bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamical study of T

ss
systems using the chiral quark model*
Authors: Ji 纪 Jiazheng 家正 , Xing 邢 Yuheng 玉恒 , Wu 吴 Xinxing 新星 , Xu 徐 Ning 宁 , Tan 谭 Yue 悦 
Published: September 2024

Abstract
Since the discovery of Tcc
by LHCb, there has been considerable interest in Tcc
and its heavy-flavor partners. However, the study of its strange partner Tss
has been largely overlooked. Within the framework of the chiral quark model, we conducted a systematic study of the bound states of Tss
based on the Gaussian Expansion Method. We considered all physical channels with 01+, including molecular and diquark structures. Moreover, by considering the coupling between diquarks and molecular states, our calculations allowed us to identify a deep bound state with a bounding energy of 60 MeV primarily composed of KK
*. Using the 3
P
0 model, we calculated the decay width of K
* within the KK
* bound state, which is approximated as the decay width of the bound state in the Tss
system. These results indicate that, owing to the effect of binding energy, the decay width of K
* in KK
* is approximately 3 MeV smaller than that of K
* in vacuum. Additionally, resonance state calculations were performed. We used the real-scaling method to search for possible resonance states in the Tss
sysytem. Because of the strong attraction in the [K
*]8[K
*]8 configuration, four resonance states were found in the vicinity of 2.2−2.8 GeV, predominantly featuring hidden-color structures. The decay widths of these states are less than 10 MeV. We strongly recommend experimental efforts to search for the resonance states in the Tss
system predicted by our calculations.
Reducing the total stimulated brillouin scattering of two-color lasers through two-ion decay
Authors: Liu D.J. , Wang Qing , Zhang S.T. , Cheng R.J. , Li X.X. , Lv S.Y. , Huang Z.M. , Chen Z.J. , Xu Z.Y. , Wang Qiang , Liu Z.J. , Cao L.H. , Zheng C.Y. 
Published: September 2024

Abstract
A mechanism coupling the stimulated Brillouin scattering (SBS) of two-color lasers with wavelengths of 527 and 351

nm

via the two-ion decay instability is proposed. When the SBS reflectivities of both lasers exceed 10%, the ion-acoustic wave excited by the 527

nm

laser seeds the decay process of the ion-acoustic wave excited by the 351

nm

laser, thereby promoting the decay of the latter into the former. This results in a significant reduction in the SBS reflectivity of the 351

nm

laser, while the SBS of the 527

nm

laser exhibits minimal variation, consequently reducing the total SBS reflectivity. The total SBS reflectivity initially decreases and then increases as the intensity fraction α of the 527

nm

laser rises. When

α
∼
(
20
%

−

30
%
)

, the laser energy reflections from both lasers become approximately equal, achieving the minimum total reflectivity. Through this mechanism, the incidence of the two-color lasers can achieve lower reflected energy compared to monochromatic lasers with the same total intensity. These results demonstrate the significant potential of replacing a small fraction of high-frequency light with low-frequency light in enhancing the laser-target coupling efficiency for inertial fusion energy.
Controllable Oil Adsorption from water Using Hydrophobic (Paraffin/Stearic Acid)/CoFe2O4 Magnetized Fibril Wax
Authors: Ghobashy M. M. 
Published: September 2024

Abstract
The development of efficient oil-water separation techniques is critical for mitigating environmental pollution from industrial oily wastewater. This study synthesized a hydrophobic and oleophilic (paraffin/stearic acid) (Par/St)/CoFe2O4 magnetized fibril wax for controllable adsorption and removal of waste engine oil from water. Structural and morphological characterization confirmed the successful incorporation of 30 wt% CoFe2O4 nanoparticles into the Par/St wax matrix with fibril morphology. Structural and morphological characterization using TEM, UV-Vis, FTIR, XRD, and SEM consistently confirmed the successful integration of CoFe2O4 nanoparticles into the Par/St wax matrix, forming fibrils with a high surface area. The oleophilic fibril demonstrated rapid adsorption and excellent removal efficiency of 99% for waste engine oil within 30 seconds. The fibrils could be magnetically guided for oil collection, ensuring reusable and eco-friendly oil remediation. This work introduces a novel solution for controllable oil spill clean-up and oily wastewater treatment.
Design of arduino-based track inspection trolley
Authors: Cao Yuhao , Liu Jilai , Yang Qiyao 
Published: September 2024

Abstract
In recent years, China’s transport industry has been booming, and among them, rail transport plays a crucial role. Along with the track laying volume and mileage of continuous growth, the track of the daily inspection work burden is increasing, the current track inspection in China is still in the manual inspection stage, it is difficult to ensure the safety of workers, so a stable, accurate, lightweight track inspection vehicle has become the development of the general trend. The core of this design is the use of Arduino as a motherboard, non-contact track detection, the ability to use the appropriate sensors to detect the track of the super-high problem, while being able to use the camera on the collection of track line information, fast and stable on the track whether there is a foreign body and the track surface levelling for the collection and sent to the upper computer, in the upper computer for subsequent image processing.
Central America’s agro-ecological suitability for cultivating coca, Erythroxylum spp
Authors: Murillo-Sandoval Paulo J , Sesnie Steven E , Ordoñez Armas Manuel Eduardo , Magliocca Nicholas , Tellman Beth , Devine Jennifer A , Nielsen Erik , McSweeney Kendra 
Published: September 2024

Abstract
We assess how much of Central America is likely to be agriculturally suitable for cultivating coca (Erythroxylum spp), the main ingredient in cocaine. Since 2017, organized criminal groups (not smallholders) have been establishing coca plantations in Central America for cocaine production. This has broken South America’s long monopoly on coca leaf production for the global cocaine trade and raised concerns about future expansion in the isthmus. Yet it is not clear how much of Central America has suitable biophysical characteristics for a crop domesticated in, and long associated with the Andean region. We combine geo-located data from coca cultivation locations in Colombia with reported coca sites in Central America to model the soil, climate, and topography of Central American landscapes that might be suitable for coca production under standard management practices. We find that 47% of northern Central America (Honduras, Guatemala, and Belize) has biophysical characteristics that appear highly suitable for coca-growing, while most of southern Central America does not. Biophysical factors, then, are unlikely to constrain coca’s spread in northern Central America. Whether or not the crop is more widely planted will depend on complex and multi-scalar social, economic, and political factors. Among them is whether Central American countries and their allies will continue to prioritize militarized approaches to the drug trade through coca eradication and drug interdiction, which are likely to induce further expansion, not contain it. Novel approaches to the drug trade will be required to avert this outcome.
On the convergence of phase space distributions to microcanonical equilibrium: dynamical isometry and generalized coarse-graining
Authors: Barkan Casey O 
Published: September 2024

Abstract
This work explores the manner in which classical phase space distribution functions converge to the microcanonical distribution. We first prove a theorem about the lack of convergence, then define a generalization of the coarse-graining procedure that leads to convergence. We prove that the time evolution of phase space distributions is an isometry for a broad class of statistical distance metrics, implying that ensembles do not get any closer to (or farther from) equilibrium, according to these metrics. This extends the known result that strong convergence of phase space distributions to the microcanonical distribution does not occur. However, it has long been known that weak convergence can occur, such that coarse-grained distributions—defined by partitioning phase space into a finite number of cells—converge pointwise to the microcanonical distribution. We define a generalization of coarse-graining that removes the need for partitioning phase space into cells. We prove that our generalized coarse-grained distribution converges pointwise to the microcanonical distribution if the dynamics are strong mixing. As an example, we study an ensemble of triangular billiard systems.
Reordering of point-vortex lattices under anisotropic diffraction: far-field analysis
Authors: Mellado-Villaseñor Gabriel , Balbuena Ortega Argelia , Karen Volke-Sepúlveda  
Published: September 2024

Abstract
A study of the far-field complex amplitude obtained from initially ordered arrays of N × M point-vortices with equal unitary topological charge embedded in carrier beams with different geometry is presented. This can be understood as the final stationary configuration after the dynamical evolution of the vortices upon propagation, and our aim is to investigate the impact of a geometric anisotropy on the diffraction process by using an elliptic Gaussian beam as a carrier and a rectangular vortex lattice. For comparison, illumination by a circular Gaussian beam and a plane wave diffracted by a rectangular aperture are also analyzed. We show that vortices tend to cluster in some regions under high eccentricity of the carrier and there can be an entire redistribution of the vortices depending on the size of the initial array with respect to the size of the carrier, which inherits some geometric characteristics of the latter.
Assessment of electrochemical removal mechanisms of diverse transition metal dichalcogenides for caesium ion removal in wastewater treatment
Authors: Boeurn Ousa , Chavalekvirat Panwad , Chanapai Parichat , Saeloo Boontarika , Hirunpinyopas Wisit , Iamprasertkul Pawin 
Published: September 2024

Abstract
Effective treatment of radioactive wastewater is crucial for broader nuclear energy adoption, with caesium radionuclides (most exist in the form of caesium chloride) presenting challenges due to their long half-life and biological hazards. Conventional adsorbents like zeolites and carbon-based materials, including graphene, face limitations in adsorption capacity due to the formation of electric double layers (EDL). This has led to the investigation of alternatives such as transition metal dichalcogenides (TMDs) e.g. MoS2, MoSe2, and WSe2, which offer promising galleries for caesium ion removal. Aside from extensively studied MoS2, there is limited research on the adsorption mechanisms and capacities of other TMDs like MoSe2 and WSe2. Here, we conduct a comparative study examining the removal mechanisms and capacities of exfoliated MoS2, MoSe2, and WSe2 nanosheets, alongside an evaluation of these properties in relation to graphene. Our investigation reveals distinct removal mechanisms and capacities among these three materials for capturing caesium ions in a variety of mechanisms. MoS2 nanosheets primarily utilise a pseudocapacitive charge storage mechanism via electrochemical intercalation, as evidenced by a total charge storage of 0.78 C g–1, with only 2.6% stored via EDL formation. In contrast, MoSe2 predominantly relies on EDL formation, with almost 60% of the total 0.54 C g–1 charge storage attributed to this mechanism. Lastly, WSe2 exhibits a combination of both charge storage behaviours, with a total charge storage of 0.77 C g–1, of which 14% is due to EDL formation. This research highlights the potential efficacy of TMDs as viable materials for caesium removal, offering an appealing alternative to conventional adsorbents and likely fostering advancements in water treatment technologies.
Theoretical analysis of structural, electronic, optical, and thermoelectric properties of XNaH2 (X = K, Rb) hybrid metal hydride composites
Authors: Khalid Ayesha , Mumtaz Umair , Rouf Syed Awais , Gulzar Shakila , Masood Hafiz Tariq , Abid Amin , Alam Hafiz Farooq , Choudhury Maria Imran , Ali Nazim , Raza Saqlain 
Published: September 2024

Abstract
Hydrogen storage has become a global challenge for scientists of this era because it is an economical, clean, and non-pollutant element present in nature. In the present work, the DFT study of structural, electronic, optical, and thermoelectric properties of metal hydride XNaH2 (X = K, Rb) has been performed. Both of these materials are found stable in ambient conditions having semiconductor nature. The optical properties have been investigated in terms of dielectric function, refractive index, absorption coefficient, extinction coefficient, optical conductivity, reflectivity, and energy loss function. The better thermoelectric profile of these composites computed from the BoltzTraP2 code to shows their remarkable thermoelectric response between 200 to 950 K temperature. Remarkably, the computational calculations of these hydrides are made, which could lead to outstanding advancements in applications for hydrogen storage.
High-precision alignment of optoelectronic devices for optical phase conjugation
Authors: Ding Chunxu , Shao Rongjun , Qu Yuan , Yang Jiamiao 
Published: September 2024

Abstract
Digital optical phase conjugation (DOPC) is considered as a promising solution to achieve optical focusing against scattering. The implementation of DOPC based on the digital micromirror device (DMD) has been proven to have great potential, supporting a large number of modulation modes and a high modulation rate. However, the accuracy of optical alignment seriously affects the focusing contrast, limiting the applications of DMD-based DOPC systems. Here we demonstrate a simple alignment protocol including a marker-assisted tuning and an embedded compensation. Our approach can realize an exact pixelwise optical conjugation between the DMD and detector, as well as a rapid compensation for aberrations and minor misalignment. Experimental results show that the proposed alignment protocol improves the focusing contrast to 66% of the highest value predicted in the theory.
Imaging through scattering media by exploiting the optical memory effect: a tutorial
Authors: Penketh H , Bertolotti J 
Published: September 2024

Abstract
Scattering, especially multiple scattering, is a well known problem in imaging, ranging from astronomy to medicine. In particular it is often desirable to be able to perform non-invasive imaging through turbid and/or opaque media. Many different approaches have been proposed and tested through the years, each with their own advantages, disadvantages, and specific situations in which they work. In this tutorial we will show how knowledge of the correlations arising from the multiple scattering of light allows for non-invasive imaging through a strongly scattering layer, with particular attention on the practicalities of how to make such an experiment work.
Optimal estimation of SoC, SoH using machine learning models and design of control algorithm for active cell balancing in lithium ion batteries
Authors: K Sabeena Beevi , S Abhishek , L Mahima , G Naveen Ram C , M Parvati , P B Adithyan , S Sonu 
Published: September 2024

Abstract
Electric vehicles transform the automotive industry by replacing traditional vehicles powered by fossil fuels with less polluting and efficient vehicles. They are powered by rechargeable Li-ion batteries. While there are drawbacks associated with Li-ion battery technology, it's important to note that these challenges can be addressed or mitigated effectively. A battery management system ensures the tracking of all functions performed by the battery. An advanced battery management system should accurately estimate the battery's state of health and state of charge. This paper aims to develop machine learning models for the estimation of the state of health and state of charge and to implement cell balancing in a battery management system. A dataset of battery charging and discharging profiles was used to train various machine learning models for estimation. These methods are computationally less complex than conventional methods. In addition, a cell balancing algorithm is implemented to control the charging and discharging of individual cells in a battery pack and balance the state of charge of each cell. The machine learning solution is created using several machine learning models, including Gradient Boosting, Random Forest, Linear Regression, AdaBoost, and Multi-layer Perceptron. Among the models Gradient Boosting and Random Forest provide good MSE and R2 score. The use of machine learning algorithms for the assessment of state of health and charge estimation combined with the design of an efficient control algorithm for active cell balancing offers significant advancements in the battery management system to optimise the performance, reliability, and useful life of Li-ion batteries. The paper also presents a case study utilising a combination of deep learning-based SoC, SoH estimation algorithms in a simulated data set. A well-designed control algorithm for active cell balancing presents a holistic and effective approach to optimise the performance, reliability, and lifespan of Li-ion batteries.
Low-order-model-based design of additive-manufactured heat exchanger
Authors: Naidu Aravin Dass , Rey Lucas , Chowdhury Nafiz H K , Povey Thomas 
Published: September 2024

Abstract
This paper discusses a comprehensive approach to the design of an additive-manufactured heat exchanger for a high-temperature application. This manufacturing route is attractive because of the flexibility afforded in design, but there is a requirement for calibration of internal friction factors and heat transfer coefficients because of uncertainty regarding the characteristics of the manufactured internal surfaces. The design was informed by physics-based low-order models (total pressure loss model; conjugate heat transfer model) calibrated against experimental data. To extract heat transfer coefficients we use transient experiments performed over timescales for which the surfaces can be regarded as semi-infinite. The calibrated models are used to predict accurate performance characteristics for the heat exchanger. Experimental results for a prototype design were found to be in excellent agreement with the model over a wide operational range, validating both the design methodology and the utility of the particular design for the given application. Our process, though not unique, has wide applicability, has been conducted with considerable care, and will be of interest to those engaged in low-order-model-based heat exchanger design.
Tone mapping algorithm based on BL-Hilbert-L2 decomposition model for HDR image
Authors: Yang Xuejie , Xu Wenjun , Su Yonggang 
Published: September 2024

Abstract
Tone mapping algorithms are mainly used to produce standard dynamic range (SDR) images from high dynamic range (HDR) images. To address the issues of halo artifacts and over-enhancement in current tone mapping algorithms based on layer decomposition model, we propose a tone mapping algorithm based on the BL-Hilbert-L
2 decomposition model. In our proposed algorithm, we first convert HDR image from RGB space to HSV space. Subsequently, utilizing the BL-Hilbert-L
2 decomposition model, we decompose the V channel of the HDR image into cartoon, texture and high-frequency detail components. Next, we separately compress the cartoon component and stretch the texture and high-frequency detail components. The processed cartoon, texture and high-frequency detail components are then recombined to form a new V channel. Finally, by converting the H and S channels of the HDR image, along with the newly formed V channel, back into the RGB color space, we obtain a tone mapped SDR image. Experimental results demonstrate that our proposed algorithm can effectively eliminate the halo artifacts and avoid the issue of over-enhancement while retaining the edge details.
Benchmarking of quantum fidelity kernels for Gaussian process regression
Authors: Guo Xuyang , Dai Jun , Krems Roman V 
Published: September 2024

Abstract
Quantum computing algorithms have been shown to produce performant quantum kernels for machine-learning classification problems. Here, we examine the performance of quantum kernels for regression problems of practical interest. For an unbiased benchmarking of quantum kernels, it is necessary to construct the most optimal functional form of the classical kernels and the most optimal quantum kernels for each given data set. We develop an algorithm that uses an analog of the Bayesian information criterion to optimize the sequence of quantum gates used to estimate quantum kernels for Gaussian process models. The algorithm increases the complexity of the quantum circuits incrementally, while improving the performance of the resulting kernels, and is shown to yield much higher model accuracy with fewer quantum gates than a fixed quantum circuit ansatz. We demonstrate that quantum kernels thus obtained can be used to build accurate models of global potential energy surfaces (PES) for polyatomic molecules. The average interpolation error of the six-dimensional PES obtained with a random distribution of 2000 energy points is 16 cm−1 for H3O+, 15 cm−1 for H2CO and 88 cm−1 for HNO2. We show that a compositional optimization of classical kernels for Gaussian process regression converges to the same errors. This indicates that quantum kernels can achieve the same, though not better, expressivity as classical kernels for regression problems.
Spatial and signaling overlap of growth factor receptor systems at clathrin-coated sites
Authors: Alfonzo-Méndez Marco A. , Strub Marie-Paule , Taraska Justin W. 
Published: September 2024

Cellular communication is regulated at the plasma membrane by the interactions of receptor, adhesion, signaling, exocytic, and endocytic proteins. Yet, the composition and control of these complexes in response to external cues remain unclear. We use high-resolution and high-throughput fluorescence imaging to map the localization of growth factor receptors and related proteins at single clathrin-coated structures in human squamous HSC3 cells. We find distinct protein signatures between control cells and cells stimulated with growth factors. Clathrin sites at the plasma membrane are preloaded with some receptors but not others. Stimulation with epidermal growth factor induces capture and concentration of epidermal growth factor, fibroblast growth factor 1, and low-density lipoprotein receptor (EGFR, FGFR1, and LDLR). Regulatory proteins including ubiquitin ligase Cbl, the scaffold Grb2, and the mechanoenzyme dynamin2 are also recruited. Disrupting FGFR1 or EGFR activity with drugs prevents the recruitment of both EGFR and FGFR1. EGF was able to activate FGFR1 phosphorylation. Our data reveal novel coclustering and activation of receptors and regulatory factors at clathrin-coated sites in response to stimulation by a single growth factor, EGF or FGF. This behavior integrates growth factor signaling and allows for complex responses to extracellular cues and drugs at the plasma membrane of human cells.