bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sensitivity of Modeled Microphysics to Stochastically Perturbed Parameters
Authors: Vukicevic T. , Posselt D. J. , Stankovic A. 
Published: July 2022

AbstractThis study examines the characteristics of several model parameter perturbation methodologies for ensemble simulations of cloud microphysical processes in convection. A simplified 1D model is used to focus the results on cloud microphysics without the complication of feedbacks to the dynamics and environment. Several parameter perturbation methods are tested, including non‐stochastic and stochastic with various distributions and parameter covariance. We find that an ensemble comprised of different time‐invariant parameters (non‐stochastic) exhibits little bias, but small spread. In addition, its behavior does not respect the time evolution of convection through its various phases. Stochastic parameter (SP) methods in which no inter‐parameter covariance is applied produce greater spread, but significant bias. The bias is particularly large for lognormal parameter perturbation distributions. The ensemble spread is retained and the bias reduced when time‐varying parameter covariance is applied. In this case, the SP scheme is able to adapt to the time and state‐dependent covariance structures and produce ensemble characteristics that are consistent with the specific microphysical processes operating at any given time. The results suggest that SP schemes would benefit from inclusion of parameter covariances, and specifically those that vary with the state of the system. It also suggests that a Normal or LogNormal SP scheme with no covariance may significantly impact the ensemble bias. Finally, the results indicate that high temporal and spatial resolution observations may be needed to characterize the variability in parameter values and covariance.
Megathrust Heterogeneity, Crustal Accretion, and a Topographic Embayment in the Western Nepal Himalaya: Insights From the Inversion of Thermochronological Data
Authors: Fan Suoya , Murphy Michael A. , Whipp David M. , Saylor Joel E. , Copeland Peter , Hoxey Andrew K. , Taylor Michael H. , Stockli Daniel F. 
Published: July 2022

AbstractBetween 81°30ʹE and 83°E, the Himalayan range's “perfect” arcuate shape is interrupted by an embayment. We hypothesize that thrust geometry and duplexing along the megathrust at midlower‐crustal depths play a leading role in growth of the embayment as well the southern margin of the Tibetan plateau. To test this hypothesis, we conducted thermokinematic modeling of published thermochronologic data from the topographic and structural embayment in the western Nepal Himalaya to investigate the three‐dimensional geometry and kinematics of the megathrust at midlower‐crustal depths. Models that can best reproduce observed cooling ages suggest that the megathrust in the western Nepal Himalaya is best described as two ramps connected by a long flat that extends further north than in segments to the east and west. These models suggest that the high‐slope zone along the embayment lies above the foreland limb of an antiformal crustal accretion zone on the megathrust with lateral and oblique ramps at midlower‐crustal depths. The lateral and oblique ramps may have initiated by ca. 10 Ma. This process may have controlled along‐strike variation in Himalayan‐plateau growth and therefore development of the topographic embayment. Finally, we analyze geological and morphologic features and propose an evolution model in which landscape and drainage systems across the central‐western Himalaya evolve in response to crustal accretion at depth and the three‐dimensional geometry of the megathrust. Our work highlights the importance of crustal accretion at different depths in orogenic‐wedge growth and that the midlower crustal accretion determines the location of plateau edge.
First Pre‐Miocene Paleomagnetic Data From the Calabrian Block Document a 160° Post‐Late Jurassic CCW Rotation as a Consequence of Left‐Lateral Shear Along Alpine Tethys
Authors: Siravo Gaia , Speranza Fabio , Macrì Patrizia 
Published: July 2022

AbstractThe Calabrian block, along with Alboran, Kabylies, and Peloritani form isolated and enigmatic igneous/metamorphic terranes (AlKaPeCa) stacked over the Meso‐Cenozoic sedimentary successions of the Apennines and Maghrebides. They are commonly interpreted as fragments of the Hercynian chain rifted apart from Europe during Jurassic Alpine Tethys spreading, drifted southward during Neogene roll‐back of (Neo) Tethyan slab fragments for hundreds of kilometers on top of nappe piles. We report on the paleomagnetism of upper Triassic‐lower Miocene sedimentary rocks from the Longobucco succession that is transgressive over the crystalline Sila Massif (NE Calabria). Well‐defined magnetization directions carried by hematite were isolated in 10 sites (122 samples) in Jurassic rocks. Nine Toarcian and one Tithonian Ammonitico Rosso sites yielded a dual polarity “A” magnetization component whit a direction over 40° from the geocentric axial dipole (GAD) field direction, that supports a positive fold test. Five sites yielded a “B” normal polarity component NE (<40°) of the GAD direction characterized by a negative fold test. We interpret the B component as a Miocene magnetic overprint later clockwise rotated by ∼20° during the well‐known Pleistocene (1–2 Ma) rotation of Calabria. When corrected for such rotation, the A component defines a ∼160° counterclockwise (CCW) rotation of the Calabrian block with respect to Europe. Of these, ∼90° likely occurred along with Corsica‐Sardinia block during its Eocene‐Miocene rotation from the Provençal margin. Thus, the Calabrian block underwent an additional Cretaceous‐Eocene 70° CCW rotation that we relate to Early‐mid Cretaceous >500 km left‐lateral transcurrent motion between Africa and Europe.
Interaction Between Proton Aurora and Stable Auroral Red Arcs Unveiled by Citizen Scientist Photographs
Authors: Nishimura Y. , Bruus E. , Karvinen E. , Martinis C. R. , Dyer A. , Kangas L. , Rikala H. K. , Donovan E. F. , Nishitani N. , Ruohoniemi J. M. 
Published: July 2022

AbstractWe utilized citizen scientist photographs of subauroral emissions in the upper atmosphere and identified a repeatable sequence of proton aurora and subauroral red (SAR) arc during substorms. The sequence started with a pair of green diffuse emissions and a red arc that drifted equatorward during the substorm expansion phase. Simultaneous spectrograph and satellite observations showed that they were subauroral proton aurora, where ion precipitation created secondary electrons that illuminated aurora in green and red colors. The ray structures in the red arc also indicated existence of low‐energy electron precipitation. The green diffuse aurora then decayed but the red arc (SAR arc) continued to move equatorward during the substorm recovery phase. This sequence suggests that the SAR arc was first generated by secondary electrons associated with ion precipitation and may then transition to heat flux or Joule heating. Proton aurora provides observational evidence that ion injection to the inner magnetosphere is the energy source for the initiation of the SAR arc.
Spatiotemporal regulation of insulin signaling by liquid–liquid phase separation
Authors: Zhou Kun , Chen Qiaoli , Chen Jiamou , Liang Derong , Feng Weikuan , Liu Minjun , Wang Qi , Wang Ruizhen , Ouyang Qian , Quan Chao , Chen Shuai 
Published: July 2022

AbstractInsulin signals through its receptor to recruit insulin receptor substrates (IRS) and phosphatidylinositol 3-kinase (PI3K) to the plasma membrane for production of phosphatidylinositol-3,4,5-trisphosphate (PIP3) from phosphatidylinositol-4,5-bisphosphate [PI(4,5)P2], which consequently activates protein kinase B (PKB). How insulin signals transduce from the plasma membrane into the cytoplasm is not clearly understood. Here we show that liquid–liquid phase separation (LLPS) plays a critical role in spatiotemporal control of insulin signaling through regulating multiple components including IRS1. Both protein concentration and insulin stimulation can drive the formation of intracellular IRS1 condensates through LLPS. Components including PI(4,5)P2, p85-PI3K and PDK1 are constitutively present in IRS1 condensates whereas production of PIP3 and recruitment of PKB in them are induced by insulin. Thus, IRS1 condensates function as intracellular signal hubs to mediate insulin signaling, whose formation is impaired in insulin resistant cells. Collectively, these data reveal an important function of LLPS in spatiotemporal control of insulin signaling.
Age-dependent cognitive impairment, hydrocephalus and leukocyte infiltration in transgenic mice with endothelial expression of human EPHX2
Authors: Davis Catherine M. , Zhang Wenri H. , Bah Thierno M. , Roese Natalie E. , Allen Elyse M. , Leung Philberta , Boutros Sydney J. , Marzulla Tessa , Patel Esha , Nie Xiao , Alkayed Farah N. , Huang Justin H. , Jensen Michael A. , Raber Jacob , Pike Martin M. , Alkayed Nabil J. 
Published: July 2022

AbstractSoluble epoxide hydrolase (sEH) is upregulated in microvascular endothelium of human brain with vascular cognitive impairment (VCI). Transgenic endothelial expression of human sEH in mice (Tie2hsEH) induces endothelial dysfunction (ED), a pathogenetic mechanism of VCI. We sought to determine if endothelial upregulation of sEH is sufficient to cause cognitive impairment, and if cognitive impairment due to chronic hypoperfusion induced by unilateral common carotid artery occlusion (CCAO) is exacerbated in Tie2hsEH mice. Behavioral performance was assessed by the open field, rotarod, novel object, Morris water maze and fear conditioning tests. Cerebral blood flow and brain morphology were evaluated by MRI, and inflammatory changes investigated using immunohistochemistry and flow cytometry. We demonstrate that transgenic endothelial expression of sEH is sufficient to induce cognitive impairment, associated with leukocyte infiltration, brain atrophy and accelerated, age-dependent ventriculomegaly, identifying ED and sEH upregulation as potential underlying mechanisms and therapeutic targets for VCI.
Photoplethysmogram based vascular aging assessment using the deep convolutional neural network
Authors: Shin Hangsik , Noh Gyujeong , Choi Byung-Moon 
Published: July 2022

AbstractArterial stiffness due to vascular aging is a major indicator during the assessment of cardiovascular risk. In this study, we propose a method for age estimation by applying deep learning to a photoplethysmogram (PPG) for the non-invasive assessment of the vascular age. The proposed deep learning-based age estimation model consists of three convolutional layers and two fully connected layers, and was developed as an explainable artificial intelligence model with Grad-Cam to explain the contribution of the PPG waveform characteristic to vascular age estimation. The deep learning model was developed using a segmented PPG by pulse from a total of 752 adults aged 20–89 years, and the performance was quantitatively evaluated using the mean absolute error, root-mean-squared-error, Pearson’s correlation coefficient, and coefficient of determination between the actual and estimated ages. As a result, a mean absolute error of 8.1 years, root mean squared error of 10.0 years, correlation coefficient of 0.61, and coefficient of determination of 0.37, were obtained. A Grad-Cam, used to determine the weight that the input signal contributes to the result, was employed to verify the contribution to the age estimation of the PPG segment, which was high around the systolic peak. The results of this study suggest that a convolutional-neural-network-based explainable artificial intelligence model outperforms existing models without an additional feature detection process. Moreover, it can provide a rationale for PPG-based vascular aging assessment.
Altered subgenomic RNA abundance provides unique insight into SARS-CoV-2 B.1.1.7/Alpha variant infections
Authors: Parker Matthew D. , Stewart Hazel , Shehata Ola M. , Lindsey Benjamin B. , Shah Dhruv R. , Hsu Sharon , Keeley Alexander J. , Partridge David G. , Leary Shay , Cope Alison , State Amy , Johnson Katie , Ali Nasar , Raghei Rasha , Heffer Joe , Smith Nikki , Zhang Peijun , Gallis Marta , Louka Stavroula F. , Hornsby Hailey R. , Alamri Hatoon , Whiteley Max , Foulkes Benjamin H. , Christou Stella , Wolverson Paige , Pohare Manoj , Hansford Samantha E. , Green Luke R. , Evans Cariad , Raza Mohammad , Wang Dennis , Firth Andrew E. , Edgar James R. , Gaudieri Silvana , Mallal Simon ,   The COVID-19 Genomics UK (COG-UK) consortium, Collins Mark O. , Peden Andrew A. , de Silva Thushan I. 
Published: July 2022

AbstractB.1.1.7 lineage SARS-CoV-2 is more transmissible, leads to greater clinical severity, and results in modest reductions in antibody neutralization. Subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome. Applying our tool (periscope) to ARTIC Network Oxford Nanopore Technologies genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA is significantly increased in B.1.1.7 (alpha) infections (n = 879). This increase is seen over the previous dominant lineage in the UK, B.1.177 (n = 943), which is independent of genomic reads, E cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median sgRNA abundance. We demonstrate that ORF9b protein levels are increased 6-fold in B.1.1.7 compared to a B lineage virus in vitro. We hypothesise that increased ORF9b in B.1.1.7 is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT > CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3’ of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles to evaluate emerging potential variants of concern.
Floquet topological superconductivity induced by chiral many-body interaction
Authors: Kitamura Sota , Aoki Hideo 
Published: July 2022

AbstractNon-equilibrium engineering is becoming a seminal way for realising novel quantum phases that are unimaginable in equilibrium. In particular, Floquet theory applied to quantum mechanics revealed that we can even control the band topology in semimetallic/insulating systems, while the straightforward application to topological superconductivity fails for typical superconductors because the supercondicting gap function does not couple to the electromagnetic field in a direct manner. Here we show that we can overcome this difficulty by taking account of correlation effects. Namely, we study how a d-wave superconductivity is changed when illuminated by circularly-polarised light (CPL) in the repulsive Hubbard model in the strong-coupling regime. We adopt the Floquet formalism for the Gutzwiller-projected effective Hamiltonian with the time-periodic Schrieffer-Wolff transformation. We find that CPL induces a topological superconductivity with a d + id pairing, which arises from the chiral spin coupling and the three-site term generated by the CPL. The latter term remains significant even for low frequencies and low intensities of the CPL. This is clearly reflected in the obtained phase diagram against the laser intensity and temperature for various frequencies red-detuned from the Hubbard U, with the transient dynamics also examined. The phenomenon revealed here can open a novel, dynamical way to induce a topological superconductivity.
A survey on deep reinforcement learning architectures, applications and emerging trends
Authors: Balhara Surjeet , Gupta Nishu , Alkhayyat Ahmed , Bharti Isha , Malik Rami Q. , Mahmood Sarmad Nozad , Abedi Firas 
Published: July 2022

AbstractFrom a future perspective and with the current advancements in technology, deep reinforcement learning (DRL) is set to play an important role in several areas like transportation, automation, finance, medical and in many more fields with less human interaction. With the popularity of its fast‐learning algorithms there is an exponential increase in the opportunities for handling dynamic environments without any explicit programming. Additionally, DRL sophisticatedly handles real‐world complex problems in different environments. It has grasped great attention in the areas of natural language processing (NLP), speech recognition, computer vision and image classification which has led to a drastic increase in solving complex problems like planning, decision‐making and perception. This survey provides a comprehensive analysis of DRL and different types of neural network, DRL architectures, and their real‐world applications. Recent and upcoming trends in the field of artificial intelligence (AI) and its categories have been emphasized and potential challenges have been discussed.
Co‐opetitive mean field type game based task offloading strategy in multi‐access edge computing networks
Authors: Yang Xiangjiang , Zhou Xiaotian , Zhang Haixia , Yuan Dongfeng 
Published: July 2022

AbstractIn this paper, a novel co‐operative mean field type game based task offloading strategy is proposed for multi‐access edge computing networks. The objective is to optimally determine the tasks offloaded to each edge computing node (ECN) in the network so that to balance the overall system performance and individual revenue of each ECN. To do so, the utility function of each ECN is first formulated, which is the payback of his time and energy cost for processing the tasks, tailed with the penalty from the network for not processing the tasks on time. A mean field type game is then formulated, where each ECN can either cooperate or compete with each other to maximize their own utility. With respect to the proposed game, the direct method is applied to find the final solutions. Simulation results reveal that the proposed strategy can well balance the utility of each ECN and the overall efficiency of the system, leading to a better performance compared with its cooperative‐ and competitive‐counterparts.
Light field spatial super‐resolution via geometric feature interaction
Authors: Chen Xin , Chen Yilei , An Ping , Huang Xinpeng , Yang Chao 
Published: July 2022

AbstractLight field (LF) enables high‐dimensional image data representation since it can capture spatial and angular information of light rays simultaneously. The low spatial resolution caused by the limited imaging ability of the capturing equipment and the trade‐off between spatial and angular resolution greatly affects the quality and application of LF images. Here, an end‐to‐end LF super‐resolution method is proposed via geometric feature interaction. First, the low‐resolution LF images are stacked in the horizontal and vertical epipolar plane image (EPI) directions and form 3D VI stacks. Then, these stacks are put into a dual‐branch network, and 3D convolution is alternately performed on the viewpoint images (VIs) and EPIs by reshaping features for better feature extraction and interaction. The proposed method can fully explore the texture information and geometric consistency of the LF, and super‐resolve all VIs at the same time. Experimental results on both real‐world and synthetic LF datasets show that the proposed method has higher performance than other state‐of‐the‐art methods.
Performance assessment and validation of inverter control current controllers in reduced sensor maximum power point tracking based photovoltaic‐grid tied system
Authors: Patowary Moushumi , Haes Alhelou Hassan , Panda Gayadhar 
Published: July 2022

AbstractA relative assessment on conventional and adaptive current controllers used in reduced sensor‐maximum power point tracking (MPPT) based photovoltaic (PV)‐grid tied inverter systems for the improvement of system power quality is suggested. The steady‐state and transients errors produced in the conventional PI and proportional resonant controllers, which are used to generate the references, can be fixed by using an intelligent ADALINE‐LMS adaptive controller; moreover, it helps in reducing the %THD (total harmonic distortion) level measured at different power zones. Also, to track the maximum PV power, which is further integrated to DC‐bus, a reduced sensor‐based technology is added into the circuit that sidesteps the problem of tracking local MPP instead of global MPP and the drawbacks of using current sensors. The use of a reduced sensor‐based MPPT controller confirms extraction of maximum PV power and it guarantees a constant DC‐link voltage under all the possible test conditions. The overall control architectures and system performances, which are tested under different system dynamics, are validated through MATLAB/Simulink as well as experimental findings obtained using the dSPACE RTI 1202 interfacing kit. These experimental results confirm that the adaptive control technique used in reduced sensor‐MPPT based PV‐grid tied inverter systems performs unbeatably with balanced load and grid voltages, less harmonics, quick response time etc. under the operation of linear, non‐linear and transient loads, whereas, conventional controllers are best only for the linear loads.
Arc decomposition behavior of C4F7N/Air gas mixture and biosafety evaluation of its by‐products
Authors: Ye Fanchao , Zhang Xiaoxing , Li Yi , Wan Qianqian , Bauchire Jean‐Marc , Hong Dunpin , Xiao Song , Tang Ju 
Published: July 2022

AbstractAt present, reports on the arc interruption and decomposition behavior of a C4F7N/air gas mixture especially the biosafety of its by‐products are limited. Herein, a 57% C4F7N/43% air gas mixture was employed as an arc‐quenching medium to conduct 200 breaking tests on a load switch (630 A/24 kV). The arc interruption and decomposition behavior of the gas mixture were evaluated, and the biosafety of the decomposition products was assessed based on an acute inhalation toxicity test. It was found that the average arcing time of the 200 breakings was about 10.1 ms and that breakings were basically completed at the zero‐crossing of the second or third current half‐cycle. The gas mixture after breaking decomposed dramatically (the C4F7N content decreased by 75.6%), generating a large number of gaseous by‐products (CO, CF4, C2F6, C3F8, CF3CN, C4F8, CO2, C4F10N2, C3F6, C2N2, etc.) as well as solid by‐products (carbon particles). The lethal concentration of 50% (LC50, 4 h) of C4F7N/air after 200 breakings was 31 ppm (male mice) and 34 ppm (female mice), respectively, and the toxicity was classified as Grade 1. In general, C4F7N has an arc interruption capability, albeit weaker than that of SF6 under the same conditions. After breaking, the C4F7N gas mixture has a relatively high acute inhalation toxicity, and relevant safety protection measures for research or operation personnel are strictly needed.