bluuebunny/crossref_metadata_2025_split huggingface dataset:
Daily glucose variability is associated with intrahepatic fat content, β cell sensitivity, and biomarkers of glycolysis in youth with obesity
Authors: Barbieri Emiliano , Bonet Jacopo , Fox Delaney , Nelson Rafaela , Nelson Michael B. , Nelson Loretta , Fernandez Cristina , Van Name Michelle , Samuels Stephanie , Caprio Sonia , Sabati Mohammad , Galderisi Alfonso , Sherr Jennifer , Dalla Man Chiara , Santoro Nicola 
Published: December 2024

AbstractObjectivePediatric obesity is associated with insulin resistance, which, in turn, impacts glucose and lipid metabolism. This study sought to assess how glucose variability relates to intrahepatic fat content, β cell insulin sensitivity, and glycolysis in youth with obesity.MethodsA total of 27 youth with obesity (11 girls, BMI percentile, median [25th–75th percentiles]: 99.0 [97.9–99.0]) wore a continuous glucose monitoring device for 10 days and underwent a 3‐h oral glucose tolerance test. β cell function was assessed using the oral minimal model, and liver proton density fat fraction was measured by magnetic resonance imaging.ResultsAverage sensor‐derived glucose and glucose standard deviation (STDEV) and coefficient of variation (CV) were associated with liver proton density fat fraction (p = 0.0130, p = 0.0005, and p = 0.0028, respectively). First‐phase insulin secretion, basal insulin secretion, and insulin sensitivity were associated with STDEV (p = 0.0344, p = 0.0091, and p = 0.0031, respectively) and CV (p = 0.0128, p = 0.0012, and p = 0.0022, respectively). STDEV and CV were also associated with 2‐h glucose (p = 0.0067 and p = 0.0324, respectively) and plasma lactate (p = 0.0030 and p = 0.0123, respectively).ConclusionsDaily glucose variability is associated with the degree of intrahepatic fat content, postprandial glucose, and plasma lactate concentrations.
Physics‐Based Spiking Neural Network as a Surrogate Model for Viscoplastic Material Law in Impulsively Loaded Beams
Authors: Polydoras Vasileios , Tandale Saurabh , Stoffel Marcus 
Published: December 2024

ABSTRACTIn the present study, the nonlinear material law of an in‐house FEM solver is substituted by physics‐informed neural networks (PINNs) and by physics‐based spiking neural networks (SNNs) for predicting the dynamic response of beams under impact loading. In the first part of this study concerning PINNs, the physics are included in the loss function of a deep neural network, also called a second‐generation neural network. The main advantage of using PINNs compared to classical ANNs is that they are considered data‐efficient function approximators. In the second part of this study, leaky integrate and fire (LIF) layers are deployed instead of dense layers in the PINN architecture, leading to a physics‐based third‐generation SNN, which enhances the PINN architecture in terms of energy efficiency. Third‐generation SNNs are inspired by the human brain function, where the information is processed via spikes. The spikes introduce sparse behavior, leading to a more energy‐efficient and sustainable deep learning method when implemented in neuromorphic hardware. The PINNs and physics‐based SNNs are employed in the implicit integration scheme of the material law of the in‐house FEM solver at the Gaussian level, and results are compared with the in‐house FEM solution in two different initial boundary value (IBV) problems. This study aims to show that PINNs can predict nonlinear material behavior and that the use of a physics‐based loss function enables the utility of less data in the training of the neural networks. Moreover, we show that we can enhance PINNs regarding energy consumption by adding a LIF layer. Therefore, the energy consumption is compared when the physics‐based SNN is deployed on the Loihi neuromorphic chip and on the CPU.
Porous Scaffolds Made From Starch Nanoparticle‐Stabilized Medium Internal Phase Emulsion Polymerization: Effect of Pore Size and Polyaniline on Cell Growth
Authors: Kavousi Fatemeh , Akbari‐Birgani Shiva , Pour‐Esmaeil Sajad , Kazemi Sayed Habib , Nikfarjam Nasser 
Published: December 2024

ABSTRACTPolymeric three‐dimensional (3D) porous scaffolds were prepared through medium internal phase emulsion (MIPE) templating. Their potential applicability as substrates for culturing human breast cancer (MCF‐7) cells and human neuroblastoma (SH‐SY5Y) cells was investigated. The crosslinked starch nanoparticle‐stabilized oil‐in‐water MIPEs containing acrylamide/methylenebisacrylamide/poly(ethylene oxide) (PEO) in the continuous phase cured in 1 and 6 h to produce 3D porous scaffolds called, respectively, PolyMIPE‐SP and PolyMIPE‐SP after the removal of the internal oil phase. Field emission scanning electron microscopy (FE‐SEM) micrographs revealed uniform interconnected porous structures with average pore sizes of 46.74 and 7.13 μm for PolyMIPE‐LP and PolyMIPE‐SP, respectively. Cell viability and cell culture studies exhibited that the biocompatibility, proliferation, and growth of SH‐SY5Y and MCF‐7 cells on PolyMIPE‐LP were better than those on PolyMIPE‐SP due to the proper placement of cells in large pores. Then, deposited conductive polyaniline (PANI) nanoparticles on the pore surface of PolyMIPE‐LP induced a rough surface with a nanoprotrusion structure and balanced hydrophobicity/hydrophilicity, enhancing cell growth in the scaffold. The cyclic voltammograms revealed that the conductivity of PolyMIPE‐LP/PANI scaffolds depends directly on the swelling degree of the scaffold. Consequently, these findings make PolyMIPE‐LP/PANI a suitable bioactive substrate for electroactive cell studies, chemo‐photothermal therapy of cancer cells, and drug testing platforms.
Fabrication of microfibrillated cellulose reinforced polypropylene composites assisted by a synergistic strategy of pre‐quaternization and paper‐making process
Authors: Guo Kunwu , Yao Chenguang , Huang Zhen , Liu Hongzhi 
Published: December 2024

AbstractTo tackle the ease of aggregation issue of highly hydrophilic microfibrillated cellulose (MFC) in polypropylene (PP) that thus results in an undesired reinforcing effect, this work developed an effective and industrially feasible strategy combining pre‐quaternization of pulp fibers with paper‐making process to fabricate PP/MFC composite with enhanced performance. Effects of MFC consistency, maleic anhydride grafted polypropylene (MAPP) content, and plasma treatment of chopped PP fibers on the mechanical and thermal properties of resultant composites were systematically investigated. The surface‐quaternized MFC obtained by a low‐consistency refiner (L‐MFC) exhibited a higher aspect ratio and degree of fibrillation than the corresponding surface‐quaternized MFC obtained by a high‐consistency one (H‐MFC). It was found that there existed a synergistic effect between pre‐quaternization and the paper‐making process in promoting the dispersion of MFC in PP. As compared with L‐MFC, a higher reinforcing efficiency on PP was achieved for H‐MFC, which was because the former one was more prone to form the fibril aggregates in the PP matrix. Due to both the entangled network of MFC and its nucleation effect on PP, the heat deflection temperature (HDT) of resulting composites was largely increased up to 159.9°C, an increase of 68.7°C with respect to that of PP.Highlights
The H‐MFC yielded a superior reinforcement on PP than L‐MFC.
The optimum mechanical properties of PP/composites were achieved at 15% MAPP.
Interfacial bonding between PP and H‐MFC was enhanced by plasma treatment.
An increase in Tc of the PP matrix was noted for PP/MFC.
A maximum increase of 159.9°C in HDT was achieved for PP/MFC.
SG‐ML‐PLAP: A structure‐guided machine learning–based scoring function for protein–ligand binding affinity prediction
Authors: Pal Sapna , Pal Ankita , Mohanty Debasisa 
Published: December 2024

AbstractComputational methods to predict binding affinity of protein–ligand complex have been used extensively to design inhibitors for proteins selected as drug targets. In recent years machine learning (ML) is being increasingly used for design of drugs/inhibitors. However, ranking compounds as per their experimental binding affinity has remained a major challenge. Therefore, it is necessary to develop ML‐based scoring function (MLSF) for predicting the binding affinity of protein–ligand complexes. In this work, protein–ligand interaction features, namely, extended connectivity interaction fingerprints (ECIF), derived from the PDBbind dataset have been used to build ML models for binding affinity prediction. The benchmarking has been done on the Comparative Assessment of Scoring Functions (CASF) dataset and also by predicting the binding affinity of unseen protein–ligand complexes which have structural features different from those present in the training dataset. Furthermore, an improvement in the performance of MLSF on the redocked CASF complexes generated by AutoDock Vina software was seen when the training set consisting of crystal structures was supplemented with redocked protein–ligand complexes. The MLSF trained on crystal structures alone using a combination of ECIF and VINA features also predicted binding affinities of crystal as well as docked complexes with high accuracy. Overall, the MLSF developed in this work shows improved performance compared to conventional SFs and several other MLSFs. It will be a valuable resource for identifying novel inhibitors by structure‐based virtual screening protocols. The proposed MLSF SG‐ML‐PLAP (Structure‐Guided Machine‐Learning–based Protein‐Ligand Affinity Predictor) is freely accessible as a webserver, http://www.nii.ac.in/sg-ml-plap.html.
Targeting MarA N‐terminal domain dynamics to prevent DNA binding
Authors: Corbella Marina , Moreira Cátia , Bello‐Madruga Roberto , Torrent Burgas Marc , Kamerlin Shina C. L. , Blair Jessica M. A. , Sancho‐Vaello Enea 
Published: December 2024

AbstractEfflux is one of the mechanisms employed by Gram‐negative bacteria to become resistant to routinely used antibiotics. The inhibition of efflux by targeting their regulators is a promising strategy to re‐sensitize bacterial pathogens to antibiotics. AcrAB–TolC is the main resistance‐nodulation‐division efflux pump in Enterobacteriaceae. MarA is an AraC/XylS family global regulator that regulates more than 40 genes related to the antimicrobial resistance phenotype, including acrAB. The aim of this work was to understand the role of the N‐terminal helix of MarA in the mechanism of DNA binding. An N‐terminal deletion of MarA showed that the N‐terminal helix is critical for recognition of the functional marboxes. By engineering two double cysteine variants of MarA that form a disulfide bond between the N‐terminal helix and the hydrophobic core of one of the helices in direct DNA contact, and combining in vitro electrophoretic mobility assays, in vivo measurements of acrAB transcription using a GFP reporter system, and molecular dynamic simulations, it was shown that the immobilization of the N‐terminal helix of MarA prevents binding to DNA. This inhibited conformation seems to be universal for the monomeric members of the AraC/XylS family, as suggested by additional molecular dynamics simulations of the two‐domain protein Rob. These results point to the N‐terminal helix of the AraC/XylS family monomeric regulators as a promising target for the development of inhibitors.
Fungal endophytes enhanced insect resistance by improving the defenses of Achnatherum sibiricum before locust feeding
Authors: Qin Tianzi , Shi Xinjian , Yin Jiaqi , Qu Yaobing , Deng Yongkang , Wei Xianqin , Zhao Nianxi , Gao Yubao , Mace Wade J. , Ren Anzhi 
Published: December 2024

AbstractBACKGROUNDEpichloë endophytes provide many benefits to host plants, including enhanced insect resistance. Fungal alkaloids are usually thought to be responsible for the endophyte‐conferred herbivore resistance. Nonetheless, the fungal alkaloid profiles and concentrations may vary considerably among grass–endophyte systems. This indicates that apart from fungal alkaloids, additional mechanisms such as endophyte‐mediated host defense are likely contributed to endophyte–grass–insect interactions. In this study, we addressed this issue by investigating the effect of Epichloë on the defense responses of Achnatherum sibiricum against locusts.RESULTSThe results showed that Epichloë endophytes increased locust resistance of A. sibiricum in both choice and non‐choice feeding experiments. In no feeding groups, endophyte infection increased the content of jasmonic acid (JA) and ethylene (ET), chitinase activity, and the biosynthetic gene expression of the relevant pathways. Endophyte infection also increased the content of total phenolics and condensed tannins. These indicators were negatively correlated with leaf consumption. In locust feeding groups, endophyte infection increased trypsin inhibitor activity. Exogenous application of phytohormones further proved that JA and ET reduced the consumption of A. sibiricum by locusts.CONCLUSIONThe present study showed that endophyte‐conferred host defense was mainly constitutive, that is, the defense characteristics of host plants were mainly manifested in no feeding groups. Endophyte presence enhanced locust resistance of the host by activating the JA/ET signaling pathway, elevating chitinase activity and phenolic compounds content, thereby improving the defense ability of host plants. © 2024 Society of Chemical Industry.
Observations and quantification of fog droplet deposition made during the SOFOG3D campaign
Authors: Price J. D. 
Published: December 2024

AbstractThis paper presents observations collected during the SOFOG3D campaign in southwestern France during 2019–2020, to elucidate the processes involved in the deposition of fog droplets to the surface, a process that is often modelled in Numerical Weather Prediction models, and forms an important component of the water budget within fog. The study considers that three main mechanisms cause deposition: turbulent, whereby water drops are transported to the surface in turbulent eddies; aerodynamic, whereby the mean horizontal wind deposits droplets directly onto surface canopy elements that protrude into the airflow, and gravitational, whereby droplets fall under the action of gravity directly onto the canopy. Results indicate that the gravitational settling is on average a minor component of the deposition, amounting to around 15% of the total figure. The study also identified that this proportion is relatively larger at 18%, when the turbulence intensity levels are low (vertical‐velocity variance <0.003 m2·s−2). Consequently, for greater values of turbulence intensity the proportion is smaller at 12%. All three deposition processes are studied further using a multiple linear regression of terms against observed water deposition rates, in an attempt to evaluate various methods to estimate the deposition. Results indicate that a simple regression of liquid‐water content against observed deposition has some predictive skill, but that a multiple regression including all three terms produces better results with smaller regression errors. A simpler multiple regression that merged turbulent and aerodynamic terms into a single ‘dynamic’ term produced results almost identical to the three‐term multiple regression. Finally, the differences in fog water deposition rates between stable shallow fog and more turbulent, deeper adiabatic fog were assessed and found to be small. Consequences for parametrisation of liquid‐water deposition in fog are discussed.
Assessment of corrosion attack morphology on reinforced concrete structures exposed to chlorides
Authors: Yilmaz Deniz , Rossi Emanuele , Angst Ueli 
Published: December 2024

AbstractChloride‐induced corrosion of the reinforcement steel is the main degradation mechanism for reinforced concrete, considerably affecting the load and deformation capacity of structures. Despite its importance, there is limited knowledge about the morphology of corrosion attacks and accordingly, relatively crude assumptions are generally made when considering corrosion in structural analyses. Improved understanding could reduce maintenance costs and extend the service life of structures. This study presents a systematic documentation and analysis of more than 600 corrosion attack morphologies, both from observations on actual engineering structures and from laboratory specimens (X‐ray computed tomography data from previous studies). Findings reveal that corrosion attacks—regardless of age, concrete type, or whether occurring in structures or laboratory specimens—without exception grow laterally and longitudinally along the reinforcement bar, rather than in depth. This shallow morphology deviates from the conventional description of pitting corrosion in the literature. Therefore, we propose using the term ‘corrosion attack’ instead of ‘corrosion pit’ for better differentiation. We discuss different mechanism that may lead to this growth pattern. Moreover, implications for the consideration of corrosion in structural analysis are assessed. A comprehensive database of the documented corrosion attacks is provided to enhance existing service life models, offering substantial data for probabilistic modeling of input parameters.
The Local Index Formula in Noncommutative Geometry
Authors: van Suijlekom Walter D. 
Published: December 2024

AbstractIn this chapter we present a proof of the Connes–Moscovici index formula, expressing the index of a (twisted) operator D in a spectral triple $$(\mathcal {A},\mathcal {H},D)$$

(
A
,
H
,
D
)

by a local formula. First, we illustrate the contents of this chapter in the context of two examples in the odd and even case: the index on the circle and on the torus.
Localization of Gauge Theories from Noncommutative Geometry
Authors: van Suijlekom Walter D. 
Published: December 2024

AbstractWe ‘localize’ the generalized gauge theory derived from any spectral triple by constructing a $$C^*$$

C
∗

-bundle on which the gauge group acts by vertical automorphisms. This will be exemplified for toric noncommutative manifolds.
The flavor invariants of the νSM
Authors: Grojean Christophe , Kley Jonathan , Leflot Damien , Yao Chang-Yuan 
Published: December 2024

Abstract
Sixty years after the experimental discovery of CP violation in the quark sector, the existence of a similar CP violation in the lepton sector is still to be established. Actually, the structure of such a violation depends crucially on the origin of the neutrino masses. In an attempt at categorizing the leptonic sources of CP violation, we studied the νSM, the Standard Model extended with three generations of sterile neutrinos, that can interpolate continuously between the Dirac and Majorana scenarios of neutrino masses. In particular, we perform a classification of the Jarlskog-like flavor invariants entering CP-violating observables and we study their suppression with the heavy Majorana mass in the seesaw limit of the model. To simplify the construction of the invariants, we introduce a graph-based method. With the guidance of the Hilbert series and plethystic logarithm of the theory, we construct the generating and primary sets of invariants for the νSM for the first time. Unlike in the Standard Model and some other theories, we find that the numbers of generating invariants and the syzygies among them cannot immediately be read off from the plethystic logarithm, but require a more careful examination. Our analysis reveals that the generating set contains 459 invariants, out of which 208 are CP-even and 251 are CP-odd. In the seesaw limit of the νSM, we show that all parameters of the UV theory can be captured in the effective theory with a certain suppression with the heavy Majorana mass, while these parameters can only appear in a flavor-invariant way with a higher mass suppression. Furthermore, we discuss how the necessary and sufficient conditions for CP violation can be captured by utilizing these invariants. Along the way, we present useful algorithms to enumerate and build the flavor invariants.
Non-supersymmetric heterotic strings on a circle
Authors: Fraiman Bernardo , Graña Mariana , Parra De Freitas Héctor , Sethi Savdeep 
Published: December 2024

Abstract
Motivated by a recent construction of non-supersymmetric AdS3, we revisit the O(16) × O(16) heterotic string compactified on a torus. The string one-loop potential energy has interesting dependence on the classical moduli; extrema of this potential include loci where the gauge symmetry is maximally enhanced. Focusing on the case of a circle, we use lattice embeddings to find the maximal enhancement points together with their spectra of massless and tachyonic modes. We find an extended Dynkin diagram that encodes the global structure of the moduli space, as well as all symmetry enhancements and the loci where they occur. We find 107 points of maximal enhancement with 8 that are free of tachyons. The tachyon-free points each have positive cosmological constant. We determine the profile of the potential energy near each of these points and find that one is a maximum while three are saddle points. The remaining four live at the boundary of a tachyonic region in field space. In this way, we show that every point of maximal symmetry enhancement is unstable. We further find that the curvature of this stringy potential satisfies the de Sitter swampland conjecture. Finally, we discuss the implications for constructions of AdS3.
Local Limit Theorems for Hook Lengths in Partitions
Authors: Bhowmik Tapas , Tsai Wei-Lun 
Published: December 2024

AbstractPartition hook lengths have wide-ranging applications in combinatorics, number theory, physics, and representation theory. We study two infinite families of random variables associated with t-hooks. For fixed $$t\ge 1,$$

t
≥
1
,

if $$Y_{t;\,n}$$

Y

t
;

n

counts the number of hooks of length t in a random integer partition of n, we prove a uniform local limit theorem for $$Y_{t;\,n}$$

Y

t
;

n

on any bounded set of $${\mathbb {R}}.$$

R
.

To achieve this, we establish an asymptotic formula with a power-saving error term for the number of partitions of n with m many t-hooks. In contrast, we define $${\widehat{Y}}_{t;\,n}$$

Y
^

t
;

n

as the count of hooks divisible by t in a randomly chosen partition of n. While $${\widehat{Y}}_{t;\,n}$$

Y
^

t
;

n

converges in distribution, we show that it fails to satisfy the local limit theorem for any $$t \ge 2$$

t
≥
2

. The proofs employ the multivariable saddle-point method, asymptotic formulas for the number of t-core partitions from Anderson and Lulov–Pittel, and estimates of certain exponential sums. Notably, for $$t=4,$$

t
=
4
,

the analysis involves the asymptotic behavior of class numbers of imaginary quadratic fields.
On a question of Davenport and diagonal cubic forms over $$\mathbb {F}_q(t)$$
Authors: Glas Jakob , Hochfilzer Leonhard 
Published: December 2024

AbstractGiven a non-singular diagonal cubic hypersurface $$X\subset \mathbb {P}^{n-1}$$

X
⊂

P

n
-
1

over $$\mathbb {F}_q(t)$$

F
q

(
t
)

with $${{\,\textrm{char}\,}}(\mathbb {F}_q)\ne 3$$

char

(

F
q

)
≠
3

, we show that the number of rational points of height at most |P| is $$O(|P|^{3+\varepsilon })$$

O
(
|
P

|

3
+
ε

)

for $$n=6$$

n
=
6

and $$O(|P |^{2+\varepsilon })$$

O
(
|
P

|

2
+
ε

)

for $$n=4$$

n
=
4

. In fact, if $$n=4$$

n
=
4

and $${{\,\textrm{char}\,}}(\mathbb {F}_q) >3$$

char

(

F
q

)
>
3

we prove that the number of rational points away from any rational line contained in X is bounded by $$O(|P|^{3/2+\varepsilon })$$

O
(
|
P

|

3
/
2
+
ε

)

. From the result in 6 variables we deduce weak approximation for diagonal cubic hypersurfaces for $$n\ge 7$$

n
≥
7

over $$\mathbb {F}_q(t)$$

F
q

(
t
)

when $${{\,\textrm{char}\,}}(\mathbb {F}_q)>3$$

char

(

F
q

)
>
3

and handle Waring’s problem for cubes in 7 variables over $$\mathbb {F}_q(t)$$

F
q

(
t
)

when $${{\,\textrm{char}\,}}(\mathbb {F}_q)\ne 3$$

char

(

F
q

)
≠
3

. Our results answer a question of Davenport regarding the number of solutions of bounded height to $$x_1^3+x_2^3+x_3^3 = x_4^3+x_5^3+x_6^3$$

x
1
3

+

x
2
3

+

x
3
3

=

x
4
3

+

x
5
3

+

x
6
3

with $$x_i \in \mathbb {F}_q[t]$$

x
i

∈

F
q

[
t
]

.