bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel Pipelines to Extract Differences in Proteome Dynamics Based on Health Status
Authors: Xu Bowen , Zhao Jiaying , Huang Tianhui , Honfo Sewanou Hermann , Trumpff Caroline , Picard Martin , Cohen Alan A. , Liu Molei 
Published: February 2025

AbstractUnderstanding dynamics and co-regulatory patterns in the human proteome is a promising path for unraveling the molecular basis of health and disease. Nevertheless, there remains an open challenge in extracting concise information from high-throughput proteomic data that can effectively characterize and predict health. We develop novel statistical and computational pipelines to tackle this problem in a longitudinal saliva proteomics data set collected throughout the awakening response in six healthy controls and six subjects with severe mitochondrial disease (MitoD), a clinical condition caused by genetic mitochondrial defects that affects cellular energy transformation and alters multiple dimensions of health.We undertook three independent unsupervised approaches to characterize proteome dynamics and assessed their ability to separate MitoD individuals from controls. First, we designed a permutation test to detect the global difference in the proteomic co-regulation structure between healthy and unhealthy subjects. Second, we performed non-linear embedding and cluster analysis on elasticity to capture a more complicated relationship between health and the proteome. Third, we developed a machine learning algorithm to extract low-dimensional representations of the proteome dynamic and use them to cluster subjects into healthy and unhealthy groups without any knowledge of their true status. All three methods showed clear differences between MitoD individuals and controls.Our results revealed a significant and consistent association between MitoD status and the saliva proteome at multiple levels during the awakening response, including its dynamic change, co-regulation structure, and elasticity. This connection is not restricted to a few MitoD-specific proteins but spreads over a wide range of proteins from many body functions and pathways. Pipelines such as those shown here are the first step toward establishing interpretable and accurate prediction rules for health based on proteome dynamics.
Comparative Analysis of Machine Learning Libraries for Neural Networks: A Benchmarking Study
Authors: Eid Aws Ismail Abu , Mjlae Salameh A. , Rababa’h Suzie Yaseen , Hammad Ahmed , Rababah Mahmoud Ali Ibrahim 
Published: February 2025

AbstractThis comprehensive benchmarking study explores the performance of three prominent machine learning libraries: PyTorch, Keras with TensorFlow backend, and Scikit-learn with the same criteria, software, and hardware. The evaluation encompasses two diverse datasets, “student performance” and “College Attending Plan Classification,” supported by Kaggle platforms utilizing feedforward neural networks (FNNs) as the modeling technique. The findings reveal that PyTorch and Keras with TensorFlow backend excel on the “College Attending Plan Classification” dataset, with PyTorch achieving impeccable precision, Recall, and F1-score for both classes. While Scikit-learn demonstrates commendable performance, it trails behind these libraries in this context. On the “Student Performance” dataset, all three libraries deliver comparable results, with Scikit-learn exhibiting the lowest accuracy at 16%. Keras with TensorFlow backend and PyTorch attain accuracy rates of 23%, respectively. Moreover, this study offers valuable insights into each library’s unique strengths and weaknesses when confronted with diverse dataset types. PyTorch emerges as the go-to choice for demanding tasks requiring high performance, while Scikit-learn proves advantageous for simpler tasks with modest computational demands. Keras with TensorFlow backend strikes a balance between performance and user-friendliness. This benchmarking endeavor equips machine learning practitioners with valuable guidance for selecting the most suitable library or framework tailored to their project requirements. It underscores the pivotal role of library choice in achieving optimal results in machine learning endeavors.
Early recovery during stroke rehabilitation predicts the functional outcome at discharge: a retrospective clinical study
Authors: Anziano Marco , Cusinato Riccardo , Tzovara Athina , Spierer Lucas , Chabwine Joelle N. 
Published: February 2025

AbstractBackgroundModels predicting functional recovery upon stroke rehabilitation (SR) are not implemented in clinical practice due to their complexity and limited power in patients with moderate/severe deficits.ObjectivesTo obtain preliminary evidence supporting the predictive value of a single measure of early recovery on SR discharge functional status.MethodsWe tested simple predictive models based on the functional independence measure (FIM) changes during the first three weeks of SR (3wFIMgain) in 81 patients with moderate/severe impairment.ResultsPatients with poor or good 3wFIMgain featured similar admission impairment, rate of complications, presence of aphasia or dominant-sided hemisyndrome, while poor early recovery was associated with lesions to the left sensory-motor cortex, temporo-parietal junction, and superior longitudinal fasciculus.The 3wFIMgain effectively predicted the discharge FIM gain in patients with ≥ 6 weeks of SR stay. Combined with the admission FIM, the 3wFIMgain improved a predictive model for the discharge FIM.ConclusionsThe 3wFIMgain bears strong discharge prognostic value and synthetizes complex information about the early recovery of stroke patients that cannot be described by individual clinical predictors. Measures of early recovery might improve the power of models and simplify them, thus favoring application in clinical practice. Future validation in confirmatory studies is required.
Geometry-driven asymmetric cell divisions pattern cell cycles and zygotic genome activation in the zebrafish embryo
Authors: Mishra Nikhil , Li Yuting I. , Hannezo Edouard , Heisenberg Carl-Philipp 
Published: February 2025

AbstractSynchrony in early embryonic cell cycles, followed by gradual desynchronization at the midblastula transition (MBT), is a widely conserved feature across animal phylogeny. Embryos that fail to maintain synchrony during these early stages do not develop properly, highlighting the critical importance of this process. However, the mechanisms underlying the initial synchronization and subsequent desynchronization of cell cycles - and their developmental significance - remain poorly understood. Here we show that the initial cell cycles in zebrafish embryos are synchronized primarily through cell-autonomous mechanisms. Furthermore, we reveal that their gradual desynchronization is spatially patterned by the geometry of the dividing embryo, which establishes a cell volume gradient through unequal cell divisions. This volume gradient translates into a cell cycle gradient by unequal S-phase lengthening due to volume-dependent changes in the nucleocytoplasmic ratio. Importantly, we find that this volume gradient, and the resulting cell cycle gradient, also spatiotemporally patterns the initiation of zygotic genome activation (ZGA) - a hallmark of MBT - within the embryo, thereby serving as a key symmetry-breaking event in animal development. Thus, our findings uncover a previously unrecognized role for early embryonic geometry in establishing an axis of transcriptional asymmetry during the transition to developmental autonomy.
Entanglement enabled intensity interferometry in ultrarelativistic ultraperipheral nuclear collisions
Authors: Brandenburg James Daniel , Duan Haowu , Tu Zhoudunming , Venugopalan Raju , Xu Zhangbu 
Published: February 2025

An important tool in studying the subfemtoscale spacetime structure of matter in ultrarelativistic heavy-ion collisions is Hanbury Brown–Twiss (HBT) intensity interferometry of identical particles in the final state of the collisions. We propose that a variant of the entanglement enabled intensity interferometry (E2I2) framework introduced by Cotler and Wilczek can provide a powerful alternative to HBT interferometry in extracting fundamental nonperturbative features of quantum chromodynamics at high energies. We apply this framework to demonstrate that the spatial distributions of color singlet (pomeron) configurations in nuclei are sensitive to measurements of exclusive resonant decays of ρ mesons into π± pairs in ultrarelativistic ultraperipheral nuclear collisions (UPCs) at the Relativistic Heavy Ion Collider and the Large Hadron Collider. A preliminary analysis suggests that the model-independent extraction of pomeron distributions will require careful treatment of the interplay of E2I2 in the vector meson exclusive decay with the incoherent cross section for exclusive vector meson production. The E2I2 framework developed here is quite general. It can also be employed as a tool to extract information on the spin structure of pomeron couplings as well as enhance the discovery potential for rare odderon configurations from exclusive vector meson decays into few-particle final states both in UPCs and at the Electron-Ion Collider.

Published by the American Physical Society
2025
Computing the interaction of light pulses with objects moving at relativistic speeds
Authors: Vavilin Maxim , Mazo-Vásquez Juan Diego , Fernandez-Corbaton Ivan 
Published: February 2025

The interaction of matter with short light pulses is relevant in optical traps, optical tweezers, and many other applications. The theoretical description of such polychromatic light-matter interaction is challenging, and more so when the object is moving with respect to the light source, albeit with constant speed. Light sails are futuristic examples where such speed should reach the relativistic regime. In here, we provide a methodology for the theoretical and numerical analysis of the interaction of light pulses with objects moving with constant speed. The methodology allows one, in particular, to readily compute the transfer of fundamental quantities such as energy and momentum from the light pulse to the object. As an example, we compute the transfer of energy and momentum between a given pulse and a silicon sphere moving at relativistic speeds. The methodology, however, is valid for generic pulses and objects. Particularizing the equations to the case of zero speed allows one to treat static or quasistatic objects. The method is based on the polychromatic T-matrix (transition matrix) formalism, which leverages the many publicly available resources for computing T matrices.

Published by the American Physical Society
2025
Image registration for accurate electrode deformation analysis in operando microscopy of battery materials
Authors: Sun Tianxiao , Peng Robert , Li Wenlong , Liu Yijin 
Published: February 2025

Operando imaging techniques have become increasingly valuable in both battery research and manufacturing. However, the reliability of these methods can be compromised by instabilities in the imaging setup and operando cells, particularly when utilizing high-resolution imaging systems. The acquired imaging data often include features arising from both undesirable system vibrations and drift, as well as the scientifically relevant deformations occurring in the battery sample during cell operation. For meaningful analysis, it is crucial to distinguish and separately evaluate these two factors. To address these challenges, we employ a suite of advanced image-processing techniques. These include fast Fourier transform analysis in the frequency domain, power spectrum-based assessments for image quality, as well as rigid and non-rigid image-registration methods. These techniques allow us to identify and exclude blurred images, correct for displacements caused by motor vibrations and sample holder drift and, thus, prevent unwanted image artifacts from affecting subsequent analyses and interpretations. Additionally, we apply optical flow analysis to track the dynamic deformation of battery electrode materials during electrochemical cycling. This enables us to observe and quantify the evolving mechanical responses of the electrodes, offering deeper insights into battery degradation. Together, these methods ensure more accurate image analysis and enhance our understanding of the chemomechanical interplay in battery performance and longevity.
Work boundary violations and daily goal progress in remote work: the importance of the work role re-engagement
Authors: Xu Nan , Tang Chunyong , Yang Chengchuan , Lai Yanzhao 
Published: February 2025

Purpose
This paper aims to empirically study the effect of work boundary violations in remote settings on daily goal progress and the important role that work role reengagement plays for remote workers.

Design/methodology/approach
This paper conducted a five-day diary study in China, involving a total of 118 remote workers, to collect data on the effects of work boundary violations on daily goal progress.

Findings
The results demonstrated that self-control resource depletion plays a mediating role in the relationship between work boundary violations and daily goal progress. In addition, work role reengagement was found to mitigate the association between work boundary violations and self-control resource depletion.

Practical implications
This paper provides employees with the signals that cause them to perform less well in remote work situations than in traditional offices. Employees can develop work−family boundary management strategies to reduce work boundary violations while teleworking.

Originality/value
This paper enriches the existing literature on work boundary violations by incorporating ego depletion theory and integrating it with the current boundary management literature. The paper provides theoretically grounded recommendations for organizations seeking to enhance the efficiency of remote workers.
Understanding the residential search process in Indian context: analysing decision dimensions for location choice set development
Authors: Saini Preety , Pandit Debapratim 
Published: February 2025

Purpose
This study aims to comprehensively explore households’ residential search process by examining various decision dimensions – search tenure, housing typology, search criteria, information sources, search extent and search duration – and identifying factors influencing each.

Design/methodology/approach
The study area includes Bidhannagar Municipal Corporation and Rajarhat Newtown. A retrospective survey was conducted with recently relocated households to investigate their search process. Based on a search process framework from literature, separate logit models were developed to analyse decision dimensions.

Findings
The study identifies the influence of household typology, size, income, car ownership, origin and education, including travel attitudes, relocation reasons and urgency on decision dimensions. Key findings indicate that households use five dominant search criteria to orient themselves spatially, also affecting the search extent. Moreover, some households enter the housing market without housing typology preferences, exploring all options.

Practical implications
Choice set development – a critical stage in residential location choice modelling – represents the outcome of household’s search process: the collection of potential locations considered before making a final selection. Traditionally, entire urban area is considered as choice set, but the study’s findings can inform screening rules to tailor choice set to household preferences.

Originality/value
To the best of the authors’ knowledge, this is the first study to comprehensively explore the housing search process in India, introducing novel factors like travel attitudes, relocation motivations and urgency. Instead of focusing on specific housing typologies, the authors investigate whether households enter the market with established preferences or not. The authors also examined search criteria households consider to define search space and its impact on search extent.
Breaking the virtual wall: analysing barriers to metaverse adoption in manufacturing industries
Authors: Agrawal Rohit , Wankhede Vishal Ashok 
Published: February 2025

Purpose
The adoption of metaverse in manufacturing holds significant benefits, but there are several barriers to its seamless integration. This paper aims to identify such barriers and prioritize them in a manner that allows industrial leaders to strategize for smooth adoption.

Design/methodology/approach
In this study, we applied two-stage methods, first the identification and validation of barriers through an empirical study applied to Exploratory Factor Analysis (EFA). A purposive sampling technique and snowball sampling facilitated data collection from these expert sources. Through snowball sampling, additional contacts working in the metaverse field were reached, resulting in 235 possible respondents; the survey yielded 104 completed responses. Thereafter, the best-worst method (BWM) was used to measure and rank the barriers.

Findings
The study results show that the two most critical barriers are “Lack of data security and privacy” and “Lack of integration compatibility with existing systems.” Such findings inform industry leaders of specific recommendations for structural changes, training programs, necessary technological investments and collaborative efforts to overcome these barriers.

Research limitations/implications
This work adds significantly to academic discussion by prioritizing barriers towards integrating metaverse technology in manufacturing. In addition, this strategic methodology aids in critical appraisal and ranking of barriers for successful adoption. This study also identifies key barriers but acknowledges that other unexamined factors might be lurking in the background, such as virtual economy, financial risks and cross-border legal issues.

Practical implications
The study’s conclusions cannot be generalized to the other sectors, thus indicating the necessity of carrying out a comparative multi-sector study in the future.

Originality/value
To the best of the authors’ knowledge, the study on systematic prioritization of barriers to adopting metaverse technology in manufacturing is the original contribution of the authors.
Accuracy analysis of herringbone gear transmission based on measured symmetry error
Authors: Guo Wanying , Bao Heyun , Cao Jianfeng , Zhou Yiping 
Published: February 2025

Purpose
The symmetry error generated in the machining process of herringbone gears will destroy the stability of the transmission system. The purpose of this paper is to establish a symmetry error measurement model of herringbone gear based on spiral measurement method, and to evaluate the transmission accuracy of herringbone gear based on the measured symmetry error.

Design/methodology/approach
A symmetry error measurement model of herringbone gear based on spiral measurement method is proposed. The measurement method is verified by three coordinate measuring instrument. The transmission error analysis model of herringbone gear is established. The influence of speed and load on it is analyzed.

Findings
At the same speed, when the load increases from 100 N·m to 500 N·m, the transmission error increases and the transmission accuracy of the system decreases. Under the same load, the speed is increased from 100 rpm to 500 rpm, which has little effect on the transmission error.

Originality/value
The measurement method and analysis model used in this paper provide reference value and significance for the measurement and analysis of symmetry error.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0350/
An axial elastic deformation of ceramets on elastohydrodynamic lubrication of wavy-tilt-dam mechanical face seals
Authors: Zhang Baojun , Wang Zeping , An Junqing , Liu Sihang , Lei Mingkai 
Published: February 2025

Purpose
This paper aims to investigate the lubrication characteristics of siliconized graphite with a wavy-tilt-dam (WTD) pattern applied to the hydrodynamic face seals.

Design/methodology/approach
It focuses on two friction pairs, carbon graphite versus tungsten carbide (CG-TC) and siliconized graphite versus siliconized graphite (SG-SG), through a three-dimensional elastic hydrodynamic lubrication numerical model that integrates finite difference method and finite element method. The consequence of axial elastic deformation of sealing pair materials on film thickness, film pressure, cavitation and sealing performance for a WTD mechanical face seal under full working conditions of ΔP = 0.8, 5.3 and 15.8 MPa are analyzed theoretically.

Findings
The nuclear hydrodynamic WTD face seal generates a convergent gap and exhibits a dual-characteristic behavior of hydrodynamic and hydrostatic effects under various ΔP. Compared to the CG-TC, the SG-SG shows a lower minimum film thickness, decreasing by 3.9%, 17.3% and 35.1%. The flow leakage rate decreases by 47.8%, 52.1% and 75.4%. In addition, the film stiffness increases by 46.8%, 49.8% and 97.8%. Thus, the SG-SG better deals with the dynamic tracking problem, and the sealing performance is stable. The strength and hardness of siliconized graphite enhance WTD sealing performance and improve cavitation control in high-pressure applications.

Originality/value
The lubrication characteristics of the siliconized graphite with a WTD pattern could inform the future design of hydrodynamic shallow groove wavy seals in boiler feedwater engineering implements under high-pressure conditions for the nuclear power industry.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0382/
Differences in sustainability orientation and asymmetric power in buyer–seller relationships: direct and moderated impacts on relationship satisfaction
Authors: Talay Cagri , AbedRabbo Majd , S. Oliveira João , Crick James M. 
Published: February 2025

Purpose
This research aims to address the knowledge gaps in determining factors affecting relationship satisfaction in buyer–seller relationships, with a specific focus on sustainability orientation and asymmetric power dynamics.

Design/methodology/approach
Drawing upon the Social Exchange Theory (SET) and using a sample of 436 US-based companies, this research uses structural equation modelling to investigate the impact of sustainability orientation and asymmetric power on relationship satisfaction within these relationships. Furthermore, this research explores the moderating role of asymmetric power in the connection between differences in sustainability orientation and relationship satisfaction.

Findings
The results uncover a significant negative association between the extent of divergence in sustainability orientation between buyers and sellers and the level of relationship satisfaction. Notably, asymmetric power in buyer–seller relationships positively moderates the influence of sustainability orientation differences on relationship satisfaction.

Originality/value
This research sheds light on the increasingly vital issue of sustainability orientation in buyer–seller relationships by enhancing our understanding of asymmetric power’s role in shaping relationship satisfaction within business-to-business relationships.