bluuebunny/crossref_metadata_2025_split huggingface dataset:
Realistic compact objects in the f(R, T) gravity in the background of polytropic and barotropic gas models
Authors: Das Samprity , Chattopadhyay Surajit 
Published: April 2024

Abstract
The f(R, T) gravity in the background of the polytropic and barotropic fluid has been investigated in this work. We have selected the TOV equation to determine the internal spacetime of a spherically symmetric galactic object. With the use of the Einstein equation, we have selected KB-spacetime to calculate the mass, compactness, and surface redshift of a spherically symmetric body. Explicit conditions for model parameters have been constructed for the boundary conditions of the interior and exterior spacetime, and the Schwarzschild solution has been employed in the modified f(R, T) gravity theory to evaluate different matching criteria. An increasing pattern in compactness with respect to the different radii is evident in the graphical representation of the compactness evolution for each of the individual star models. After selecting a non-vacuum field equation for higher order curvature, we reformulated f(R, T) for R and T. As a result, the tangential pressure, radial pressure, and matter density have all been calculated. According to the study, as the radius goes to infinity, the tangential and radial pressures display asymptotic flatness and converge to zero. Polytropic and barotropic gas EoS have been adopted since the star model confronts the presence of an isotropic fluid backdrop. It has been noted that in a polytropic background, density and pressure increase with distance from the star’s core, but in a barotropic background, the pressure exhibits an ascending pattern as a function of radius.
Cross-modal credibility modelling for EEG-based multimodal emotion recognition
Authors: Zhang Yuzhe , Liu Huan , Wang Di , Zhang Dalin , Lou Tianyu , Zheng Qinghua , Quek Chai 
Published: April 2024

Abstract

Objective. The study of emotion recognition through electroencephalography (EEG) has garnered significant attention recently. Integrating EEG with other peripheral physiological signals may greatly enhance performance in emotion recognition. Nonetheless, existing approaches still suffer from two predominant challenges: modality heterogeneity, stemming from the diverse mechanisms across modalities, and fusion credibility, which arises when one or multiple modalities fail to provide highly credible signals. Approach. In this paper, we introduce a novel multimodal physiological signal fusion model that incorporates both intra-inter modality reconstruction and sequential pattern consistency, thereby ensuring a computable and credible EEG-based multimodal emotion recognition. For the modality heterogeneity issue, we first implement a local self-attention transformer to obtain intra-modal features for each respective modality. Subsequently, we devise a pairwise cross-attention transformer to reveal the inter-modal correlations among different modalities, thereby rendering different modalities compatible and diminishing the heterogeneity concern. For the fusion credibility issue, we introduce the concept of sequential pattern consistency to measure whether different modalities evolve in a consistent way. Specifically, we propose to measure the varying trends of different modalities, and compute the inter-modality consistency scores to ascertain fusion credibility. Main results. We conduct extensive experiments on two benchmarked datasets (DEAP and MAHNOB-HCI) with the subject-dependent paradigm. For the DEAP dataset, our method improves the accuracy by 4.58%, and the F1 score by 0.63%, compared to the state-of-the-art baseline. Similarly, for the MAHNOB-HCI dataset, our method improves the accuracy by 3.97%, and the F1 score by 4.21%. In addition, we gain much insight into the proposed framework through significance test, ablation experiments, confusion matrices and hyperparameter analysis. Consequently, we demonstrate the effectiveness of the proposed credibility modelling through statistical analysis and carefully designed experiments. Significance. All experimental results demonstrate the effectiveness of our proposed architecture and indicate that credibility modelling is essential for multimodal emotion recognition.
Predicting resting-state brain functional connectivity from the structural connectome using the heat diffusion model: a multiple-timescale fusion method
Authors: Lv Zhengyuan , Li Jingming , Yao Li , Guo Xiaojuan 
Published: April 2024

Abstract

Objective. Understanding the intricate relationship between structural connectivity (SC) and functional connectivity (FC) is pivotal for understanding the complexities of the human brain. To explore this relationship, the heat diffusion model (HDM) was utilized to predict FC from SC. However, previous studies using the HDM have typically predicted FC at a critical time scale in the heat kernel equation, overlooking the dynamic nature of the diffusion process and providing an incomplete representation of the predicted FC. Approach. In this study, we propose an alternative approach based on the HDM. First, we introduced a multiple-timescale fusion method to capture the dynamic features of the diffusion process. Additionally, to enhance the smoothness of the predicted FC values, we employed the Wavelet reconstruction method to maintain local consistency and remove noise. Moreover, to provide a more accurate representation of the relationship between SC and FC, we calculated the linear transformation between the smoothed FC and the empirical FC. Main results. We conducted extensive experiments in two independent datasets. By fusing different time scales in the diffusion process for predicting FC, the proposed method demonstrated higher predictive correlation compared with method considering only critical time points (Singlescale). Furthermore, compared with other existing methods, the proposed method achieved the highest predictive correlations of 0.6939

±

0.0079 and 0.7302

±

0.0117 on the two datasets respectively. We observed that the visual network at the network level and the parietal lobe at the lobe level exhibited the highest predictive correlations, indicating that the functional activity in these regions may be closely related to the direct diffusion of information between brain regions. Significance. The multiple-timescale fusion method proposed in this study provides insights into the dynamic aspects of the diffusion process, contributing to a deeper understanding of how brain structure gives rise to brain function.
Degradation of fast-ion confinement depending on the neutral beam power in MHD quiescent LHD plasmas
Authors: Nuga H. , Seki R. , Ogawa K. , Yamaguchi H. , Kamio S. , Fujiwara Y. , Kawamoto Y. , Yoshinuma M. , Kobayashi T. , Takemura Y. , Isobe M. , Osakabe M. , Yokoyama M. 
Published: April 2024

Abstract
We investigated the degradation of neutral beam (NB) fast-ion confinement depending on the NB power without magnetohydrodynamics instabilities in the Large Helical Device (LHD). In the LHD deuterium experiment, the neutron emission rate per NB power decreased by up to 20% with increasing injected NBs during a single discharge. Because there were no significant variations in the electron temperature and density, the NB shine-through rate, or the magnetic fluctuation due to the change in NB power, the reduction in the neutron emission rate indicates the degradation of the fast-ion confinement. In this paper, we formulated this degradation depending on the NB power and quantitatively estimated the degraded effective confinement time. In addition, we performed neutron emission rate simulations using the obtained effective confinement time. The simulation and experimental results were in good agreement, suggesting that the degraded effective confinement time is valid.
Modeling electron temperature profiles in the pedestal with simple formulas for ETG transport
Authors: Hatch D.R. , Kotschenreuther M.T. , Li P.-Y. , Chapman-Oplopoiou B. , Parisi J. , Mahajan S.M. , Groebner R. 
Published: April 2024

Abstract
This paper reports on the refinement (building on (Hatch D.R. et al 2022 Phys. Plasmas
29 062501)) and application of simple formulas for electron heat transport from electron temperature gradient (ETG) driven turbulence in the pedestal. The formulas are improved by (1) improving the parameterization for certain key parameters and (2) carefully accounting for the impact of geometry and shaping in the underlying gyrokinetic simulation database. Comparisons with nonlinear gyrokinetic simulations of ETG transport in the MAST pedestal demonstrate the model’s applicability to spherical tokamaks in addition to standard aspect ratio tokamaks. We identify bounds for model applicability: the model is accurate in the steep gradient region, where the ETG turbulence is largely slab-like, but accuracy decreases as the temperature gradient becomes weaker in the pedestal top. We use the formula to model the electron temperature profile in the pedestal for four experimental scenarios while extensively varying input parameters to represent uncertainties. In all cases, the predicted electron temperature profile exhibits extreme sensitivity to separatrix temperature and density, which has implications for core-edge integration. The model reproduces the electron temperature profile for high

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=

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e

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scenarios but not for low η

e
scenarios in which microtearing modes (MTMs) have been identified. We develop a proof-of-concept model for MTM transport and explore the relative roles of ETG and MTM in setting the electron temperature profile.
A first look at AS-ROC: a Si-Ge integrated chip readout for fast timing
Authors: DeWitt J. , Galloway Z. , Saffier-Ewing G. , Gignac M. , Mazza S.M. , McKinney-Martinez F. , Mobtaker N. , Nagel N. , Nizam M. , Ott J. , Sadrozinski H.F.-W. , Schumm B. , Seiden A. , Wilder M. 
Published: April 2024

Abstract
Advances in timing detector technology require new specialized readout electronics. Applications demand below 10 ps time of arrival resolution and low power for a low repetition rate. A possible path to achieve O(10 ps) time resolution is an integrated chip using Silicon Germanium (SiGe) technology. Using DoE SBIR funding, Anadyne, Inc., in collaboration with UC Santa Cruz, has developed a prototype SiGe front-end readout chip optimized for low power and timing resolution. Two versions of the chip were produced with performance in simulation: a more power version with 10 ps resolution at 5 fC with 1.1 mW/channel, and a less power version with 10 ps resolution at 8 fC with 0.6 mW/channel.
The chip was produced at Tower Semiconductor with 350 nm technology. The ASIC from the prototype run shows good performance: a rise time of 0.7–1 ns and 25 mV per fC response with RMS noise <1 mV. Simulation and results from the prototype will be reported in this paper.
Optimized design and characterization of HYLITE, a charge-integration readout chip of XFEL
Authors: Li M. , Wei W. , Jiang X. , Zhang J. , Li X. , Liu H. , Liu Z. 
Published: April 2024

Abstract
HYLITE (High dYnamic range free electron Laser Imaging deTEctor) is a charge-integration pixel readout chip designed for SHINE (Shanghai HIgh repetition rate XFEL aNd Extreme light facility). The target specifications for the full-size HYLITE chip include a pixel matrix of 128 × 128 pixels and a frame rate of 10 kHz. In order to meet these specifications, two small-scale chips, designated HYLITE0.1 and HYLITE0.2, were fabricated and underwent comprehensive testing. Some issues were discovered during tests including the noise performance and the error of output ADU (Analog Digital Units) codes.

The HYLITE200S represents the third prototype chip developed to address the above issues. The CDS (Correlated Double Sampling) circuits and glitch-clear clock structures are integrated in pixels. Furthermore, to meet the data output rate requirements of the full-size chip, a high-speed data interface has been designed. Test results show that the signal-to-noise ratio is improved to 9.31 for a 12 keV single photon, and the ADU error is fixed. By integrating a phase-locked loop and a balanced encoding logic, the data interface can work steadily at a speed of 3.125 Gbps.
Performance of a novel charge sensor on the ion detection for the development of a high-pressure avalancheless ion TPC
Authors: Liang Tianyu , Zhang Dongliang , Wang Hulin , Gao Chaosong , Liu Jun , Sun Xiangming , Xiao Le , Liu Feng , You Bihui , Liu Ling , Yang Yichen , Chen Kai 
Published: April 2024

Abstract
Within the project of building a time projection chamber using 100 kg of high-pressure
86SeF6 gas to search for the neutrinoless double-beta decay in the NvDEx
collaboration, we are developing a CMOS charge sensor, named Topmetal-S, which is tailored for the
experiment to detect the ions without gas amplification. In this work, the performance of
the sensor is presented. The equivalent noise charge of the sensor is measured to be about 120 to
140 e- depending on the operating point, with the charge injection capacitance
calibrated against external capacitors. The signal waveforms are investigated with various chip
parameters and experimental settings. In addition to electrons, both negatively and positively
charged ions could be detected, and their waveforms are studied using air and SF6
gases. Using the sensor, the mobility of negative ions in ambient air in the atmospheric pressure
is measured to be 1.555 ± 0.038 cm2 · V-1 · s-1. Our study
demonstrates that the Topmetal-S chip could be used as the ion detection charge sensor for the
experiment. Further work is ongoing to reduce the noise of the sensor and to develop a
small readout plane with tens of the sensors.
Implementation and performance comparison of MMC firmware on RISC-V and ARM-based MCUs
Authors: Su Aoqi , Zhang Jie , Yang Jie 
Published: April 2024

Abstract
The control and data acquisition systems for high energy physics (HEP) applications require a suitable hardware platform to ensure system availability and reliability, so the micro telecommunications computing architecture (MicroTCA) standard is widely utilized in the field of HEP. As a fundamental component of the MicroTCA system, the advanced mezzanine card (AMC) requires efficient module management controller (MMC) to perform board monitoring and management. Therefore, the real-time responsiveness of the module management controller is crucial. Presently, most existing MMC solutions implemented on microcontroller chips with commercial architecture cores such as AVR and ARM. The open-source and customizable RISC-V instruction set architecture has gained widespread attention and adoption due to its advantages such as simplicity, modularity, scalability, low power consumption, and efficiency. In this study, we successfully implemented a MMC solution based on the RISC-V core microcontroller GD32VF103, and evaluated the real-time performance of MMC on both the GD32VF103 and the ARM-based STM32F100 through hot swap response time testing. The results reveal real-time performance of the firmware on the GD32VF103 chip compared to the STM32F100 chip, exhibiting a notable speed improvement of approximately 61.4%. Thus, RISC-V architecture chips exhibit significant potential as MMC solutions within MicroTCA systems.
Design of low-cost digital pulse processing unit for gamma spectrometry
Authors: Shaker Hesham H. , Salama S. , Kasban H. , Saleh A.A. , Dessouky M. 
Published: April 2024

Abstract
Gamma spectrometers are used to quantify and identify
radioisotopes in the sample under test. There is a recent interest
around the world in implementing low-cost gamma spectrometers. One
of the main parts of the modern gamma spectrometer is the digital
pulse processing unit (DPP). The implementation of this unit using
advanced microcontroller chips has appeared in recent years as an
attractive approach. This is due to its advanced performance and low
cost. In this paper, we present a design flow to implement a DPP
unit using an ARM Cortex-M3-based microcontroller chip. The sodium
iodide detector is the targeted detector for this design. Our
prototype is approved experimentally to construct spectrums
comparable to commercial devices. And it can cope with input count
rates up to 45 kC/s.
Feasibility study of real-time imaging of an Ir-192 source using compact gamma camera with curved diverging collimator for brachytherapy
Authors: Oh G. , Jeong S.H. , Choi H.J. , Kim D.H. , Baek C.H. , Cha H.M. , Lee H.J. , Lee B.R. 
Published: April 2024

Abstract
Brachytherapy is a treatment method that requires the
accurate positioning of a radioactive source to deliver high doses
to a tumor while minimizing exposure to surrounding tissues. Herein,
we propose a compact gamma camera system based on a diverging
collimator for real-time source positioning during brachytherapy. In
the process of developing and fabricating such a gamma camera
system, Monte Carlo simulations for diverging and pinhole
collimators are performed under conditions that are similar to the
actual detection environment, with the camera-to-source distance set
at 50 cm to verify the feasibility of the gamma camera. Full width
at half maximum (FWHM) and signal-to-noise ratio (SNR) values are
analyzed based on the horizontal and vertical profiles at each
location as the source shifts stepwise from the center to the right
and diagonal direction. On average, the diverging collimator had
FWHM values of 18 and 13 mm and SNR values of 30 and 31, while the
pinhole collimator had FWHM values of 26 and 25 mm and SNR values
of 47 and 46 when profiled horizontally and vertically. The
diverging collimator has a lower SNR than pinhole collimator but
performs better in terms of spatial resolution. Additionally, to
test the performance of the manufactured gamma camera, the distance
between the camera and the source was set to 100 cm and an
experiment was conducted. The experimental results exhibit a trend
similar to the simulation. Numerically, the average FWHM value were
39 mm in the vertical direction and 71 mm in the horizontal
direction. Additionally, the average SNR values were 27 for the
vertical direction and 17 for the horizontal direction. Based on
these results, we confirm the possibility of Ir-192 source imaging.
Climate policy and the SDGs agenda: how does near-term action on nexus SDGs influence the achievement of long-term climate goals?
Authors: Schmidt Tagomori Isabela , Harmsen Mathijs , Awais Muhammad , Byers Edward , Daioglou Vassilis , Doelman Jonathan , Vinca Adriano , Riahi Keywan , van Vuuren Detlef P 
Published: April 2024

Abstract
The sustainable development goals (SDGs) represent the global ambition to accelerate sustainable development. Several SDGs are directly related to climate change and policies aiming to mitigate it. This includes, among others, the set of SDGs that directly influence the climate, land, energy, and water (CLEW) nexus (SDGs 2, 6, 7, 13, 15). This study aims at understanding the synergies and trade-offs between climate policy and the SDGs agenda: how does near-term action on SDGs influence long-term climate goals? Based on a multi-model comparison, we evaluate three scenarios: (i) reference; (ii) climate mitigation; and (iii) a CLEW nexus SDGs scenario. We find clear positive effects of combining the climate and the sustainable development agendas. Notably, healthier diets, with reduced meat consumption, have strong co-benefits for climate, with positive effects across multiple SDGs: improvements in food security, reductions in air pollution and water stress, and improvements in biodiversity conservation. Such positive outcomes are prominent in the Global South, where regions typically at higher risk of food and energy insecurity and other environmental stresses (e.g. Sub-Saharan Africa, Asia and Latin America) benefit from a shorter term agenda focusing not only on the climate but also on the other sustainable development dimensions. However, trade-offs are also observed (e.g. increases in the prices of food and electricity), especially in the dynamics of land and the food systems, highlighting the importance of exploring policy synergies: if individually applied, some measures can negatively impact other sustainability goals, while taking into consideration the nexus interactions can reduce trade-offs and increase co-benefits. Finally, near-term action on SDGs can help speed up the transition towards the long-term climate goals, reducing the reliance on negative emissions options. In 2100, the SDG scenario in significantly less reliant on carbon dioxide removals both from AFOLU and the energy system.
3D hydrogel microfibers promote the differentiation of encapsulated neural stem cells and facilitate neuron protection and axon regrowth after complete transactional spinal cord injury
Authors: Zhang Jin , Li Xinda , Guo Lili , Gao Mingjun , Wang Yangyang , Xiong Huan , Xu Tao , Xu Ruxiang 
Published: April 2024

Abstract
Spinal cord injury (SCI) can cause permanent impairment to motor or sensory functions. Pre-cultured neural stem cell (NSC) hydrogel scaffolds have emerged as a promising approach to treat SCI by promoting anti-inflammatory effects, axon regrowth, and motor function restoration. Here, in this study, we performed a coaxial extrusion process to fabricate a core-shell hydrogel microfiber with high NSC density in the core portion. Oxidized hyaluronic acid, carboxymethyl chitosan, and matrigel blend were used as a matrix for NSC growth and to facilitate the fabrication process. During the in vitro differentiation culture, it was found that NSC microfibers could differentiate into neurons and astrocytes with higher efficiency compared to NSC cultured in petri dishes. Furthermore, during in vivo transplantation, NSC microfibers were coated with polylactic acid nanosheets by electrospinning for reinforcement. The coated NSC nanofibers exhibited higher anti-inflammatory effect and lesion cavity filling rate compared with the control group. Meanwhile, more neuron- and oligodendrocyte-like cells were visualized at the lesion epicenter. Finally, axon regrowth across the whole lesion site was observed, demonstrating that the microfiber could guide renascent axon regrowth. Experiment results indicate that the NSC microfiber is a promising bioactive treatment for complete SCI treatment with superior outcomes.
Sandwich-structured nano-adhesive based on the synergistic action of two nanoparticles (SiC and MWCNTs)
Authors: Marathe Umesh , Bijwe Jayashree 
Published: April 2024

Abstract
This study encompasses the development of sandwich-structured adhesive reporting the synergism in the functioning of two kinds of nanoparticles (NPs)-SiC (Silicon carbide) and MWCNTs (multiwalled carbon nanotubes). Two adhesives using MWCNTs and NPs of SiC in selected amounts were developed using Polyaryletherketone (PAEK) thermoplastic polymer as a base matrix. Fabricated joints using these adhesives were characterized for degglomeration and dispersion of NPs, lap shear strength (LSS), and failure modes. Based on the data on the LSS, the advantages and disadvantages of using individual NPs were analyzed, and the third adhesive was designed in a sandwich manner, where positive points of both the NPs were expected to work synergistically. The sandwich adhesive showed higher LSS than the individual ones, i.e., an 8.6% and 26% improvement to SiC-based and MWCNT-based adhesives, respectively. It was concluded that the strengthening mechanism of MWCNTs of bulk polymer in the central portion was beneficial. The two outer layers of SiC NPs in PAEK interacting with the two steel surfaces of coupons proved helpful in increasing friction and, hence, synergistically increasing the LSS of sandwich adhesive.