bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Conductive Hydrogel‐Based Microneedle Platform for Real‐Time pH Measurement in Live Animals
Authors: Odinotski Sarah , Dhingra Karan , GhavamiNejad Amin , Zheng Hanjia , GhavamiNejad Peyman , Gaouda Hager , Mohammadrezaei Dorsa , Poudineh Mahla 
Published: September 2022

AbstractConventional microneedles (MNs) have been extensively reported and applied toward a variety of biosensing and drug delivery applications. Hydrogel forming MNs with the added ability to electrically track health conditions in real‐time is an area yet to be explored. The first conductive hydrogel microneedle (HMN) electrode that is capable of on‐needle pH detection with no postprocessing required is presented here. The HMN array is fabricated using a swellable dopamine (DA) conjugated hyaluronic acid (HA) hydrogel, and is embedded with poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) to increase conductivity. The catechol‐quinone chemistry intrinsic to DA is used to measure pH in interstitial fluid (ISF). The effect of PEDOT:PSS on the characteristics of the HMN array such as swelling capability and mechanical strength is fully studied. The HMN's capability for pH measurement is first demonstrated using porcine skin equilibrated with different pH solutions ranging from 3.5 to 9. Furthermore, the HMN‐pH meter is capable of in vivo measurements with a 93% accuracy compared to a conventional pH probe meter. This HMN technology bridges the gap between traditional metallic electrochemical biosensors and the direct extraction of ISF, and introduces a platform for the development of polymeric wearable sensors capable of on‐needle detection.
Engineering properties of structural lightweight concrete containing expanded shale and clay with high volume class F and class C fly ash
Authors: Mohammed Tijani , Aguayo Federico , Nodehi Mehrab , Ozbakkaloglu Togay 
Published: September 2022

AbstractStructural optimization is a broad term in the construction sector, whereby material efficiency, as well as cost effectiveness of structures, are optimized. In concrete technology, high‐performance lightweight concrete structures often represent such optimized properties, including cost‐effectiveness and ease of application, while having a lower structural dead load. Although the use of lightweight concrete is often viewed as a sustainable practice, it does not address the high use and dependance on Portland cement, which has a high ecological footprint. In this regard, this study evaluates the engineering properties of structural lightweight concrete containing expanded shale and clay, as coarse aggregate, with a high quantity of coal fly ash (class F and C). For this purpose, a total of 15 mixes have been produced and a comprehensive series of physico‐mechanical and durability tests have been conducted. Based on the results, it is found that expanded clay outperforms expanded shale in terms of physico‐mechanical and durability properties of the resulting concrete, potentially due to its lower particle size distribution (used in this study) and the resulting porosity compared to expanded shale. Nonetheless, comparable physico‐mechanical properties are achieved when expanded shale and clay are used, as a full replacement of limestone. In turn, the performance of class C fly ash is found to be better in mechanical, but lower in certain durability variables, compared to their class F companions. The result of this study is found significant and point to suitability of using expanded shale and clay in combination with high‐volume fly ash.
Developing language in a developing body, revisited: The cascading effects of motor development on the acquisition of language
Authors: Iverson Jana M. 
Published: September 2022

AbstractIn the first years of life, infants rapidly acquire a series of new motor skills. They learn to sit independently, to walk with skill, and to engage in a wide variety of interactions with objects. Over these same years, infants also begin to develop language. These are not isolated events. In a complex developing system, even small changes in one domain can have far‐reaching effects on development in other domains. This is the fundamental idea behind the rich framework known as thedevelopmental cascadesperspective. Here we employ this framework to show how early motor advances can exert downstream effects on the development of language. Focusing first on the emergence of independent sitting, then on the development of walking, and finally on changes in the ways in which infants act on and combine actions on objects, we describe how the nature and quality of infant actions change dramatically over the first few years and how this brings with it new possibilities for engaging the environment, more sophisticated ways of interacting with people, and significant alterations in communications directed by caregivers to the infant and coordinated with infant action in time and in meaning. The developmental cascades framework provides an approach for understanding how advances in motor skills influence communicative and language development, and more generally, for conceptualizing the constant, dynamic, and complex interplay between developing infants and their environments as it unfolds over time.This article is categorized under:Linguistics > Language AcquisitionPsychology > Motor Skill and PerformancePsychology > Development and Aging
Improving heavy Dirac neutrino prospects at future hadron colliders using machine learning
Authors: Feng Jie , Li Mingqiu , Yan Qi-Shu , Zeng Yu-Pan , Zhang Hong-Hao , Zhang Yongchao , Zhao Zhijie 
Published: September 2022

Abstract
In this work, by using the machine learning methods, we study the sensitivities of heavy pseudo-Dirac neutrino N in the inverse seesaw at the high-energy hadron colliders. The production process for the signal is pp → ℓ → 3ℓ + $$ {E}_T^{\mathrm{miss}} $$

E
T
miss

, while the dominant background is pp → WZ → 3ℓ + $$ {E}_T^{\mathrm{miss}} $$

E
T
miss

. We use either the Multi-Layer Perceptron or the Boosted Decision Tree with Gradient Boosting to analyse the kinematic observables and optimize the discrimination of background and signal events. It is found that the reconstructed Z boson mass and heavy neutrino mass from the charged leptons and missing transverse energy play crucial roles in separating the signal from backgrounds. The prospects of heavy-light neutrino mixing |VℓN|2 (with ℓ = e, μ) are estimated by using machine learning at the hadron colliders with $$ \sqrt{s} $$

s

= 14 TeV, 27 TeV, and 100 TeV, and it is found that |VℓN|2 can be improved up to $$ \mathcal{O} $$
O
(10−6) for heavy neutrino mass mN = 100 GeV and $$ \mathcal{O} $$
O
(10−4) for mN = 1 TeV.
The phase structure and effective action of 3D CDT at higher spatial genus
Authors: Brunekreef Joren , Németh Dániel 
Published: September 2022

Abstract
We perform a detailed investigation of the phase structure and the semiclassical effective action of (2+1)-dimensional Causal Dynamical Triangulations (CDT) quantum gravity using computer simulations. On the one hand, we study the effect of enlarging the ensemble of triangulations by relaxing the simplicial manifold conditions in a controlled way. On the other hand, we cast a first look at CDT geometries with spatial topology beyond that of the sphere or torus. We measure the phase structure of the model for several triangulation ensembles and spatial topologies, finding evidence that the phase structure is qualitatively unaffected by these generalizations. Furthermore, we determine the effective action for the spatial volumes of the system, again varying the simplicial manifold conditions and the spatial topology. In all cases where we were able to gather sufficient statistics, we found the resulting effective action to be consistent with a minisuperspace action derived from continuum Einstein gravity, although more work is needed to confirm this conclusion. We interpret our overall results as evidence that 1) partially relaxing simplicial manifold conditions or changing the spatial genus does not affect the continuum limit of 3D CDT and that 2) increasing the spatial genus of the system likely does not influence the leading-order terms in the emergent effective action.
Supersymmetric dS4 solutions in D = 11 supergravity
Authors: Di Gioia M. , Gutowski J. 
Published: September 2022

Abstract
The necessary and sufficient conditions for warped product dS4 solutions in D = 11 supergravity to be supersymmetric are determined. The Killing spinor is associated with two possible stabilizer groups, SU(3) and G2. We show that there are no solutions to the Killing Spinor equations in the G2 stabilizer case. For the SU(3) stablilzer case, all of the conditions imposed from supersymmetry on the 4-form flux, and the geometry of the internal manifold, are determined in terms of SU(3) invariant spinor bilinears.
Fundamental membranes and the string dilaton
Authors: Meissner Krzysztof A. , Nicolai Hermann 
Published: September 2022

AbstractWe study the quantization of the bosonic sector of supermembrane theory in double dimensional reduction, in order to extract the dependence of the resulting world-sheet action on the string dilaton (which cannot be obtained from a purely kinematic reduction). Our construction relies on a Polyakov-type approach with all six metric components on the world-volume as independent quantum fields, and shows that the correct and unique answer is only obtained if the target-space dimension of the theory is restricted to the critical value (D= 11 for the supermembrane). As a corollary, our analysis implies that there are no analogs of the non-critical string for (super-)membrane theory.
Morphological risk factors for scaphoid fracture: a case–control study
Authors: Cohen Abigael , Claessen Thomas , van den Berg Corne , Siebelt Michiel , Hagenaars Tjebbe , Kraan Gerald A. , Waarsing Johannes H. , Reijman Max , Colaris Joost W. 
Published: September 2022

Abstract
Purpose
Most patients with a clinically suspected scaphoid fracture and normal initial radiograph are unnecessarily treated. Previously developed prediction rules using demographic and clinical risk are unable to accurately predict occult fractures. Adding other risk factors could enhance this. Therefore, we aim to explore if there are morphological risk factors of the wrist for sustaining a scaphoid fracture.

Methods
We retrospectively included adult patients with a clinically suspected scaphoid fracture between 2013 and 2019 in our case–control study. There were 82 patients with a scaphoid fracture and 158 patients with a wrist contusion. Morphological risk factors were identified using statistical shape modelling (SSM) and linear measurements. Independent wrist shape variations on posteroanterior and lateral radiographs were captured in modes using SSM. Associations between outcomes and a scaphoid fracture were explored using logistic regression and the reliability was assessed.

Results
Of the 15 posteroanterior modes and 8 lateral modes identified and linear measurements performed, 1 PA mode was associated with a scaphoid fracture (PA mode 4; OR 1.40, CI 1.04–1.93, p = 0.031). We described this mode as an ulna plus and narrower distal radius with more volar tilt and radial inclination. The reliability of the posteroanterior modes and linear measurements was mostly good/excellent and moderate/poor for the lateral modes.

Conclusion
There was one complex wrist shape significantly associated with a scaphoid fracture. Since the association was weak and the shape is difficult to identify radiographs, we believe this morphological risk factor would not enhance identifying occult scaphoid fractures in the future.
Versorgernetzwerke für Menschen mit Seltenen Erkrankungen: Daten und Expertise bündeln
Authors: Graessner Holm , Storf Holger , Schaefer Franz 
Published: September 2022

ZusammenfassungAls Seltene Erkrankungen (SE) gelten in der Europäischen Union (EU) Krankheiten, von denen nicht mehr als 5 von 10.000 Menschen betroffen sind. Aufgrund ihrer Seltenheit sind klinische Expertise und qualitätsgesicherte Versorgungsstrukturen rar, die Forschung ist hier im Vergleich zu anderen Krankheiten erschwert. Diese Probleme können jedoch mittels nationaler und länderübergreifender SE-Versorgernetzwerke überwunden werden. Daten und Expertise werden darin gebündelt.In der Europäischen Union arbeiten die Europäischen Referenznetzwerke (ERN) für Seltene und Komplexe Erkrankungen grenzübergreifend zusammen. Wichtige Leistungen der ERN unter Nutzung von Gesundheitsdaten umfassen die diagnostische Kodierung der SE, die Durchführung von virtuellen, grenzübergreifenden Fallkonferenzen und die Etablierung von europäischen Registern, die zur Messung und Verbesserung der Versorgungsqualität genutzt werden. In den ERN verbinden sich die lokale Datenerzeugung und Dokumentation mit netzwerkweiten Dateninfrastrukturen. In diesem Beitrag werden die datenbasierten Leistungen in und für SE-Versorgernetzwerke beschrieben: 1) diagnostische Kodierung, 2) grenzüberschreitende Fallkonferenzen und 3) ERN-Register für die Versorgung der SE-Patient*innen. Im letzten Abschnitt wird auf die Integration der Netzwerke in die nationalen Gesundheitssysteme eingegangen.Um einen bestmöglichen Nutzen für die SE-Patient*innen erzielen zu können, müssen die ERN-Aktivitäten und -Strukturen noch besser in die nationalen Gesundheitssysteme integriert werden. In Deutschland nehmen diesbezüglich die Medizininformatik-Initiative und die Deutschen Referenznetzwerke eine zentrale Rolle ein.
Modelling and prediction of GNSS time series using GBDT, LSTM and SVM machine learning approaches
Authors: Gao Wenzong , Li Zhao , Chen Qusen , Jiang Weiping , Feng Yanming 
Published: September 2022

AbstractGlobal navigation satellite system (GNSS) site coordinate time series provides essential data for geodynamic and geophysical studies, realisation of a regional or global geodetic reference frames, and crustal deformation research. The coordinate time series has been conventionally modelled by least squares (LS) fitting with harmonic functions, alongside many other analysis methods. As a key limitation, the traditional modelling approaches simply use the functions of time variable, despite good knowledge of various underlying physical mechanisms responsible for the site displacements. This paper examines the use of machine learning (ML) models to reflect the effects or residential effects of physical variables related to Sun and the Moon ephemerides, polar motion, temperature, atmospheric pressure, and hydrology on the site displacements. To form the ML problem, these variables are constructed as the input vector of each ML training sample, while the vertical displacement of a GNSS site is regarded as the output value. In the evaluation experiments, three ML approaches, namely the gradient boosting decision tree (GBDT) approach, long short-term memory (LSTM) approach, and support vector machine (SVM) approach, are introduced and evaluated with the time series datasets collected from 9 GNSS sites over the period of 13 years. The results indicate that all three approaches achieve similar fitting precision in the range of 3–5 mm in the vertical displacement component, which is an improvement in over 30% with respect to the traditional LS fitting precision in the range of 4–7 mm. The prediction of the vertical time series with the three ML approaches shows the precision in the range of 4–7 mm over the future 24- month period. The results also indicate the relative importance of different physical features causing the displacements of each site. Overall, ML approaches demonstrate better performance and effectiveness in modelling and prediction of GNSS time series, thus impacting maintenance of geodetic reference frames, geodynamics, geophysics, and crustal deformation analysis.
Time dependency of automated collateral scores in computed tomography angiography and computed tomography perfusion images in patients with intracranial arterial occlusion
Authors: Su Jiahang , Wolff Lennard , van Doormaal Pieter Jan , Dippel Diederik W.J. , van Zwam Wim , Niessen Wiro J , van der Lugt Aad , van Walsum Theo 
Published: September 2022

Abstract
Purpose
The assessment of collateral status may depend on the timing of image acquisition. The purpose of this study is to investigate whether there are optimal time points in CT Perfusion (CTP) for collateral status assessment, and compare collaterals scores at these time points with collateral scores from multiphase CT angiography (mCTA).

Methods
Patients with an acute intracranial occlusion who underwent baseline non-contrast CT, mCTA and CT perfusion were selected. Collateral status was assessed using an automatically computed Collateral Ratio (CR) score in mCTA, and predefined time points in CTP acquisition. CRs extracted from CTP were correlated with CRs from mCTA. In addition, all CRs were related to baseline National Institutes of Health Stroke Scale (NIHSS) and Alberta Stoke Program Early CT Score (ASPECTS) with linear regression analysis to find the optimal CR.

Results
In total 58 subjects (median age 74 years; interquartile range 61–83 years; 33 male) were included. When comparing the CRs from the CTP vs. mCTA acquisition, the strongest correlations were found between CR from baseline mCTA and the CR at the maximal intensity projection of time-resolved CTP (r = 0.81) and the CR at the peak of arterial enhancement point (r = 0.78). Baseline mCTA-derived CR had the highest correlation with ASPECTS (β = 0.36 (95%CI 0.11, 0.61)) and NIHSS (β = − 0.48 (95%CI − 0.72, − 0.16)).

Conclusion
Collateral status assessment strongly depends on the timing of acquisition. Collateral scores obtained from mCTA imaging is close to the optimal collateral score obtained from CTP imaging.
[11C]carfentanil PET imaging for studying the peripheral opioid system in vivo: effect of photoperiod on mu-opioid receptor availability in brown adipose tissue
Authors: Sun Lihua , Aarnio Richard , Herre Erika Atencio , Kärnä Salli , Palani Senthil , Virtanen Helena , Liljenbäck Heidi , Virta Jenni , Honkaniemi Aake , Oikonen Vesa , Han Chunlei , Laurila Sanna , Bucci Marco , Helin Semi , Yatkin Emrah , Nummenmaa Lauri , Nuutila Pirjo , Tang Jing , Roivainen Anne 
Published: September 2022

Abstract

Purpose
Photoperiod determines the metabolic activity of brown adipose tissue (BAT) and affects the food intake and body mass of mammals. Sympathetic innervation of the BAT controls thermogenesis and facilitates physiological adaption to seasonal changes, but the exact mechanism remains elusive. Previous studies have shown that central opioid signaling regulates BAT thermogenesis, and that the expression of the brain mu-opioid receptor (MOR) varies seasonally. Therefore, it is important to know whether MOR expression in BAT shows seasonal variation.

Methods
We determined the effect of photoperiod on BAT MOR availability using [11C]carfentanil positron emission tomography (PET). Adult rats (n = 9) were repeatedly imaged under various photoperiods in order to simulate seasonal changes.

Results
Long photoperiod was associated with low MOR expression in BAT (β =  − 0.04, 95% confidence interval: − 0.07, − 0.01), but not in muscles. We confirmed the expression of MOR in BAT and muscle using immunofluorescence staining.

Conclusion
Photoperiod affects MOR availability in BAT. Sympathetic innervation of BAT may influence thermogenesis via the peripheral MOR system. The present study supports the utility of [11C]carfentanil PET to study the peripheral MOR system.
Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor
Authors: Zwezerijnen Gerben J. C. , Eertink Jakoba J. , Ferrández Maria C. , Wiegers Sanne E. , Burggraaff Coreline N. , Lugtenburg Pieternella J. , Heymans Martijn W. , de Vet Henrica C. W. , Zijlstra Josée M. , Boellaard Ronald 
Published: September 2022

Abstract
Introduction
Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics.

Methods
PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans.

Results
Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15–18% and 9–18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images.

Conclusion
SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies.

Trial registration
EudraCT: 2006–005,174-42, 01–08-2008.
Noise-driven bifurcations in a neural field system modelling networks of grid cells
Authors: Carrillo José A. , Holden Helge , Solem Susanne 
Published: September 2022

AbstractThe activity generated by an ensemble of neurons is affected by various noise sources. It is a well-recognised challenge to understand the effects of noise on the stability of such networks. We demonstrate that the patterns of activity generated by networks of grid cells emerge from the instability of homogeneous activity for small levels of noise. This is carried out by analysing the robustness of network activity patterns with respect to noise in an upscaled noisy grid cell model in the form of a system of partial differential equations. Inhomogeneous network patterns are numerically understood as branches bifurcating from unstable homogeneous states for small noise levels. We show that there is a phase transition occurring as the level of noise decreases. Our numerical study also indicates the presence of hysteresis phenomena close to the precise critical noise value.