bluuebunny/crossref_metadata_2025 huggingface dataset:
High-resolution inelastic x-ray scattering at the high energy density scientific instrument at the European X-Ray Free-Electron Laser
Authors: Wollenweber L. , Preston T. R. , Descamps A. , Cerantola V. , Comley A. , Eggert J. H. , Fletcher L. B. , Geloni G. , Gericke D. O. , Glenzer S. H. , Göde S. , Hastings J. , Humphries O. S. , Jenei A. , Karnbach O. , Konopkova Z. , Loetzsch R. , Marx-Glowna B. , McBride E. E. , McGonegle D. , Monaco G. , Ofori-Okai B. K. , Palmer C. A. J. , Plückthun C. , Redmer R. , Strohm C. , Thorpe I. , Tschentscher T. , Uschmann I. , Wark J. S. , White T. G. , Appel K. , Gregori G. , Zastrau U.
Published: January 2021

We introduce a setup to measure high-resolution inelastic x-ray scattering at the High Energy Density scientific instrument at the European X-Ray Free-Electron Laser (XFEL). The setup uses the Si (533) reflection in a channel-cut monochromator and three spherical diced analyzer crystals in near-backscattering geometry to reach a high spectral resolution. An energy resolution of 44 meV is demonstrated for the experimental setup, close to the theoretically achievable minimum resolution. The analyzer crystals and detector are mounted on a curved-rail system, allowing quick and reliable changes in scattering angle without breaking vacuum. The entire setup is designed for operation at 10 Hz, the same repetition rate as the high-power lasers available at the instrument and the fundamental repetition rate of the European XFEL. Among other measurements, it is envisioned that this setup will allow studies of the dynamics of highly transient laser generated states of matter.
A boundary value “reservoir problem” and boundary conditions for multi-moment multifluid simulations of sheaths
Authors: Cagas Petr , Hakim Ammar H. , Srinivasan Bhuvana
Published: January 2021

Multifluid simulations of plasma sheaths are increasingly used to model a wide variety of problems in plasma physics ranging from global magnetospheric flows around celestial bodies to plasma–wall interactions in thrusters and fusion devices. For multifluid problems, accurate boundary conditions to model an absorbing wall that resolves a classical sheath remain an open research area. This work justifies the use of vacuum boundary conditions for absorbing walls to show comparable accuracy between a multifluid sheath and lower moments of a continuum-kinetic sheath.
Existence of semiclassical solutions for some critical Dirac equation
Authors: Ding Yanheng , Guo Qi , Yu Yuanyang
Published: January 2021

In this paper, we study the following critical Dirac equation −iε∑k=13αk∂ku+aβu+V(x)u=P(x)f(|u|)u+Q(x)|u|u,x∈R3, where ɛ > 0 is a small parameter; a > 0 is a constant; α1, α2, α3, and β are 4 × 4 Pauli–Dirac matrices; and V, P, Q, and f are continuous but are not necessarily of class C1. We prove the existence and concentration of semiclassical solutions under suitable assumptions on the potentials V(x), P(x), and Q(x) by using variational methods. We also show the semiclassical solutions ωɛ with maximum points xɛ of |ωɛ| concentrating at a special set HP characterized by V(x), P(x), and Q(x) and for any sequence xε→x0∈HP,vε(x)≔ωε(εx+xε) converges in W1,q(R3,C4) for q ≥ 2 to a ground state solution u of −i∑k=13αk∂ku+aβu+V(x0)u=P(x0)f(|u|)u+Q(x0)|u|u,inR3. Finally, we estimate the exponential decay properties of solutions.
On explaining the surprising success of reservoir computing forecaster of chaos? The universal machine learning dynamical system with contrast to VAR and DMD
Authors: Bollt Erik
Published: January 2021

Machine learning has become a widely popular and successful paradigm, especially in data-driven science and engineering. A major application problem is data-driven forecasting of future states from a complex dynamical system. Artificial neural networks have evolved as a clear leader among many machine learning approaches, and recurrent neural networks are considered to be particularly well suited for forecasting dynamical systems. In this setting, the echo-state networks or reservoir computers (RCs) have emerged for their simplicity and computational complexity advantages. Instead of a fully trained network, an RC trains only readout weights by a simple, efficient least squares method. What is perhaps quite surprising is that nonetheless, an RC succeeds in making high quality forecasts, competitively with more intensively trained methods, even if not the leader. There remains an unanswered question as to why and how an RC works at all despite randomly selected weights. To this end, this work analyzes a further simplified RC, where the internal activation function is an identity function. Our simplification is not presented for the sake of tuning or improving an RC, but rather for the sake of analysis of what we take to be the surprise being not that it does not work better, but that such random methods work at all. We explicitly connect the RC with linear activation and linear readout to well developed time-series literature on vector autoregressive (VAR) averages that includes theorems on representability through the Wold theorem, which already performs reasonably for short-term forecasts. In the case of a linear activation and now popular quadratic readout RC, we explicitly connect to a nonlinear VAR, which performs quite well. Furthermore, we associate this paradigm to the now widely popular dynamic mode decomposition; thus, these three are in a sense different faces of the same thing. We illustrate our observations in terms of popular benchmark examples including Mackey–Glass differential delay equations and the Lorenz63 system.
Injection of a short electron bunch into THz radiation section with an undulator and strong guiding magnetic fields
Authors: Lurie Yu. , Bratman V. L.
Published: January 2021

To implement an efficient source of coherent radiation with negative mass longitudinal stabilization, the methods of the formation and injection of a dense electron bunch onto a stationary helical trajectory in a combined helical undulator and a strong uniform magnetic field are studied. Using a magnetic or electric lens permits sending particles almost along the converging lines of the magnetic field (magnetic following) and obtaining a nearly rectilinearly moving compressed bunch inside a solenoid. After that, the bunch can be injected into an adiabatically increasing field of the helical undulator. In this way, it is possible to excite operating undulator oscillations of particles, significantly mitigating the effects of destructive bunch expansion, the excitation of parasitic cyclotron oscillations, and velocity spread, thereby providing stabilization and terahertz radiation of a dense bunch. Due to a significant mode selection for an axis-encircling bunch, as well as due to the long-term interaction of the particles with a dominant mode, which is closest to the group synchronism conditions, radiation with a relatively narrow spectrum and high efficiency can be obtained even in a strongly oversized waveguide. An additional efficiency enhancement can be obtained due to the reduction of the velocity spread caused by the mutual Coulomb repulsion of electrons during injection due to the initial energy chirp of the bunch.
Compact, portable, laser induced fluorescence diagnostic for laboratory plasma sources
Authors: Paul M. C. , Steinberger T. E. , Lister E. A. M. , Arnold N. Ivan , Artis D. , Thakur S. Chakraborty , Hall T. , LeBlanc S. , Scime E. E. , Thomas E. , Tynan G. R.
Published: January 2021

As diagnostic groups are increasingly called upon to participate in experimental campaigns at remote facilities, there is a need to develop portable versions of plasma diagnostic systems. One such diagnostic is laser induced fluorescence (LIF). Here, we describe a portable LIF apparatus that eliminates the need for an optical table, beam splitters, and an optical chopper. All of the light exiting the laser system is coupled through optical fibers to the experiment and housekeeping diagnostics. The collected light is coupled through an optical fiber as well. A key feature is modulation of the tapered amplifier current instead of physical modulation of the laser output. Using this portable LIF system, measurements of ion temperature, ion flow, and relative metastable ion density are reported for two different remote experiments.
Use of hexapole magnet and spin flipper combined with time-of-flight analysis to characterize state-selected paramagnetic atomic/molecular beams
Authors: Kurahashi Mitsunori
Published: January 2021

In the past, the Stern–Gerlach experiment has been used as a standard method for analyzing the population of magnetic substates contained in spin-polarized and/or state-selected atomic/molecular beams. However, this experiment is quite demanding due to its low signal intensity and difficulty in beam alignment. The present study shows that the use of a hexapole magnet and a spin flipper, together with the time-of-flight analysis, allows us to conduct an almost equivalent analysis while greatly improving the signal intensity. Applications to the analysis of spin-polarized triplet excited helium and state-selected O2(  3 Σg−) beams are presented.
Reynolds analogy for the fluid flow past a flat plate at different regimes
Authors: Abramov A. A. , Butkovskii A. V.
Published: January 2021

The Reynolds analogy for the fluid flow past a flat plate at zero incidence is considered. For viscous incompressible fluid, we show that at any positive Eckert number, the Reynolds analogy as a function of the Prandtl number has a maximum. For a rarefied gas flow, we investigate the extended Reynolds analogy, i.e., the relation between the shear stress and the energy flux transferred to the plate using the direct simulation Monte Carlo method. We find that the extended Reynolds analogy for a supersonic monatomic rarefied gas flow with the temperature of the undisturbed gas equal to the surface temperature depends weakly on the Knudsen number, it is close to 0.5. We show that the extended Reynolds analogy for supersonic gas flow depends on the plate velocity and temperature and undisturbed gas temperature mainly via the Knudsen and Eckert numbers. We generalize the extended Reynolds analogy. The generalized Reynolds analogy depends on the Knudsen number much more than on the Eckert number.
Fast flux control of 3D transmon qubits using a magnetic hose
Authors: Gargiulo O. , Oleschko S. , Prat-Camps J. , Zanner M. , Kirchmair G.
Published: January 2021

Fast magnetic flux control is a crucial ingredient for circuit quantum electrodynamics (cQED) systems. So far, it has been a challenge to implement this technology with the high coherence 3D cQED architecture. In this paper, we control the magnetic field inside a superconducting waveguide cavity using a magnetic hose, which allows flux control of 3D transmon qubits on time scales less than 100 ns while maintaining a cavity quality factor larger than 106. The magnetic hose is designed as an effective microwave filter to not compromise the energy relaxation time of the qubit. The magnetic hose is a promising tool for fast magnetic flux control in various platforms intended for quantum information processing and quantum optics.
Polymorphic arrangement of an organic molecule in its hydration environment
Authors: Lucht Karsten , Morgenstern Karina
Published: January 2021

We investigate the polymorphism of complexes formed by the hydration of a functionalized azobenzene molecule by low-temperature scanning tunneling microscopy. Under conditions at which the water-less azobenzene molecules remain as monomers on Au(111), co-adsorption of water leads to water–azobenzene complexes. These complexes prefer to adopt linear arrangements of the azobenzene mediated by its functionalized end groups. Such structures may serve as model systems for investigating the influence of a solvent on a surface reaction.
Numerical analysis of combined electroosmotic-pressure driven flow of a viscoelastic fluid over high zeta potential modulated surfaces
Authors: Mahapatra Bimalendu , Bandopadhyay Aditya
Published: January 2021

We report a numerical study on the mixed electroosmotic and pressure-driven transport of an Oldroyd-B fluid through a microchannel having high surface charge modulated walls. We report an augmentation in the net-throughput for higher surface potentials and thinner electrical double layers. We have shown that the enhanced fluid elasticity is responsible for the generation of asymmetric flow structures inside the micro-channel. A great augmentation in the streaming current is achieved by increasing the strength of surface potential or reducing the thickness of the electrical double layer. By accounting for the nonlinear fluid behavior and nonlinear nature of ionic transport, we show that the electrochemical parameters such as zeta potential, the relative strength of the applied electric field and pressure gradient, followed by the thickness of the electrical double layer, contribute largely toward altering the net-throughput inside the micro-channel. We observe the formation and shifting of re-circulation zones due to the complex interaction of the fluid rheology and asymmetric surface potential at the channel walls. The results of the present study hold the key toward understanding the complex fluid flow mimicking bio-fluid transport in the microfluidic platform under the mixed influence of electroosmotic forcing and pressure gradient.
Frequency selectivity of spin Hall magnetoresistance sensor and its applications in eddy current testing
Authors: Lu Ling , Xie Hang , Luo Ziyan , Muthu Natchammai , Chen Xin , Li Xiaomin , Hua Younan , Wu Yihong
Published: January 2021

Recently, we have developed a spin Hall magnetoresistance (SMR) sensor using the spin–orbit torque effective field as the built-in linearization mechanism, which allows us to achieve a linear, zero-offset, and low-noise magnetic field sensor without any dedicated magnetic bias. In this work, we examine the response of the SMR sensor to a time-varying magnetic field and demonstrate that its inherent frequency selectivity makes it uniquely suited for applications in eddy current testing. By applying a square wave current to both the coil and the sensor, and with the help of principal component analysis, we show that it is possible to detect surface cracks on an aluminum plate with dimensions down to 0.2 mm, without the need to use any sophisticated detection circuitry.
New cutoff and resonance for dust acoustic waves in dusty mesosphere
Authors: Banerjee Gadadhar , Maitra Sarit , Dasgupta Chitrita
Published: January 2021

The WKB approximation has been employed to study the impacts of dust density inhomogeneity and dust size variation on dust acoustic (DA) wave propagation in the mesosphere. A local dispersion relation is obtained, which introduces one cutoff and one resonance frequency. It is shown that the growth rate of a gradient instability and the range of the amplifying wave propagation are substantially affected by the dust size distribution and density inhomogeneity. Moreover, in the low dust density region, the amplitude and the steepness of DA increase.
Rationalization of promoted reverse water gas shift reaction by Pt3Ni alloy: Essential contribution from ensemble effect
Authors: Zhang Hong , Wang Xuelong , Frenkel Anatoly I. , Liu Ping
Published: January 2021

Bimetallic alloys have attracted considerable attention due to the tunable catalytic activity and selectivity that can be different from those of pure metals. Here, we study the superior catalytic behaviors of the Pt3Ni nanowire (NW) over each individual, Pt and Ni NWs during the reverse Water Gas Shift (rWGS) reaction, using density functional theory. The results show that the promoted rWGS activity by Pt3Ni strongly depends on the ensemble effect (a particular arrangement of active sites introduced by alloying), while the contributions from ligand and strain effects, which are of great importance in electrocatalysis, are rather subtle. As a result, a unique Ni–Pt hybrid ensemble is observed at the 110/111 edge of the Pt3Ni NW, where the synergy between Ni and Pt sites is active enough to stabilize carbon dioxide on the surface readily for the rWGS reaction but moderate enough to allow for the facile removal of carbon monoxide and hydrogenation of hydroxyl species. Our study highlights the importance of the ensemble effect in heterogeneous catalysis of metal alloys, enabling selective binding–tuning and promotion of catalytic activity.
Subwavelength confinement of propagating surface acoustic waves
Authors: Ash B. J. , Rezk A. R. , Yeo L. Y. , Nash G. R.
Published: January 2021

The ability to confine light to subwavelength scales has led to exciting developments in fields ranging from sensing to single molecule chemistry. In this paper, we demonstrate how arrays of annular hole resonators can be used to confine surface acoustic waves (SAWs) to regions of the propagating surface that are much smaller than the wavelength of the SAWs. These microscopic elastic waves are used in devices for signal processing and sensing and, increasingly, in areas such as quantum information and microfluidics. This work potentially transforms the ability to enhance interactions with SAWs and could pave the way for advances that mirror those in nano-photonics.
Generation of plasmon modes in a supernarrow nanoslit formed by silver surfaces
Authors: Sarychev A.K. , Ivanov A.V. , Barbillon G.
Published: January 2021

We report a theoretical study of plasmon generation of a giant electromagnetic field in a supernarrow nanoslit formed by a silver cylinder and a flat mirror surface. It is shown that as the silver surfaces approach each other, gap plasmons are excited in the gap between them, which results in a resonant amplification of the field. It is demonstrated for the first time that the electric field amplification increases with decreasing distance between the cylindrical and flat surfaces and reaches saturation, at which the field intensity becomes record high, exceeding the incident wave intensity by ten orders of magnitude. The found gap plasmon modes will increase the sensitivity to the detection of small concentrations of molecules, down to single molecules, by the methods of giant Raman scattering of light and plasmon-enhanced IR spectroscopy.
Optical coherence tomograph for non-invasive examination of the human middle ear
Authors: Shilyagin P.A. , Novozhilov A.A. , Abubakirov T.E. , Dilenyan A.L. , Shakhov A.V. , Moiseev A.A. , Terpelov D.A. , Ksenofontov S.Yu. , Matkivsky V.A. , Gelikonov V.M. , Gelikonov G.V.
Published: January 2021

The paper describes the design of an optical coherence tomograph adapted for studying the state of the tympanic cavity of the human middle ear. We present the images obtained by the method of optical coherence tomography, which are characteristic of the norm and of the case of pathology – otitis media with effusion.
Ghost bats exhibit informative daily and seasonal temporal patterns in the production of social vocalisations
Authors: Hanrahan Nicola , Turbill Christopher , Armstrong Kyle N. , Dalziell Anastasia H. , Welbergen Justin A.
Published: January 2021

The ghost bat (Macroderma gigas) is a colonial and highly vocal species that is impacted by human visitation of caves. The ability to document behaviours inside the roost by recording vocalisations could provide an important new tool for the management of this disturbance-prone species by removing the need for in-person confirmation of reproductive activity, and, in turn, identifying roosts of conservation importance. To assess whether vocalisations are indicators of daily and seasonal behavioural events, we aimed to determine whether total vocal activity significantly varied by time of day and time of year and, further, how the relative frequencies of occurrence of three common social vocalisations (‘Chirp-trill’, ‘Squabble’ and ‘Ultrasonic Social’) aligned with previously reported seasonal reproductive behaviour. We recorded sound inside the largest known maternity roost, extracted all vocal signals and classified them into types using semiautomated methods. Total vocal activity varied significantly by time of day and time of year, peaking around sunrise and sunset, and during the mating and nursing seasons. The relative frequencies of occurrence of vocalisation types varied significantly seasonally, with the Chirp-trill and Squabble produced most during the mating season and first flight periods, whereas the Ultrasonic Social peaked during parturition and weaning periods. This timing aligns with a previously suggested vocalisation function, providing further evidence that these signals are important in mating and maternity behaviours. Further, this suggests that peaks in the relative frequency of occurrence of distinct social vocalisations may act as indicators of in-roost reproductive and pup development behaviours and provides a low-disturbance, semiautomated method for using long-term acoustic recordings to study and monitor behaviour in this sensitive species.
Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening
Authors: Kim Sung-Hyun , Yang Sumin , Lim Key-Hwan , Ko Euiseng , Jang Hyun-Jun , Kang Mingon , Suh Pann-Ghill , Joo Jae-Yeol
Published: January 2021

Exon splicing triggered by unpredicted genetic mutation can cause translational variations in neurodegenerative disorders. In this study, we discovered Alzheimer’s disease (AD)-specific single-nucleotide variants (SNVs) and abnormal exon splicing of the phospholipase c gamma-1 (
PLCγ1
) gene using genome-wide association study (GWAS) and a deep learning-based exon splicing prediction tool. GWAS revealed that the identified single-nucleotide variations were mainly distributed in the H3K27ac-enriched region of the
PLCγ1
gene body during brain development in an AD mouse model. A deep learning analysis, trained with human genome sequences, predicted 14 splicing sites in the human
PLCγ1
gene, one of which completely matched an SNV in exon 27 of the
PLCγ1
gene in an AD mouse model. In particular, the SNV in exon 27 of the
PLCγ1
gene is associated with abnormal splicing during messenger RNA maturation. Taken together, our findings suggest that this approach, which combines in silico and deep learning-based analyses, has potential for identifying the clinical utility of critical SNVs in AD prediction.
Climate shock effects and mediation in fisheries
Authors: Fisher Mary C. , Moore Stephanie K. , Jardine Sunny L. , Watson James R. , Samhouri Jameal F.
Published: January 2021

Significance

Climate shocks are increasingly disruptive to global food systems, with far-reaching consequences for resource-based communities. Yet quantitative assessments of community impacts rarely account for economic connectivity between alternative resources. We show that patterns of resource use influence the sensitivity of US West Coast fishing communities to unprecedented fishery closures in the wake of a recent climate shock. Patterns of participation in commercial fisheries were significantly altered during the fishery closures, but rebounded to preexisting states after closures were lifted, indicating community-level resilience to this particular perturbation. Our study provides evidence that more complex networks of resource use buffer the impact of climate shocks, and reveals strategies that alter emergent patterns of resource use in affected fishing communities.
Acute skin exposure to ultraviolet light triggers neutrophil-mediated kidney inflammation
Authors: Skopelja-Gardner Sladjana , Tai Joyce , Sun Xizhang , Tanaka Lena , Kuchenbecker James A. , Snyder Jessica M. , Kubes Paul , Mustelin Tomas , Elkon Keith B.
Published: January 2021

Significance

Neutrophils are the most abundant leukocytes in circulation and the first responders to infectious and sterile inflammation, including skin exposure to ultraviolet (UV) light. We demonstrate that neutrophils not only migrate to the UV light–exposed skin but also disseminate systemically. In the kidney, neutrophils mediate inflammatory and injury responses triggered by skin exposure to UV. They had a proinflammatory phenotype: increased production of reactive oxygen species and a subpopulation of neutrophils in the kidney extravasated from UV light-exposed skin tissue. These studies demonstrate a direct link between skin inflammation by UV light and kidney injury and implicate neutrophils as pathogenic mediators, therefore providing a model by which exposure to UV light might contribute to kidney damage in lupus patients.
Gold nanoparticle-based nanoprobes with enhanced tumor targeting and photothermal/photodynamic response for therapy of osteosarcoma
Authors: Xiong Shengren , Xiong Guosheng , Li Zhaohui , Jiang Qing , Yin Jia , Yin Ting , Zheng Hong
Published: January 2021

Abastract

Plasmonic nanomaterials, especially a wide variety of gold nanoparticles, demonstrate great potential for theranostics of cancer. Herein, a gold nanotriangle with CD133 and hyaluronic acid on its surface loaded with a near-infrared photosensitizer was prepared for enhanced photodynamic/photothermal combined anti-tumor therapy. CD133 and hyaluronic acid provide the nanoprobe with dual tumor targeting, while the hyaluronic acid also protects photosensitive drugs from photodegradation. Thus, the nanoprobe has enhanced photothermal/photodynamic effects. This integrated treatment strategy significantly enhanced photodynamic/photothermal destruction of osteosarcoma cells. In addition, this treatment, induced by mild irradiation with a single wavelength laser, inhibited tumor growth in an osteosarcoma mouse model. These results indicate that this systemic treatment strategy can achieve enhanced anti-tumor therapeutic effects through active tumor targeting and protection of the loaded drugs.
Bayesian parameter estimation using Gaussian states and measurements
Authors: Morelli Simon , Usui Ayaka , Agudelo Elizabeth , Friis Nicolai
Published: January 2021

Bayesian analysis is a framework for parameter estimation that applies even in uncertainty regimes where the commonly used local (frequentist) analysis based on the Cramér–Rao bound (CRB) is not well defined. In particular, it applies when no initial information about the parameter value is available, e.g., when few measurements are performed. Here, we consider three paradigmatic estimation schemes in continuous-variable (CV) quantum metrology (estimation of displacements, phases, and squeezing strengths) and analyse them from the Bayesian perspective. For each of these scenarios, we investigate the precision achievable with single-mode Gaussian states under homodyne and heterodyne detection. This allows us to identify Bayesian estimation strategies that combine good performance with the potential for straightforward experimental realization in terms of Gaussian states and measurements. Our results provide practical solutions for reaching uncertainties where local estimation techniques apply, thus bridging the gap to regimes where asymptotically optimal strategies can be employed.
Testing gravity with cold atom interferometry: results and prospects
Authors: Tino Guglielmo M
Published: January 2021

Atom interferometers have been developed in the last three decades as new powerful tools to investigate gravity. They were used for measuring the gravity acceleration, the gravity gradient, and the gravity-field curvature, for the determination of the gravitational constant, for the investigation of gravity at microscopic distances, to test the equivalence principle of general relativity and the theories of modified gravity, to probe the interplay between gravitational and quantum physics and to test quantum gravity models, to search for dark matter and dark energy, and they were proposed as new detectors for the observation of gravitational waves. Here I describe past and ongoing experiments with an outlook on what I think are the main prospects in this field and the potential to search for new physics.
BERT-GT: cross-sentence n-ary relation extraction with BERT and Graph Transformer
Authors: Lai Po-Ting , Lu Zhiyong
Published: January 2021

Motivation

A biomedical relation statement is commonly expressed in multiple sentences and consists of many concepts, including gene, disease, chemical and mutation. To automatically extract information from biomedical literature, existing biomedical text-mining approaches typically formulate the problem as a cross-sentence n-ary relation-extraction task that detects relations among n entities across multiple sentences, and use either a graph neural network (GNN) with long short-term memory (LSTM) or an attention mechanism. Recently, Transformer has been shown to outperform LSTM on many natural language processing (NLP) tasks.

Results

In this work, we propose a novel architecture that combines Bidirectional Encoder Representations from Transformers with Graph Transformer (BERT-GT), through integrating a neighbor–attention mechanism into the BERT architecture. Unlike the original Transformer architecture, which utilizes the whole sentence(s) to calculate the attention of the current token, the neighbor–attention mechanism in our method calculates its attention utilizing only its neighbor tokens. Thus, each token can pay attention to its neighbor information with little noise. We show that this is critically important when the text is very long, as in cross-sentence or abstract-level relation-extraction tasks. Our benchmarking results show improvements of 5.44% and 3.89% in accuracy and F1-measure over the state-of-the-art on n-ary and chemical-protein relation datasets, suggesting BERT-GT is a robust approach that is applicable to other biomedical relation extraction tasks or datasets.

Availability and implementation

the source code of BERT-GT will be made freely available at https://github.com/ncbi/bert_gt upon publication.

Supplementary information

Supplementary data are available at Bioinformatics online.
Long neglected diversity in the Accursed Mountains (western Balkan Peninsula):Ranunculus bertisceusis a genetically and morphologically divergent new species
Authors: Kuzmanović Nevena , Lakušić Dmitar , Frajman Božo , Stevanoski Ivana , Conti Fabio , Schönswetter Peter
Published: January 2021

Southern European mountain ranges have long been recognized as important hotspots of genetic diversity and areas of high endemism. Reflecting the geographical complexity of these mountain ranges, many European high-mountain species exhibit disjunctions on a variety of geographical scales. One of the long-neglected, poorly investigated and unresolved taxonomic problems concerns Apennine and Balkan members of Ranunculus section Leucoranunculus. According to the most recent taxonomic treatment, this section includes Ranunculus crenatus, distributed predominantly in siliceous massifs of the Carpathians and the Balkan Peninsula, but with a highly disjunct partial distribution area in the eastern Alps, and Ranunculus magellensis, which is usually considered a calcicolous endemic of the central Apennines. However, R. magellensis has also been suggested to occur in the carbonate ranges of the Albanian Alps, which would render this species amphi-Adriatic. We used complementary molecular methods (sequences of the nuclear ribosomal ITS region and of plastid DNA and amplified fragment length polymorphisms), relative genome size measurements and morphometric analyses to elucidate the relationships in Ranunculus section Leucoranunculus. Specifically, we asked if it comprises only a single, widespread and morphologically variable species or several narrowly distributed species with constant morphology. The results of our study showed that populations growing on limestone in the Albanian Alps in northern Albania and southern Montenegro are divergent and should be recognized as a new species, Ranunculus bertisceus Kuzmanović, D.Lakušić, Frajman & Schönsw., sp. nov. These populations differ not only from R. crenatus s.s., which grows on silicates, but also from the calcicolous Apennine endemic R. magellensis. The eastern Alpine populations of R. crenatus, which occur very locally in the Niedere Tauern area, originate from immigration from the Bosnian mountains.
Stability and fragmentation versus demographic expansion: different phylogeographic patterns in closely related sympatric legumes (Senna) from arid and semi-arid zones of mid-latitude South America
Authors: Robbiati Federico O , Nores María J , Anton Ana M , Fortunato Renée H
Published: January 2021

This is the first comparative research in which phylogeographical patterns and present and palaeoclimatic distribution were investigated in desert plants that inhabit the Argentinian Monte and Chaco biogeographic provinces. We investigated two closely related and partially sympatric species of legume shrubs, Senna aphylla and Senna pachyrrhiza, to contribute to understand the evolutionary history of arid plants and the impact of Quaternary climatic oscillations in these regions. We carried out phylogeographic analyses using plastid DNA accD-psa1 and rpL32-trnL sequences and reconstructed palaeodistribution by ecological niche modelling (ENM). In S. aphylla, that inhabits northern areas of the Monte, the haplotype network, demographic and spatial analyses and ENM indicated that the populations have remained demographic and spatially stable and would have undergone fragmentation in intermountain valleys and bolsons. In S. pachyrrhiza, distributed mainly along the Monte and southwestern Dry Chaco, the haplotype network presented a ‘star-like’ topology and demographic analyses and ENM supported a recent demographic expansion but no range expansion. The species diversified c. 2.5 Mya, survived Quaternary glaciations and responded differently to climatic changes, complex topography and environmental heterogeneity. The complex geological and climatic history of arid lands in mid-latitude South America provides different scenarios that promoted a mosaic of phylogeographical patterns.
Hybrid-based Deep Belief Network Model for Cement Compressive Strength Prediction
Authors: Shaswat Kumar
Published: January 2021

Compressive strength is one of the most important qualities of concrete, and most of the conventional regression models for predicting the concrete strength could not achieve an expected result due to the unstructured factors. Moreover, the utilization of machine learning and statistical approaches playing its vital role in predicting the concrete compressive strength based on mixture proportions accounting to its industrial importance as well. In this manner, this paper attempts to introduce a new deep learning-based prediction model that makes the prediction more accurate, hence Deep Belief Network (DBN) is used. Moreover, to make the prediction more precise, it is planned to have the fine-tuning of activation function and weights of DBN, which makes the model efficient in its performance. For this purpose, an improved optimization concept is introduced called Lion Algorithm with new Rate Evaluation, which is the modified Lion Algorithm (LA). Finally, the performance of the proposed model is evaluated over other state-of-the-art models concerning certain error analysis.
Repeated loss of consciousness as the first symptom of recurrence of head and neck malignancy: a case report
Authors: Funabashi Sayaka , Yamagata Kenichiro , Nishii Tatsuya , Kusano Kengo
Published: January 2021

Background

Head and neck malignancies rarely cause reflex syncope. Three mechanistic patterns of reflex syncope are known in such patients: carotid sinus syndrome, glossopharyngeal neuralgia syndrome, and parapharyngeal space lesions syncope syndrome. There are few reports describing parapharyngeal space lesions syncope syndrome.

Case summary

A 61-year-old man with a history of head and neck cancer underwent left lingual resection and left anterior cervical lymph node dissection followed by chemoradiotherapy. Two months later, he experienced his first syncope and was admitted to our hospital for further investigation. During the first few days in the hospital, he experienced loss of consciousness. Carotid artery massage and cervical rotation-extension examinations revealed no abnormalities, and glossopharyngeal neuralgia was not observed. Cervical computed tomography showed recurrence of tongue cancer infiltrating the para-nasopharyngeal space. Consequently, the patient had sinus pause during the loss of consciousness; hence, we suspected parapharyngeal space lesions syncope syndrome. Pacemaker implantation was considered but could not be performed as the patient passed away because of the original malignancy.

Discussion

Parapharyngeal space tumours are often characterized by the absence of subjective symptoms, although symptoms such as neck swelling and discomfort in the throat have been reported. Parapharyngeal space lesions syncope syndrome is caused by tumour invasion into the parapharyngeal space, and there is no known trigger for syncope. Our case is unique because the patient’s first symptom of recurrence of tongue cancer infiltrating the para-nasopharyngeal space was repeated loss of consciousness.
Genome sequence of Monilinia vaccinii-corymbosi sheds light on mummy berry disease infection of blueberry and mating type
Authors: Yow Ashley G , Zhang Yucheng , Bansal Kamaldeep , Eacker Stephen M , Sullivan Shawn , Liachko Ivan , Cubeta Marc A , Rollins Jeffrey A , Ashrafi Hamid
Published: January 2021

Mummy berry disease, caused by the fungal pathogen Monilinia vaccinii-corymbosi (Mvc), is one of the most economically important diseases of blueberries in North America. Mvc is capable of inducing two separate blighting stages during its life cycle. Infected fruits are rendered mummified and unmarketable. Genomic data for this pathogen is lacking, but could be useful in understanding the reproductive biology of Mvc and the mechanisms it deploys to facilitate host infection. In this study, PacBio sequencing and Hi-C interaction data were utilized to create a chromosome-scale reference genome for Mvc. The genome comprises nine chromosomes with a total length of 30 Mb, an N50 length of 4.06 Mb, and an average 413X sequence coverage. A total of 9399 gene models were predicted and annotated, and BUSCO analysis revealed that 98% of 1,438 searched conserved eukaryotic genes were present in the predicted gene set. Potential effectors were identified, and the mating-type (MAT) locus was characterized. Biotrophic effectors allow the pathogen to avoid recognition by the host plant and evade or mitigate host defense responses during the early stages of fruit infection. Following locule colonization, necrotizing effectors promote the mummification of host tissues. Potential biotrophic effectors utilized by Mvc include chorismate mutase for reducing host salicylate and necrotrophic effectors include necrosis-inducing proteins and hydrolytic enzymes for macerating host tissue. The MAT locus sequences indicate the potential for homothallism in the reference genome, but a deletion allele of the MAT locus, characterized in a second isolate, indicates heterothallism. Further research is needed to verify the roles of individual effectors in virulence and to determine the role of the MAT locus in outcrossing and population genotypic diversity.
Investigation and Resolution of Interference in the LC–QTOF-MS Detection of 4-MePPP
Authors: Allen Darren R , Warnholtz Christopher , McWhinney Brett C
Published: January 2021

An interference resulting in the false-positive detection of the synthetic cathinone 4ʹ-methyl-α-pyrrolidinopropiophenone (4-MePPP) in urine was suspected following the recent addition of 4-MePPP spectral data to a liquid chromatography–quadrupole time-of-flightmass spectrometry drug library. Although positive detection criteria were achieved, it was noted that all urine samples suspected of containing 4-MePPP also concurrently contained high levels of tramadol and its associated metabolites. Using quadrupole time-of-flightmass spectrometry software elucidation tools, candidate compounds for the suspected interference were proposed. To provide further confidence in the identity of the interference, in silico fragmentation tools were used to match product ions generated in the analysis with product ions predicted from the theoretical fragmentation of candidate compounds. The ability of the suspected interference to subsequently produce the required product ions for spectral library identification of 4-MePPP was also tested. This information was used to provide a high preliminary confidence in the compound identity prior to purchase and subsequent confirmation with certified reference material. A co-eluting isobaric interference was identified and confirmed as an in-source fragment of the tramadol metabolite, N,N-bisdesmethyltramadol. Proposed resolutions for this interference are also described and subsequently validated by retrospective interrogation of previous cases of suspected interference.
The effect of magnetic fields on properties of the circumgalactic medium
Authors: van de Voort Freeke , Bieri Rebekka , Pakmor Rüdiger , Gómez Facundo A , Grand Robert J J , Marinacci Federico
Published: January 2021

We study the effect of magnetic fields on a simulated galaxy and its surrounding gaseous halo, or circumgalactic medium (CGM), within cosmological ‘zoom-in’ simulations of a Milky Way-mass galaxy as part of the Simulating the Universe with Refined Galaxy Environments (SURGE) project. We use three different galaxy formation models, each with and without magnetic fields, and include additional spatial refinement in the CGM to improve its resolution. The central galaxy’s star formation rate and stellar mass are not strongly affected by the presence of magnetic fields, but the galaxy is more disc dominated and its central black hole is more massive when B > 0. The physical properties of the CGM change significantly. With magnetic fields, the circumgalactic gas flows are slower, the atomic hydrogen-dominated extended discs around the galaxy are more massive and the densities in the inner CGM are therefore higher, the temperatures in the outer CGM are higher, and the pressure in the halo is higher and smoother. The total gas fraction and metal mass fraction in the halo are also higher when magnetic fields are included, because less gas escapes the halo. Additionally, we find that the CGM properties depend on azimuthal angle and that magnetic fields reduce the scatter in radial velocity, whilst enhancing the scatter in metallicity at fixed azimuthal angle. The metals are thus less well-mixed throughout the halo, resulting in more metal-poor halo gas. These results together show that magnetic fields in the CGM change the flow of gas in galaxy haloes, making it more difficult for metal-rich outflows to mix with the metal-poor CGM and to escape the halo, and therefore should be included in simulations of galaxy formation.
Vector modes in ΛCDM: the gravitomagnetic potential in dark matter haloes from relativistic N-body simulations
Authors: Barrera-Hinojosa Cristian , Li Baojiu , Bruni Marco , He Jian-hua
Published: January 2021

We investigate the transverse modes of the gravitational and velocity fields in ΛCDM, based on a high-resolution simulation performed using the adaptive-mesh refinement general-relativistic N-body code gramses. We study the generation of vorticity in the dark matter velocity field at low redshift, providing fits to the shape and evolution of its power spectrum over a range of scales. By analysing the gravitomagnetic vector potential, which is absent in Newtonian simulations, in dark matter haloes with masses ranging from ∼1012.5 h−1M⊙ to ∼1015 h−1M⊙, we find that its magnitude correlates with the halo mass, peaking in the inner regions. Nevertheless, on average, its ratio against the scalar gravitational potential remains fairly constant, below percent level, decreasing roughly linearly with redshift and showing a weak dependence on halo mass. Furthermore, we show that the gravitomagnetic acceleration in haloes peaks towards the core and reaches almost 10−10  h cm/s2 in the most massive halo of the simulation. However, regardless of the halo mass, the ratio between the gravitomagnetic force and the standard gravitational force is typically at around the 10−5 level inside the haloes, again without significant radius dependence. This result confirms that the gravitomagnetic effects have negligible impact on structure formation, even for the most massive structures, although its behaviour in low density regions remains to be explored. Likewise, the impact on observations remains to be understood in the future.
SatGen: a semi-analytical satellite galaxy generator – I. The model and its application to Local-Group satellite statistics
Authors: Jiang Fangzhou , Dekel Avishai , Freundlich Jonathan , van den Bosch Frank C , Green Sheridan B , Hopkins Philip F , Benson Andrew , Du Xiaolong
Published: January 2021

We present a semi-analytical model of satellite galaxies, SatGen, which can generate large statistical samples of satellite populations for a host halo of desired mass, redshift, and assembly history. The model combines dark matter (DM) halo merger trees, empirical relations for the galaxy–halo connection, and analytical prescriptions for tidal effects, dynamical friction, and ram-pressure stripping. SatGen emulates cosmological zoom-in hydrosimulations in certain aspects. Satellites can reside in cored or cuspy DM subhaloes, depending on the halo response to baryonic physics that can be formulated from hydrosimulations and physical modelling. The subhalo profile and the stellar mass and size of a satellite evolve depending on its tidal mass-loss and initial structure. The host galaxy can include a baryonic disc and a stellar bulge, each described by a density profile that allows analytic satellite orbit integration. SatGen complements simulations by propagating the effect of halo response found in simulated field galaxies to satellites (not properly resolved in simulations) and outperforms simulations by sampling the halo-to-halo variance of satellite statistics and overcoming artificial disruption due to insufficient resolution. As a first application, we use the model to study satellites of Milky Way (MW)- and M31-sized hosts, making it emulate simulations of bursty star formation and of smooth star formation, respectively, and to experiment with a disc potential in the host halo. We find that our model reproduces the observed satellite statistics reasonably well. Different physical recipes make a difference in satellite abundance and spatial distribution at the 25 per cent level, not large enough to be distinguished by current observations given the halo-to-halo variance. The MW/M31 disc depletes satellites by ${\sim } 20{{\ \rm per\ cent}}$ and has a subtle effect of diversifying the internal structure of satellites, which is important for alleviating certain small-scale problems. We discuss the conditions for a massive satellite to survive in MW/M31.
Machine Learning the Cosmic Curvature in a Model-independent Way
Authors: Wang Guo-Jian , Ma Xiao-Jiao , Xia Jun-Qing
Published: January 2021

In this work, we achieve the determination of the cosmic curvature ΩK in a cosmological model-independent way, by using the Hubble parameter measurements H(z) and type Ia supernovae (SNe Ia). In our analysis, two nonlinear interpolating tools are used to reconstruct the Hubble parameter, one is the Artificial Neural Network (ANN) method, and the other is the Gaussian process (GP) method. We find that ΩK based on the GP method can be greatly influenced by the prior of H0, while the ANN method can overcome this. Therefore, the ANN method may have more advantages than GP in the measurement of the cosmic curvature. Based on the ANN method, we find a spatially open universe is preferred by the current H(z) and SNe Ia data, and the difference between our result and the value inferred from Planck CMB is 1.6σ. In order to test the reliability of the ANN method, and the potentiality of the future gravitational waves (GW) standard sirens in the measurement of the cosmic curvature, we constrain ΩK using the simulated Hubble parameter and GW standard sirens in a model-independent way. We find that the ANN method is reliable and unbiased, and the error of ΩK is ∼0.186 when 100 GW events with electromagnetic counterparts are detected, which is $\sim 56\%$ smaller than that constrained from the Pantheon SNe Ia. Therefore, the data-driven method based on ANN has potential in the measurement of the cosmic curvature.