bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-dimensional drift correction of localised non-raster scanning on atomic force microscopy
Authors: Sun Xizhi , Heaps Edward , Yacoot Andrew , Yang Qingping , Grolich Petr , Klapetek Petr 
Published: July 2024

Abstract
Non-raster scanning can increase the scanning frame rate and measurement speed of atomic force microscopes (AFMs). It is also possible to correct the 3D drift during the non-raster scanning. However, the algorithm for the drift correction depends upon the properties of each scan pattern. While localised non-raster scanning using a rosette scan may be faster than the frequently used Lissajous scanning patterns, the drift correction is more challenging because the scan has crossing points only in local neighbouring segments where there are short temporal and spatial separations of the crossing paths. This design note presents a novel solution that successfully overcomes this problem and extends a drift correction method previously developed for Lissajous scans to the 3D drift correction of localised non-raster scanning using a rosette scan trajectory. The drift in the X, Y and Z axes can be determined using the crossing points and locally repeated scans of the same features. The general procedure is presented together with experiments using rosette scans of a two-dimensional lateral calibration standard. Experimental results have demonstrated that the method can effectively correct both the drift in the three axes and sample tilt, leading to significantly improved images. The method requires only localised crossing points in the scan and does not need additional scans to determine the three-dimensional drift based on cross-correlation and least squares techniques, and it can be used with any AFMs capable of rosette scanning.
Development and fault-tolerant control of a distributed piezoelectric stack actuator
Authors: Zhang Yunzhi , Ling Jie , Zhu Yuchuan 
Published: July 2024

Abstract
Piezoelectric stack actuator (PSA) has attracted widespread attention in aerospace applications. However, the severe operating conditions would bring certain risks to PSA, leading to decreased performance or even failure. The conventional PSA structure lacks adaptability in the event of a complete failure occurring within the piezoelectric stack layer (PSL) due to its centralized design and driving method. To address the reliability challenges inherent in PSAs, this paper proposes a novel distributed PSA (DPSA) by means of mechanical and electrical dispersion. Additionally, dual-redundant PSLs are integrated into the DPSA as backups, providing hardware redundancy for active fault-tolerant control (FTC). Building upon this foundation, an sliding mode observer (SMO)-based fault detector for DPSA is developed to facilitate fault reconstruction. Subsequently, an active FTC strategy, comprising dual-SMO-based fault detectors and a tracking controller, is introduced to effectively manage faults and reallocate control resources. Comprehensive experiments under various fault scenarios are carried out to assess the performance of the SMO-based fault detector and FTC strategy. The results demonstrate that the proposed fault detector and FTC strategy promptly detect faults and efficiently restore the DPSA to a stable state, thereby ensuring effective trajectory tracking even in the presence of faults.
Adaptive quantum accelerated imaging for space domain awareness
Authors: Choi Hyunsoo , Bao Fanglin , Jacob Zubin 
Published: July 2024

Abstract
The growth in space activity has increased the need for Space Domain Awareness (SDA) to ensure safe space operations. Imaging and detecting space targets is, however, challenging due to their dim appearance, small angular size/separation, dense distribution, and atmospheric turbulence. These challenges render space targets in ground-based imaging observations as point-like objects in the sub-Rayleigh regime, with extreme brightness contrast but a low photon budget. Here, we propose to use the recently developed quantum-accelerated imaging (QAI) for the SDA challenge. We mainly focus on three SDA challenges (1) minimal a priori assumptions (2) many-object problem (3) extreme brightness ratio. We also present results on source estimation and localization in the presence of atmospheric turbulence. QAI shows significantly improved estimation in position, brightness, and number of targets for all SDA challenges. In particular, we demonstrate up to 2.5 times better performance in source detection than highly optimized direct imaging in extreme scenarios like stars with a 1000 times brightness ratio. With over 10 000 simulations, we verify the increased resolution of our approach compared to conventional state-of-the-art direct imaging paving the way towards quantum optics approaches for SDA.
Global gyrokinetic analysis of Wendelstein 7-X discharge: unveiling the importance of trapped-electron-mode and electron-temperature-gradient turbulence
Authors: Wilms Felix , Bañón Navarro Alejandro , Windisch Thomas , Bozhenkov Sergey , Warmer Felix , Fuchert Golo , Ford Oliver , Zhang Daihong , Stange Torsten , Jenko Frank ,   the W7-X Team
Published: July 2024

Abstract
We present the first nonlinear, gyrokinetic, radially global simulation of a discharge of the Wendelstein 7-X-like stellarator, including kinetic electrons, an equilibrium radial electric field, as well as electromagnetic and collisional effects. By comparison against flux-tube and full-flux-surface simulations, we assess the impact of the equilibrium ExB-flow and flow shear on the stabilisation of turbulence. In contrast to the existing literature, we further provide substantial evidence for the turbulent electron heat flux being driven by trapped-electron-mode and electron-temperature-gradient turbulence in the core of the plasma. The former manifests as a hybrid together with ion-temperature-gradient turbulence and is primarily driven by the finite electron temperature gradient, which has largely been neglected in nonlinear stellarator simulations presented in the existing literature.
Production and launch studies of cryogenic pellets for the ITER disruption mitigation system
Authors: Zoletnik Sándor , Bartók Gergely , Buzás Attila , Cseh Gábor , Dunai Dániel , Gárdonyi Gábor , Hegedűs Sándor , Kocsis Gábor , Málics Marcell , Nagy Domonkos , Réfy Dániel Imre , Szabolics Tamás , Szepesi Tamás , Vavrik Márton , Vécsei Miklós , Walcz Erik , Jachmich Stefan , Kruezi Uron , Lehnen Michael 
Published: July 2024

Abstract
A support laboratory has been set up to study pellet production, launch and shattering of cryogenic protium, deuterium, and neon pellets for the ITER disruption mitigation system, which plans to use 28.5 × 57 mm (diameter × length) protium, neon an mixture pellets in the Shattered Pellet Injectors. Such large protium pellets have not been produced and launched before, therefore the desublimation and launch process have been studied in detail in two steps. First 19 mm diameter pellets were produced, followed by the demonstration of the final pellet size. Pellet desublimation recipes were established for all pellet types, and it was found that, under certain conditions, even the large neon pellets can be launched with a propellant gas pulse, without requiring a mechanical punch device. This is attributed to cryogenic snow formation on the surface of the pellet. Conditions for the snow formation are studied and tendencies are understood using simple calculations.
Re-patterning of cylindrical packing of diblock copolymers under confinement and curvature effects by using approximations of PDE’s involved in the CDS model on polar mesh system
Authors: Iqbal Muhammad Javed , Soomro Inayatullah , Mahar Mumtaz Hussain 
Published: July 2024

Abstract
Soft materials, including diblock copolymers, are advancing nanotechnology due to their unique properties, applications materials include energy harvesting, water sanitation, environmental treatment, nanosensors, drug delivery and nanolithography. These materials are light, cheap, efficient, sensitive, durable and more functional, whose new morphologies have been predicted by mathematicians through simulation. This work produces and predicts the pattern of packing of nano-cylinders by using confinement to appreciate the frustration in the packing of nano-cylinders under the influence of curvature. In this contribution, the cell dynamic simulations model is used to examine the impact of circular annular pore confinement on system orientation toward cylindrical morphologies. A 9-point stencil approximates the isotropic Laplacian by finite-difference discretization on a polar grid to meet the requirement of a cell dynamic simulation model. FORTRAN codes are generated for the set of PDEs included in the CDS model. OPEN DX is used to visualise the predicted cylindrical patterns. The consistency of our results with experimental observations makes our research valid and significant.
Machinability of gas metal arc based 3D printed Al-Mg 5356 alloy using wire-EDM
Authors: Doreswamy Deepak , Vijayan Vijeesh , Jain Krrish , Bhat Subraya Krishna 
Published: July 2024

Abstract
Wire-Arc Additive Manufactured (WAAM) is relatively new method of metal 3D printing in which the raw material is heated by the gas metal arc and the molten metal pool is deposited layer-by-layer using a computer numerically controlled axis drive system. Since WAAM needs a finishing process for attaining the final dimensions of the components, there is a need to investigate the machinability aspects of WAAM fabricated materials. This work investigates the machinability of Al-Mg 5356 alloy test samples fabricated by WAAM process using wire-electric discharge machining (Wire-EDM). The test samples were subjected to Wire-EDM and the obtained material removal rate (MRR), kerf width (KW) and surface roughness (Ra) were investigated at different Wire-EDM process settings of voltage, current, pulse-on time (Ton), pulse-off time (Toff) and wire speed (Ws). Statistical analysis revealed that current had a significant influence on MRR. Ton had a strong influence on KW and Ra, whereas Toff exhibited a considerable impact on all these responses. Notably, Ws demonstrated a significant impact on Ra. However, voltage was found to have statistically negligible impact on all the machining responses. Microstructural investigations and compositional analysis were conducted providing valuable information on the cut surfaces. The results derived from the present investigation are useful for predicting the optimum process parameter settings for machining of WAAM-based 3D printed Al-Mg alloy in various manufacturing industries.
Coarse-graining model reveals universal exponential scaling in axonal length distributions
Authors: Józsa Máté , Ercsey-Ravasz Mária , Zsolt I Lázár  
Published: July 2024

Abstract
The exponential distance rule (EDR) is a well-documented phenomenon suggesting that the distribution of axonal lengths in the brain follows an exponential decay pattern. Nevertheless, individual-level axon data supporting this assertion is limited to Drosophila and mice, while inter-region connectome data is also accessible for macaques, marmosets, and humans. Although axon-level data in Drosophila and mice support the generality of the EDR, region-level data can significantly deviate from the exponential curve. In this study, we establish that the axon number-weighted length distribution of region-level connections converges onto a universal curve when rescaled to the mean axonal length, demonstrating similarities across different species. To explain these observations, we present a simple mathematical model that attributes the observed deviations from the EDR in the weighted length distribution of inter-regional connectomes to the inherent coarse-graining effect of translating from neuron-level to region-level connectomics. We demonstrate that the qualitative predictions of the model are robust with respect to various aspects of brain region-geometry, including dimensionality, resolution, and curvature. On the other hand, the performance of the model exhibits a monotonous dependence on the amount of region-geometry related detail incorporated into the model. The findings validate the universality of the EDR rule across various species, paving the way for further in-depth exploration of this remarkably simple principle.
OmniJet-α: the first cross-task foundation model for particle physics
Authors: Birk Joschka , Hallin Anna , Kasieczka Gregor 
Published: July 2024

AbstractFoundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of downstream applications. The successful development of such general-purpose models for physics data would be a major breakthrough as they could improve the achievable physics performance while at the same time drastically reduce the required amount of training time and data. We report significant progress on this challenge on several fronts. First, a comprehensive set of evaluation methods is introduced to judge the quality of an encoding from physics data into a representation suitable for the autoregressive generation of particle jets with transformer architectures (the common backbone of foundation models). These measures motivate the choice of a higher-fidelity tokenization compared to previous works. Finally, we demonstrate transfer learning between an unsupervised problem (jet generation) and a classic supervised task (jet tagging) with our newOmniJet-αmodel. This is the first successful transfer between two different and actively studied classes of tasks and constitutes a major step in the building of foundation models for particle physics.
Multi-perspective feedback-attention coupling model for continuous-time dynamic graphs
Authors: Zhu Xiaobo , Wu Yan , Che Jin , Wang Chao , Wang Liying , Chen Zhanheng 
Published: July 2024

Abstract
Representation learning over graph networks has recently gained popularity, with many models showing promising results. However, several challenges remain: (1) most methods are designed for static or discrete-time dynamic graphs; (2) existing continuous-time dynamic graph algorithms focus on a single evolving perspective; and (3) many continuous-time dynamic graph approaches necessitate numerous temporal neighbors to capture long-term dependencies. In response, this paper introduces a Multi-Perspective Feedback-Attention Coupling (MPFA) model. MPFA incorporates information from both evolving and original perspectives to effectively learn the complex dynamics of dynamic graph evolution processes. The evolving perspective considers the current state of historical interaction events of nodes and uses a temporal attention module to aggregate current state information. This perspective also makes it possible to capture long-term dependencies of nodes using a small number of temporal neighbors. Meanwhile, the original perspective utilizes a feedback attention module with growth characteristic coefficients to aggregate the original state information of node interactions. Experimental results on one dataset organized by ourselves and seven public datasets validate the effectiveness and competitiveness of our proposed model.
Policy Recommendations
Authors: Pflücke Felix 
Published: July 2024

Abstract
This chapter aims to translate the monograph’s empirical findings into targeted and actionable policy recommendations to increase the efficiency of EU consumer contract law and trader compliance. However, it is not an exhaustive list of necessary reforms. All policy recommendations build on the findings of the book’s empirical inquiry or similar studies in the field, comply with the EU’s principles of conferral, subsidiarity, and proportionality, adhere to the Better Regulation guidelines, and align with existing proposals or laws on the EU and national levels. The chapter addresses all policy recommendations to the relevant stakeholders, the EU legislator, the Member States, and other groups, such as e-commerce traders or consumer organizations.
Phloem
Authors: Roy Sumana 
Published: July 2024

Abstract
This chapter delves into the intertwined narratives of individuals whose works, though not explicitly focused on environmentalism, subtly contribute to a rich tradition of plant thinking in the Indian subcontinent. Through a mosaic of interconnected lives and creative endeavours, the chapter illuminates a hidden thread of botanical consciousness that permeates literature, art, and everyday life. From physicists fascinated by wireless communication to poets crafting a new poetic language around plant life, the narrative weaves through diverse experiences and perspectives. It challenges the Western-centric lens through which academia often views intellectual traditions, advocating for a decolonized approach that honours indigenous modes of thought. The chapter underscores the intrinsic connection between literary history and ecological consciousness, urging readers to reconsider the boundaries of theory and literature. Through meticulous examination of texts and cultural artifacts, the chapter aims to resurrect a history of plant thinking that is at risk of being forgotten, offering a glimpse into a world where humans coexist intimately with the botanical realm.
Anonymous
Authors: Roy Sumana 
Published: July 2024

Abstract
In trying to understand the colloquial culture around plant life, this chapter goes to Maya-mashi, a Bangladeshi refugee living in sub-Himalayan Bengal, whose tic is to annotate her conversations with Bangla idioms and phrases about plants. What made her, a single mother who had chosen a new country to save her life, identify with the plant world? As we move towards a world where both the proverbs and the plant life that gave birth to them seem on the verge of extinction, this rich archive that was polished by everyone who walked in the language shows that the anonymous were also plant thinkers.
Understanding proteome quantification in an interactive learning module on Google Cloud Platform
Authors: O’Connell Kyle A , Kopchick Benjamin , Carlson Thad , Belardo David , Byrum Stephanie D 
Published: July 2024

Abstract
This manuscript describes the development of a resource module that is part of a learning platform named ‘NIGMS Sandbox for Cloud-based Learning’ https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on protein quantification in an interactive format that uses appropriate cloud resources for data access and analyses. Quantitative proteomics is a rapidly growing discipline due to the cutting-edge technologies of high resolution mass spectrometry. There are many data types to consider for proteome quantification including data dependent acquisition, data independent acquisition, multiplexing with Tandem Mass Tag reporter ions, spectral counts, and more. As part of the NIH NIGMS Sandbox effort, we developed a learning module to introduce students to mass spectrometry terminology, normalization methods, statistical designs, and basics of R programming. By utilizing the Google Cloud environment, the learning module is easily accessible without the need for complex installation procedures. The proteome quantification module demonstrates the analysis using a provided TMT10plex data set using MS3 reporter ion intensity quantitative values in a Jupyter notebook with an R kernel. The learning module begins with the raw intensities, performs normalization, and differential abundance analysis using limma models, and is designed for researchers with a basic understanding of mass spectrometry and R programming language. Learners walk away with a better understanding of how to navigate Google Cloud Platform for proteomic research, and with the basics of mass spectrometry data analysis at the command line.
This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
Frequency-specific directed connectivity between the hippocampus and parietal cortex during verbal and spatial episodic memory: an intracranial EEG replication
Authors: Das Anup , Menon Vinod 
Published: July 2024

Abstract
Hippocampus-parietal cortex circuits are thought to play a crucial role in memory and attention, but their neural basis remains poorly understood. We employed intracranial electroencephalography (iEEG) to investigate the neurophysiological underpinning of these circuits across three memory tasks spanning verbal and spatial domains. We uncovered a consistent pattern of higher causal directed connectivity from the hippocampus to both lateral parietal cortex (supramarginal and angular gyrus) and medial parietal cortex (posterior cingulate cortex) in the delta–theta band during memory encoding and recall. This connectivity was independent of activation or suppression states in the hippocampus or parietal cortex. Crucially, directed connectivity from the supramarginal gyrus to the hippocampus was enhanced in participants with higher memory recall, highlighting its behavioral significance. Our findings align with the attention-to-memory model, which posits that attention directs cognitive resources toward pertinent information during memory formation. The robustness of these results was demonstrated through Bayesian replication analysis of the memory encoding and recall periods across the three tasks. Our study sheds light on the neural basis of casual signaling within hippocampus–parietal circuits, broadening our understanding of their critical roles in human cognition.