bluuebunny/crossref_metadata_2025_split huggingface dataset:
Markov generators as non-Hermitian supersymmetric quantum Hamiltonians: spectral properties via bi-orthogonal basis and singular value decompositions
Authors: Monthus Cécile 
Published: August 2024

AbstractContinuity equations associated with continuous-time Markov processes can be considered as Euclidean Schrödinger equations, where the non-Hermitian quantum HamiltonianH=divJis naturally factorized into the product of the divergence operatordivand the current operatorJ. For non-equilibrium Markov jump processes in a space ofNconfigurations withMlinks andC=M−(N−1)⩾1independent cycles, this factorization of theN × NHamiltonianH=I†Jinvolves the incidence matrixIand the current matrixJof sizeM × N, so that the supersymmetric partnerH^=JI†governing the dynamics of the currents existing on theMlinks is of sizeM × M. To better understand the relations between the spectral decompositions of these two HamiltoniansH=I†JandH^=JI†with respect to their bi-orthogonal basis of right and left eigenvectors that characterize the relaxation dynamics towards the steady state and the steady currents, it is useful to analyze the properties of the singular value decomposition of the two rectangular matricesIandJof sizeM × Nand the interpretations in terms of discrete Helmholtz decompositions. This general framework concerning Markov jump processes can be adapted to non-equilibrium diffusion processes governed by Fokker–Planck equations in dimensiond, where the numberNof configurations, the numberMof links and the numberC=M−(N−1)of independent cycles become infinite, while the two matricesIandJbecome first-order differential operators acting on scalar functions to produce vector fields.
Quenches in the Sherrington–Kirkpatrick model
Authors: Erba Vittorio , Behrens Freya , Krzakala Florent , Zdeborová Lenka 
Published: August 2024

Abstract
The Sherrington–Kirkpatrick model is a prototype of a complex non-convex energy landscape. Dynamical processes evolving on such landscapes and locally aiming to reach minima are generally poorly understood. Here, we study quenches, i.e. dynamics that locally aim to decrease energy. We analyse the energy at convergence for two distinct algorithmic classes, single-spin flip and synchronous dynamics, focusing on greedy and reluctant strategies. We provide precise numerical analysis of the finite size effects and conclude that, perhaps counter-intuitively, the reluctant algorithm is compatible with converging to the ground state energy density, while the greedy strategy is not. Inspired by the single-spin reluctant and greedy algorithms, we investigate two synchronous time algorithms, the sync-greedy and sync-reluctant algorithms. These synchronous processes can be analysed using dynamical mean field theory (DMFT), and a new backtracking version of DMFT. Notably, this is the first time the backtracking DMFT is applied to study dynamical convergence properties in fully connected disordered models. The analysis suggests that the sync-greedy algorithm can also achieve energies compatible with the ground state, and that it undergoes a dynamical phase transition.
Evaluating AI’s capability to reflect physical mechanisms: a case study of tropical cyclone impacts on extreme rainfall
Authors: Xu Hongxiong , Duan Yihong , Xu Xiangde 
Published: August 2024

Abstract
Tropical cyclones not only induce extreme precipitation events but also exert indirect influences on precipitation, a factor often underestimated in forecasting. Traditionally, these influences are identified using numerical sensitivity experiments with numerical models like the Weather Research and Forecasting (WRF) model, which require substantial computational resources. This study investigates the potential of the Artificial intelligence (AI)-based Pangu-Weather model to reveal these complex mechanisms by comparing its performance with the WRF model, focusing on Typhoon Khanun’s impact on the extreme rainfall event in North China from 29 July to 1 August 2023. Our analysis shows that Pangu-Weather effectively captures key atmospheric systems and TC positions, outperforming WRF. Specifically, WRF simulations excluding Khanun demonstrate a reduction in northward moisture transport on the eastern side of North China, but minimal impact on the extreme precipitation area for most of the period. Pangu-Weather successfully reproduces these processes, aligning closely with WRF at larger scales (e.g. greater than 300 km). However, Pangu-Weather struggles to discern and explain smaller-scale processes (e.g. less than 300 km). These findings highlight Pangu-Weather’s potential to advance meteorological research and disaster prevention, demonstrating AI’s capability to accurately depict complex large-scale physical processes.
Experimental study on the effects of composite reinforcement of ionic soil stabilizer and sand on bentonite
Authors: Wang Fenghua , Yuan Yuefeng , Hou Meiying , Wang Ailin , Yang Yani , Xiong Qian 
Published: August 2024

Abstract
This paper utilizes both the ionic soil stabilizer (ISS) and sand to strengthen bentonite, as ISS effectively reduces its expansive properties and sand rapidly improves its strength to reduce cracks. Various experiments are conducted to analyze the changes in physical and mechanical properties of the bentonite strengthened by ISS-sand (ISB). The results show that not only do the sand particles enhance the strength of bentonite, but also the ISS significantly reduces its expansibility. Furthermore, the mass ratio of sand to bentonite has different effects on the unconfined compressive strength (UCS) and the freeze-tolerance of sand-reinforced bentonite (SB) and ISB. These findings suggest that a comprehensive consideration of the sand mixing rate is necessary when implementing ISS reinforcement on natural expansive soil.
Composite fault diagnosis of gearbox based on deep graph residual convolutional network
Authors: Fan Bingbing , Liu Chang , Chang Guochao , He Feifei , Liu Tao 
Published: August 2024

Abstract
In gearbox systems, a composite fault diagnosis resulting from mutual interference among different components poses a significant challenge. The traditional composite fault diagnosis methods based on conventional signal analyses and feature extractions often suffer from low sensitivity to fault characteristics and difficulty in effectively identifying composite faults. On the other hand, composite fault diagnosis research via deep learning and data-driven approaches typically faces issues such as incomplete training datasets and insufficient exploration of feature correlation information, leading to an underutilization of the fault information. Therefore, this paper proposes a deep graph residual convolutional neural network (DGRCN) based on feature correlation mining for composite fault diagnosis in gearboxes. First, Pearson correlation coefficients are utilized to explore the relationships among features in the traditional feature set, transforming these relationships into a graph-structured feature set. Next, a deep graph residual convolutional network is constructed by integrating deep graph structures into a residual framework. This network globally extracts composite fault subgraph features and explores local feature correlations. Finally, the model is trained via various composite fault datasets under complex working conditions, achieving the diagnosis and identification of composite faults under the constraint of limited samples. The experimental results demonstrate that the proposed method significantly improves composite fault diagnosis accuracy, outperforming commonly used methods in this field.
Gate mesa terminal with drain-field-plated β-Ga2O3 MOSFET with ultra-high power figure of merit
Authors: Zhang Yunfei , Luan Suzhen , Cheng Xuepei 
Published: August 2024

Abstract
In this article, a novel gate mesa terminal (GMT) device structure incorporating a drain field plate is proposed. This design features mesa terminals with varying bevel angles positioned atop the gate. The objective is to enhance the breakdown voltage (Vbr) and reduce the on-resistance (Ron) of the lateral β-Ga2O3 metal-oxide-semiconductor field-effect transistor (MOSFET). Through the implementation of the GMT structure, the peak electric field within the β-Ga2O3 MOSFET is redirected towards the passivation layer. This effectively mitigates the electric field in the epitaxial layer, thereby increasing Vbr. The optimal values for Vbr, specific on-resistance (Ron,sp) and maximum transconductance (gm) across various GMT structures are 4827 V, 9.9 mΩ·cm2 and 15.32 mS/mm, respectively. These metrics represent a 2.63-fold, 0.88-fold, and 1.25-fold improvement compared to the non-GMT structure. Additionally, when the doping concentration of epitaxial layer is 1 × 1016 cm−3, the GMT achieves an enhanced threshold voltage of +0.26 V. By simulating different bevel angles, field plate parameters, epitaxial layer doping concentrations, and mesa thicknesses, an optimal power figure of merit (PFOM) of 1.914 GW cm−2 is attained. This innovative design introduces a fresh concept for the development of the next generation of high voltage and high-power devices rated above 4 KV.
Towards a comprehensive visualisation of structure in large scale data sets
Authors: Garriga Joan , Bartumeus Frederic 
Published: August 2024

Abstract
Dimensionality reduction methods are fundamental to the exploration and visualisation of large data sets. Basic requirements for unsupervised data exploration are flexibility and scalability. However, current methods have computational limitations that restrict our ability to explore data structures to the lower range of scales. We focus on t-SNE and propose a chunk-and-mix protocol that enables the parallel implementation of this algorithm, as well as a self-adaptive parametric scheme that facilitates its parametric configuration. As a proof of concept, we present the pt-SNE algorithm, a parallel version of Barnes-Hat-SNE (an

O

(
n

log

n
)

implementation of t-SNE). In pt-SNE, a single free parameter for the size of the neighbourhood, namely the perplexity, modulates the visualisation of the data structure at different scales, from local to global. Thanks to parallelisation, the runtime of the algorithm remains almost independent of the perplexity, which extends the range of scales to be analysed. The pt-SNE converges to a good global embedding comparable to current solutions, although it adds little noise at the local scale. This noise illustrates an unavoidable trade-off between computational speed and accuracy. We expect the same approach to be applicable to faster embedding algorithms than Barnes-Hat-SNE, such as Fast-Fourier Interpolation-based t-SNE or Uniform Manifold Approximation and Projection, thus extending the state of the art and allowing a more comprehensive visualisation and analysis of data structures.
SpatialOne: end-to-end analysis of visium data at scale
Authors: Kamel Mena , Sarangi Amrut , Senin Pavel , Villordo Sergio , Sunaal Mathew , Barot Het , Wang Seqian , Solbas Ana , Cano Luis , Classe Marion , Bar-Joseph Ziv , Pla Planas Albert 
Published: August 2024

Abstract

Motivation
Spatial transcriptomics allow to quantify mRNA expression within the spatial context. Nonetheless, in-depth analysis of spatial transcriptomics data remains challenging and difficult to scale due to the number of methods and libraries required for that purpose.

Results
Here we present SpatialOne, an end-to-end pipeline designed to simplify the analysis of 10x Visium data by combining multiple state-of-the-art computational methods to segment, deconvolve, and quantify spatial information; this approach streamlines the analysis of reproducible spatial-data at scale.

Availability and implementation
SpatialOne source code and execution examples are available at https://github.com/Sanofi-Public/spatialone-pipeline, experimental data is available at https://zenodo.org/records/12605154. SpatialOne is distributed as a docker container image.
Effects of an online mindfulness-based intervention on brain haemodynamics: a pilot randomized controlled trial using functional near-infrared spectroscopy
Authors: Adachi Koichiro , Takizawa Ryu 
Published: August 2024

Abstract
Although many neuroimaging studies have evaluated changes in the prefrontal cortex during mindfulness-based interventions, most of these studies were cross-sectional studies of skilled participants or involved pre–post comparisons before and after a single session. While functional near-infrared spectroscopy is a useful tool to capture changes in the hemodynamic response of the prefrontal cortex during continuous mindfulness-based intervention, its ability to detect the accumulated effects of continuous mindfulness-based intervention is currently unclear. We investigated whether a 12-wk online mindfulness-based intervention changed the hemodynamic response of the prefrontal cortex during a verbal fluency task. Eighty-two healthy university students were randomly allocated to a 12-wk online mindfulness-based intervention group or a wait-list control group. The integral values of oxygenated hemoglobin measured using functional near-infrared spectroscopy before and after the intervention were compared to the values in the wait-list group. The intervention condition showed significantly greater functional near-infrared spectroscopy signal activation than the control condition; however, the effect sizes before and after the intervention were small. Thus, continuous mindfulness-based intervention could alter prefrontal cortex function, and functional near-infrared spectroscopy could be useful for measuring the accumulated effects of continuous mindfulness-based interventions. With a better understanding of the association between mindfulness and functional near-infrared spectroscopy signals, functional near-infrared spectroscopy can be used for biofeedback analyses.
Alzheimer’s disease risk gene CD2AP is a dose-sensitive determinant of synaptic structure and plasticity
Authors: Pavešković Matea , De-Paula Ruth B , Ojelade Shamsideen A , Tantry Evelyne K , Kochukov Mikhail Y , Bao Suyang , Veeraragavan Surabi , Garza Alexandra R , Srivastava Snigdha , Song Si-Yuan , Fujita Masashi , Duong Duc M , Bennett David A , De Jager Philip L , Seyfried Nicholas T , Dickinson Mary E , Heaney Jason D , Arenkiel Benjamin R , Shulman Joshua M 
Published: August 2024

Abstract
CD2-Associated protein (CD2AP) is a candidate susceptibility gene for Alzheimer’s disease, but its role in the mammalian central nervous system remains largely unknown. We show that CD2AP protein is broadly expressed in the adult mouse brain, including within cortical and hippocampal neurons, where it is detected at pre-synaptic terminals. Deletion of Cd2ap altered dendritic branching and spine density, and impaired ubiquitin-proteasome system activity. Moreover, in mice harboring either one or two copies of a germline Cd2ap null allele, we noted increased paired-pulse facilitation at hippocampal Schaffer-collateral synapses, consistent with a haploinsufficient requirement for pre-synaptic release. Whereas conditional Cd2ap knockout in the brain revealed no gross behavioral deficits in either 3.5- or 12-month-old mice, Cd2ap heterozygous mice demonstrated subtle impairments in discrimination learning using a touchscreen task. Based on unbiased proteomics, partial or complete loss of Cd2ap triggered perturbation of proteins with roles in protein folding, lipid metabolism, proteostasis, and synaptic function. Overall, our results reveal conserved, dose-sensitive requirements for CD2AP in the maintenance of neuronal structure and function, including synaptic homeostasis and plasticity, and inform our understanding of possible cell-type specific mechanisms in Alzheimer’s Disease.
Occurrence of blaNDM-1, blaNDM-5, blaNDM-7, and blaKPC-2 genes in clinical isolates of enterobacterales with high genetic variability, from colonization and infection in patients with or without COVID-19, from a hospital in Brazil
Authors: Martins Lamartine Rodrigues , Pimentel Maria Izabely Silva , de Oliveira Érica Maria , Jucá Moacir Batista , Beltrão Elizabeth Maria Bispo , Lopes Ana Catarina de Souza 
Published: August 2024

Abstract

Aims
This study aimed to investigate the presence of beta-lactams resistance genes and the clonal relationship of clinical isolates of Enterobacterales obtained from patients with and without COVID-19, in a hospital in northeastern Brazil.

Methods and results
The study analyzed 45 carbapenem-resistant clinical isolates using enterobacterial repetitive intergenic consensus (ERIC-PCR), PCR, and amplicon sequencing to detect resistance genes (blaKPC, blaGES, blaNDM, blaVIM, and blaIMP). The main species were Klebsiella pneumoniae, Serratia marcescens, and Proteus mirabilis. Detected genes included blaNDM (46.66%), blaKPC (35.55%), and both (17.79%). ERIC-PCR showed multiclonal dissemination and high genetic variability. The main resistance gene was blaNDM, including blaNDM-5 and blaNDM-7.

Conclusions
The presence of Enterobacterales carrying blaKPC and blaNDM in this study, particularly K. pneumoniae, in infections and colonizations of patients with COVID-19 and non-COVID-19, highlights genetic variability and resistance to carbapenems observed in multiple species of this order.
Dietary xylo-oligosaccharides alleviates LPS-induced intestinal injury via endoplasmic reticulum-mitochondrial system pathway in piglets
Authors: Liu Guangmang , Sun Weixiao , Zhang Ruinan , Shen Fei , Jia Gang , Zhao Hua , Chen Xiaoling , Wang Jing 
Published: August 2024

Abstract
The beneficial effects of xylo-oligosaccharides (XOS) on the intestine have been widely reported, including anti-inflammation, antioxidant, maintenance of intestinal epithelial barrier, and treatment of intestinal injury. However, the specific mechanism of XOS in mitigating intestinal injury in weaned piglets remains unclear. Therefore, this study aimed to explore the specific mechanism of XOS in mitigating intestinal injury. The study is a complete randomized design with 24 weaned piglets in a 2 × 2 factorial arrangement that includes diet treatments (basal diet vs. 0.02% XOS) and immunological challenge [saline vs. lipopolysaccharide (LPS)]. All piglets were fed a basal diet or a XOS diet for 21 d. On day 22, all piglets received an injection of LPS or saline. In this study, dietary XOS increased jejunal villus height, reduced crypt depth and oxidative stress, and enhanced the gene and protein expression of Claudin-1, Occludin, and zonula occludens 1 (P &lt; 0.05). The piglets fed the XOS diet had lower serum Diamine oxidase activity and d-lactic acid content (P &lt; 0.05). In addition, dietary XOS regulates endoplasmic reticulum (ER)–mitochondria system function and the expression of key molecules, including mitochondrial dynamics dysfunction [mitofusin (Mfn)-1, optic atrophy 1, fission 1, and dynamin-related protein 1], ER stress [activating transcription factor 4 (ATF4), ATF6, C/EBP-homologous protein, eukaryotic initiation factor 2α, glucose-regulated protein (GRP) 78, GRP94, and protein kinase R-like ER kinase] and the mitochondria-associated ER membranes (MAM) disorders (Mfn2, GRP75, and voltage-dependent anion channel 1) (P &lt; 0.05). Therefore, the findings to indicate that dietary XOS is effective against LPS-induced jejunal injury may be attributed to its ability to alleviate mitochondrial dynamics dysfunction, ER stress, and MAM disorders.
Fractures by race and ethnicity in a diverse sample of postmenopausal women: a current evaluation among Hispanic and Asian origin groups
Authors: Wright Nicole C , Follis Shawna , Larson Joseph C , Crandall Carolyn J , Stefanick Marcia L , Ing Steven W , Cauley Jane A 
Published: August 2024

Abstract
Using 1998-2022 Women’s Health Initiative (WHI) data, our study provides contemporary fracture data by race and ethnicity, specifically focusing on Hispanic and Asian women. Fractures of interest included any clinical, hip, and major osteoporotic fractures (MOFs). We utilized the updated race and ethnicity information collected in 2003, which included seven Asian and five Hispanic origin groups. We computed crude and age-standardized fracture incidence rates per 10 000 woman-years across race and ethnic categories and by Asian and Hispanic origin. We used Cox proportional hazards model, adjusting for age and WHI clinical trial arm, to evaluate the risk of fracture (1) by race compared to White women, (2) Asian origin compared to White women, (3) Hispanic compared to non-Hispanic women, and (4) Asian and Hispanic origins compared the most prevalent origin group. Over a median (interquartile range) follow-up of 19.4 (9.2-24.2) years, 44.2% of the 160 824 women experienced any clinical fracture, including 36 278 MOFs and 8962 hip fractures. Compared to White women, Black, Pacific Islander, Asian, and multiracial women had significantly lower risk of any clinical and MOFs, while only Black and Asian women had significantly lower hip fracture risk. Within Asian women, Filipina women had 24% lower risk of any clinical fracture compared to Japanese women. Hispanic women had significantly lower risk of any clinical, hip, and MOF fractures compared to non-Hispanic women, with no differences in fracture risk observed within Hispanic origin groups. In this diverse sample of postmenopausal women, we confirmed racial and ethnic differences in fracture rates and risk, with novel findings among within Asian and Hispanic subgroups. These data can aid in future longitudinal studies evaluate contributors to racial and ethnic differences in fractures.
Dynamic diffusion
Authors: Bradford Anu , Chilton Adam , Linos Katerina 
Published: August 2024

Abstract
Research on legal diffusion typically focuses on laws’ initial adoption and ignores their later evolution. We develop a typology of three subsequent diffusion patterns: convergence, when countries revise laws to move closer to leading regulators; customization, when countries revise laws to move away from leading regulators; and stagnation, when countries cease legislating, leaving initially adopted laws in place. We then propose a general theory suggesting that economic size and geographic distance from leading regulators predict which of the three patterns countries follow. We explore this theory with case studies on the dynamic diffusion of antitrust laws in Russia, Colombia, and Australia.
Sterile activation of RNA-sensing pathways in autoimmunity
Authors: Li Jiaxin , Zhu Junyan , Yang Hui , Hou Fajian 
Published: August 2024

Abstract
RNA-sensing pathways play a pivotal role in host defense against pathogenic infections to maintain cellular homeostasis. However, in the absence of infection, certain endogenous RNAs can serve as the activators of RNA-sensing pathways as well. The inappropriate activation of RNA-sensing pathways by self-ligands leads to systemic inflammation and autoimmune diseases. In this review, we summarize current findings on the sterile activation of RNA sensors, as well as its implications in autoimmunity, inflammatory diseases, and therapeutics.