bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interlayer-coupling-engineerable flat bands in twisted MoSi2N4 bilayers
Authors: Dai Yang , Zhang Zhineng , Zhao Puqin , Cheng Yingchun 
Published: January 2024

Abstract
The two-dimensional layered semiconductor MoSi2N4, which has several advantages including high strength, excellent stability, high hole mobility, and high thermal conductivity, was recently successfully synthesized using chemical vapor deposition. Based on first-principles calculations, we investigate the effects of the twist angle and interlayer distance variation on the electronic properties of twisted bilayer MoSi2N4. The flat bands are absent for twisted bilayer MoSi2N4 when the twist angle θ is reduced to 3.89°. Taking twisted bilayer MoSi2N4 with θ of 5.09° as an example, we find that flat bands emerge as the interlayer distance decreases. As the interlayer distance can be effectively modulated by hydrostatic pressure, we propose hydrostatic pressure as a knob for tailoring the flat bands in twisted bilayer MoSi2N4. Our findings provide theoretical support for extending the applications of MoSi2N4 in strong correlation physics and superconductivity.
Advancing robust state estimation of wheeled robots in degenerate environments: harnessing ground manifold and motion states
Authors: Liang Bowen , Tao Yourui , Zhu Huabo , Song Yao 
Published: January 2024

Abstract
State estimation is crucial for enabling autonomous mobility in mobile robots. However, traditional localization methods often falter in degraded environments, including issues like visual occlusion, lidar performance degradation, and global navigation satellite system signal interference. This paper presents a novel estimation approach for wheeled robots, exclusively utilizing proprioceptive sensors such as encoders and inertial measurement units (IMU). Initially, the motion manifolds extracted from the historical trajectories are used to assist the encoder in realizing the orientation estimation. Furthermore, a hybrid neural network is designed to categorize the robot’s operational state, and the corresponding pseudo-constraints are added to improve the estimation accuracy. We utilize an error state Kalman filter for the encoder and IMU data fusion. Lastly, comprehensive testing is conducted using both datasets and real-world robotic platforms. The findings underscore that the integration of manifold and motion constraints within our proposed state estimator substantially elevates accuracy compared to conventional approaches. Compare with the methods commonly used in engineering, the accuracy of this method is improved by more than 20%. Crucially, this methodology enables dependable estimation even in degraded environments.
A nudge over the relaxation plateau: effect of pH, particle concentration, and medium viscosity on the AC induction heating efficiency of biocompatible chitosan-coated Fe3O4 nanoparticles
Authors: Mahendravada Srujana , Lahiri B B , Khan Fouzia , Sathyanarayana A T , Vizhi R Ezhil , Moorthy Anbalagan , Philip John 
Published: January 2024

Abstract
The effects of pH, MNP concentration, and medium viscosity on the magnetic fluid hyperthermia (MFH) properties of chitosan-coated superparamagnetic Fe3O4 nanoparticles (MNPs) are probed here. Due to the protonation of the amide groups, the MNPs are colloidally stable at lower pH (∼2), but form aggregates at higher pH (∼8). The increased aggregate size at higher pH causes the Brownian relaxation time (τ
B) to increase, leading to a decrease in specific absorption rate (SAR). For colloidal conditions ensuring Brownian-dominated relaxation dynamics, an increase in MNP concentrations or medium viscosity is found to increase the τ
B. SAR decreases with increasing MNP concentration, whereas it exhibits a non-monotonic variation with increasing medium viscosity. Dynamic hysteresis loop-based calculations are found to be in agreement with the experimental results. The findings provide a greater understanding of the variation of SAR with the colloidal properties and show the importance of relaxation dynamics on MFH efficiency, where variations in the frequency-relaxation time product across the relaxation plateau cause significant variations in SAR. Further, the in vitro cytotoxicity studies show good bio-compatibility of the chitosan-coated Fe3O4 MNPs. Higher SAR at acidic pH for bio-medically acceptable field parameters makes the bio-compatible chitosan-coated Fe3O4 MNPs suitable for MFH applications.
Investigation of SiGe/Si heterojunction inductive line tunneling TFET with source Schottky contact for prospect ultra-low power applications
Authors: Lin Jyi-Tsong , Yang Ruei-Kai 
Published: January 2024

Abstract
In this paper, a SiGe/Si heterojunction inductive line tunneling tunnel field-effect transistor with source Schottky contact (SC HJLT-iTFET) is proposed and investigated by the Sentaurus Technology Computer Aided Design (TCAD) simulator. By utilizing an appropriate source Schottky metal, the need for multiple ion implantation and annealing steps required for traditional P–I–N TFETs can be avoided, and the problems of self-alignment and random dopant fluctuations (RDF) during ion implantation can be solved. A high ON-state current (I
ON) is obtained as fully overlapping the source and gate by line tunneling mechanism dominated, the appropriate Si1−x
Ge
x
mole fraction material in the source region and high-k gate dielectric employed can further improve I
ON. The incorporation of the block layer effectively decreases the lateral electric field at the drain end to reduce the OFF-state current (I
OFF). Furthermore, the proposed charge enhancement layer (CEL) on the SiGe channel can suppress the Fermi level pinning effect (FLP) and enhance the charge of the source region. Based on the feasibility of the practical fabrication process, and the rigorous simulations indicate that the device has an SSavg of 19.8 mV/dec and SSmin of 6.8 mV/dec at V
D = 0.2 V, I
ON of 2.27 × 10−6 A

μ

m−1, and an I
ON/I
OFF ratio of 1.02 × 1010, with extremely fast switching speed. These features make the device suitable for future ultra-low power applications on the internet of things, artificial intelligence, and related fields.
Simulation and experimental results of plasma opening switch operation with inductive and electron beam diode loads in different plasma regimes
Authors: Kanchi Sunil , Shukla Rohit , Sharma Archana 
Published: January 2024

Abstract
This paper reports the experimental results of a plasma opening switch (POS) that operates at hydrogen and carbon plasma regimes confirmed based on the conduction bipolar limit of the plasma species and the availability of plasma species during the conduction based on the density profiles. The generator is the compact capacitor bank developed using the synchronization of four field distortion spark gap switches. The plasma source is coaxial cable plasma guns characterized using the Faraday cup plasma diagnostic. The experimental results are compared with the time domain simulation code in which the POS is represented as the dynamic resistance governed by the physical equations of the bipolar model. The experiments and simulations are compared for inductive load and dynamic load of accelerating gap of 5 mm between the anode and cathode at the load end. From the results, POS can be operated based on the availability of plasma species with proper synchronized triggering between the plasma gun firing and generator firing that can operate at low and high values of currents.
Sound insulation performance of membrane-type acoustic metamaterial based on defect state structure
Authors: Cai Tong , Huang Shuang , Guo Hui , Yuan Tao , Sun Pei , Liu NingNing 
Published: January 2024

Abstract
Although conventional Membrane-type Acoustic Metamaterial(MAM) has good sound insulation performance in low frequency bands, the sound insulation performance in middle and high frequency bands is not as good as conventional sound insulation materials with the same quality. This problem still persists by using the double-layer MAM structures. To solve this problem, the defect state is introduced into the double-layer MAM structure. Although the ideal periodic structure is destroyed, the sound insulation performance will also change greatly, and it has a strong creativity. In this paper, the sound insulation performance of MAM with defect states is studied. Firstly, the theoretical model of sound insulation of double-layer membrane-type acoustic metamaterial with eccentric composite mass block (MAMEM) structure is calculated by using modal superposition method and transfer matrix method. Secondly, the influence of different defect locations on the sound insulation of membrane-type acoustic metamaterial with eccentric composite mass block(MAMECM) structure is discussed. The results show that the sound insulation peaks of the angular defect structure appear at 300 Hz, 320 Hz, 1040 Hz and 1410 Hz. The average sound insulation in the whole study frequency band of the angular defect structure is 4.23 dB higher than the non-defect structure. In addition, the experiment verifies the accuracy of the results. Thirdly, based on genetic algorithm, the area enclosed by the sound translation loss (STL) curve of the double-layer MAMECM structure above the mass law curve is taken as the optimization target to optimize the structure topology. The results show that the optimal structure not only has good sound insulation performance in the low frequency band, but also reaches the sound insulation peak at 1230 Hz, 1300 Hz, 1430 Hz and 1450 Hz. Besides, the optimal structure heaviness is reduced by 12%.
Mode-locked Yb:CALGO laser with high peak power sub-100 fs pulses at 26.9 MHz repetition rate
Authors: Reza Md A R , Major A 
Published: January 2024

Abstract
The development of a diode-pumped high peak power sub-100 fs mode-locked Yb:CALGO laser is presented. The laser delivered 1.3 W of output power with 81 fs pulses at a repetition rate of 26.9 MHz. The corresponding pulse energy was 48 nJ and the peak power was 596 kW. The cavity was extended by using a 1:1 imaging telescope. Mode locking was based on a semiconductor saturable absorber mirror and chirped mirrors were used to compensate for the positive dispersion in the cavity. To the best of our knowledge, this is one of the shortest pulse durations obtained from Yb:CALGO laser around this low repetition rate.
Neural signal data collection and analysis of Percept™ PC BrainSense recordings for thalamic stimulation in epilepsy
Authors: Sanger Zachary T , Henry Thomas R , Park Michael C , Darrow David , McGovern Robert A , Netoff Theoden I 
Published: January 2024

Abstract
Deep brain stimulation (DBS) using Medtronic’s Percept™ PC implantable pulse generator is FDA-approved for treating Parkinson’s disease (PD), essential tremor, dystonia, obsessive compulsive disorder, and epilepsy. Percept™ PC enables simultaneous recording of neural signals from the same lead used for stimulation. Many Percept™ PC sensing features were built with PD patients in mind, but these features are potentially useful to refine therapies for many different disease processes. When starting our ongoing epilepsy research study, we found it difficult to find detailed descriptions about these features and have compiled information from multiple sources to understand it as a tool, particularly for use in patients other than those with PD. Here we provide a tutorial for scientists and physicians interested in using Percept™ PC’s features and provide examples of how neural time series data is often represented and saved. We address characteristics of the recorded signals and discuss Percept™ PC hardware and software capabilities in data pre-processing, signal filtering, and DBS lead performance. We explain the power spectrum of the data and how it is shaped by the filter response of Percept™ PC as well as the aliasing of the stimulation due to digitally sampling the data. We present Percept™ PC’s ability to extract biomarkers that may be used to optimize stimulation therapy. We show how differences in lead type affects noise characteristics of the implanted leads from seven epilepsy patients enrolled in our clinical trial. Percept™ PC has sufficient signal-to-noise ratio, sampling capabilities, and stimulus artifact rejection for neural activity recording. Limitations in sampling rate, potential artifacts during stimulation, and shortening of battery life when monitoring neural activity at home were observed. Despite these limitations, Percept™ PC demonstrates potential as a useful tool for recording neural activity in order to optimize stimulation therapies to personalize treatment.
Topology of 2D Dirac operators with variable mass and an application to shallow-water waves
Authors: Rossi Sylvain , Tarantola Alessandro 
Published: January 2024

Abstract
A Dirac operator on the plane with constant (positive) mass is a Chern insulator, sitting in class D of the Kitaev table. Despite its simplicity, this system is topologically ill-behaved: the non-compact Brillouin zone prevents definition of a bulk invariant, and naively placing the model on a manifold with boundary results in violations of the bulk-edge correspondence (BEC). We overcome both issues by letting the mass spatially vary in the vertical direction, interpolating between the original model and its negative-mass counterpart. Proper bulk and edge indices can now be defined. They are shown to coincide, thereby embodying BEC.
The shallow-water model exhibits the same illnesses as the 2D massive Dirac. Identical problems suggest identical solutions, and indeed extending the approach above to this setting yields proper indices and another instance of BEC.
How well does your e-nose detect cancer? Application of artificial breath analysis for performance assessment
Authors: Martin Justin D M , Claudia Falzone , Romain Anne-Claude 
Published: January 2024

Abstract
Comparing electronic nose (e-nose) performance is a challenging task because of a lack of standardised method. This paper proposes a method for defining and quantifying an indicator of the effectiveness of multi-sensor systems in detecting cancers by artificial breath analysis. To build this method, an evaluation of the performances of an array of metal oxide sensors built for use as a lung cancer screening tool was conducted. Breath from 20 healthy volunteers has been sampled in fluorinated ethylene propylene sampling bags. These healthy samples were analysed with and without the addition of nine volatile organic compound (VOC) cancer biomarkers, chosen from literature. The concentration of the VOC added was done in increasing amounts. The more VOC were added, the better the discrimination between ‘healthy’ samples (breath without additives) and ‘cancer’ samples (breath with additives) was. By determining at which level of concentration the e-nose fails to reliably discriminate between the two groups, we estimate its ability to well predict the presence of the disease or not in a realistic situation. In this work, a home-made e-nose is put to the test. The results underline that the biomarkers need to be about 5.3 times higher in concentration than in real breath for the home-made nose to tell the difference between groups with a sufficient confidence.
Carbon emission disclosure in the agriculture industry in Indonesia: The determinant factors
Authors: Ika S R , Puisi P U I S I , Vitaningsih C W , Ducati D , Widagdo A K 
Published: January 2024

Abstract
The agriculture industry in Indonesia, despite its huge contribution to the country’s economy, is responsible for a substantial amount of carbon emissions. Hence, according to the country’s stock exchange regulation, agriculturally listed companies shall annually report their carbon emissions and carbon emission mitigation. The main objective of our research is to analyze the factors that influence the reporting of greenhouse gas emissions by agriculture corporations. The examined factors are environmental performance, which is assessed through environmental performance ratings and environmental management certification, the released sustainability report, ownership structure, and financial characteristics. Using 91 publicly traded agriculture companies from 2019 to 2022 as a sample, the ordinally least squares regression analysis shows that publications of a company’s carbon emissions tend to rise in accordance with both the rating of its environmental performance and the issuance of its sustainability report. Institutional ownership and financial characteristics of a company do not have any relationship with the extent of carbon emission disclosures. This study delivers an understanding to the Financial Service Authority Agency that the environmental performance rating assessment by the KLH and the yearly sustainability report encourage companies to do activities related to environmental sustainability.
Access and function of oil palm farmers to information and communication technology in Riau Province, Indonesia
Authors: Yulida R , Rosnita R , Andriani Y , Septya F , Herlon M , Ikhwan M 
Published: January 2024

Abstract
Based on a 2018 study, it was discovered that nearly 60% of oil palm farmers in Riau Province have embraced the use of smartphones. This trend presents an opportunity for information and communication technology to be leveraged in oil palm development initiatives. The research aimed to explore how oil palm farmers utilize technology and access information. The survey method was employed, and respondents were selected from two districts in Riau Province where oil palm plantations have been developed and replanted. Only farmers who use smartphones were included, resulting in a sample size of 279. The study utilized quantitative descriptive analysis to examine farmers’ access to and use of smartphone technology. The findings show that farmers primarily use smartphones for entertainment, with WhatsApp and Facebook being the most popular apps. However, only 16% of farmers use their smartphones to check palm oil prices online, and a mere 3% have accessed websites for knowledge and skills relevant to oil palm farming. The study recommends the creation of social media apps that are user-friendly, easily accessible, and present information in a clear and understandable format.
Decay of Taylor–Green flow type initial conditions in a two-dimensional domain
Authors: Kandre Shivakumar , Patil Dhiraj V 
Published: January 2024

Abstract
Geophysical flows are often two-dimensional (2D) in nature. The decay dynamics of the canonical, symmetric initial conditions defined by the Taylor–Green (TG) flow is simulated in a 2D domain. The standard lattice Boltzmann equation method with the Bhatnagar–Gross–Krook collision model is employed. The vortex dynamics is investigated for bounded and unbounded flows with various sets of Gaussian vortices and varying Reynolds numbers. The formation of thin filaments and the generation of small-scale structures near the no-slip walls are found. To characterize the decay properties, the integral quantities, namely, kinetic energy, E(t), enstrophy,

Ω
(
t
)

, and palinstrophy, P(t), are tracked as a function of the eddy-turnover-time. The initial vortex population in the domain dictates the decay rate of these integral quantities. The energy spectra, E(k), are computed to investigate the effect of domain boundaries and vortex populations on energy distribution among different length scales for

Re

=
50
000

. The evolution of TG flow in a bounded domain shows an exponent close to −3, which may be attributed to the generation of thin filaments and small-scale structures in vortex-wall interactions. Exponent changes with an increase in the vortex populations.
ATSFCNN: a novel attention-based triple-stream fused CNN model for hyperspectral image classification
Authors: Cai Jizhen , Boust Clotilde , Mansouri Alamin 
Published: January 2024

Abstract
Recently, the convolutional neural network (CNN) has gained increasing importance in hyperspectral image (HSI) classification thanks to its superior performance. However, most of the previous research has mainly focused on 2D-CNN, and the limited applications of 3D-CNN have been attributed to its complexity, despite its potential to enhance information extraction between adjacent channels of the image. Moreover, 1D-CNN is typically restricted to the field of signal processing as it ignores the spatial information of HSIs. In this paper, we propose a novel CNN model named attention-based triple-stream fused CNN (ATSFCNN) that fuses the features of 1D-CNN, 2D-CNN, and 3D-CNN to consider all the relevant information of the hyperspectral dataset. Our contributions are twofold: First, we propose a strategy to extract and homogenize features from 1D, 2D, and 3D CNN. Secondly, we propose a way to efficiently fuse these features. This attention-based methodology adeptly integrates features from the triple streams, thereby transcending the former limitations of singular stream utilization. Consequently, it becomes capable of attaining elevated outcomes in the context of hyperspectral classification, marked by increased levels of both accuracy and stability. We compared the results of ATSFCNN with those of other deep learning models, including 1D-CNN, 2D-CNN, 2D-CNN+PCA, 3D-CNN, and 3D-CNN+PCA, and demonstrated its superior performance and robustness. Quantitative assessments, predicated on the metrics of overall accuracy (OA), average accuracy (AA), and kappa coefficient (κ) emphatically corroborate the preeminence of ATSFCNN. Notably, spanning the three remote sensing datasets, ATSFCNN consistently achieves peak levels of OA, quantified at 98.38%, 97.09%, and 96.93% respectively. This prowess is further accentuated by concomitant AA scores of 98.47%, 95.80%, and 95.80%, as well as kappa coefficient values amounting to 97.41%, 96.14%, and 95.21%.
Midgap state requirements for optically active quantum defects
Authors: Xiong Yihuang , Mathew Milena , Griffin Sinéad M , Sipahigil Alp , Hautier Geoffroy 
Published: January 2024

Abstract
Optically active quantum defects play an important role in quantum sensing, computing and communication. The electronic structure and the single-particle energy levels of these quantum defects in the semiconducting host have been used to understand their optoelectronic properties. Optical excitations that are central for their initialization and readout are linked to transitions between occupied and unoccupied single-particle states. It is commonly assumed that only quantum defects introducing levels well within the band gap and far from the band edges are of interest for quantum technologies as they mimic an isolated atom embedded in the host. In this perspective, we contradict this common assumption and show that optically active defects with energy levels close to the band edges can display similar properties. We highlight quantum defects that are excited through transitions to or from a band-like level (bound exciton) such as the T center and Se

S
i

+

in silicon. We also present how defects such as the silicon split-vacancy in diamond can involve transitions between localized levels that are above the conduction band or below the valence band. Loosening the commonly assumed requirement on the electronic structure of quantum defects offers opportunities in quantum defects design and discovery especially in smaller band gap hosts such as silicon. We discuss the challenges in terms of operating temperature for photoluminescence or radiative lifetime in this regime. We also highlight how these alternative type of defects bring their own needs in terms of theoretical developments and fundamental understanding. This perspective clarifies the electronic structure requirement for quantum defects and will facilitate the identification and design of new color centers for quantum applications especially driven by first principles computations.