bluuebunny/crossref_metadata_2025_split huggingface dataset:
Particle-resolved optical diagnostics of solid fuel combustion for clean power generation: a review
Authors: Li Tao , Geschwindner Christopher , Dreizler Andreas , Böhm Benjamin 
Published: August 2023

Abstract
Chemical energy carriers are crucial for addressing challenges that arise from time lag, large distances, and temporal fluctuations in renewable energy production, which lead to unbalanced energy production and demand. The thermochemical utilization of chemical energy carriers such as solid fuels must be decarbonized to achieve a climate-neutral circular economy as soon as possible, while remaining important for reliable electricity generation and stable economics. To accomplish this, extensive fundamental research is required to understand the underlying chemical and physical processes that can potentially be realized at an industrial scale. This paper reviews optical diagnostics used for particle-level combustion studies for clean power generation applications. The focus is on particle-resolved optical experiments for oxy-fuel coal combustion, biomass combustion, and utilization of iron in regenerative oxidation–reduction schemes. Previous studies are categorized by fuel and reactor types, investigated parameters, and experimental methodology. Phenomenological aspects of the multi-stage combustion process at the particle level are outlined using examples of bituminous coal and iron particle burning in hot gas. A selection of experimental studies is highlighted, with a particular methodological focus on measuring quantities at the particle level. These representative examples address relevant parameters, including particle number density, particle size and shape, surface temperature, ignition and combustion time, gas flame structure, gas temperature and species, nanoparticle formation, gas velocity, and particle dynamics. Finally, issues and problems that require further effort to improve diagnostics for solid fuel combustion studies are discussed.
MAS-Net:Multi-modal Assistant Segmentation Network For Lumbar Intervertebral Disc
Authors: Qinhong Du , Yue He , Wendong Bu , Yukun Du , Huan Yang , Yongming Xi 
Published: August 2023

Abstract

Objective. Despite advancements in medical imaging technology, the diagnosis and positioning of lumbar disc diseases still heavily rely on the expertise and experience of medical professionals. This process is often time-consuming, labor-intensive, and susceptible to subjective factors. Achieving automatic positioning and segmentation of lumbar intervertebral disc (LID) is the first and critical step in intelligent diagnosis of lumbar disc diseases. However, due to the complexity of the vertebral body and the ambiguity of the soft tissue boundaries of the LID, accurate and intelligent segmentation of LIDs remains challenging. The study aims to accurately and intelligently segment and locate LIDs by fully utilizing multi-modal lumbar magnetic resonance Images (MRIs). Approach. A novel multi-modal assistant segmentation network (MAS-Net) is proposed in this paper. The architecture consists of four key components: the multi-branch fusion encoder (MBFE), the cross-modality correlation evaluation (CMCE), the channel fusion transformer (CFT), and the selective Kernel (SK) based decoder. The MBFE module captures and integrates various modal features, while the CMCE module facilitates the fusion process between the MBFE and decoder. The CFT module selectively guides the flow of information between the MBFE and decoder and effectively utilizes skip connections from multiple layers. The SK module computes the significance of each channel using global pooling operations and applies weights to the input feature maps to improve the models recognition of important features. Main results. The proposed MAS-Net achieved a dice coefficient of 93.08% on IVD3Seg and 93.22% on DualModalDisc dataset, outperforming the current state-of-the-art network, accurately segmenting the LIDs, and generating a 3D model that can precisely display the LIDs. Significance. MAS-Net automates the diagnostics process and addresses challenges faced by doctors. Simplifying and enhancing the clarity of visual representation, multi-modal MRI allows for better information complementation and LIDs segmentation. By successfully integrating data from various modalities, the accuracy of LID segmentation is improved.
Unsupervised learning-based dual-domain method for low-dose CT denoising
Authors: Yu Jie , Zhang Huitao , Zhang Peng , Zhu Yining 
Published: August 2023

Abstract

Objective. Low-dose CT (LDCT) is an important research topic in the field of CT imaging because of its ability to reduce radiation damage in clinical diagnosis. In recent years, deep learning techniques have been widely applied in LDCT imaging and a large number of denoising methods have been proposed. However, One major challenge of supervised deep learning-based methods is the exactly geometric pairing of datasets with different doses. Therefore, the aim of this study is to develop an unsupervised learning-based LDCT imaging method to address the aforementioned challenges. Approach. In this paper, we propose an unsupervised learning-based dual-domain method for LDCT denoising, which consists of two stages: the first stage is projection domain denoising, in which the unsupervised learning method Noise2Self is applied to denoise the projection data with statistically independent and zero-mean noise. The second stage is an iterative enhancement approach, which combines the prior information obtained from the generative model with an iterative reconstruction algorithm to enhance the details of the reconstructed image. Main results. Experimental results show that our proposed method outperforms the comparison method in terms of denoising effect. Particularly, in terms of SSIM, the denoised results obtained using our method achieve the highest SSIM. Significance. In conclusion, our unsupervised learning-based method can be a promising alternative to the traditional supervised methods for LDCT imaging, especially when the availability of the labeled datasets is limited.
A non-destructive method for detecting turn-to-turn resistivity distribution in NI REBCO coils
Authors: Wu Wei , Lu Li , Zhong Zhuoyan , Li Kai , Jin Zhijian 
Published: August 2023

Abstract
A non-destructive method is proposed for detecting the turn-to-turn resistivity distribution (TTRD) of non-insulation (NI) coils made of REBCO tapes. In conventional designs, TTRD is often estimated to be a constant, while it is actually non-uniform. It is crucial to detect the TTRD of NI coils more accurately as it determines the behaviour of NI coils and may lead to peculiar phenomena such as local reverse currents. The proposed approach involves acquiring the temporal change of voltage distribution during an excitation/demagnetization process, which is subsequently incorporated into a system of ordinary differential equations derived from an equivalent circuit model. A genetic algorithm (GA) is then employed to fit the collected time-varying voltage data and generate the results of the ‘measured’ TTRD. The system of equations can actually be numerically solved. The solved time-varying TTRD results are averaged over the measuring period, which serve as the initial value of GA fitting, and accelerates the fitting process. Virtual measurements were performed on an artificially established mock coil, demonstrating high accuracy in reproducing the predetermined TTRD. Furthermore, an actual measurement was also conducted on a single-pancake coil, however with unknown TTRD, using eight voltage measurement points during the demagnetization process. The measured TTRD was incorporated into the equivalent circuit model to predict the temporal changes in voltage and magnetic field of the coil under additional excitation/demagnetization conditions. By comparing the predicted results with the experimental data, a high level of agreement was observed, thus confirming the potential application of the proposed method.
On analytical study of Griffith crack propagation in a transversely isotropic dry sandy punch pressured strip
Authors: Singh Ajeet Kumar , Singh Abhishek Kumar , Kaushik Shubham Kumar 
Published: August 2023

Abstract
The present study focuses on the propagation of a Griffith crack in an infinitely extending finitely thick transversely isotropic dry sandy strip with moving parallel punch pressure acting at the bounding surface of the layer because of the propagation of plane waves under mechanical point loading. Furthermore, the present model is developed using coupled singular integral equations, Dirac delta function & Cauchy-type singularities; it is applied to investigate the point load at the moving crack edge, and Hilbert transformation properties are also used to derive the stress intensity factor (SIF) with constant point loading in closed form. Numerical computation & graphical demonstrations have been provided to examine the influence of the prevailing parameters, viz. length & speed of the crack, pressure of the punch, sandiness parameter and different positions of point load, on the SIF for transversely isotropic dry sandy and also for isotropic material strips. A comparative study of the SIF at the tip of moving crack has been carried out for the transversely isotropic dry sandy strip and isotropic materials strip with and without punch pressure and sandiness to highlight some of the important peculiarities of the problem.
Nonlinear localized wave modes in optomechanical array
Authors: Houwe Alphonse , Djorwé Philippe , Souleymanou Abbagari , Nana Engo Serge Guy , Doka Serge Yamigno 
Published: August 2023

Abstract
Optomechanical arrays have been used in many areas of research, from nonlinear optics to acoustics. In particular, the optomechanical array has been studied for its interesting properties such as strong optical force and high frequency resonance. In this work, we carry out the modulated wave patterns and nonlinear modes by driving one end of the optomechanical array in the forbidden gap. We use the discrete nonlinear Schrödinger equation with self-Kerr nonlinear term to determine the threshold amplitude. We then consider the driven amplitude to drive the model above the phonon band. The result is a train of waves with an asymmetric shape in the forbidden gap. For large values of the nonlinear term, we observe unstable modes of the modulation growth rates and the modulated wave patterns also emerge from the driven optomechanical array. At the specific cell index, the pulse train increases in amplitude and brings instability in the bandgap. These results open a new feature of the position modulated self-Kerr nonlinear term as an internal force to drive the nonlinear Schrödinger equation.
Towards a large-area RPWELL detector: design optimization and performance
Authors: Zavazieva D. , Moleri L. , Jash A. , Sela G. , de Vito-Halevy F. , Bressler S. 
Published: August 2023

Abstract
We present a new design and assembly procedure of a
large-area gas-avalanche Resistive-Plate WELL (RPWELL) detector. A
50 × 50 cm2 prototype was tested in
80 GeV/c muon beam at CERN-SPS, presenting improved
performances compared to previous ones: MIP detection efficiency
over 96% with 3% uniformity across the entire detector area, a
charge gain of ≈ 7.5 × 103 with a uniformity of 22%,
and discharge probability below 10-6 with a few single
hotspots attributed to production imperfections. These results pave
the way towards further up-scaling detectors of this kind.
PDOZ: innovative personal electronic dosimeter for electron and gamma H
*(d) dosimetry
Authors: Salvi Lucia , Rossi Giulia , Bartolini Giovanni , Alpat Ali Behcet , Bozkurt Arca , Cegil Mustafa Dogukan , Guleryuz Ahmet Talha 
Published: August 2023

Abstract
The personal (or active) electronic dosimeters (PEDs) are
devices used to determine the individual exposure to ionizing
radiations and they are employed in hospitals, research laboratories
and nuclear power plants. The PDOZ project is a personal electronic
dosimeter able to detect, discriminate and measure the delivered
dose by beta particles and gamma rays. In this paper, several Monte
Carlo simulations are described. The first one is regarding the ICRU
sphere, [11,12] implemented to evaluate the ambient
dose equivalent, H
*(10), and the fluence-to-dose equivalent
conversion coefficients for gamma rays and beta particles. The
second simulation is carried out to study the prototype dosimeter
response to gamma rays and beta particles and, also thanks to
previous one, to obtain the conversion curve necessary to calculate
the ambient dose equivalent from the silicon photomultipliers
counts. In the last one, instead, the performance of a prototype
dosimeter, composed by a small plastic scintillator coupled to two
SiPMs, is evaluated and a simulation with different radioactive
sources is made whose results are compared with the experimental
measurements. All simulations are carried out by Geant4 including
the optical photon transport.
Fabrication and in vitro evaluation of photo cross-linkable silk fibroin–epsilon-poly-L-lysine hydrogel for wound repair
Authors: Sundaran Sneha , Kok Li-Ching , Chang Hwan-You 
Published: August 2023

Abstract
An optimal wound-healing hydrogel requires effective antibacterial properties and a favorable cell adhesion and proliferation environment. Although Bombyx mori silk fibroin (SF) possesses inherent wound-healing properties, it lacks these essential qualities. This study aimed to fabricate a novel photo-polymerizable hydrogel by utilizing SF’s wound-healing efficiency and the epsilon-poly-L-lysine (EPL) antimicrobial activity. The SF was modified with three different concentrations of glycidyl methacrylate (GMA) to obtain SF–GMA(L), SF–GMA(M), and SF–GMA(H). A methacrylated EPL (EPL–GMA) was also produced. Then, SF–GMA was mixed with EPL–GMA to produce photo-crosslinkable SF–GMA–EPL hydrogels. The SF–GMA(L)–EPL, SF–GMA(M)–EPL, and SF–GMA(H)–EPL hydrogels, fabricated with 20% EPL–GMA, demonstrated maximum antimicrobial activity and mammalian cell adhesion ability. The hydroxyl radical (•OH) scavenging efficiency of the hydrogels was tested and shown to be between 69% and 74%. These hydrogels also exhibited 60% efficiency in removing bacterial lipopolysaccharides. The water absorption ability of the hydrogels was consistent with the size of their internal pores. The hydrogels exhibited a slow degradation fashion, and their degradation products appeared cytocompatible. Finally, the elastomeric properties of the hydrogels were determined, and a storage modulus (G′) of 300–600 Pa was demonstrated. In conclusion, the hydrogels created in this study possess excellent biological and physical properties to support wound healing.
Nonperturbative gravity corrections to bulk reconstruction
Authors: Gesteau Elliott , Kang Monica Jinwoo 
Published: August 2023

Abstract
We introduce a new algebraic framework for understanding nonperturbative gravitational aspects of bulk reconstruction with a finite or infinite-dimensional boundary Hilbert space. We use relative entropy equivalence between bulk and boundary with an inclusion of nonperturbative gravitational errors, which give rise to approximate recovery. We utilize the privacy/correctability correspondence to prove that the reconstruction wedge, the intersection of all entanglement wedges in pure and mixed states, manifestly satisfies bulk reconstruction. We explicitly demonstrate that local operators in the reconstruction wedge of a given boundary region can be recovered in a state-independent way for arbitrarily large code subspaces, up to nonperturbative errors in GN
. We further discuss state-dependent recovery beyond the reconstruction wedge and the use of the twirled Petz map as a universal recovery channel. We discuss our setup in the context of quantum islands and the information paradox.
Photon centroids and their subluminal propagation
Authors: Bliokh Konstantin Y 
Published: August 2023

Abstract
We examine properties of the energy-density and photon-probability centroids of electromagnetic wavepackets in free space. In the second-order paraxial approximation, both of these centroids propagate with the same subluminal velocity because of the transverse confinement of the wavepacket and its diffraction. The tiny difference between the energy and probability centroid velocities appears only in the fourth order. We consider three types of wavepackets: Gaussian, Bessel, and non-diffracting Bessel. In all these cases, the subluminal propagation is clearly visible in the intensity distributions and can be measured experimentally in both classical-light and single-photon regimes. For Gaussian wavepackets, the half-wavelength delay is accumulated after propagation over about 12 Rayleigh lengths.
Comparison of printing techniques for the fabrication of flexible carbon nanotube-based ammonia chemiresistive gas sensors
Authors: Vasquez Sahira , Costa Angeli Martina Aurora , Petrelli Mattia , Ahmad Mukhtar , Shkodra Bajramshahe , Salonikidou Barbara , Sporea Radu A , Rivadeneyra Almudena , Lugli Paolo , Petti Luisa 
Published: August 2023

Abstract
Even though a plethora of printing technologies are currently available and their potential for the fabrication of low-cost and flexible sensors has been widely investigated, systematically based, and statistically sustained comparative studies are missing in the literature. In this work, we compare screen, inkjet, and dispense printing for the fabrication of carbon nanotube (CNT)-based ammonia (NH3) chemiresistive flexible gas sensors for the first time. Moreover, we report the first CNT-based gas sensor fabricated via Voltera printer. The devices were made of a thin layer of spray-coated CNTs and printed silver-based interdigitated electrodes. To draw a thoughtful comparison the same sensor layout, materials, and fabrication flow were used. The device morphological features were acquired through microscopic, atomic force microscope, and 3D images; additionally, the response to NH3 as well as the printing process characteristics for each technique was analyzed. From 300 µm nominal spacing between lines, we obtained a decrease of 25%, 13%, and 5% on the printed spacings with dispense, screen, and inkjet printing, respectively. At 100 ppm of NH3, a maximum response of 33%, 31%, and 27% with the dispense-, inkjet-, and screen-printed sensors were found, respectively. Statistical differences were observed between the mean values on the NH3 response of dispense- compared to the inkjet- and screen-printed sensors, which in effect showed the highest response in the Tukey test. This demonstrated that the fabrication technique employed can induce a different response mainly driven by the printed outcomes. Following a holistic approach that includes the sensor response, the application, the market perspective, and the process versatility, we suggest screen printing as the most suitable method for CNT-based NH3 gas sensor fabrication.
Quantum gates with oscillating exchange interaction
Authors: Nguyen Daniel Q L , Heinz Irina , Burkard Guido 
Published: August 2023

Abstract
Two-qubit gates between spin qubits are often performed using a rectangular or an adiabatic exchange interaction pulse resulting in a CZ gate. An oscillating exchange pulse not only performs a CZ gate, but also enables the iSWAP gate, which offers more flexibility to perform quantum algorithms. We provide a detailed description for two-qubit gates using resonant and off-resonant exchange pulses, give conditions for performing the respective gates, and compare their performance to the state-of-the-art static counterpart. We find that for relatively low charge noise the gates still perform reliably and compare to the conventional CZ gate.
Resource frugal optimizer for quantum machine learning
Authors: Moussa Charles , Hunter Gordon Max , Baczyk Michal , Cerezo M , Cincio Lukasz , Coles Patrick J 
Published: August 2023

Abstract
Quantum-enhanced data science, also known as quantum machine learning (QML), is of growing interest as an application of near-term quantum computers. Variational QML algorithms have the potential to solve practical problems on real hardware, particularly when involving quantum data. However, training these algorithms can be challenging and calls for tailored optimization procedures. Specifically, QML applications can require a large shot-count overhead due to the large datasets involved. In this work, we advocate for simultaneous random sampling over both the dataset as well as the measurement operators that define the loss function. We consider a highly general loss function that encompasses many QML applications, and we show how to construct an unbiased estimator of its gradient. This allows us to propose a shot-frugal gradient descent optimizer called Refoqus (REsource Frugal Optimizer for QUantum Stochastic gradient descent). Our numerics indicate that Refoqus can save several orders of magnitude in shot cost, even relative to optimizers that sample over measurement operators alone.
Urban theories and urbanization perspectives in cities across Nigeria
Authors: Essien Etido 
Published: August 2023

Abstract
One of the emerging research trends from urbanization is the study of urban growth patterns. These growth patterns are primarily based on the growth of the local economy that directly affects agricultural lands. In Africa, the local economy has spurred the extinction of many agrarian sectors. Yet, few studies at the regional level have paid attention to these changes. Using diverse scientific literature on global urbanization, urban remote sensing, and economic geography, this study aimed to understand the theory behind urban developments in Nigeria. The primary data were collected in two study regions in the country’s eastern and southern parts, making it a large dataset to assess urban formation in these areas. We examined the evolution of urban development from the perspectives of infrastructural development, expansion, change in land use, and urban job migration opportunities that affect agrarian activities. White-collar job opportunities are limited in urban areas, substantially increasing the startup of small-scale businesses. We introduce the notion of natural resource urbanism, which implies urbanization that is triggered by the influx of natural resource revenue to strengthen the dwindling local economy. The infusion of a shared natural resource revenue creates a reform in the local economy and the advent of a consumption-based economy. A shared natural resource revenue drives massive infrastructural developments, but the dependence on the availability of those natural resources in the states raises concerns about its long-term sustainability for strengthening the local economy.