Impact of the foliar application of magnesium nanofertilizer on physiological and biochemical parameters and yield in green beans

One of the most significant challenges humanity will face is food production. In order to preserve the output, mineral fertilizers are essential. However, it's not a suitable option in the long term. Magnesium is a crucial macronutrient, but it is the most limiting element in agriculture. Nanotechnology, with the implementation of nanofertilizers, is an excellent alternative since it provides nutrients, supports growth, and improves production; this in low amounts is more sustainable than conventional fertilizers. Although there is a piece of limited information regarding the proper foliar application of this macronutrient, the study helped to validate the effect of the foliar application of Magnesium nano fertilizer on the physiological, biochemical responses and yield of bean plants. Bean plants ejotero cv. ‘Strike’ and magnesium nanoparticles were applied at doses of 0, 50, 100, and 200 ppm. The biomass accumulation, yield, activity of the enzyme nitrate reductase, and photosynthetic pigments were evaluated. The foliar application of Mg nanoparticles at 50 ppm generated the highest amount of biomass and photosynthetic pigments. The 100 ppm dose improved pods yield and allowed the increased activity of the Nitrate Reductase enzyme. The results obtained suggest that, when increasing the dose of magnesium in plants, the amount of carotenes decreases

Inferring the dark matter splashback radius from cluster gas and observable profiles in the FLAMINGO simulations.

The splashback radius, coinciding with the minimum in the dark matter radial density gradient, is thought to be a universal definition of the edge of a dark matter halo. Observational methods to detect it have traced the dark matter using weak gravitational lensing or galaxy number counts. Recent attempts have also claimed the detection of a similar feature in Sunyaev-Zel'dovich (SZ) observations of the hot intracluster gas. Here, we use the FLAMINGO simulations to investigate whether an extremum gradient in a similar position to the splashback radius is predicted to occur in the cluster gas profiles. We find that the minimum in the gradient of the stacked 3D gas density and pressure profiles, and the maximum in the gradient of the entropy profile, broadly align with the splashback feature though there are significant differences. While the dark matter splashback radius varies with specific mass accretion rate, in agreement with previous work, the radial position of the deepest minimum in the log-slope of the gas density is more sensitive to halo mass. In addition, we show that a similar minimum is also present in projected 2D pseudo-observable profiles: emission measure (X-ray); Compton-$y$ (SZ) and surface mass density (weak lensing). We find that the latter traces the dark matter results reasonably well albeit the minimum occurs at a slightly smaller radius. While results for the gas profiles are largely insensitive to accretion rate and various observable proxies for dynamical state, they do depend on the strength of the feedback processes

Inferring the dark matter splashback radius from cluster gas and observable profiles in the FLAMINGO simulations

The splashback radius, coinciding with the minimum in the dark matter radial density gradient, is thought to be a universal definition of the edge of a dark matter halo. Observational methods to detect it have traced the dark matter using weak gravitational lensing or galaxy number counts. Recent attempts have also claimed the detection of a similar feature in Sunyaev–Zel’dovich (SZ) observations of the hot intracluster gas. Here, we use the FLAMINGO simulations to investigate whether an extremum gradient in a similar position to the splashback radius is predicted to occur in the cluster gas profiles. We find that the minimum in the gradient of the stacked 3D gas density and pressure profiles, and the maximum in the gradient of the entropy profile, broadly align with the splashback feature though there are significant differences. While the dark matter splashback radius varies with specific mass accretion rate, in agreement with previous work, the radial position of the deepest minimum in the log-slope of the gas density is more sensitive to halo mass. In addition, we show that a similar minimum is also present in projected 2D pseudo-observable profiles: emission measure (X-ray), Compton-y (SZ), and surface mass density (weak lensing). We find that the latter traces the dark matter results reasonably well albeit the minimum occurs at a slightly smaller radius. While results for the gas profiles are largely insensitive to accretion rate and various observable proxies for dynamical state, they do depend on the strength of the feedback processes

Non-linear CMB lensing with neutrinos and baryons: FLAMINGO simulations versus fast approximations

Weak lensing of the cosmic microwave background is rapidly emerging as a powerful probe of neutrinos, dark energy, and newphysics. We present a fast computation of the non-linear CMB lensing power spectrum that combines non-linear perturbationtheory at early times with powerspectrum emulation using cosmologicalsimulations at late times.Comparing our calculation withlight-cones from the FLAMINGO 5.6 Gpc cube dark-matter-only simulation, we confirm its accuracy to 1 per cent (2 per cent)up to multipoles L = 3000 (L = 5000) for a νCDM cosmology consistent with current data. Clustering suppression due tosmall-scale baryonic phenomena such as feedback from active galactic nuclei can reduce the lensing power by ∼ 10 per cent.To our perturbation theory and emulator-based calculation, we add SP(k), a new fitting function for this suppression, andconfirm its accuracy compared to the FLAMINGO hydrodynamic simulations to 4 per cent at L = 5000, with similar accuracy formassive neutrino models. We further demonstrate that scale-dependent suppression due to neutrinos and baryons approximatelyfactorize, implying that a careful treatment of baryonic feedback can limit biasing neutrino mass constraints

The FLAMINGO project: revisiting the S8S_8 tension and the role of baryonic physics

A number of recent studies have found evidence for a tension between observations of large-scale structure (LSS) and the predictions of the standard model of cosmology with the cosmological parameters fit to the cosmic microwave background (CMB). The origin of this '$S_8$ tension' remains unclear, but possibilities include new physics beyond the standard model, unaccounted for systematic errors in the observational measurements and/or uncertainties in the role that baryons play. Here we carefully examine the latter possibility using the new FLAMINGO suite of large-volume cosmological hydrodynamical simulations. We project the simulations onto observable harmonic space and compare with observational measurements of the power and cross-power spectra of cosmic shear, CMB lensing, and the thermal Sunyaev-Zel'dovich (tSZ) effect. We explore the dependence of the predictions on box size and resolution, cosmological parameters including the neutrino mass, and the efficiency and nature of baryonic 'feedback'. Despite the wide range of astrophysical behaviours simulated, we find that baryonic effects are not sufficiently large to remove the $S_8$ tension. Consistent with recent studies, we find the CMB lensing power spectrum is in excellent agreement with the standard model, whilst the cosmic shear power spectrum, tSZ effect power spectrum, and the cross-spectra between shear, CMB lensing, and the tSZ effect are all in varying degrees of tension with the CMB-specified standard model. These results suggest that some mechanism is required to slow the growth of fluctuations at late times and/or on non-linear scales, but that it is unlikely that baryon physics is driving this modification.Comment: 26 pages, 12 figures, MNRAS, accepted with minor revision

Directly Coupled Tiles as Elements of a Scintillator Calorimeter with MPPC Readout

Abstract We present results on the direct i.e. fiberless coupling of scintillator tiles to Multipixel Photon Counters (MPPC). The fiberless option has the potential of simplifying the assembly and construction of a finely-segmented scintillator-based calorimeter with MPPC readout. In this paper we show detailed studies on the response and uniformity of directly coupled tiles and describe our concept for an Integrated Readout Layer (IRL)

Pion and proton showers in the CALICE scintillator-steel analogue hadron calorimeter

Showers produced by positive hadrons in the highly granular CALICE scintillator-steel analogue hadron calorimeter were studied. The experimental data were collected at CERN and FNAL for single particles with initial momenta from 10 to 80 GeV/c. The calorimeter response and resolution and spatial characteristics of shower development for proton- and pion-induced showers for test beam data and simulations using Geant4 version 9.6 are compared.Comment: 26 pages, 16 figures, JINST style, changes in the author list, typos corrected, new section added, figures regrouped. Accepted for publication in JINS

The FLAMINGO project: cosmological hydrodynamical simulations for large-scale structure and galaxy cluster surveys

We introduce the Virgo Consortium's FLAMINGO suite of hydrodynamical simulations for cosmology and galaxy cluster physics. To ensure the simulations are sufficiently realistic for studies of large-scale structure, the subgrid prescriptions for stellar and AGN feedback are calibrated to the observed low-redshift galaxy stellar mass function and cluster gas fractions. The calibration is performed using machine learning, separately for three resolutions. This approach enables specification of the model by the observables to which they are calibrated. The calibration accounts for a number of potential observational biases and for random errors in the observed stellar masses. The two most demanding simulations have box sizes of 1.0 and 2.8 Gpc and baryonic particle masses of $1\times10^8$ and $1\times10^9 \text{M}_\odot$, respectively. For the latter resolution the suite includes 12 model variations in a 1 Gpc box. There are 8 variations at fixed cosmology, including shifts in the stellar mass function and/or the cluster gas fractions to which we calibrate, and two alternative implementations of AGN feedback (thermal or jets). The remaining 4 variations use the unmodified calibration data but different cosmologies, including different neutrino masses. The 2.8 Gpc simulation follows $3\times10^{11}$ particles, making it the largest ever hydrodynamical simulation run to $z=0$. Lightcone output is produced on-the-fly for up to 8 different observers. We investigate numerical convergence, show that the simulations reproduce the calibration data, and compare with a number of galaxy, cluster, and large-scale structure observations, finding very good agreement with the data for converged predictions. Finally, by comparing hydrodynamical and `dark-matter-only' simulations, we confirm that baryonic effects can suppress the halo mass function and the matter power spectrum by up to $\approx20$ per cent.Comment: 44 pages, 23 figures. Accepted for publication in MNRAS. V3 includes changes made in published version: jet simulations were redone to fix a bug, but the differences are nearly invisible. For visualizations, see the FLAMINGO website at https://flamingo.strw.leidenuniv.nl

FLAMINGO: Calibrating large cosmological hydrodynamical simulations with machine learning

To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller-volume simulations, we model how the galaxy stellar mass function and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the stellar mass function. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters.Comment: 24 pages, 10 figures (Including the appendix). Submitted to MNRAS. For visualisations, see the FLAMINGO website at https://flamingo.strw.leidenuniv.nl

FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning.

To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO (Fullhydro Large-scale structure simulations with All-sky Mapping for the Interpretation of Next Generation Observations) cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller volume simulations, we model how the galaxy stellar mass function (SMF) and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the SMF. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters. [Abstract copyright: © 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.