bluuebunny/crossref_metadata_2025_split huggingface dataset:
Energy spectra of elemental groups of cosmic rays with the KASCADE experiment data and machine learning
Authors: Kuznetsov M.Yu. , Petrov N.A. , Plokhikh I.A. , Sotnikov V.V. 
Published: May 2024

Abstract
We report the reconstruction of the mass component spectra of cosmic rays (protons,
helium, carbon, silicon and iron) and their mean mass composition, at energies from 1.4 to 100 PeV. The results are derived from the archival data of the extensive air shower experiment
KASCADE. We use a novel machine learning technique developed specifically for this
reconstruction, and post-LHC hadronic interaction models: QGSJet-II.04, EPOS-LHC and
Sibyll 2.3c. We have found an excess of the proton component and a deficit of intermediate
and heavy nuclei components compared to the original KASCADE results. The spectra of protons and
helium show a knee-like behavior at ∼ 4.4 PeV and ∼ 11 PeV, with significances
5.2σ and 3.9σ, respectively. The spectrum of the iron component has a
hint (2.4σ) of a hardening at ∼ 4.5 PeV, which can be interpreted as a counterpart of
a hardening in the proton spectrum at 166 TeV, recently reported by the GRAPES-3
experiment. The systematic uncertainties of our analysis were found to be smaller than those of
the original KASCADE, as well as those of IceTop and TALE experiments, over the most part of the
energy range studied. We also estimated separately the uncertainty related to the difference
between the three mentioned hadronic interaction models. We also compute a mean logarithm mass of
CR flux as a function of energy. It is in agreement with the results of IceTop, TALE and LHAASO
within the uncertainties.
Parity-violating scalar trispectrum from a rolling axion during inflation
Authors: Fujita Tomohiro , Murata Tomoaki , Obata Ippei , Shiraishi Maresuke 
Published: May 2024

Abstract
We study a mechanism of generating the trispectrum (4-point correlation) of curvature
perturbation through the dynamics of a spectator axion field and U(1) gauge field during
inflation. Owing to the Chern-Simons coupling, only one helicity mode of gauge field experiences
a tachyonic instability and sources scalar perturbations. Sourced curvature perturbation exhibits
parity-violating nature which can be tested through its trispectrum. We numerically compute
parity-even and parity-odd component of the sourced trispectrum. It is found that the ratio of
parity-odd to parity-even mode can reach 𝒪(10%) in an exact equilateral momentum
configuration. We also investigate a quasi-equilateral shape where only one of the momenta is
slightly longer than the other three, and find that the parity-odd mode can reach, and more
interestingly, surpass the parity-even one. This may help us to interpret a large parity-odd
trispectrum signal extracted from BOSS galaxy-clustering data.
Strip method to construct a two-dimensional quasilattice with eight-fold symmetry
Authors: Huang 黄 Weishen 伟深 , Fu 傅 Xiujun 秀军 
Published: May 2024

Abstract
Based on the substitution rule and symmetry, we propose a method to generate an octagonal quasilattice consisting of square and rhombus tiles. Local configurations and Ammann lines are used to guide the growth of the tiles in a quasiperiodic order. The structure obtained is a perfect eight-fold symmetric quasilattice, which is confirmed by the radial distribution function and the diffraction pattern.
Microstripe pattern substrate consisting of alternating planar and nanoprotrusive regions improved hiPSC-derived cardiomyocytes’ unidirectional alignment and functional properties
Authors: Saotome Hideo , Yatsuka Yukiko , Minowa Osamu , Shinotsuka Kei , Tsuchida Katsuharu , Hirose Hitomi , Dai Kotaro , Tokuno Hisako , Hayakawa Tomohiro , Hiranuma Hidenori , Hasegawa Akari , Nakatomi Ichiro , Okazaki Atsuko , Okazaki Yasushi 
Published: May 2024

Abstract
The alignment of each cell in human myocardium is considered critical for the efficient movement of cardiac tissue. We investigated 96-well microstripe-patterned plates to align human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs), which resemble fetal myocardium. The aligned CMs (ACMs) cultured on the microstripe-patterned plates exhibited pathology, motor function, gene expression, and drug response that more closely resembled those of adult cells than did unaligned CMs cultured on a flat plate (FCMs). We used these ACMs to evaluate drug side effects and efficacy, and to determine whether these were similar to adult-like responses. When CMs from patients with hypertrophic cardiomyopathy (HCMs) were seeded and cultured on the microstripe-patterned plates or layered on top of the ACMs, both sets of HCMs showed increased heart rate and synchronized contractions, indicating improved cardiac function. It is suggested that the ACMs could be used for drug screening as cells representative of adult-like CMs and be transplanted in the form of a cell sheet for regenerative treatment of heart failure.
Genipin crosslinked quaternary ammonium chitosan hydrogels for wound dressings
Authors: Wang Ling , Ding Xiaoyue , Li Jingyu , Li Man , Ding Peng , Guo Wei , Wu Qiaoyun , Sun Yanfang , Jiang Guohua , Okoro Oseweuba Valentine , Mirzaei Mahta , Shavandi Amin , Fan Lihong , Nie Lei 
Published: May 2024

Abstract
Bacterial infection can lead to various complications, such as inflammations on surrounding tissues, which can prolong wound healing and thus represent a significant clinical and public healthcare problem. Herein, a report on the fabrication of a novel genipin/quaternized chitosan (CS) hydrogel for wound dressing is presented. The hydrogel was prepared by mixing quaternized CS and genipin under 35 °C bath. The hydrogels showed porous structure (250–500 μm) and mechanical properties (3000–6000 Pa). In addition, the hydrogels displayed self-healing ability and adhesion performance on different substrates. Genipin crosslinked quaternized CS hydrogels showed antibacterial activities against E. coli and S. aureus. The CCK-8 and fluorescent images confirmed the cytocompatibility of hydrogels by seeding with NIH-3T3 cells. The present study showed that the prepared hydrogel has the potential to be used as wound dressing.
Condition numbers for real eigenvalues of real elliptic ensemble: weak non-normality at the edge
Authors: Tarnowski Wojciech 
Published: May 2024

Abstract
Sensitivity of an eigenvalue λ

i
to the perturbation of matrix elements is controlled by the eigenvalue condition number defined as

κ
i

=

⟨

L
i

|

L
i

⟩
⟨

R
i

|

R
i

⟩

, where

⟨

L
i

|

and

|

R
i

⟩

are left and right eigenvectors to the eigenvalue λ

i
. In random matrix theory the squared eigenvalue condition number is also known as the eigenvector self-overlap. In this work we calculate the asymptotics of the joint probability density function of the real eigenvalue and the square of the corresponding eigenvalue condition number for the real elliptic ensemble in the double scaling regime of almost Hermiticity and close to the edge of the spectrum. As a byproduct, we also calculate the one-parameter deformation of the Scorer’s function.
Electrical, optical and nonlinear optical process in spray pyrolyzed Zn:CuO nanostructures for optoelectronic device applications
Authors: Corda Neil , Thundiyil Ramseena , Ani Aninamol , Anusha  , P Poornesh , Rao Ashok , Manjunatha KB 
Published: May 2024

Abstract
Nanostructured pure and Zn doped CuO thin films were deposited on a glass substrate at 400 °C using the chemical spray pyrolysis method. The fabricated thin films were characterized to study the compositional, structural, morphological, optical and electrical properties. X-ray diffraction spectra show the polycrystalline nature of the sample and confirm the monoclinic phase of copper oxide. Raman analysis further confirms the absence of cuprous oxide phases and impurities. High absorbance in the visible region was observed for the films with bandgap values ranging from 1.7–2.0 eV. A near-band edge emission peak in the red region is recorded in the photoluminescence spectra. Uniformly distributed nanoparticles are observed in SEM images. Hall effect measurements indicate p-type conductivity and 5% Zn doped copper oxide showed the highest conductivity and carrier concentration. The non-linear absorption coefficient (β
eff) of the samples was obtained with the help of z-scan method with a Helium-Neon laser under the CW regime. Zn doping results in an increase in nonlinear absorption, supporting the use of Zn:CuO for optoelectronic devices.
Navigating the frontiers of graphene quality control to enable product optimisation and market confidence
Authors: Marchesini Sofia , Paton Keith R , Pollard Andrew J 
Published: May 2024

Abstract
With graphene and related two-dimensional (2D) materials now enhancing products used in everyday life, the scale of industrial production of many different types of 2D nanomaterials requires quality control (QC) processes that can be performed rapidly, non-destructively, in-line and in a cost-effective manner. These materials must be repeatably produced with targeted material properties, to reduce the costs associated with nonconformity of products, and so multiple QC methods that can monitor different material properties are required. Herein, we describe different measurands and associated techniques that either have the potential to be used for QC, or are already being used in this way, whether that off-line, at-line or in-line. The advantages and disadvantages of different techniques are detailed, as well as possible solutions that can ensure confidence in these methods and lead to measurement traceability in this growing industry.
In-sensor neuromorphic computing using perovskites and transition metal dichalcogenides
Authors: Li Shen-Yi , Li Ji-Tuo , Zhou Kui , Yan Yan , Ding Guanglong , Han Su-Ting , Zhou Ye 
Published: May 2024

Abstract
With the advancements in Web of Things, Artificial Intelligence, and other emerging technologies, there is an increasing demand for artificial visual systems to perceive and learn about external environments. However, traditional sensing and computing systems are limited by the physical separation of sense, processing, and memory units that results in the challenges such as high energy consumption, large additional hardware costs, and long latency time. Integrating neuromorphic computing functions into the sensing unit is an effective way to overcome these challenges. Therefore, it is extremely important to design neuromorphic devices with sensing ability and the properties of low power consumption and high switching speed for exploring in-sensor computing devices and systems. In this review, we provide an elementary introduction to the structures and properties of two common optoelectronic materials, perovskites and transition metal dichalcogenides (TMDs). Subsequently, we discuss the fundamental concepts of neuromorphic devices, including device structures and working mechanisms. Furthermore, we summarize and extensively discuss the applications of perovskites and TMDs in in-sensor computing. Finally, we propose potential strategies to address challenges and offer a brief outlook on the application of optoelectronic materials in term of in-sensor computing.
Tackling the small data problem in medical image classification with artificial intelligence: a systematic review
Authors: Piffer Stefano , Ubaldi Leonardo , Tangaro Sabina , Retico Alessandra , Talamonti Cinzia 
Published: May 2024

Abstract
Though medical imaging has seen a growing interest in AI research, training models require a large amount of data. In this domain, there are limited sets of data available as collecting new data is either not feasible or requires burdensome resources. Researchers are facing with the problem of small datasets and have to apply tricks to fight overfitting. 147 peer-reviewed articles were retrieved from PubMed, published in English, up until 31 July 2022 and articles were assessed by two independent reviewers. We followed the Preferred Reporting Items for Systematic reviews and Meta-Analyse (PRISMA) guidelines for the paper selection and 77 studies were regarded as eligible for the scope of this review. Adherence to reporting standards was assessed by using TRIPOD statement (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). To solve the small data issue transfer learning technique, basic data augmentation and generative adversarial network were applied in 75%, 69% and 14% of cases, respectively. More than 60% of the authors performed a binary classification given the data scarcity and the difficulty of the tasks. Concerning generalizability, only four studies explicitly stated an external validation of the developed model was carried out. Full access to all datasets and code was severely limited (unavailable in more than 80% of studies). Adherence to reporting standards was suboptimal (<50% adherence for 13 of 37 TRIPOD items). The goal of this review is to provide a comprehensive survey of recent advancements in dealing with small medical images samples size. Transparency and improve quality in publications as well as follow existing reporting standards are also supported.
Momentum accelerates evolutionary dynamics
Authors: Harper Marc , Safyan Joshua 
Published: May 2024

Abstract
We combine momentum from machine learning with evolutionary dynamics, where momentum can be viewed as a simple mechanism of intergenerational memory similar to epigenetic mechanisms. Using information divergences as Lyapunov functions, we show that momentum accelerates the convergence of evolutionary dynamics including the continuous and discrete replicator equations and Euclidean gradient descent on populations. When evolutionarily stable states are present, these methods prove convergence for small learning rates or small momentum, and yield an analytic determination of the relative decrease in time to converge that agrees well with computations. The main results apply even when the evolutionary dynamic is not a gradient flow. We also show that momentum can alter the convergence properties of these dynamics, for example by breaking the cycling associated to the rock–paper–scissors landscape, leading to either convergence to the ordinarily non-absorbing equilibrium, or divergence, depending on the value and mechanism of momentum.
Multifractal analysis of the perimeters of glaciers in the Svalbard Archipelago
Authors: Carpineti Marina , Lupo Sepe Valerio , Senese Antonella , Traversa Giacomo , Diolaiuti Guglielmina A , Vailati Alberto 
Published: May 2024

Abstract
The investigation of the evolution of glaciers largely relies on the characterisation of extensive quantities like their mass, area, and perimeter. In this work we use fractal and multifractal analysis to investigate the non-extensive structural properties of the perimeters of glaciers in the Svalbard Archipelago. We show that the perimeters of the glaciers exhibit a fractal structure with a fractal dimension

D
f

≃
1.25

, independently from the area of the glaciers. The investigation of the multifractal properties of the perimeters shows that small glaciers exhibit a more pronounced multifractal structure, as witnessed by the larger range of generalized dimensions Dq
needed to characterise them. The range ΔD

q
of generalised dimensions required to characterise the multifractal perimeter of a glacier exhibits a power-law dependence with exponent −1.2 from the area, and represents a non-extensive parameter able to grab effectively the dependence of the multifractal structure of the perimeters on the size of glaciers. The comparison with similar results obtained in a previous study performed on glaciers in the Lombardy region of the Italian Alps confirms the robustness of the analysis performed, which does not appear to be affected by the morphology of the substrate or by climate conditions.
The twin peaks of learning neural networks
Authors: Demyanenko Elizaveta , Feinauer Christoph , Malatesta Enrico M , Saglietti Luca 
Published: May 2024

Abstract
Recent works demonstrated the existence of a double-descent phenomenon for the generalization error of neural networks, where highly overparameterized models escape overfitting and achieve good test performance, at odds with the standard bias-variance trade-off described by statistical learning theory. In the present work, we explore a link between this phenomenon and the increase of complexity and sensitivity of the function represented by neural networks. In particular, we study the Boolean mean dimension (BMD), a metric developed in the context of Boolean function analysis. Focusing on a simple teacher-student setting for the random feature model, we derive a theoretical analysis based on the replica method that yields an interpretable expression for the BMD, in the high dimensional regime where the number of data points, the number of features, and the input size grow to infinity. We find that, as the degree of overparameterization of the network is increased, the BMD reaches an evident peak at the interpolation threshold, in correspondence with the generalization error peak, and then slowly approaches a low asymptotic value. The same phenomenology is then traced in numerical experiments with different model classes and training setups. Moreover, we find empirically that adversarially initialized models tend to show higher BMD values, and that models that are more robust to adversarial attacks exhibit a lower BMD.
Profiles and the impact of affective temperaments on alcohol use disorder: a cross-sectional study
Authors: Kurihara Kazuhiro , Koda Munenaga , Zamami Yu , Shinzato Hotaka , Takaesu Yoshikazu , Kondo Tsuyoshi 
Published: May 2024

Abstract

Aims
This study aimed to explore the profiles and impact of affective temperaments, together with social and clinical backgrounds, including affective symptoms, in patients with alcohol use disorder (AUD).

Methods
This study included 314 low-risk drinkers and 257 patients with AUD. To assess affective temperament, we used the short version of the temperament evaluation of Memphis, Pisa, Paris, and San Diego. To evaluate depressive and mixed symptoms, the quick inventory of depressive symptomatology self-report Japanese version and 12-item questionnaire for the quantitative assessment of the depressive mixed state were used. We compared the profiles of affective temperaments as well as social and clinical backgrounds, including affective symptoms, between the two groups and further performed logistic regression analyses to explore the factors contributing to AUD.

Results
Our analysis showed higher cyclothymic, hyperthymic, and irritable temperament scores and lower depressive temperament scores in patients with AUD than that in nonclinical drinkers. Regarding other social and clinical backgrounds, patients with AUD were less educated and employed and more experienced depressive and mixed symptoms. Logistic regression analysis identified hyperthymic temperament as a positive contributor and depressive temperament as a negative contributor to AUD.

Conclusions
Our findings indicated potential bipolarity in patients with AUD, as manifested by a more hyperthymic temperament in contrast to less depressive temperament. Despite their self-perceived adaptive temperament profiles, patients showed poorer social outcomes and more affective symptoms. This gap may be partly explained by a lack of insight unique to AUD psychology, which potentially disturbs problem recognition.
CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data
Authors: Thuilliez Corentin , Moquin-Beaudry Gaël , Khneisser Pierre , Marques Da Costa Maria Eugenia , Karkar Slim , Boudhouche Hanane , Drubay Damien , Audinot Baptiste , Geoerger Birgit , Scoazec Jean-Yves , Gaspar Nathalie , Marchais Antonin 
Published: May 2024

Abstract

Motivation
Spatial transcriptomics enables the analysis of cell crosstalk in healthy and diseased organs by capturing the transcriptomic profiles of millions of cells within their spatial contexts. However, spatial transcriptomics approaches also raise new computational challenges for the multidimensional data analysis associated with spatial coordinates.

Results
In this context, we introduce a novel analytical framework called CellsFromSpace based on independent component analysis (ICA), which allows users to analyze various commercially available technologies without relying on a single-cell reference dataset. The ICA approach deployed in CellsFromSpace decomposes spatial transcriptomics data into interpretable components associated with distinct cell types or activities. ICA also enables noise or artifact reduction and subset analysis of cell types of interest through component selection. We demonstrate the flexibility and performance of CellsFromSpace using real-world samples to demonstrate ICA’s ability to successfully identify spatially distributed cells as well as rare diffuse cells, and quantitatively deconvolute datasets from the Visium, Slide-seq, MERSCOPE, and CosMX technologies. Comparative analysis with a current alternative reference-free deconvolution tool also highlights CellsFromSpace’s speed, scalability and accuracy in processing complex, even multisample datasets. CellsFromSpace also offers a user-friendly graphical interface enabling non-bioinformaticians to annotate and interpret components based on spatial distribution and contributor genes, and perform full downstream analysis.

Availability and implementation
CellsFromSpace (CFS) is distributed as an R package available from github at https://github.com/gustaveroussy/CFS along with tutorials, examples, and detailed documentation.
Pathologic RFC1 repeat expansions do not contribute to the development of inflammatory neuropathies
Authors: Nagy Sara , Carr Aisling , Mroczek Magdalena , Rinaldi Simon , Curro Riccardo , Dominik Natalia , Japzon Nicole , Magrinelli Francesca , Lunn Michael P , Manji Hadi , Reilly Mary M , Cortese Andrea , Houlden Henry 
Published: May 2024

Abstract
Biallelic expansions of the AAGGG repeat in the replication factor C subunit 1 (RFC1) have recently been described to be responsible for cerebellar ataxia, peripheral neuropathy and vestibular areflexia syndrome. This genetic alteration has also allowed genetic classification in up to one-third of cases with idiopathic sensory neuropathy. Here, we screened a well-characterized cohort of inflammatory neuropathy patients for RFC1 repeat expansions to explore whether RFC1 was increased from background rates and possibly involved in the pathogenesis of inflammatory neuropathy. A total of 259 individuals with inflammatory neuropathy and 243 healthy controls were screened for the AAGGG repeat expansion using short-range flanking PCR and repeat-primed PCR. Cases without amplifiable PCR product on flanking PCR and positive repeat-primed PCR were also tested for the mostly non-pathogenic expansions of the AAAGG and AAAAG repeat units. None of the patients showed biallelic AAGGG expansion of RFC1, and their carrier frequency for AAGGG was comparable with controls [n = 27 (5.2%) and n = 23 (4.7%), respectively; P &gt; 0.5]. Data suggest that the pathologic expansions of AAGGG repeats do not contribute to the development of inflammatory neuropathies nor lead to misdiagnosed cases. Accordingly, routine genetic screening for RFC1 repeat expansion is not indicated in this patient population.