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Myxococcus xanthus is a unicellular organism whose cells possess the ability to move and communicate, leading to the emergence of complex collective properties and behaviours. This has made it an ideal model system to study the emergence of collective behaviours in interdisciplinary research efforts lying at the intersection of biology and physics, especially in the growing field of active matter research. Often, challenges arise when setting up reliable and reproducible culturing protocols. This tutorial provides a clear and comprehensive guide on the culture, growth, development, and experimental sample preparation of \textit{M. xanthus}. Additionally, it includes some representative examples of experiments that can be conducted using these samples, namely motility assays, fruiting body formation, predation, and elasticotaxis.

On 2022 February 15, an impressive filament eruption was observed off the solar eastern limb from three remote-sensing viewpoints, namely Earth, STEREO-A, and Solar Orbiter. In addition to representing the most-distant observed filament at extreme ultraviolet wavelengths -- captured by Solar Orbiter's field of view extending to above 6 $R_{\odot}$ -- this event was also associated with the release of a fast ($\sim$2200 km$\cdot$s$^{-1}$) coronal mass ejection (CME) that was directed towards BepiColombo and Parker Solar Probe. These two probes were separated by 2$^{\circ}$ in latitude, 4$^{\circ}$ in longitude, and 0.03 au in radial distance around the time of the CME-driven shock arrival in situ. The relative proximity of the two probes to each other and to the Sun ($\sim$0.35 au) allows us to study the mesoscale structure of CMEs at Mercury's orbit for the first time. We analyse similarities and differences in the main CME-related structures measured at the two locations, namely the interplanetary shock, the sheath region, and the magnetic ejecta. We find that, despite the separation between the two spacecraft being well within the typical uncertainties associated with determination of CME geometric parameters from remote-sensing observations, the two sets of in-situ measurements display some profound differences that make understanding of the overall 3D CME structure particularly challenging. Finally, we discuss our findings within the context of space weather at Mercury's distances and in terms of the need to investigate solar transients via spacecraft constellations with small separations, which has been gaining significant attention during recent years., Comment: 31 pages, 13 figures, 5 tables, accepted for publication in The Astrophysical Journal

We present the one-dimensional Lyman-$\alpha$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$, contained in the DESI Early Data Release and the first two months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated to the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on log-normal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Lyman-$\alpha$ forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement., Comment: 23 pages, 23 figures, Journal version

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space.The BraTS-METS 2023 challenge successfully curated well-annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied clinical environments and providing personalized volumetric reports to patients undergoing BM treatment.

The Lyman-$\alpha$ forest offers a unique avenue for studying the distribution of matter in the high redshift universe and extracting precise constraints on the nature of dark matter, neutrino masses, and other $\Lambda$CDM extensions. However, interpreting this observable requires accurate modelling of the thermal and ionisation state of the intergalactic medium, and therefore resorting to computationally expensive hydrodynamical simulations. In this work, we build a neural network that serves as a surrogate model for rapid predictions of the one-dimensional \lya flux power spectrum ($P_{\rm 1D}$), thereby making Bayesian inference feasible for this observable. Our emulation technique is based on modelling $P_{\rm 1D}$ as a function of the slope and amplitude of the linear matter power spectrum rather than as a function of cosmological parameters. We show that our emulator achieves sub-percent precision across the full range of scales ($k_{\parallel }=0.1$ to 4Mpc$^{-1}$) and redshifts ($z=2$ to 4.5) considered, and also for three $\Lambda$CDM extensions not included in the training set: massive neutrinos, running of the spectral index, and curvature. Furthermore, we show that it performs at the 1% level for ionisation and thermal histories not present in the training set and performs at the percent level when emulating down to $k_{\parallel}$=8Mpc$^{-1}$. These results affirm the efficacy of our emulation strategy in providing accurate predictions even for cosmologies and reionisation histories that were not explicitly incorporated during the training phase, and we expect it to play a critical role in the cosmological analysis of the DESI survey., Comment: 15 pages, 17 figures

The Solar MAgnetic Connection HAUS tool (Solar-MACH) is an open-source tool completely written in Python that derives and visualizes the spatial configuration and solar magnetic connection of different observers (i.e., spacecraft or planets) in the heliosphere at different times. For doing this, the magnetic connection in the interplanetary space is obtained by the classic Parker Heliospheric Magnetic Field (HMF). In close vicinity of the Sun, a Potential Field Source Surface (PFSS) model can be applied to connect the HMF to the solar photosphere. Solar-MACH is especially aimed at providing publication-ready figures for the analyses of Solar Energetic Particle events (SEPs) or solar transients such as Coronal Mass Ejections (CMEs). It is provided as an installable Python package (listed on PyPI and conda-forge), but also as a web tool at solar-mach.github.io that completely runs in any web browser and requires neither Python knowledge nor installation. The development of Solar-MACH is open to everyone and takes place on GitHub, where the source code is publicly available under the BSD 3-Clause License. Established Python libraries like sunpy and pfsspy are utilized to obtain functionalities when possible. In this article, the Python code of Solar-MACH is explained, and its functionality is demonstrated using real science examples. In addition, we introduce the overarching SERPENTINE project, the umbrella under which the recent development took place., Comment: 14 pages, 5 figures

Optical tweezers are tools made of light that enable contactless pushing, trapping, and manipulation of objects ranging from atoms to space light sails. Since the pioneering work by Arthur Ashkin in the 1970s, optical tweezers have evolved into sophisticated instruments and have been employed in a broad range of applications in life sciences, physics, and engineering. These include accurate force and torque measurement at the femtonewton level, microrheology of complex fluids, single micro- and nanoparticle spectroscopy, single-cell analysis, and statistical-physics experiments. This roadmap provides insights into current investigations involving optical forces and optical tweezers from their theoretical foundations to designs and setups. It also offers perspectives for applications to a wide range of research fields, from biophysics to space exploration., Comment: 181 pages, 61 figures

We investigate the effects of the evolutionary processes in the internal magnetic structure of two interplanetary coronal mass ejections (ICMEs) detected in situ between 2020 November 29 and December 1 by Parker Solar Probe (PSP). The sources of the ICMEs were observed remotely at the Sun in EUV and subsequently tracked to their coronal counterparts in white light. This period is of particular interest to the community since it has been identified as the first widespread solar energetic particle event of Solar Cycle 25. The distribution of various solar and heliospheric-dedicated spacecraft throughout the inner heliosphere during PSP observations of these large-scale magnetic structures enables a comprehensive analysis of the internal evolution and topology of such structures. By assembling different models and techniques, we identify the signatures of interaction between the two consecutive ICMEs and the implications for their internal structure. We use multispacecraft observations in combination with a remote-sensing forward modeling technique, numerical propagation models, and in-situ reconstruction techniques. The outcome, from the full reconciliations, demonstrates that the two CMEs are interacting in the vicinity of PSP. Thus, we identify the in-situ observations based on the physical processes that are associated with the interaction and collision of both CMEs. We also expand the flux rope modeling and in-situ reconstruction technique to incorporate the aging and expansion effects in a distorted internal magnetic structure and explore the implications of both effects in the magnetic configuration of the ICMEs.

A detailed correlative structural, magnetic and chemical analysis of non-stoichiometric cobalt ferrite micrometric crystals was performed by x-ray magnetic circular dichroism combined with photoemission microscopy, low energy electron microscopy, and atomic force microscopy. The vector magnetization at the nanoscale is obtained from magnetic images at different x-ray incidence angles and compared with micromagnetic simulations, revealing the presence of defects which pin the magnetic domain walls. A comparison of different types of defects and the domain walls location suggests that the main source of pinning in these microcrystals are linear structural defects induced in the spinel by the substrate steps underneath the islands., Comment: 9 pages, 3 figures