bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mass and density determination of porous nanoparticle films using a quartz crystal microbalance
Authors: van Ginkel Hendrik Joost , Vollebregt Sten , Schmidt-Ott Andreas , Zhang Guo Qi 
Published: June 2022

Abstract
A method is presented to directly measure the mass output of an impaction printer coupled with a spark ablation generator. It is based on a quartz crystal microbalance and shown to be reliable in quantifying mass deposition rate. Here, the method is demonstrated with an Au nanoparticle aerosol synthesized under several spark ablation and deposition settings. Changes in the deposition rate in response to changed synthesis conditions follow the spark ablation models on generation rate made in previous studies, validating this novel measurement method. In combination with the volume of a deposit, a good estimate of the film porosity can be made. The Au nanoparticle films synthesized here have a low porosity of 0.18 due to extensive restructuring and compaction on impact with the substrate. The porosity is found to be insensitive to deposition settings and is constant throughout the film. The simplicity and low cost of a quartz crystal microbalance setup make this an accessible method to determine porosity in porous thin films.
Self-assembly of anisotropy gold nanocubes into large area two-dimensional monolayer superlattices
Authors: Li Jinlan , Liu Xuejie , Jin Jing , Yan Nan , Jiang Wei 
Published: June 2022

Abstract
The spontaneous self-assembly of metal nanocrystals into two-dimensional (2D) monolayer superlattices with highly ordered symmetry and configuration paves the way towards the fabrication of functional materials. However, there remains great challenge for anisotropic nanocrystals to self-assembly into high quality superlattice because of the orientation and configuration consistency. Here, a facile yet universal solvent annealing driven 2D interfacial assembly of synthetic dried metal nanocrystals is firstly developed to realize the construction of the non-close-packing 2D monolayer gold nanocube (AuNC) superlattice with tunable interparticle distance and internal configurations (i.e. face-to-face and hexagonally-packed arrangement), which is achieved by precisely controlling molecular weight of polymer ligands tethered on AuNCs and the van der Waals forces between the adjacent AuNCs. In addition, the scale of the generated 2D monolayer AuNC superlattice with highly ordered internal arrangement and orientation can reach up to hundreds of micrometers, thus acquiring significant surface-enhanced Raman scattering performance of the large scale superlattice due to the strong plasma coupling effect. This strategy not only provides a robust route to fabricate nanocrystal superlattice structures but also offers a promising platform for preparing diverse functional materials with potential applications in electronics, photonics, detections, and others.
A personalized deep learning denoising strategy for low-count PET images
Authors: Liu Qiong , Liu Hui , Mirian Niloufar , Ren Sijin , Viswanath Varsha , Karp Joel , Surti Suleman , Liu Chi 
Published: June 2022

Abstract

Objective. Deep learning denoising networks are typically trained with images that are representative of the testing data. Due to the large variability of the noise levels in positron emission tomography (PET) images, it is challenging to develop a proper training set for general clinical use. Our work aims to develop a personalized denoising strategy for the low-count PET images at various noise levels. Approach. We first investigated the impact of the noise level in the training images on the model performance. Five 3D U-Net models were trained on five groups of images at different noise levels, and a one-size-fits-all model was trained on images covering a wider range of noise levels. We then developed a personalized weighting method by linearly blending the results from two models trained on 20%-count level images and 60%-count level images to balance the trade-off between noise reduction and spatial blurring. By adjusting the weighting factor, denoising can be conducted in a personalized and task-dependent way. Main results. The evaluation results of the six models showed that models trained on noisier images had better performance in denoising but introduced more spatial blurriness, and the one-size-fits-all model did not generalize well when deployed for testing images with a wide range of noise levels. The personalized denoising results showed that noisier images require higher weights on noise reduction to maximize the structural similarity and mean squared error. And model trained on 20%-count level images can produce the best liver lesion detectability. Significance. Our study demonstrated that in deep learning-based low dose PET denoising, noise levels in the training input images have a substantial impact on the model performance. The proposed personalized denoising strategy utilized two training sets to overcome the drawbacks introduced by each individual network and provided a series of denoised results for clinical reading.
Exploring novel algorithms for atrial fibrillation detection by driving graduate level education in medical machine learning
Authors: Rohr Maurice , Reich Christoph , Höhl Andreas , Lilienthal Timm , Dege Tizian , Plesinger Filip , Bulkova Veronika , Clifford Gari , Reyna Matthew , Hoog Antink Christoph 
Published: June 2022

Abstract
During the lockdown of universities and the COVID-Pandemic most students were restricted to their homes. Novel and instigating teaching methods were required to improve the learning experience and so recent implementations of the annual PhysioNet/Computing in Cardiology (CinC) Challenges posed as a reference. For over 20 years, the challenges have proven repeatedly to be of immense educational value, besides leading to technological advances for specific problems. In this paper, we report results from the class ‘Artificial Intelligence in Medicine Challenge’, which was implemented as an online project seminar at Technical University Darmstadt, Germany, and which was heavily inspired by the PhysioNet/CinC Challenge 2017 ‘AF Classification from a Short Single Lead ECG Recording’. Atrial fibrillation is a common cardiac disease and often remains undetected. Therefore, we selected the two most promising models of the course and give an insight into the Transformer-based DualNet architecture as well as into the CNN-LSTM-based model and finally a detailed analysis for both. In particular, we show the model performance results of our internal scoring process for all submitted models and the near state-of-the-art model performance for the two named models on the official 2017 challenge test set. Several teams were able to achieve F1 scores above/close to 90% on a hidden test-set of Holter recordings. We highlight themes commonly observed among participants, and report the results from the self-assessed student evaluation. Finally, the self-assessment of the students reported a notable increase in machine learning knowledge.
Assessing systemic vascular resistance using arteriolar pulse transit time based on multi-wavelength photoplethysmography
Authors: Lu Yiqian , Yu Zengjie , Liu Jikui , An Qi , Chen Cong , Li Ye , Wang Yishan 
Published: June 2022

Abstract

Objective. Sympathetic nerve activity affects blood pressure by contracting the arteriole, which can increase systemic vascular resistance (SVR). Consequently, SVR is a key factor affecting blood pressure. However, a method for measuring SVR continuously is lacking. This paper formulated and experimentally validated a method that uses the arteriolar pulse transmit time (aPTT) to track changes in SVR. Approach. multi-wavelength photoplethysmogram (PPG), electrocardiogram (ECG), and galvanic skin response (GSR) data were simultaneously gathered using a measurement system designed by this study. Blood perfusion was monitored by laser Doppler. Least mean square (LMS) is an adaptive filtering algorithm. Our LMS-based algorithm formulated in this study was used to calculate the aPTT from the multi-wavelength PPGs. A cold stimulation experiment was conducted to verify the relationship between aPTT determined by algorithm and arteriole vasodilation. An emotinal stimulation experiment conducted, in which GSR was employed to further verify the relationship between aPTT and SVR. Twenty healthy young participants were asked to watch movie clips, which excited their sympathetic nerves. The dynamic time warping (DTW) distance is applied to evaluate between correlation of GSR and aPTT. Main results. The changes in aPTT was extracted using our LMS-based method. During the recovery period after cold stimulation, aPTT decreased with the average slope of −0.2080, while blood perfusion increased with the average slope of 0.7046. Meanwhile, 70% participants’ DTW distances median between aPTT and GSR were significantly smaller than that between PTT and GSR during emotion stimulation. Significance. Our method uses aPTT, a continuous measurable parameter, to closely reflect SVR, as verified through experiments.
Epoxy-free fabrication techniques for layered/2-2 magnetoelectric composite: a review
Authors: Kumar Amritesh , Arockiarajan A 
Published: June 2022

Abstract
Layered or 2-2 configuration magnetoelectric (ME) composites have gained significant interest in the last few decades owing to their ease of fabrication and relatively high ME output realizable at room temperature. Conventionally, layered ME composites are fabricated by bonding the constituent magnetostrictive and piezoelectric layers via an epoxy or adhesive. Thus, the epoxied interface acts as the medium of strain transfer between the constituent layers resulting in the ME effect. However, the presence of epoxy makes the composite prone to limitations such as reduced device life due to aging epoxy, reduced strain transfer efficacy due to low stiffness of epoxy, and degradation of composite properties at elevated temperatures due to the low glass transition temperature of epoxy material. Thus, various epoxy-free methods for layered or 2-2 type ME composite fabrication have been developed in the last two decades to circumvent these limitations. These methods include co-firing technique, electroless deposition, electrodeposition, shrink-fit, and press-fit. Each of these methods has tried to mitigate the disadvantages of its predecessors, however posing its own set of limitations. This review article captures the evolutionary journey of the development of each of these aforementioned techniques in a chronological sequence by highlighting the advantages and disadvantages offered by each of them. Subsequently, a brief overview of state of the art has been provided in summary, followed by a discussion on the potential avenues that may be probed further to improve the available epoxy-free fabrication techniques for layered or 2-2 ME composites.
Optical noise in a free-space quantum communications link from natural and nuclear disturbed environments*
Authors: Wilson Brandon A , Miloshevsky Alexander , Hooper David A , Grice Warren , Peters Nicholas A 
Published: June 2022

Abstract
Satellite communications at radio frequencies can experience a ‘blackout’ period following the atmospheric detonation of a nuclear weapon. The wavelengths used for free-space quantum communications will not incur the same ‘blackout’ effects from a nuclear detonation, but the optical systems will suffer from a phenomenon called redout. Redout occurs in an optical detector when ambient light scatters into the optical receiver, causing elevated background photon counts in the detector such that background noise overwhelms the signal. In this work, the duration of the redout effect is quantified from a nuclear disturbed environment on a ground-to-space quantum optical link. In addition, we comment on various techniques for reducing ambient and nuclear disturbed background counts in a quantum free-space optical link. For low-altitude nuclear detonations (i.e., under 50 km), the maximum interference time will be less than 1 min. Implementing a telescope, timing gate, and wavelength filter to the detector can reduce the background counts in the detector significantly. Aerosol levels and ground albedo are major contributors to background noise in a ground-to-satellite quantum channel, and ground station location should factor in both variables.
Testing super heavy dark matter from primordial black holes with gravitational waves
Authors: Samanta Rome , Urban Federico R. 
Published: June 2022

Abstract
Ultra-light primordial black holes with masses M
BH < 109 g evaporate before big-bang nucleosynthesis producing all matter fields, including dark matter, in particular super-heavy dark matter: M
DM ≳ 1010 GeV. If the dark matter gets its mass via U(1) symmetry-breaking, the phase transition that gives a mass to the dark matter also produces cosmic strings which radiate gravitational waves. Because the symmetry-breaking scale ΛCS is of the same order as M
DM, the gravitational waves radiated by the cosmic strings have a large enough amplitude to be detectable across all frequencies accessible with current and planned experimental facilities. Moreover, an epoch of early primordial black hole domination introduces a unique spectral break in the gravitational wave spectrum whose frequency is related to the super-heavy dark matter mass. Hence, the features of a stochastic background of primordial gravitational waves could indicate that super-heavy dark matter originated from primordial black holes. In this perspective, the recent finding of a stochastic common-spectrum process across many pulsars by two nano-frequency pulsar timing arrays would fix the dark matter mass to be 3 × 1013 GeV ≲ M
DM ≲ 1014 GeV. The (non-)detection of a spectral break at 0.2 Hz ≲ f
* ≲ 0.4 Hz would (exclude) substantiate this interpretation of the signal.
Relative entropies of coherence of X states in three-dimensional mutually unbiased bases
Authors: Song Yuan-Feng , Ge Li-Zhu , Wang Yao-Kun , Tang Hui , Tian Yan 
Published: June 2022

Abstract
In this paper, we calculate the density matrices of one class of X states in the three-dimensional mutually unbiased bases and find that the density matrices are equal to their corresponding conjugate transpose matrices. After obtaining the relations of these density matrices, we calculate the relative entropies of coherence for the density matrices of X states in these nontrivial mutually unbiased bases and obtain that their relative entropies of coherence are equal. At last, the density matrices of other two classes of X states in these mutually unbiased bases are discussed. We also investigate their relative entropies of coherence and clarify their relationships.
A spectroscopic inference and SOLPS-ITER comparison of flux-resolved edge plasma parameters in detachment experiments on TCV
Authors: Perek A. , Wensing M. , Verhaegh K. , Linehan B.L. , Reimerdes H. , Bowman C. , van Berkel M. , Classen I.G.J. , Duval B.P. , Février O. , Koenders J.T.W. , Ravensbergen T. , Theiler C. , de Baar M.R. , the EUROfusion MST1 Team  , the TCV Team  
Published: June 2022

Abstract
This work presents the use of a collisional-radiative model to infer plasma parameters from 2D emissivities of several deuterium Balmer lines. The emissivities were obtained by MANTIS, an absolutely calibrated, ten-camera imaging polychromator with

<
5

m
m

spatial resolution, up to 800 Hz frame rate, viewing the lower divertor tangentially. Our analysis of those image frames generates 2D maps of plasma parameters such as electron density, temperature, neutral atomic density and the reaction rates for ionisation, recombination and charge exchange as a function of time. The analysis is compared and validated against a SOLPS-ITER simulation accounting for drifts. The results are compared against the simulation in 2D, radial and poloidal profiles to probe the numerous effects of particle transport in the scrape-off layer, in particular in the approach to detached divertor leg conditions. The inferred inner divertor leg radial profiles of the electron density and temperature were consistent with the SOLPS-ITER predictions. A significant transport of particles to the private flux region is found experimentally, that is not captured in the simulation. The simulation diverges from the experiment at the outer divertor target, where the plasma emission appears to be consistent with the emission driven by plasma–molecule interactions. Our analysis also shows prospects for aiding the power exhaust control efforts by potentially providing an optical tracking of the particle balance in the divertor.
A sensitive and flexible interdigitated capacitive strain gauge based on carbon nanofiber/PANI/silicone rubber nanocomposite for body motion monitoring
Authors: Hosseini Seyedmajid , Hajghassem Hassan , Ghazani Masoud Faraghi 
Published: June 2022

Abstract
Stretchable nanocomposites-based strain gauges have received much attention due to their adjustable properties in various applications, including soft robotics, human health monitoring, body motion detection, structural health monitoring, and artificial intelligence. Although low sensitivity (gauge factor) is one of the challenges of capacitive strain gauges, in this study, we design, manufacture, and illustrate characterizations of a stretchable interdigitated capacitive strain gauge based on carbon nanofiber/polyaniline/silicone rubber nanocomposite by an improvement in sensitivity with linearity, and low hysteresis. This strain gauge reaches a gauge factor of about 14 over an applied strain of 2% and about 2.8 over an applied strain of 20% and demonstrates linearity with negligible hysteresis. The sensitivity of the strain sensor is enhanced not only by the interdigitated design of electrodes but also by the electrodes’ outstanding electrical conductivity, even in a large strain. Due to its sensitivity, the proposed device is suitable for detecting small and large strains and can be used in wearable applications or straight on the skin for human motion detection.
Hadrons, better, faster, stronger
Authors: Buhmann Erik , Diefenbacher Sascha , Hundhausen Daniel , Kasieczka Gregor , Korcari William , Eren Engin , Gaede Frank , Krüger Katja , McKeown Peter , Rustige Lennart 
Published: June 2022

Abstract
Motivated by the computational limitations of simulating interactions of particles in highly-granular detectors, there exists a concerted effort to build fast and exact machine-learning-based shower simulators. This work reports progress on two important fronts. First, the previously investigated Wasserstein generative adversarial network and bounded information bottleneck autoencoder generative models are improved and successful learning of hadronic showers initiated by charged pions in a segment of the hadronic calorimeter of the International Large Detector is demonstrated for the first time. Second, we consider how state-of-the-art reconstruction software applied to generated shower energies affects the obtainable energy response and resolution. While many challenges remain, these results constitute an important milestone in using generative models in a realistic setting.
Brief, interoceptive exposure focused treatment for anxiety in mild cognitive impairment
Authors: Schmidt Norman B , Schubert Frederick T , Sheffler Julia L 
Published: June 2022

Abstract
Anxiety is common in older adults with mild cognitive impairment (MCI), and Alzheimer's disease and related dementias (ADRD). Anxiety has also been identified as a risk factor for cognitive decline. Brief interventions targeting risk mechanisms of anxiety, such as anxiety sensitivity (AS), have been effective in reducing overall anxiety in a variety of populations. This case series investigated the feasibility and efficacy of a brief AS intervention in anxious older adults with MCI (n = 9). Paired samples t-test results indicate that this intervention is capable of significantly reducing AS as measured by the Anxiety Sensitivity Index-3 (Δ = 5.11, Hedges g = 0.82, P &lt; 0.05). Given these large AS reductions and high acceptability, further investigation of this intervention is warranted in older adults with MCI.
Decisions on antibiotic prescribing for suspected urinary tract infections in frail older adults: a qualitative study in four European countries
Authors: Hartman Esther A R , Groen Wim G , Heltveit-Olsen Silje Rebekka , Lindbæk Morten , Høye Sigurd , Sundvall Pär-Daniel , Skoglund Ingmarie , Snaebjörnsson Arnljots Egill , Gunnarsson Ronny , Kowalczyk Anna , Godycki-Cwirko Maciek , Kosiek Katarzyna , Platteel Tamara N , van de Pol Alma C , Verheij Theo J M , Monnier Annelie A , Hertogh Cees M P M 
Published: June 2022

Abstract

Background
a suspected urinary tract infection (UTI) is the most common reason to prescribe antibiotics in a frail older patient. Frequently, antibiotics are prescribed unnecessarily. To increase appropriate antibiotic use for UTIs through antibiotic stewardship interventions, we need to thoroughly understand the factors that contribute to these prescribing decisions.

Objectives
(1) to obtain insight into factors contributing to antibiotic prescribing for suspected UTIs in frail older adults. (2) To develop an overarching model integrating these factors to guide the development of antibiotic stewardship interventions for UTIs in frail older adults.

Methods
we conducted an exploratory qualitative study with 61 semi-structured interviews in older adult care settings in Poland, the Netherlands, Norway and Sweden. We interviewed physicians, nursing staff, patients and informal caregivers.

Results
participants described a chain of decisions by patients, caregivers and/or nursing staff preceding the ultimate decision to prescribe antibiotics by the physician. We identified five themes of influence: (1) the clinical situation and its complexity within the frail older patient, (2) diagnostic factors, such as asymptomatic bacteriuria, (3) knowledge (gaps) and attitude, (4) communication: interprofessional, and with patients and relatives and (5) context and organisation of care, including factors such as availability of antibiotics (over the counter), antibiotic stewardship efforts and factors concerning out-of-hours care.

Conclusions
decision-making on suspected UTIs in frail older adults is a complex, multifactorial process. Due to the diverse international setting and stakeholder variety, we were able to provide a comprehensive overview of factors to guide the development of antibiotic stewardship interventions.
SNIKT: sequence-independent adapter identification and removal in long-read shotgun sequencing data
Authors: Ranjan Piyush , Brown Christopher A , Erb-Downward John R , Dickson Robert P 
Published: June 2022

AbstractSummaryHere, we introduce SNIKT, a command-line tool for sequence-independent visual confirmation and input-assisted removal of adapter contamination in whole-genome shotgun or metagenomic shotgun long-read sequencing DNA or RNA data.Availability and ImplementationSNIKT is implemented in R and is compatible with Unix-like platforms. The source code, along with documentation, is freely available under an MIT license at https://github.com/piyuranjan/SNIKT.Supplementary informationSupplementary data are available at Bioinformatics online.
SPEAR: Systematic ProtEin AnnotatoR
Authors: Crown Matthew , Teruel Natália , Najmanovich Rafael , Bashton Matthew 
Published: June 2022

AbstractSummaryWe present Systematic ProtEin AnnotatoR (SPEAR), a lightweight and rapid SARS-CoV-2 variant annotation and scoring tool, for identifying mutations contributing to potential immune escape and transmissibility (ACE2 binding) at point of sequencing. SPEAR can be used in the field to evaluate genomic surveillance results in real time and features a powerful interactive data visualization report.Availability and implementationSPEAR and documentation are freely available on GitHub: https://github.com/m-crown/SPEAR and are implemented in Python and installable via Conda environment.Supplementary informationSupplementary data are available at Bioinformatics online.