bluuebunny/crossref_metadata_2025_split huggingface dataset:
Root foraging in the leguminous zinc hyperaccumulator Crotalaria novae-hollandiae from Queensland, Australia
Authors: Chen Fuyao , Nti Nkrumah Philip , Tang Roger H. , van der Ent Antony 
Published: March 2023

Context Root foraging by hyperaccumulator plants in response to patchily distributed metals has been observed in several obligate hyperaccumulators, but it is not known whether facultative hyperaccumulators respond similarly. Aims This study investigated the root-growth behaviour in the leguminous zinc (Zn) hyperaccumulator Crotalaria novae-hollandiae compared with the non-accumulating Crotalaria cunninghamii in response to localised soil Zn enrichment in the soil to observe foraging versus avoidance responses. Methods We conducted rhizotron experiments in which we exposed the Crotalaria species pair to juxtaposed treatments, which were either homogenous (each half of the treatments containing same Zn concentrations) or heterogenous (different Zn concentrations in each half of the treatments). The Zn concentrations were 0 μg Zn g−1 (control), 2000 μg Zn g−1 and 5000 μg Zn g−1 in the form of zinc carbonate). Key results We found that none of the treatments had significantly different rooting density and root biomass, regardless of the Crotalaria species. This finding contrasts with increased root proliferation in Zn-rich patches found for other obligate hyperaccumulator species. Conclusions and implications The no-preference root response towards Zn in Crotalaria may partly explain the facultative hyperaccumulation mechanism displayed by these species. This root response towards Zn may ultimately affect Zn phytoextraction efficacy when utilising Crotalaria species in a heterogenous Zn soil substrate. These findings highlight the need for rhizosphere investigations prior to field phytoextraction applications.
A goodness-of-fit test based on a recursive product of spacings
Authors: Eller Philipp , Shtembari Lolian 
Published: March 2023

Abstract
We introduce a new statistical test based on the observed spacings of ordered data.
The statistic is sensitive to detect non-uniformity in random samples, or short-lived features in event time series.
Under some conditions, this new test can outperform existing ones, such as the well known Kolmogorov-Smirnov or Anderson-Darling tests, in particular when the number of samples is small and differences occur over a small quantile of the null hypothesis distribution.
A detailed description of the test statistic is provided including a detailed discussion of the parameterization of its distribution via asymptotic bootstrapping as well as a novel per-quantile error estimation of the empirical cumulative distribution.
Two example applications are provided, using the test to boost the sensitivity in generic “bump hunting”, and employing the test to detect supernovae.
The article is rounded off with an extended performance comparison to other, established goodness-of-fit tests.
Equity implications of electric vehicles: A systematic review on the spatial distribution of emissions, air pollution and health impacts
Authors: Sharma Anjali , Shiwang Jinyu , Lee Anna , Peng Wei 
Published: March 2023

Abstract
Scaling up electric vehicles (EVs) provides an avenue to mitigate both carbon emissions and air pollution from road transport. The benefits of EV adoption for climate, air quality, and health have been widely documented. Yet, evidence on the distribution of these impacts has not been systematically reviewed, despite its central importance to ensure a just and equitable transition. Here, we perform a systematic review of recent EV studies that have examined the spatial distribution of the emissions, air pollution, and health impacts, as an important aspect of the equity implications. Using the Context-Interventions-Mechanisms-Outcome framework with a two-step search strategy, we narrowed down to 47 papers that met our inclusion criteria for detailed review and synthesis. We identified two key factors that have been found to influence spatial distributions. First, the cross-sectoral linkages may result in unintended impacts elsewhere. For instance, the generation of electricity to charge EVs, and the production of batteries and other materials to manufacture EVs could increase the emissions and pollution in locations other than where EVs are adopted. Second, since air pollution and health are local issues, additional location-specific factors may play a role in determining the spatial distribution, such as the wind transport of pollution, and the size and vulnerability of the exposed populations. Based on our synthesis of existing evidence, we highlight two important areas for further research: (1) fine-scale pollution and health impact assessment to better characterize exposure and health disparities across regions and population groups; and (2) a systematic representation of the EV value chain that captures the linkages between the transport, power and manufacturing sectors as well as the regionally-varying activities and impacts.
Estimating coastal slope of sandy beach from ICESat-2: a case study in Texas
Authors: Ma Yue , Wang Lin , Xu Nan , Zhang Shiyi , Hua Wang Xiao , Li Song 
Published: March 2023

Abstract
Coastal slope is a fundamental land characteristic that can influence the hydrodynamic and morphological processes, which is the essential parameter to calculate the wave setup and wave run up for further estimating extreme coastal water levels. Slope information of coastal zones also plays a key role in estimating the coastline erosion and evaluating the coastal vulnerability under sea level rise. However, accurate estimates of coastal slopes are currently limited, especially over sparsely populated and remote areas. The recent ICESat-2 photon-counting lidar provides unprecedented along-track dense and accurate height measurements in coastal zones. This study aims to demonstrate the potential of ICESat-2 measurements to estimate coastal slope of sandy beach at a large scale, and the proposed method is tested in Texas, USA. The validation with local airborne lidar data (with an average slope of 0.023 in Texas) indicates that, the ICESat-2 derived coastal slopes (0.026) have much better accuracy than current large-scale coastal slopes (0.0032) derived from SRTM and MERIT DEMs. With globally covered ICESat-2 datasets, this method can be expanded to estimate coastal slopes even at a global scale.
Tropical influences on European summer climate variability
Authors: Maidens Anna , Knight Jeff R 
Published: March 2023

Abstract
Numerous studies have established a link between tropical atmospheric conditions and northern midlatitude circulation mediated by Rossby wave propagation in winter. In recent years, research has also investigated tropical to midlatitude teleconnections in northern hemisphere summer. In this paper, we examine summer connections further by imposing observed tropical conditions in climate model simulations. We examine resulting changes in the representation of seasonal mean surface climate variables and mid-troposphere circulation in the northern hemisphere summer, identifying regions where model fidelity improves following the imposition of tropical conditions. We demonstrate robust connections between the tropics and mid-latitudes on the seasonal timescale, with these connections apparent in three mid-latitude regions, namely eastern North America, central Europe and northern Siberia. These regions are shown to be impacted by wave trains originating in specific regions of the subtropics associated with patterns of upper-level convergence. The results provide a clearer picture of tropical to extratropical teleconnections that affect summer mean climate in the northern midlatitudes.
Elliptic BCS-Richardson model and the modified algebraic Bethe ansatz
Authors: Skrypnyk T 
Published: March 2023

Abstract
We consider the elliptic Gaudin-type model in an external magnetic field (Skrypnyk T 2005 Phys. Lett. A 334 390–9; Skrypnyk T 2005 Phys. Lett. A 347 266–7; Skrypnyk T 2006 J. Geom. Phys.
57 53–67; Skrypnyk T 2006 J. Math. Phys.
47; Skrypnyk T 2007 J. Phys. A 40 1611–23; Skrypnyk T 2019 Nucl. Phys.
B 941 225–48) associated with non-skew-symmetric elliptic r-matrix (Skrypnyk T 2005 Phys. Lett. A 334 390–9; Skrypnyk T 2005 Phys. Lett. A 347 266–7; Skrypnyk T 2006 J. Geom. Phys.
57 53–67; Skrypnyk T 2006 J. Math. Phys.
47). Using them we construct a new integrable fermion Hamiltonian of the Richardson type. We use the modified algebraic Bethe ansatz obtained for integrable models with the considered elliptic r-matrix in (Skrypnyk T 2023 Nucl. Phys. B 988 116102) and find the spectrum of the obtained Richardson-type Hamiltonian in terms of solutions of the modified Bethe equations. The obtained results generalize our previous results on Richardson-type models (Skrypnyk T 2022 Nucl. Phys. B 975 115679).
Closed forms of the Zassenhaus formula
Authors: Dupays Léonce , Pain Jean-Christophe 
Published: March 2023

Abstract
The Zassenhaus formula finds many applications in theoretical physics or mathematics, from fluid dynamics to differential geometry. The non-commutativity of the elements of the algebra implies that the exponential of a sum of operators cannot be expressed as the product of exponentials of operators. The exponential of the sum can then be decomposed as the product of the exponentials multiplied by a supplementary term which takes generally the form of an infinite product of exponentials. Such a procedure is often referred to as ‘disentanglement’. However, for some special commutators, closed forms can be found. In this work, we propose a closed form for the Zassenhaus formula when the commutator of operators

X
ˆ

and

Y
ˆ

satisfy the relation

[

X
ˆ

,

Y
ˆ

]
=
u

X
ˆ

+
v

Y
ˆ

+
c
𝟙

. Such an expression boils down to three equivalent versions, a left-sided, a centered and a right-sided formula:

e

X
ˆ

+

Y
ˆ

=

e

X
ˆ

e

Y
ˆ

e

g

r

(
u
,
v
)
[

X
ˆ

,

Y
ˆ

]

=

e

X
ˆ

e

g

c

(
u
,
v
)
[

X
ˆ

,

Y
ˆ

]

e

Y
ˆ

=

e

g

ℓ

(
u
,
v
)
[

X
ˆ

,

Y
ˆ

]

e

X
ˆ

e

Y
ˆ

,

with respective arguments,

g

r

(
u
,
v
)
=

g

c

(
v
,
u
)

e

u

=

g

ℓ

(
v
,
u
)
=

u

e

u
−
v

−

e

u

+
v

e

u

−
1

v
u
(
u
−
v
)

for

u
≠
v

and

g

r

(
u
,
u
)
=

u
+
1
−

e
u

u
2

w
i
t
h

g
r

(
0
,
0
)
=
−
1

/

2.

With additional special case

g

r

(
0
,
v
)
=
−

e

−
v

−
1
+
v

v

2

,

g

r

(
u
,
0
)
=

e

u

(
1
−
u
)
−
1

u

2

.
Correlating surface topography of relaxed layer of ZA/ZrB2
in situ composites to wear and friction
Authors: Kumar Vineet , Gautam Gaurav , Ankit  , Mohan Anita , Mohan Sunil 
Published: March 2023

Abstract
In the present study, the correlation between the surface topography of relaxed layer and wear and friction has been investigated. For this purpose, the lubricating tribology and surface topography of insitu formed ZrB2 reinforced Zn-Al (ZA) composites have been studied. The wear and friction properties of composites have been evaluated on a pin-on-disc tribometer under synthetic SAE20W40 motor oil. The worn surface has been studied by SEM, AFM, and profilometer. Results indicate high wear resistance and low COF with smoother topography with ZrB2 reinforcement. The composite with 9 vol. % ZrB2 exhibits lower kurtosis and negative skewness values confirming the smoother topography with higher load-carrying capacity. This composite exhibits little wear and COF even at higher loads and sliding distances in the presence of lubricant. A comparative study with existing tribological materials indicates that the present materials have huge potential to be used as bearings and bushings.
A transfer learning based artificial neural network in geometrical design of textured surfaces for tribological applications
Authors: Mousavirad Seyed Jalaleddin , Rahmani Ramin , Dolatabadi Nader 
Published: March 2023

Abstract
This study aims at introducing the potential to utilise transfer learning methods in the training of artificial neural networks for tribological applications. Artificially enhanced surfaces through surface texturing, as an example, are investigated under hydrodynamic regime of lubrication. The performance of these surface features is assessed in terms of load carrying capacity and friction. A large performance dataset including bearing load carrying capacity and friction is initially obtained for a specific category of textures with rectangular cross-sectional profile through analytical methods. The produced bearing performance are used to train a neural network. This neural network was then trained further by a minimal set of performance measure data from an intended category of textures with triangular cross-sectional profiles. It is shown that the resulting neural network performs with acceptable level of confidence for those intended texture profiles when trained with such relatively low number of performance data points. The results indicate that fast analytical methods can potentially produce a large volume of training datasets, which effectively allows for use of relatively lower number of training data sets from the intended category, where creating data for trainings can be more complex or time consuming. Use of transfer learning method in tribological applications and use of bearing performance parameters, as opposed to bearing design parameters, for training the neural networks are the major novel contributions of this study, which has not hitherto been reported elsewhere.
A deep supervised cross-attention strategy for ischemic stroke segmentation in MRI studies
Authors: Gómez Santiago , Mantilla Daniel , Rangel Edgar , Ortiz Andrés , D Vera Daniela , Martínez Fabio 
Published: March 2023

Abstract
The key component of stroke diagnosis is the localization and delineation of brain lesions, especially from MRI studies. Nonetheless, this manual delineation is time-consuming and biased by expert opinion. The main purpose of this study is to introduce an autoencoder architecture that effectively integrates cross-attention mechanisms, together with hierarchical deep supervision to delineate lesions under scenarios of remarked unbalance tissue classes, challenging geometry of the shape, and a variable textural representation. This work introduces a cross-attention deep autoencoder that focuses on the lesion shape through a set of convolutional saliency maps, forcing skip connections to preserve the morphology of affected tissue. Moreover, a deep supervision training scheme was herein adapted to induce the learning of hierarchical lesion details. Besides, a special weighted loss function remarks lesion tissue, alleviating the negative impact of class imbalance. The proposed approach was validated on the public ISLES2017 dataset outperforming state-of-the-art results, achieving a dice score of 0.36 and a precision of 0.42. Deeply supervised cross-attention autoencoders, trained to pay more attention to lesion tissue, are better at estimating ischemic lesions in MRI studies. The best architectural configuration was achieved by integrating ADC, TTP and Tmax sequences. The contribution of deeply supervised cross-attention autoencoders allows better support the discrimination between healthy and lesion regions, which in consequence results in favorable prognosis and follow-up of patients.
Automatic measurement of slice thickness in CT images of a Siemens phantom
Authors: Amatullah Nada S , Anam Choirul , Hidayanto Eko , Naufal Ariij , Dougherty Geoff 
Published: March 2023

Abstract
This study aims to develop a program in Python language for automatic measurement of slice thickness in computed tomography (CT) images of a Siemens phantom with different values of slice thickness, field of view (FOV), and pitch. A Siemens phantom was scanned using a Siemens 64-slice Somatom Perspective CT scanner with various slice thicknesses (i.e. 2, 4, 6, 8, and 10 mm), FOVs (i.e. 220, 260, and 300 mm), and pitch (i.e. 0.7, 0.9, and 1). Automatic measurement of slice thickness was performed by segmenting the ramp insert in the image and detecting angles of the ramp insert using the Hough transform. The resulting angles were subsequently used to rotate the image. Profiles of pixel along the ramp insert were made from the rotated images, and the slice thickness was calculated by determining the full-width at half maximum (FWHM) of the profiles. The product of the FWHM in pixels and the pixel size was corrected by the tangent of the ramp insert (i.e., 23°) to obtain the measured slice thickness. The results of the automatic measurements were compared with manual measurements carried out using a MicroDicom Viewer. The differences between the automatic and manual measurements at all slice thicknesses were less than 0.30 mm. The automatic and manual measurements had high linear correlations. For variations of the FOV and pitch, the differences between the automatic and manual measurement were less than 0.16 mm. The automatic and manual measurements were significantly different (p-value < 0.05) for slice thickness variation. In addition, the automatic and manual measurements were not significantly different (p-value > 0.05) for variations of FOV and pitch.
Printing of electromagnetic interference shielding materials
Authors: Doshi Pranay , Wong Hiu Yung , Gutierrez Daniel H , Lopez Arlene , Nordlund Dennis , Gandhiraman Ram P 
Published: March 2023

Abstract
The proliferation of electronic devices has made electromagnetic interference (EMI) shielding an exponentially growing business. Regulatory requirements change constantly as new technologies continue to emerge. Innovations in materials and new advances in shielding implementation techniques are needed to pass regulatory compliance tests at an affordable cost. Here, we print various EMI shielding materials such as copper, silver and a composite of copper with Fe3O4 using plasma jet printing. Printing enables shields only a few microns thick capable of high shielding effectiveness. Copper’s EMI shielding performance is primarily contributed by reflection mechanism, as expected and this is known to cause secondary pollution. A Green Index for EMI shielding, given by the ratio of absorption and reflection contributions to shielding, indicates values lower than 0.1 for printed copper films.
Numerical and geometrical aspects of flow-based variational quantum Monte Carlo
Authors: Stokes James , Chen Brian , Veerapaneni Shravan 
Published: March 2023

Abstract
This article aims to summarize recent and ongoing efforts to simulate continuous-variable quantum systems using flow-based variational quantum Monte Carlo techniques, focusing for pedagogical purposes on the example of bosons in the field amplitude (quadrature) basis. Particular emphasis is placed on the variational real- and imaginary-time evolution problems, carefully reviewing the stochastic estimation of the time-dependent variational principles and their relationship with information geometry. Some practical instructions are provided to guide the implementation of a PyTorch code. The review is intended to be accessible to researchers interested in machine learning and quantum information science.
Coding for climate: sourcing better climate-health data from medical billing
Authors: Wheat Stefan , Sbiroli Emily , Dunn Marie , Chekuri Bhargavi , Millstein Amanda , O’Connor Terry , Rublee Caitlin , Lemery Jay , Limaye Vijay S 
Published: March 2023

Abstract
While evidence points to climate change adversely impacting health and wellbeing, there remains a great need for more authoritative and actionable data that better describes the full magnitude and scope of this growing crisis. Given the uncertainty inherent to current detection and attribution studies, the improved specificity offered by the 10th revision of the International Classification of Diseases (ICD-10) coding of climate-sensitive health outcomes at the point of care may help to better quantify the connection between more intense and frequent extreme weather events and specific health sequela. With improved application of the available ICD-10 codes designed to capture climate-sensitive health outcomes, the ICD-10 system can function as a leading indicator. In this collaboration, publicly available ICD-10 code data was downloaded from Centers for Medicare and Medicaid Services archives and cross-referenced with 29 keywords (e.g. heat, hurricane, smoke, etc) determined by relevance to climate impacts on human health from consensus literature. We identified 46 unique ICD-10 codes for climate-sensitive health conditions. By highlighting the need for broader application of these codes and advocating for the development of new codes that better document the growing burden of climate-sensitive health outcomes, we hope to drive the development of more evidence-based, health-protective interdisciplinary climate action strategies across health systems.
On asymptotic periodic solutions of fractional differential equations and applications
Authors: Luong Vu Trong , Huy Nguyen , Minh Nguyen , Vien Nguyen 
Published: March 2023

In this paper we study the asymptotic behavior of solutions of fractional differential equations of the form

D
C

α

u
(
t
)
=
A
u
(
t
)
+
f
(
t
)
,
u
(
0
)
=
x
,
0
>
α
≤
1
,
(
∗
)

D^{\alpha }_Cu(t)=Au(t)+f(t), u(0)=x, 0>\alpha \le 1, ( *)

where

D
C

α

u
(
t
)

D^{\alpha }_Cu(t)

is the derivative of the function

u
u

in the Caputo’s sense,

A
A

is a linear operator in a Banach space

X

\mathbb {X}

that may be unbounded and

f
f

satisfies the property that

lim

t
→
∞

(
f
(
t
+
1
)
−
f
(
t
)
)
=
0

\lim _{t\to \infty } (f(t+1)-f(t))=0

which we will call asymptotic

1
1

-periodicity. By using the spectral theory of functions on the half line we derive analogs of Katznelson-Tzafriri and Massera Theorems. Namely, we give sufficient conditions in terms of spectral properties of the operator

A
A

for all asymptotic mild solutions of Eq. (*) to be asymptotic

1
1

-periodic, or there exists an asymptotic mild solution that is asymptotic

1
1

-periodic.
Uniform Turán density of cycles
Authors: Bucić Matija , Cooper Jacob , Kráľ Daniel , Mohr Samuel , Munhá Correia David 
Published: March 2023

In the early 1980s, Erdős and Sós initiated the study of the classical Turán problem with a uniformity condition: the uniform Turán density of a hypergraph

H
H

is the infimum over all

d
d

for which any sufficiently large hypergraph with the property that all its linear-size subhypergraphs have density at least

d
d

contains

H
H

. In particular, they raise the questions of determining the uniform Turán densities of

K
4

(
3
)
−

K_4^{(3)-}

and

K
4

(
3
)

K_4^{(3)}

. The former question was solved only recently by Glebov, Král’, and Volec [Israel J. Math. 211 (2016), pp. 349–366] and Reiher, Rödl, and Schacht [J. Eur. Math. Soc. 20 (2018), pp. 1139–1159], while the latter still remains open for almost 40 years. In addition to

K
4

(
3
)
−

K_4^{(3)-}

, the only

3
3

-uniform hypergraphs whose uniform Turán density is known are those with zero uniform Turán density classified by Reiher, Rödl and Schacht [J. London Math. Soc. 97 (2018), pp. 77–97] and a specific family with uniform Turán density equal to

1

/

27

1/27

.

We develop new tools for embedding hypergraphs in host hypergraphs with positive uniform density and apply them to completely determine the uniform Turán density of a fundamental family of

3
3

-uniform hypergraphs, namely tight cycles

C
ℓ

(
3
)

C_\ell ^{(3)}

. The uniform Turán density of

C
ℓ

(
3
)

C_\ell ^{(3)}

,

ℓ
≥
5

\ell \ge 5

, is equal to

4

/

27

4/27

if

ℓ
\ell

is not divisible by three, and is equal to zero otherwise. The case

ℓ
=
5

\ell =5

resolves a problem suggested by Reiher.