of the main plasma species, corresponding to uncertainties up to

60
%

and within 50%–150% in oxygen and helium, respectively. Since transport accounts for more than

50
%

of total charge losses, this mechanism should always be part of the quantitative sensitivity analysis of a kinetic scheme, considering several models with different validity domains, according to the electro-positive/-negative single-/multi-ion plasma under study and the low/high pressure conditions considered.
Spacetime foam: a review
Authors: Carlip S 
Published: April 2023

AbstractMore than 65 years ago, John Wheeler suggested that quantum uncertainties of the metric would be of order one at the Planck scale, leading to large fluctuations in spacetime geometry and topology, which he termed ‘spacetime foam.’ In this review I discuss various attempts to implement this idea and to test it, both theoretically and, to a lesser extent, observationally.
A novel MXene-based high-performance flexible pressure sensor for detection of human motion
Authors: Zhang Zhidong , Zhang Qingchao , Zhang Huinan , Li Bo , Zang Junbin , Zhao Xuefeng , Zhao Xiaolong , Xue Chenyang 
Published: April 2023

Abstract
Flexible pressure sensors possess superior conformal ability, great flexibility, and strong biocompatibility than conventional silicon-based sensors, thereby widely used in electronic skin, wearable devices, and robotic tactile sensing, among other fields. However, flexible pressure sensors are still limited by many challenges related to extended linearity and high sensitivity. In this paper, MXene with a loose layered structure was employed to fabricate high-performance flexible piezoresistive sensors comprising polydimethylsiloxane (PDMS) film with cylindrical microstructure, multilayer Ti3C2T
x
-MXene film, and interdigital electrodes. A cylindrical microstructured silicon wafer was designed and processed by deep silicon etching process, and PDMS flexible substrate was obtained by two inversions as the pressure sensing layer. The resulting flexible pressure sensor exhibited excellent performance in terms of excellent sensitivity up to 519 kPa−1 in the large detection range of 0–8 kPa coupled with great linearity, a response time of 62.7 ms, and a recovery time of 62.8 ms. The high sensitivity was associated with the compression of the interlayer spacing of multilayer MXene nanosheets. In addition, a single flexible pressure sensor and integrated array were utilized to detect the human physical signals and quantitative measurements of pressure distributions. Overall, these findings provided experimental verification for the design and manufacturing of highly sensitive and linear flexible pressure sensors.
Design of a programmable particle filtering medium using a novel auxetic metamaterial
Authors: Ali Hafiz M A , Abdi Meisam , Zahedi S Abolfazl , Sun Yong 
Published: April 2023

Abstract
This study presents the design and development of a 2D auxetic filtering medium with programmable geometric features specifically designed to vary under in-plane tensile strain. This feature empowers the filtering medium to control the particles separation. A novel design and optimisation algorithm developed in Matlab® determines the final optimized geometry of the filtering medium based on the desired particle size input. Upon thorough numerical investigation, an empirical relationship between the linear elastic in-plane tensile strain and aperture size of the proposed metamaterial is revealed. This empirical relation can be used in mechatronic and control systems to steer the proposed filtering medium. A prototype of such filtering medium capable of classification of particles of size 4 mm to 4.5 mm, when subjected to linear strain, is fabricated through fused deposition modelling process. The developed geometry configurations in this research are scalable, providing a potential cost-effective and efficient solution for industrial applications including reconfigurable filtration and segregation systems.
Cyclotron radiation from shaped electron wavefunctions
Authors: Khalaf Majed , Rivera Nicholas , Kaminer Ido 
Published: April 2023

Abstract
Recent years have shown increasing interest in understanding the role of the wavefunction of a quantum source on the characteristics of its emitted radiation. In this work, we demonstrate that shaping the wavefunction of the source can drastically change the instantaneous emission. We exemplify this concept by examining an electron in cyclotron motion, calculating the angular power distribution of emission by an electron in a Schrodinger cat state. The emitted cyclotron radiation reveals a breakdown of classical–quantum correspondence. The short-time dynamics of the radiation process shows deviations in the power and electron trajectory that disappear at long times, where the predictions of classical electrodynamics are recovered.
Dynamical N-photon bundle emission
Authors: Zou F , Li Y , Liao J-Q 
Published: April 2023

Abstract
Engineering multiphoton resources is of importance in quantum metrology, quantum lithography, and biological sensing. Here we propose a concept of dynamical emission of N strongly-correlated photons. This is realized in a circuit quantum electrodynamical system driven by two Gaussian-pulse sequences. The underlying physical mechanism relies on the stimulated Raman adiabatic passage that allows efficient and selective preparation of target multiphoton states. Assisted by the photon decay, a highly pure N-photon bundle emission takes place in this system. In particular, the dynamical N-photon bundle emission can be tuned by controlling the time interval between consecutive pulses so that the device behaves as an N-photon gun, which can be triggered on demand. Our work opens up a route to achieve multiphoton source devices, which have wide potential applications in quantum information processing and quantum metrology.
An efficient numerical method for the time-fractional distributed order nonlinear Klein–Gordon equation with shifted fractional Gegenbauer multi-wavelets method
Authors: Ghuraibawi Amer A , Marasi H R , Derakhshan M H , Kumar Pushpendra 
Published: April 2023

Abstract
In this paper, we propose an effective numerical method using two-dimensional Shifted fractional-order Gegenbauer Multi-wavelets to find the approximate solutions of the time-fractional distributed order non-linear partial differential equations. The method is applied to numerically solve the fractional distributed order non-linear Klein–Gordon equation. We derive an exact formula for the Riemann-Liouville fractional integral operator for the Shifted fractional Gegenbauer Multi-wavelets. Applying function approximations obtained by this method turns the considered equation into a system of algebraic equations. Error estimation and convergence analysis of the method are also studied. Some numerical examples are included to show and check the effectiveness of the proposed method.
Measurement-based quantum computation using two-component BECs
Authors: Fujii Genji 
Published: April 2023

Abstract
Measurement-based quantum computation (MBQC) using two-component Bose–Einstein condensates (BECs) is proposed in this paper. An arbitrary state for one logical qubit is obtained by three-body measurement. Furthermore, a method is proposed for implementing controlled-Z gates for logical qubits in a graph state using BEC qubits and controlled-Z gates for BEC-type encoding. Results showed that the state after a measurement depends on the number of particles. These results pave the way for a novel quantum computing process based on particle control.
Right-handed sneutrino and gravitino multicomponent dark matter in light of neutrino detectors
Authors: Kim Jong Soo , López-Fogliani Daniel E. , Perez Andres D. , Ruiz de Austri Roberto 
Published: April 2023

Abstract
We investigate the possibility that right-handed (RH) sneutrinos and gravitinos can coexist and explain the dark matter (DM) problem. We compare extensions of the minimal supersymmetric standard model (MSSM) and the next-to-MSSM (NMSSM) adding RH neutrinos superfields, with special emphasis on the latter. If the gravitino is the lightest supersymmetric particle (LSP) and the RH sneutrino the next-to-LSP (NLSP), the heavier particle decays to the former plus left-handed (LH) neutrinos through the mixing between the scalar partners of the LH and RH neutrinos.
However, the interaction is suppressed by the Planck mass, and if the LH-RH sneutrino mixing parameter is small, ≪ O(10-2), a long-lived RH sneutrino NLSP is possible even surpassing the age of the Universe.
As a byproduct, the NLSP to LSP decay produces monochromatic neutrinos in the ballpark of current and planned neutrino telescopes like Super-Kamiokande, IceCube and Antares that we use to set constraints and show prospects of detection.
In the NMSSM+RHN, assuming a gluino mass parameter M
3 = 3 TeV we found the following lower limits for the gravitino mass m
3/2 ≳ 1-600 GeV and the reheating temperature T
R ≳ 105 - 3 × 107 GeV, for mν̃
R
10-800 GeV. If we take M
3 = 10 TeV, then the limits on TR
are relaxed by one order of magnitude.