bluuebunny/crossref_metadata_2025 huggingface dataset:
Stacking-dependent structural and electronic properties of trilayer γ-graphyne: an approach for new 2D carbon allotropes
Authors: Li Wentao , Yang Le
Published: October 2024

Vertical stacks of two-dimensional (2D) materials with interlayer van der Waals (vdW) force have provided a versatile approach for creating hybrid materials and modulating various properties. In this work, the structural and electronic properties of trilayer γ-graphyne, involving different stacking patterns, have been investigated through first-principles approaches. The result indicates that a metal-to-semiconducting transition can be triggered simply by switching the stacking order of trilayer γ-graphyne. More interestingly, in addition to typical vdW homostructures, new 2D carbon allotropes with novel carbon networks can be achieved on the basis of trilayer γ-graphyne, arising from the absence of intralayer acetylene linkages during the structural relaxation. One of the new 2D carbon allotropes possesses an intrinsic semiconducting nature with a wide bandgap of 1.827 eV, coupled with superior structural stability beyond single-layer γ-graphyne. Moreover, the biaxial strain effect on the new 2D carbon allotrope, as well as the trilayer vdW stacks, has also been revealed in this work. Correspondingly, the in-plane tensile strain is demonstrated to further enlarge the electronic bandgaps in these carbon sheets. Therefore, the results of this work imply the great potential of few-layer graphyne in future carbon-based nanoelectronic devices, and simultaneously provide a new approach for developing and synthesizing novel 2D carbon allotropes via the vertical stacking of graphyne with inherent acetylene linkages.
National Council on Radiation Protection (NCRP) 2024 annual meeting: advanced and small modular nuclear power reactors*
Authors: Kennedy William E , Meserve Richard A , Higley Kathryn A , Huff Kathryn D , Hanson Christopher T , Ford Michael , Schultheisz Daniel , Smith Todd , Kugelmass Bret , Abou-Jaoude Abdalla , Lovering Jessica R , Semancik Jeffery D , Cullen Gregory V , Cheatham Jesse , Peterson Per F , Redmond II Everett , Mirsky Steven M , Mahowald Matt , Houts Michael G , Perkins David , Vaghetto Rodolfo , Duhig John , VanHorne-Sealy Col Jama D
Published: October 2024

On 25–26 March 2023, the U.S. National Council on Radiation Protection and Measurements (NCRP) held its 2024 annual meeting in Bethesda, Maryland, USA. The NCRP dates from 1929, and this meeting celebrated the 60th anniversary of receiving a U.S. Congressional Charter. For this annual meeting the NCRP felt it was essential to provide a briefing about advanced and small modular nuclear reactors (SMRs). The Journal of Radiological Protection is delighted to publish the following synopsis of material presented at the U.S. NCRP meeting. This synopsis is divided into five sections. The first section provides an overview of the whole meeting together with summaries of two context setting overview papers. The following four sessions of this synopsis are specific to advanced and small modular nuclear power reactors. The meeting also included keynote presentations by three of NCRP annual award recipients. The meeting topical areas were Technology Overview and Critical Issues. The individual papers laid the groundwork to understanding reactor technologies, terminology, and the fundamental concepts and processes for electrical generation. The perspectives of the U.S. Environmental Protection Agency and states, through the Conference of Radiation Control Program Directors were provided. The papers included a discussion of diverse topics including potential emergency preparedness considerations, radiological survey requirements, an evaluation of the future of nuclear power, the economics of reactors (both large and small), and the critical issues identified by the recent National Academies of Sciences’ study on advanced reactors. The summary papers were developed to briefly document the major points and concepts presented during the oral papers presented at the 2024 NCRP Annual Meeting. The meeting heralded the dawn of a new era for commercial nuclear power.
UWB/IMU integrated indoor positioning algorithm based on robust extended Kalman filter
Authors: Sun Wei , Zhang Heming , Ding Wei , Shi Peng , Chen Haonan
Published: October 2024

As a fundamental method for integrated indoor positioning, Ultra wideband (UWB)/ Inertial Measurement Unit (IMU) offers more stable performance compared to separate UWB sensor and IMU sensor positioning and uses the least squares (LS) and extended Kalman filter (EKF) for positioning processing, however, the performance of conventional LS and EKF will be seriously affected when the contamination rate of measurement noise is high. To address this problem, this paper proposes a robust extended Kalman filter (REKF) based algorithm for robot-integrated indoor positioning, which combines UWB and IMU positioning methods to obtain a more robust system performance and optimal positioning accuracy. In this paper, a vehicle equipped with a UWB/IMU sensor and four anchor points is set up to perform linear, circular, and trajectory motions in an experimental environment with visible obstacles. The experimental results show that compared with EKF, REKF improves the localization precision and accuracy in the three motions by 20.98%, 35.51%, and 47.06%, respectively. REKF effectively improves the accuracy and robustness of the robot’s indoor positioning, and provides an improved and practical method for integrated indoor positioning algorithms to make indoor positioning more accurate and reliable.
Thermal, mechanical, and electrical properties of Si-stacked nanosheet transistors using machine learning interatomic potentials
Authors: Saleh Mohamed , Abdelhamid Hamdy , Bayoumi Amr M
Published: October 2024

Thermal and mechanical properties play a key role in optimizing the performance of nanoelectronic devices. In this study, the lattice thermal conductivity (κ
L) and elastic constants of Si nanosheets at different sheet thicknesses were determined using recently developed machine learning interatomic potentials (MLIPs). A Si nanosheet with a minimum thickness of 10 atomic layers was used for model training to predict the properties of sheets with greater thicknesses. The training dataset was efficiently constructed using stochastic sampling of the Born-Oppenheimer potential energy surface. Density functional theory calculations were used to extract the MLIP, which served as the basis for further analysis. The moment tensor potential method was used to obtain the MLIP in this study. The results showed that, at sub-6 nm sheet thickness, the thermal conductivity dropped to ~7% of its bulk value, whereas some stiffness tensor components dropped to ~3% of the bulk values. These findings contribute to the understanding of heat transport and mechanical behavior of ultrathin Si nanosheets, which is crucial for designing and optimizing nanoelectronic devices. The technological implications of the extracted parameters on nanosheet field-effect transistor performance at advanced technology nodes were evaluated using TCAD device simulations.
A novel flexural damping channel magnetorheological damper with high effective magnetic field coverage and experimental verification of damping performance
Authors: Lei Bingyue , Li Jiahao , Wang Jiashuo , Peng Guojian , Fu Benyuan , Zhao Feng , Liao Changrong
Published: October 2024

Conventional magnetorheological dampers (MRDs) have limitations owing to their low effective magnetic field coverage, and improving MRD structures is a common approach to address this issue. However, many existing MRD designs have limitations such as large radial dimensions and high coil power consumption. Therefore, this paper transformed the conventional damping channel into the flexural damping channel to increase the effective magnetic field coverage of the MRD based on the conventional structure. And then, the pressure drop model was utilized to preliminarily determine the structural parameters of the new MRD. Subsequently, a multi-physics coupling finite element method analysis model was constructed to accurately determine the structural parameters, ensuring that the novel flexural damping channel (NFDC) MRD increases the output peak damping force while reducing the radial dimension and input power. Furthermore, the damping force variable range is stabilized when the excitation current is zero (field-off). Finally, a large number of vibration tests were conducted on both the conventional and NFDC MRDs, and it was found that the NFDC MRD has better vibration energy dissipation capacity and higher output peak damping force while maintaining a basically same field-off damping force variable range compared with the conventional MRD. The above process not only proved that the NFDC MRD possesses excellent output damping capability and working condition adaptability, but also validated the operational effectiveness of employing the multi-physics coupling analysis method to design the NFDC MRD.
Feasibility study on time-domain extraction method for zero-frequency pulse signal of nonlinear Lamb waves and early fatigue damage detection
Authors: Tang Weili , Wang Zhijiao , Li Xinxin , Wei Yuming , Ceng Xiaoyi , Bi Yiwen
Published: October 2024

The early damage can be effectively and sensitively characterized by zero-frequency component of nonlinear Lamb waves, which exhibits some more favorable properties than higher harmonics. However, in the process of extracting zero-frequency component, it is challenging to determine the time period that needs to be analyzed. In this study, the residual component obtained from the empirical mode decomposition of nonlinear Lamb waves was compared with the zero-frequency pulse signal after low-pass filtering. The results showed consistency between the two. Furthermore, a method for extracting the zero-frequency pulse signal in the time domain is developed, which is without signal decomposition. Furthermore, a time-domain index is established by zero-frequency pulse signal to indicate the severity of early damage in mechanical parts. Finite element simulation validates the accuracy of zero-frequency pulse signal extraction and evaluates nonlinear damage. Experimental validation is conducted by ultrasonic nonlinear testing on alloy-6061 plates with fatigue damage, affirming the effectiveness of early damage detection. This work proposes a method that allows for the intuitive analysis of the time domain zero-frequency pulse signal, providing a reference for determining the time duration in subsequent studies. Additionally, the established index provides a reference for early fatigue damage detection.
Improved wear and corrosion resistance of magnesium AZ80 alloy prepared by laser surface remelting
Authors: Zhang Yuan , Taheri Morteza , Shirvani Kourosh , Entezarian Mohammad Mahdi
Published: October 2024

Laser surface remelting (LSR) is a laser-based surface treatment method. In the LSR process, microstructural defects such as cracks and porosity are suppressed in addition to grain refinement, and the mechanical properties are improved. The present research investigated the effects of LSR parameters on the microstructure, wear, and corrosion behavior of Mg AZ80 alloy. The results showed that in LSR, the coarse-grained (29.8 μm) structure of AZ80 was transformed into a fine-grained structure (3.1 μm) with no microstructural defects. The evaporation of Mg during LSR and the formation of Al-rich and Mg-poor phases are the most important challenges in the surface treatment of AZ80. This limitation was solved by optimizing the LSR parameters, which included a gas flow rate of 2 L min−1, pulse duration of 3 ms, scanning speed of 3 mm s−1, pulse frequency of 8 Hz, and heat input of 64 J mm−1. The prevention of Mg evaporation was associated with the elimination of porosity and cracks, reducing of the solidification range, and uniform distribution of β-Mg17Al12 precipitation phases in α-Mg refined grains. The tribological behavior of the laser-treated region showed that the COF, depth of the wear scar, wear rate, and wear volume loss were reduced by 18%, 48%, 37%, and 66%, respectively, compared to AZ80. This result is attributed to the refinement of α-Mg grains and the uniform distribution of β-Mg17Al12 in the laser-treated region. The results of the polarization curves of the corrosion test in 3.5 wt% NaCl solution showed that the optimal laser-treated region with the lowest corrosion current density (34.68 × 10−6 μA.cm−2) and highest self-corrosion potential (1.425 V) exhibited the highest corrosion resistance. A slight change in the breakdown potential current slope in the laser-treated region indicates the formation of a protective film on the surface after the completion of LSR, which increases corrosion resistance.
Modular invariant slow roll inflation
Authors: Ding Gui-Jun , Jiang Si-Yi , Zhao Wenbin
Published: October 2024

We propose new classes of inflation models based on the modular symmetry, where the modulus field τ serves as the inflaton. We establish a connection between modular inflation and modular stabilization, wherein the modulus field rolls towards a fixed point along the boundary of the fundamental domain. We find the modular symmetry strongly constrain the possible shape of the potential and identify some parameter space where the inflation predictions agree with cosmic microwave background observations. The tensor-to-scalar ratio is predicted to be smaller than 10-6 in our models, while the running of spectral index is of the order of 10-4.
Significant impact of Galactic dark matter particles on annihilation signals from Sagittarius analogues
Authors: Vienneau Evan , Evans Addy J. , Hartl Odelia V. , Bozorgnia Nassim , Strigari Louis E. , Riley Alexander H. , Shipp Nora
Published: October 2024

We examine the gamma-ray signal from dark matter (DM) annihilation from analogues of the
Sagittarius (Sgr) dwarf spheroidal galaxy in the Auriga cosmological simulations. For
velocity-dependent annihilation cross sections, we compute emissions from simulated Sgr subhalos
and from the Milky Way (MW) foreground. In addition to the annihilation signals from DM particles
bound to Sgr, we consider for the first time the annihilation of DM particles bound to the MW that
overlap spatially with Sgr. For p-wave models this contribution can enhance the signal by over an
order of magnitude, while for d-wave models the enhancement can be over three orders of
magnitude. For Sommerfeld and s-wave models, the corresponding emission does not significantly
change. For the Sommerfeld model, the Sgr source can be visible above the MW foreground emission,
while for s, p and d-wave models, the signal towards Sgr is most likely dominated by foreground MW
emission. We interpret our results within the context of the observed gamma-ray emission from
Sgr. We find that, given the background emission estimated from this region, the templates from
simulations likely have spatial morphology that is too extended to explain the point-like emission
that is observed.
Heterojunction-engineered carrier transport in elevated-metal metal-oxide thin-film transistors
Authors: Li Xiao , Ma Zhikang , Li Jinxiong , Pan Wengao , Liao Congwei , Zhang Shengdong , Gao Zhuo , Fu Dong , Lu Lei
Published: October 2024

This study investigates the carrier transport of heterojunction channel in oxide semiconductor thin-film transistor (TFT) using the elevated-metal metal-oxide (EMMO) architecture and indium−zinc oxide (InZnO). The heterojunction band diagram of InZnO bilayer was modified by the cation composition to form the two-dimensional electron gas (2DEG) at the interface quantum well, as verified using a metal−insulator−semiconductor (MIS) device. Although the 2DEG indeed contributes to a higher mobility than the monolayer channel, the competition and cooperation between the gate field and the built-in field strongly affect such mobility-boosting effect, originating from the carrier inelastic collision at the heterojunction interface and the gate field-induced suppression of quantum well. Benefited from the proper energy-band engineering, a high mobility of 84.3 cm2·V−1·s−1, a decent threshold voltage (V
th) of −6.5 V, and a steep subthreshold swing (SS) of 0.29 V/dec were obtained in InZnO-based heterojunction TFT.
Pharmacy 3D printing
Authors: Cheng Jessica T Y , Tan Edwin C K , Kang Lifeng
Published: October 2024

A significant limitation of the ‘one size fits all’ medication approach is the lack of consideration for special population groups. 3D printing technology has revolutionised the landscape of pharmaceuticals and pharmacy practice, playing an integral role in enabling on-demand production of customised medication. Compared to traditional pharmaceutical processes, 3D printing has major advantages in producing tailored dosage forms with unique drug release mechanisms. Moreover, this technology has enabled the combination of multiple drugs in a single formulation addressing key issues of medication burden. Development of 3D printing in pharmacy applications and large-scale pharmaceutical manufacturing has substantially increased in recent years. This review focuses on the emergence of extrusion-based 3D printing, particularly semi solid extrusion, fused deposition modelling and direct powder extrusion, which are currently the most commonly studied for pharmacy practice. The concept of each technique is summarised, with examples of current and potential applications. Next, recent advancements in the 3D printer market and pharmacist perceptions are discussed. Finally, the benefits, challenges and prospects of pharmacy 3D printing technology are highlighted, emphasising its significance in changing the future of this field.
Transfer learning-assisted modulation classification and OSNR estimation using constellation diagrams
Authors: Jha Dhirendra Kumar , Mishra Jitendra K
Published: October 2024

A cost-effective deep transfer learning (TL) learned with characteristics derived from the constellation diagram is proposed for executing modulation classification and optical signal-to-noise ratio (OSNR) estimation for the future generation of elastic optical networks. The information acquired with the ImageNet dataset is transferred using pre-trained TL versions including VGG19, ResNet152V2, InceptionV3, and ResNet50 to identify various modulation formats and their corresponding OSNR. Adam optimizer is employed to ascertain the appropriate settings for the hyperparameters. Numerical results demonstrate that the proposed VGG19 method achieves the highest level of accuracy (100%) in the recognition of various modulation forms. To fulfil the requirements of actual use, OSNR monitoring is also explored, with a total precision equal to 95.2%. Furthermore, a thorough investigation of the impact of training data dimensions, on TL performance is conducted. The outcomes of the proposed method demonstrate that the suggested TL-based algorithms are more accurate and need much less training and testing time than non-TL approaches.
Hybrid algorithm for the time-dependent Hartree–Fock method using the Yang–Baxter equation on quantum computers*
Authors: Gulania Sahil , Gray Stephen K , Alexeev Yuri , Peng Bo , Govind Niranjan
Published: October 2024

The time-dependent Hartree–Fock (TDHF) method is an approach to simulate the mean field dynamics of electrons within the assumption that the electrons move independently in their self-consistent average field and within the space of single Slater determinants. One of the major advantages of performing time dynamics within Hartree–Fock theory is the free fermionic nature of the problem, which makes TDHF classically simulatable in polynomial time. Here, we present a hybrid TDHF implementation for quantum computers. This quantum circuit grows with time; but with our recent work on circuit compression via the Yang–Baxter equation (YBE), the resulting circuit is constant depth. This study provides a new way to simulate TDHF with the aid of a quantum device as well as provides a new direction for the application of YBE symmetry in quantum chemistry simulations.
Evaluating the robustness of the ARIO model for a local disaster: 2021 flooding in Germany
Authors: Juhel Samuel , Delahais Adrien , Viguié Vincent
Published: October 2024

Given the interconnectedness of modern economies and the widespread adoption of just-in-time production methods, even minor disruptions caused by natural disasters can lead to substantial indirect economic impact. A substantial body of literature has explored this phenomenon, using input-output analysis, computable general equilibrium and agent-based models. However, these models (i) heavily rely on parameters and data that often lack empirical grounding or (ii) exhibit considerable uncertainty, making it challenging to assess their reliability. The ARIO model has been widely used in the literature and has provided theoretical foundation for several related models. Using the July 2021 floods in Germany as a case study, we assess the sensitivity of the results of this model by varying key parameters, as well as the multi-regional input-output tables (MRIOTs), which constitute its primary input data. To facilitate this analysis, we introduce a new, resource-efficient Python implementation of the ARIO model, enabling the execution of a large number of simulations. Our findings highlight the substantial impact of data source and parameter selection on model outcomes, especially so when post-disaster rebuilding is costly. To ensure the robustness of their results, future studies on indirect economic impacts should be careful about recovery dynamics, consider multiple scenarios and compare results using MRIOTs from various sources.
A node-conservative vorticity preserving finite volume method for linear acoustics on unstructured grids
Authors: Barsukow Wasilij , Loubère Raphaël , Maire Pierre-Henri
Published: October 2024

Instead of ensuring that fluxes across edges add up to zero, we split the edge in two halves and also associate different fluxes to each of its sides. This is possible due to non-standard Riemann solvers with free parameters. We then enforce conservation by making sure that the fluxes around a node sum up to zero, which fixes the value of the free parameter. We demonstrate that for linear acoustics one of the non-standard Riemann solvers leads to a vorticity preserving method on unstructured meshes.
Low-rank quaternion tensor completion for color video inpainting via a novel factorization strategy
Authors: Qin Zhenzhi , Ming Zhenyu , Sun Defeng , Zhang Liping
Published: October 2024

Recently, a quaternion tensor product named Qt-product was proposed, and then the singular value decomposition and the rank of a third-order quaternion tensor were given. From a more applicable perspective, we extend the Qt-product and propose a novel multiplication principle for third-order quaternion tensor named gQt-product. With the gQt-product, we introduce a brand-new singular value decomposition for third-order quaternion tensors named gQt-SVD and then define gQt-rank and multi-gQt-rank. We prove that the optimal low-rank approximation of a third-order quaternion tensor exists and some numerical experiments demonstrate the low-rankness of color videos. So, we apply the low-rank quaternion tensor completion to color video inpainting problems and present alternating least-square algorithms to solve the proposed low gQt-rank and multi-gQt-rank quaternion tensor completion models. The convergence analyses of the proposed algorithms are established and some numerical experiments on various color video datasets show the high recovery accuracy and computational efficiency of our methods.
An efficient algorithm for the ℓ_{𝑝} norm based metric nearness problem
Authors: Tang Peipei , Jiang Bo , Wang Chengjing
Published: October 2024

Given a dissimilarity matrix, the metric nearness problem is to find the nearest matrix of distances that satisfy the triangle inequalities. This problem has wide applications, such as sensor networks, image processing, and so on. But it is of great challenge even to obtain a moderately accurate solution due to the

O
(

n

3

)

O(n^{3})

metric constraints and the nonsmooth objective function which is usually a weighted

ℓ

p

\ell _{p}

norm based distance. In this paper, we propose a delayed constraint generation method with each subproblem solved by the semismooth Newton based proximal augmented Lagrangian method (PALM) for the metric nearness problem. Due to the high memory requirement for the storage of the matrix related to the metric constraints, we take advantage of the special structure of the matrix and do not need to store the corresponding constraint matrix. A pleasing aspect of our algorithm is that we can solve these problems involving up to

10

8

10^{8}

variables and

10

13

10^{13}

constraints. Numerical experiments demonstrate the efficiency of our algorithm.

Concerning the theory, firstly, under a mild condition, we establish a calmness condition which is very essential for the analysis of local convergence rate of PALM. Secondly, we prove the equivalence between the dual nondegeneracy condition and nonsingularity of the generalized Jacobian for the inner subproblem of PALM. Thirdly, for the

ℓ

1

\ell _{1}

or

ℓ

∞

\ell _{\infty }

norm based problem, without the strict complementarity condition, we also prove the equivalence between the dual nondegeneracy condition and the uniqueness of the primal solution.
Quadratic constraint consistency in the projection-free approximation of harmonic maps and bending isometries
Authors: Akrivis Georgios , Bartels Sören , Palus Christian
Published: October 2024

We devise a projection-free iterative scheme for the approximation of harmonic maps that provides a second-order accuracy of the constraint violation and is unconditionally energy stable. A corresponding error estimate is valid under a mild but necessary discrete regularity condition. The method is based on the application of a BDF2 scheme and the considered problem serves as a model for partial differential equations with holonomic constraint. The performance of the method is illustrated via the computation of stationary harmonic maps and bending isometries.
The 𝑅𝑂(𝐶_{2ⁿ})-graded homotopy of 𝐻\underline{𝔽₂}
Authors: Yan Guoqi
Published: October 2024

We give explicit formulas for the

R
O
(

C

2
n

)

RO(C_{2^n})

-graded homotopy of the Eilenberg-Mac Lane spectrum

H

F

2

_

H\underline {\mathbb {F}_2}

.
Jumps of Jacobians via orthogonal canonical forms
Authors: Kaya Enis , Maex Michaël , Waeterschoot Art
Published: October 2024

Given a smooth, proper curve

C
C

over a discretely valued field

k
k

, we equip the

k
k

-vector space

H

0

(
C
,

ω

C

/

k

)

H^{0}(C,\omega _{C/k})

with a canonical discrete valuation

v

c
a
n

v_\mathrm {can}

which measures how canonical forms degenerate on regular integral models of

C
C

. More precisely,

v

c
a
n

v_\mathrm {can}

maps a canonical form to the minimal value of its associated weight function, as introduced by Mustaţă–Nicaise [Algebr. Geom. 2 (2015), pp. 365–404]. Our main result states that

v

c
a
n

v_\mathrm {can}

computes Edixhoven’s jumps of the Jacobian of

C
C

when evaluated in an orthogonal basis. As a byproduct, we deduce a short proof for the rationality of the jumps of Jacobians. We also show how

v

c
a
n

v_\mathrm {can}

and the jumps can be computed efficiently for the class of

Δ
v

\Delta _v

-regular curves introduced by Dokchitser [Duke Math. J. 170 (2021), pp. 2519–2574].
General components of tangent spaces and Rees algebras associated with derivations
Authors: Morán Cañón Mario , Sebag Julien
Published: October 2024

Let

k
k

be a field of characteristic zero and

V
V

be a reduced affine

k
k

-variety with tangent space

T
(
V
)

T(V)

and arc scheme

L

∞

(
V
)

\mathscr {L}_{\infty }(V)

. In this article, we establish a connection between the Zariski closure

G

1

(
V
)

\mathscr G_1(V)

of the nonsingular locus of the tangent space

T
(
V
)

T(V)

of

V
V

and the blow-up of

V
V

along the closed subvariety of

V
V

associated with the datum of the ideal

J
D

J_D

generated by the coefficients of any nonzero

k
k

-derivation

D
D

on

V
V

. Precisely, we construct a closed immersion from the affine cone of this blow-up to

G

1

(
V
)

\mathscr G_1(V)

. If

dim
⁡
(
V
)
≥
2

\dim (V)\geq 2

, this results in a strict closed embedding, but it is an isomorphism if

dim
⁡
(
V
)
=
1

\dim (V)=1

. As an application, when

dim
⁡
(
V
)
=
1

\dim (V)=1

, we derive a characterization, in terms of the derivations on

V
V

, of the nilpotent regular functions in

O

(

L

∞

(
V
)
)

\mathcal O(\mathscr {L}_{\infty }(V))

that are defined in

O

(
T
(
V
)
)

\mathcal O(T(V))

. As a by-product, this isomorphism offers an alternative algorithm for computing a presentation of the ideal formed by such nilpotent functions.
An explicit Wishart moment formula for the product of two disjoint principal minors
Authors: Genest Christian , Ouimet Frédéric , Richards Donald
Published: October 2024

This paper provides the first explicit formula for the expectation of the product of two disjoint principal minors of a Wishart random matrix, solving a part of a broader problem put forth by Samuel S. Wilks [Ann. of Math. (2) 35 (1934), pp. 312–340]. The proof makes crucial use of hypergeometric functions of matrix argument and their Laplace transforms. Additionally, a Wishart generalization of the Gaussian product inequality conjecture is formulated and a stronger quantitative version is proved to hold in the case of two minors.
Homotopy rigidity for quasitoric manifolds over a product of 𝑑-simplices
Authors: Fu Xin , So Tseleung , Song Jongbaek , Theriault Stephen
Published: October 2024

For a fixed integer

d
≥
1

d\geq 1

, we show that two quasitoric manifolds over a product of

d
d

-simplices are homotopy equivalent after appropriate localization, provided that their integral cohomology rings are isomorphic.
Stability and finiteness theorems for Wasserstein spaces
Authors: Alattar Mohammad
Published: October 2024

Under Gromov–Hausdorff convergence, and equivariant Gromov–Hausdorff convergence, we prove stability results of Wasserstein spaces over certain classes of singular and non-singular spaces. For example, we obtain an analogue of Perelman’s stability theorem on Wasserstein spaces.
Amenable covers and relative bounded cohomology
Authors: Capovilla Pietro
Published: October 2024

We establish a relative version of Gromov’s Vanishing Theorem in the presence of amenable open covers with small multiplicity, extending a result of Li, Löh and Moraschini. Our approach relies on Gromov’s theory of multicomplexes.
Spectra of the Dirichlet Laplacian in 3-dimensional polyhedral layers
Authors: Bakharev F. , Matveenko S.
Published: October 2024

The structure of the spectrum of the three-dimensional Dirichlet Laplacian in a 3D polyhedral layer of fixed width is studied. It turns out that the essential spectrum is determined by the smallest dihedral angle that forms the boundary of the layer while the discrete spectrum is always finite. An example of a layer with empty discrete spectrum is constructed. The spectrum is proved to be nonempty in regular polyhedral layer.
Order-boundary characterization of the linear lattice of Riemann 𝜇-integrable functions as a certain completion of the linear lattice of bounded continuous functions
Authors: Zakharov V.
Published: October 2024

The linear lattice of Riemann

μ
\mu

-integrable functions on a completely regular space with a bounded positive Radon measure

μ
\mu

is viewed as an extension of the linear lattice of bounded continuous functions. To characterize this Riemann extension, the new functional analysis category of

c
c

-latlineals with refinements (

≡
c
r

\equiv cr

-latlineals) is introduced. On this basis, the procedure of

c
r

cr

-completion of certain order-boundary type is defined. The

μ
\mu

-Riemann extension is shown to be the result of applying this procedure to the

c

r

μ

cr_{\mu }

-latlineal of bounded continuous functions.
The weak-type Carleson theorem via wave packet estimates
Authors: Di Plinio Francesco , Fragkos Anastasios
Published: October 2024

We prove that the weak-

L

p

L^{p}

norms, and in fact the sparse

(
p
,
1
)

(p,1)

-norms, of the Carleson maximal partial Fourier sum operator are

≲
(
p
−
1

)

−
1

\lesssim (p-1)^{-1}

as

p
→

1
+

p\to 1^+

. This is an improvement on the Carleson-Hunt theorem, where the same upper bound on the growth order is obtained for the restricted weak-

L
p

L^p

type norm, and which was the strongest quantitative bound prior to our result. Furthermore, our sparse

(
p
,
1
)

(p,1)

-norms bound imply new and stronger results at the endpoint

p
=
1

p=1

. In particular, we obtain that the Fourier series of functions from the weighted Arias de Reyna space

Q
A

∞

(
w
)

\mathrm {QA}_{\infty }(w)

, which contains the weighted Antonov space

L
log
⁡
L
log
⁡
log
⁡
log
⁡
L
(

T

;
w
)

L\log L\log \log \log L(\mathbb T; w)

, converge almost everywhere whenever

w
∈

A
1

w\in A_1

. This is an extension of the results of Antonov [Proceedings of the XXWorkshop on Function Theory (Moscow, 1995), 1996, pp. 187–196] and Arias De Reyna, where

w
w

must be Lebesgue measure.

The backbone of our treatment is a new, sharply quantified near-

L
1

L^1

Carleson embedding theorem for the modulation-invariant wave packet transform. The proof of the Carleson embedding relies on a newly developed smooth multi-frequency decomposition which, near the endpoint

p
=
1

p=1

, outperforms the abstract Hilbert space approach of past works, including the seminal one by Nazarov, Oberlin and Thiele [Math. Res. Lett. 17 (2010), pp. 529–545]. As a further example of application, we obtain a quantified version of the family of sparse bounds for the bilinear Hilbert transforms due to Culiuc, Ou and the first author.
Positive mass theorem for asymptotically flat spin manifolds with isolated conical singularities
Authors: Dai Xianzhe , Sun Yukai , Wang Changliang
Published: October 2024

There has been a lot of interest in positive mass theorems for singular metrics on smooth manifolds. We prove a positive mass theorem for asymptotically flat (AF) spin manifolds with isolated conical singularities or more generally horn singularities. In particular, we allow topological singularities in the space as we do not require the cross sections of the conical singularities to be spherical. Note that the negative mass Schwarzschild metric is AF with a horn singularity.
Evaluating the Impact of BoNT-A Injections on Facial Expressions: A Deep Learning Analysis
Authors: Aktar Ugurlu Gulay , Ugurlu Burak Numan , Yalcinkaya Meryem
Published: October 2024

Background

Botulinum toxin type A (BoNT-A) injections are widely administered for facial rejuvenation, but their effects on facial expressions remain unclear.

Objectives

In this study, we aimed to objectively measure the impact of BoNT-A injections on facial expressions with deep learning techniques.

Methods

One hundred eighty patients age 25 to 60 years who underwent BoNT-A application to the upper face were included. Patients were photographed with neutral, happy, surprised, and angry expressions before and 14 days after the procedure. A convolutional neural network (CNN)-based facial emotion recognition (FER) system analyzed 1440 photographs with a hybrid data set of clinical images and the Karolinska Directed Emotional Faces (KDEF) data set.

Results

The CNN model accurately predicted 90.15% of the test images. Significant decreases in the recognition of angry and surprised expressions were observed postinjection (P < .05), with no significant changes in happy or neutral expressions (P > .05). Angry expressions were often misclassified as neutral or happy (P < .05), and surprised expressions were more likely to be perceived as neutral (P < .05).

Conclusions

Deep learning can effectively assess the impact of BoNT-A injections on facial expressions, providing more standardized data than traditional surveys. BoNT-A may reduce the expression of anger and surprise, potentially leading to a more positive facial appearance and emotional state. Further studies are needed to understand the broader implications of these changes.

Level of Evidence: 4 (Therapeutic)
Detectability of a poison frog and its Batesian mimic depends on body posture and viewing angle
Authors: McEwen Brendan L , Yeager Justin , Kinley Isaac , Anderson Hannah M , Barnett James B
Published: October 2024

Aposematic signals warn predators that prey should be avoided due to dangerous secondary defences. However, as warning signals do not always produce avoidance, warning colors may evolve as a trade-off balancing detectability against signal saliency. For Batesian mimics, which display salient signals but lack secondary defenses, the costs of predator encounters are greater, potentially increasing the benefit of crypsis. This raises the question of whether imperfect mimicry may reduce detectability while retaining mimetic efficacy. We tested this hypothesis with the poisonous frog Ameerega bilinguis and undefended Batesian mimic Allobates zaparo, using computational visual modeling and screen-based detection trials with human participants. We found that both species incorporate camouflage into their warning colors, but to different degrees depending on viewing angle and behavior. Contrary to expectation, we found differences in detectability between model and mimic that do not adhere to the hypothesized cryptic mimetic phenotype. To aerial observers, we found the mimic to be more detectable than the model. To terrestrial observers, likely owing to the model’s bright ventral color, we found the model more detectable in viewing angles that highlight the ventral coloration, whereas the mimic was more detectable in viewing angles that highlight the dorsal coloration. Consequently, we suggest that in addition to being the result of perceptual or developmental constraints, imperfect mimicry may also evolve as an adaptive strategy which balances camouflage with different signaling functions. Our findings complement the emerging view that aposematic signals may evolve in response to a multitude of selection pressures beyond aversion alone.
Learning to handle flowers increases pollen collection for bees but does not affect pollination success for plants
Authors: Mayberry Maggie M , Naumer Katherine C , Novinger Annaliese N , McCart Dalton M , Wilkins Rachel V , Muse Haley , Ashman Tia-Lynn , Russell Avery L
Published: October 2024

Cooperation and conflict are common in plant–pollinator interactions. Flowering plants often entice pollinators to visit by offering floral food rewards, thereby facilitating pollination. However, pollinators such as bees can learn to improve their collection of floral rewards (such as pollen), changing how they interact with the flower’s reproductive organs, which together could reduce pollination success. Consequently, complex flowers that slow pollinator learning might benefit the plant. Yet how pollinator learning and flower complexity interact to affect pollination success is unknown. We therefore asked how differences in complexity of 4 flower types (Phacelia campanularia, Exacum affine, Solanum elaeagnifolium, and Erythranthe guttata) affected learning by pollen-foraging generalist bumble bees (Bombus impatiens) and how learning affected pollen collection and pollen deposition on these flowers. We found that bees generally learned how to efficiently handle more complex flower types more slowly. Bees that required more visits to become efficient foragers collected less pollen, with no effect on pollen deposition. Except for the simplest flower type, learning also involved development of motor routines unique to each flower type. Experienced bees overall collected more pollen, but individual differences in motor routines did not affect pollen collection. Conversely, individual differences in motor routines affected pollen deposition, but there was no overall effect of experience. Thus, even though learning overall benefits the bee, it does not alter female (and potentially male) fitness benefits for the plant. We discuss potential reasons for these patterns and consequences for bee behavior and flower evolution.
Sustained improvements in brain health and metabolic markers 24 months following bariatric surgery
Authors: Legault Marianne , Pelletier Mélissa , Lachance Amélie , Lachance Marie-Ève , Zeighami Yashar , Gauthier Marie-Frédérique , Iceta Sylvain , Biertho Laurent , Fulton Stephanie , Richard Denis , Dagher Alain , Tchernof André , Dadar Mahsa , Michaud Andréanne
Published: October 2024

Obesity and its metabolic complications are associated with lower grey matter and white matter densities, whereas weight loss after bariatric surgery leads to an increase in both measures. These increases in grey and white matter density are significantly associated with post-operative weight loss and improvement of the metabolic/inflammatory profiles. While our recent studies demonstrated widespread increases in white matter density 4 and 12 months after bariatric surgery, it is not clear if these changes persist over time. The underlying mechanisms also remain unknown. In this regard, numerous studies demonstrate that the enlargement or hypertrophy of mature adipocytes, particularly in the visceral fat compartment, is an important marker of adipose tissue dysfunction and obesity-related cardiometabolic abnormalities. We aimed (i) to assess whether the increases in grey and white matter densities previously observed at 12 months are maintained 24 months after bariatric surgery; (ii) to examine the association between these structural brain changes and adiposity and metabolic markers 24 months after bariatric surgery; and (iii) to examine the association between abdominal adipocyte diameter at the time of surgery and post-surgery grey and white matter densities changes. Thirty-three participants undergoing bariatric surgery were recruited. Grey and white matter densities were assessed from T1-weighted magnetic resonance imaging scans acquired prior to and 4, 12 and 24 months post-surgery using voxel-based morphometry. Omental and subcutaneous adipose tissue samples were collected during the surgical procedure. Omental and subcutaneous adipocyte diameters were measured by microscopy of fixed adipose tissue samples. Linear mixed-effects models were performed controlling for age, sex, surgery type, initial body mass index, and initial diabetic status. The average weight loss at 24 months was 33.6 ± 7.6%. A widespread increase in white matter density was observed 24 months post-surgery mainly in the cerebellum, brainstem and corpus callosum (P < 0.05, false discovery rate) as well as some regions in grey matter density. Greater omental adipocyte diameter at the time of surgery was associated with greater changes in total white matter density at 24 months (P = 0.008). A positive trend was observed between subcutaneous adipocyte diameter at the time of surgery and changes in total white matter density at 24 months (P = 0.05). Our results show prolonged increases in grey and white matter densities up to 24 months post-bariatric surgery. Greater preoperative omental adipocyte diameter is associated with greater increases in white matter density at 24 months, suggesting that individuals with excess visceral adiposity might benefit the most from surgery.
The role of kidney biopsy in the diagnosis of membranous nephropathy
Authors: Roccatello Dario , Fenoglio Roberta , Sciascia Savino
Published: October 2024

The discovery of the target antigen M-type phospholipase A2 receptor (PLA2R) with the possibility to detect anti-PLA2R antibodies in serum as well as the identification of several other antigens, overall accounting for almost all cases of membranous nephropathy, paved the way to a revolutionary change in the classification of membranous nephropathy. Serum anti-PLA2R autoantibody titers have been found to be highly specific diagnostic and prognostic biomarkers. Therefore, a positive test for anti-PLA2R serology in patients who present with nephrotic syndrome, normal kidney function, and no evidence of another process to account for proteinuria is believed to suffice to make a diagnosis of primary membranous nephropathy, thus removing the need for a renal biopsy. While technological advances will likely allow this proposal to prevail in the near future, the reasons why renal biopsy could still remain a critical tool for the management of membranous nephropathy in real life are discussed.
Cellular communication network factor 2 regulates smooth muscle cell transdifferentiation and lipid accumulation in atherosclerosis
Authors: Xu Qian , Sun Jisheng , Holden Claire M , Neto Hildebrando Candido Ferreira , Wang Ti , Zhang Chiyuan , Fu Zuli , Joseph Giji , Shi Ruizheng , Wang Jinhu , Leask Andrew , Taylor W Robert , Lin Zhiyong
Published: October 2024

Aims

Accruing evidence illustrates an emerging paradigm of dynamic vascular smooth muscle cell (SMC) transdifferentiation during atherosclerosis progression. However, the molecular regulators that govern SMC phenotype diversification remain poorly defined. This study aims to elucidate the functional role and underlying mechanisms of cellular communication network factor 2 (CCN2), a matricellular protein, in regulating SMC plasticity in the context of atherosclerosis.

Methods and results

In both human and murine atherosclerosis, an up-regulation of CCN2 is observed in transdifferentiated SMCs. Using an inducible murine SMC CCN2 deletion model, we demonstrate that SMC-specific CCN2 knockout mice are hypersusceptible to atherosclerosis development as evidenced by a profound increase in lipid-rich plaques along the entire aorta. Single-cell RNA sequencing studies reveal that SMC deficiency of CCN2 positively regulates machinery involved in endoplasmic reticulum stress, endocytosis, and lipid accumulation in transdifferentiated macrophage-like SMCs during the progression of atherosclerosis, findings recapitulated in CCN2-deficient human aortic SMCs.

Conclusion

Our studies illuminate an unanticipated protective role of SMC-CCN2 against atherosclerosis. Disruption of vascular wall homeostasis resulting from vascular SMC CCN2 deficiency predisposes mice to atherosclerosis development and progression.
The Circulating Methylome in Childhood-Onset Inflammatory Bowel Disease
Authors: Noble Alexandra , Adams Alex , Nowak Jan , Cheng Guo , Nayak Komal , Quinn Aisling , Kristiansen Mark , Kalla Rahul , Ventham Nicholas T , Giachero Federica , Jayamanne Chamara , Hansen Richard , Hold Georgina L , El-Omar Emad , Croft Nicholas M , Wilson David , Beattie R Mark , Ashton James J , Zilbauer Matthias , Ennis Sarah , Uhlig Holm H , Satsangi Jack
Published: October 2024

Background

The genetic contribution to inflammatory bowel disease (IBD), encompassing both Crohn’s disease (CD) and ulcerative colitis (UC), accounts for around 20% of disease variance, highlighting the need to characterize environmental and epigenetic influences. Recently, considerable progress has been made in characterizing the adult methylome in epigenome-wide association studies.

Methods

We report detailed analysis of the circulating methylome in 86 patients with childhood-onset CD and UC and 30 controls using the Illumina Infinium Human MethylationEPIC platform.

Results

We derived and validated a 4-probe methylation biomarker (RPS6KA2, VMP1, CFI, and ARHGEF3), with specificity and high diagnostic accuracy for pediatric IBD in UK and North American cohorts (area under the curve: 0.90-0.94). Significant epigenetic age acceleration is present at diagnosis, with the greatest observed in CD patients. Cis-methylation quantitative trait loci (meQTL) analysis identifies genetic determinants underlying epigenetic alterations notably within the HLA 6p22.1-p21.33 region. Passive smoking exposure is associated with the development of UC rather than CD, contrary to previous findings.

Conclusions

These data provide new insights into epigenetic alterations in IBD and illustrate the reproducibility and translational potential of epigenome-wide association studies in complex diseases.