bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shotgun crystal structure prediction using machine-learned formation energies
Authors: Chang Liu , Tamaki Hiromasa , Yokoyama Tomoyasu , Wakasugi Kensuke , Yotsuhashi Satoshi , Kusaba Minoru , Oganov Artem R. , Yoshida Ryo 
Published: December 2024

AbstractStable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configurations. Generally, this requires repeated first-principles energy calculations, which is often impractical for large crystalline systems. Here, we present significant progress toward solving the crystal structure prediction problem: we performed noniterative, single-shot screening using a large library of virtually created crystal structures with a machine-learning energy predictor. This shotgun method (ShotgunCSP) has two key technical components: transfer learning for accurate energy prediction of pre-relaxed crystalline states, and two generative models based on element substitution and symmetry-restricted structure generation to produce promising and diverse crystal structures. First-principles calculations were performed only to generate the training samples and to refine a few selected pre-relaxed crystal structures. The ShotunCSP method is less computationally intensive than conventional methods and exhibits exceptional prediction accuracy, reaching 93.3% in benchmark tests with 90 different crystal structures.
Topological phase transition in quasi-one-dimensional bismuth iodide Bi4I4
Authors: Zhao W. X. , Yang M. , Du X. , Li Y. D. , Zhai K. Y. , Hu Y. Q. , Han J. F. , Huang Y. , Liu Z. K. , Yao Y. G. , Zhuang J. C. , Du Y. , Zhou J. J. , Chen Y. L. , Yang L. X. 
Published: December 2024

AbstractQuasi-one-dimensional (quasi-1D) bismuth iodide Bi4I4 exhibits versatile topological phases of matter including weak topological insulator (WTI) and higher-order topological insulator (HOTI) phases with high tunability in response to external parameters. In this work, performing laser-based angle-resolved photoemission spectroscopy with submicron spatial resolution (micro-ARPES), we reveal the presence of an energy gap on the (100) surface of the low-temperature α-Bi4I4, providing spectroscopic evidence for the HOTI phase. Conversely, the high-temperature β-Bi4I4 harbors gapless Dirac fermions on the (100) surface alongside gapped states on the (001) surface, thereby establishing a WTI phase. By tracking the temperature evolution of the (100) surface states, we unveil a thermal hysteresis of the surface gap in line with the α-β structural phase transition. Our findings directly evidence a temperature-induced topological phase transition from WTI to HOTI in Bi4I4, which paves the way to its potential applications at room temperature.
Systematic review of the impact of intestinal microbiota on vaccine responses
Authors: Ardura-Garcia Cristina , Curtis Nigel , Zimmermann Petra 
Published: December 2024

AbstractThe intestinal microbiota plays a critical role in host immunity and might contribute to the significant variation between individuals’ vaccine responses. A systematic search was done using MEDLINE and Embase to identify original human studies investigating the association between intestinal microbiota composition and humoral and cellular vaccine responses. In total, 30 publications (26 studies, 14 in infants, 12 in adults), were included. Of these, 26 publications found an association between intestinal microbiota composition and vaccine responses. A beneficial effect of Actynomycetota (particularly Bifidobacterium) and a detrimental effect of Pseudomonadota (particularly Gammaproteobacteria) were observed across studies. Study designs were highly heterogenous, with variation in vaccine type, outcome measure, timing of stool analysis and analysis methods. Overall, studies support the concept that the composition of the intestinal microbiota influences vaccine responses. Further adequately powered studies are needed to confirm this association and inform potential microbiota-targeted interventions to optimise vaccine responses.
Human driven climate change increased the likelihood of the 2023 record area burned in Canada
Authors: Kirchmeier-Young Megan C. , Malinina Elizaveta , Barber Quinn E. , Garcia Perdomo Karen , Curasi Salvatore R. , Liang Yongxiao , Jain Piyush , Gillett Nathan P. , Parisien Marc-André , Cannon Alex J. , Lima Aranildo R. , Arora Vivek K. , Boulanger Yan , Melton Joe R. , Van Vliet Laura , Zhang Xuebin 
Published: December 2024

AbstractIn 2023, wildfires burned 15 million hectares in Canada, more than doubling the previous record. These wildfires caused a record number of evacuations, unprecedented air quality impacts across Canada and the northeastern United States, and substantial strain on fire management resources. Using climate models, we show that human-induced climate change significantly increased the likelihood of area burned at least as large as in 2023 across most of Canada, with more than two-fold increases in the east and southwest. The long fire season was more than five times as likely and the large areas across Canada experiencing synchronous extreme fire weather were also much more likely due to human influence on the climate. Simulated emissions from the 2023 wildfire season were eight times their 1985-2022 mean. With continued warming, the likelihood of extreme fire seasons is projected to increase further in the future, driving additional impacts on health, society, and ecosystems.
Low-temperature fabrication of amorphous carbon films as a universal template for remote epitaxy
Authors: Henksmeier T. , Mahler P. , Wolff A. , Deutsch D. , Voigt M. , Ruhm L. , Sanchez A. M. , As D. J. , Grundmeier G. , Reuter D. 
Published: December 2024

AbstractRecently, remote epitaxy has been explored for the fabrication of freestanding semiconductor membranes and substrate re-use. For remote epitaxy a thin 2D material layer is either manually transferred to a substrate or grown directly on a substrate at high temperature, thus limiting the process scalability or the choice of substrates. Here, we report on the low-temperature deposition (300 °C) of ultrathin sp2-hybridized 2D amorphous carbon layers with roughness ≤0.3 nm on III-V semiconductor substrates by plasma-enhanced chemical vapor deposition as a universal template for remote epitaxy. We present growth and detailed characterization of 2D amorphous carbon layers on various host substrates and their subsequent remote epitaxial overgrowth by solid-source molecular beam epitaxy. We observe that a low-temperature nucleation step is favorable for nucleation of III-V material growth on amorphous carbon coated substrates. Under optimized preparation conditions, we obtain high-quality, single-crystalline GaAs, cubic-AlN, cubic-GaN and $${{\rm{I}}}{{{\rm{n}}}}_{{{\rm{x}}}}{{{\rm{Ga}}}}_{1-{{\rm{x}}}}{{\rm{As}}}$$
I

n

x

Ga

1
−
x

As
layers on GaAs, 3C-SiC and InP carbon-coated (001)-oriented substrates. Our results demonstrate a universal template fabrication process for remote epitaxy.
Coexistence of SMA Type I with Citrate Transporter Deficiency Disorder: A Case Report
Authors: Tawari Asmaa Al , Pavlovic Milen , Heberle Lada Cindro , Bastaki Laila 
Published: December 2024

AbstractThe coexistence of spinal muscular atrophy (SMA) with other diseases has been rarely described. We report a unique case with dual pathogenic gene mutations: survival motor neuron 1 (SMN1) gene causing SMA and SLC13A5 gene causing citrate transporter deficiency-induced epilepsy (early infantile epileptic encephalopathy 25, OMIM 615905).A girl presented with recurrent focal seizures with semiology of eyelid blinking, deviation of eyes, and facial twitches, which started on the second day of her life. Interictal EEG showed bilateral multifocal and generalized discharges. Brain MRI revealed delayed myelination and generalized volume loss. PET scan showed diffuse cortical hypometabolism. She had refractory seizures, including two episodes of status epilepticus while being treated with various antiseizure medications. Genetic analysis revealed a homozygous deletion of the SLC13A5 gene at 17p13.1. At 1 year of age, progressive hypotonia, initially ascribed to seizures and antiseizure medications, the appearance of tongue fasciculations and the need for respiratory support, prompted testing for SMA. Mutation at the SMN1 gene locus (5q11.2-13.2) was found and an SMA type I diagnosis was established. EMG/nerve conduction velocity revealed a motor neuron disorder. She was started on nusinersen at the age of 2.5 years once it became available. She was tracheostomized for bilevel positive airway pressure support. At the age of 4.5 years, she had a cardiac arrest and passed away.This is a case report of coexistent mutations in the SMN1 and SCL13A5 genes with overlapping and diagnostically confusing features of progressive hypotonia. The constellation of these separate genetic entities constitutes a clinical phenotype that has not been reported previously.
Generation of magnetic fields in pulsars
Authors: Sedrakyan D. M. 
Published: December 2024

We consider a new mechanism of generation of magnetic fields in neutron stars, based on the superfluidity and superconductivity of neutrons and protons in the “pre” phase of a neutron star.
The currents of neutron “drag” of protons results in the formation of a dense network of proton vortices around a neutron vortex. The size of the region in which the magnetic field is not zero depends on the coefficient of the “drag” of superconducting protons.
A microscopic theory that has been developed for the interaction of the neutron and proton condensates has yielded analytic expressions for the “drag” coefficient at temperatures near the superconducting transition point of protons.
As is seen from the formula derived as well as from estimates made by other authors, the “drag” coefficient should be of the order of unity as T→0. It has been shown that (average) magnetic fields of the order of 10 G can be generated in neutron stars. This field is concentrated in proton vortices which occupy only 10% of the volume of the neutron star.
Topological order of atomically rough boundaries of crystals
Authors: Marchenko V. I. 
Published: December 2024

It is shown that three types of atomically rough crystal boundaries exist. One, two, or even three rough states, between which specific phase transitions occur, can exist on a face, depending on its symmetry.
An analogy has been noted between the transition from an atomically smooth to an atomically rough state and the transition from a commensurate to an incommensurate state. An estimate of the temperatures of these phase transitions is given.
Hydrodynamics equations for a rotating crystal
Authors: Vardanyan G. A. , Papoyan K. V. , Sedrakyan D. M. 
Published: December 2024

In order to explain the physical picture of the rotation of a superfluid crystal we consider the case in which the crystal contains linear defects of the type of vortex filaments; as the condensate revolves around these defects the phase of its wave function changes by 2π.
Vortex filaments are responsible for motion throughout the crystal with the curl of the velocity equal to twice the frequency of rotation of the crystal. As a consequence, forces which are associated with the curl of the superfluid velocity and angular velocity of the crystal appear in the equations of motion.
The stress tensor of the crystal in this case contains a part which is due to the vortices and, therefore, the thermodynamic functions undergo substantial changes.
The correction to the momentum flux tensor consists of two parts, as in the case of a superfluid liquid: the renormalization of the pressure and the tension of the filaments. In the hydrodynamics equations the velocity of the vortex filaments is taken into account along with the velocity of the lattice sites.
Investigation of compressive strength of 3D-printed PLA/continuous glass fibers composites manufactured by simultaneous impregnation extrusion-based additive manufacturing
Authors: Safi Jahanshahi Amin , Akhoundi Behnam , Quagliato Luca 
Published: December 2024

Abstract
The enhancement of stiffness and strength in additively manufactured components has garnered significant attention from scientists and engineers in recent years. This study explores the improvement of compressive strength in polylactic acid (PLA) composites reinforced with continuous glass fibers (CGFs) using a simultaneous impregnation extrusion-based additive manufacturing process. In this method, continuous fibers are introduced into the molten polymer through a side nozzle, coated with the polymer, and subsequently deposited onto the substrate or previously deposited layers. The primary advantage of this technique lies in its elimination of the need for pre-impregnated fibers, enabling the use of various continuous fiber types as reinforcing phases and different thermoplastics as matrices. To evaluate the impact of fiber orientation, fibers were aligned both parallel and perpendicular to the load direction, allowing an analysis of tensile lateral strain during compression. Compression test results revealed that neat PLA exhibited compressive strengths of 84.6 MPa and 72.3 MPa for parallel and perpendicular raster orientations, respectively. For the composite specimens, parallel fiber alignment resulted in delamination between the PLA matrix and fibers, with a compressive strength of 40.7 ± 1.2 MPa. Conversely, perpendicular fiber alignment increased compressive strength to 93 ± 1.1 MPa. The main innovation of this research is enhancing the compressive strength of composite samples by positioning continuous fibers perpendicular to the load direction within the samples. This arrangement induces transverse strain when the compressive force is applied, resulting in tensile stress being exerted on the continuous fibers, which in turn contributes to an increase in the compressive strength of the composite samples. Failure in these specimens occurred in regions where tensile strain direction changed, particularly at the corners of rounded-square cross-sections. This study demonstrates that aligning CGFs perpendicular to the loading direction enhances compressive strength by approximately 10.5%, introducing a bilinear elastic behavior and a more brittle-like fracture. The findings provide valuable insights for improving the crashworthiness and energy-absorbing capabilities of components in the automotive industry.
An insulating composite material defects detection CNN model using knowledge-based 2D structured ultrasonic signals
Authors: Liu Xiaojian , Li Zhifeng , Song Shaoheng , Li Hang , Suo Haodong , Liu Weihua , Liu Dongliang , Song Yaqin 
Published: December 2024

Abstract
Defects detection of insulators is crucial for the safe operation of power grid. A strategy of domain knowledge-assisted convolutional neural network is implemented for evaluating various depths and sizes of internal defects in insulating composite materials. A novel periodic-based 2D structuring method for ultrasonic signals is used to assist the CNN feature extraction process, leveraging the invariance of defect types with respect to the ultrasound sampling window and real background noise levels for data augmentation to enhance signal fidelity. Two supervised learning-based CNN models are trained to demonstrate the effectiveness of the proposed method. It is observed that the periodic-based 2D representation of ultrasonic signals facilitated superior performance of the 2DCNN compared to the 1DCNN using one-dimensional signals. In our strategy, the 2D ultrasonic signal can be interpreted as a feature map depicting the dependencies among different reflected echoes, as well as the intra- and inter-periodic variations of individual echoes. This domain-knowledge-compliant representation enhances the interpretability of the convolutional neural network. The results show that the trained 2DCNN achieved a defect recognition accuracy of 98.3% on unseen test sets and provided a relatively conservative accuracy estimate of 90% for defect-free samples, fully meeting the real industrial detection requirements to avoid misjudgment and missed judgment. Utilizing domain knowledge to assist neural networks effectively improves the quality of models required for industrial inspection.
Machine learning configuration-dependent friction tensors in Langevin heatbaths
Authors: Sachs Matthias , Stark Wojciech G , Maurer Reinhard J , Ortner Christoph 
Published: December 2024

Abstract
Dynamics of coarse-grained particle systems derived via the Mori–Zwanzig projection formalism commonly take the form of a (generalized) Langevin equation with configuration-dependent friction tensor and diffusion coefficient matrix. In this article, we introduce a class of equivariant representations of tensor-valued functions based on the Atomic Cluster Expansion framework that allows for efficient learning of such configuration-dependent friction tensors from data. Besides satisfying the correct equivariance properties with respect to the Euclidean group E(3), the resulting heat bath models satisfy a fluctuation-dissipation relation. We demonstrate the capabilities of the model approach by fitting a model of configuration-dependent tensorial electronic friction calculated from first principles that arises during reactive molecular dynamics at metal surfaces.
Multimorbidity patterns, sociodemographic characteristics, and mortality: Data science insights from low-resource settings
Authors: Bazo-Alvarez Juan Carlos , Del Castillo Darwin , Piza Luis , Bernabé-Ortiz Antonio , Carrillo-Larco Rodrigo M , Smeeth Liam , Gilman Robert H , Checkley William , Miranda J Jaime 
Published: December 2024

Abstract
Multimorbidity data is typically analysed by tallying disease counts, which overlooks nuanced relationships among conditions. We identified clusters of multimorbidity and subpopulations with varying risks and examined their association with all-cause mortality using a data-driven approach. We analysed 8-year follow-up data of people ≥35 years who were part of the CRONICAS Cohort Study, a multisite cohort from Peru. First, we used Partitioning Around Medoids and multidimensional scaling to identify multimorbidity clusters. We then estimated the association between multimorbidity clusters and all-cause mortality. Second, we identified subpopulations using finite mixture modelling. Our analysis revealed three clusters of chronic conditions: respiratory (cluster 1: bronchitis, COPD and asthma), lifestyle, hypertension, depression and diabetes (cluster 2), and circulatory (cluster 3: heart disease, stroke and peripheral artery disease). While only the cluster comprising circulatory diseases showed a significant association with all-cause mortality in the overall population, we identified two latent subpopulations (named I and II) exhibiting differential mortality risks associated with specific multimorbidity clusters. These findings underscore the importance of considering multimorbidity clusters and sociodemographic characteristics in understanding mortality risks. They also highlight the need for tailored interventions to address the unique needs of different subpopulations living with multimorbidity to reduce mortality risks effectively.
SARS-CoV-2 infection and risk of subsequent demyelinating diseases: national register–based cohort study
Authors: Montgomery Scott , Vingeliene Snieguole , Li Huiqi , Backman Helena , Udumyan Ruzan , Jendeberg Johan , Rasmussen Gunlög , Sundqvist Martin , Fall Katja , Hiyoshi Ayako , Nyberg Fredrik 
Published: December 2024

Abstract
Demyelinating diseases including multiple sclerosis are associated with prior infectious exposures, so we assessed whether SARS-CoV-2 infection is associated with subsequent diagnoses of non-multiple sclerosis demyelinating diseases and multiple sclerosis. All residents of Sweden aged 3–100 years were followed between 1 January 2020 and 30 November 2022, excluding those with demyelinating disease prior to 2020, comprising 9 959 818 individuals divided into uninfected and those who were infected were categorized into those with and without hospital admission for the infection as a marker of infection severity. Cox regression assessed the risk of two separate outcomes: hospital diagnosed non-multiple sclerosis demyelinating diseases of the CNS and multiple sclerosis. The exposures were modelled as time-varying covariates (uninfected, infection without hospital admission and infected with hospital admission). Hospital admission for COVID-19 was associated with raised risk of subsequent non-multiple sclerosis demyelinating disease, but only 12 individuals had this outcome among the exposed, and of those, 7 has an unspecified demyelinating disease diagnosis. Rates per 100 000 person-years (and 95% confidence intervals) were 3.8 (3.6–4.1) among those without a COVID-19 diagnosis and 9.0 (5.1–15.9) among those admitted to hospital for COVID-19, with an adjusted hazard ratio and (and 95% confidence interval) of 2.35 (1.32–4.18, P = 0.004). Equivalent associations with multiple sclerosis (28 individuals had this outcome among the exposed) were rates of 9.5 (9.1–9.9) and 21.0 (14.5–30.5) and an adjusted hazard ratio of 2.48 (1.70–3.61, P &lt; 0.001). Only a small number of non-multiple sclerosis demyelinating disease diagnoses were associated with hospital admission for COVID-19, and while the number with multiple sclerosis was somewhat higher, longer duration of follow-up will assist in identifying whether the associations are causal or due to shared susceptibility or surveillance bias, as these diseases can have long asymptomatic and prodromal phases.