bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantum-cascade-laser-based dual-comb thermometry and speciation at high temperatures
Authors: Pinkowski Nicolas H , Cassady Séan J , Strand Christopher L , Hanson Ronald K 
Published: October 2020

Abstract
This work presents a methodology for using spectroscopic models to fit absorption-spectrum measurements made by a quantum-cascade-laser-based dual-comb spectrometer (QCL-DCS) for high-temperature kinetics research. A pair of quantum-cascade frequency combs was employed to detect methane’s

ν
4

absorption features between 1270 and 1320 cm−1 in high-temperature shock-tube environments and extract methane mole fraction and gas temperature from the results. The methodology was first validated by comparing DCS measurements against modeled methane spectra at room temperature in a static cell, followed by assessing the fitting procedure in shock-heated mixtures of 2% methane in Ar at 1000 K. In both validation experiments, the tradeoffs between time resolution and measurement precision were explored. Measurements were achieved at a 4 µs measurement rate with 5% uncertainty for temperature and 4% uncertainty for mole fraction at 1000 K. Higher accuracy was achieved with longer measurement averaging, e.g. 1.8% uncertainty for temperature at 40

μ

s resolution. Finally, the DCS spectral-fitting methodology was demonstrated to capture temperature and methane time-history evolution during the pyrolysis of iso-octane, a primary gasoline reference fuel. Good agreement was observed with kinetic models, and future applications for DCS kinetics research are discussed.
On the extraction of MoO
x
photothermally active nanoparticles by gel filtration from a byproduct of few-layer MoS2 exfoliation
Authors: Annušová Adriana , Bodík Michal , Hagara Jakub , Kotlár Mário , Halahovets Yuriy , Mičušík Matej , Chlpík Juraj , Cirák Július , Hofbauerová Monika , Jergel Matej , Majková Eva , Šiffalovič Peter 
Published: October 2020

Abstract
Gel filtration is a versatile technique employed for biological molecules and nanoparticles, offering their reproducible classification based on size and shape. Colloidal nanoparticles are of significant interest in biomedical applications due to a large number of solution-based bioconjugation procedures. Nevertheless, the inherent polydispersity of the nanoparticles produced by various techniques necessitates the employment of high yield separation and purification techniques. Here we demonstrate the employment of gel filtration on non-stoichiometric plasmonic MoO
x
nanoparticles, prepared by an oxidation process during liquid-phase exfoliation of few-layer MoS2 nanosheets. This resulted in the separation of two types of MoO
x
particles, in the form of two different chromatographic fractions. They showed different sizes, morphological and optical properties. The fraction containing smaller particles with diameters of 1–4 nm, exhibited an increased absorbance peak in the near IR region and responded with a significant temperature increase to laser irradiation at the wavelength close to the maximal absorption. The fraction with the larger particles from 3 up to 10 nm, showed weak photoluminescence and a preferred orientation upon the deposition on a planar substrate. However, it had no absorbance in the near IR compared to the former fraction. According to our knowledge, this is the first time that the gel filtration was applied to the separation of molybdenum oxide nanomaterials. This step ensured the isolation of plasmonic MoO
x
nanoparticles suitable for further bioconjugation and target photothermal treatment.
Photocatalytic hydrogen evolution activity over Pt-assisted metal-organic frameworks dominated by transition metal ions and local coordination environments
Authors: Li Lei , Wang Jia-Jun , Zhao Yan , Ding Bo , Wang Xiu-Guang , Zhao Xiao-Jun , Yang En-Cui 
Published: October 2020

Abstract
Three isostructural pillared-layer frameworks with M-BDC-X layers supported by ditopic HL connectors, [M(HL)(BDC)0.5X]
n
(HL = 4′-(4-hydroxyphenyl)-4,2′:6′,4″-terpyridine, BDC = terephthalate, M = Cd, X = Cl for (1), M = Cd, X = formate for (2), and M = Co, X = formate for (3)), were solvothermally synthesized, and used as photocatalysts for Pt-assisted visible-light-initiated hydrogen evolution from water splitting. These water-durable frameworks exhibit varied hydrogen production rates of 361.2, 271.3, and 327.5 μmol · g−1 · h−1 in 12 h due to their slightly different donor environments of the octahedral CdII and CoII ions. Further experimental and theoretical investigations reveal that the metal ions and the local coordination surroundings have essentially dominated the conduction band minimum and electric resistance of the charge transport, which play highly important roles for the improved catalytic hydrogen evolution ability. These findings demonstrate the electronic effect of the slightly ligand field modifications on the boosting hydrogen generation activity in the noble metal-assisted MOF photocatalytic systems.
Bi metal/oxygen-deficient BiO2−x
with tetrahedral morphology and high photocatalytic activity
Authors: Liang Mengjun , Zou Chentao , Wang Weihua , Yang Zhiyuan , Shen Kaixiang , Yang Yun , Yang Shuijin 
Published: October 2020

Abstract
Vacancy-rich materials with high photocatalytic activity are of great interest for pollutants removal and play a significant role in green chemistry. Herein, we successfully synthesized Bi/BiO2−x
composite through hydrothermal route. In this case, the surface plasmon resonance effect of Bi and oxygen vacancies of BiO2−x
collectively increase the removal rate of pollutants. More importantly, the Bi/BiO2−x
composites have enhanced activity in the degradation of RhB, MO, BPA and CIP, and the reduction of Cr(VI) and PNA. Besides, an enhanced photocatalytic activity is due to the main reactive species of ·

O

2

−

and h+ that is confirmed by trapping experiments and ESR analyses. The electronic structure and visible light harvesting of photocatalysts were measured and also theoretically calculated by using density functional theory and finite difference time domain calculations, DRS, VB x-ray photoelectron spectroscopy and Mott–Schottky plots, which allowed to propose a possible photocatalytic mechanism for the degradation process.
Alsedà–Misiurewicz systems with place-dependent probabilities*
Authors: Czudek Klaudiusz 
Published: October 2020

Abstract
We consider systems of two specific piecewise linear homeomorphisms of the unit interval, so called Alsedà–Misiurewicz systems, and investigate the basic properties of Markov chains which arise when these two transformations are applied randomly with probabilities depending on the point of the interval. Though this iterated function system is not contracting in average and known methods do not apply, stability and the strong law of large numbers are proven.
Is the Archimedes principle a law of nature? Discussions in an ‘extended teacher room’
Authors: Dahl Olof , Eklund Bo , Pendrill Ann-Marie 
Published: October 2020

Abstract
Is a suction cup at the bottom of a bathtub subject to an upward force from the surrounding water, even if there is no water under it? A student question, posted in a teacher facebook group on a Monday morning, led to a discussion involving 21 comments with 225 replies offered by 16 teachers during the next few days, including several simple experiments, as well as modeling, to evaluate different arguments. The discussions, summarized in this paper, provide an example of how social media can provide an ‘extended teacher room’ where teachers can explore and refine their understanding in a safe and mostly supportive environment, and also find ways to give more elaborate answers to challenging student questions.
Active contour regularized semi-supervised learning for COVID-19 CT infection segmentation with limited annotations
Authors: Ma Jun , Nie Ziwei , Wang Congcong , Dong Guoqiang , Zhu Qiongjie , He Jian , Gui Luying , Yang Xiaoping 
Published: October 2020

Abstract
Infection segmentation on chest CT plays an important role in the quantitative analysis of COVID-19. Developing automatic segmentation tools in a short period with limited labelled images has become an urgent need. Pseudo label-based semi-supervised method is a promising way to leverage unlabelled data to improve segmentation performance. Existing methods usually obtain pseudo labels by first training a network with limited labelled images and then inferring unlabelled images. However, these methods may generate obviously inaccurate labels and degrade the subsequent training process. To address these challenges, in this paper, an active contour regularized semi-supervised learning framework was proposed to automatically segment infections with few labelled images. The active contour regularization was realized by the region-scalable fitting (RSF) model which is embedded to the loss function of the network to regularize and refine the pseudo labels of the unlabelled images. We further designed a splitting method to separately optimize the RSF regularization term and the segmentation loss term with iterative convolution-thresholding method and stochastic gradient descent, respectively, which enable fast optimization of each term. Furthermore, we built a statistical atlas to show the infection spatial distribution. Extensive experiments on a small public dataset and a large scale dataset showed that the proposed method outperforms state-of-the-art methods with up to 5% in dice similarity coefficient and normalized surface dice, 10% in relative absolute volume difference and 8 mm in 95% Hausdorff distance. Moreover, we observed that the infections tend to occur at the dorsal subpleural lung and posterior basal segments that are not mentioned in current radiology reports and are meaningful to advance our understanding of COVID-19.
Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T
1 mapping images
Authors: Nezafat Maryam , El-Rewaidy Hossam , Kucukseymen Selcuk , Hauser Thomas H , Fahmy Ahmed S 
Published: October 2020

Abstract
We developed a deep convolutional neural network (CNN) based method to remove streaking artefact from accelerated radial acquisitions of myocardial T
1-mapping images. A deep CNN based on a modified U-Net architecture was developed and trained to remove the streaking artefacts from under-sampled T
1 mapping images. A total of 2090 T
1-weighted images for 33 patients (55 ± 15 years, 19 males) and five healthy subjects (30 ± 14 years, 2 males) were used for training and testing the network. The images were acquired using radial slice interleaved T
1 mapping sequence (STONE) and retrospectively under-sampled to achieve acceleration rate of 4 (corresponding to 48 spokes). The dataset was split into training and testing subsets with 23 subjects (60%) and 15 subjects (40%), respectively. For generating voxel-wise T
1 maps, a two-parameter fitting model was used. Network performance was evaluated using normalized mean square error (NMSE), structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) metrics. The proposed network allowed fast (<0.3 s/image) removal of the artefact from all T
1-weighted testing images and the corresponding T
1 maps with PSNR = 64.3 ± 1.02, NMSE = 0.2 ± 0.09 and SSIM = 0.9 ± 0.3 × 10−4. There was no statistically significant difference between the measured T
1 maps for both per-subject (reference: 1085 ± 37 ms, CNN: 1088 ± 37 ms, p = 0.4) and per-segment (reference: 1084 ± 48 ms, CNN: 1083 ± 58 ms, p = 0.9) analyses. In summary, deep CNN allows fast and reliable removal of streaking artefact from under-sampled radial T
1 mapping images. Our results show that the highly non-linear operations of deep CNN processing of T
1 mapping images do not impact accurate reconstruction of myocardial T
1 maps.
Design of fiber-reinforced soft bending pneumatic artificial muscles for wearable tremor suppression devices
Authors: Wirekoh Jackson , Parody Nicholas , Riviere Cameron N , Park Yong-Lae 
Published: October 2020

Abstract
Soft robotics is a rapidly evolving field offering novel solutions in the development of wearable technologies. Soft pneumatic artificial muscles in particular, have seen widespread use in the development of human scale rehabilitative and assistive wearables. However, these soft actuators have not yet been adapted to address the complex dynamic regime of active (essential tremor) and resting (Parkinson’s disease) hand tremor, the most common movement disorder affecting humans. Current solutions to address hand tremor involve expensive medication and surgical interventions, as well as wearable assistive devices that fall short of providing an effective compact design for the suppression of hand tremor. This study focuses on the design of a novel lightweight, compact, bending actuator that will be capable of actively suppressing hand tremor when adapted into an assistive wearable device. The proposed fiber-reinforced bending pneumatic artificial muscle (BPAM), including its design specifications, fabrication process, theoretical modeling, and experimental characterization, are detailed. The developed actuator was capable of producing sinusoidal trajectories with peak-to-peak amplitudes of 40° and a bandwidth of 8 Hz, the dynamic regime of pathological hand tremor. The ability of the fiber-reinforced BPAM to act within the dynamic regime of hand tremor demonstrates its potential to be further developed into a system capable of the active suppression of hand tremor.
Complex imprint of solar variability on tree rings
Authors: Land Alexander , Kromer Bernd , Remmele Sabine , Brehm Nicolas , Wacker Lukas 
Published: October 2020

Abstract
Many studies have investigated the role of solar variability in Holocene climate. Beyond sunspot observations, solar activity can be reconstructed from 14C in tree rings. Due to the lack of sub-decadal resolution of 14C records, these studies focused on long-term processes. In this study, we use an annually-resolved 14C record to examine solar variability (e.g. 11-year Schwabe solar cycle) and its connection to European seasonal climate inferred from tree-ring records during the entire past millennium with spectral and wavelet techniques. The 11-year Schwabe solar cycle shows a significant impact in European moisture- and temperature-sensitive tree-ring records. Complex ’top-down’/‘bottom-up’ effects in the strato-tropoatmospheric system are assumed to affect European spring and summer climate with a temporal-shift as evident from observed changes in phase behavior. Significant evidence is also found for the ∼60- and ∼90-year band during the first half of the past millennium.
Text emotion mining on Twitter
Authors: Alkhushayni Suboh M , Zellmer Daniel C , DeBusk Ryan J , Alzaleq Du’a 
Published: October 2020

Abstract
Twitter has become a medium through which a substantial percentage of the global population communicates their feelings and reactions to current events. Emotion mining from text aims to capture these emotions by using a series of algorithms to evaluate the contents of each tweet. In this study, tweets that expressed at least one of seven basic emotions were collected. The resulting dataset was a corpus of 42,000 tweets with a balanced presence of each emotion. From this corpus a lexicon of roughly 40,000 words, each associated with a weighted vector corresponding to one of the emotions, was created. Next, different methods of identifying emotion in these ‘cleaned’ tweets were performed and evaluated. These methods included both lexically-based classification and supervised machine learning-based classification. Finally, an ensemble method involving several multi-class classifiers trained on unigram features of the lexicon was evaluated. This evaluation revealed that the ensemble method outperformed all other tested methods when tested on existing datasets as well as on the dataset created for this study.
Detecting axonal injury in individual patients after traumatic brain injury
Authors: Jolly Amy E , Bălăeţ Maria , Azor Adriana , Friedland Daniel , Sandrone Stefano , Graham Neil S N , Zimmerman Karl , Sharp David J 
Published: October 2020

Abstract
Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains limited in the clinical setting. Currently, axonal injury is diagnosed based on clinical presentation, visible damage to the white matter or via surrogate markers of axonal injury such as microbleeds. These do not accurately quantify axonal injury leading to misdiagnosis in a proportion of patients. Diffusion tensor imaging provides a quantitative measure of axonal injury in vivo, with fractional anisotropy often used as a proxy for white matter damage. Diffusion imaging has been widely used in TBI but is not routinely applied clinically. This is in part because robust analysis methods to diagnose axonal injury at the individual level have not yet been developed. Here, we present a pipeline for diffusion imaging analysis designed to accurately assess the presence of axonal injury in large white matter tracts in individuals. Average fractional anisotropy is calculated from tracts selected on the basis of high test-retest reliability, good anatomical coverage and their association to cognitive and clinical impairments after TBI. We test our pipeline for common methodological issues such as the impact of varying control sample sizes, focal lesions and age-related changes to demonstrate high specificity, sensitivity and test-retest reliability. We assess 92 patients with moderate-severe TBI in the chronic phase (≥6 months post-injury), 25 patients in the subacute phase (10 days to 6 weeks post-injury) with 6-month follow-up and a large control cohort (n = 103). Evidence of axonal injury is identified in 52% of chronic and 28% of subacute patients. Those classified with axonal injury had significantly poorer cognitive and functional outcomes than those without, a difference not seen for focal lesions or microbleeds. Almost a third of patients with unremarkable standard MRIs had evidence of axonal injury, whilst 40% of patients with visible microbleeds had no diffusion evidence of axonal injury. More diffusion abnormality was seen with greater time since injury, across individuals at various chronic injury times and within individuals between subacute and 6-month scans. We provide evidence that this pipeline can be used to diagnose axonal injury in individual patients at subacute and chronic time points, and that diffusion MRI provides a sensitive and complementary measure when compared to susceptibility weighted imaging, which measures diffuse vascular injury. Guidelines for the implementation of this pipeline in a clinical setting are discussed.
Abnormal dorsal attention network activation in memory impairment after traumatic brain injury
Authors: Mallas Emma-Jane , De Simoni Sara , Scott Gregory , Jolly Amy E , Hampshire Adam , Li Lucia M , Bourke Niall J , Roberts Stuart A G , Gorgoraptis Nikos , Sharp David J 
Published: October 2020

AbstractMemory impairment is a common, disabling effect of traumatic brain injury. In healthy individuals, successful memory encoding is associated with activation of the dorsal attention network as well as suppression of the default mode network. Here, in traumatic brain injury patients we examined whether: (i) impairments in memory encoding are associated with abnormal brain activation in these networks; (ii) whether changes in this brain activity predict subsequent memory retrieval; and (iii) whether abnormal white matter integrity underpinning functional networks is associated with impaired subsequent memory. Thirty-five patients with moderate-severe traumatic brain injury aged 23–65 years (74% males) in the post-acute/chronic phase after injury and 16 healthy control subjects underwent functional MRI during performance of an abstract image memory encoding task. Diffusion tensor imaging was used to assess structural abnormalities across patient groups compared to 28 age-matched healthy controls. Successful memory encoding across all participants was associated with activation of the dorsal attention network, the ventral visual stream and medial temporal lobes. Decreased activation was seen in the default mode network. Patients with preserved episodic memory demonstrated increased activation in areas of the dorsal attention network. Patients with impaired memory showed increased left anterior prefrontal activity. White matter microstructure underpinning connectivity between core nodes of the encoding networks was significantly reduced in patients with memory impairment. Our results show for the first time that patients with impaired episodic memory show abnormal activation of key nodes within the dorsal attention network and regions regulating default mode network activity during encoding. Successful encoding was associated with an opposite direction of signal change between patients with and without memory impairment, suggesting that memory encoding mechanisms could be fundamentally altered in this population. We demonstrate a clear relationship between functional networks activated during encoding and underlying abnormalities within the structural connectome in patients with memory impairment. We suggest that encoding failures in this group are likely due to failed control of goal-directed attentional resources.
Sex-specific relationships between urbanization, parasitism, and plumage coloration in house finches
Authors: Sykes Brooke E , Hutton Pierce , McGraw Kevin J 
Published: October 2020

Abstract
Historically, studies of condition-dependent signals in animals have been male-centric, but recent work suggests that female ornaments can also communicate individual quality (e.g., disease state, fecundity). There also has been a surge of interest in how urbanization alters signaling traits, but we know little about if and how cities affect signal expression in female animals. We measured carotenoid-based plumage coloration and coccidian (Isospora spp.) parasite burden in desert and city populations of house finches Haemorhous mexicanus to examine links between urbanization, health state, and feather pigmentation in males and females. In earlier work, we showed that male house finches are less colorful and more parasitized in the city, and we again detected such patterns in this study for males; however, urban females were less colorful, but not more parasitized, than rural females. Moreover, contrary to rural populations, we found that urban birds (regardless of sex) with larger patches of carotenoid coloration were also more heavily infected with coccidia. These results show that urban environments can disrupt condition-dependent color expression and highlight the need for more studies on how cities affect disease and signaling traits in both male and female animals.