bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bursting core-localized ellipticity-induced Alfvén eigenmodes driven by energetic electrons during EAST ohmic discharges
Authors: Su P. , Lan H. , Zhou C. , Bao J. , Liu A. , Zhu X. , Wu M. , Luo C. , Han J. , Wang J. , Liu H. , Zhang T. , Zhou R. , Lin S. , Zhao H. , Sun Y. , Qiu Z. , Chu N. , Tang T. , Tan Y. , Zeng L. , Gao Z. 
Published: January 2024

Abstract
A series of high-frequency (

400
∼
1000

kHz

) bursting core-localized Alfvén instabilities have been observed during ohmic discharges in EAST tokamak. The instability trigger favours the discharge conditions of low toroidal magnetic field and low electron density. The toroidal mode numbers are mainly

n
=
2
∼
3

and they propagate in the ion diamagnetic drift (co-current) direction. These modes are radially localized in the range of

ρ

tor

=
0.2
∼
0.35

based on Doppler BackScatter measurement. They are identified as ellipticity-induced Alfvén eigenmodes (EAEs) occurring at

q
=
1

rational surfaces by magnetohydrodynamics simulations using the realistic geometry and plasma profiles. The EAEs show regular bursts with ∼10 ms duration along with the mode frequency chirping downwards and upwards rapidly. It is also found that sawtooth events can interrupt the growth and evolution of the EAEs, causing the modes to disappear immediately. Passing energetic electrons (EEs) that move much faster than Alfvén velocity are responsible for the destabilization of these EAEs, which attribute to the fact that the large poloidal and toroidal frequencies mostly cancel each other and satisfy the EAE resonance condition with primary energy exchange. These novel experimental results of the wave-particle interaction between EAEs and EEs are helpful for extrapolating alpha particle physics that are characterized by small orbit width with respect to machine size in future fusion reactors.
Pattern recognition and signal parameters extraction using machine learning methods
Authors: Buchakchiev Valentin , Dimitrova Kalina , Georgiev Georgi , Georgieva Gergana , Kozhuharov Venelin 
Published: January 2024

Abstract
Machine learning methods can be used for signal processing in different cases of physics research. A convolutional neural network was developed for the task of pulse counting in particle detectors for high energy physics. For the extraction of signal parameters was used a network with convolutional autoencoder architecture and a subsequent result reconstruction algorithm was developed and applied. A convolutional neural network was also developed for seismic studies with the task of identifying different events in seismograms. All of the algorithms with their architecture, input and output are presented and discussed.
Semi-empirical model of galactic cosmic ray spectrum
Authors: Buchvarova M 
Published: January 2024

Abstract
The galactic cosmic rays are high-energy particles that reach us from all directions of the vast universe. Their transport in the interplanetary medium is well described by the transport equation, first derived by Parker in 1965. An approximate solution of the cosmic ray transport equation for 1 AU is used to construct a simplified, semi-empirical model of the cosmic ray spectrum. The model parameters are obtained by fitting the proton spectra of the PAMELA experiment. The values of the model parameters are presented for the period 2006-2014, which includes the solar minimum between cycles 23 and 24 and the maximum phase of cycle 24. Our analysis shows that the proposed semi-empirical model agrees approximately well with the force-field approximation to the cosmic ray transport equation.
The forward calorimeter of the ALICE experiment at CERN LHC
Authors: Simeonov Radoslav ,   the ALICE Collaboration
Published: January 2024

Abstract
A new forward calorimeter (FoCal), covering the pseudorapidity range 3.4 ≤ η ≤ 5.8, is proposed in order to extend the physics reach of ALICE during the LHC Run 4. The FoCal comprises a high-granularity electromagnetic calorimeter with silicon pixel and pad readout as well as a hadronic calorimeter. FoCal gives access to the nuclear gluon densities down to Bjorken-x ∼ 10−6, where they are not constrained by other measurements and their evolution may be affected by non-linear effects of quantum chromodynamics. The hadronic subsystem of FoCal (FoCal-H) will be based on capillary copper tubes with scintillating fibers inside. A full-length prototype was assembled and it was exposed to a non-separated charged particle beam in the H2 SPS CERN beamline in November 2022. An energy scan from 60 to 350 GeV was performed and the reconstructed signals are processed in a custom developed ROOT based environment. The design of the 2022 prototype as well as the first results from the energy reconstruction are presented.
Study of the motivation for choosing physics as an elective course among 10th-grade students
Authors: Kotseva I. , Yaneva N. 
Published: January 2024

Abstract
The article presents the original results of a study of various parameters of motivation for choosing physics as an elective course among students in the 10th grade of High schools in Bulgaria. Since motivation is one of the main factors for taking certain actions, it also determines whether or not a student will choose physics as an elective course after the 10th grade. That is why it is very important to find out those motivational features that are a prerequisite for choosing the “Physics” profile in high school. One possible way to analyze these features is to look for statistically significant differences using the independent samples method. The instrument of measurement and the selection of the independent samples are described in the Methods of Research section, followed by the presentation of the Statistical analysis and the results and their interpretation in the Results and Discussion section.
Complex analysis of earthquake deformations using SAR images: Examples from Croatia and Greece
Authors: Dimova L , Raykova R 
Published: January 2024

Abstract
This study presents an assessment of the displacements of the Earth’s crust generated by two earthquakes: one in Croatia on 29th December 2020 and one in Greece on 3rd March 2021. The main data source is SAR satellite images from Sentinel-1A and B (ascending and descending orbits) in the form of images of the amplitude and phase signals. The data is processed via SNAP software package. The results are obtained applying the differential radar interferometry method (DInSAR). The Line of Sight (LoS) displacements are converted into vertical displacements and compared with modeled deformations of the Earth’s surface using rectangle finite source model proposed by Okada.
Methodology based on the Hu moment invariants for object comparison on radar satellite imagery
Authors: Gancheva Irina , Peneva Elisaveta 
Published: January 2024

Abstract
In this paper we present a methodology for comparing objects, identified on satellite images acquired by Synthetic Aperture Radar (SAR). The methodology describes object transformations mathematically and provides a quantitative estimate of the similarity of different shapes. To demonstrate its capabilities we examine a case study – we detect an underwater structure in the Western Black Sea, which becomes visible on radar imagery under favourable sea conditions. Our aim is to quantitatively describe if it changes over time and to determine on which dates the detections reveal the greatest similarity.
The suggested methodology is based on computation of the Hu moment invariants, or the image moments. They give a set of 7 invariants, which describe object transformations, such as translation, scale, rotation and reflection. The presented methodology can be applied in different contexts on satellite imagery for quantitative description of structure transformations.
Architectural gear ratio depends on actuator spacing in a physical model of pennate muscle
Authors: Sleboda David A , Roberts Thomas J , Azizi Emanuel 
Published: January 2024

Abstract
Pennate muscles are defined by the architectural arrangement of their muscle fibers, which run at an angle to the primary axis of muscle shortening. Pennation angles can vary dynamically over the course of individual contractions, influencing the speed and distance of muscle shortening. Despite their relevance to muscle performance, the physical mechanisms that drive dynamic changes in pennation angle remain poorly understood. Muscle fibers bulge radially as they shorten, a consequence of maintaining a constant internal fluid volume, and we hypothesized that radial interactions between tightly packed muscle fibers are essential to dynamic pennation angle changes. To explore this, we built physical models of pennate muscles in which the radial distance between fiber-like actuators could be experimentally altered. Models were built from pennate arrays of McKibben actuators, a type of pneumatic actuator that forcefully shortens and bulges radially when inflated with compressed air. Consistent with past studies of biological muscle and engineered pennate actuators, we found that the magnitude of pennation angle change during contraction varied with load. Importantly, however, we found that pennation angle changes were also strongly influenced by the radial distance between neighboring McKibben actuators. Increasing the radial distance between neighboring actuators reduced pennation angle change during contraction and effectively eliminated variable responses to load. Radial interactions between muscle fibers are rarely considered in theoretical and experimental analyses of pennate muscle; however, these findings suggest that radial interactions between fibers drive pennation angle changes and influence pennate muscle performance. Our results provide insight into the fundamental mechanism underlying dynamic pennation angle changes in biological muscle and highlight design considerations that can inform the development of engineered pennate arrays.
Hydrodynamic analysis of fin–fin interactions in two-manta-ray schooling in the vertical plane
Authors: Huang Zihao , Menzer Alec , Guo Jiacheng , Dong Haibo 
Published: January 2024

Abstract
This study investigates the interaction of a two-manta-ray school using computational fluid dynamics simulations. The baseline case consists of two in-phase undulating three-dimensional manta models arranged in a stacked configuration. Various vertical stacked and streamwise staggered configurations are studied by altering the locations of the top manta in the upstream and downstream directions. Additionally, phase differences between the two mantas are considered. Simulations are conducted using an in-house developed incompressible flow solver with an immersed boundary method. The results reveal that the follower will significantly benefit from the upstroke vortices (UVs) and downstroke vortices depending on its streamwise separation. We find that placing the top manta 0.5 body length (BL) downstream of the bottom manta optimizes its utilization of UVs from the bottom manta, facilitating the formation of leading-edge vortices (LEVs) on the top manta’s pectoral fins during the downstroke. This LEV strengthening mechanism, in turn, generates a forward suction force on the follower that results in a 72% higher cycle-averaged thrust than a solitary swimmer. This benefit harvested from UVs can be further improved by adjusting the phase of the top follower. By applying a phase difference of

π

/

3

to the top manta, the follower not only benefits from the UVs of the bottom manta but also leverages the auxiliary vortices during the upstroke, leading to stronger tip vortices and a more pronounced forward suction force. The newfound interaction observed in schooling studies offers significant insights that can aid in the development of robot formations inspired by manta rays.
Bridging the gap between the water-energy-food nexus and compound risks
Authors: Leah Jones-Crank J , Lu Jessie , Orlove Ben 
Published: January 2024

Abstract
The water-energy-food (WEF) nexus is a concept and approach to examine the interactions of water, energy, and food resources. Similarly, compound risks are a set of risk types that consider multiple connected factors that amplify risks. While both concepts are promoted as approaches to move beyond silos and address complex problems in environmental governance, there has been limited exploration of their overlap. Our study integrates these two approaches for more holistic assessment and management of resources in the context of climate risks. We examine the connections between the WEF nexus and compound risk in two ways. First, we review the literature to identify previous conceptual connections between the WEF nexus and compound risks. Second, we review seven case studies with WEF nexus interactions and compound risks to identify how the two approaches might be considered in practice. Our results demonstrate that there is limited, though not non-existent, integration of the two concepts in both the theoretical literature and in the case studies. The four of the seven cases that do show some level of connection in practice demonstrate opportunities for greater integration in the future, such as leveraging the water sector as a bridge to address WEF nexus and compound risk challenges together.
Focus on the future of water-limited agricultural landscapes
Authors: Peterson Caitlin A , Davis Kyle Frankel , E Dybala Kristen , Fernández Francisco J , Ghimire Rajan , Nidumolu Uday , Roche Rose 
Published: January 2024

Abstract
Water scarcity and related climate volatility are growing constraints on agricultural production landscapes around the world. While the adaptation options available are often dictated by system context, in many places broad-scale transformations are occurring in response to water-related pressures. We sought contributions from across regions, agricultural system types, and scientific disciplines to examine agricultural land use transitions driven by water scarcity, including the tradeoffs associated with alternative land uses; impacts on food production, environment, and society; innovations that can buffer risk; and considerations for planning and implementation. The research presented in this collection highlights the spectrum of policy and practice changes that are needed to facilitate beneficial land use transitions and system transformations, from quantifying risks, to evaluating multidimensional tradeoffs, to developing socio-technical policy bundles to maximize co-benefits.
Ionically annealed zwitterionic microgels for bioprinting of cartilaginous constructs
Authors: Surman František , Asadikorayem Maryam , Weber Patrick , Weber Daniel , Zenobi-Wong Marcy 
Published: January 2024

Abstract
Foreign body response (FBR) is a pervasive problem for biomaterials used in tissue engineering. Zwitterionic hydrogels have emerged as an effective solution to this problem, due to their ultra-low fouling properties, which enable them to effectively inhibit FBR in vivo. However, no versatile zwitterionic bioink that allows for high resolution extrusion bioprinting of tissue implants has thus far been reported. In this work, we introduce a simple, novel method for producing zwitterionic microgel bioink, using alginate methacrylate (AlgMA) as crosslinker and mechanical fragmentation as a microgel fabrication method. Photocrosslinked hydrogels made of zwitterionic carboxybetaine acrylamide (CBAA) and sulfobetaine methacrylate (SBMA) are mechanically fragmented through meshes with aperture diameters of 50 and 90 µm to produce microgel bioink. The bioinks made with both microgel sizes showed excellent rheological properties and were used for high-resolution printing of objects with overhanging features without requiring a support structure or support bath. The AlgMA crosslinker has a dual role, allowing for both primary photocrosslinking of the bulk hydrogel as well as secondary ionic crosslinking of produced microgels, to quickly stabilize the printed construct in a calcium bath and to produce a microporous scaffold. Scaffolds showed ∼20% porosity, and they supported viability and chondrogenesis of encapsulated human primary chondrocytes. Finally, a meniscus model was bioprinted, to demonstrate the bioink’s versatility at printing large, cell-laden constructs which are stable for further in vitro culture to promote cartilaginous tissue production. This easy and scalable strategy of producing zwitterionic microgel bioink for high resolution extrusion bioprinting allows for direct cell encapsulation in a microporous scaffold and has potential for in vivo biocompatibility due to the zwitterionic nature of the bioink.
Recent progress on degradation mechanism and antioxidation of low-dimensional black phosphorus
Authors: Fu Mingfu , Li Jiabao , Yang Wen , Zhang Yong , Yang Peizhi 
Published: January 2024

Abstract
Among the allotropes of phosphorus, black phosphorus (BP) is one of the most thermodynamically stable structures. Due to its unique physical and chemical properties, BP has shown considerable potential in many applications, such as field-effect transistors, energy storage and conversion, and photocatalysis. However, low-dimensional BP is easily corroded by oxygen and water owing to the large specific surface area and unbonded lone pair electrons on the surface, which reduces its chemical stability in the environment. As a result, different passivation approaches, relying on noncovalent bonding, covalent functionalization, and surface coordination, are employed to enhance the stability and performance of BP. In this review, the degradation mechanisms of BP are first analyzed for the material in both its ground state and excited state. Subsequently, the promising strategies for improving stability are overviewed. A comprehensive and in-depth understanding of the oxidation mechanisms and protection strategies of BP will provide guidance for the large-scale applications of BP and its derivatives.
Initial measurement of ultrafast charge exchange recombination spectroscopy on the EAST tokamak
Authors: JIANG 蒋 Jun 军 , LI 李 Yingying 颖颖 , CHEN 陈 Ran 冉 , FU 符 Jia 佳 , LYU 吕 Bo 波 , YU 余 Yi 羿 , XU 徐 Guosheng 国盛 , YE 叶 Minyou 民友 
Published: January 2024

Abstract
Ultrafast charge exchange recombination spectroscopy (UF-CXRS) has been developed on the EAST tokamak (Yingying Li et al 2019 Fusion Eng. Des. 146 522) to measure fast evolutions of ion temperature and toroidal velocity. Here, we report the preliminary diagnostic measurements after relative sensitivity calibration. The measurement results show a much higher temporal resolution compared with conventional CXRS, benefiting from the usage of a prism-coupled, high-dispersion volume-phase holographic transmission grating and a high quantum efficiency, high-gain detector array. Utilizing the UF-CXRS diagnostic, the fast evolutions of the ion temperature and rotation velocity during a set of high-frequency small-amplitude edge-localized modes (ELMs) are obtained on the EAST tokamak, which are then compared with the case of large-amplitude ELMs.
Metabolic Syndrome, Modifiable Lifestyle Factors, and Sleep-Disordered Breathing: The Hispanic Community Health Study
Authors: Richard Shannon L , Renn Brenna N , Tran Dieu-My T , Kim Jinyoung , Feng Du 
Published: January 2024

Abstract

Background
US Hispanics/Latinos are disproportionately susceptible to metabolic syndrome (MetS), attributed in part to systemic inequities related to health and lifestyle factors such as low physical activity (PA) levels, diet quality, alcohol use, tobacco use, and sleep disorder. Gender and heritage group differences are vastly understudied and need to be examined in this heterogeneous population.

Purpose
To examine the relationships between select health and lifestyle factors and MetS among Hispanic gender and heritage subgroups (Hypothesis 1) and determine whether gender and heritage moderate those relationships (Hypothesis 2).

Methods
Participants included 14,155 Hispanic Americans aged 18–76 (59% female, mean age 45.92 ± 13.97) from seven heritage subgroups. This secondary analysis of cross-sectional data from the observational Hispanic Community Health Study/Study of Latinos (HCHS/SOL) dataset used hierarchical multinomial logistic regression to test Hypothesis 1; the dependent variable, MetS, included three categories delineating absence of MetS and presence of MetS with or without related medication use. Hayes’ PROCESS macro tested Hypothesis 2.

Results
Low PA and sleep-disordered breathing (SDB) each had significant (p &lt; .001) predictive value of MetS group membership, whereas both low and high alcohol use (p &lt; .001) were associated with decreased MetS risk. Cigarette pack-years were not significantly associated with MetS outcomes. Gender moderated the association between MetS and alcohol use (p &lt; .001), cigarette pack-years (p &lt; .001), and SDB (p &lt; .001) such that the effects on MetS were higher in females than males. The association between MetS and diet quality (p &lt; .001) was stronger among males than in females.

Conclusions
Gender and heritage differences were prominent among study variables.
Comprehensive assessment of protein loop modeling programs on large-scale datasets: prediction accuracy and efficiency
Authors: Wang Tianyue , Wang Langcheng , Zhang Xujun , Shen Chao , Zhang Odin , Wang Jike , Wu Jialu , Jin Ruofan , Zhou Donghao , Chen Shicheng , Liu Liwei , Wang Xiaorui , Hsieh Chang-Yu , Chen Guangyong , Pan Peichen , Kang Yu , Hou Tingjun 
Published: January 2024

Abstract
Protein loops play a critical role in the dynamics of proteins and are essential for numerous biological functions, and various computational approaches to loop modeling have been proposed over the past decades. However, a comprehensive understanding of the strengths and weaknesses of each method is lacking. In this work, we constructed two high-quality datasets (i.e. the General dataset and the CASP dataset) and systematically evaluated the accuracy and efficiency of 13 commonly used loop modeling approaches from the perspective of loop lengths, protein classes and residue types. The results indicate that the knowledge-based method FREAD generally outperforms the other tested programs in most cases, but encountered challenges when predicting loops longer than 15 and 30 residues on the CASP and General datasets, respectively. The ab initio method Rosetta NGK demonstrated exceptional modeling accuracy for short loops with four to eight residues and achieved the highest success rate on the CASP dataset. The well-known AlphaFold2 and RoseTTAFold require more resources for better performance, but they exhibit promise for predicting loops longer than 16 and 30 residues in the CASP and General datasets. These observations can provide valuable insights for selecting suitable methods for specific loop modeling tasks and contribute to future advancements in the field.