搜索结果：Plant-environment interactions (Hoboken, N.J.)

The theory talks at Moriond QCD and High-Energy Interactions 2025 covered the full range of scales from BSM, top, Higgs, EW, and hard QCD physics, through resummation, factorisation, and PDFs, to hadronic, heavy-ion, nonperturbative, and lattice QCD. A few talks also touched on methodologies. We here summarise main points of most of these contributions.

High-throughput pheno-, geno-, and envirotyping allows characterization of plant genotypes and the trials they are evaluated in, producing different types of data. These different data modalities can be integrated into statistical or machine learning models for genomic prediction in several ways. One commonly used approach within the analysis of multi-environment trial data in plant breeding is to create linear or nonlinear kernels which are subsequently used in linear mixed models (LMMs) to model genotype by environment (G$\times$E) interactions. Current implementations of these kernel-based LMMs present a number of opportunities in terms of methodological extensions. Here we show how these models can be implemented in standard software, allowing direct restricted maximum likelihood (REML) estimation of all parameters. We also further extend the models by combining the kernels with unstructured covariance matrices for three-way interactions in genotype by environment by management (G$\times$E$\times$M) datasets, while simultaneously allowing for environment-specific genetic variances. We show how the models incorporating nonlinear kernels and heterogeneous variances maximize the a

This article explores human-horse interactions as a metaphor for understanding and designing effective human-AI partnerships. Drawing on the long history of human collaboration with horses, we propose that AI, like horses, should complement rather than replace human capabilities. We move beyond traditional benchmarks such as the Turing test, which emphasize AI's ability to mimic human intelligence, and instead advocate for a symbiotic relationship where distinct intelligences enhance each other. We analyze key elements of human-horse relationships: trust, communication, and mutual adaptability, to highlight essential principles for human-AI collaboration. Trust is critical in both partnerships, built through predictability and shared understanding, while communication and feedback loops foster mutual adaptability. We further discuss the importance of taming and habituation in shaping these interactions, likening it to how humans train AI to perform reliably and ethically in real-world settings. The article also addresses the asymmetry of responsibility, where humans ultimately bear the greater burden of oversight and ethical judgment. Finally, we emphasize that long-term commitment

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because t

Magnetic interactions between a planet and its environment are known to lead to aurorae and shocks in the solar system. The large number of close-in exoplanets that have been discovered so far triggered a renewed interest in understanding magnetic interactions in other star-planet systems. Multiple magnetic effects were then unveiled, such as planet inflation or heating, planet migration, planetary material escape, and even some modifications of the host star apparent activity. Our goal here is to lay out the basic physical principles underlying star-planet magnetic interactions. We first briefly review the hot exoplanets' population as we know it. We then move to a general description of star-planet magnetic interactions, and finally focus on the fundamental concept of Alfvén wings and its implication for exosystems.

Plant breeding underpins global food security through incremental, accumulating improvements in crop yield, quality and sustainability, achieved via repeated cycles of crop ranking, selection and crossing. Climate change disrupts this process by altering local growing conditions, thereby shifting the relative performance of crop genotypes. Predicting these relative changes in yield is critical for food security. Yet, this problem remains an open challenge in plant breeding, and relatively unexplored within the AI community. We propose MixINN, an approach that first isolates high-quality genotype-environment interaction labels using mixed models, and then predicts these interactions for new crop varieties in future environmental conditions with a deep neural network. We evaluate our method on a corn multi-environment trial across the continental United States and show improved prediction of genotype ranking over current plant breeding methods. MixINN demonstrated superior performance in identifying the 20% most productive corn genotypes, leading to a 5.8% higher average yield, which further improved to 7.2% when targeting specific growing environments. These are competitive results

Two types of solute-solute interactions are investigated in this work. Quadrupole interactions caused by nearby Ag-solute atoms were measured at nuclei of 111In/Cd solute probe atoms in the binary compound GdAl2 using the method of perturbed angular correlation of gamma rays (PAC). Locations of In-probes and Ag-solutes on both Gd- and Al-sublattices were identified by comparing site fractions in Gd-poor and Gd-rich GdAl2(Ag) samples. Interaction enthalpies between solute-atom pairs were determined from temperature dependences of observed site fractions. Repulsive interactions were observed for close-neighbor complexes In/Gd/+Ag/Gd/ and In/Gd/+Ag/Al/ pairs, whereas a slightly attractive interaction was observed for In/Al/+Ag/Al/. Interaction enthalpies were all in the range +/- 0.15 eV. Temperature dependences of site fractions of In-probes on locally defect-free Gd- and Al-sites yields a transfer enthalpy that was found to be 0.343 eV in a previous study of undoped GdAl2. The corresponding values in GdAl2(Ag) samples are much smaller. This is attributed to competition of In- and Ag-solutes to occupy sites of the same sublattice. While the difference in site-enthalpies of In-solutes

Much effort has been invested in recent years, both observationally and theoretically, to understand the interacting processes taking place in planetary systems consisting of a hot Jupiter orbiting its star within 10 stellar radii. Several independent studies have converged on the same scenario: that a short-period planet can induce activity on the photosphere and upper atmosphere of its host star. The growing body of evidence for such magnetic star-planet interactions includes a diverse array of photometric, spectroscopic and spectropolarimetric studies. The nature of which is modeled to be strongly affected by both the stellar and planetary magnetic fields, possibly influencing the magnetic activity of both bodies, as well as affecting irradiation and non-thermal and dynamical processes. Tidal interactions are responsible for the circularization of the planet orbit, for the synchronization of the planet rotation with the orbital period, and may also synchronize the outer convective envelope of the star with the planet. Studying such star-planet interactions (SPI) aids our understanding of the formation, migration and evolution of hot Jupiters.

Amorphous media at finite temperatures, be them liquids, colloids or glasses, are made of interacting particles that move chaotically due to thermal energy, colliding and scattering continuously off each other. When the average configuration in these systems relaxes only at long times, one can introduce {\em effective interactions} that keep the {\em mean positions} in mechanical equilibrium. We introduce a new framework to determine these effective force-laws that define an effective Hessian that can be employed to discuss stability properties and density of states of the amorphous system. We exemplify the approach with a thermal glass of hard spheres; these feel zero forces when not in contact and infinite forces when they touch. The present approach recaptures the effective interactions which for sufficiently dense spheres at temperature $T$ depends on the gap $h$ between spheres as $T/h$ [C. Brito and M. Wyart, Europhys. Lett. 76 149 (2006)]. In systems at lower densities or with longer microscopic interaction (say like Lennard-Jones), the emergent force laws will include ternary, quaternary and generally higher order many-body terms, even if the microscopic interactions are st

Despite the progress made in understanding the NN interactions at long distances based on effective field theories, the understanding of the dynamics of short range NN interactions remains as elusive as ever. One of the most fascinating properties of short range interaction is its repulsive nature which is responsible for the stability of strongly interacting matter. The relevant distances, $\le 0.5$ fm, in this case are such that one expects the onset of quark-gluon degrees of freedom with interaction being dominated by QCD dynamics. We review the current status of the understanding of the QCD dynamics of NN interactions at short distances, highlight outstanding questions and outline the theoretical foundation of QCD description of hard NN processes. We present examples of how the study of the hard elastic NN interaction can reveal the symmetry structure of valence quark component of the nucleon wave function and how the onset of pQCD regime is correlated with the onset of color transparency phenomena in hard $pp$ scattering in the nuclear medium. The discussions show how the new experimental facilities can help to advance the knowledge about the QCD nature of nuclear forces at sh

We develop a unified framework for understanding the sign of fermion-mediated interactions by exploiting the symmetry classification of Green's functions. In particular, we establish a theorem regarding the sign of fermion-mediated interactions in systems with chiral symmetry. The strength of the theorem is demonstrated within multiple examples with an emphasis on electron-mediated interactions in materials.

Plants respond to biotic and abiotic stresses through complex and dynamic mechanisms that integrate physical, chemical, and biological cues. Here, we present a multi-physics platform designed to systematically investigate these responses across scales. The platform combines a six-axis micromanipulator with interchangeable probes to deliver precise mechanical, electrostatic, optical, and chemical stimuli. Using this system, we explore calcium signaling in Arabidopsis thaliana, thigmonastic motion in Mimosa pudica, and chemical exchange via microinjection in Rosmarinus officinalis L. and Ocimum basilicum. Our findings highlight stimulus-specific and spatially dependent responses: mechanical and electrostatic stimuli elicit distinct calcium signaling patterns, while repeated electrostatic stimulation exhibited evidence of response fatigue. Thigmonastic responses in Mimosa pudica depend on the location of perturbation, highlighting the intricate bi-directional calcium signaling. Microinjection experiments successfully demonstrate targeted chemical perturbations in glandular trichomes, opening avenues for biochemical studies. This open-source platform provides a versatile tool for disse

We present a general analysis of the effective potential for neutrino propagation in matter, assuming a generic set of Lorentz invariant non-derivative interactions. We find that in addition to the known vector and axial vector terms, in a polarized medium also tensor interactions can play an important role. We compute the effective potential arising from a tensor interaction. We show that the components of the tensor potential transverse to the direction of the neutrino propagation can induce a neutrino spin-flip, similar to the one induced by a transverse magnetic field.

Robotic navigation in dense, cluttered environments such as agricultural canopies presents significant challenges due to physical and visual occlusion caused by leaves and branches. Traditional vision-based or model-dependent approaches often fail in these settings, where physical interaction without damaging foliage and branches is necessary to reach a target. We present a novel reactive controller that enables safe navigation for a robotic arm in a contact-rich, cluttered, deformable environment using end-effector position and real-time tactile feedback. Our proposed framework's interaction strategy is based on a trade-off between minimizing disturbance by maneuvering around obstacles and pushing through them to move towards the target. We show that over 35 trials in 3 experimental plant setups with an occluded target, the proposed controller successfully reached the target in all trials without breaking any branch and outperformed the state-of-the-art model-free controller in robustness and adaptability. This work lays the foundation for safe, adaptive interaction in cluttered, contact-rich deformable environments, enabling future agricultural tasks such as pruning and harvestin

The study of critical properties of systems with long-range interactions has attracted in the last decades a continuing interest and motivated the development of several analytical and numerical techniques, in particular in connection with spin models. From the point of view of the investigation of their criticality, a special role is played by systems in which the interactions are long-range enough that their universality class is different from the short-range case and, nevertheless, they maintain the extensivity of thermodynamical quantities. Such interactions are often called weak long-range. In this paper we focus on the study of the critical behaviour of spin systems with weak-long range couplings using renormalization group, and we review their remarkable properties. For the sake of clarity and self-consistency, we start from the classical $O(N)$ spin models and we then move to quantum spin systems.

Theories beyond the Standard Model must respect its gauge symmetry. This implies strict constraints on the possible models of Non-Standard Neutrino Interactions (NSIs). We review here the present status of NSIs from the point of view of effective field theory. Our recent work on the restrictions implied by Standard Model gauge invariance is provided along with some examples of possible gauge invariant models featuring non-standard interactions.

We show that the "ridge" phenomenon in the two-particle angular correlation function, as observed by the CMS experiment, can be reproduced by implementing an impact parameter dependent azimuthal correlation of the scattering planes of individual partonic interactions. Such an approach is motivated by the observation that even for moderate impact parameters a substantial number of partonic interactions may be produced, while at the same time the protons are sufficiently far apart to create a preferential direction in azimuth. A re-tune of the Pythia6 Z2 tune based on underlying event and minimum bias distributions measured at the LHC shows that a better description of data can be obtained with this approach and that some tension existing between underlying event and minimum bias distributions can be removed. We show that, even though the CMS result on the angular correlation function itself is not used in the re-tune, we can predict the appearance of long-range, near-side angular correlations in proton-proton collisions.

Personality computing has become an emerging topic in computer vision, due to the wide range of applications it can be used for. However, most works on the topic have focused on analyzing the individual, even when applied to interaction scenarios, and for short periods of time. To address these limitations, we present the Dyadformer, a novel multi-modal multi-subject Transformer architecture to model individual and interpersonal features in dyadic interactions using variable time windows, thus allowing the capture of long-term interdependencies. Our proposed cross-subject layer allows the network to explicitly model interactions among subjects through attentional operations. This proof-of-concept approach shows how multi-modality and joint modeling of both interactants for longer periods of time helps to predict individual attributes. With Dyadformer, we improve state-of-the-art self-reported personality inference results on individual subjects on the UDIVA v0.5 dataset.

Consistent interactions with electromagnetism and gravity for mass $m$ particles of any spin are obtained. This is done by finding interactions which preserve the covariantized massive gauge symmetry present in recently constructed massive particle actions. This gauge principle is sufficient for finding consistent completions of minimal as well as non-minimal couplings of any type. For spins $s\geq 3/2$, consistency requires infinitely many interaction terms in the action, including arbitrarily high order derivatives of electromagnetic and gravitational curvatures, with correspondingly high powers of $1/m$. These interactions may be formally resummed and expressed in terms of non-local operators. Finally, although the interactions appear non-local, evidence is presented for the existence of a field redefinition which makes the interacting action local. This work provides the first explicit realization of an exactly gauge invariant formulation of massive particles interacting with electromagnetism and gravity.