bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Stone-Wales defects on the mechanical properties of TiAl/CNT core-shell nanowires
Authors: Wang Nan , Gao Tinghong , Yan Wanjun , Ding Yi , Xie Quan 
Published: August 2024

Abstract
In this study, the effect of Stone-Wales (SW) defects on the mechanical properties of TiAl/CNT core-shell nanowire was studied using molecular dynamics simulations. Our study revealed that SW defects can reduce the ultimate tensile strength and the fracture strain of TiAl/CNT core-shell nanowires. Notably, the ultimate tensile strength of TiAl/CNT core-shell nanowires initially decreased and then increased with the increasing number of SW defects. Conversely, the effect of SW defects on the Young’s modulus of TiAl/CNT core-shell nanowires was less pronounced, with the Young’s modulus showing little dependence on the presence of SW defects. The effect on the mechanical properties is a result of the combined effect of lattice changes, Stair-rod and Hirth dislocations, laminar faults and voids brought by the SW defects. These results provide new insights for further design and fabrication of advanced materials.
An ab initio analysis of the electronic, optical, and thermoelectric characteristics of the Zintl phase CsGaSb2
Authors: Al-Essa Sumayah , Saad Essaoud Saber , Bouhemadou Abdelmadjid , Ketfi Mohammed Elamin , Maabed Said , Djilani Fatima , Bin-Omran Saad , Radjai Missoum , Allali Djamel , Khenata Rabah , Al-Douri Yarub 
Published: August 2024

Abstract
We present and analyze the findings of a comprehensive ab initio computation that examines the electronic, optical, and thermoelectric characteristics of a recently synthesized Zintl compound known as CsGaSb2. The electronic and optical characteristics were examined using the DFT-based FP-L/APW+loapproach. Toaddress the exchange–correlation effects, we employed the GGA-PBEsol and TB-mBJ approaches.The CsGaSb2 semiconductor exhibits an indirect bandgap of 0.695 eV when analyzed with the GGA-PBEsol approach, and a bandgap of 1.254 eV when analyzed with the TB-mBJ approach.The PDOS diagrams were used to discover the origins of the electronic states that make up the energy bands. The charge density study reveals that the Ga-Sb link within the [GaSb2] block is mostly governed by a covalent character, whereas the cation Cs+ and polyanion [MSb2]−bonding is predominantly ionic. The frequency dependence of macroscopic linear optical coefficients was evaluated over a broad range of photon energies from 0 to 25 eV. The thermoelectric characteristics were investigated via the Boltzmann kinetic transport theoryassuming a constant relaxation time.The compound’s figure of merit at a temperature of 900 K is roughly 0.8.
Analysis of the periodic variation of pellet ablation radiation intensity in ASDEX Upgrade
Authors: Lang P.T. , Conway G.D. , Kardaun O.J.W.F. , Maraschek M. , Pégourié B. , Ploeckl B. , Samulyak R. ,   the ASDEX Upgrade Team
Published: August 2024

Abstract
In a future fusion reactor, the main fuelling method will likely rely on the injection of solid hydrogen pellets. Current predictions assume that this goal can be achieved, since being based on a technology which is already largely developed. However, this belief is founded on modelling tools that are usually aligned to the observation made in existing devices and then extrapolated to reactor conditions. This approach needs a sound consideration of its intrinsic restrictions and any observed feature not reproduced by the utilised codes should be applied to check their validation and possibly contribute to their refinement. One specific feature still lacking an explanation of a reasonable and self-consistent mechanism in the current models is the appearance of a phenomenon called striations, which are high frequency variations in the radiation emitted during the pellet ablation process. In order to provide a sound and reliable database for further considerations, a dedicated analysis of this effect has been performed on the mid-size tokamak ASDEX Upgrade. Therefore, such cases have been selected with the relevant signal recorded with sufficient temporal resolution during experiments covering a wide variation of plasma and pellet parameters which are regarded to be potentially influential on the striation pattern. In addition, it was ensured that for any specific case the observed behaviour was reproducible for several individual ablation events under identical conditions. In all cases considered, the observed radiation-intensity variations appear with a typical pattern showing a broad peak of frequencies in the range 50–150 kHz. This characteristic unveils a notable resilience against any parameter variation. This new collection of data can now act as firm basis to corroborate future modelling code-validation efforts. In addition, the analysis method can provide a relatively simple way of reviewing future modelling predictions.
A long-pulse small edge-localized-mode high-confinement plasma with detachment feedback control by floating potential in an experimental advanced superconducting tokamak in a metal wall environment
Authors: Ding G.F. , Xu G.S. , Tao Y.Q. , Wu K. , Yu L. , Lin X. , Meng L.Y. , Wang L. , Yang Q.Q , Chen R. , Liang R.R. , Li K.D. , Zang Q. , Zhou Z.Q. , Yuan Q.P. , Xu J.C. 
Published: August 2024

Abstract
One of the key challenges facing magnetic fusion research is to demonstrate the compatibility between high confinement and radiative divertors in long-pulse discharges with a metal wall environment. A small edge-localized-mode (ELM) high-confinement plasma with an energy confinement factor H
98 ∼ 1.1 and Greenwald density fraction f
GW ∼ 0.65 maintained for 26 s is obtained in the upgraded lower divertor of the Experimental Advanced Superconducting Tokamak (EAST), and periodical detachment is achieved through active control of neon impurity seeding in this long-pulse discharge. For the divertor region, partial detachment is achieved periodically on the outer divertor target plates with the plasma temperature near the outer strike point decreasing to below 5 eV and the peak surface temperature on the outer divertor target plates maintained below 350 °C. The peak heat flux of the lower outer divertor decreases significantly and its profile along the target becomes very flat in the detached state. Two low-frequency (<10 kHz) fluctuations that are related to the rippling mode caused by a resistive instability appear in the detached state. For the pedestal region, the electron pressure profile is flatter and the ELM amplitude is smaller in the detached state than that in the attached state. Edge-coherent mode appears in the attached state and disappears in the detached state. To achieve this experimentally, a new impurity seeding feedback control scheme is applied, where the floating potential measured by divertor Langmuir probes is used as a feedback sensor, which is more reliable in long-pulse discharges with high heat fluxes and thus more suitable for application in future devices. This study provides a new approach for the actively controlled radiative divertor as a solution to the divertor heat loads of future fusion reactors.
Ensemble seasonal forecasting of typhoon frequency over the western North Pacific using multiple machine learning algorithms
Authors: Xiao Zhixiang , Wang Ziqian , Luo Xiaoli , Yao Cai 
Published: August 2024

Abstract
This study introduces an ensemble prediction methodology employing multiple machine learning algorithms for forecasting the frequency of typhoons (TYFs) over the western North Pacific (WNP) during June‒November. Potential predictors were initially identified based on the relationships between the year-by-year variation (DY) of the TYFs and preseason (March–May) environmental factors. These predictors were subsequently further refined, resulting in the selection of eight key predictors. Prediction models were constructed using twenty machine learning algorithms, utilizing data from 1965 to 2010. These trained models were then applied to perform hindcasts of TYFs from 2011 to 2023. The forecasted DY was added to the observed TYF of the preceding year to obtain the current year’s TYF. The results indicate that the TYFs predicted by the multi-model ensemble (MME) closely align with the observation during the hindcast period. Compared to individual models, the MME improves the prediction skill for the DY by at least 5.56% and up to 56.92%. Furthermore, the mean bias of the MME for TYF is notably smaller than that of the ECMWF’s most recent seasonal forecasting system (SEAS5) in the years of 2017‒2023. The superior performance of the ensemble prediction approach was also validated through leave-one-out cross-validation. This research underscores the potential of ensemble prediction approach utilizing multiple machine learning algorithms to improve the forecasting skill of TYF over the WNP.
Systematic large flavor fTWA approach to interaction quenches in the Hubbard model
Authors: Osterkorn Alexander , Kehrein Stefan 
Published: August 2024

Abstract
We study the nonequilibrium dynamics after an interaction quench in the two-dimensional Hubbard model using the recently introduced fermionic truncated Wigner approximation (fTWA). To assess the range of validity of the method in a systematic way, we consider the SU(N) Hubbard model with the fermion degeneracy N as a natural semiclassical expansion parameter. Using both a numerical and a perturbative analytical approach we show that fTWA is exact at least up to and including the prethermalization dynamics. We discuss the limitations of the method beyond this regime.
Novel ASEP-inspired solutions of the Yang-Baxter equation
Authors: Barik Suvendu , Garkun Alexander S , Gritsev Vladimir 
Published: August 2024

Abstract
We explore the algebraic structure of a particular ansatz of the Yang-Baxter equation (YBE), which is inspired by the Bethe Ansatz treatment of the asymmetric simple exclusion process spin-model. Various classes of Hamiltonian density arriving from the two types of R-matrices are found, which also appear as solutions of the constant YBE. We identify the idempotent and nilpotent categories of such constant R-matrices and perform a rank-1 numerical search for the lowest dimension. A summary of the final results reveals general non-Hermitian spin-1/2 chain models.
In vitro three-dimensional volumetric printing of vitreous body models using decellularized extracellular matrix bioink
Authors: Kong Jeong Sik , Kim Joeng Ju , Riva Leonardo , Ginestra Paola Serena , Cho Dong-Woo 
Published: August 2024

Abstract
Hyalocytes, which are considered to originate from the monocyte/macrophage lineage, play active roles in vitreous collagen and hyaluronic acid synthesis. Obtaining a hyalocyte-compatible bioink during the 3D bioprinting of eye models is challenging. In this study, we investigated the suitability of a cartilage-decellularized extracellular matrix (dECM)-based bioink for printing a vitreous body model. Given that achieving a 3D structure and environment identical to those of the vitreous body necessitates good printability and biocompatibility, we examined the mechanical and biological properties of the developed dECM-based bioink. Furthermore, we proposed a 3D bioprinting strategy for volumetric vitreous body fabrication that supports cell viability, transparency, and self-sustainability. The construction of a 3D structure composed of bioink microfibers resulted in improved transparency and hyalocyte-like macrophage activity in volumetric vitreous mimetics, mimicking real vitreous bodies. The results indicate that our 3D structure could serve as a platform for drug testing in disease models and demonstrate that the proposed printing technology, utilizing a dECM-based bioink and volumetric vitreous body, has the potential to facilitate the development of advanced eye models for future studies on floater formation and visual disorders.
Analyzing the likelihood of OAM mode energy transfer in turbulent environments with stochastic Cn
2
Authors: Kupferman Judy , Arnon Shlomi 
Published: August 2024

Abstract
Orbital angular momentum (OAM) is a crucial property of electromagnetic waves used in various applications such as free space communication, light detection and ranging, and remote sensing. However, turbulence can disrupt OAM-based systems by causing energy transfer between OAM modes, significantly impacting emerging fields in the optical spectrum. While traditional analyses assumed a constant turbulence parameter (Cn
2), recent research highlights its stochastic nature in specific scenarios. Our study introduces a new model that considers the stochastic nature of Cn
2. By incorporating this characteristic, our approach provides better predictions of system performance and valuable insights for accurately characterizing and designing communication and remote sensing systems in weak turbulent environments, enhancing their reliability and efficiency.
A combinatorial approach to validate the surface plasmon resonance (SPR) biosensor response
Authors: Chopra Aditi , Mohanta Girish C , Pal Sudipta S 
Published: August 2024

Abstract
One of the fundamental challenges of working with surface plasmon resonance (SPR) biosensors is their inherent lack of specificity. Being very sensitive to minute refractive index (RI) changes in their surrounding medium, SPR biosensors are highly susceptible to variations in pH, temperature, and buffer composition. Therefore, it is often necessary to include an additional validation step downstream to SPR biosensing, particularly for clinical analysis. In this proof-of-study work, we have tried to evaluate the utility of surface-enhanced Raman scattering (SERS) tags as secondary labels for validating SPR biosensor response. Accordingly, a Fibre-optic SPR (FO-SPR) biosensor set-up was fabricated by immobilizing anti-BSA antibodies on the sensor platform for capturing and sensing biotinylated-BSA as a model analyte. Subsequently, the bound analyte and the concomitant shift in SPR response were validated by employing streptavidin-functionalized SERS tags. Intriguingly, apart from validation of the SPR response, the SERS tags also significantly improved the sensitivity of the SPR response and provided semi-quantitative information on the bound analyte. Although utilizing SERS tags undermines the label-free tag of SPR biosensors, the huge improvement in sensitivity and specificity of the sensor makes it suitable for clinical analysis. Furthermore, SERS measurements with a portable Raman spectrometer utilized in this study further highlight the potential of this approach for achieving point-of-care (POC) sensing.
FMD-UNet: fine-grained feature squeeze and multiscale cascade dilated semantic aggregation dual-decoder UNet for COVID-19 lung infection segmentation from CT images
Authors: Wang Wenfeng , Mao Qi , Tian Yi , Zhang Yan , Xiang Zhenwu , Ren Lijia 
Published: August 2024

Abstract
With the advancement of computer-aided diagnosis, the automatic segmentation of COVID-19 infection areas holds great promise for assisting in the timely diagnosis and recovery of patients in clinical practice. Currently, methods relying on U-Net face challenges in effectively utilizing fine-grained semantic information from input images and bridging the semantic gap between the encoder and decoder. To address these issues, we propose an FMD-UNet dual-decoder U-Net network for COVID-19 infection segmentation, which integrates a Fine-grained Feature Squeezing (FGFS) decoder and a Multi-scale Dilated Semantic Aggregation (MDSA) decoder. The FGFS decoder produces fine feature maps through the compression of fine-grained features and a weighted attention mechanism, guiding the model to capture detailed semantic information. The MDSA decoder consists of three hierarchical MDSA modules designed for different stages of input information. These modules progressively fuse different scales of dilated convolutions to process the shallow and deep semantic information from the encoder, and use the extracted feature information to bridge the semantic gaps at various stages, this design captures extensive contextual information while decoding and predicting segmentation, thereby suppressing the increase in model parameters. To better validate the robustness and generalizability of the FMD-UNet, we conducted comprehensive performance evaluations and ablation experiments on three public datasets, and achieved leading Dice Similarity Coefficient (DSC) scores of 84.76, 78.56 and 61.99% in COVID-19 infection segmentation, respectively. Compared to previous methods, the FMD-UNet has fewer parameters and shorter inference time, which also demonstrates its competitiveness.
Evaluation of TOPAS MC tool performance in optical photon transport and radioluminescence-based dosimetry
Authors: Khodaei A , Moradi F , Oresegun A , Zubair H T , Bradley D A , Ibrahim S A , Abdul-Rashid H A 
Published: August 2024

Abstract
Radiation therapy plays a pivotal role in modern cancer treatment, demanding precise and accurate dose delivery to tumor sites while minimizing harm to surrounding healthy tissues. Monte Carlo simulations have emerged as indispensable tools for achieving this precision, offering detailed insights into radiation transport and interaction at the subatomic level. As the use of scintillation and luminescence dosimetry becomes increasingly prevalent in radiation therapy, there arises a need for validated Monte Carlo tools tailored to optical photon transport applications. In this paper, an evaluation process of the TOPAS (TOol for PArticle Simulation) Monte Carlo tool for Cerenkov light generation, optical photon transport and radioluminescence based dosimetry is presented. Three distinct sources of validation data are utilized: one from a published set of experimental results and two others from simulations performed with the Geant4 code. The methodology employed for evaluation includes the selection of benchmark experiments, making use of opt3 and opt4 Geant4 physics models and simulation setup, with observed slight discrepancies within the calculation uncertainties. Additionally, the complexities and challenges associated with modeling optical photons generation through luminescence or Cerenkov radiation and their transport are discussed. The results of our evaluation suggests that TOPAS can be used to reliably predict Cerenkov generation, luminescence phenomenon and the behavior of optical photons in common dosimetry scenarios.
Classification of optic neuritis in neuromyelitis optica spectrum disorders (NMOSD) on MRI using CNN with transfer learning and manipulation of pre-processing on augmentation
Authors: Feng Yang , Chow Li Sze , Gowdh Nadia Muhammad , Ramli Norlisah , Tan Li Kuo , Abdullah Suhailah 
Published: August 2024

Abstract
Neuromyelitis optica spectrum disorder (NMOSD), also known as Devic disease, is an autoimmune central nervous system disorder in humans that commonly causes inflammatory demyelination in the optic nerves and spinal cord. Inflammation in the optic nerves is termed optic neuritis (ON). ON is a common clinical presentation; however, it is not necessarily present in all NMOSD patients. ON in NMOSD can be relapsing and result in severe vision loss. To the best of our knowledge, no study utilises deep learning to classify ON changes on MRI among patients with NMOSD. Therefore, this study aims to deploy eight state-of-the-art CNN models (Inception-v3, Inception-ResNet-v2, ResNet-101, Xception, ShuffleNet, DenseNet-201, MobileNet-v2, and EfficientNet-B0) with transfer learning to classify NMOSD patients with and without chronic ON using optic nerve magnetic resonance imaging. This study also investigated the effects of data augmentation before and after dataset splitting on cropped and whole images. Both quantitative and qualitative assessments (with Grad-Cam) were used to evaluate the performances of the CNN models. The Inception-v3 was identified as the best CNN model for classifying ON among NMOSD patients, with accuracy of 99.5%, sensitivity of 98.9%, specificity of 93.0%, precision of 100%, NPV of 99.0%, and F1-score of 99.4%. This study also demonstrated that the application of augmentation after dataset splitting could avoid information leaking into the testing datasets, hence producing more realistic and reliable results.
Evaluation of suitable sites for concentrated solar power desalination systems: case study of Mauritania
Authors: Ntaghry Khadijetou , Thiam Ababacar , Habib Sidahmed Mohamed Sidi , Faye Kory , Faye Mactar 
Published: August 2024

Abstract
It is imperative to address the critical problem of water scarcity in sub-Saharan Africa, especially in light of the aggravating effects of climate change brought on by the extraction of fossil fuels. In order to ensure the availability of drinkable water in these places, this research proposes integrating concentrated solar power (CSP) with desalination systems (DS). Present research is focused on identifying and evaluating potential locations for DS/CSP implementation within Mauritania by employing a comprehensive, multi-criteria decision-making framework. This framework synthesizes mathematical approaches from multi-criteria analysis with geospatial analysis techniques, considering a range of factors including environmental impact, economic viability, demographic demands, and climatic conditions. Research findings reveal that 10% of the Mauritanian, approximately 103070 km2, presents optimal conditions for the deployment of DS/CSP facilities. The study delineates the coastal regions as prime candidates for seawater desalination plants, while the densely populated southeastern areas are identified as suitable for brackish water desalination systems. Conversely, the less inhabited northern territories hold the potential for decentralized brackish water desalination plants. Hence this study provides a holistic approach for DS/CSP systems installation to manage water scarcity as well as energy security issues in Mauritania. And also provides basis for formulating future policies in the region.