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Thermal point clouds integrate thermal radiation and laser point clouds effectively. However, the semantic information for the interpretation of building thermal point clouds can hardly be precisely inferred. Transferring the semantics encapsulated in 3D building models at LoD3 has a potential to fill this gap. In this work, we propose a workflow enriching thermal point clouds with the geo-position and semantics of LoD3 building models, which utilizes features of both modalities: The proposed method can automatically co-register the point clouds from different sources and enrich the thermal point cloud in facade-detailed semantics. The enriched thermal point cloud supports thermal analysis and can facilitate the development of currently scarce deep learning models operating directly on thermal point clouds., Comment: Accepted to the 3D GeoInfo 2024

We present radio observations of the galaxy cluster Abell S1136 at 888 MHz, using the Australian Square Kilometre Array Pathfinder radio telescope, as part of the Evolutionary Map of the Universe Early Science program. We compare these findings with data from the Murchison Widefield Array, XMM-Newton, the Wide-field Infrared Survey Explorer, the Digitised Sky Survey, and the Australia Telescope Compact Array. Our analysis shows the X-ray and radio emission in Abell S1136 are closely aligned and centered on the BCG, while the X-ray temperature profile shows a relaxed cluster with no evidence of a cool core. We find that the diffuse radio emission in the centre of the cluster shows more structure than seen in previous low-resolution observations of this source, which appeared formerly as an amorphous radio blob, similar in appearance to a radio halo; our observations show the diffuse emission in the Abell S1136 galaxy cluster contains three narrow filamentary structures visible at 888 MHz, between$\sim 80$ and 140 kpc in length; however the properties of the diffuse emission do not fully match that of a radio (mini-)halo or (fossil) tailed radio source., Comment: To appear in PASA

The Semmeldetector, is a machine learning application that utilizes object detection models to detect, classify and count baked goods in images. Our application allows commercial bakers to track unsold baked goods, which allows them to optimize production and increase resource efficiency. We compiled a dataset comprising 1151 images that distinguishes between 18 different types of baked goods to train our detection models. To facilitate model training, we used a Copy-Paste augmentation pipeline to expand our dataset. We trained the state-of-the-art object detection model YOLOv8 on our detection task. We tested the impact of different training data, model scale, and online image augmentation pipelines on model performance. Our overall best performing model, achieved an AP@0.5 of 89.1% on our test set. Based on our results, we conclude that machine learning can be a valuable tool even for unforeseen industries like bakeries, even with very limited datasets.

Infrared emission features toward interstellar gas of the IC 348 star cluster in Perseus have been recently proposed to originate from the amino acid tryptophan. The assignment was based on laboratory infrared spectra of tryptophan pressed into pellets, a method which is known to cause large frequency shifts compared to the gas phase. We assess the validity of the assignment based on the original Spitzer data as well as new data from JWST. In addition, we report new spectra of tryptophan condensed in para-hydrogen matrices to compare with the observed spectra. The JWST MIRI data do not show evidence for tryptophan, despite deeper integration toward IC 348. In addition, we show that several of the lines attributed to tryptophan are likely due to instrumental artifacts. This, combined with the new laboratory data, allows us to conclude that there is no compelling evidence for the tryptophan assignment.

The ability to build and leverage world models is essential for a general-purpose AI agent. Testing such capabilities is hard, in part because the building blocks of world models are ill-defined. We present Elements of World Knowledge (EWOK), a framework for evaluating world modeling in language models by testing their ability to use knowledge of a concept to match a target text with a plausible/implausible context. EWOK targets specific concepts from multiple knowledge domains known to be vital for world modeling in humans. Domains range from social interactions (help/hinder) to spatial relations (left/right). Both, contexts and targets are minimal pairs. Objects, agents, and locations in the items can be flexibly filled in enabling easy generation of multiple controlled datasets. We then introduce EWOK-CORE-1.0, a dataset of 4,374 items covering 11 world knowledge domains. We evaluate 20 openweights large language models (1.3B--70B parameters) across a battery of evaluation paradigms along with a human norming study comprising 12,480 measurements. The overall performance of all tested models is worse than human performance, with results varying drastically across domains. These data highlight simple cases where even large models fail and present rich avenues for targeted research on LLM world modeling capabilities., Comment: 21 pages (11 main), 7 figures. Authors Anna Ivanova, Aalok Sathe, Benjamin Lipkin contributed equally

Methods. We utilized the combined five SRG/eROSITA All-Sky Survey data (eRASS:5) to perform X-ray imaging and spectral analyses of the Centaurus cluster in various directions to large radii. Surface brightness (SB) profiles out to $2R_{200}$ were constructed. We acquired gas temperature, metallicity, and normalization per area profiles out to $R_{200}$. We compared our results with previous Centaurus studies, cluster outskirts measurements, and simulations. Comprehensive sky background analysis was done across the FoV, in particular, to assess the variation of the eROSITA Bubble emission that partially contaminates the field. Results. The processed X-ray images show the known sloshing-induced structures in the core. The core ($r\leq11~\mathrm{kpc}$) is better described with a 2T model than a 1T model. Here, we measured lower T from the cooler component (~1.0 keV) and higher Z ($\sim\!1.6Z_\odot$), signifying an iron bias. In the intermediate radial range, we observed prominent SB and normalization per area excesses in the eastern sector (Cen 45 location), reaching out to $R_{500}$. Temperature enhancements near the location of Cen 45 imply that the gas is shock-heated due to the interaction with Cen 30, the significant excess behind Cen 45 center might be the tail/ram-pressure-stripped gas. We found good agreement between the outskirt temperatures with the profile from simulations and fit from Suzaku outskirts measurements. We detected significant SB emission to the sky background level out to $R_{200}$ with a $3.5\sigma$ and followed by $2.9\sigma$ at $1.1R_{200}$. The metallicity at $R_{500}-R_{200}$ is low but within the ranges of other outskirts studies. Conclusions. We present the first measurement of ICM morphology and properties of Centaurus cluster sampling the whole azimuth beyond $30'$, increasing the probed volume by a factor of almost 30., Comment: Submitted to the Astronomy & Astrophysics journal: 19 pages, 10 figures (main text), 2 figure (appendix)

We investigated the potential of optical coherence tomography (OCT) as an additional imaging technique to predict future cardiovascular disease (CVD). We utilised a self-supervised deep learning approach based on Variational Autoencoders (VAE) to learn low-dimensional representations of high-dimensional 3D OCT images and to capture distinct characteristics of different retinal layers within the OCT image. A Random Forest (RF) classifier was subsequently trained using the learned latent features and participant demographic and clinical data, to differentiate between patients at risk of CVD events (MI or stroke) and non-CVD cases. Our predictive model, trained on multimodal data, was assessed based on its ability to correctly identify individuals likely to suffer from a CVD event(MI or stroke), within a 5-year interval after image acquisition. Our self-supervised VAE feature selection and multimodal Random Forest classifier differentiate between patients at risk of future CVD events and the control group with an AUC of 0.75, outperforming the clinically established QRISK3 score (AUC= 0.597). The choroidal layer visible in OCT images was identified as an important predictor of future CVD events using a novel approach to model explanability. Retinal OCT imaging provides a cost-effective and non-invasive alternative to predict the risk of cardiovascular disease and is readily accessible in optometry practices and hospitals., Comment: 18 pages for main manuscript, 7 figures, 2 pages for appendix and preprint for a journal

We study the size and structure of globular clusters (GC) systems of 118 early-type galaxies from the NGVS, MATLAS, and ACSVCS surveys. Fitting S\'ersic profiles, we investigate the relationship between effective radii of GC systems ($R_{e, \rm gc}$) and galaxy properties. GC systems are 2--4 times more extended than host galaxies across the entire stellar mass range of our sample ($10^{8.3} < M_* < 10^{11.6}~M_{\odot}$). The relationship between $R_{e, \rm gc}$ and galaxy stellar mass exhibits a characteristic "knee" at a stellar mass of $M_p \simeq 10^{10.8}$, similar to galaxy $R_e$--stellar mass relationship. We present a new characterization of the traditional blue and red GC color sub-populations, describing them with respect to host galaxy $(g'-i')$ color ($\Delta_{gi}$): GCs with similar colors to their hosts have a "red" $\Delta_{gi}$, and those significantly bluer GCs have a "blue" $\Delta_{gi}$. The GC populations with red $\Delta_{gi}$, even in dwarf galaxies, are twice as extended as the stars, suggesting that formation or survival mechanisms favor the outer regions. We find a tight correlation between $R_{e, \rm gc}$ and the total number of GCs, with intrinsic scatter $\lesssim 0.1$ dex spanning two and three orders of magnitude in size and number, respectively. This holds for both red and blue subpopulations, albeit with different slopes. Assuming that $N_{GC, Total}$ correlates with $M_{200}$, we find that the red GC systems have effective radii of roughly 1-5\% $R_{\rm 200}$, while the blue GC systems in massive galaxies can have sizes as large as $\sim$10\% $R_{\rm 200}$. Environmental dependence on $R_{e, \rm gc}$ is also found, with lower density environments exhibiting more extended GC systems at fixed mass., Comment: 28 pages, 18 Figures, 3 tables, accepted for publication in ApJ

We use spectral energy distribution (SED) fitting to place constraints on the stellar populations of 59 ultra-diffuse galaxies (UDGs) in the low-to-moderate density fields of the MATLAS survey. We use the routine PROSPECTOR, coupled with archival data in the optical from DECaLS, and near- and mid-infrared imaging from WISE, to recover the stellar masses, ages, metallicities and star formation timescales of the UDGs. We find that a subsample of the UDGs lies within the scatter of the mass-metallicity relation (MZR) for local classical dwarfs. However, another subsample is more metal-poor, being consistent with the evolving MZR at high-redshift. We investigate UDG positioning trends in the mass-metallicity plane as a function of surface brightness, effective radius, axis ratio, local volume density, mass-weighted age, star formation timescale, globular cluster (GC) counts and GC specific frequency. We find that our sample of UDGs can be separated into two main classes. Class A: Comprised of UDGs with lower stellar masses, prolonged star formation histories (SFHs), more elongated, inhabiting less dense environments, hosting fewer GCs, younger, consistent with the classical dwarf MZR, and fainter. Class B: UDGs with higher stellar masses, rapid SFHs, rounder, inhabiting the densest of our probed environments, hosting on average the most numerous GC systems, older, consistent with the high-redshift MZR (i.e., consistent with early-quenching), and brighter. The combination of these properties suggests that UDGs of Class A are consistent with a `puffed-up dwarf' formation scenario, while UDGs of Class B seem to be better explained by `failed galaxy' scenarios., Comment: Accepted for publication in MNRAS. 19 pages (+6 of appendices), 10 figures, 5 tables

We aim to participate in the calibration of the X-ray photon count rate to halo mass scaling relation of galaxy clusters selected in the first eROSITA All-Sky Survey on the Western Galactic Hemisphere (eRASS1) using KiDS-1000 weak-lensing (WL) data. We measure the radial shear profiles around eRASS1 galaxy clusters using background galaxies in KiDS-1000, as well as the cluster member contamination. Furthermore we provide consistency checks with the other stage-III WL surveys who take part in the eRASS1 mass calibration, DES Y3 and HSC-Y3. We determine the cluster member contamination of eRASS1 clusters present in KiDS-1000 based on source number density profiles, where we account for the obscuration caused by cluster galaxies. The extracted shear profiles, together with the contamination model and the lens sample selection, are then analysed through a Bayesian population model. We calibrate the WL mass bias parameter by analysing realistic synthetic shear profiles from mock cluster catalogues. Our consistency checks between KiDS-1000 and DES Y3 & HSC-Y3 include the comparison of contamination-corrected density contrast profiles employing the union of background sources around common clusters, as well as the individual scaling relation results. We present a global contamination model for eRASS1 clusters in KiDS-1000 and the calibration results of the X-ray photon count rate to halo mass relation. The results of the WL mass bias parameter show that the uncertainty of the multiplicative shear bias dominates the systematic error budget at low clusters redshifts while the uncertainty of our contamination model does at high ones. The cross-checks between the three WL surveys show that they are statistically consistent with each other. This enables for the first time cosmological constraints from clusters calibrated by three state-of-the-art WL surveys. (abridged), Comment: 22 pages, 23 figures

When benchmarking optimization heuristics, we need to take care to avoid an algorithm exploiting biases in the construction of the used problems. One way in which this might be done is by providing different versions of each problem but with transformations applied to ensure the algorithms are equipped with mechanisms for successfully tackling a range of problems. In this paper, we investigate several of these problem transformations and show how they influence the low-level landscape features of a set of 5 problems from the CEC2022 benchmark suite. Our results highlight that even relatively small transformations can significantly alter the measured landscape features. This poses a wider question of what properties we want to preserve when creating problem transformations, and how to fairly measure them.

As the closest galaxy cluster, the Virgo Cluster is an exemplary environment for the study of large-scale filamentary structure and physical effects that are present in cluster outskirts but absent from the more easily studied inner regions. Here, we present an exploration of the SRG/eROSITA data from five all-sky surveys. eROSITA allows us to resolve the entire Virgo cluster and its outskirts on scales between 1 kpc and 3 Mpc, covering a total area on the sky of about 25 by 25 degrees. We utilize image manipulation techniques and surface brightness profiles to search for extended emission, surface brightness edges, and features in the outskirts. We employ a method of comparing mean and median profiles to measure gas clumping beyond the virial radius. Surface brightness analysis of the cluster and individual sectors of the cluster reveal the full extent of previously identified cold fronts to the north and south. The emissivity bias due to gas clumping, which we quantify over three orders of magnitude in radial range, is found to be mild, consistent with previous findings. We find an estimated virial gas mass of $M_{\mathrm{gas},r

We give a version of the Artin-Tate formula for surfaces over finite fields not assuming Tate's conjecture. It gives an equality between terms related to the Brauer group on the one hand and terms related to the Neron-Severi group on the other hand. We give estimates on the terms appearing in the formula and use this to gives sharp estimates on the size of the Brauer group of abelian surfaces depending on the p-rank.

We present new optical reflectance spectra of three potentially silicate-rich trans-Neptunian Objects (TNOs). These spectra were obtained with the aim of confirming past hints and detections of 0.7 micron absorption features associated with the presence of iron-bearing phyllosilicates. Our new spectrum of 120216 (2004 EW95) presents clearly detected absorption features that are similar in shape to hydrated mineral absorption bands present in the spectra of aqueously altered outer main belt asteroids. Four new reflectance spectra of 208996 (2003 AZ84) obtained at separate epochs all appear featureless, but vary significantly in spectral gradient (between approximately 3.5 %/0.1 micron and 8.5 %/0.1 micron) on a timescale consistent with this object's nominal rotational period. We report the first four optical reflectance spectra of 90568 (2004 GV9), finding them all to be featureless but consistent with colors previously reported for this object. We speculate that impacts are the only mechanism capable of delivering, excavating, or forming hydrated minerals at the surfaces of TNOs in detectable concentrations; as a result, any deposits of hydrated minerals on TNOs are predicted to be localized and associated with impact sites. Globally altered TNOs (as observationally suggested for 2004 EW95) plausibly formed more easily at smaller heliocentric distances (< 15 au) before being transplanted into the current trans-Neptunian population., Comment: 25 pages, 7 figures, 6 tables, accepted for publication in PSJ, v2 adjusted after proofing

Aims. We aim to characterize the gas properties in the cluster outskirts ($R_{500}R_{200}$) of the A3391/95 system and to compare them to predictions. Methods. We performed X-ray image and spectral analyses using the eROSITA PV data to assess the gas morphology and properties in the outskirts and the filaments in the directions of the previously detected Northern and Southern Filament of the A3391/95 system. We took particular care of the foreground. Results. In the filament-facing outskirts of A3391 and the Northern Clump, we find higher temperatures than typical cluster outskirts profiles, with a significance of $1.6-2.8\sigma$, suggesting heating due to their connections with the filaments. We confirm SB excess in the profiles of the Northern, Eastern, and Southern Filaments. From spectral analysis, we detect hot gas of ~1 keV for the Northern and Southern Filaments. The filament metallicities are below 10% solar metallicity and the $n_e$ range between 2.6 and $6.3\times10^{-5}~\mathrm{cm^{-3}}$. The characteristic properties of the Little Southern Clump (~1.5$R_{200}$ from A3395S in the Southern Filament) suggest that it is a small galaxy group. Excluding the LSC from the analysis of the Southern Filament decreases the gas density by 30%. This shows the importance of taking into account any clumps to avoid overestimation of the gas measurement in the outskirts and filament regions. Conclusions. The $n_e$ of the filaments are consistent with the WHIM properties as predicted by cosmological simulations, but the temperatures are higher, close to the upper WHIM temperature limit. As both filaments are short and located in a denser environment, stronger gravitational heating may be responsible for this temperature enhancement. The metallicities are low, but still within the expected range from the simulations., Comment: Accepted for publication in Astronomy & Astrophysics: 17 pages, 6 figures (main text), 1 figure (appendix)

Image super-resolution (SR) aims to learn a mapping from low-resolution (LR) to high-resolution (HR) using paired HR-LR training images. Conventional SR methods typically gather the paired training data by synthesizing LR images from HR images using a predetermined degradation model, e.g., Bicubic down-sampling. However, the realistic degradation type of test images may mismatch with the training-time degradation type due to the dynamic changes of the real-world scenarios, resulting in inferior-quality SR images. To address this, existing methods attempt to estimate the degradation model and train an image-specific model, which, however, is quite time-consuming and impracticable to handle rapidly changing domain shifts. Moreover, these methods largely concentrate on the estimation of one degradation type (e.g., blur degradation), overlooking other degradation types like noise and JPEG in real-world test-time scenarios, thus limiting their practicality. To tackle these problems, we present an efficient test-time adaptation framework for SR, named SRTTA, which is able to quickly adapt SR models to test domains with different/unknown degradation types. Specifically, we design a second-order degradation scheme to construct paired data based on the degradation type of the test image, which is predicted by a pre-trained degradation classifier. Then, we adapt the SR model by implementing feature-level reconstruction learning from the initial test image to its second-order degraded counterparts, which helps the SR model generate plausible HR images. Extensive experiments are conducted on newly synthesized corrupted DIV2K datasets with 8 different degradations and several real-world datasets, demonstrating that our SRTTA framework achieves an impressive improvement over existing methods with satisfying speed. The source code is available at https://github.com/DengZeshuai/SRTTA., Comment: Accepted by 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Learning to navigate to an image-specified goal is an important but challenging task for autonomous systems. The agent is required to reason the goal location from where a picture is shot. Existing methods try to solve this problem by learning a navigation policy, which captures semantic features of the goal image and observation image independently and lastly fuses them for predicting a sequence of navigation actions. However, these methods suffer from two major limitations. 1) They may miss detailed information in the goal image, and thus fail to reason the goal location. 2) More critically, it is hard to focus on the goal-relevant regions in the observation image, because they attempt to understand observation without goal conditioning. In this paper, we aim to overcome these limitations by designing a Fine-grained Goal Prompting (FGPrompt) method for image-goal navigation. In particular, we leverage fine-grained and high-resolution feature maps in the goal image as prompts to perform conditioned embedding, which preserves detailed information in the goal image and guides the observation encoder to pay attention to goal-relevant regions. Compared with existing methods on the image-goal navigation benchmark, our method brings significant performance improvement on 3 benchmark datasets (i.e., Gibson, MP3D, and HM3D). Especially on Gibson, we surpass the state-of-the-art success rate by 8% with only 1/50 model size. Project page: https://xinyusun.github.io/fgprompt-pages, Comment: Accepted by NeurIPS 2023

Purpose: This work aims to address the limitations faced by researchers in developing and sharing new MRI sequences by implementing an interpreter for the open-source MRI pulse sequence format, Pulseq, on a Philips MRI scanner. Methods: The implementation involved modifying a few source code files to create a Pulseq interpreter for the Philips MRI system. Validation experiments were conducted using simulations and phantom scans performed on a 7T Achieva MRI system. The observed sequence and waveforms were compared to the intended ones, and the gradient waveforms produced by the scanner were verified using a field camera. Image reconstruction was performed using the raw k-space samples acquired from both the native vendor environment and the Pulseq interpreter. Results: The reconstructed images obtained through the Pulseq implementation were found to be comparable to those obtained through the native implementation. The performance of the Pulseq interpreter was assessed by profiling the CPU utilization of the MRI spectrometer, showing minimal resource utilization for certain sequences. Conclusion: The successful implementation of the Pulseq interpreter on the Philips MRI scanner demonstrates the feasibility of utilizing Pulseq sequences on Philips MRI scanners. This provides an open-source platform for MRI sequence development, facilitating collaboration among researchers and accelerating scientific progress in the field of MRI., Comment: 15 pages, 4 figures and one table. Code for the MRI scanners will be made available for other research sites, through the vendor's code repository and forum, linked at http://openmr.nl/

The goal of the current pilot study was to examine the effects of bystander intervention training on a sample of 27 high school students who were selected by their peers as opinion leaders. Measures of bystander intervention knowledge, attitudes, and behaviors were included in the within-subjects design. Sixteen of the students also participated in focus groups to provide feedback about their experiences with the training. Results showed that participating students reported increases in knowledge about bullying and sexual harassment, confidence in intervening, acceptance of responsibility, knowing what to do, and acting to intervene (including direct intervention, providing support, and reporting to an adult) from pre-to posttest. Themes from focus groups indicated that students found the training relevant and helpful, particularly for focusing on both bullying and sexual harassment and for providing opportunities to learn and practice multiple intervention strategies. Barriers to intervening based on the type of violence (e.g., physical vs. relational or verbal) and relationship with the people involved were also themes. Directions for future research and implications for practice, such as focusing on dissemination to the larger student body and implementing bystander intervention training within the context of a positive school climate that emphasizes social and emotional competencies, are discussed. [This paper will be published in "Journal of Prevention and Health Promotion."]