bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sampling rate requirement for accurate calculation of heart rate and its variability based on the electrocardiogram
Authors: Zhou Yuanyuan , Lindsey Bryndan , Snyder Samantha , Bell Elizabeth , Reider Lucy , Vignos Michael , Bar-Kochba Eyal , Mousavi Azin , Parreira Jesse , Hanley Casey , Shim Jae Kun , Hahn Jin-Oh 
Published: February 2024

Abstract

Objective. To develop analytical formulas which can serve as quantitative guidelines for the selection of the sampling rate for the electrocardiogram (ECG) required to calculate heart rate (HR) and heart rate variability (HRV) with a desired level of accuracy. Approach. We developed analytical formulas which relate the ECG sampling rate to conservative bounds on HR and HRV errors: (i) one relating HR and sampling rate to a HR error bound and (ii) the others relating sampling rate to HRV error bounds (in terms of root-mean-square of successive differences (RMSSD) and standard deviation of normal sinus beats (SDNN)). We validated the formulas using experimental data collected from 58 young healthy volunteers which encompass a wide HR and HRV ranges through strenuous exercise. Main results. The results strongly supported the validity of the analytical formulas as well as their tightness. The formulas can be used to (i) predict an upper bound of inaccuracy in HR and HRV for a given sampling rate in conjunction with HR and HRV as well as to (ii) determine a sampling rate to achieve a desired accuracy requirement at a given HR or HRV (or its range). Significance. HR and its variability (HRV) derived from the ECG have been widely utilized in a wide range of research in physiology and psychophysiology. However, there is no established guideline for the selection of the sampling rate for the ECG required to calculate HR and HRV with a desired level of accuracy. Hence, the analytical formulas may guide in selecting sampling rates for the ECG tailored to various applications of HR and HRV.
Nonlinear dynamic morphing of conical bistable dielectric elastomer actuator
Authors: Zhang Jian , Zhao Jian , Wang Xuefeng , Wang Hongyu , Liu Pengbo , Huang Yu 
Published: February 2024

Abstract
The bistable dielectric elastomer actuator (BDEA) possesses two stable positions which offers notable advantages of stable-state self-maintenance, fast response, and threshold snap-through characteristic in comparison with conventional dielectric elastomers. However, the strong nonlinearity induced by the coupling among materials, structure, and electrostatic fields greatly affect the dynamic response and gives rise to stability issues. Hence, a novel BDEA is proposed by introducing DEA film centrally connected with one mass block and linear spring, and the bistability can be adjusted by applying external voltage. A nonlinear dynamical model considering the electro-mechanical coupling effects is established using the Euler-Lagrange method, with which the snap-through procedure is theoretically analyzed and validated through the analytic method and finite element method. The influences of the electric actuation and structural parameters on the number of stable states and natural frequency are analyzed. Additionally, the supercritical pitchfork bifurcation and saddle-node bifurcation are investigated through dynamic analysis under forced vibration. Furthermore, the ranges of electrical actuation parameters can be determined for preventing the bifurcation phenomena under parametric excitations. Moreover, an active morphing strategy for achieving nonlinear dynamic morphing between steady states of BDEA using drive voltage is obtained, thereby enhancing the versatility of conical BDEA.
Multimode auxetic piezoelectric energy harvester for low-frequency vibration
Authors: He Longfei , Kurita Hiroki , Narita Fumio 
Published: February 2024

Abstract
Herein, we propose a piezoelectric energy harvester (PEH) capable of vibrating in multi-degrees-of-freedom. The resonant frequency, working bandwidth, and output power of the PEH were improved by introducing an auxetic structure (AS). The proposed PEH exhibited a symmetric serpentine structure with a doubly clamped configuration comprising several proof masses at the junctions. Finite element method (FEM) simulation was conducted to investigate the characteristics of an AS PEH and a plain-structure PEH. Prototypes of the PEHs were manufactured by three-dimensional (3D) printing technology, and their performance was evaluated through vibrational energy-harvesting experimental tests. The results showed that introducing the AS reduced the first and second resonant frequencies by 49% and 44%, respectively, considerably improved the output power in the first mode (up to 2548%) and narrowed the frequency bandgap between the first two resonance modes by 29%. The proposed multimode AS PEH can operate in a low-frequency environment of less than 20 Hz. Finally, we discussed several ways of optimizing the AS. It has been found that the PEH performance could be further improved by selecting a reasonable thickness for the AS, increasing the number of periodic unit cells, and using an AS with a variable cross-section unit cell.
The effect of multiple cooling channels on the formation of dark compact objects
Authors: Bramante Joseph , Diamond Melissa , Kim J. Leo 
Published: February 2024

Abstract
A dissipative dark sector can result in the formation of compact objects with masses comparable to stars and planets. In this work, we investigate the formation of such compact objects from a subdominant inelastic dark matter model, and study the resulting distributions of these objects. In particular, we consider cooling from dark Bremsstrahlung and a rapid decay process that occurs after inelastic upscattering. Inelastic transitions introduce an additional radiative processes which can impact the formation of compact objects via multiple cooling channels. We find that having multiple cooling processes changes the mass and abundance of compact objects formed, as compared to a scenario with only one cooling channel. The resulting distribution of these astrophysical compact objects and their properties can be used to further constrain and differentiate between dark sectors.
Development and implementation of an automated four-terminal-pair Josephson impedance bridge
Authors: Pimsut Yaowaret , Bauer Stephan , Kraus Marco , Behr Ralf , Kruskopf Mattias , Kieler Oliver , Palafox Luis 
Published: February 2024

Abstract
The four-terminal-pair impedance bridge using pulse-driven Josephson voltage standards at PTB has been fully automated. The same bridge configuration was employed to determine R:R and C:C ratios over the frequency range between 53 Hz to 50 kHz. Only minor changes are needed to cover this large frequency range: amplifiers to increase the sensitivity of the current detections for low frequencies and signal generators with higher resolution at high frequencies to reach 50 kHz. Furthermore, the bridge can be operated for quadrature R:(1/ωC) measurements. The combined standard uncertainties (k = 1) for the new bridge were evaluated for all operating frequencies. They reach 2 nF F−1 and 4 nΩ Ω−1 at 1233.15 Hz. At this frequency, the 10 nF:10 nF ratio matched the ratio of PTB’s bridge employing inductive voltage dividers within 1 nF F−1 ± 3 nF F−1 (k = 1). Over 45 days, the 10 nF:10 nF ratio deviated less than −2 nF F−1 ± 3 nF F−1 (k = 1). The 12.9 kΩ:10 kΩ ratio at 53 Hz differed −2 nΩ Ω−1 ± 5 nΩ Ω−1 (k = 1) from the DC ratio measured by the PTB’s cryogenic current comparator bridge. Using a 12.9 kΩ resistance standard and a graphene AC quantum Hall resistance, the 10 nF:10 nF ratios derived from quadrature measurements agreed with the PTB’s inductive voltage divider bridge better than 9 nF F−1 ± 13 nF F−1 (k = 1).
Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes
Authors: Verardo Claudio , Mele Leandro Julian , Selmi Luca , Palestri Pierpaolo 
Published: February 2024

Abstract

Objective. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing. Approach. We present a finite-element model describing a PEDOT:PSS-coated microelectrode (herein, simply ionic actuator) able to release potassium and thus modulate the activity of a cortical neuron in an in-vitro-like setting. The dynamics of ions in the ionic actuator, the neural membrane, and the cellular fluids are solved self-consistently. Main results. We showcase the capability of the model to describe on a physical basis the modulation of the intrinsic excitability of the cell and of the synaptic transmission following the electro-ionic stimulation produced by the actuator. We consider three case studies for the ionic actuator with different levels of selectivity to potassium: ideal selectivity, no selectivity, and selectivity achieved by embedding ionophores in the polymer. Significance. This work is the first step toward a comprehensive computational framework aimed to investigate novel neuromodulation devices targeting specific ionic species, as well as to optimize their design and performance, in terms of the induced modulation of neural activity.
Study of cosmogenic activation above ground of Ar for DarkSide-20k
Authors: Cebrián S. ,   the DarkSide-20k collaboration
Published: February 2024

Abstract
The production of long-lived radioactive isotopes due to the exposure to cosmic rays on the Earth's surface is an hazard for experiments searching for rare events like the direct detection of galactic dark matter particles. The use of large amounts of liquid argon is foreseen in different projects, like the DarkSide-20k experiment, intended to look for Weakly Interacting Massive Particles at the Laboratori Nazionali del Gran Sasso. Here, results from the study of the cosmogenic activation of argon carried out in the context of DarkSide-20k are presented. The induced activity of several isotopes, including 39Ar, and the expected counting rates in the detector have been deduced, considering exposure conditions as realistic as possible.
Model and analysis of the data readout architecture for the ITS3 ALICE Inner Tracker System
Authors: Viqueira Rodriguez M. ,   the ALICE collaboration
Published: February 2024

Abstract
The ALICE collaboration is developing the Inner Tracker System 3 (ITS3), a novel detector that exploits the stitching technique to construct single-die monolithic pixel sensors of up-to 266 mm × 93 mm. ITS3 requires all hits from a particle flux of 5.75 MHz/cm2 to be transmitted on-chip to one of the sensor edges. This on-chip readout must balance the resources of power consumption, dead area, and readout performance by tuning different design parameters such as on-chip memories or on-chip links bandwidth. For doing so, a model of the ITS3 on-chip readout architecture will be presented. This model combines an accurate simulation of the particle flux fluctuations expected in ALICE with a clock-accurate digital readout simulator, combining high accuracy with fast code in terms of simulation speed.
Measurement of radon emanation and impurity adsorption from argon gas using ultralow radioactive zeolite
Authors: Ogawa Hiroshi , Iyoki Kenta , Matsukura Minoru , Wakihara Toru , Abe Ko , Miuchi Kentaro , Umehara Saori 
Published: February 2024

Abstract
The amount of radioactive impurities contaminated in the detector gases is required to be
kept at a very low level for rare event particle physics such as dark matter and neutrino
observation experiments. Zeolite is a well-known class of materials and is one of the possible
candidates for removing impurities from gases. At the same time, the amount of radioactive
impurities released from the adsorbent material needs to be sufficiently small. In this paper, a
development of a new ultralow radioactive zeolite as a product of the selection of ultralow
radioactive materials is reported. Results on the radon emanation and impurity adsorption from
argon gas measurements are also described.
The development of segmented electrode thin-film parallel plate avalanche counter (PPAC)
Authors: Li Zhijie , Wei Xianglun , Yang Yuansheng , He Zhoubo , He Zhixuan , Wen Xiangjie , Deng Yubin , Yang Herun , Lu Chengui , Ma Peng , He Zhiyong , Xiao Zhigang , Hu Rongjiang , Duan Limin , Qiu Tianli 
Published: February 2024

Abstract
In order to improve the counting rate and position
resolution of the Parallel Plate Avalanche Counter (PPAC) within the
Compact Spectrometer for Heavy Ion Experiment, a new strip
film-structured PPAC has been developed. The developped PPAC
detector consists of three layers of film electrodes. The upper and
lower layers which serve as the anodes are comprised of
self-developed strip film electrodes, oriented perpendicularly to
each other. The middle layer utilizes double-sided aluminized Mylar
film as the cathode. There is a 3 mm gap between each layer, and
the detector has an effective area of 76 mm×
76 mm. Operating in a low-pressure environment with isobutane gas
as the working medium, the performance of the PPAC has been measured
using a 5.486 MeV α radiation source. The measurement
results indicate that the overall position resolution of the PPAC
attains approximately 380 μm, and the position resolution
improves to 300 μm when using slit width correction. Finally,
the Monte Carlo simulation has been performed to simulate the
distribution of electrons generated by the detector's ionization
under the same conditions on the anode readout strip. The simulation
results closely matches the observed multiplicity of hit anode
readout strips in measurement.
Silica silanization graft-strengthening bone cement poly(methyl methacrylate): process and dynamic mechanical properties
Authors: Shi Shih-Chen , Zeng Xin-Xing 
Published: February 2024

Abstract
Poly(methyl methacrylate) (PMMA) has garnered widespread interest as a potential polymer-based bone cement (BC). However, many challenges in its mechanical properties, especially elongation behavior, need to be overcome. This study focused on PMMA reinforcement with SiO2 particles from two different perspectives, i.e., particle size (nano, submicro, and micro) and surface silanization of the SiO2 particles. Silanization improves the bonding between the additive and polymer matrix, which should improve the dynamic mechanical properties of the composite. The presence of silane bonding was confirmed through Fourier transform infrared spectroscopy, chemical titration, and x-ray photoelectron spectroscopy, and it was determined that 6000 μmol g−1 of silane was successfully coated onto the SiO2 particles. Reinforcement with silanized SiO2 nanoparticles increased elongation at break by 136%. The mechanism by which the size and silanization of the SiO2 additive affected elongation behavior was also discussed in detail.
Carbide precipitation during tempering of hybrid steel 60
Authors: Zheng Zhuo , Lei Min , Huang Chaowen , Wan Mingpan 
Published: February 2024

Abstract
The effects of carbide precipitation on mechanical performance of Hybrid Steel 60, known as a novel bearing steel, have not been investigated. In this study, the austenite transformation temperatures of Hybrid Steel 60 during heating were revealed by the thermal expansion curve. The temperature and effective activation energy of the second phase precipitation were determined by the differential scanning calorimetry (DSC) curve. Different solid solution structures after austenitization were detected using various cooling rates. The solubility temperature was determined based on hardness and residual austenite content. The carbides precipitated at the peak temperature were qualitatively identified using XRD. It was discovered that the temperature points Ac1 and Ac3 of the steel were 786 °C and 864 °C, respectively. In addition, the effect of solid solution temperature on quenching hardness is minimal, while the cooling rate has a greater impact on hardness, reaching a peak at 5 °C s−1. The primary carbide phase in Hybrid Steel 60 is the M7C3 and VC. When the temperature ranges from 500 °C to 550 °C, M23C6 begins to precipitate. As a result, after tempering at 525 °C, the hardness peak value reached 566 HV.
Growth of telecom C-band In(Ga)As quantum dots for silicon quantum photonics
Authors: Vijayan Ponraj , Joos Raphael , Werner Marco , Hirlinger-Alexander Jakob , Seibold Matthias , Vollmer Sergej , Sittig Robert , Bauer Stephanie , Braun Fiona , Portalupi Simone Luca , Jetter Michael , Michler Peter 
Published: February 2024

Abstract
Photonic integrated circuits (PICs) based on the silicon-on-insulator platform currently allow high-density integration of optical and electro-optical components on the same chip. This high complexity is also transferred to quantum PICs, where non-linear processes are used for the generation of quantum light on the silicon chip. However, these intrinsically probabilistic light emission processes pose challenges to the ultimately achievable scalability. Here, an interesting solution would be employing on-demand sources of quantum light based on III–V platforms, which are nonetheless very complex to grow directly on silicon. In this paper, we show the integration of InAs quantum dots (QDs) on silicon via the growth on a wafer-bonded GaAs/Si template. To ensure emission in the telecom C-band (∼1550 nm), a metamorphic buffer layer approach is utilized. We show that the deposited single QDs show similar performance to their counterparts directly grown on the well-established GaAs platform. Our results demonstrate that on-demand telecom emitters can be directly and effectively integrated on silicon, without compromises on the performances of either the platforms.
Deep centroid: a general deep cascade classifier for biomedical omics data classification
Authors: Xie Kuan , Hou Yuying , Zhou Xionghui 
Published: February 2024

Abstract

Motivation
Classification of samples using biomedical omics data is a widely used method in biomedical research. However, these datasets often possess challenging characteristics, including high dimensionality, limited sample sizes, and inherent biases across diverse sources. These factors limit the performance of traditional machine learning models, particularly when applied to independent datasets.

Results
To address these challenges, we propose a novel classifier, Deep Centroid, which combines the stability of the nearest centroid classifier and the strong fitting ability of the deep cascade strategy. Deep Centroid is an ensemble learning method with a multi-layer cascade structure, consisting of feature scanning and cascade learning stages that can dynamically adjust the training scale. We apply Deep Centroid to three precision medicine applications—cancer early diagnosis, cancer prognosis, and drug sensitivity prediction—using cell-free DNA fragmentations, gene expression profiles, and DNA methylation data. Experimental results demonstrate that Deep Centroid outperforms six traditional machine learning models in all three applications, showcasing its potential in biological omics data classification. Furthermore, functional annotations reveal that the features scanned by the model exhibit biological significance, indicating its interpretability from a biological perspective. Our findings underscore the promising application of Deep Centroid in the classification of biomedical omics data, particularly in the field of precision medicine.

Availability and implementation
Deep Centroid is available at both github (github.com/xiexiexiekuan/DeepCentroid) and Figshare (https://figshare.com/articles/software/Deep_Centroid_A_General_Deep_Cascade_Classifier_for_Biomedical_Omics_Data_Classification/24993516).
StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides
Authors: Wang Ding , Jin Junru , Li Zhongshen , Wang Yu , Fan Mushuang , Liang Sirui , Su Ran , Wei Leyi 
Published: February 2024

Abstract

Motivation
Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next generation of anti-diabetic drugs, known as dipeptidyl peptidase IV inhibitory peptides (DPP-IV-IPs). However, the discovery of these promising drugs has been restricted due to the lack of effective peptide-mining tools.

Results
Here, we presented StructuralDPPIV, a deep learning model designed for DPP-IV-IP identification, which takes advantage of both molecular graph features in amino acid and sequence information. Experimental results on the independent test dataset and two wet experiment datasets show that our model outperforms the other state-of-art methods. Moreover, to better study what StructuralDPPIV learns, we used CAM technology and perturbation experiment to analyze our model, which yielded interpretable insights into the reasoning behind prediction results.

Availability and implementation
The project code is available at https://github.com/WeiLab-BioChem/Structural-DPP-IV.
Prognostic nomogram model for selecting between transarterial chemoembolization plus lenvatinib, with and without PD-1 inhibitor in unresectable hepatocellular carcinoma
Authors: Sheng Ye , Wang Qing , Liu HaiFeng , Wang Qi , Chen WenHua , Xing Wei 
Published: February 2024

Abstract

Objectives
To establish and verify a prognostic nomogram model for selecting in unresectable hepatocellular carcinoma (uHCC) treated by transarterial chemoembolization plus lenvatinib (TACE-L) with or without PD-1 inhibitor.

Methods
Data of 241 uHCC patients who underwent TACE-L (n = 128) and TACE-L plus PD-1 inhibitor (TACE-L-P, n = 113) were retrospectively reviewed. The differences in tumour responses, progression-free survival (PFS), overall survival (OS), and adverse events (AEs) between two groups were compared, and a prognostic nomogram model was established based on independent clinical-radiologic factors and confirmed by Cox regression analysis for predicting PFS and OS. The treatment selection for uHCC patients was stratified by the nomogram score.

Results
Compared to TACE-L, TACE-L-P presented prolonged PFS (14.0 vs. 9.0 months, P &lt; .001), longer OS (24.0 vs. 15.0 months, P &lt; .001), and a better overall objective response rate (54.0% vs. 32.8%, P = .001). There was no significant difference between the rate of AEs in the TACE-L-P and the TACE-L (56.64% vs. 46.09%, P = .102) and the rate of grade ≥ 3 AEs (11.50% vs. 9.38%, P = .588), respectively. The nomogram model presented good discrimination, with a C-index of 0.790 for predicting PFS and 0.749 for predicting OS. Patients who underwent TACE-L and obtained a nomogram score &gt;9 demonstrated improved 2-year PFS when transferred to TACE-L-P, and those with a nomogram ≤25 had better 2-year OS when transferred to TACE-L-P.

Conclusions
TACE-L-P showed significant improvements in efficiency and safety for uHCC patients compared with TACE-L. The nomogram was useful for stratifying treatment decisions and selecting a suitable population for uHCC patients.

Advances in knowledge
Prognostic nomogram model is of great value in predicting individualized survival benefits for uHCC patients after TACE-L or/and TACE-L-P. And the nomogram was helpful for selection between TACE-L-P and TACE-L among uHCC patients.