bluuebunny/crossref_metadata_2025 huggingface dataset:
Bianchi I ‘asymptotically Kasner’ solutions of the Einstein scalar field equations
Authors: Ritchie J
Published: May 2022

In this work we investigate the asymptotic behaviour of solutions to the Einstein equations with a minimally coupled scalar field. The primary focus of the present paper here establishing under what conditions a solution becomes ‘asymptotically Kasner’ sufficiently close to the initial singularity. To address this question we restrict our attention to Bianchi I space-times. By restricting our attention to a strictly monotonic scalar field we are able to provide necessary conditions on a potential so that the resulting solution is asymptotically Kasner. Moreover, we provide both explicit and numerical examples of asymptotically Kasner space-times.
Antiferromagnetic skyrmion based shape-configured leaky-integrate-fire neuron device
Authors: Bindal Namita , Raj Ravish Kumar , Kaushik Brajesh Kumar
Published: May 2022

Spintronic devices based on antiferromagnetic (AFM) skyrmion motion on the nanotracks have gained significant interest as a key component of neuromorphic data processing systems. AFM skyrmions are favorable over the ferromagnetic (FM) skyrmions as they follow the straight trajectories and prevent its annihilation at the nanotrack edges. In this paper, the AFM skyrmion-based neuron device that exhibits the leaky-integrate-fire functionality is proposed for the first time. It exploits the current-driven skyrmion dynamics on the shape-configured nanotracks that are linearly decreasing and exponentially decaying. The device structure creates the regions from lower to higher energy states for the AFM skyrmions during its motion from the wider to narrower region. This causes the repulsion force from the nanotrack edges to act on the AFM skyrmion thereby, drifting it in the backward direction in order to minimize the system energy. This provides the leaking functionality to the neuron device without any external stimuli and additional hardware cost. The average velocities during the integration and leaky processes are in the order of 103 and 102 m s−1, respectively, for the linearly and exponentially tapered nanotracks. Moreover, the energy of the skyrmion is in the order 10−20 J. Hence, the suggested device opens up the path for the development of high-speed and energy-efficient devices in AFM spintronics for neuromorphic computing.
Flexoelectricity in periodically poled lithium niobate by PFM
Authors: Liang Xu , Yu Yiwen , Liu Ruijia , Liu Wenyuan , Shen Shengping
Published: May 2022

Piezoresponse force microscopy (PFM) has become an indispensable tool for investigating the electromechanical coupling properties of materials at the nanoscale, from bulk ferroelectric/piezoelectric materials to thin films. However, it has been gradually accepted that PFM signals can originate from various sources, including the piezoelectric effect, electrostatic interaction, and flexoelectric effect. Herein, we utilized the contact resonance-enhanced modes of PFM and non-contact Kelvin probe force microscopy to qualitatively and quantitatively determine the electromechanical coupling properties of periodically poled lithium niobite. We used the dc bias feedback from the kelvin-probe force microscopy to compensate for the interaction from the electrostatic force between the surface potential, and we demonstrate that the amplitude of the PFM signal on adjacent domains is asymmetric owing to the flexoelectricity. Based on theoretical and experimental data, we estimated the flexoelectric coefficient of lithium niobate to be on the order of 10−8 C m−1. Because the flexoelectric effect is inversely proportional to the critical dimension of the materials, our results suggest that flexoelectricity may play an important role in electromechanical coupling in periodically poled lithium niobate (PPLN) thin films. This work provides a new insight into the electromechanical coupling in PPLN; and might be helpful in designing lithium niobate-based integrated nanoelectromechanical devices, such as photonic and waveguide devices.
The role of the underlying event in the

Λc+

enhancement in high-energy pp collisions
Authors: Varga Zoltán , Vértesi Róbert
Published: May 2022

We study the enhanced production of charmed baryons relative to charmed mesons in proton–proton collisions at LHC energies. Utilizing PYTHIA 8 simulations with enhanced color-reconnection we propose methods based on the comparative use of several event-activity classifiers to identify the source of the charmed-baryon enhancement. We conclude that in this enhanced color-reconnection scenario the excess

Λ

c

+

production is primarily linked to the underlying event activity and not to the production of high-momentum jets.
Dirac-cone-like electronic states on nematic antiferromagnetic FeSe and FeTe
Authors: Zhao L L , Li Y Z , Zhao X M , Dai T A , Li Y R , Meng L J
Published: May 2022

We investigate the Dirac-cone-like (DCL) topological electronic properties of nematic-like antiferromagnetic (AFM) states of monolayer FeSe and FeTe designed artificially through first-principles calculations and Wannier-function-based tight-binding (WFTB) method. Our calculations reveal most of them have a pair of DCL bands on the Γ–X line in the Brillouin zone (BZ) near the Fermi level and open a gap of about 20 meV in the absence and presence of spin–orbit coupling (SOC), respectively, similar to the lowest-energy pair-checkerboard AFM FeSe. We further confirm that they are weak topological insulators based on nonzero Z
2 and fragile surface states, which are calculated by the WFTB method. For FeSe and FeTe in pair-checkerboard AFM states, we find that the in-plane compression strain in a certain range can give rise to another pair of DCL bands located on the Γ–X′ line in the BZ. In addition, the magnetic moments, energies, and Fe–Se/Te distances for various nematic-like AFM configurations are presented. These calculations the combining effect of magnetism and topology in a single material and the understanding of the superconducting phenomena in iron-based FeSe and FeTe.
Optical and optoelectronic neuromorphic devices based on emerging memory technologies
Authors: Shen Jiabin , Cheng Zengguang , Zhou Peng
Published: May 2022

As artificial intelligence continues its rapid development, inevitable challenges arise for the mainstream computing hardware to process voluminous data (Big data). The conventional computer system based on von Neumann architecture with separated processor unit and memory is approaching the limit of computational speed and energy efficiency. Thus, novel computing architectures such as in-memory computing and neuromorphic computing based on emerging memory technologies have been proposed. In recent years, light is incorporated into computational devices, beyond the data transmission in traditional optical communications, due to its innate superiority in speed, bandwidth, energy efficiency, etc. Thereinto, photo-assisted and photoelectrical synapses are developed for neuromorphic computing. Additionally, both the storage and readout processes can be implemented in optical domain in some emerging photonic devices to leverage unique properties of photonics. In this review, we introduce typical photonic neuromorphic devices rooted from emerging memory technologies together with corresponding operational mechanisms. In the end, the advantages and limitations of these devices originated from different modulation means are listed and discussed.
Controllable synthesis of BiPr composite oxide nanowires electrocatalyst for sensitive L-cysteine sensing properties
Authors: Huang Jianfeng , Tao Feihu , Li Feiyang , Cai Zhengyu , Zhang Yong , Fan Chuangang , Pei Lizhai
Published: May 2022

BiPr composite oxide nanowires with rhombodedral Bi1.35Pr0.65O3, monoclinic Bi2O3and monoclinic Pr5O9phases were synthesized via a facile sodium dodecyl sulfate (SDS) assisted hydrothermal route. The obtained nanowires were characterized by x-ray diffraction, electron microscopy, x-ray photoelectron spectroscopy and electrochemical measurements. The BiPr composite oxide nanowires possess poly-crystalline structure, semi-circular tips, diameter and length of 20–100 nm and several micrometers, respectively. SDS is essential for the formation of the BiPr composite oxide nanowires which can be explained by a SDS assisted hydrothermal growth process. Electrochemical impedance spectroscopy shows that the electrons are easier to transfer by the surface of the BiPr composite oxide nanowires modified glassy carbon electrode (GCE) than bare GCE. The BiPr composite oxide nanowires modified GCE possesses good electro-catalytic activity for L-cysteine detection with a pair of quasi-reversible cyclic voltammetry peaks at +0.04 V and –0.72 V for the oxidation and reduction of L-cysteine, respectively. The roles of the scan rate, electrolyte species and L-cysteine concentration on the electrochemical responses of L-cysteine at the nanowires modified GCE were systematically analyzed. The BiPr composite oxide nanowires modified GCE presents a linear response range from 0.001 to 2 mM and detection limit of 0.27μM, good reproducibility and stability.
Pulsed neutron source from interaction of relativistic laser pulse with micro-structure assisted pitcher–catcher target
Authors: Deng H X , Sha R , Hu L X , Jiang X R , Zhao N , Zou D B , Yu T P , Shao F Q
Published: May 2022

Neutron detection technology is a powerful method for characterizing fundamental and industrial materials, such as magnetic materials, nanomaterials, polymers, and biological substances. A compact pulsed neutron source is desired, as the traditional way of producing high-yield neutrons depends mainly on large-scale accelerators or fission reactors. Here, we propose a scheme to generate a high-yield pulsed neutron source by using a

>

100 fs relativistic laser pulse interacting with a micro-structure assisted pitcher–catcher target. Three-dimensional particle-in-cell and Monte Carlo hybrid simulations demonstrate that an energetic deuterium ion beam with a cutoff energy of 75 MeV and a 7.23

%

laser-to-deuterium energy conversion efficiency can be obtained with a laser pulse of intensity

1.37
×

10

20

W cm−2, duration 330 fs, power 34 TW and energy 6.7 J. When they strike the following lithium fluoride converter of thickness 2 cm, a large number of neutrons are thus produced via a 7Li(d,n) nuclear reaction. The neutron yield is up to 109 and its pulse duration is as short as 20 ps. This scheme could be realized in laboratories with current hundreds-of-terawatt or multi-petawatt laser facilities.
Experimental investigation of high velocity neutral flow interaction with a magnetized plasma
Authors: Kelly Charles L , Thoreau Peter , Little Justin M
Published: May 2022

Plasma aerocapture is an orbit insertion method that leverages a magnetic dipole plasma to generate drag by ionizing, capturing, and deflecting atmospheric flow. Key physical assumptions about energy and momentum exchange during aerocapture are tested here by a novel experiment that characterizes the interaction between a high velocity free molecular flow and a magnetized plasma. A neutral beam source accelerates ions from a helicon plasma to a conductive plate, neutralizes them, and reflects them as a collimated flow. A hollow cathode plasma with an applied axial magnetic field of 1 kg acts as the target for the flow. It is found that interaction with the flow causes an increase in both density and temperature of the target plasma by up to a factor of two. The voltage required to operate the hollow cathode at a fixed current is reduced by up to 5% while the neutral beam is operating, suggesting power deposition by the flow. A 0D power balance model is invoked to show that flow kinetic energy is absorbed by the plasma at a rate of up to 50% of the hollow cathode power. The absorbed power correlates linearly with an electron temperature increase of up to 100%, indicative of electron heating by flow kinetic energy transfer. Deflection of the flow by the plasma is not resolved due to extraneous forces on the measurement device and uncertainties in plasma properties. Using the results found here, it is shown that the experiment can feasibly scale to demonstrate significantly higher energy and momentum transfer as required for a plasma aerocapture proof-of-concept.
Bacterial active matter
Authors: Aranson Igor S
Published: May 2022

Bacteria are among the oldest and most abundant species on Earth. Bacteria successfully colonize diverse habitats and play a significant role in the oxygen, carbon, and nitrogen cycles. They also form human and animal microbiota and may become sources of pathogens and a cause of many infectious diseases. Suspensions of motile bacteria constitute one of the most studied examples of active matter: a broad class of non-equilibrium systems converting energy from the environment (e.g., chemical energy of the nutrient) into mechanical motion. Concentrated bacterial suspensions, often termed active fluids, exhibit complex collective behavior, such as large-scale turbulent-like motion (so-called bacterial turbulence) and swarming. The activity of bacteria also affects the effective viscosity and diffusivity of the suspension. This work reports on the progress in bacterial active matter from the physics viewpoint. It covers the key experimental results, provides a critical assessment of major theoretical approaches, and addresses the effects of visco-elasticity, liquid crystallinity, and external confinement on collective behavior in bacterial suspensions.
Towards high performance near infrared sensitive multilayer organic phototransistors: effects of the acceptor and its position
Authors: Tang Chenyu , Lu Chengyu , Dai Qingyong , Zhang Ningbo , Sun Lei , Xu Sunan , Peng Yingquan , Lv Wenli
Published: May 2022

Due to its strong optical absorption in the near infrared (NIR) region, lead phthalocyanine (PbPc) is frequently used as the photoactive material in NIR sensitive organic phototransistors (OPTs). Limited by the low charge carrier mobility of NIR sensitive organic semiconductors, the active part of NIR OPTs adopts generally multilayer or multicomponent structure consisting of electron donor, electron acceptor and charge transporting molecules. Here, we investigate the effect of acceptor locations in the active structure on the performances of NIR phototransistors with PbPc as the photoactive electron donor. The performances of OPTs with C60 layer lying on the top of PbPc (Si/SiO2/pentacene/PbPc/C60/Au (source and drain electrode, S&D)), above PbPc and Au S&D (Si/SiO2/pentacene/PbPc/Au (S&D)/C60)), and in the form of bulk-heterojunction with PbPc (Si/SiO2/pentacene/PbPc:C60/Au (S&D)) were comparatively studied. The results show that the device with pentacene/PbPc:C60 exhibits the best performance among them. At an incident light intensity of 0.08 mW cm−2, a high photoresponsivity of 44.35 A W−1, and specific detectivity of 1.08 × 1012 Jones are achieved.
A multi-level damage classification technique of aircraft plate structures using Lamb wave-based deep transfer learning network
Authors: Shao Weihan , Sun Hu , Wang Yishou , Qing Xinlin
Published: May 2022

Lamb wave-based damage detection is one of the most promising structural health monitoring (SHM) technologies for aircraft structures. In this paper, a Lamb wave-based deep transfer learning network is developed for multi-level damage classification of plate-type structures. A one-dimensional convolutional neural network (1D-CNN) is employed to deeply mine the damage characteristics of complex Lamb wave signals with multiple modes and multiple boundary reflections. The concept of multi-level damage classification is carried out to get different results for different engineers, and a multi-task cascaded 1D-CNN architecture is established for three levels of damage classifications, which is corresponding to different SHM levels, i.e. identifying the damage presence, location, and severity, respectively. In the multi-task cascaded architecture, a fine-tune transfer learning concept is adopted to share partial structures and weight values among different classification models, which could greatly improve the efficiency of the model calculation. In the multi-level damage classification model, the one-dimensional Lamb wave scattering signals with different damage locations and sizes are used as the input without any preprocessing steps, while the classifications of the damage presence, location and size are designated as output of different levels. An experiment has been conducted to verify the proposed multi-level damage classification model. The experimental results show that the training time of this model is reduced by 35% and the accuracy of the proposed model is greater than 99%, which verifies the effectiveness and reliability of the proposed technique.
Entanglement in prepare-and-measure scenarios: many questions, a few answers
Authors: Pauwels Jef , Tavakoli Armin , Woodhead Erik , Pironio Stefano
Published: May 2022

Entanglement and quantum communication are paradigmatic resources in quantum information science leading to correlations between systems that have no classical analogue. Correlations due to entanglement when communication is absent have for long been studied in Bell scenarios. Correlations due to quantum communication when entanglement is absent have been studied extensively in prepare-and-measure (PM) scenarios in the last decade. Here, we set out to understand and investigate correlations in scenarios that involve both entanglement and communication, focussing on entanglement-assisted (EA) PM scenarios. In a recent companion paper (arXiv:2103.10748), we investigated correlations based on unrestricted entanglement. Here, our focus is on scenarios with restricted entanglement. We establish several elementary relations between standard classical and quantum communication and their EA counterparts. In particular, while it was already known that bits or qubits assisted by two-qubit entanglement between the sender and receiver constitute a stronger resource than bare bits or qubits, we show that higher-dimensional entanglement further enhance the power of bits or qubits. We also provide a characterisation of generalised dense coding protocols, a natural subset of EA quantum communication protocols, finding that they can be understood as standard quantum communication protocols in real-valued Hilbert space. Though such dense coding protocols can convey up to two bits of information, we provide evidence, perhaps counter-intuitively, that resources with a small information capacity, such as a bare qutrits, can sometimes produce stronger correlations. Along the way we leave several conjectures and conclude with a list of interesting open problems.
On UV-completion of Palatini-Higgs inflation
Authors: Mikura Yusuke , Tada Yuichiro
Published: May 2022

We investigate the UV-completion of the Higgs inflation in
the metric and the Palatini formalisms. It is known that the cutoff
scales for the perturbative unitarity of these inflation models
become much smaller than the Planck scale to be consistent with
observations. Expecting that the low cutoff scales originate in the
curvature of a field-space spanned by the Higgs fields, we consider
embedding the curved field-space into a higher dimensional flat
space and apply this procedure to the metric-Higgs and the
Palatini-Higgs scenarios. The new field introduced in this way
successfully flattens the field-space and UV-completes the Higgs
inflation in the metric formalism. However, in the Palatini
formalism, the new field cannot uplift the cutoff up to the Planck
scale. We also discuss the unavoidable low cutoff in the Palatini
formalism in the context of the local conformal symmetry.
Unified neutron star EOSs and neutron star structures in RMF models
Authors: Xia Cheng-Jun , Maruyama Toshiki , Li Ang , Yuan Sun Bao , Long Wen-Hui , Zhang Ying-Xun
Published: May 2022

In the framework of the Thomas-Fermi approximation, we systematically study the EOSs and microscopic structures of neutron star matter in a vast density range with n
b ≈ 10−10-2 fm−3, where various covariant density functionals are adopted, i.e., those with nonlinear self couplings (NL3, PK1, TM1, GM1, MTVTC) and density-dependent couplings (DD-LZ1, DDME-X, PKDD, DD-ME2, DD2, TW99). It is found that the EOSs generally coincide with each other at n
b ≲ 10−4 fm−3 and 0.1 fm−3 ≲ n
b ≲ 0.3 fm−3, while in other density regions they are sensitive to the effective interactions between nucleons. By adopting functionals with a larger slope of symmetry energy L, the curvature parameter K
sym and neutron drip density generally increases, while the droplet size, proton number of nucleus, core-crust transition density, and onset density of non-spherical nuclei, decrease. All functionals predict neutron stars with maximum masses exceeding the two-solar-mass limit, while those of DD2, DD-LZ1, DD-ME2, and DDME-X predict optimum neutron star radii according to the observational constraints. Nevertheless, the corresponding skewness coefficients J are much larger than expected, while only the functionals MTVTC and TW99 meet the start-of-art constraints on J. More accurate measurements on the radius of PSR J0740 + 6620 and the maximum mass of neutron stars are thus essential to identify the functional that satisfies all constraints from nuclear physics and astrophysical observations. Approximate linear correlations between neutron stars’ radii at M = 1.4M
⊙ and 2M
⊙, the slope L and curvature parameter K
sym of symmetry energy are observed as well, which are mainly attributed to the curvature-slope correlations in the functionals adopted here. The results presented here are applicable for investigations of the structures and evolutions of compact stars in a unified manner.
A deep learning method for solving high-order nonlinear soliton equations
Authors: Cui Shikun , Wang Zhen , Han Jiaqi , Cui Xinyu , Meng Qicheng
Published: May 2022

We propose an effective scheme of the deep learning method for high-order nonlinear soliton equations and explore the influence of activation functions on the calculation results for higher-order nonlinear soliton equations. The physics-informed neural networks approximate the solution of the equation under the conditions of differential operator, initial condition and boundary condition. We apply this method to high-order nonlinear soliton equations, and verify its efficiency by solving the fourth-order Boussinesq equation and the fifth-order Korteweg–de Vries equation. The results show that the deep learning method can be used to solve high-order nonlinear soliton equations and reveal the interaction between solitons.
Variational Bayesian dropout with a Gaussian prior for recurrent neural networks application in rainfall–runoff modeling
Authors: Sadeghi Tabas S , Samadi S
Published: May 2022

Recurrent neural networks (RNNs) are a class of artificial neural networks capable of learning complicated nonlinear relationships and functions from a set of data. Catchment scale daily rainfall–runoff relationship is a nonlinear and sequential process that can potentially benefit from these intelligent algorithms. However, RNNs are perceived as being difficult to parameterize, thus translating into significant epistemic (lack of knowledge about a physical system) and aleatory (inherent randomness in a physical system) uncertainties in modeling. The current study investigates a variational Bayesian dropout (or Monte Carlo dropout (MC-dropout)) as a diagnostic approach to the RNNs evaluation that is able to learn a mapping function and account for data and model uncertainty. MC-dropout uncertainty technique is coupled with three different RNN networks, i.e. vanilla RNN, long short-term memory (LSTM), and gated recurrent unit (GRU) to approximate Bayesian inference in a deep Gaussian noise process and quantify both epistemic and aleatory uncertainties in daily rainfall–runoff simulation across a mixed urban and rural coastal catchment in North Carolina, USA. The variational Bayesian outcomes were then compared with the observed data as well as with a well-known Sacramento soil moisture accounting (SAC-SMA) model simulation results. Analysis suggested a considerable improvement in predictive log-likelihood using the MC-dropout technique with an inherent input data Gaussian noise term applied to the RNN layers to implicitly mitigate overfitting and simulate daily streamflow records. Our experiments on the three different RNN models across a broad range of simulation strategies demonstrated the superiority of LSTM and GRU approaches relative to the SAC-SMA conceptual hydrologic model.
Non-equilibrium thermodynamics of diffusion in fluctuating potentials
Authors: Alston Henry , Cocconi Luca , Bertrand Thibault
Published: May 2022

A positive rate of entropy production at steady-state is a distinctive feature of truly non-equilibrium processes. Exact results, while being often limited to simple models, offer a unique opportunity to explore the thermodynamic features of these processes in full detail. Here we derive analytical results for the steady-state rate of entropy production in single particle systems driven away from equilibrium by the fluctuations of an external potential of arbitrary shapes. Subsequently, we provide exact results for a diffusive particle in a harmonic trap whose potential stiffness varies in time according to both discrete and continuous Markov processes. In particular, studying the case of a fully intermittent potential allows us to introduce an effective model of stochastic resetting for which it is possible to obtain finite non-negative entropy production. Altogether, this work lays the foundation for a non-equilibrium thermodynamic theory of fluctuating potentials, with immediate applications to stochastic resetting processes, fluctuations in optical traps and fluctuating interactions in living systems.
Shooting function for 1D Schrödinger operators
Authors: MacKay R S
Published: May 2022

For Schrödinger operators with suitable 1D potentials, focussing particularly on those that go to infinity at infinity, a characteristic function is constructed, via shooting functions. It is proved to be entire and its zeroes to be the eigenvalues.
Computational properties of multi-compartment LIF neurons with passive dendrites
Authors: Stöckel Andreas , Eliasmith Chris
Published: May 2022

Mixed-signal neuromorphic computers often emulate some variant of the LIF neuron model. While, in theory, two-layer networks of these neurons are universal function approximators, single-layer networks consisting of slightly more complex neurons can, at the cost of universality, be more efficient. In this paper, we discuss a family of LIF neurons with passive dendrites. We provide rules that describe how input channels targeting different dendritic compartments interact, and test in how far these interactions can be harnessed in a spiking neural network context. We find that a single layer of two-compartment neurons approximates some functions at smaller errors than similarly sized hidden-layer networks. Single-layer networks with with three compartment neurons can approximate functions such as XOR and four-quadrant multiplication well; adding more compartments only offers small improvements in accuracy. From the perspective of mixed-signal neuromorphic systems, our results suggest that only small modifications to the neuron circuit are necessary to construct more computationally powerful and energy efficient systems that move more computation into the dendritic, analogue domain.
Developing metrics to assess the effectiveness of cybersecurity awareness program
Authors: Chaudhary Sunil , Gkioulos Vasileios , Katsikas Sokratis
Published: May 2022

Cybersecurity awareness (CSA) is not just about knowing, but also transforming things learned into practice. It is a continuous process that needs to be adjusted in subsequent iterations to improve its usability as well as sustainability. This is possible only if a CSA program is reviewed and evaluated timely. Review and evaluation of an awareness program offer an insight into the program's effectiveness on the audience and organization, an invaluable piece of information for the continuous improvement of the program. Further, it provides the information required by the management and sponsor to decide on whether to invest in the program or not. Despite these advantages, there does not exist a common understanding of what factors to measure and how to measure them during the evaluation process. As a result, we have proposed evaluation metrics for the purpose. In order to do so, we performed a literature review of 32 papers mainly to extract the following data: (i) what factors did the paper measure, and (ii) how did it measure the factors? Next, we adapted the European Literacy Policy Network's four indicators (i.e. impact, sustainability, accessibility, and monitoring) for awareness evaluation to make it appropriate for evaluating a CSA program. We believe that measuring all four indicators will contribute to making the evaluation process systematic, complete, and replicable. More importantly, it will help to produce more inclusive, accurate, and usable results for the future enhancement of the program.
The Effect of Thermally Robust Ballistic Mechanisms on Climatic Niche in Salamanders
Authors: Friedman Sarah T , Muñoz Martha M
Published: May 2022

Synopsis

Many organismal functions are temperature-dependent due to the contractile properties of muscle. Spring-based mechanisms offer a thermally robust alternative to temperature-sensitive muscular movements and may correspondingly expand a species’ climatic niche by partially decoupling the relationship between temperature and performance. Using the ballistic tongues of salamanders as a case study, we explore whether the thermal robustness of elastic feeding mechanisms increases climatic niche breadth, expands geographic range size, and alters the dynamics of niche evolution. Combining phylogenetic comparative methods with global climate data, we find that the feeding mechanism imparts no discernable signal on either climatic niche properties or the evolutionary dynamics of most climatic niche parameters. Although biomechanical innovation in feeding influences many features of whole-organism performance, it does not appear to drive macro-climatic niche evolution in salamanders. We recommend that future work incorporate micro-scale environmental data to better capture the conditions that salamanders experience, and we discuss a few outstanding questions in this regard. Overall, this study lays the groundwork for an investigation into the evolutionary relationships between climatic niche and biomechanical traits in ectotherms.
The Persistent Poverty of Diversity in International Relations and the Emergence of a Critical Canon
Authors: Andrews Nathan
Published: May 2022

Discussions about diversifying the discipline of international relations (IR) are often met with limited evidence in practice. Employing the concepts of epistemic oppression and academic dependency, this article contributes to filling the existing knowledge gap by examining what the pedagogical practices of IR professors, particularly in terms of syllabi design and content, tell us about the state of disciplinary diversity. The article examines results from a preliminary study that analyzes different graduate-level IR syllabi from leading universities in the Global North (represented by United States and United Kingdom) and Global South (Africa in particular) in order to determine how their design, including required readings and other pedagogical choices in the classroom, contributes to the explicit diversity needed to push IR beyond its usual canon. The findings suggest that although more perspectives have become accepted or recognized, what is considered essential for graduate students to study and further propagate is still primarily mainstream. Another point is that what has become known as “critical IR” cannot automatically be equated with diversity. This means there is the need to further interrogate and open up more avenues that go beyond what can be characterized as a “critical canon” of IR.
Application and Management of Cultured Epidermal Autografts on Posterior Burns—A 5-Year, Multicenter, Retrospective Review of Outcomes
Authors: Homsombath Bounthavy , Mullins Robert F , Brandigi Claus , Hassan Zaheed , Fagan Shawn , Craft-Coffman Beretta , Olaveson Tait , Fidler Philip , Cramer Caryn , Hershman John
Published: May 2022

Severe burns on the posterior trunk present a treatment challenge in that these surfaces bear the major portion of body weight, with shearing forces exerted when changing the patient from supine to prone position. In their high-volume center at Burn and Reconstructive Centers of America, the authors developed protocols for use of cultured epidermal autografts (CEAs) for coverage of large burns, including those specific to posterior burns. This paper describes techniques and approaches, including milestone timelines, to treat and manage these patients. Key factors for successful treatment begin with early development of a detailed surgical plan. Members of the trained team participate in the plan and understand standard procedures and any deviation. Patients are identified early for treatment with CEA so that a full thickness skin biopsy can be sent to the manufacturer for processing. Patients with >30% total body surface area (TBSA) burns are considered for CEA burn wound coverage due to the potential for conversion of superficial partial thickness to deep partial thickness or full thickness burns over hospitalization time. We also present the outcomes in patients with posterior trunk burns treated with CEA from 2016 to 2019 in three participating centers within our network. Data in 40 patients with mean TBSA of 56% demonstrated a high rate of successful CEA engraftment (83%), and overall survival rate (90%) following one or two applications with CEA and/or CEA + split thickness skin graft (STSG). Development of standard treatment protocols and surgical plans has enabled positive outcomes with CEA in severe burns including posterior burns.
Rehabilitation of Burn Victims: Improving Quality of Life in Victims With Face and Neck Burn Through an Augmented Reality Coupled Pamphlet
Authors: Zal Masoumeh , Deldar Kolsoum , Froutan Razieh , Ahmadabadi Ali , Mazlom Seyed Reza
Published: May 2022

The present study aimed to investigate the effect of implementing rehabilitation programs using an augmented reality (AR) coupled pamphlet on the quality of life (QOL) of patients with face/neck burns. This randomized clinical trial was conducted on 60 patients (intervention = 30, control = 30) admitted to the burn center of Imam Reza Hospital, Mashhad, Iran. Patients in the intervention group performed their rehabilitation program using AR coupled pamphlet during 6 weeks, while control patients used simple pamphlet. The Burn-Specific Health Scale for Face and Neck (BSHS-FN) was completed at the beginning, and 2 and 6 weeks after the intervention. The results for 2 weeks after intervention measures in model 1 ANCOVA showed significant raise of measures only for Hand function (P = .035). However, for the total QOL score and other domains the differences were not significant (All P > .05). Adjusting for confounders, model 2 ANCOVA showed similar results for 2 weeks after intervention. However, in both models, the results indicated significant intervention effect for 6 weeks after intervention in QOL score and all domains (All P < .05), so that the amount of increase in measures were significantly higher in the intervention group. According to the findings, implementing rehabilitation program for patients with face and neck burns using AR coupled pamphlet can improve their QOL.
Real-World Use of Tedizolid Phosphate for 28 Days or More: A Case Series Describing Tolerability and Clinical Success
Authors: Morrisette Taylor , Molina Kyle C , Da Silva Beatriz , Mueller Scott W , Damioli Laura , Krsak Martin , Miller Matthew A , Fish Douglas N
Published: May 2022

Tedizolid has activity against Gram-positive pathogens as well as Mycobacterium spp and Nocardia spp. Real-world evidence supporting long-term tolerability and clinical success of tedizolid is lacking. Prolonged tedizolid therapy (median, 188 days; interquartile range, 62–493 days) appeared to be well tolerated in 37 patients (8.1% experienced adverse effect leading to discontinuation). Clinical success was 81.3% in those evaluated.
A molecular framework of ethylene-mediated fruit growth and ripening processes in tomato
Authors: Huang Wei , Hu Nan , Xiao Zhina , Qiu Yuping , Yang Yan , Yang Jie , Mao Xin , Wang Yichuan , Li Zhengguo , Guo Hongwei
Published: May 2022

Although the role of ethylene in tomato (Solanum lycopersicum) fruit ripening has been intensively studied, its role in tomato fruit growth remains poorly understood. In addition, the relationship between ethylene and the developmental factors NON-RIPENING (NOR) and RIPENING INHIBITOR (RIN) during ripening is under debate. Here, we carried out comprehensive genetic analyses of genome-edited mutants of tomato ETHYLENE INSENSITIVE 2 (SlEIN2), four EIN3-like genes (SlEIL1–4), and three EIN3 BINDING F-box protein genes (SlEBF1–3). Both slein2-1 and the high-order sleil mutant (sleil1 sleil2 sleil3/SlEIL3 sleil4) showed reduced fruit size, mainly due to decreased auxin biosynthesis. During fruit maturation, slein2 mutants displayed the complete cessation of ripening, which was partially rescued by slebf1 but not slebf2 or slebf3. We also discovered that ethylene directly activates the expression of the developmental genes NOR, RIN, and FRUITFULL1 (FUL1) via SlEIL proteins. Indeed, overexpressing these genes partially rescued the ripening defects of slein2-1. Finally, the signal intensity of the ethylene burst during fruit maturation was intimately connected with the progression of full ripeness. Collectively, our work uncovers a critical role of ethylene in fruit growth and supports a molecular framework of ripening control in which the developmental factors NOR, RIN, and FUL1 act downstream of ethylene signaling.
Stochastic block models reveal a robust nested pattern in healthy human gut microbiomes
Authors: Cobo-López Sergio , Gupta Vinod K , Sung Jaeyun , Guimerà Roger , Sales-Pardo Marta
Published: May 2022

A key question in human gut microbiome research is what are the robust structural patterns underlying its taxonomic composition. Herein, we use whole metagenomic datasets from healthy human guts to show that such robust patterns do exist, albeit not in the conventional enterotype sense. We first introduce the concept of mixed-membership enterotypes using a network inference approach based on stochastic block models. We find that gut microbiomes across a group of people (hosts) display a nested structure, which has been observed in a number of ecological systems. This finding led us to designate distinct ecological roles to both microbes and hosts: generalists and specialists. Specifically, generalist hosts have microbiomes with most microbial species, while specialist hosts only have generalist microbes. Moreover, specialist microbes are only present in generalist hosts. From the nested structure of microbial taxonomies, we show that these ecological roles of microbes are generally conserved across datasets. Our results show that the taxonomic composition of healthy human gut microbiomes is associated with robustly structured combinations of generalist and specialist species.
Tick Size Wars: The Market Quality Effects of Pricing Grid Competition
Authors: Foley Sean , Meling Tom G , Ødegaard Bernt Arne
Published: May 2022

We explore the effects of a “tick size war” in which European trading venues directly competed on the minimum pricing increment in the limit order book, the tick size. We find that venues that reduced their tick size immediately captured market shares of both quoted and executed volume from the exchanges that kept their ticks large. We find that tick size competition improves market quality, reducing trading costs, and increasing market-wide depth and volume. These market quality improvements are strongest in stocks where the bid–ask spread was constrained to one tick, where liquidity providers use the finer pricing grid to engage in price competition.
Using Artificial Neural Networks to Predict Intra-Abdominal Abscess Risk Post-Appendectomy
Authors: Alramadhan Morouge M. , Al Khatib Hassan S. , Murphy James R. , Tsao KuoJen , Chang Michael L.
Published: May 2022

Objective:

To determine if artificial neural networks (ANN) could predict the risk of intra-abdominal abscess (IAA) development post-appendectomy.

Background:

IAA formation occurs in 13.6% to 14.6% of appendicitis cases with “complicated” appendicitis as the most common cause of IAA. There remains inconsistency in describing the severity of appendicitis with variation in treatment with respect to perforated appendicitis.

Methods:

Two “reproducible” ANN with different architectures were developed on demographic, clinical, and surgical information from a retrospective surgical dataset of 1574 patients less than 19 years old classified as either negative (n = 1,328) or positive (n = 246) for IAA post-appendectomy for appendicitis. Of 34 independent variables initially, 12 variables with the highest influence on the outcome selected for the final dataset for ANN model training and testing.

Results:

A total of 1574 patients were used for training and test sets (80%/20% split). Model 1 achieved accuracy of 89.84%, sensitivity of 70%, and specificity of 93.61% on the test set. Model 2 achieved accuracy of 84.13%, sensitivity of 81.63%, and specificity of 84.6%.

Conclusions:

ANN applied to selected variables can accurately predict patients who will have IAA post-appendectomy. Our reproducible and explainable ANNs potentially represent a state-of-the-art method for optimizing post-appendectomy care.
Additional Imaging is of Limited Value in Traumatic Hip Fractures With a History of Distant Malignancy and No Suspicious Lesion on Plain Radiographs
Authors: Sharrock Martin , Mati Wael , Peng Koh Shang , Abdullah Mustafa , Charalambous Charalambos P.
Published: May 2022

Objective:

To determine the value of obtaining additional preoperative imaging in patients with a traumatic hip fracture and a history of malignancy in whom plain radiographs show no lesion suspicious for metastases.

Design:

Retrospective review.

Setting:

Teaching NHS Trust in the United Kingdom, over an 8-year period treating 4421 hip fractures.

Patients/Participants:

Three hundred sixty-seven patients with hip fracture and a history of malignancy at a site distant to the hip. Three hundred thirty patients had a history of trauma and no lesion on the plain radiograph suspicious for metastases.

Main Outcomes Measurements:

Whether obtaining additional imaging preoperatively (MRI, CT, and bone scan) identified metastases or affected management.

Results:

32/330 patients had further preoperative imaging, none of which demonstrated a pathological fracture secondary to malignancy. On follow-up, 3/330 (0.9%) cases were found to have occult metastasis at the hip fracture site. All 3 had only plain radiographs before surgery. In 2, this was identified on histological examination of intraoperative samples, and in 1, radiologically as a metastatic metaphyseal lesion 18 months after a hemiarthroplasty. Only in the latter case, preoperative identification of hip metastasis could have altered surgical management. Patients undergoing further preoperative imaging waited significantly longer for surgery (35 ± 26 vs. 51 ± 26 hours, P = 0.0011).

Conclusions:

In the absence of a suspicious metastatic lesion on initial plain radiographs, further preoperative imaging is unlikely to identify a lesion that will affect management and confers significant delays to surgery. Sending intraoperative histological samples may help guide postoperative oncological management, but further work is needed to prove its utility.

Level of Evidence:

Diagnostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
Implementation of a Dedicated Orthopaedic Trauma Room in Hip and Femur Fracture Care: A 17-Year Analysis
Authors: Denisiuk Marek , Layson James T. , Bandovic Ivan , Waldron Jacob , Diedring Benjamin , Frisch Nicholas B. , Afsari Alan , Hayward R. David , Best Benjamin
Published: May 2022

Objective:

To examine the effects of implementing a dedicated orthopaedic trauma room (DOTR) on hip and femur fracture care.

Design:

A retrospective cohort study. Setting: Level 1 trauma center. Patients: 2928 patients with femoral neck, pertrochanteric, and femoral shaft and distal femur (FSDF) fractures.

Intervention:

Implementation of a DOTR.

Main Outcome Measures:

Hospital length of stay (LOS), emergency department (ED) LOS, intensive care unit (ICU) LOS, and time to operating room (TTOR).

Results:

Implementation of a DOTR resulted in significant improvement in TTOR for all patient groups (P < 0.05). We found shorter TTOR for pertrochanteric (P < 0.001), femoral neck (P = 0.039), and FSDF groups (P = 0.046). Total hospital LOS was shorter for patients with pertrochanteric (P < 0.001) and femoral neck fractures (P = 0.044). Patients with pertrochanteric hip fractures demonstrated shorter ICU LOS (P < 0.001). No LOS improvements were observed among patients in the FSDF group. ED LOS was significantly longer in all patient groups (P < 0.001).

Conclusions:

Implementation of a DOTR was associated with shorter TTOR, shorter hospital and ICU LOS, and longer ED LOS. There was a greater number of patients transferred into the investigating institution and fewer patients transferred out. These data support the utility of a DOTR as it relates to an improvement in hospital stay–related outcomes in patients with fractures of the hip and femur. Our results suggest that a DOTR in a Level I trauma hospital is associated with improvement in patient care.

Level of Evidence:

Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
Prospective Characterization of Pain and Function in Patients With Unstable Pelvic Fractures Treated With Posterior Screw Fixation
Authors: O'Hara Nathan N. , Sim Danielle , Moore Darby , Campbell Peter , Allen Vincent , Nascone Marco , Hasan Sania , Stockton David J. , Demyanovich Haley , Sciadini Marcus F. , O'Toole Robert V. , Slobogean Gerard P.
Published: May 2022

Objectives:

Describe patient-reported pain and function within 24 months of a pelvic fracture treated with posterior screw fixation and identify factors associated with increased pain.

Design:

Prospective case series.

Setting:

Academic trauma center.

Patients/Intervention:

Eighty-eight patients with adult pelvic fracture treated with sacroiliac or transiliac screws.

Main Outcome Measures:

Average pain measured with the Brief Pain Inventory (BPI); function measured with the Majeed Pelvic Outcome Score from 6 to 24 months postinjury.

Results:

The mean pain from 6 to 24 months postinjury was 2.22 on the 10-point BPI scale (95% CI, 0.64–3.81). Sixty-nine patients (78.4%) reported mild to no pain at 6 months; 12 (13.6%) patients had severe pain. Two years after injury, 71 patients (80.6%) exhibited mild to no pain. Within 24 months of injury, the mean pelvic function was 71 on the 100-point Majeed scale (95% CI, 60–82). Half of the sample (n = 44) had good to excellent pelvis function by 6 months postinjury; 55 patients (62.5%) attained this level of function by 24 months. A history of chronic pain (1.31; 95% CI, 0.26–2.37; P = 0.02), initial fracture displacement (≥5 mm) (0.99; 95% CI, 0.23–1.69; P = 0.01), and socioeconomic deprivation (0.28; 95% CI, 0.11–0.44; P < 0.01) were significantly associated with increased pain.

Conclusion:

Our findings suggest that most patients with unstable pelvic ring fractures treated with posterior screw fixation achieve minimal to no pelvis pain and good to excellent pelvic function 6–24 months after injury.

Level of Evidence:

Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.