Miracle-dz/UniFAR-FTUs huggingface dataset:
PLGSLAM: Progressive Neural Scene Represenation with Local to Global Bundle Adjustment

Neural implicit scene representations have recently shown encouraging results in dense visual SLAM. However, existing methods produce low-quality scene reconstruction and low-accuracy localization performance when scaling up to large indoor scenes and long sequences. These limitations are mainly due to their single, global radiance field with finite capacity, which does not adapt to large scenarios. Their end-to-end pose networks are also not robust enough with the growth of cumulative errors in large scenes. To this end, we introduce PLGSLAM, a neural visual SLAM system capable of high-fidelity surface reconstruction and robust camera tracking in real-time. To handle large-scale indoor scenes, PLGSLAM proposes a progressive scene representation method which dynamically allocates new local scene representation trained with frames within a local sliding window. This allows us to scale up to larger indoor scenes and improves robustness (even under pose drifts). In local scene representation, PLGSLAM utilizes tri-planes for local high-frequency features with multi-layer perceptron (MLP) networks for the low-frequency feature, achieving smoothness and scene completion in unobserved areas. Moreover, we propose local-to-global bundle adjustment method with a global keyframe database to address the increased pose drifts on long sequences. Experimental results demonstrate that PLGSLAM achieves state-of-the-art scene reconstruction results and tracking performance across various datasets and scenarios (both in small and large-scale indoor environments).
Discovery of a Large-scale H i Plume in the NGC 7194 Group

We present the discovery of a new H i structure in the NGC 7194 group from the observations using the Karl G. Jansky Very Large Array. NGC 7194 group is a nearby (z ∼ 0.027) small galaxy group with five quiescent members. The observations reveal a 200 kpc long H i plume that spans the entire group with a total mass of M H I = 3.4 × 1010 M ⊙. The line-of-sight velocity of the H i gas gradually increases from south (7200 km s−1) to north (8200 km s−1), and the local velocity dispersion is up to 70 km s−1. The structure is not spatially coincident with any member galaxies but it shows close associations with a number of blue star-forming knots. Intragroup H i gas is not rare, but this particular structure is still one of the unusual cases in the sense that it does not show any clear connection with sizable galaxies in the group. We discuss the potential origins of this large-scale H i gas in the NGC 7194 group and its relation with the intergalactic star-forming knots. We propose that this H i feature could have originated from tidal interactions among group members or the infall of a late-type galaxy into the group. Alternatively, it might be leftover gas from flyby intruders.
A Deep Representation Learning-Based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencoder

Generally, the performance of deep neural networks (DNNs) heavily depends on the quality of data representation learning. Our preliminary work has emphasized the significance of deep representation learning (DRL) in the context of speech enhancement (SE) applications. Specifically, our initial SE algorithm employed a gated recurrent unit variational autoencoder (VAE) with a Gaussian distribution to enhance the performance of certain existing SE systems. Building upon our preliminary framework, this paper introduces a novel approach for SE using deep complex convolutional recurrent networks with a VAE (DCCRN-VAE). DCCRN-VAE assumes that the latent variables of signals follow complex Gaussian distributions that are modeled by DCCRN, as these distributions can better capture the behaviors of complex signals. Additionally, we propose the application of a residual loss in DCCRN-VAE to further improve the quality of the enhanced speech. {Compared to our preliminary work, DCCRN-VAE introduces a more sophisticated DCCRN structure and probability distribution for DRL. Furthermore, in comparison to DCCRN, DCCRN-VAE employs a more advanced DRL strategy. The experimental results demonstrate that the proposed SE algorithm outperforms both our preliminary SE framework and the state-of-the-art DCCRN SE method in terms of scale-invariant signal-to-distortion ratio, speech quality, and speech intelligibility.
Covariant cosmography: the observer-dependence of the Hubble parameter

The disagreement between low- and high-redshift measurements of the Hubble parameter is emerging as a serious challenge to the standard model of cosmology. We develop a covariant cosmographic analysis of the Hubble parameter in a general spacetime, which is fully model-independent and can thus be used as part of a robust assessment of the tension. Here our focus is not on the tension but on understanding the relation between the physical expansion rate and its measurement by observers -- which is critical for model-independent measurements and tests. We define the physical Hubble parameter and its multipoles in a general spacetime and derive for the first time the covariant boost transformation of the multipoles measured by a heliocentric observer. The analysis is extended to the covariant deceleration parameter. Current cosmographic measurements of the expansion anisotropy contain discrepancies and disagreements, some of which may arise because the correct transformations for a moving observer are not applied. A heliocentric observer will detect a dipole, generated not only by a Doppler effect, but also by an aberration effect due to shear. In principle, the observer can measure both the intrinsic shear anisotropy and the velocity of the observer relative to the matter -- without any knowledge of peculiar velocities, which are gauge dependent and do not arise in a covariant approach. The practical implementation of these results is investigated in a follow-up paper. We further show that the standard cosmographic relation between the Hubble parameter, the redshift and the luminosity distance (or magnitude) is not invariant under boosts and holds only in the matter frame. A moving observer who applies the standard cosmographic relation should correct the luminosity distance by a redshift factor -- otherwise an incorrect dipole and a spurious octupole are predicted.
A pure dipole analysis of the Gondwana apparent polar wander path: Paleogeographic implications in the evolution of Pangea

The paleogeography of prebreakup Pangea at the beginning of the Atlantic Spreading has been a subject of debate for the past 50 years. Reconciling this debate involves theoretical corrections that cast doubt on available data and paleomagnetism as an effective tool for performing paleoreconstructions. This 50 year old debate focuses specifically on magnetic remanence and its ability to correctly record the inclination of the paleomagnetic field. In this paper, a selection of paleopoles was made to find the great circles containing the paleomagnetic pole and the respective sampling site. The true dipole pole (TDP) was then calculated by intersecting these great circles, effectively avoiding nondipolar contributions and inclination shallowing, in an innovative method. The great circle distance between each of these TDPs and the paleomagnetic means show the accuracy of paleomagnetic determinations in the context of a dominantly geocentric, axial, and dipolar geomagnetic field. The TDPs calculated allowed a bootstrap analysis to be performed to further consider the flattening factor that should be applied to the sedimentary‐derived paleopoles. It is argued that the application of a single theoretical correction factor for clastic sedimentary‐derived records could lead to a bias in the paleolatitude calculation and therefore to incorrect paleogeographic reconstructions. The unbiased APWP makes it necessary to slide Laurentia to the west in relation to Gondwana in a B‐type Pangea during the Upper Carboniferous, later evolving, during the Early Permian, to reach the final A‐type Pangea configuration of the Upper Permian.
Dynamic Transmission Models: The Impact of Behavioural Feedbacks and Parametrization Methods on Disease Intervention Effectiveness

DYNAMIC TRANSMISSION MODELS: THE IMPACT OF BEHAVIOURAL FEEDBACKS AND PARAMETRIZATION METHODS ON DISEASE INTERVENTION EFFECTIVENESS Michael Andrews Advisor: University of Guelph, 2016 Chris T. Bauch Infectious diseases impose significant health and economic burdens across the world, continuously threatening human quality of life. Mathematical models of infectious disease epidemiology can help to gain insight on potential health outcomes of a population that is vulnerable to disease spread. Models that incorporate decision-making mechanisms can furthermore capture how behaviour-driven aspects of transmission such as vaccination choices and the use of non-pharmaceutical interventions (NPIs) interact with disease dynamics. In this thesis, we present three models of disease spread using the dynamic transmission and behaviour-disease modelling frameworks. Firstly, we investigate an age-stratified compartmental model of influenza transmission and the impact of estimating this model’s parameters using different surveillance data has on population level outcomes. In the latter two models, we remove random mixing assumptions and incorporate an individual-based approach. We also simultaneously integrate an individual’s decision making processes for utilizing two fundamental disease interventions: vaccination and NPIs. In the past, models have only considered the use of these interventions separately. All of our approaches focus on examining health outcomes of populations that are exposed to acute self-limited diseases, and offering insight on the effectiveness of disease mitigation strategies.
Modelling individual aesthetic judgements over time

Listening to music, watching a sunset—many sensory experiences are valuable to us, to a degree that differs significantly between individuals, and within an individual over time. We have theorized (Brielmann & Dayan 2022 Psychol. Rev. 129, 1319–1337 (doi:10.1037/rev0000337))) that these idiosyncratic values derive from the task of using experiences to tune the sensory-cognitive system to current and likely future input. We tested the theory using participants’ (n = 59) ratings of a set of dog images (n = 55) created using the NeuralCrossbreed morphing algorithm. A full realization of our model that uses feature representations extracted from image-recognizing deep neural nets (e.g. VGG-16) is able to capture liking judgements on a trial-by-trial basis (median r = 0.65), outperforming predictions based on population averages (median r = 0.01). Furthermore, the model’s learning component allows it to explain image sequence dependent rating changes, capturing on average 17% more variance in the ratings for the true trial order than for simulated random trial orders. This validation of our theory is the first step towards a comprehensive treatment of individual differences in evaluation. This article is part of the theme issue ‘Art, aesthetics and predictive processing: theoretical and empirical perspectives’.
Aesthetics and predictive processing: grounds and prospects of a fruitful encounter

In the last few years, a remarkable convergence of interests and results has emerged between scholars interested in the arts and aesthetics from a variety of perspectives and cognitive scientists studying the mind and brain within the predictive processing (PP) framework. This convergence has so far proven fruitful for both sides: while PP is increasingly adopted as a framework for understanding aesthetic phenomena, the arts and aesthetics, examined under the lens of PP, are starting to be seen as important windows into our mental functioning. The result is a vast and fast-growing research programme that promises to deliver important insights into our aesthetic encounters as well as a wide range of psychological phenomena of general interest. Here, we present this developing research programme, describing its grounds and highlighting its prospects. We start by clarifying how the study of the arts and aesthetics encounters the PP picture of mental functioning (§1). We then go on to outline the prospects of this encounter for the fields involved: philosophy and history of art (§2), psychology of aesthetics and neuroaesthetics (§3) and psychology and neuroscience more generally (§4). The upshot is an ambitious but well-defined framework within which aesthetics and cognitive science can partner up to illuminate crucial aspects of the human mind. This article is part of the theme issue ‘Art, aesthetics and predictive processing: theoretical and empirical perspectives’.
Retrospective analysis of Covid-19 hospitalization modelling scenarios which guided policy response in France

Epidemiological modelling has played a key role in proposing, analyzing and justifying non-pharmaceuticals interventions in response to the COVID-19 pandemic. Despite its importance, evaluations of models ability to accurately anticipate the evolution of the disease remain scarce. Thus, robust, systematic, and pre-specified evaluation criteria are needed to assess the relevance of modelling scenarios that guided policy response during the pandemic. We conduct a retrospective assessment of modelling reports which guided policy response in France from April 2020 to April 2022. After systematically verifying the scenarios hypotheses (e.g., exclusion of no-lockdown scenarios when a lockdown was effectively in place), we find that epidemiological models were (a) uncertain, (b) unaccurate, and (c) biased towards an overestimation of predicted COVID-19 related hospitalizations. In more than half of the reports, reality is below or equal to even the best-case scenario. To our knowledge, this is the only national systematic retrospective assessment of COVID-19 pandemic scenarios; such an approach should be reproduced in other countries whenever possible.
Factors affecting low-temperature cracking of asphalt pavements: analysis of field observations using the ordered logistic model

ABSTRACT Accurate identification of factors that primarily affect the number of low-temperature cracks is crucial for selection of road materials and planning of pavement maintenance. Field investigations of low-temperature cracks were performed in the years 2014 and 2020 on the same 68 road sections being in service in typical traffic conditions. The collected data were statistically analysed using the ordered logistic regression model. Comparison of the odds ratios which were calculated on the basis of the model enabled ordering of the selected factors from those having the greatest effect on low-temperature cracking of pavements to those with the least influence: (1) pavement age, (2) type of asphalt concrete, (3) modification of bitumen, (4) climatic zone (on the basis of low performance grade temperature). The odds of a section belonging to the group of cracked sections decreased by half when a polymer-modified bitumen was used in its binder course and asphalt base. Regardless of the considered factors, the odds of a pavement section being classified into the group of heavily cracked sections are comparable. It means that some external factors, including quality of paving works and bitumen chemistry, may prove the most crucial.
The primary moult of adult Red-headed Finches Amadina erythrocephala

Little is known about the biology of the Red-headed Finch Amadina erythrocephala. This study investigates its primary moult, the first aspect of its life history to be looked at in depth. Additionally, we used a modified Cook’s distance algorithm to explore the influence of individual years on the moult parameter estimates. Lastly, the primary moult of Red-headed Finches is compared to that of other passerines resident in the Highveld region of South Africa. Red-headed Finches breed through the Highveld winter, and start moult on 22 August, on average. Moult extends through spring and most of the summer, reaching completion on 22 February, on average. However, the moult started unusually early in the years 1988, 2005, 2008 and 2019, whereas in 2017 moult started unusually late. The duration of moult was estimated to be 185 days. The majority of other passerines resident in the central Highveld breed through summer, undergo primary moult in autumn, and complete moult before the regular frosts start to occur during the Highveld winter. The moult duration of the Red-headed Finch is substantially longer than that of other resident passerines.
Estimation of permanent deformation behaviour of crushed waste rocks using multistage repeated load triaxial and CBR tests

ABSTRACT Crushed waste rocks (CWR) are widely used to build mine haul roads. However, the permanent deformation in waste rocks layers can result in surface rutting. Realistic prediction of pavement rutting requires models that can accurately capture the permanent deformation behaviour under repeated loading. However, such models are usually based on advanced laboratory apparatus such as multistage (MS) repeated load triaxial (RLT) tests. In this study, a new approach, using MS repeated load California Bearing Ratio (RLCBR) tests, was proposed to estimate the permanent deformation behaviour of CWR. MS RLCBR tests are faster, easier and more often available than MS RLT tests. A series of MS RLCBR and MS RLT tests for different stress levels were therefore carried out on the same material to characterise CWR permanent deformation behaviour. Results showed that Rahman and Erlingsson model that modified by time hardening approach could satisfactorily capture CWR permanent deformation behaviour for MS RLT tests. A new model was proposed and fitted on MS RLCBR test results to predict CWR permanent deformation behaviour. This model performed well in describing MS RLCBR test results and predicting the CWR permanent deformation behaviour. Results indicate that MS RLCBR tests could be an effective alternative to MS RLT tests for estimating the permanent deformation behaviour of CWR.
Transgenic mice overexpressing Pitx2 in the atria develop tachycardia-bradycardia syndrome

Sinoatrial node (SAN) dysfunction often accompanies supraventricular tachyarrhythmias such as atrial fibrillation (AF), which is referred to as tachycardia-bradycardia syndrome (TBS). Although there have been many studies on electrical remodeling in TBS, the regulatory mechanisms that cause electrical remodeling in the SAN and atrial muscles by chronic bradycardia or tachycardia have not yet been fully investigated. Here we hypothesized that Pitx2c, a transcription factor that plays a central role in the late aspects of left-right asymmetric morphogenesis, regulates an interrelationship between the SAN and the atrial muscles and is involved in TBS-like pathology. To test this hypothesis, we generated transgenic mice overexpressing Pitx2c specifically in the atria (OE mice). Although Pitx2c is normally expressed only in left atria, the expression levels of Pitx2c protein in the right atria were significantly increased to similar levels of those in the left atria of non-transgenic control mice (WT). We found that the heart rate of OE mice was significantly variable although the average heart rate was similar between WT and OE mice. Electrophysiological examination showed that OE mice exhibited prolonged SAN recovery time and higher AF inducibility. In addition, recording of the atrial monophasic action potential duration using a Langendorff perfusion system demonstrated shorter action potential duration in OE atria. Histological analysis revealed that SAN-specific ion channel HCN4-positive cells were hardly detected in the SAN of OE mice, along with ectopic expression in the right atria. Furthermore, transcription factors associated with sinus node formation were down-regulated in the right atria of OE mice. Therefore, SAN dysfunction by Pitx2 dysregulation predisposed OE mice to a TBS-like phenotype. We conclude that Pitx2c is a key regulator that defines SAN function in the atria.
AAGGG repeat expansions trigger RFC1-independent synaptic dysregulation in human CANVAS Neurons

Cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS) is a late onset, recessively inherited neurodegenerative disorder caused by biallelic, non-reference pentameric AAGGG(CCCTT) repeat expansions within the second intron of replication factor complex subunit 1 (RFC1). To investigate how these repeats cause disease, we generated CANVAS patient induced pluripotent stem cell (iPSC) derived neurons (iNeurons) and utilized calcium imaging and transcriptomic analysis to define repeat-elicited gain-of-function and loss-of-function contributions to neuronal toxicity. AAGGG repeat expansions do not alter neuronal RFC1 splicing, expression, or DNA repair pathway functions. In reporter assays, AAGGG repeats are translated into pentapeptide repeat proteins that selectively accumulate in CANVAS patient brains. However, neither these proteins nor repeat RNA foci were detected in iNeurons, and overexpression of these repeats in isolation did not induce neuronal toxicity. CANVAS iNeurons exhibit defects in neuronal development and diminished synaptic connectivity that is rescued by CRISPR deletion of a single expanded allele. These phenotypic deficits were not replicated by knockdown of RFC1 in control neurons and were not rescued by ectopic expression of RFC1. These findings support a repeat-dependent but RFC1-independent cause of neuronal dysfunction in CANVAS, with important implications for therapeutic development in this currently untreatable condition. Summary Human CANVAS neurons exhibit transcriptional and functional synaptic defects that are corrected by heterozygous repeat deletion but are independent of the gene within which they reside—RFC1.