Single Field Research Articles

Lanthanum modulated reaction pacemakers on a single catalytic nanoparticle

Promoters are important in catalysis, but the atomistic details of their function and particularly their role in reaction instabilities such as kinetic phase transitions and oscillations are often unknown. Employing hydrogen oxidation as probe reaction, a Rh nanotip for mimicking a single Rh nanoparticle and field electron microscopy for in situ monitoring, we demonstrate a La-mediated local catalytic effect. The oscillatory mode of the reaction provides a tool for studying the interplay between different types of reaction pacemakers, i.e., specific local surface atomic configurations that initiate kinetic transitions. The presence of La shifts the bistable reaction states, changes the oscillation pattern and deactivates one of two pacemaker types for the La-free surface. The observed effects originate from the La-enhanced oxygen activation on the catalyst. The experimental observations are corroborated by micro-kinetic model simulations comprising a system of 25 coupled oscillators.

Acoustic evaluation of a vehicle cabin by using energy-based surface contributions

Contribution analyses play a crucial role in the design process of vehicle cabins. In current implementations, however, surface contributions are only evaluated for single field points. The identification of surface contributions with regard to an entire cavity is accompanied with a cumbersome volume integral. This study aims to abridge this tedious volume integral by evaluating the surface contributions regarding a grid with regularly distributed field points. For this purpose, the boundary element method is used to solve the acoustic Helmholtz equation. In contrast to current techniques, the sound energy is deployed as the objective function. As the sound energy is sensitive to the sound pressure and the particle velocity, surface contributions can be also identified in regions with low sound pressure values. In order to validate the proposed framework, the vehicle interior noise problem is examined. Initial findings confirm the relevance of energy-based surface contributions, as entire volumes can be acoustically evaluated in an efficient way.

Widespread and largely unknown prophage activity, diversity, and function in two genera of wheat phyllosphere bacteria

Environmental bacteria host an enormous number of prophages, but their diversity and natural functions remain largely elusive. Here, we investigate prophage activity and diversity in 63 Erwinia and Pseudomonas strains isolated from flag leaves of wheat grown in a single field. Introducing and validating Virion Induction Profiling Sequencing (VIP-Seq), we identify and quantify the activity of 120 spontaneously induced prophages, discovering that some phyllosphere bacteria produce more than 108 virions/mL in overnight cultures, with significant induction also observed in planta. Sequence analyses and plaque assays reveal E. aphidicola prophages contribute a majority of intraspecies genetic diversity and divide their bacterial hosts into antagonistic factions engaged in widespread microbial warfare, revealing the importance of prophage-mediated microdiversity. When comparing spontaneously active prophages with predicted prophages we also find insertion sequences are strongly correlated with non-active prophages. In conclusion, we discover widespread and largely unknown prophage diversity and function in phyllosphere bacteria.

Comparative transcriptome analysis reveals candidate genes for cold stress response and early flowering in pineapple

Pineapple originates from tropical regions in South America and is therefore significantly impacted by cold stress. Periodic cold events in the equatorial regions where pineapple is grown may induce early flowering, also known as precocious flowering, resulting in monetary losses due to small fruit size and the need to make multiple passes for harvesting a single field. Currently, pineapple is one of the most important tropical fruits in the world in terms of consumption, and production losses caused by weather can have major impacts on worldwide exportation potential and economics. To further our understanding of and identify mechanisms for low-temperature tolerance in pineapple, and to identify the relationship between low-temperature stress and flowering time, we report here a transcriptomic analysis of two pineapple genotypes in response to low-temperature stress. Using meristem tissue collected from precocious flowering-susceptible MD2 and precocious flowering-tolerant Dole-17, we performed pairwise comparisons and weighted gene co-expression network analysis (WGCNA) to identify cold stress, genotype, and floral organ development-specific modules. Dole-17 had a greater increase in expression of genes that confer cold tolerance. The results suggested that low temperature stress in Dole-17 plants induces transcriptional changes to adapt and maintain homeostasis. Comparative transcriptomic analysis revealed differences in cuticular wax biosynthesis, carbohydrate accumulation, and vernalization-related gene expression between genotypes. Cold stress induced changes in ethylene and abscisic acid-mediated pathways differentially between genotypes, suggesting that MD2 may be more susceptible to hormone-mediated early flowering. The differentially expressed genes and module hub genes identified in this study are potential candidates for engineering cold tolerance in pineapple to develop new varieties capable of maintaining normal reproduction cycles under cold stress. In addition, a total of 461 core genes involved in the development of reproductive tissues in pineapple were also identified in this study. This research provides an important genomic resource for understanding molecular networks underlying cold stress response and how cold stress affects flowering time in pineapple.

Modeling the hot deformation behavior of micro-alloyed steel in the single and two-phase fields

Continuous casting is a well-established process to produce steel slabs. However, the surfaces of the slabs may crack during processing. The occurrence of cracks is related to different phenomena, i.e., ferrite formation, presence of precipitates, and microstructural modifications during manufacturing processing. In the present work, we developed a physically based mesoscale model to describe the plastic deformation of micro-alloyed steel in the single and two-phase fields, as well as the microstructure evolution. We implemented a dislocation density-based constitutive model to calculate the strain hardening and the stress softening produced by dynamic recovery using the Kocks-Mecking (KM) formalism for the austenite and ferrite. We coupled the KM model with the Johnson-Mehl-Avrami-Kolmogorov model to consider the dynamic recrystallization of the austenitic phase. The nucleation and growth of the recrystallized grains, driven by the stored energy, compete with the annihilation of dislocations due to dynamic recovery. In the two-phase domain, the iso-work condition for the load partition is implemented. We calculated the ferrite volume fraction by fitting the data obtained using JmatPro software. Moreover, an Arrhenius-type equation correlates the yield stress to the Zener-Hollomon parameter. We validated the model with isothermal uniaxial compression tests of microalloyed steel over the temperature range of 650 °C-1100 °C and strain rates of 10−2 s−1 and 10−3 s−1 using a Gleeble® 3800 thermomechanical simulator.

Reionisation time field reconstruction from 21 cm signal maps

Context. During the epoch of reionisation, the intergalactic medium is reionised by the UV radiation from the first generation of stars and galaxies. One tracer of the process is the 21 cm line of hydrogen that will be observed by the Square Kilometre Array (SKA) at low frequencies, thus imaging the distribution of ionised and neutral regions and their evolution. Aims. To prepare for these upcoming observations, we investigate a deep learning method to predict from 21 cm maps the reionisation time field (treion(r)), the time at which each location has been reionised. The treion(r) method encodes the propagation of ionisation fronts in a single field, and gives access to times of local reionisation or to the extent of the radiative reach of early sources. Moreover it gives access to the time evolution of ionisation on the plane of sky, when this evolution is usually probed along the line-of-sight direction. Methods. We trained a convolutional neural network (CNN) using simulated 21 cm maps and reionisation time fields produced by the simulation code 21cmFAST. We also investigated the performance of the CNN when adding instrumental effects. Results. Overall, we find that without instrumental effects the 21 cm maps can be used to reconstruct the associated reionisation times field in a satisfying manner. The quality of the reconstruction is dependent on the redshift at which the 21 cm observation is being made, and in general it is found that small-scale features (< 10 cMpc h−1) are smoothed in the reconstructed field, while larger-scale features are recovered well. When instrumental effects are included, the scale dependence of reconstruction is even further pronounced, with significant smoothing on small and intermediate scales. Conclusions. The reionisation time field can be reconstructed, at least partially, from 21 cm maps of IGM during the epoch of reionisation. This quantity can thus be derived in principle from observations, and should then provide a means to investigate the effect of local histories of reionisation on the first structures that appear in a given region.

Orbital precession and hidden symmetries in scalar-tensor theories

We revisit the connection between relativistic orbital precession, the Laplace-Runge-Lenz symmetry, and the t-channel discontinuity of scattering amplitudes. Applying this to scalar-tensor theories of gravity, we compute the conservative potential and orbital precession induced by both conformal/disformal-type couplings at second Post-Minkowskian order (𝒪(GN 2)), complementing the known third/first order Post-Newtonian results. There is a particular tuning of the conformal coupling for which the precession vanishes at leading PN order, and we show that this coincides with the emergence of a Laplace-Runge-Lenz symmetry and a corresponding soft behaviour of the amplitude. While a single scalar field inevitably breaks this symmetry at higher PN orders, certain supersymmetric extensions have recently been shown to have an exact Laplace-Runge-Lenz symmetry and therefore classical orbits do not precess at any PN order. This symmetry can be used to relate scattering amplitudes at different loop orders, and we show how this may be used to bootstrap the (classically relevant part of the) three-loop 2 → 2 scattering of charged black holes in 𝒩 = 8 supergravity from existing two-loop calculations.

Stochastic dynamics of multi-waterfall hybrid inflation and formation of primordial black holes

We show that a hybrid inflation model with multiple waterfall fields can result in the formation of primordial black holes (PBHs) with an astrophysical size, by using an advanced algorithm to follow the stochastic dynamics of the waterfall fields. This is in contrast to the case with a single waterfall field, where the wavelength of density perturbations is usually too short to form PBHs of the astrophysical scale (or otherwise PBHs are overproduced and the model is ruled out) unless the inflaton potential is tuned. In particular, we demonstrate that PBHs with masses of order 1020 g can form after hybrid inflation consistently with other cosmological observations if the number of waterfall fields is about 5 for the case of instantaneous reheating. Observable gravitational waves are produced from the second-order effect of large curvature perturbations as well as from the dynamics of texture or global defects that form after the waterfall phase transition.

Quintessential α-attractor inflation:a dynamical systems analysis

The equations for quintessential α-attractor inflationwith a single scalar field, radiation and matter in a spatially flatFLRW spacetime are recast into a regular dynamical system on acompact state space. This enables a complete description of thesolution space of these models. The inflationary attractor solutionis shown to correspond to the unstable center manifold of a deSitter fixed point, and we describe connections between slow-rolland dynamical systems approximations for this solution, includingPadé approximants. We also introduce a new method forsystematically obtaining initial data for quintessence evolution byusing dynamical systems properties; in particular, this method exploitsthat there exists a radiation dominated line of fixed points withan unstable quintessence attractor submanifold, which plays a rolethat is reminiscent of that of the inflationary attractor solutionfor inflation.

A hybrid framework for efficient and accurate orientation estimation based on single and multiple orientation vector fields

This article presents a hybrid framework for efficient and accurate orientation estimation. The proposed scheme combines the single orientation information given by a novel method and the multiple orientation information provided by a bank of linear orientated morphological openings. The single orientations are estimated by means of an energy-minimization Gaussian filtering which solves the drawback related to phase changes of other methods. After describing the formulation of these two approaches for estimating the existing orientations in the pixels of an image, several strategies have been analyzed to fuse and discriminate the information of both orientation vector fields in the resulting hybrid orientation vector field. The objective of the proposed hybrid method is to reduce the computational cost involved in calculating multiple orientations only in those pixels where they exist while maintaining the accuracy provided by the single orientation method in the remaining pixels. To this end, strategies ranging from a threshold in the multiple orientation vector field to a convolutional neural network trained with a set of patterns specifically designed to detect pixels with multiple orientations, passing through the Harris corner detector, have been tested to identify those pixels where multiple orientations exist. Results on natural and synthetic images show the accuracy and the computational efficiency achieved by the proposed hybrid framework to provide the vector field with single and multiple orientations.

Quantum loop effects on the power spectrum and constraints on primordial black holes

We present a detailed exposition on the prospects of the formation of Primordial Black Holes (PBHs) during Slow Roll (SR) to Ultra Slow Roll (USR) sharp transitions in the framework of single-field inflation. We use an effective field theory (EFT) approach in order to keep the analysis model-independent and applicable to both the canonical and non-canonical cases. We show in detail how renormalizing the power spectrum to one loop order in P(X,ϕ) theories severely limits the prospects for PBH formation in a single-field inflationary framework. We demonstrate that for the allowed range of effective sound speed, 1 < cs < 1.17, the consistency of one-loop corrected power spectrum leaves a small window for black hole masses, M PBH∼𝒪(102–103)gm to have sufficient e-foldings, Δ𝒩Total ∼ 𝒪(54–59) for inflation. We confirm that adding an SR regime after USR before the end of inflation does not significantly alter our conclusions. Our findings for sharp transition strictly rule out the possibility of generating large masses of PBHs from all possible models of single field inflation (canonical and non-canonical).Our results are at least valid for the situation where constraints from the loop effects are computed using either Late-Time (LT) or Adiabatic-Wave function(AF) scheme followed by Power Spectrum (PS) renormalization schemes.

Characterizing finitely generated fields by a single field axiom

Characterizing finitely generated fields by a single field axiom

A Universal Digital Lock-in Amplifier Design for Calibrating the Photo-Detector Responses with Standard Black-Bodies.

The lock-in amplifier (LIA) is widely utilized to detect ultra-weak optical periodic signals based on the phase-sensitive and enhanced detecting theory. In this paper, we present an all-digital and universal embedded LIA platform that accurately and conveniently describes the spectrum generated by standard black bodies at various temperatures with different optical detectors. The proposed design significantly reduces the complexity and cost of traditional analog LIAs while maintaining accuracy. The LIA components are implemented using a single field programmable gate array (FPGA), offering flexibility to modify parameters for different situations. The normalized mean-square error (NMSE) of the captured spectra in the experiments is within 0.9% compared the theoretical values.

A lateral-immobilization zebrafish microfluidic chip-based system for in vivo real-time evaluation of antithrombotic agents

Thrombosis remains a major global health concern mainly characterized by high rates of morbidity and mortality. Animal models serve as an indispensable tool to understand the underlying pathogenesis of thrombosis and assess the efficacy of novel antithrombotic drugs. Currently, zebrafish has emerged as a valuable model organism for thrombosis research. However, the traditional method of studying zebrafish thrombosis requires a laborious and time-consuming procedure, including anesthesia and manual immobilization of zebrafish. In this study, based on hydrodynamic force, a lateral-immobilization zebrafish microfluidic chip (LIZMC) was designed to evaluate the cardiovascular system of multiple larvae within a single microscope field of view. Specifically, coupling with microscope imaging, real-time monitoring of the peripheral blood circulation in the tail of phenylhydrazine (PHZ)-induced zebrafish thrombosis was enabled. Furthermore, the reliability of LIZMC for in vivo evaluation of antithrombotic agents in zebrafish was verified using aspirin. Collectively, this novel LIZMC-based system can be used for in vivo zebrafish thrombosis studies and rapid screening of antithrombotic agents.

Transferable Force Field for Gallium Nitride Crystal Growth from the Melt Using On-The-Fly Active Learning.

Atomic-scale simulations of reactive processes have been stymied by two factors: the lack of a suitable semiempirical force field on one hand and the impractically large computational burden of using ab initio molecular dynamics on the other hand. In this paper, we use an "on-the-fly" active learning technique to develop a nonparameterized force field that, in essence, exhibits the accuracy of density functional theory and the speed of a classical molecular dynamics simulation. We developed a force field capable of capturing the crystallization of gallium nitride (GaN) during a novel additive manufacturing process featuring the reaction of liquid Ga and gaseous nitrogen precursors to grow crystalline GaN thin films. We show that this machine learning model is capable of producing a single force field that can model solid, liquid, and gas phases involved in the process. We verified our computational predictions against a range of experimental measurements relevant to each phase and against ab initio calculations, showing that this nonparametric force field produces properties with excellent accuracy as well as exhibits computationally tractable efficiency. The force field is capable of allowing us to simulate the solid-liquid coexistence interface and the crystallization of GaN from the melt. The development of this transferable force field opens the opportunity to simulate the liquid-phase epitaxial growth more accurately than before to analyze reaction and diffusion processes and ultimately to establish a growth model of the additive manufacturing process to create the gallium nitride thin films.

Evaluation of the Effectiveness of Paris Agreement - An Angle from the Determining of Normative Framework

The previous studies on Paris Agreement almost only analyzed the single field related to it, such as international cooperation and low-carbon economy. Therefore, this study will make an overall consideration of the Paris Agreement. In the sixth year after the implementation of the Paris Agreement, this study evaluates the effectiveness of the Paris Agreement under the circumstance that various scholars and academic circles attach great importance to climate change. In accordance with the chronological and systematic archival research methods, this study clearly sorted out information related to climate change and global governance in the context of the signing of the Paris Agreement by citing empirical literature and analytical theoretical knowledge. This study analyzed the scholars views on climate change, for example, in international cooperation in the field of climate change is compare difficult, the Paris agreement itself, namely, the main goal of target, NDC and some related regulations, the implementation of the Paris agreement triple dilemma, such as the global inventory for further analysis, assess the effectiveness of the Paris Agreement. According to the above analysis, the Paris agreement can only be said to be relatively effective. At the end of the paper, the author also evaluates this research.

Formula omitted]- inflation: Sourced by energy–momentum squared gravity

In this paper, we examine chaotic inflation within the context of the energy–momentum squared gravity (EMSG) focusing on the energy–momentum powered gravity (EMPG) that incorporates the functional f(T2)∝(T2)β in the Einstein–Hilbert action, in which β is a constant and T2≡TμνTμν where Tμν is the energy–momentum tensor, which we consider to represent a single scalar field with a power-law potential. We also demonstrate that the presence of EMSG terms allows the single-field monomial chaotic inflationary models to fall within current observational constraints, which are otherwise disfavored by Planck and BICEP/Keck findings. We show that the use of a non-canonical Lagrangian with chaotic potential in EMSG can lead to significantly larger values of the non-Gaussianity parameter, fNlequi whereas EMSG framework with canonical Lagrangian gives rise to results similar to those of the standard single-field model.

Frontal cortex activity during the production of diverse social communication calls in marmoset monkeys

Vocal communication is essential for social behaviors in humans and non-human primates. While the frontal cortex is crucial to human speech production, its role in vocal production in non-human primates has long been questioned. It is unclear whether activities in the frontal cortex represent diverse vocal signals used in non-human primate communication. Here we studied single neuron activities and local field potentials (LFP) in the frontal cortex of male marmoset monkeys while the animal engaged in vocal exchanges with conspecifics in a social environment. We found that both single neuron activities and LFP were modulated by the production of each of the four major call types. Moreover, neural activities showed distinct patterns for different call types and theta-band LFP oscillations showed phase-locking to the phrases of twitter calls, suggesting a neural representation of vocalization features. Our results suggest important functions of the marmoset frontal cortex in supporting the production of diverse vocalizations in communication.

Type 1 diabetes in the pancreas: A histological perspective.

This review aims to introduce research in the pancreas to a broader audience. The pancreas is a heterocrine gland residing deep within our abdominal cavity. It is the home to our islets, which play a pivotal role in regulating metabolic homeostasis. Due to its structure and location, it is an impossible organ to study, in molecular detail, in living humans, and yet, understanding the pancreas is critical if we aim to characterise the immunopathology of type 1 diabetes (T1D) and one day prevent the triggering of the autoimmune attack associated with ß-cell demise. Over a 100 years ago, we began studying pancreatic histology using cadaveric samples and clever adaptations to microscopes. As histologists, some may say nothing much has changed. Nevertheless, our microscopes can now interrogate multiple proteins at molecular resolution. Images of pancreas sections are no longer constrained to a single field of view and can capture a thousands and thousands of cells. AI-image-analysis packages can analyse these massive data sets offering breakthrough findings. This narrative review will provide an overview of pancreatic anatomy, and the importance of research focused on the pancreas in T1D. It will range from histological breakthroughs to briefly discussing the challenges associated with characterising the organ. I shall briefly introduce a selection of the available global biobanks and touch on the distinct pancreatic endotypes that differ immunologically and in ß-cell behaviour. Finally, I will introduce the idea of developing a collaborative tool aimed at developing a cohesive framework for characterising heterogeneity and stratifying endotypes in T1D more readily.

Jeffreys Divergence and Generalized Fisher Information Measures on Fokker-Planck Space-Time Random Field.

In this paper, we present the derivation of Jeffreys divergence, generalized Fisher divergence, and the corresponding De Bruijn identities for space-time random field. First, we establish the connection between Jeffreys divergence and generalized Fisher information of a single space-time random field with respect to time and space variables. Furthermore, we obtain the Jeffreys divergence between two space-time random fields obtained by different parameters under the same Fokker-Planck equations. Then, the identities between the partial derivatives of the Jeffreys divergence with respect to space-time variables and the generalized Fisher divergence are found, also known as the De Bruijn identities. Later, at the end of the paper, we present three examples of the Fokker-Planck equations on space-time random fields, identify their density functions, and derive the Jeffreys divergence, generalized Fisher information, generalized Fisher divergence, and their corresponding De Bruijn identities.