bluuebunny/crossref_metadata_2025_split huggingface dataset:
A DFT study of the physical properties of novel vanadium-based half-Heusler alloys VYAl (Y = Ni,Pd, and Pt) pertinent to their optoelectronics application
Authors: Lawati Dhan Raj , Shrestha Pitamber , Sharma Shriram , Joshi Leela Pradhan , Parajuli Rajendra 
Published: June 2024

Abstract
We investigated three novel 18-valence electron count (VEC) vanadium-based half-Heusler alloys, VYAl (Y = Ni, Pd, and Pt), for their structural, mechanical, electronic, and optical properties using density functional theory (DFT). The computation was carried out employing Vienna Ab-initio Simulation Package (VASP) and all three alloys have exhibited structural, chemical, mechanical, and thermodynamic stability. We obtained the lattice constants of 5.520, 5.800, and 5.820 Å for VNiAl, VPdAl, and VPtAl, respectively. The elastic parameters imply a ductile and hard nature of the system and exhibit anisotropic behavior. Electronic band characterization demonstrated that all three alloys are semiconductors with direct narrow gaps at the Γ-point which is crucial for photovoltaic applications. In addition to that, the high density of the band states near the Fermi level indicates a promising candidate for thermoelectric conversion. The influence of SOC interaction in the system generates a small shift in the bands. From the optical response, we infer that the studied compounds have exceptional light absorption and reflection quality, making them suitable for optoelectronics purposes.
Complete analysis of the background and anisotropies of scalar-induced gravitational waves: primordial non-Gaussianity f
NL and g
NL considered
Authors: Li Jun-Peng , Wang Sai , Zhao Zhi-Chao , Kohri Kazunori 
Published: June 2024

Abstract
Investigation of primordial non-Gaussianity holds immense importance in testing the inflation paradigm and shedding light on the physics of the early Universe. In this study, we conduct the complete analysis of scalar-induced gravitational waves (SIGWs) by incorporating the local-type non-Gaussianity f
NL and g
NL. We develop Feynman-like diagrammatic technique and derive semi-analytic formulas for both the energy-density fraction spectrum and the angular power spectrum. For the energy-density fraction spectrum, we analyze all the relevant Feynman-like diagrams, determining their contributions to the spectrum in an order-by-order fashion. As for the angular power spectrum, our focus lies on the initial inhomogeneities, giving rise to anisotropies in SIGWs, that arise from the coupling between short- and long-wavelength modes due to primordial non-Gaussianity. Our analysis reveals that this spectrum exhibits a typical multipole dependence, characterized by C̃
ℓ ∝ [ℓ(ℓ + 1)]-1, which plays a crucial role in distinguishing between different sources of gravitational waves. Depending on model parameters, significant anisotropies can be achieved. We also show that the degeneracies in model parameters can be broken. The findings of our study underscore the angular power spectrum as a robust probe for investigating primordial non-Gaussianity and the physics of the early Universe. Moreover, our theoretical predictions can be tested using space-borne gravitational-wave detectors and pulsar timing arrays.
Constraining the variable generalized Chaplygin gas model in matter creation cosmology
Authors: Bhardwaj Yogesh , Singh C P 
Published: June 2024

Abstract
We explore the variable generalized Chaplygin gas (VGCG) model in the theory of matter creation cosmology within the framework of a spatially homogeneous and isotropic flat Friedmann—Lemaître—Robertson—Walker space-time. Matter creation cosmology is based on reinterpretation of the energy–momentum tensor in Einstein’s field equations. This creation corresponds to an irreversible energy flow from the gravitational field to the created matter constituents. The variable Chaplygin gas (VCG) is also studied as a particular solution. We use the Markov chain Monte Carlo method to constrain the free parameters of three models, namely, Lambda-Cold-Dark matter (ΛCDM), VGCG and VCG models with and without matter creation from the latest observational data from baryon acoustic oscillations, cosmic chronometer, type Ia supernovae (Pantheon) including gamma-ray bursts, quasars and the local measurement of H
0 from R21 data. Two different combinations of dataset provide a fairly tight constraint on the parameters of the ΛCDM, VGCG and VCG models. The present values of various cosmological parameters are obtained, which are very close to the ΛCDM model. Furthermore, we perform stability analysis, Bayesian evidence analysis and information criteria analysis for these models through studying the sound speed, Bayes factor, and Akaike information criteria (AIC) and Bayesian information criteria (BIC) selection criteria. The values of sound speed for VGCG and VCG models shows that both the models are stable. According to AIC, it is observed that VGCG and VCG models with matter creation are supported considerably less by current observations, while BIC shows that these models are not favoured by observational data.
Dynamic properties of rumor propagation model induced by Lévy noise on social networks
Authors: Jing 景 Ying 颖 , Wang 王 Youguo 友国 , Zhai 翟 Qiqing 其清 , Sun 孙 Xianli 先莉 
Published: June 2024

Abstract
Social networks are inevitably subject to disruptions from the physical world, such as sudden internet outages that sever local connections and impede information flow. While Gaussian white noise, commonly used to simulate stochastic disruptions, only fluctuates within a narrow range around its mean and fails to capture large-scale variations, Lévy noise can effectively compensate for this limitation. Therefore, a susceptible–infected–removed rumor propagation model with Lévy noise is constructed on homogeneous and heterogeneous networks, respectively. Then, the existence of a global positive solution and the asymptotic path-wise of the solution are derived on heterogeneous networks, and the sufficient conditions of rumor extinction and persistence are investigated. Subsequently, theoretical results are verified through numerical calculations and the sensitivity analysis related to the threshold is conducted on the model parameters. Through simulation experiments on Watts–Strogatz (WS) and Barabási–Albert networks, it is found that the addition of noise can inhibit the spread of rumors, resulting in a stochastic resonance phenomenon, and the optimal noise intensity is obtained on the WS network. The validity of the model is verified on three real datasets by particle swarm optimization algorithm.
Coupling of photovoltaics with neurostimulation electrodes—optical to electrolytic transduction
Authors: Jakešová Marie , Kunovský Ondřej , Gablech Imrich , Khodagholy Dion , Gelinas Jennifer , Głowacki Eric Daniel 
Published: June 2024

Abstract

Objective. The wireless transfer of power for driving implantable neural stimulation devices has garnered significant attention in the bioelectronics field. This study explores the potential of photovoltaic (PV) power transfer, utilizing tissue-penetrating deep-red light—a novel and promising approach that has received less attention compared to traditional induction or ultrasound techniques. Our objective is to critically assess key parameters for directly powering neurostimulation electrodes with PVs, converting light impulses into neurostimulation currents. Approach. We systematically investigate varying PV cell size, optional series configurations, and coupling with microelectrodes fabricated from a range of materials such as Pt, TiN, IrO
x
, Ti, W, PtO
x
, Au, or poly(3,4 ethylenedioxythiophene):poly(styrene sulfonate). Additionally, two types of PVs, ultrathin organic PVs and monocrystalline silicon PVs, are compared. These combinations are employed to drive pairs of electrodes with different sizes and impedances. The readout method involves measuring electrolytic current using a straightforward amplifier circuit. Main results. Optimal PV selection is crucial, necessitating sufficiently large PV cells to generate the desired photocurrent. Arranging PVs in series is essential to produce the appropriate voltage for driving current across electrode/electrolyte impedances. By carefully choosing the PV arrangement and electrode type, it becomes possible to emulate electrical stimulation protocols in terms of charge and frequency. An important consideration is whether the circuit is photovoltage-limited or photocurrent-limited. High charge-injection capacity electrodes made from pseudo-faradaic materials impose a photocurrent limit, while more capacitive materials like Pt are photovoltage-limited. Although organic PVs exhibit lower efficiency than silicon PVs, in many practical scenarios, stimulation current is primarily limited by the electrodes rather than the PV driver, leading to potential parity between the two types. Significance. This study provides a foundational guide for designing a PV-powered neurostimulation circuit. The insights gained are applicable to both in vitro and in vivo applications, offering a resource to the neural engineering community.
NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage
Authors: Li Yi , Frederick Rebecca A , George Daniel , Cogan Stuart F , Pancrazio Joseph J , Bleris Leonidas , Hernandez-Reynoso Ana G 
Published: June 2024

Abstract

Objective. The safe delivery of electrical current to neural tissue depends on many factors, yet previous methods for predicting tissue damage rely on only a few stimulation parameters. Here, we report the development of a machine learning approach that could lead to a more reliable method for predicting electrical stimulation-induced tissue damage by incorporating additional stimulation parameters. Approach. A literature search was conducted to build an initial database of tissue response information after electrical stimulation, categorized as either damaging or non-damaging. Subsequently, we used ordinal encoding and random forest for feature selection, and investigated four machine learning models for classification: Logistic Regression, K-nearest Neighbor, Random Forest, and Multilayer Perceptron. Finally, we compared the results of these models against the accuracy of the Shannon equation. Main Results. We compiled a database with 387 unique stimulation parameter combinations collected from 58 independent studies conducted over a period of 47 years, with 195 (51%) categorized as non-damaging and 190 (49%) categorized as damaging. The features selected for building our model with a Random Forest algorithm were: waveform shape, geometric surface area, pulse width, frequency, pulse amplitude, charge per phase, charge density, current density, duty cycle, daily stimulation duration, daily number of pulses delivered, and daily accumulated charge. The Shannon equation yielded an accuracy of 63.9% using a k value of 1.79. In contrast, the Random Forest algorithm was able to robustly predict whether a set of stimulation parameters was classified as damaging or non-damaging with an accuracy of 88.3%. Significance. This novel Random Forest model can facilitate more informed decision making in the selection of neuromodulation parameters for both research studies and clinical practice. This study represents the first approach to use machine learning in the prediction of stimulation-induced neural tissue damage, and lays the groundwork for neurostimulation driven by machine learning models.
Experiments on plasma detachment in a V-shaped slot divertor in the DIII-D tokamak
Authors: Maurizio R. , Thomas D. , Yu J.H. , Abrams T. , Hyatt A.W. , Herfindal J. , Leonard A. , Ma X. , McLean A.G. , Ren J. , Scotti F. , Shafer M.W. , Sinclair G. , Wang H.Q. , Watkins J. 
Published: June 2024

Abstract
Experiments in DIII-D demonstrate that the upstream plasma density to detach an un-pumped slot divertor is similar for a V-shaped and a flat-end slot, despite significantly higher neutral pressure in the V-shaped slot and in contrast to SOLPS-ITER predictions. The detachment threshold can be reduced by using in-slot instead of main-chamber gas fuelling or by placing the strike point on the inner slanted slot baffle instead of the slot end, as described by simulations with full drift physics. When increasing the plasma line-averaged density (without extrinsic impurities), the transition to detachment in DIII-D slot divertor is sharp and requires a high value of plasma density with the ion

B

→

×

∇
B

drift into the slot, whereas it is smooth and requires a lower value of plasma density with the opposite drift direction, in accord with detachment experiments in the DIII-D open lower divertor. Unique experiments on DIII-D and comparison to advanced simulations expand the scientific understanding of slot-shaped divertors, considered highly desirable for next step fusion devices.
Implications of vertical stability control on the SPARC tokamak
Authors: Nelson A.O. , Garnier D.T. , Battaglia D.J. , Paz-Soldan C. , Stewart I. , Reinke M. , Creely A.J. , Wai J. 
Published: June 2024

Abstract
To achieve its performance goals, SPARC plans to operate in equilibrium configurations with a strong elongation of

κ

areal

∼
1.75

, which in turn will destabilize the n = 0 vertical instability. However, SPARC also features a relatively thick conducting wall that is designed to withstand disruption forces, leading to lower vertical instability growth rates than usually encountered. In this work, we use the TokSyS framework to survey families of accessible shapes near the SPARC baseline configuration, finding maximum growth rates in the range of

γ
≲
100

s−1. The addition of steel vertical stability plates has only a modest (

∼

25
%

) effect on reducing the vertical growth rate and almost no effect on the plasma controllability when the full vertical stability system is taken into account, providing flexibility in the plate conductivity in the SPARC design. Analysis of the maximum controllable displacement on SPARC is used to inform the power supply voltage and current limit requirements needed to control an initial vertical displacement of 5% of the minor radius. From the expected spectra of plasma disturbances and diagnostic noise, requirements for filter latency and vertical stability coil heating tolerances are also obtained. Small modifications to the outboard limiter location are suggested to allow for an unmitigated vertical disturbance as large as 5% of the minor radius without allowing the plasma to become limited. Further, investigations with the 3D COMSOL code reveal that strategic inclusion of insulating structures within the VSC supports are needed to maintain sufficient magnetic response. The workflows presented here help to establish a model for the integrated predictive design for future devices by coupling engineering decisions with physics needs.
Cell information processing via frequency encoding and excitability
Authors: Givré Alan , Ponce Dawson Silvina 
Published: June 2024

Abstract
Cells continuously interact with their environment mediating their responses through signaling cascades. Very often, external stimuli induce pulsatile behaviors in intermediaries of the cascade of increasing frequency with the stimulus strength. This is characteristic of intracellular Ca2+ signals involving Ca2+ release through Inositol Trisphosphate Receptors (IP3Rs). The mean frequency of IP3R-mediated Ca2+ pulses has been observed to scale exponentially with the stimulus strength in many cell types. In this paper we use a simple ODE model of the intracellular Ca2+ dynamics for parameters for which there is one excitable fixed point. Including fluctuations through an additive noise term, we derive the mean escape rate from the stationary state and, thus, the mean interpulse time, as a function of the fraction, β, of readily openable IP3Rs. Using an IP3R kinetic model, experimental observations of spatially resolved Ca2+ signals and previous estimates of the IP3 produced upon stimulation we quantify the fluctuations and relate β to [IP3] and the stimulus strength. In this way we determine that the mean interpulse time can be approximated by an exponential function of the latter for ranges such that the covered mean time intervals are similar or larger than those observed experimentally. The study thus provides an easily interpretable explanation, applicable to other pulsatile signaling intermediaries, of the observed exponential dependence between frequency and stimulus, a key feature that makes frequency encoding qualitatively different from other ways commonly used by cells to ‘read’ their environment.
Critical exponents testing of a random number generator with the Wolff cluster algorithm
Authors: Zhu Dongjie , Lin Yun , Sun Guoya , Wang Fuming 
Published: June 2024

Abstract
Finite-size scaling (FSS) of critical exponents including γ, β and α of 2D Ising models of sizes up to 327682 are studied using the Wolff clustering algorithm and are used to assess the quality of pseudorandom number generators (PRNGs). Critical exponents of PRNGs with quality issues are found to diverge from their theoretical values at large lattice sizes, similar to previous reports that used the Metropolis algorithm to simulate the Ising lattice. Four high-quality PRNGs, including Mersenne Twister, an additive lagged Fibonacci generator, Xorshift and Xorwow are tested and assessed with their FSS behaviors. Dynamic exponent z is also used to assess the quality of the four tested PRNGs and corroborating results are obtained.
Status of the MDT Trigger Processor for the ATLAS Level-0 Muon trigger at the HL-LHC
Authors: Rojas Rimsky ,   the ATLAS TDAQ collaboration
Published: June 2024

Abstract
The MDT Trigger Processor (MDTTP) is a key ATLAS Level-0 Muon trigger upgrade component designed to meet High-Luminosity LHC requirements. The MDTTP will use MDT hits in the hardware level trigger for the first time in ATLAS to improve the momentum resolution of muon candidates provided by RPC and TGC detectors and reduce the fake muon trigger rate.

The MDTTP hardware is based on the Apollo ATCA platform. The prototype includes a VU13P-FPGA, high-speed FireFly optical transceivers, peripherals, and other improvements learned from using the previous hardware demonstrator. We present the prototype status, firmware implementation, core algorithm, slow-control software, and first integration tests.
The DarkSide-20k underground argon procurement chain
Authors: Cocco V. ,   the DarkSide-20k collaboration
Published: June 2024

Abstract
The DarkSide-20k experiment searches for dark matter by looking for interactions of WIMPs in a 50-tonnes target of liquid argon using double-phase time projection chamber (TPC) technology. The key component of the experiment is low radioactivity argon depleted in the isotope 39Ar. Unfortunately, 39Ar is naturally present in atmospheric argon and it is constantly produced due to the interaction with cosmic rays. Finding a source of depleted argon was the first step of the Collaboration when it started to size the DarkSide-20k detector.

The procurement chain begins with the Urania plant in Colorado, which can produce argon with a purity of 99.99% from a crude CO2 stream extracted from a deep well, at a rate of about 250 kg per day. The plant has already been fabricated while the site is being prepared for installation. After the extraction and purification of 120 t of underground argon (UAr), it will be transported to Sardinia, Italy, where the ARIA plant, consisting of a 350 m cryogenic distillation column, will further remove impurities up to 2 orders of magnitude. The final purity is expected to be 99.9999%. After the ARIA purification stage, the ultra-pure UAr will be delivered to the Laboratori Nazionali del Gran Sasso, L'Aquila, Italy where it will fill the DarkSide-20k TPC.

The ARIA plant has already been fully fabricated and is now in the installation phase in a mine shaft. A shorter version, about 26 m high, has been tested over the last three years with very positive results. We were able to measure the separation factor between two isotopes of nitrogen (29N2, 28N2) and three of argon (40Ar, 38Ar, 36Ar) thus validating the capability of performing isotopic distillation with ARIA.
Flash droughts and their impacts—using newspaper articles to assess the perceived consequences of rapidly emerging droughts
Authors: Henrique Lima Alencar Pedro , Sodoge Jan , Nora Paton Eva , Madruga de Brito Mariana 
Published: June 2024

Abstract
Flash droughts (FDs) have attracted increasing attention in the past decade. They are characterised by a rapid depletion of soil moisture resulting from interactions between the soil and atmospheric conditions. To date, there is a lack of consistent FD definitions and an understanding of their socio-economic impacts. Here, we explore the relationship between biophysical FD conditions and the perceived impacts of FDs in Germany between 2000 and 2022. We measured perceived impacts by analysing consequences reported in newspaper articles (2000–2022) and online search behaviour using Google trends data (2004–2022). To characterise the physical process, we considered root zone soil moisture data. Our results show that FDs are becoming increasingly frequent in Germany, occurring once every two years on average. Despite the lack of knowledge from the general public regarding the phenomenon of FDs, the peaks of interest in drought impacts correspond to the physical occurrence of FDs across the country. We identified an average time gap of four weeks between FD onset and the reporting of perceived impacts. This gap is longer than the average duration of FDs’ onset. Consequently, our findings highlight that consistent monitoring of FD conditions and drivers is necessary to guarantee effective preparedness. As impact perception is too slow to allow the adoption of mitigation measures, FDs require new schemes for response measures compared with slowly emerging (conventional) drought events. The novel method also allows the consistent and impact-based validation of FD identification methods.
Variational Gaussian approximation for the magnetic Schrödinger equation
*
Authors: Burkhard Selina , Dörich Benjamin , Hochbruck Marlis , Lasser Caroline 
Published: June 2024

Abstract
In the present paper we consider the semiclassical magnetic Schrödinger equation, which describes the dynamics of particles under the influence of a magnetic field. The solution of the time-dependent Schrödinger equation is approximated by a single Gaussian wave packet via the time-dependent Dirac–Frenkel variational principle. For the approximation we derive ordinary differential equations of motion for the parameters of the variational solution. Moreover, we prove L
2-error bounds and observable error bounds for the approximating Gaussian wave packet.