bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of contact number among graphene nanosheets on the conductivities of tunnels and polymer composites
Authors: Zare Yasser , Kim Tae-Hoon , Gharib Nima , Chang Young-Wook 
Published: June 2023

AbstractSimple equations are expressed for tunnel conductivity, tunnel resistance and conductivity of a graphene-filled composite by the number of contacts and interphase part. More specially, the active filler amount is suggested by interphase depth, which changes the contact number. The conductivity of nanocomposite is presented by filler content, filler dimensions, tunneling length and interphase depth. The innovative model is surveyed by the experimented conductivity of real examples. Too, the impacts of numerous issues on the tunnel resistance, tunnel conductivity and conductivity of nanocomposite are discussed to validate the novel equations. The estimates agree with the experimented data and the impacts of several terms on the tunnel resistance, tunnel conductivity and conductivity of system are sensible. Thin and big nanosheets positively affect the nanocomposite’s conductivity, but thick nanosheets improve the tunnel conductivity. High conductivity is found at short tunnels, while the nanocomposite’s conductivity directly depends on the tunneling length. The dissimilar effects of these features on the tunneling properties and conductivity are described.
LKC-Net: large kernel convolution object detection network
Authors: Wang Weina , Li Shuangyong , Shao Jiapeng , Jumahong Huxidan 
Published: June 2023

AbstractDeep learning-based object detection methods have achieved great performance improvement. However, since small kernel convolution has been widely used, the semantic feature is difficult to obtain due to the small receptive fields, and the key information cannot be highlighted, resulting in a series of problems such as wrong detection, missing detection, and repeated detection. To overcome these problems, we propose a large kernel convolution object detection network based on feature capture enhancement and vast receptive field attention, called LKC-Net. Firstly, a feature capture enhancement block based on large kernel convolution is proposed to improve the semantic feature capturing ability, and depth convolution is used to reduce the number of parameters. Then, the vast receptive filed attention mechanism is constructed to enhance channel direction information extraction ability, and it is more compatible with the proposed backbone than other existing attention mechanisms. Finally, the loss function is improved by introducing the SIoU, which can overcome the angle mismatch problem between the ground truth and prediction box. Experiments are conducted on Pascal VOC and MS COCO datasets for demonstrating the performance of LKC-Net.
Host defense peptides combined with MTA extract increase the repair in dental pulp cells: in vitro and ex vivo study
Authors: Silva Poliana Amanda Oliveira , Martins Danilo César Mota , de Castro Cantuária Ana Paula , de Andrade Rosangela V. , Lacorte Cristiano , de Almeida Jeeser Alves , Aguiar Lana Ribeiro , Corrêa José Raimundo , da Silva Ingrid Gracielle Martins , Franco Octávio Luiz , Rezende Taia Maria Berto 
Published: June 2023

AbstractHost Defense Peptides (HDPs) have, in previous studies, been demonstrating antimicrobial, anti-inflammatory, and immunomodulatory capacity, important factors in the repair process. Knowing these characteristics, this article aims to evaluate the potential of HDPs IDR1018 and DJK-6 associated with MTA extract in the repair process of human pulp cells. Antibacterial activity of HDPs, MTA and HDPs combined with MTA in Streptococcus mutans planktonic bacteria and antibiofilm activity was evaluated. Cell toxicity was assayed with MTT and cell morphology was observed by scanning electron microscopy (SEM). Proliferation and migration of pulp cells were evaluated by trypan blue and wound healing assay. Inflammatory and mineralization related genes were evaluated by qPCR (IL-6, TNFRSF, DSPP, TGF-β). Alkaline phosphatase, phosphate quantification and alizarin red staining were also verified. The assays were performed in technical and biological triplicate (n = 9). Results were submitted for the calculation of the mean and standard deviation. Then, normality verification by Kolmogorov Smirnov test, analyzing one-way ANOVA. Analyses were considered at a 95% significance level, with a p-value < 0.05. Our study demonstrated that HDPs combined with MTA were able to reduce biofilms performed in 24 h and biofilm performed over 7 days S. mutans biofilm (p < 0.05). IDR1018 and MTA, as well as their combination, down-regulated IL-6 expression (p < 0.05). Tested materials were not cytotoxic to pulp cells. IDR1018 induced high cell proliferation and combined with MTA induced high cellular migration rates in 48 h (p < 0.05). Furthermore, the combination of IDR1018 and MTA also induced high expression levels of DSPP, ALP activity, and the production of calcification nodules. So, IDR-1018 and its combination with MTA could assist in pulp-dentine complex repair process in vitro.
Momentum-resolved spin-conserving two-triplon bound state and continuum in a cuprate ladder
Authors: Tseng Yi , Paris Eugenio , Schmidt Kai P. , Zhang Wenliang , Asmara Teguh Citra , Bag Rabindranath , Strocov Vladimir N. , Singh Surjeet , Schlappa Justine , Rønnow Henrik M. , Schmitt Thorsten 
Published: June 2023

AbstractStudying multi-particle elementary excitations has provided unique access to understand collective many-body phenomena in correlated electronic materials, paving the way towards constructing microscopic models. In this work, we perform O K-edge resonant inelastic X-ray scattering (RIXS) on the quasi-one-dimensional cuprate $${{{{{{\rm{Sr}}}}}}}_{14}{{{{{{\rm{Cu}}}}}}}_{24}{{{{{{\rm{O}}}}}}}_{41}$$

Sr

14

Cu

24

O

41

with weakly-doped spin ladders. The RIXS signal is dominated by a dispersing sharp mode ~ 270 meV on top of a damped incoherent component ~ 400-500 meV. Comparing with model calculations using the perturbative continuous unitary transformations method, the two components resemble the spin-conserving ΔS = 0 two-triplon bound state and continuum excitations in the spin ladders. Such multi-spin response with long-lived ΔS = 0 excitons is central to several exotic magnetic properties featuring Majorana fermions, yet remains unexplored given the generally weak cross-section with other experimental techniques. By investigating a simple spin-ladder model system, our study provides valuable insight into low-dimensional quantum magnetism.
A neural machine code and programming framework for the reservoir computer
Authors: Kim Jason Z. , Bassett Dani S. 
Published: June 2023

AbstractFrom logical reasoning to mental simulation, biological and artificial neural systems possess an incredible capacity for computation. Such neural computers offer a fundamentally novel computing paradigm by representing data continuously and processing information in a natively parallel and distributed manner. To harness this computation, prior work has developed extensive training techniques to understand existing neural networks. However, the lack of a concrete and low-level machine code for neural networks precludes us from taking full advantage of a neural computing framework. Here we provide such a machine code along with a programming framework by using a recurrent neural network—a reservoir computer—to decompile, code and compile analogue computations. By decompiling the reservoir’s internal representation and dynamics into an analytic basis of its inputs, we define a low-level neural machine code that we use to program the reservoir to solve complex equations and store chaotic dynamical systems as random-access memory. We further provide a fully distributed neural implementation of software virtualization and logical circuits, and even program a playable game of pong inside of a reservoir computer. Importantly, all of these functions are programmed without requiring any example data or sampling of state space. Finally, we demonstrate that we can accurately decompile the analytic, internal representations of a full-rank reservoir computer that has been conventionally trained using data. Taken together, we define an implementation of neural computation that can both decompile computations from existing neural connectivity and compile distributed programs as new connections.
Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection
Authors: Paranjpe Ishan , Jayaraman Pushkala , Su Chen-Yang , Zhou Sirui , Chen Steven , Thompson Ryan , Del Valle Diane Marie , Kenigsberg Ephraim , Zhao Shan , Jaladanki Suraj , Chaudhary Kumardeep , Ascolillo Steven , Vaid Akhil , Gonzalez-Kozlova Edgar , Kauffman Justin , Kumar Arvind , Paranjpe Manish , Hagan Ross O. , Kamat Samir , Gulamali Faris F. , Xie Hui , Harris Joceyln , Patel Manishkumar , Argueta Kimberly , Batchelor Craig , Nie Kai , Dellepiane Sergio , Scott Leisha , Levin Matthew A. , He John Cijiang , Suarez-Farinas Mayte , Coca Steven G. , Chan Lili , Azeloglu Evren U. , Schadt Eric , Beckmann Noam , Gnjatic Sacha , Merad Miram , Kim-Schulze Seunghee , Richards Brent , Glicksberg Benjamin S. , Charney Alexander W. , Nadkarni Girish N. 
Published: June 2023

Abstract
Background
Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms.

Methods
Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N = 437), we identified 413 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p < 0.05). Of these, 62 proteins were validated in an external cohort (p < 0.05, N = 261).

Results
We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p < 0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury.

Conclusions
Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.
Compressing fully connected layers of deep neural networks using permuted features
Authors: Nagaraju Dara , Chandrachoodan Nitin 
Published: June 2023

AbstractModern deep neural networks typically have some fully connected layers at the final classification stages. These stages have large memory requirements that can be expensive on resource‐constrained embedded devices and also consume significant energy just to read the parameters from external memory into the processing chip. The authors show that the weights in such layers can be modelled as permutations of a common sequence with minimal impact on recognition accuracy. This allows the storage requirements of FC layer(s) to be significantly reduced, which reflects in the reduction of total network parameters from 1.3× to 36× with a median of 4.45× on several benchmark networks. The authors compare the results with existing pruning, bitwidth reduction, and deep compression techniques and show the superior compression that can be achieved with this method. The authors also showed 7× reduction of parameters on VGG16 architecture with ImageNet dataset. The authors also showed that the proposed method can be used in the classification stage of the transfer learning networks.
Recurrent mini-outbursts and a magnetic white dwarf in the symbiotic system FN Sgr
Authors: Magdolen J. , Dobrotka A. , Orio M. , Mikołajewska J. , Vanderburg A. , Monard B. , Aloisi R. , Bezák P. 
Published: June 2023

Aims. We investigated the optical variability of the symbiotic binary FN Sgr with photometric monitoring over a period of ≃55 years and with a high-cadence Kepler light curve lasting 81 days.
Methods. The data obtained in the V and I bands were reduced with standard photometric methods. The Kepler data were divided into subsamples and were analysed with the Lomb-Scargle algorithm.
Results. The V and I band light curves show a phenomenon never before observed with such recurrence in any symbiotic system, namely short outbursts starting between orbital phases 0.3 and 0.5 and lasting about 1 month, with a fast rise, a slower decline, and amplitudes of 0.5–1 mag. In the Kepler light curve, we discovered three frequencies with sidebands. We attribute a stable frequency of 127.5 d−1 (corresponding to a period of 11.3 min) to the white dwarf rotation. We suggest that this detection probably implies that the white dwarf accretes through a magnetic stream, as in intermediate polars. The small outbursts may be ascribed to the stream–disc interaction. Another possibility is that they are due to localised thermonuclear burning, perhaps confined by the magnetic field, such as those recently inferred in intermediate polars, albeit on different timescales. We also measured a second frequency around 116.9 d−1 (corresponding to about 137 min), which is much less stable and has a drift. This latter may be due to rocky detritus around the white dwarf, but is more likely caused by an inhomogeneity in the accretion disc. Finally, there is a third frequency close to the first one that appears to correspond to the beating between the rotation and the second frequency.
High-contrast detection of exoplanets with a kernel-nuller at the VLTI
Authors: Chingaipe Peter Marley , Martinache Frantz , Cvetojevic Nick , Ligi Roxanne , Mary David , N’Diaye Mamadou , Defrère Denis , Ireland Michael J. 
Published: June 2023

Context. The conventional approach to direct imaging is to use a single aperture coronagraph with wavefront correction via extreme adaptive optics (AO). Such systems are limited to observing beyond an inner working angle (IWA) of a few λ/D. Nulling interferometry with two or more apertures will enable detections of companions at separations at and beyond the formal diffraction limit.
Aims. In this paper, we evaluate the astrophysical potential of a kernel-nuller as the prime high-contrast imaging mode of the Very Large Telescope Interferometer (VLTI).
Methods. By taking into account baseline projection effects induced by Earth rotation, we introduce some diversity in the response of the nuller as a function of time. This response is depicted by transmission maps. We also determine whether we can extract the astrometric parameters of a companion from the kernel outputs, which are the primary intended observable quantities of the kernel-nuller. This then leads us to comment on the characteristics of a possible observing program for the discovery of exoplanets.
Results. We present transmission maps for both the raw nuller outputs and their subsequent kernel outputs. To further examine the properties of the kernel-nuller, we introduce maps of the absolute value of the kernel output. We also identify 38 targets for the direct detection of exoplanets with a kernel-nuller at the focus of the VLTI.
Conclusions. With continued upgrades of the VLTI infrastructure, which will reduce fringe tracking residuals, a kernel-nuller would enable the detection of young giant exoplanets at separations <10 AU, where radial velocity and transit methods are more sensitive.
iNNterpol: High-precision interpolation of stellar atmospheres with a deep neural network using a 1D convolutional auto encoder for feature extraction
Authors: Westendorp Plaza C. , Asensio Ramos A. , Allende Prieto C. 
Published: June 2023

Context. Given the widespread availability of grids of models for stellar atmospheres, it is necessary to recover intermediate atmospheric models by means of accurate techniques that go beyond simple linear interpolation and capture the intricacies of the data.Aims. Our goal is to establish a reliable, precise, lightweight, and fast method for recovering stellar model atmospheres, that is to say the stratification of mass column, temperature, gas pressure, and electronic density with optical depth given any combination of the defining atmospheric specific parameters: metallicity, effective temperature, and surface gravity, as well as the abundances of other key chemical elements.Methods. We employed a fully connected deep neural network which in turn uses a 1D convolutional auto-encoder to extract the nonlinearities of a grid using the ATLAS9 and MARCS model atmospheres.Results. This new method we call iNNterpol effectively takes into account the nonlinearities in the relationships of the data as opposed to traditional machine-learning methods, such as the light gradient boosting method (LightGBM), that are repeatedly used for their speed in well-known competitions with reduced datasets. We show a higher precision with a convolutional auto-encoder than using principal component analysis as a feature extractor. We believe it constitutes a useful tool for generating fast and precise stellar model atmospheres, mitigating convergence issues, as well as a framework for future developments. The code and data for both training and direct interpolation are available online for full reproducibility and to serve as a practical starting point for other continuous 1D data in the field and elsewhere.
Hunting for gamma-ray emission from fast radio bursts
Authors: Principe G. , Di Venere L. , Negro M. , Di Lalla N. , Omodei N. , Di Tria R. , Mazziotta M. N. , Longo F. 
Published: June 2023

Context.Fast radio bursts (FRBs) are a recently discovered class of GHz-band, ms-duration, Jansky-level-flux astrophysical transients. Although hundreds of models have been proposed so far for FRB progenitors (the most popular ones involve magnetars), their physical origin and emission mechanism are still a mystery, making them one of the most compelling problems in astrophysics.Aims.FRBs are caused by astrophysical processes that are not yet understood. Exploring their high-energy counterpart is crucial for constraining their origin and emission mechanism.Methods.Thanks to more than 13 years of gamma-ray data collected by the Large Area Telescope on board theFermiGamma-ray Space Telescope, and to more than 1000 FRB events (from 561 non-repeating and 22 repeating sources), one of the largest samples created thus far, we performed the largest and deepest search for high-energy emission from FRB sources to date (between 100 MeV and 1 TeV). In addition to the analysis involving individual FRB events on different timescales (from a few seconds up to several years), we performed, for the first time, a stacking analysis on the full sample of FRB events as well as a search for triplet photons in coincidence with the radio event.Results.We do not detect significant emission, reporting the most stringent constraints, on short timescales, for the FRB-like emission from SGR 1935+2154 withEγ < 1041erg, corresponding to a factorη < 107with respect to the emitted radio energy. Similarly, for the stacked signal of steady emission from all repeaters, the obtained upper limit (UL) on the FRBs luminosity (Lγ < 1.6 × 1043erg s−1) is more than two orders of magnitude lower than those derived from the individual sources. Finally, no individual or triplet photons have been significantly associated with FRB events. We derived the LAT ms-sensitivity to be ∼0.3 ph cm−2s−1and constrained the gamma-ray energyEγ,δT = 1 ms ≲ 1047(DL/150 Mpc)2erg, ruling out a gamma-ray-to-radio energy ratio greater than 109on ms timescales.Conclusions.The results reported here represent the most stringent UL reported so far on the high-energy emission from FRBs on short and long time scales, as well as on cumulative emission and individual photon searches. While the origin of FRBs is still unclear, our work provides important constraints for FRB modelling, which might shed light on their emission mechanism.
Catalytic Dehydrative Transformations Mediated by Moisture-Tolerant Zirconocene Triflate
Authors: Lundberg Helena , Margarita Cristiana , Di Francesco Davide 
Published: June 2023

AbstractZirconocene triflate is a powerful moisture-tolerant catalyst for activation of C–O bonds in carboxylic acids and alcohols in the absence of water scavenging techniques. Herein, an overview of the use of this robust metal complex for direct amidation, esterification, and etherification is presented, along with a discussion on mechanistic aspects of the transformations and the catalyst class.
Iodine-Catalyzed Simple and Efficient Synthesis of 1,3,5-Triarylbenzenes and 2,3-Dihydrobenzofuran Derivatives under Mild Reaction Conditions
Authors: Meng Xiangzhen , Cheng Dong , Li Dongmei , Jie Sunying , Liu Yifan , Jiao Xiaoqing 
Published: June 2023

AbstractThe I2-catalyzed cyclization reaction of chalcones and 2-aryl propionaldehydes or isobutyraldehyde has been developed for the synthesis of 1,3,5-triarylbenzenes and 2,3-dihydrobenzofuran derivatives. This reaction tolerates a wide range of functional groups. Moreover, this method features an inexpensive catalyst and available starting materials.
Incidental Finding of Arteria Lusoria in COVID-19 Patient with Aortic Thrombus Complicated by Recurrent Limb Ischemia
Authors: Khedija Soumer , Nadia Azabou , Houcine Horchani , Mouna Bousnina , Amine Jemel 
Published: June 2023

AbstractCoronavirus disease causes a hypercoagulable state with endothelial inflammation. These conditions can produce embolic complications. Thrombosis can occur in different locations and may lead to ischemic stroke and ischemic limb.We report the case of a 64-year-old woman with recent severe acute respiratory syndrome coronavirus 2 pneumonia who was admitted to the hospital due to a giant floating thrombus in the ascending aorta with multiple ischemic events. Aortic computed tomography angiogram revealed an aberrant right subclavian artery associated with bicarotid trunk that might have protected carotid arteries from embol migration. Thrombosis is a rare clinical presentation in coronavirus disease 2019 infection but with serious complications that must be kept in mind to detect and avoid morbidities like ischemic stroke.
Malignant Pleural Effusions in the Era of Immunotherapy and Antiangiogenic Therapy
Authors: Wong Terrence , Fuld Alexander D. , Feller-Kopman David J. 
Published: June 2023

AbstractMalignant pleural effusions (MPE) have historically been associated with a poor prognosis, and patients often require a series of invasive procedures and hospitalizations that significantly reduce quality of life at the terminus of life. However, advances in the management of MPE have coincided with the era of immunotherapies, and to a lesser extent, antiangiogenic therapies for the treatment of lung cancer. Landmark studies have shown these drugs to improve overall survival and progression-free survival in patients with lung cancer, but a paucity of phase III trial data exists for the impact of immune checkpoint inhibitors (ICI) on lung cancers associated with MPE. This review will focus on the leading studies investigating the impact of ICI and antiangiogenic therapies in patients with lung cancer and MPE. The diagnostic and prognostic values of vascular endothelial growth factor and endostatin expression levels in malignancy will also be discussed. These advancements are changing the paradigm of MPE management from palliation to treatment for the first time since 1767 when MPE was first reported. The future holds the promise of durable response and extended survival in patients with MPE.