bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring Italian Resilience
Authors: Lau Chloe , Chiesi Francesca , Li Catherine , Saklofske Donald H. 
Published: May 2022

Abstract: The Essential Resilience Scale (ERS) measures global trait resilience and three factors of physical, emotional, and social resilience. This study developed an Italian adaptation of the ERS and recruited participants from Italy ( N = 500) to complete the measure along with criterion validity measures of broad personality traits and related psychological concepts. Confirmatory factor analysis (CFA) demonstrated robust evidence for a well-fitting three-factor model of the ERS, with items strongly loading onto their respective latent factors. Utilizing Samejima’s graded response model, most item discrimination values were moderate-to-high, and category threshold parameters were well-distributed throughout the latent continuum. The ERS showed correlations in the expected directions with extraversion, emotionality, optimism, mastery, resilience, behavioral activation, behavioral inhibition, stress, and well-being. Cultural invariance was supported (at the scale- and item-level) with multigroup CFA and differential item functioning (DIF) with a sample of Canadian English speakers ( N = 874). Findings evinced the internal consistency (i.e., total MacDonald’s ω), factorial validity (i.e., three-factor CFA), criterion validity (i.e., personality, temperament), and convergent validity (i.e., trait resilience and well-being) of the Italian ERS. Results suggest the Italian ERS can be applied for measuring resilience for future research studies in Italian-speaking populations.
Drag Force on Coronal Mass Ejections (CMEs)
Authors: Lin Chia‐Hsien , Chen James 
Published: May 2022

AbstractThe drag force experienced by coronal mass ejections (CMEs) plays an important role in determining the dynamics of CMEs. Numerous empirical studies have attempted to estimate the drag coefficient (cd) using the assumption that the observed deceleration of CMEs is primarily caused by drag alone. The observed CME motion, however, is determined by the net force—the sum of all the forces, and data contain no information to allow one to separately determine the individual forces. In the present work, we revisit the forces acting on CMEs using the erupting flux rope (EFR) model, making no assumptions on the magnitude of any force. Calculating the individual forces for four observed CME trajectories, it is shown that drag is generally not the dominant retarding force and that drag, magnetic tension, and pressure gradient can yield comparable deceleration. No force can be assumed negligible. It is further shown that the EFR equations can qualitatively replicate the observed deceleration with zero drag, contradicting the assertion that deceleration of CMEs necessarily implies the dominance of drag. A theoretical derivation of the drag coefficient cd for flux‐rope CMEs is given for a range of idealized flows including the so‐called “snow plow” effect. We show that cd ∼ 0–1 unless the snow‐plow effect is significant or the solar wind flows are specularly reflected, in which case cd ∼ 2–3. The values of cd predicted by the EFR model for the observed trajectories are cd ≃ 1.1–1.2 for three events and cd ≃ 0.4 for one.
Sediment Supply Effects in Hydrology‐Sediment Modeling of an Alpine Basin
Authors: Battista Giulia , Schlunegger Fritz , Burlando Paolo , Molnar Peter 
Published: May 2022

AbstractIn mountain river basins, sediment availability on hillslopes and in channels is key to predict the sediment response to hydrological forcing. However, quantification of sediment availability and its variability in time is challenging, because sediment supply is often strongly stochastic and dominated by mass wasting. In this paper, we introduce a variable landslide sediment supply as a function of topography, hydrology, and hillslope activity in the hydrology‐sediment model TOPKAPI‐ETH. We use the model to analyze the dynamics of sediment storage in a mesoscale pre‐Alpine basin. We simulate a range of transport‐ and supply‐limited conditions to quantify the variability of suspended sediment concentrations and load, and the seasonal dynamics of sediment storage. We show that supply limitation dampens the natural variability of the hydrological and sediment transport processes, and therefore reduces the scatter of the suspended sediment rating curve. By comparing the model results with observations, we demonstrate that alternation of low and high sediment availability favors sediment load variability at the outlet. The temporal dynamics of sediment storage depends on the hillslope activity, and the balance between sediment supply by landslides and evacuation by runoff. When the export flux is comparable or greater than the recharge flux, the storage shows seasonal fluctuations with a maximum in late winter or spring, and sediment starvation in summer. By representing the dynamics of both inputs and outputs of the sediment storage, the proposed model provides a physically based tool to isolate the effect of transport‐ and supply‐limited conditions in basin sediment response.
Earth Structure Across Many Scales
Authors: Kennett Brian 
Published: May 2022

AbstractOver my research career I have worked on many aspects of Earth Structure on scales from the whole globe to the very local, this has provided insights into the nature of heterogeneity and the importance of features with small length scales (up to tens of kilometers) revealed with higher‐frequency seismic waves (>1 Hz). Progress in determining 3‐D structure depends on representing the dominant variation with depth and large‐scale structure as a starting point. Intermediate and fine scales of heterogeneity (less than 100 km), below the typical resolution of seismic tomography, play an important role in shaping the seismic wavefield. The larger scales of variation in seismic structure can be directly linked to geodynamics through the influence of temperature and composition. The smaller scales retain a memory of past processes that can link to geochemical studies.
Large Scale Evaluation of Relationships Between Hydrologic Signatures and Processes
Authors: McMillan Hilary K. , Gnann Sebastian J. , Araki Ryoko 
Published: May 2022

AbstractDominant processes in a watershed are those that most strongly control hydrologic function and response. Estimating dominant processes enables hydrologists to design physically realistic streamflow generation models, design management interventions, and understand how climate and landscape features control hydrologic function. A recent approach to estimating dominant processes is through their link to hydrologic signatures, which are metrics that characterize the streamflow timeseries. Previous authors have used results from experimental watersheds to link signature values to underlying processes, but these links have not been tested on large scales. This paper fills that gap by testing signatures in large sample data sets from the U.S., Great Britain, Australia, and Brazil, and in Critical Zone Observatory (CZO) watersheds. We found that most inter‐signature correlations are consistent with process interpretations, that is, signatures that are supposed to represent the same process are correlated, and most signature values are consistent with process knowledge in CZO watersheds. Some exceptions occurred, such as infiltration and saturation excess processes that were often misidentified by signatures. Signature distributions vary by country, emphasizing the importance of regional context in understanding signature‐process links and in classifying signature values as “high” or “low.” Not all signatures were easily transferable from single, small watersheds to large sample studies, showing that visual or process‐based assessment of signatures is important before large‐scale use. We provide a summary table with information on the reliability of each signature for process identification. Overall, our results provide a reference for future studies that seek to use signatures to identify hydrological processes.
Estimation of Resolution and Covariance of Ambient Seismic Source Distributions: Full Waveform Inversion and Matched Field Processing
Authors: Xu Zongbo , Mikesell T. Dylan 
Published: May 2022

AbstractBoth natural and anthropogenic seismic sources generate so‐called ambient seismic waves. One in turn can use ambient seismic waves to estimate these source distributions and study source characteristics, for instance the source mechanism. A commonly used estimation method is called matched field processing (MFP), and the MFP results are inherently smeared by the array geometry. Another approach to estimate ambient seismic sources is to apply full waveform inversion (FWI) to the crosscorrelations of ambient seismic wave recordings. Both methods have pros and cons, but the model resolution and uncertainty in these two methods are important for the interpretation. Unfortunately, this topic has attracted little attention in the past. We propose to estimate both the model resolution matrix and model covariance matrix of the inversion using singular value decomposition. We demonstrate our estimates using two examples, one of which is an actual field array geometry. We quantitatively compare the model resolution of the two methods and discuss the model null space. We demonstrate that FWI has superior resolution with enough independent data and should be used when computational resources permit.
Probabilistic Prediction of Dst Storms One‐Day‐Ahead Using Full‐Disk SoHO Images
Authors: Hu A. , Shneider C. , Tiwari A. , Camporeale E. 
Published: May 2022

AbstractWe present a new model for the probability that the disturbance storm time (Dst) index exceeds −100 nT, with a lead time between 1 and 3 days. Dst provides essential information about the strength of the ring current around the Earth caused by the protons and electrons from the solar wind, and it is routinely used as a proxy for geomagnetic storms. The model is developed using an ensemble of Convolutional Neural Networks that are trained using Solar and Heliospheric Observatory (SoHO) images (Michelson Doppler Imager, Extreme ultraviolet Imaging Telescope, and Large Angle and Spectrometric Coronagraph). The relationship between the SoHO images and the solar wind has been investigated by many researchers, but these studies have not explicitly considered using SoHO images to predict the Dst index. This work presents a novel methodology to train the individual models and to learn the optimal ensemble weights iteratively, by using a customized class‐balanced mean square error (CB‐MSE) loss function tied to a least‐squares based ensemble. The proposed model can predict the probability that Dst < −100 nT 24 hr ahead with a True Skill Statistic (TSS) of 0.62 and Matthews Correlation Coefficient (MCC) of 0.37. The weighted TSS and MCC is 0.68 and 0.47, respectively. An additional validation during non‐Earth‐directed CME periods is also conducted which yields a good TSS and MCC score.
Analytical Solution for Predicting Salt Precipitation During CO2 Injection Into Saline Aquifers in Presence of Capillary Pressure
Authors: Norouzi A. M. , Niasar V. , Gluyas J. G. , Babaei M. 
Published: May 2022

AbstractSalt precipitation within pores of the reservoir is an important phenomenon occurring during CO2 injection into saline aquifers. The phenomenon results in permeability reduction and injectivity impairment. Salt precipitation mainly happens because of water vaporization inside the CO2‐saturated (dry‐out) region. For water‐wet systems, the capillary pressure acts toward the lower water saturation regions in the reservoir, thereby displacing a film of brine backward to the dry‐out region. This results in more precipitation. Overlooking this phenomenon, referred to as capillary‐driven backflow, results in over‐estimations of injectivity in the dried region. Here, we have developed an analytical solution based on fractional flow theory and shock waves for CO2‐brine systems considering the effect of capillary pressure. The validity of the solution is verified by comparing the outputs of our model with those of numerical results from a commercial numerical simulator for a hypothetical reservoir. An equation is derived to calculate the distance at which capillary pressure is most influential, and also the injectivity impairment at injection well due to salt precipitation was reasonably accurately estimated. The results emphasize that effects of capillary pressure should not be ignored.
Achieving low-power single-wavelength-pair nanoscopy with NIR-II continuous-wave laser for multi-chromatic probes
Authors: Guo Xin , Pu Rui , Zhu Zhimin , Qiao Shuqian , Liang Yusen , Huang Bingru , Liu Haichun , Labrador-Páez Lucía , Kostiv Uliana , Zhao Pu , Wu Qiusheng , Widengren Jerker , Zhan Qiuqiang 
Published: May 2022

AbstractStimulated emission depletion (STED) microscopy is a powerful diffraction-unlimited technique for fluorescence imaging. Despite its rapid evolution, STED fundamentally suffers from high-intensity light illumination, sophisticated probe-defined laser schemes, and limited photon budget of the probes. Here, we demonstrate a versatile strategy, stimulated-emission induced excitation depletion (STExD), to deplete the emission of multi-chromatic probes using a single pair of low-power, near-infrared (NIR), continuous-wave (CW) lasers with fixed wavelengths. With the effect of cascade amplified depletion in lanthanide upconversion systems, we achieve emission inhibition for a wide range of emitters (e.g., Nd3+, Yb3+, Er3+, Ho3+, Pr3+, Eu3+, Tm3+, Gd3+, and Tb3+) by manipulating their common sensitizer, i.e., Nd3+ ions, using a 1064-nm laser. With NaYF4:Nd nanoparticles, we demonstrate an ultrahigh depletion efficiency of 99.3 ± 0.3% for the 450 nm emission with a low saturation intensity of 23.8 ± 0.4 kW cm−2. We further demonstrate nanoscopic imaging with a series of multi-chromatic nanoprobes with a lateral resolution down to 34 nm, two-color STExD imaging, and subcellular imaging of the immunolabelled actin filaments. The strategy expounded here promotes single wavelength-pair nanoscopy for multi-chromatic probes and for multi-color imaging under low-intensity-level NIR-II CW laser depletion.
Versatile strategy for homogeneous drying patterns of dispersed particles
Authors: Rey Marcel , Walter Johannes , Harrer Johannes , Perez Carmen Morcillo , Chiera Salvatore , Nair Sharanya , Ickler Maret , Fuchs Alesa , Michaud Mark , Uttinger Maximilian J. , Schofield Andrew B. , Thijssen Job H. J. , Distaso Monica , Peukert Wolfgang , Vogel Nicolas 
Published: May 2022

AbstractAfter spilling coffee, a tell-tale stain is left by the drying droplet. This universal phenomenon, known as the coffee ring effect, is observed independent of the dispersed material. However, for many technological processes such as coating techniques and ink-jet printing a uniform particle deposition is required and the coffee ring effect is a major drawback. Here, we present a simple and versatile strategy to achieve homogeneous drying patterns using surface-modified particle dispersions. High-molecular weight surface-active polymers that physisorb onto the particle surfaces provide enhanced steric stabilization and prevent accumulation and pinning at the droplet edge. In addition, in the absence of free polymer in the dispersion, the surface modification strongly enhances the particle adsorption to the air/liquid interface, where they experience a thermal Marangoni backflow towards the apex of the drop, leading to uniform particle deposition after drying. The method is independent of particle shape and applicable to a variety of commercial pigment particles and different dispersion media, demonstrating the practicality of this work for everyday processes.
Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning
Authors: Riba Andrea , Oravecz Attila , Durik Matej , Jiménez Sara , Alunni Violaine , Cerciat Marie , Jung Matthieu , Keime Céline , Keyes William M. , Molina Nacho 
Published: May 2022

AbstractDespite the fact that the cell cycle is a fundamental process of life, a detailed quantitative understanding of gene regulation dynamics throughout the cell cycle is far from complete. Single-cell RNA-sequencing (scRNA-seq) technology gives access to these dynamics without externally perturbing the cell. Here, by generating scRNA-seq libraries in different cell systems, we observe cycling patterns in the unspliced-spliced RNA space of cell cycle-related genes. Since existing methods to analyze scRNA-seq are not efficient to measure cycling gene dynamics, we propose a deep learning approach (DeepCycle) to fit these patterns and build a high-resolution map of the entire cell cycle transcriptome. Characterizing the cell cycle in embryonic and somatic cells, we identify major waves of transcription during the G1 phase and systematically study the stages of the cell cycle. Our work will facilitate the study of the cell cycle in multiple cellular models and different biological contexts.
Carbene and photocatalyst-catalyzed decarboxylative radical coupling of carboxylic acids and acyl imidazoles to form ketones
Authors: Ren Shi-Chao , Yang Xing , Mondal Bivas , Mou Chengli , Tian Weiyi , Jin Zhichao , Chi Yonggui Robin 
Published: May 2022

AbstractThe carbene and photocatalyst co-catalyzed radical coupling of acyl electrophile and a radical precursor is emerging as attractive method for ketone synthesis. However, previous reports mainly limited to prefunctionalized radical precursors and two-component coupling. Herein, an N-heterocyclic carbene and photocatalyst catalyzed decarboxylative radical coupling of carboxylic acids and acyl imidazoles is disclosed, in which the carboxylic acids are directly used as radical precursors. The acyl imidazoles could also be generated in situ by reaction of a carboxylic acid with CDI thus furnishing a formally decarboxylative coupling of two carboxylic acids. In addition, the reaction is successfully extended to three-component coupling by using alkene as a third coupling partner via a radical relay process. The mild conditions, operational simplicity, and use of carboxylic acids as the reacting partners make our method a powerful strategy for construction of complex ketones from readily available starting materials, and late-stage modification of natural products and medicines.
Nine-day continuous recording of EEG and 2-hour of high-density EEG under chronic sleep restriction in mice
Authors: Han Hio-Been , Kim Bowon , Kim Youngsoo , Jeong Yong , Choi Jee Hyun 
Published: May 2022

AbstractThis work provides an EEG dataset collected from nine mice during the sleep deprivation (SD) paradigm for the sleep science community. It includes 9-day of continuous recording of the frontal and parietal EEG, accelerometer, and 2-hour of high-density EEG (HD-EEG) under SD and SD-free conditions. Eighteen hours of SD were conducted on 5 consecutive days. The HD-EEG data were saved in the EEGLAB format and stored as the brain imaging data structure (BIDS). These datasets can be used to (i) compare mouse HD-EEG to human HD-EEG, (ii) track oscillatory activities of the sleep EEG (e.g., slow waves, spindles) across the cortical regions under different conditions of sleep pressure, and (iii) investigate the cortical traveling waves in the mouse brain. We also provided Python code for basic analyses of this dataset, including the detection of slow waves and sleep spindles. We hope that our dataset will reveal hidden activities during sleep and lead to a better understanding of the functions and mechanisms of sleep.
Machine learning and bioinformatics approaches for classification and clinical detection of bevacizumab responsive glioblastoma subtypes based on miRNA expression
Authors: Shi Jian 
Published: May 2022

AbstractFor the precise treatment of patients with glioblastoma multiforme (GBM), we classified and detected bevacizumab (BVZ)-responsive subtypes of GBM and found their differential expression (DE) of miRNAs and mRNAs, clinical characteristics, and related functional pathways. Based on miR-21 and miR-10b expression z-scores, approximately 30% of GBM patients were classified as having the GBM BVZ-responsive subtype. For this subtype, GBM patients had a significantly shorter survival time than other GBM patients (p = 0.014), and vascular endothelial growth factor A (VEGF) methylation was significantly lower than that in other GBM patients (p = 0.005). It also revealed 14 DE miRNAs and 7 DE mRNAs and revealed functional characteristics between GBM BVZ subgroups. After comparing several machine learning algorithms, the construction and cross-validation of the SVM classifier were performed. For clinical use, miR-197 was optimized and added to the miRNA panel for better classification. Afterwards, we validated the classifier with several GBM datasets and discovered some key related issues. According to this study, GBM BVZ subtypes can be classified and detected by a combination of SVM classifiers and miRNA panels in existing tissue GBM datasets. With certain modifications, the classifier may be used for the classification and detection of GBM BVZ subtypes for future clinical use.
Mitochondrial genome recombination in somatic hybrids of Solanum commersonii and S. tuberosum
Authors: Cho Kwang-Soo , Lee Hyun-Oh , Lee Sang-Choon , Park Hyun-Jin , Seo Jin-Hee , Cho Ji-Hong , Park Young-Eun , Choi Jang-Gyu , Yang Tae-Jin 
Published: May 2022

AbstractInterspecific somatic hybridization has been performed in potato breeding experiments to increase plant resistance against biotic and abiotic stress conditions. We analyzed the mitochondrial and plastid genomes and 45S nuclear ribosomal DNA (45S rDNA) for the cultivated potato (S. tuberosum, St), wild potato (S. commersonii, Sc), and their somatic hybrid (StSc). Complex genome components and structure, such as the hybrid form of 45S rDNA in StSc, unique plastome in Sc, and recombinant mitogenome were identified. However, the mitogenome exhibited dynamic multipartite structures in both species as well as in the somatic hybrid. In St, the mitogenome is 756,058 bp and is composed of five subgenomes ranging from 297,014 to 49,171 bp. In Sc, it is 552,103 bp long and is composed of two sub-genomes of 338,427 and 213,676 bp length. StSc has 447,645 bp long mitogenome with two subgenomes of length 398,439 and 49,206 bp. The mitogenome structure exhibited dynamic recombination mediated by tandem repeats; however, it contained highly conserved genes in the three species. Among the 35 protein-coding genes of the StSc mitogenome, 21 were identical for all the three species, and 12 and 2 were unique in Sc and St, respectively. The recombinant mitogenome might be derived from homologous recombination between both species during somatic hybrid development.
Automatic lung segmentation in chest X-ray images using improved U-Net
Authors: Liu Wufeng , Luo Jiaxin , Yang Yan , Wang Wenlian , Deng Junkui , Yu Liang 
Published: May 2022

AbstractThe automatic segmentation of the lung region for chest X-ray (CXR) can help doctors diagnose many lung diseases. However, extreme lung shape changes and fuzzy lung regions caused by serious lung diseases may incorrectly make the automatic lung segmentation model. We improved the U-Net network by using the pre-training Efficientnet-b4 as the encoder and the Residual block and the LeakyReLU activation function in the decoder. The network can extract Lung field features efficiently and avoid the gradient instability caused by the multiplication effect in gradient backpropagation. Compared with the traditional U-Net model, our method improves about 2.5% dice coefficient and 6% Jaccard Index for the two benchmark lung segmentation datasets. Our model improves about 5% dice coefficient and 9% Jaccard Index for the private lung segmentation datasets compared with the traditional U-Net model. Comparative experiments show that our method can improve the accuracy of lung segmentation of CXR images and it has a lower standard deviation and good robustness.