bluuebunny/crossref_metadata_2025_split huggingface dataset:
A machine learning approach for investigation of the natural frequency of a nitinol-reinforced composite beam
Authors: Rane Santosh B , Patil Ranjit Anil , Raykar N R , Kumbhar Samir B 
Published: November 2023

Abstract
Many applications are using composites to improve performance and reduce weight, but it is essential to know the different properties of the composite before manufacturing. Properties like natural frequency and elastic modulus are also crucial in many applications. The use of shape memory alloys (SMA) composite has increased in the last few years due to various advantages of the shape memory alloys, like a shift in natural frequency and elastic modulus during phase transformation. Hence it is essential to know the composite’s natural frequency and elastic modulus before constructing it. Although experimental and numerical methods for calculating natural frequency exist, they are time-consuming and infrastructure-dependent. This paper explores relationships between SMA composite construction parameters and natural frequency to predict it better. Nitinol-reinforced silicon rubber composite beams are investigated with various parametric combinations using an orthogonal array. Different machine-learning techniques are applied for natural frequency prediction after training models on numerical results from varied construction combinations. The study identifies the best-performing algorithm and provides tuning recommendations. Linear regression model, Ridge regression model, and Decision Tree regression are the best-performing algorithms for the dataset in this paper. A weighted sum method finds optimal construction parameters for maximum natural frequency. These models can predict natural frequency before construction and the shift during SMA phase transformation. The research aids in designing SMA-reinforced beams by identifying optimal parameters like volume fraction, location, and activation pattern, targeting maximum natural frequency. The composite studied in this research shows a maximum natural frequency of 19.58 Hz for a 3.53% volume fraction of SMA, 3 mm distance of reinforcement, all wires activated, and austenite temperature.
Improved decision making with similarity based machine learning: applications in chemistry
Authors: Lemm Dominik , Falk von Rudorff Guido , Anatole von Lilienfeld O 
Published: November 2023

AbstractDespite the fundamental progress in autonomous molecular and materials discovery, data scarcity throughout chemical compound space still severely hampers the use of modern ready-made machine learning models as they rely heavily on the paradigm, ‘the bigger the data the better’. Presenting similarity based machine learning (SML), we show an approach to select data and train a model on-the-fly for specific queries, enabling decision making in data scarce scenarios in chemistry. By solely relying on query and training data proximity to choose training points, only a fraction of data is necessary to converge to competitive performance. After introducing SML for the harmonic oscillator and the Rosenbrock function, we describe applications to scarce data scenarios in chemistry which include quantum mechanics based molecular design and organic synthesis planning. Finally, we derive a relationship between the intrinsic dimensionality and volume of feature space, governing the overall model accuracy.
Machine learning of microscopic structure-dynamics relationships in complex molecular systems
Authors: Crippa Martina , Cardellini Annalisa , Cioni Matteo , Csányi Gábor , Pavan Giovanni M 
Published: November 2023

Abstract
In many complex molecular systems, the macroscopic ensemble’s properties are controlled by microscopic dynamic events (or fluctuations) that are often difficult to detect via pattern-recognition approaches. Discovering the relationships between local structural environments and the dynamical events originating from them would allow unveiling microscopic-level structure-dynamics relationships fundamental to understand the macroscopic behavior of complex systems. Here we show that, by coupling advanced structural (e.g. Smooth Overlap of Atomic Positions, SOAP) with local dynamical descriptors (e.g. Local Environment and Neighbor Shuffling, LENS) in a unique dataset, it is possible to improve both individual SOAP- and LENS-based analyses, obtaining a more complete characterization of the system under study. As representative examples, we use various molecular systems with diverse internal structural dynamics. On the one hand, we demonstrate how the combination of structural and dynamical descriptors facilitates decoupling relevant dynamical fluctuations from noise, overcoming the intrinsic limits of the individual analyses. Furthermore, machine learning approaches also allow extracting from such combined structural/dynamical dataset useful microscopic-level relationships, relating key local dynamical events (e.g. LENS fluctuations) occurring in the systems to the local structural (SOAP) environments they originate from. Given its abstract nature, we believe that such an approach will be useful in revealing hidden microscopic structure-dynamics relationships fundamental to rationalize the behavior of a variety of complex systems, not necessarily limited to the atomistic and molecular scales.
Scalable quantum measurement error mitigation via conditional independence and transfer learning
Authors: Lee Changwon , Park Daniel K 
Published: November 2023

Abstract
Mitigating measurement errors in quantum systems without relying on quantum error correction is of critical importance for the practical development of quantum technology. Deep learning-based quantum measurement error mitigation (QMEM) has exhibited advantages over the linear inversion method due to its capability to correct non-linear noise. However, scalability remains a challenge for both methods. In this study, we propose a scalable QMEM method that leverages the conditional independence (CI) of distant qubits and incorporates transfer learning (TL) techniques. By leveraging the CI assumption, we achieve an exponential reduction in the size of neural networks used for error mitigation. This enhancement also offers the benefit of reducing the number of training data needed for the machine learning model to successfully converge. Additionally, incorporating TL provides a constant speedup. We validate the effectiveness of our approach through experiments conducted on IBM quantum devices with 7 and 13 qubits, demonstrating excellent error mitigation performance and highlighting the efficiency of our method.
Convergence rate to equilibrium for conservative scattering models on the torus: a new tauberian approach
Authors: Lods B. , Mokhtar-Kharroubi M. 
Published: November 2023

The object of this paper is to provide a new and systematic tauberian approach to quantitative long time behaviour of

C

0

C_{0}

-semigroups

(

V

(
t
)
)

t
⩾
0

\left (\mathcal {V}(t)\right )_{t \geqslant 0}

in

L

1

(

T

d

×

R

d

)

L^{1}(\mathbb {T}^{d}\times \mathbb {R}^{d})

governing conservative linear kinetic equations on the torus with general scattering kernel

k
(
v
,

v
′

)

\boldsymbol {k}(v,v’)

and degenerate (i.e. not bounded away from zero) collision frequency

σ
(
v
)
=

∫

R

d

k
(

v
′

,
v
)
m
(

d

v
′

)

\sigma (v)=\int _{\mathbb {R}^{d}}\boldsymbol {k}(v’,v)\boldsymbol {m}(\mathrm {d}v’)

, (with

m
(

d

v
)

\boldsymbol {m}(\mathrm {d}v)

being absolutely continuous with respect to the Lebesgue measure). We show in particular that if

N

0

N_{0}

is the maximal integer

s
⩾
0

s \geqslant 0

such that

1

σ
(
⋅
)

∫

R

d

k
(
⋅
,
v
)

σ

−
s

(
v
)
m
(

d

v
)
∈

L

∞

(

R

d

)
,

\begin{equation*} \frac {1}{\sigma (\cdot )}\int _{\mathbb {R}^{d}}\boldsymbol {k}(\cdot ,v)\sigma ^{-s}(v)\boldsymbol {m}(\mathrm {d}v) \in L^{\infty }(\mathbb {R}^{d}), \end{equation*}

then, for initial datum

f
f

such that

∫

T

d

×

R

d

|

f
(
x
,
v
)

|

σ

−

N

0

(
v
)

d

x
m
(

d

v
)
>
∞

\displaystyle \int _{\mathbb {T}^{d}\times \mathbb {R}^{d}}|f(x,v)|\sigma ^{-N_{0}}(v)\mathrm {d}x\boldsymbol {m}(\mathrm {d}v) >\infty

it holds

‖

V

(
t
)
f
−

ϱ

f

Ψ
‖

L

1

(

T

d

×

R

d

)

=

ε

f

(
t
)

(
1
+
t

)

N

0

−
1

,

ϱ

f

≔

∫

R

d

f
(
x
,
v
)

d

x
m
(

d

v
)
,

\begin{equation*} \left \|\mathcal {V}(t)f-\varrho _{f}\Psi \right \|_{L^{1}(\mathbb {T}^{d}\times \mathbb {R}^{d})}=\dfrac {{\varepsilon }_{f}(t)}{(1+t)^{N_{0}-1}}, \qquad \varrho _{f}≔\int _{\mathbb {R}^{d}}f(x,v)\mathrm {d}x\boldsymbol {m}(\mathrm {d}v), \end{equation*}

where

Ψ
\Psi

is the unique invariant density of

(

V

(
t
)
)

t
⩾
0

\left (\mathcal {V}(t)\right )_{t \geqslant 0}

and

lim

t
→
∞

ε

f

(
t
)
=
0

\lim _{t\to \infty }{\varepsilon }_{f}(t)=0

. We in particular provide a new criteria of the existence of invariant density. The proof relies on the explicit computation of the time decay of each term of the Dyson-Phillips expansion of

(

V

(
t
)
)

t
⩾
0

\left (\mathcal {V}(t)\right )_{t \geqslant 0}

and on suitable smoothness and integrability properties of the trace on the imaginary axis of Laplace transform of remainders of large order of this Dyson-Phillips expansion. Our construction resorts also on collective compactness arguments and provides various technical results of independent interest. Finally, as a by-product of our analysis, we derive essentially sharp “subgeometric” convergence rate for Markov semigroups associated to general transition kernels.
Playing with second language metaphor: An exploration with advanced Chinese learners of English
Authors: O’Reilly David , Yan Luling 
Published: November 2023

Abstract
The present study continues research that takes non-serious language more seriously (Cekaite and Aronsson 2005) by focusing on a central second language (L2) Metaphoric Competence factor, Metaphor Language Play (MLP). For willing learners, MLP offers a diversity of benefits (Bushnell 2009; Bell 2012a) despite being one of the most challenging Metaphoric Competence aspects (O’Reilly and Marsden 2021). While studies provide rich descriptions of naturally occurring MLP, elicitation approaches are needed to target comprehension/production of specific forms/meanings/usages and types of play, for example, comprehension of US sitcom humour (Dore 2015). With 69 advanced first-language Mandarin L2 English learners, we addressed these issues via an Exploratory Factor Analysis to uncover hitherto unknown relationships between written/spoken/receptive/productive MLP measures, and a thematic analysis of the linguistic, conceptual, and metalinguistic themes in learners’ MLP. The findings revealed three underlying MLP factors, two positively related, and a rich set of linguistic, conceptual, and metalinguistic themes. The implications of findings for future research and pedagogy are discussed.
deepFPlearn
+: enhancing toxicity prediction across the chemical universe using graph neural networks
Authors: Soulios Kyriakos , Scheibe Patrick , Bernt Matthias , Hackermüller Jörg , Schor Jana 
Published: November 2023

Abstract

Summary
Sophisticated approaches for the in silico prediction of toxicity are required to support the risk assessment of chemicals. The number of chemicals on the global chemical market and the speed of chemical innovation stand in massive contrast to the capacity for regularizing chemical use. We recently proved our ready-to-use application deepFPlearn as a suitable approach for this task. Here, we present its extension deepFPlearn+ incorporating (i) a graph neural network to feed our AI with a more sophisticated molecular structure representation and (ii) alternative train-test splitting strategies that involve scaffold structures and the molecular weights of chemicals. We show that the GNNs outperform the previous model substantially and that our models can generalize on unseen data even with a more robust and challenging test set. Therefore, we highly recommend the application of deepFPlearn+ on the chemical inventory to prioritize chemicals for experimental testing or any chemical subset of interest in monitoring studies.

Availability and implementation
The software is compatible with python 3.6 or higher, and the source code can be found on our GitHub repository: https://github.com/yigbt/deepFPlearn. The data underlying this article are available in Zenodo, and can be accessed with the link below: https://zenodo.org/record/8146252. Detailed installation guides via Docker, Singularity, and Conda are provided within the repository for operability across all operating systems.
Diverse macrophage populations contribute to distinct manifestations of human cutaneous graft-versus-host disease
Authors: Strobl Johanna , Gail Laura M , Krecu Laura , Madad Shaista , Kleissl Lisa , Unterluggauer Luisa , Redl Anna , Brazdilova Kveta , Saluzzo Simona , Wohlfarth Philipp , Knaus Hanna A , Mitterbauer Margit , Rabitsch Werner , Haniffa Muzlifah , Stary Georg 
Published: November 2023

Abstract

Background
Graft-versus-host disease (GvHD) is a major life-threatening complication of allogeneic haematopoietic stem cell transplantation (HSCT), limiting the broad application of HSCT for haematological malignancies. Cutaneous GvHD is described as a post-transplant inflammatory reaction by skin-infiltrating donor T cells and remaining recipient tissue-resident memory T cells. Despite the major influence of lymphocytes on GvHD pathogenesis, the complex role of mononuclear phagocytes (MNPs) in tissues affected by GvHD is increasingly appreciated.

Objectives
To characterize the identity, origin and functions of MNPs in patients with acute cutaneous GvHD.

Methods
Using single-cell RNA sequencing and multiplex tissue immunofluorescence, we identified an increased abundance of MNPs in skin and blood from 36 patients with acute cutaneous GvHD. In cases of sex-mismatched transplantation, we used expression of X-linked genes to detect rapid tissue adaptation of newly recruited donor MNPs resulting in similar transcriptional states of host- and donor-derived macrophages within GvHD skin lesions.

Results
We showed that cutaneous GvHD lesions harbour expanded CD163+ tissue-resident macrophage populations with anti-inflammatory and tissue-remodelling properties including interleukin-10 cytokine production. Cell–cell interaction analyses revealed putative signalling to strengthen regulatory T-cell responses. Notably, macrophage polarization in chronic cutaneous GvHD types was proinflammatory and drastically differed from acute GvHD, supporting the notion of distinct cellular players in different clinical GvHD subtypes.

Conclusions
Overall, our data reveal a surprisingly dynamic role of MNPs after HSCT. Specific and time-resolved targeting to repolarize this cell subset may present a promising therapeutic strategy in combatting GvHD skin inflammation.
Subcortical grey matter volume and asymmetry in the long-term course of Rasmussen’s encephalitis
Authors: Bauer Tobias , Reiter Johannes T , Enders Selma , Keil Vera C W , Radbruch Alexander , Helmstaedter Christoph , Surges Rainer , Rüber Theodor 
Published: November 2023

Abstract
Rasmussen’s encephalitis is characterized by drug-resistant focal seizures and chronic inflammation of one hemisphere leading to progressive loss of hemispheric volume. In this cohort study, we aimed to investigate subcortical grey matter volumes and asymmetries in Rasmussen’s encephalitis longitudinally in clinically relevant subgroups. We retrospectively included all T1-weighted MRI scans of all people with Rasmussen’s encephalitis who were treated at the University Hospital Bonn between 1995 and 2022 (n = 56, 345 scans, median onset 8 years, 36 female). All cases were classified as type 1 (onset ≤ 6 years) or type 2 (onset &gt; 6 years). Subcortical segmentations were performed using FreeSurfer. Longitudinal trajectories of subcortical volumes and hemispheric ratios (ipsi-/contralesional) were assessed using linear mixed-effect models. Unihemispheric cortical degeneration was accompanied by ipsilesional atrophy of the nucleus accumbens, caudate nucleus, putamen, thalamus and contralesional atrophy of the nucleus accumbens and caudate nucleus both in type 1 (all P ≤ 0.014) and type 2 (all P &lt; 0.001). In type 1, however, contralesional volume increase of the amygdala, hippocampus, pallidum and thalamus was found (all P ≤ 0.013). Both ipsilesional and contralesional subcortical atrophies, like cortical atrophy, are most probably caused by neurodegeneration following chronic neuroinflammation. We speculate that contralesional volume increase in type 1 could be related to either neuroplasticity or ongoing acute neuroinflammation, which needs to be investigated in further studies.
Dupilumab-associated inflammatory arthritis: a literature review
Authors: Napolitano Maddalena , Ruggiero Angelo , Patruno Cataldo 
Published: November 2023

Abstract
Dupilumab is a fully human monoclonal antibody that acts by inhibiting the interleukin (IL)-4 receptor subunit α, and hence the IL-4 and IL-13 signalling pathway. Dupilumab treatment has been linked to the onset of T helper 17-driven inflammatory diseases, including cases of seronegative arthritis and enthesitis. To date, dupilumab-associated inflammatory arthritis (DAIA) represents a relatively unknown adverse event, initially reported in single cases or case series reports. Indeed, the onset of DAIA may not be promptly recognized, and is probably underestimated. Here we have reviewed the available English literature regarding arthritis and enthesitis onset during dupilumab treatment for atopic dermatitis, aiming to improve rapid recognition and thus prompt treatment of these diseases.
Characterization of skin barrier defects using infrared spectroscopy in patients with atopic dermatitis
Authors: Williams Samuel F , Wan Helen , Chittock John , Brown Kirsty , Wigley Andrew , Cork Michael J , Danby Simon G 
Published: November 2023

Abstract

Background
Atopic dermatitis (AD) is characterized by skin barrier defects that are often measured by biophysical tools that observe the functional properties of the stratum corneum (SC).

Objectives
To employ in vivo infrared spectroscopy alongside biophysical measurements to analyse changes in the chemical composition of the SC in relation to AD severity.

Methods
We conducted an observational cross-sectional cohort study where attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy measurements were collected on the forearm alongside surface pH, capacitance, erythema and transepidermal water loss (TEWL), combined with tape stripping, in a cohort of 75 participants (55 patients with AD stratified by phenotypic severity and 20 healthy controls). Common FLG variant alleles were genotyped.

Results
Reduced hydration, elevated TEWL and redness were all associated with greater AD severity. Spectral analysis showed a reduction in 1465 cm–1 (full width half maximum) and 1340 cm–1 peak areas, indicative of less orthorhombic lipid ordering and reduced carboxylate functional groups, which correlated with clinical severity (lipid structure r = –0.59, carboxylate peak area r = –0.50).

Conclusions
ATR-FTIR spectroscopy is a suitable tool for the characterization of structural skin barrier defects in AD and has potential as a clinical tool for directing individual treatment based on chemical structural deficiencies.
Left-sided primary cardiac lymphoma diagnosed by needle biopsy with total endoscopic anterolateral mini-thoracotomy: a case report
Authors: Sano Madoka , Okada Taiji , Yamashita Daisuke , Koyama Tadaaki , Furukawa Yutaka 
Published: November 2023

Abstract

Background
Primary cardiac lymphoma (PCL) is an extremely rare tumour that typically affects the right heart chamber. It is a life-threatening tumour presenting with rapid growth; therefore, early diagnosis and treatment are crucial for improving the prognosis of patients with PCL.

Case summary
An 81-year-old female with a history of dermatomyositis and interstitial pneumonia was referred to the cardiology department for cardiomegaly detected on chest radiography and computed tomography (CT). She experienced shortness of breath on exertion. Electrocardiography revealed negative T-waves in various leads. Transthoracic and transoesophageal echocardiography revealed a large mass on the epicardial free wall of the left atrium and ventricle. Coronary CT angiography showed feeding vessels from the left circumflex artery and the posterolateral branch of the right coronary artery. Positron emission tomography showed elevated mass uptake and no systemic metastasis. Needle biopsy with total endoscopic anterolateral mini-thoracotomy was performed. Histopathological examination revealed diffuse large B-cell lymphoma. She received systemic chemotherapy and achieved a complete metabolic response.

Discussion
Herein, we report an extremely rare case of PCL located on the left side of the heart. Owing to the location of the tumour, percutaneous or transcatheter biopsy could not be performed. Early diagnosis with needle biopsy via anterolateral mini-thoracotomy and systemic chemotherapy resulted in good outcomes.
Recurrent giant cell myocarditis following orthotopic heart transplant resulting in urgent redo orthotopic heart transplantation: a case report
Authors: AlJohani Abdullah , Solomon Joshua , Joury Abdulaziz , Cecere Renzo , Giannetti Nadia 
Published: November 2023

Abstract

Background
Giant cell myocarditis (GCM) is a severe and rapidly progressing condition that can lead to end-stage heart failure. We present a case of a 51-year-old male with a history of orthotopic heart transplantation (OHTx) for GCM, who experienced recurrent GCM in the allograft, leading to progressive heart failure and the need for a second heart transplant.

Case summary
A 51-year-old male with a history of OHTx for GCM presented with rapidly worsening heart failure symptoms. Despite initial stability, he deteriorated to cardiogenic shock and required intensive support. His clinical course was complicated by recurrent COVID-19 infections, worsened left ventricular ejection fraction, and withdrawal of guideline-directed medical therapy. Imaging showed extensive scar burden, and subsequent investigations ruled out coronary artery disease. With declining functional status and worsening cardiogenic shock, he was re-listed for OHTx and successfully underwent a second heart transplant.

Discussion
Giant cell myocarditis poses challenges due to its aggressive nature. Early, aggressive immunosuppression and mechanical circulatory support are crucial. The recurrence rate of GCM post-OHTx is notable, often within the first year, and the optimal immunosuppressive regimen remains uncertain. In this case, GCM recurrence following OHTx led to continued deterioration despite treatment, necessitating a second heart transplant. This unique case emphasizes the complexity of managing recurrent GCM post-OHTx.