bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the impact of smoking habits through photoplethysmography analysis
Authors: Qananwah Qasem , Khader Ateka , Al-Hashem Munder , Mumani Ahmad , Dagamseh Ahmad 
Published: January 2024

Abstract
Smoking is widely recognized as a significant risk factor in the progression of arterial stiffness and cardiovascular diseases. Valuable information related to cardiac arrhythmias and heart function can be obtained by analyzing biosignals such as the electrocardiogram (ECG) and the photoplethysmogram (PPG). The PPG signal is a non-invasive optical technique that can be used to evaluate the changes in blood volume, and thus it can be linked to the health of the vascular system. Objective. In this study, the impact of three smoking habits—cigarettes, shisha, and electronic cigarettes (e-cigarettes)—on the features of the PPG signal were investigated. Approach. The PPG signals are measured for 45 healthy smokers before, during, and after the smoking session and then processed to extract the morphological features. Quantitative statistical techniques were used to analyze the PPG features and provide the most significant features of the three smoking habits. The impact of smoking is observed through significant changes in the features of the PPG signal, indicating blood volume instability. Main results. The results revealed that the three smoking habits influence the characteristics of the PPG signal significantly, which presentseven after 15 min of smoking. Among them, shisha has the greatest impact on PPG features, particularly on heart rate, systolic time, augmentation index, and peak pulse interval change. In contrast, e-cigarettes have the least effect on PPG features. Interestingly, smoking electronic cigarettes, which many participants use as a substitute for traditional cigarettes when attempting to quit smoking, has nearly a comparable effect to regular smoking. Significance. The findings suggest that individuals who smoke shisha are more likely to develop cardiovascular diseases at an earlier age compared to those who have other smoking habits. Understanding the variations in the PPG signal caused by smoking can aid in the early detection of cardiovascular disorders and provide insight into cardiac conditions. This ultimately contributes to the prevention of the development of cardiovascular diseases and the development of a health screening system.
Generation of meter-scale hydrogen plasmas and efficient, pump-depletion-limited wakefield excitation using 10 GeV electron bunches
Authors: Zhang C , Storey D , San Miguel Claveria P , Nie Z , Marsh K A , Hogan M , Mori W B , Adli E , An W , Ariniello R , Cao G J , Clarke C , Corde S , Dalichaouch T , Doss C E , Emma C , Ekerfelt H , Gerstmayr E , Gessner S , Hansel C , Knetsch A , Lee V , Li F , Litos M , O’Shea B , White G , Yocky G , Zakharova V , Joshi C 
Published: January 2024

Abstract
High repetition rates and efficient energy transfer to the accelerating beam are important for a future linear collider based on the beam-driven plasma wakefield acceleration scheme (PWFA-LC). This paper reports the first results from the Plasma Wakefield Acceleration Collaboration (E300) that are beginning to address both of these issues using the recently commissioned FACET-II facility at SLAC national accelerator laboratory. We have generated meter-scale hydrogen plasmas using time-structured 10 GeV electron bunches from FACET-II, which hold the promise of dramatically increasing the repetition rate of PWFA by rapidly replenishing the gas between each shot compared to the hitherto used lithium plasmas that operate at 1–10 Hz. Furthermore, we have excited wakes in such plasmas that are suitable for high gradient particle acceleration with high drive-bunch to wake energy transfer efficiency- a first step in achieving a high overall energy transfer efficiency. We have done this by using time-structured electron drive bunches that typically have one or more ultra-high current (

>

30 kA) femtosecond spike(s) superimposed on a longer (∼0.4 ps) lower current (

<

10 kA) bunch structure. The first spike effectively field-ionizes the gas and produces a meter-scale (30–160 cm) plasma, whereas the subsequent beam charge creates a wake. The length and amplitude of the wake depends on the longitudinal current profile of the bunch and plasma density. We find that the onset of pump depletion, when some of the drive beam electrons are nearly fully depleted of their energy, occurs for hydrogen pressure

⩾

1.5 Torr. We also show that some electrons in the rear of the bunch can gain several GeV energies from the wake. These results are reproduced by particle-in-cell simulations using the QPAD code. At a pressure of ∼2 Torr, simulation results and experimental data show that the beam transfers about 60% of its energy to the wake.
Low-resistive gate module for RF GaN-HFETs by electroplating
Authors: Yazdani H , Thies A , Stützle P , Bengtsson O , Hilt O , Heinrich W , Würfl J 
Published: January 2024

Abstract
This paper presents a novel approach for reducing the gate resistance (R
g) of K and Ka-band GaN HFETs with 150 nm gate length through a new gate metallization technique. The method involves increasing the gate cross-section via galvanic metallization using FBH’s Ir-sputter gate technology, which allows an increase in gate metal thickness from the current 0.4 μm to approximately 1.0 μm for the transistors under investigation. This optimization leads to a substantial 50% reduction in gate series resistance, resulting in significant improvements in the RF performance. Specifically, the devices achieve 20% higher output power density and 10% better power-added efficiency at 20 GHz and V
ds = 20 V. The decreased gate resistance enables new degrees of freedom in design, such as longer gate fingers and/or shorter gate lengths, for more efficient power cells operating in this frequency range.
On the coupling of magnetic moments to superconducting quantum interference devices
Authors: Linek J , Wyszynski M , Müller B , Korinski D , Milošević M V , Kleiner R , Koelle D 
Published: January 2024

Abstract
We investigate the coupling factor φ

µ
that quantifies the magnetic flux Φ per magnetic moment µ of a point-like magnetic dipole that couples to a superconducting quantum interference device (SQUID). Representing the dipole by a tiny current-carrying (Amperian) loop, the reciprocity of mutual inductances of SQUID and Amperian loop provides an elegant way of calculating

ϕ
μ

(
r
,

e
ˆ

μ

)

vs. position

r

and orientation

e
ˆ

μ

of the dipole anywhere in space from the magnetic field

B
J

(
r
)

produced by a supercurrent circulating in the SQUID loop. We use numerical simulations based on London and Ginzburg–Landau theory to calculate φ

µ
from the supercurrent density distributions in various superconducting loop geometries. We treat the far-field regime (

r
≳
a
=

inner size of the SQUID loop) with the dipole placed on (oriented along) the symmetry axis of circular or square shaped loops. We compare expressions for φ

µ
from simple filamentary loop models with simulation results for loops with finite width w (outer size A > a), thickness d and London penetration depth λ
L and show that for thin (

d
≪
a

) and narrow (w < a) loops the introduction of an effective loop size

a

eff

in the filamentary loop-model expressions results in good agreement with simulations. For a dipole placed right in the center of the loop, simulations provide an expression

ϕ
μ

(
a
,
A
,
d
,

λ

L

)

that covers a wide parameter range. In the near-field regime (dipole centered at small distance z above one SQUID arm) only coupling to a single strip representing the SQUID arm has to be considered. For this case, we compare simulations with an analytical expression derived for a homogeneous current density distribution, which yields excellent agreement for

λ

L

>
w
,
d

. Moreover, we analyze the improvement of φ

µ
provided by the introduction of a narrow constriction in the SQUID arm below the magnetic dipole.
Ordering dynamics and aging in the symmetrical threshold model
Authors: Abella David , González-Avella Juan Carlos , San Miguel Maxi , Ramasco José J 
Published: January 2024

Abstract
The so-called Granovetter–Watts model was introduced to capture a situation in which the adoption of new ideas or technologies requires a certain redundancy in the social environment of each agent to take effect. This model has become a paradigm for complex contagion. Here we investigate a symmetric version of the model: agents may be in two states that can spread equally through the system via complex contagion. We find three possible phases: a mixed one (dynamically active disordered state), an ordered one, and a heterogeneous frozen phase. These phases exist for several configurations of the contact network. Then, we consider the effect of introducing aging as a non-Markovian mechanism in the model, where agents become increasingly resistant to change their state the longer they remain in it. We show that when aging is present, the mixed phase is replaced, for sparse networks, by a new phase with different dynamical properties. This new phase is characterized by an initial disordering stage followed by a slow ordering process toward a fully ordered absorbing state. In the ordered phase, aging modifies the dynamical properties. For random contact networks, we develop a theoretical description based on an approximate master equation that describes with good accuracy the results of numerical simulations for the model with and without aging.
Information cascade prediction of complex networks based on physics-informed graph convolutional network
Authors: Yu Dingguo , Zhou Yijie , Zhang Suiyu , Li Wenbing , Small Michael , Shang Ke-ke 
Published: January 2024

Abstract
Cascade prediction aims to estimate the popularity of information diffusion in complex networks, which is beneficial to many applications from identifying viral marketing to fake news propagation in social media, estimating the scientific impact (citations) of a new publication, and so on. How to effectively predict cascade growth size has become a significant problem. Most previous methods based on deep learning have achieved remarkable results, while concentrating on mining structural and temporal features from diffusion networks and propagation paths. Whereas, the ignorance of spread dynamic information restricts the improvement of prediction performance. In this paper, we propose a novel framework called Physics-informed graph convolutional network (PiGCN) for cascade prediction, which combines explicit features (structural and temporal features) and propagation dynamic status in learning diffusion ability of cascades. Specifically, PiGCN is an end-to-end predictor, firstly splitting a given cascade into sub-cascade graph sequence and learning local structures of each sub-cascade via graph convolutional network , then adopting multi-layer perceptron to predict the cascade growth size. Moreover, our dynamic neural network, combining PDE-like equations and a deep learning method, is designed to extract potential dynamics of cascade diffusion, which captures dynamic evolution rate both on structural and temporal changes. To evaluate the performance of our proposed PiGCN model, we have conducted extensive experiment on two well-known large-scale datasets from Sina Weibo and ArXIv subject listing HEP-PH to verify the effectiveness of our model. The results of our proposed model outperform the mainstream model, and show that dynamic features have great significance for cascade size prediction.
Design and performance analysis of Si-SiGe heterostructure based double gate feedback FET
Authors: Das Subir , Katta Sai Shirov , Raj Pushp , Singh Jawar , Tiwari Pramod Kumar 
Published: January 2024

Abstract
The design and performance analysis of a Si-SiGe heterostructure-based double gate feedback field-effect transistor (HDG FBFET) are presented in this paper. The proposed HDG FBFET is capable of providing high on current (3 × 10−4 A/μm) with a large I

ON
/I

OFF
ratio (3 × 1011) and is scalable up to 20 nm channel length. Its exceptionally steep switching characteristics (SS < 1 mV/decade) and ability to switch ON/OFF at lower gate voltage due to the use of smaller band-gap material (Si1−x
Ge
x
) in channel-2 and drain regions make it suitable for use in low power applications. A significant hysteresis window of 4.99 V is also achieved by the device, which can be extremely helpful for memory applications. Moreover, a comprehensive investigation of the nature of hysteresis in relation to the different device parameters has also been carried out. The designing of the device structure and all of the electrical performance characterization have been done using the Sentaurus TCAD tool.
Hartree-fock roothaan calculations using optimized huzinaga orbitals on small molecules
Authors: Jaelani Achmad , Riyanto Fiqri A , Prayitno Teguh B , Sarwono Yanoar P 
Published: January 2024

Abstract
We present the ground-state solution of some small molecules using the Hartree–Fock Roothaan method with the optimized Huzinaga basis set. Unlike the previously used least-square methods, the contraction coefficients and exponents of Huzinaga-parameterized primitive Gaussian functions for minimal basis sets are energy-optimized at the atomic level for each molecule. Consequently, as an alternative to and in comparison with standard parameterization, the optimized orbitals significantly improve the total energy and the equilibrium bond length with substantial enhancement shown for heavier nuclei. Despite similar computational cost, the application of our scheme leads to much improved minimal-basis-set Hartree–Fock calculations with less required parameters to match the large basis set calculations. Furthermore, the localization of the electrons near the nuclei which is missing with the standard parameterization is observed with the current scheme.
Derivation of Rytov variance for jet engine-induced turbulence
Authors: Oktay Semih , Bayraktar Mert , Tabaru Timuçin Emre , Chatzinotas Symeon 
Published: January 2024

Abstract
In this study, we analytically derived the Rytov variance and scintillation index value of turbulence caused by jet engines. In addition, we analyzed the variation characteristics of the Rytov variance and scintillation index values numerically depending on the variations in turbulence strength, experimental data, and wavelength. We observe that Rytov variance reaches up to high values due to the strong turbulence resulting from high refractive index fluctuations. This result brings high-intensity fluctuations regardless of the anisotropy of the turbulence. Rytov variance is directly proportional to turbulence strength. We present scintillation index curves considering the aperture averaged case. We plot our results considering the variations in the operating wavelength, turbulence strength, and the scaling parameter. According to our results, we think that it will be useful for a system such as directed infrared countermeasure (DIRCM), which is highly sensitive and should be exposed to minimum turbulence in the field of use. Since DIRCMs transmit codes to paralyze the missile’s seeker, intensity fluctuations play a vital role during this transmission. It could reduce the performance of these systems when intensity fluctuations are high.
Crystal structure, phase transitions, dielectric and conduction mechanisms of the new long chain organic-inorganic hybrid [(CH2)8(NH3)2]CoCl4
Authors: Mostafa Mohga F , Tammam Ahmed K 
Published: January 2024

Abstract
Two dimensional long chain organic inorganic hybrid [NH3(CH2)8NH3]CoCl4, (2C8CoCl) crystallizes in triclinic system, (P1/P

1

̅

), lattice parameters: a = 8.368 Ǻ, b = 12.888 Ǻ, c = 15.045 Ǻ, α = 97.56°, β = 86.82°, γ = 89.82°, Z = 4, d = 1.44 gm cm−3 and V = 1597.3 Ǻ3. Calculated lattice potential energy (ΔUpot) and change of enthalpy (ΔH) are ΔUpot = 1835.01 (kJ mol−1) and ΔH = 425.92 (kJ mol−1) respectively. Thermal study using differential thermal analysis (DTA) and thermogravimetric analysis (TGA) confirm different phase transitions, in the temperature range (300 < T(K) < 500) with onset temperatures at T1 = 401 ± 1 K, T2 = 358.3 K and T3 = 328.9 K, such transitions are reflected in impedance spectroscopy. The transition at T3 corresponds to chain melting. Dielectric constant and ac-conductivity are studied in the temperature range (300 < T (K) < 420) and frequency range (0.11 < f(kHz) < 65). Three different thermally activated conduction regions were observed corresponding to phases I (404–414) K; (ΔEo~ 0.83 eV), II (360–400) K; (ΔEo~ 1.19 eV) and III (T < 348 K); ΔEo = (0.03 eV– 0.006 eV). Equivalent circuit derived from impedance analysis, is composed of combination of resistor and two series of parallel (R//CPE) circuits. Super-linear power law dominates for ac- conduction in the measured temperature ranges. Conduction mechanism is analyzed on the basis of different conduction models which varies as the phases change. Quantum mechanical tunneling prevails at low temperatures with s value ~0.77 while correlated barrier hopping dominates in the range (363 < T (K) < 400) with barrier height WM = 0.34 eV. Comparison to previously studied long chain hybrids [NH3(CH2)nNH3]CoCl4, n = 6 and 7 is discussed. A linear decrease in lattice potential energy and enthalpy values is observed as chain length increases. The room temperature conductivity reveals that σ
ac(2C7CoCl) > σ
ac(2C6CoCl) >σ
ac(2C8CoCl), which is discussed in light of structural characteristics.
Spin reorientation, spin switching, and magnetic compensation in Er1−xSmxFeO3 single crystals
Authors: Bairwa Dhanpal , Elizabeth Suja 
Published: January 2024

Abstract
We investigated spin reorientation, magnetic compensation and spin switching transitions in a series of high-quality single crystals of Er1−xSmxFeO3 (x = 0, 0.2, 0.4, 0.6, 0.8) prepared using the optical floating zone method. Structural and other preliminary characterizations confirmed the quality and phase purity of the crystals. Rietveld refinement of powder XRD data indicates that lattice parameters a and c increase linearly with increasing Sm concentration, whereas b remained constant. Field-cooled cooling (FCC) measurements revealed a temperature-induced spin reorientation transition (SRT) from Γ4 (Gx, Ay, Fz) to Γ2 (Fx, Cy, Gz) for all the samples. SRT temperature increased with Sm concentration and spread widely above and below room temperature. Moreover, magnetic compensation is common to all the compositions but decreases as Sm doping increases. We also observe type-I spin switching in samples with x = 0, 0.2, and 0.4 at an applied field of 60 Oe under FCC protocol, with a reduction in spin switching temperature as Sm content increased. For Sm-rich samples (x = 0.6, 0.8), spin switching was absent at 60 Oe.
EEG-based hierarchical classification of level of demand and modality of auditory and visual sensory processing
Authors: Massaeli Faghihe , Power Sarah D 
Published: January 2024

Abstract

Objective. To date, most research on electroencephalography (EEG)-based mental workload detection for passive brain-computer interface (pBCI) applications has focused on identifying the overall level of cognitive resources required, such as whether the workload is high or low. We propose, however, that being able to determine the specific type of cognitive resources being used, such as visual or auditory, would also be useful. This would enable the pBCI to take more appropriate action to reduce the overall level of cognitive demand on the user. For example, if a high level of workload was detected and it is determined that the user is primarily engaged in visual information processing, then the pBCI could cause some information to be presented aurally instead. In our previous work we showed that EEG could be used to differentiate visual from auditory processing tasks when the level of processing is high, but the two modalities could not be distinguished when the level of cognitive processing demand was very low. The current study aims to build on this work and move toward the overall objective of developing a pBCI that is capable of predicting both the level and the type of cognitive resources being used. Approach. Fifteen individuals undertook carefully designed visual and auditory tasks while their EEG data was being recorded. In this study, we incorporated a more diverse range of sensory processing conditions including not only single-modality conditions (i.e. those requiring one of either visual or auditory processing) as in our previous study, but also dual-modality conditions (i.e. those requiring both visual and auditory processing) and no-task/baseline conditions (i.e. when the individual is not engaged in either visual or auditory processing). Main results. Using regularized linear discriminant analysis within a hierarchical classification algorithm, the overall cognitive demand was predicted with an accuracy of more than 86%, while the presence or absence of visual and auditory sensory processing were each predicted with an accuracy of approximately 70%. Significance. The findings support the feasibility of establishing a pBCI that can determine both the level and type of attentional resources required by the user at any given moment. This pBCI could assist in enhancing safety in hazardous jobs by triggering the most effective and efficient adaptation strategies when high workload conditions are detected.
Modified motor unit properties in residual muscle following transtibial amputation
Authors: Rubin Noah , Hinson Robert , Saul Katherine , Filer William , Hu Xiaogang , Huang He (Helen) 
Published: January 2024

Abstract

Objective. Neural signals in residual muscles of amputated limbs are frequently decoded to control powered prostheses. Yet myoelectric controllers assume muscle activities of residual muscles are similar to that of intact muscles. This study sought to understand potential changes to motor unit (MU) properties after limb amputation. Approach. Six people with unilateral transtibial amputation were recruited. Surface electromyogram (EMG) of residual and intact tibialis anterior (TA) and gastrocnemius (GA) muscles were recorded while subjects traced profiles targeting up to 20% and 35% of maximum activation for each muscle (isometric for intact limbs). EMG was decomposed into groups of MU spike trains. MU recruitment thresholds, action potential amplitudes (MU size), and firing rates were correlated to model Henneman’s size principle, the onion-skin phenomenon, and rate-size associations. Organization (correlation) and modulation (rates of change) of relations were compared between intact and residual muscles. Main results. The residual TA exhibited significantly lower correlation and flatter slopes in the size principle and onion-skin, and each outcome covaried between the MU relations. The residual GA was unaffected for most subjects. Subjects trained prior with myoelectric prostheses had minimally affected slopes in the TA. Rate-size association correlations were preserved, but both residual muscles exhibited flatter decay rates. Significance. We showed peripheral neuromuscular damage also leads to spinal-level functional reorganizations. Our findings suggest models of MU recruitment and discharge patterns for residual muscle EMG generation need reparameterization to account for disturbances observed. In the future, tracking MU pool adaptations may also provide a biomarker of neuromuscular control to aid training with myoelectric prostheses.