Analyzing reaction time distributions can provide insights into decision-making processes in the brain. The Linear Approach to Threshold with Ergodic Rate (LATER) model is arguably the simplest model for predicting reaction time distributions and can summarize distributions with as few as two free parameters. However, the coordinates for visualizing and fitting distributions with LATER ("reciprobit" space) are irregular, making the application of this simple model inaccessible to those without a programming background. Here we describe an open-source R package, LATERmodel, that allows for easy visualization of reaction time distributions, along with fitting of these with the LATER model. Using canonical data from the literature, we show that our tool replicates key features from previous LATER analysis tools, while also providing more robust fitting procedures and a more flexible method for fitting subpopulations of very rapid, early responses. Although all features of LATERmodel can be used directly in the statistical programming language R, key features are also available through a RShiny graphical user interface to allow researchers without programming background to apply the LATER model to their reaction time data.NEW & NOTEWORTHY Analyzing reaction time distributions provides a powerful tool for investigating decision-making processes. Here we describe an open-source toolbox to allow the Linear Approach to Threshold with Ergodic Rate (LATER) model, the simplest principled model linking reaction times and decisions, to be applied to empirical reaction time data, including by clinicians and scientists without any programming experience.

Repetitive DNA sequences underpin genome architecture and evolutionary processes, yet they remain challenging to classify accurately. Terrier is a deep learning model designed to overcome these challenges by classifying repetitive DNA sequences using a publicly available, curated repeat sequence library trained under the RepeatMasker schema. Poor representation of taxa within repeat databases often limits the classification accuracy and reproducibility of current repeat annotation methods, limiting our understanding of repeat evolution and function. Terrier overcomes these challenges by leveraging deep learning for improved accuracy. Trained on Repbase, which includes over 100,000 repeat families-four times more than Dfam-Terrier maps 97.1% of Repbase sequences to RepeatMasker categories, offering the most comprehensive classification system available. When benchmarked against DeepTE, TERL, and TEclass2 in model organisms (rice, fruit flies, humans, and mice), Terrier achieved superior accuracy while classifying a broader range of sequences. Further validation in non-model amphibian, flatworm, and Northern krill genomes highlights its effectiveness in improving classification in non-model species, facilitating research on repeat-driven evolution, genomic instability, and phenotypic variation.

Linear Approach to Threshold with Ergodic Rate for Reaction Times Version 0.2.0 Description Implements the Linear Approach to Threshold with Ergodic Rate (LATER) model, which predicts distributions of reaction times and summarises them with as little as two free parameters.Allows for easy visualisation and comparison of datasets, along with fitting of datasets using the LATER model.

MetaGenePipe (MGP) is an efficient, flexible, portable, and scalable metagenomics pipeline that uses performant bioinformatics software suites and genomic databases to create an accurate taxonomic and functional characterization of the prokaryotic fraction of sequenced microbiomes. Written in the Workflow Definition Language (WDL), MGP produces output that is useful in its default form, or that can be used for further downstream analysis. MGP is a pipeline-development best practice tool which uses Singularity for containerization and includes a setup script that downloads the necessary databases for setup. The source code for MGP is freely available and is distributed under the Apache 2.0 license.

Recent advances in bioinformatics and high-throughput sequencing have enabled the large-scale recovery of genomes from metagenomes. This has the potential to bring important insights as researchers can bypass cultivation and analyze genomes sourced directly from environmental samples. There are, however, technical challenges associated with this process, most notably the complexity of computational workflows required to process metagenomic data, which include dozens of bioinformatics software tools, each with their own set of customizable parameters that affect the final output of the workflow. At the core of these workflows are the processes of assembly-combining the short-input reads into longer, contiguous fragments (contigs)-and binning, clustering these contigs into individual genome bins. The limitations of assembly and binning algorithms also pose different challenges depending on the selected strategy to execute them. Both of these processes can be done for each sample separately or by pooling together multiple samples to leverage information from a combination of samples. Here we present Metaphor, a fully automated workflow for genome-resolved metagenomics (GRM). Metaphor differs from existing GRM workflows by offering flexible approaches for the assembly and binning of the input data and by combining multiple binning algorithms with a bin refinement step to achieve high-quality genome bins. Moreover, Metaphor generates reports to evaluate the performance of the workflow. We showcase the functionality of Metaphor on different synthetic datasets and the impact of available assembly and binning strategies on the final results.

We have entered a new era where integral-field spectroscopic surveys of galaxies are sufficiently large to adequately sample large-scale structure over a cosmologically significant volume. This was the primary design goal of the SAMI Galaxy Survey. Here, in Data Release 3 (DR3), we release data for the full sample of 3068 unique galaxies observed. This includes the SAMI cluster sample of 888 unique galaxies for the first time. For each galaxy, there are two primary spectral cubes covering the blue (370-570nm) and red (630-740nm) optical wavelength ranges at spectral resolving power of R=1808 and 4304 respectively. For each primary cube, we also provide three spatially binned spectral cubes and a set of standardized aperture spectra. For each galaxy, we include complete 2D maps from parameterized fitting to the emission-line and absorption-line spectral data. These maps provide information on the gas ionization and kinematics, stellar kinematics and populations, and more. All data are available online through Australian Astronomical Optics (AAO) Data Central.

The world’s most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here we present a dataset of annual, monthly, global-, hemispheric- and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing simple climate models against the behaviour of physically complete models. In addition to its use for simple climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global-, hemispheric- and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialised ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, i.e. identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way.

We present the second major release of data from the Sydney - Australian Astronomical Observatory Multi-Object Integral Field Spectrograph (SAMI) Galaxy Survey. Data Release Two includes data for 1559 galaxies, about 50 per cent of the full survey. Galaxies included have a redshift range 0.004 11], the velocity dispersion strongly increases towards the centre, whereas below log (M-*/M-circle dot) < 10 we find no evidence for a clear increase in the central velocity dispersion. This suggests a transition mass around log (M-*/M-circle dot) similar to 10 for galaxies with or without a dispersion-dominated bulge.

We present the similar to 800 star formation rate maps for the Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey based on II alpha emission maps, corrected for dust attenuation via the Balmer decrement, that are included in the SAMI Public Data Release 1. We mask out spaxels contaminated by non-stellar emission using the [O III]/II beta, [NII]/II alpha, [S II]/II alpha, and [O I]/II alpha line ratios. Using these maps, we examine the global and resolved star-forming main sequences of SAMI galaxies as a function of morphology, environmental density, and stellar mass. Galaxies further below the star-forming main sequence are more likely to have flatter star formation profiles. Early-type galaxies split into two populations with similar stellar masses and central stellar mass surface densities. The main-sequence population has centrally concentrated star formation similar to late-type galaxies, while galaxies >3 sigma below the main sequence show significantly reduced star formation most strikingly in the nuclear regions. The split populations support a two-step quenching mechanism, wherein halo mass first cuts off the gas supply and remaining gas continues to form stars until the local stellar mass surface density can stabilize the reduced remaining fuel against further star formation. Across all morphologies, galaxies in denser environments show a decreased specific star formation rate from the outside in, supporting an environmental cause for quenching, such as ram-pressure stripping or galaxy interactions.

This work presents a study of galactic outflows driven by stellar feedback. We extract main-sequence disc galaxies with stellar mass 10(9) <= M-*/M-circle dot <= 5.7 x 10(10) at redshift z = 0 from the highest resolution cosmological simulation of the Evolution and Assembly of GaLaxies and their Environments (EAGLE) set. Synthetic gas rotation velocity and velocity dispersion (s) maps are created and compared to observations of disc galaxies obtained with the Sydney-AAO (Australian Astronomical Observatory) Multi-object Integral field spectrograph (SAMI), where sigma-values greater than 150 km s(-1) are most naturally explained by bipolar outflows powered by starburst activity. We find that the extension of the simulated edge-on (pixelated) velocity dispersion probability distribution depends on stellar mass and star formation rate surface density (Sigma(SFR)), with low-M*/low-Sigma(SFR) galaxies showing a narrow peak at low sigma (similar to 30 km s(-1)) and more active, high-M-*/high-Sigma(SFR) galaxies reaching sigma > 150 km s(-1). Although supernova-driven galactic winds in the EAGLE simulations may not entrain enough gas with T < 10(5) K compared to observed galaxies, we find that gas temperature is a good proxy for the presence of outflows. There is a direct correlation between the thermal state of the gas and its state of motion as described by the sigma-distribution. The following equivalence relations hold in EAGLE: (i) low-sigma peak double left right arrow disc of the galaxy double left right arrow gas with T < 10(5) K; (ii) high-sigma tail double left right arrow galactic winds double left right arrow gas with T >= 10(5) K.

We present a theoretical model to predict the properties of an observed $z =$ 5.72 Lyman $\alpha$ emitter galaxy - CIV absorption pair separated by 1384 comoving kpc/h. We use the separation of the pair and an outflow velocity/time travelling argument to demonstrate that the observed galaxy cannot be the source of metals for the CIV absorber. We find a plausible explanation for the metal enrichment in the context of our simulations: a dwarf galaxy with $M_{\star} =$ 1.87 $\times$ 10$^{9} M_{\odot}$ located 119 comoving kpc/h away with a wind velocity of $\sim$ 100 km/s launched at $z \sim$ 7. Such a dwarf ($M_{\text{UV}} =$ - 20.5) is fainter than the detection limit of the observed example. In a general analysis of galaxy - CIV absorbers, we find galaxies with -20.5 $< M_{\text{UV}} <$ - 18.8 are responsible for the observed metal signatures. In addition, we find no correlation between the mass of the closest galaxy to the absorber and the distance between them, but a weak anti-correlation between the strength of the absorption and the separation of galaxy - absorber pairs.

We present a theoretical study of intergalactic metal absorption lines imprinted in the spectra of distant quasars during and after the Epoch of Reionization (EoR). We use high-resolution hydrodynamical simulations at high redshift (4 < z < 8), assuming a uniform UV background Haardt-Madau 12, post-processing with CLOUDY photoionization models and Voigt profile fitting to accurately calculate column densities of the ions C II, C IV, Si II, Si IV and OI in the intergalactic medium (IGM). In addition, we generate mock observations of neutral hydrogen (H I) at z < 6. Our simulations successfully reproduce the evolution of the cosmological mass density (Omega) of CII and C IV, with Omega(CII) exceeding Omega(CIV) at z > 6, consistent with the current picture of the tail of the EoR. The simulated C II exhibits a bimodal distribution with large absorptions in and around galaxies, and some traces in the lower density IGM. We find some discrepancies between the observed and simulated column density relationships among different ionic species at z = 6, probably due to uncertainties in the assumed UV background. Finally, our simulations are in good agreement with observations of the HI column density distribution function at z = 4 and the HI cosmological mass density Omega(HI) at 4 < z < 6.

At low densities, the standard ionization history of the intergalactic medium (IGM) predicts a decreasing temperature of the IGM with decreasing density once hydrogen (and helium) reionization is complete. Heating the high-redshift, low-density IGM above the temperature expected from photoheating is difficult, and previous claims of high/rising temperatures in low-density regions of the Universe based on the probability density function (PDF) of the opacity in Ly α forest data at 2 < z < 4 have been met with considerable scepticism, particularly since they appear to be in tension with other constraints on the temperature–density relation (TDR). We utilize here an ultrahigh signal-to-noise spectrum of the Quasi-stellar object HE0940-1050 and a novel technique to study the low opacity part of the PDF. We show that there is indeed evidence (at 90 per cent confidence level) that a significant volume fraction of the underdense regions at z ∼ 3 has temperatures as high or higher than those at densities comparable to the mean and above. We further demonstrate that this conclusion is nevertheless consistent with measurements of a slope of the TDR in overdense regions that imply a decreasing temperature with decreasing density, as expected if photoheating of ionized hydrogen is the dominant heating process. We briefly discuss implications of our findings for the need to invoke either spatial temperature fluctuations, as expected during helium reionization, or additional processes that heat a significant volume fraction of the low-density IGM.

An interesting transient has been detected in one of our three Dark Energy Camera deep fields. Observations of these deep fields take advantage of the high red sensitivity of DECam on the Cerro Tololo Interamerican Observatory Blanco telescope. The survey includes the Y band with rest wavelength 1430{\AA} at z = 6. Survey fields (the Prime field 0555-6130, the 16hr field 1600-75 and the SUDSS New Southern Field) are deeper in Y than other infrared surveys. They are circumpolar, allowing all night to be used efficiently, exploiting the moon tolerance of 1 micron observations to minimize conflict with the Dark Energy Survey. As an i-band dropout (meaning that the flux decrement shortward of Lyman alpha is in the i bandpass), the transient we report here is a supernova candidate with z ~ 6, with a luminosity comparable to the brightest known current epoch superluminous supernova (i.e., ~ 2 x 10^11 solar luminosities).

In this paper, we compare the radio emission at 1.4 GHz with optical outflowsignatures of edgeon galaxies. We report observations of six edge-on star-forming galaxies in the Sydney-AAO Multiobject Integral-field spectrograph Galaxy Survey with 1.4 GHz luminosities > 1 x 10(21) WHz(-1). Extended minor axis optical emission is detected with enhanced [N II]/II alpha line ratios and velocity dispersions consistent with galactic winds in three of six galaxies. These galaxies may host outflows driven by a combination of thermal and cosmic ray processes. We find that galaxies with the strongest wind signatures have extended radio morphologies. Our results form a baseline for understanding the driving mechanisms of galactic winds.

We present predictions of spectral energy distributions (SEDs), from the UV to the FIR, of simulated galaxies at z = 0. These were obtained by post-processing the results of an N-body+hydro simulation of a cosmological box of side 25 Mpc, which uses the Multi-Phase Particle Integrator (MUPPI) for star formation and stellar feedback, with the GRASIL-3D radiative transfer code that includes reprocessing of UV light by dust. Physical properties of our sample of similar to 500 galaxies resemble observed ones, though with some tension at small and large stellar masses. Comparing predicted SEDs of simulated galaxies with different samples of local galaxies, we find that these resemble observed ones, when normalized at 3.6 mu m. A comparison with the Herschel Reference Survey shows that the average SEDs of galaxies, divided in bins of star formation rate (SFR), are reproduced in shape and absolute normalization to within a factor of similar to 2, while average SEDs of galaxies divided in bins of stellar mass show tensions that are an effect of the difference of simulated and observed galaxies in the stellar mass-SFR plane. We use our sample to investigate the correlation of IR luminosity in Spitzer and Herschel bands with several galaxy properties. SFR is the quantity that best correlates with IR light up to 160 mu m, while at longer wavelengths better correlations are found with molecular mass and, at 500 mu m, with dust mass. However, using the position of the FIR peak as a proxy for cold dust temperature, we assess that heating of cold dust is mostly determined by SFR, with stellar mass giving only a minor contribution. We finally show how our sample of simulated galaxies can be used as a guide to understand the physical properties and selection biases of observed samples.

We investigate the evolution of the galaxy star formation rate function (SFRF) and cosmic star formation rate density (CSFRD) of z similar to 1-4 galaxies, using cosmological smoothed particle hydrodynamic (SPH) simulations and a compilation of ultraviolet (UV), infrared (IR) and Ha observations. These tracers represent different populations of galaxies with the IR light being a probe of objects with high star formation rates and dust contents, while UV and Ha observations provide a census of low star formation galaxies where mild obscuration occurs. We compare the above SFRFs with the results of SPH simulations run with the code P-GADGET3(XXL). We focus on the role of feedback from active galactic nuclei (AGN) and supernovae in form of galactic winds. The AGN feedback prescription that we use decreases the simulated CSFRD at z < 3 but is not sufficient to reproduce the observed evolution at higher redshifts. We explore different wind models and find that the key factor for reproducing the evolution of the observed SFRF and CSFRD at z similar to 1-4 is the presence of a feedback prescription that is prominent at high redshifts (z >= 4) and becomes less efficient with time. We show that variable galactic winds which are efficient at decreasing the SFRs of low-mass objects are quite successful in reproducing the observables.

Superluminous supernovae are beginning to be discovered at redshifts as early as the epoch of reionization. A number of candidate mechanisms is reviewed, together with the discovery programs.

We investigate a sample of 40 local, main-sequence, edge-on disc galaxies using integral field spectroscopy with the Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey to understand the link between properties of the extraplanar gas and their host galaxies. The kinematics properties of the extraplanar gas, including velocity asymmetries and increased dispersion, are used to differentiate galaxies hosting large-scale galactic winds from those dominated by the extended diffuse ionized gas. We find rather that a spectrum of diffuse gas-dominated to wind-dominated galaxies exist. The wind-dominated galaxies span a wide range of star formation rates (SFRs; -1 a parts per thousand(2) log (SFR/M-aS (TM) yr(-1)) a parts per thousand(2) 0.5) across the whole stellar mass range of the sample (8.5 a parts per thousand(2) log (M-*/M-aS (TM)) a parts per thousand(2) 11). The wind galaxies also span a wide range in SFR surface densities (10(- 3)-10(- 1.5) M-aS (TM) yr(- 1) kpc(- 2)) that is much lower than the canonical threshold of 0.1 M-aS (TM) yr(- 1) kpc(- 2). The wind galaxies on average have higher SFR surface densities and higher H delta(A) values than those without strong wind signatures. The enhanced H delta(A) indicates that bursts of star formation in the recent past are necessary for driving large-scale galactic winds. We demonstrate with Sloan Digital Sky Survey data that galaxies with high SFR surface density have experienced bursts of star formation in the recent past. Our results imply that the galactic winds revealed in our study are indeed driven by bursts of star formation, and thus probing star formation in the time domain is crucial for finding and understanding galactic winds.