Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Neural Constitutive Laws From Motion Observations for Generalizable PDE Dynamics

We propose a hybrid neural network (NN) and PDE approach for learning generalizable PDE dynamics from motion observations. Many NN approaches learn an end-to-end model that implicitly models both the governing PDE and constitutive models (or material models). Without explicit PDE knowledge, these approaches cannot guarantee physical correctness and have limited generalizability. We argue that the governing PDEs are often well-known and should be explicitly enforced rather than learned. Instead, constitutive models are particularly suitable for learning due to their data-fitting nature. To this end, we introduce a new framework termed"Neural Constitutive Laws"(NCLaw), which utilizes a network architecture that strictly guarantees standard constitutive priors, including rotation equivariance and undeformed state equilibrium. We embed this network inside a differentiable simulation and train the model by minimizing a loss function based on the difference between the simulation and the motion observation. We validate NCLaw on various large-deformation dynamical systems, ranging from solids to fluids. After training on a single motion trajectory, our method generalizes to new geometries, initial/boundary conditions, temporal ranges, and even multi-physics systems. On these extremely out-of-distribution generalization tasks, NCLaw is orders-of-magnitude more accurate than previous NN approaches. Real-world experiments demonstrate our method's ability to learn constitutive laws from videos.
Rumor Detection with Hierarchical Representation on Bipartite Adhoc Event Trees

The rapid growth of social media has caused tremendous effects on information propagation, raising extreme challenges in detecting rumors. Existing rumor detection methods typically exploit the reposting propagation of a rumor candidate for detection by regarding all reposts to a rumor candidate as a temporal sequence and learning semantics representations of the repost sequence. However, extracting informative support from the topological structure of propagation and the influence of reposting authors for debunking rumors is crucial, which generally has not been well addressed by existing methods. In this article, we organize a claim post in circulation as an ad hoc event tree, extract event elements, and convert it into bipartite ad hoc event trees in terms of both posts and authors, i.e., author tree and post tree. Accordingly, we propose a novel rumor detection model with hierarchical representation on the bipartite ad hoc event trees called BAET. Specifically, we introduce word embedding and feature encoder for the author and post tree, respectively, and design a root-aware attention module to perform node representation. Then we adopt the tree-like RNN model to capture the structural correlations and propose a tree-aware attention module to learn tree representation for the author tree and post tree, respectively. Extensive experimental results on two public Twitter datasets demonstrate the effectiveness of BAET in exploring and exploiting the rumor propagation structure and the superior detection performance of BAET over state-of-the-art baseline methods.
Quantifying gliding forces of filamentous cyanobacteria by self-buckling

Filamentous cyanobacteria are one of the oldest and today still most abundant lifeforms on earth, with manifold implications in ecology and economics. Their flexible filaments, often several hundred cells long, exhibit gliding motility in contact with solid surfaces. The underlying force generating mechanism is not yet understood. Here, we demonstrate that propulsion forces and friction coefficients are strongly coupled in the gliding motility of filamentous cyanobacteria. We directly measure their bending moduli using micropipette force sensors, and quantify propulsion and friction forces by analyzing their self-buckling behavior, complemented with analytical theory and simulations. The results indicate that slime extrusion unlikely generates the gliding forces, but support adhesion-based hypotheses, similar to the better-studied single-celled myxobacteria. The critical self-buckling lengths align well with the peaks of natural length distributions, indicating the importance of self-buckling for the organization of their collective in natural and artificial settings.
Multi-Agent Coordination Fluid Flow Modeling and Experimental Evaluation

Reliability is a critical aspect of multi-agent system coordination as it ensures that the system functions correctly and consistently. If one agent in the system fails or behaves unexpectedly, it can negatively impact the performance and effectiveness of the entire system. Therefore, it is important to design and implement multi-agent systems with a high level of reliability to ensure that they can operate safely and move smoothly in the presence of unforeseen agent failure or lack of communication with some agent teams moving in a shared motion space. This paper presents a novel fluid flow navigation model that, in an ideal fluid flow, divides agents into cooperative (non-singular) and noncooperative (singular) agents, with cooperative agents sliding along streamlines safely enclosing noncooperative agents in a shared motion space. A series of flight experiments utilizing crazyflie quadcopters will experimentally validate the suggested model.
Cardiac magnetic resonance in Fabry disease

Abstract Fabry disease (FD) is a rare X-linked inherited lysosomal storage disorder caused by deficient a-galactosidase A activity that leads to an accumulation of glycolipids, mainly globotriaosylceramide (Gb3) and globotriaosylsphingosine, in affected tissues, including the heart. Cardiovascular involvement usually manifests as left ventricular hypertrophy (LVH), myocardial fibrosis, heart failure, and arrhythmias, which limit the quality of life and represent the most common causes of death. Following the introduction of enzyme replacement therapy, early diagnosis and treatment have become essential in slowing down the disease progression and preventing major cardiac complications. Recent advances in the understanding of FD pathophysiology suggest that in addition to Gb3 accumulation, other mechanisms contribute to the development of cardiac damage. FD cardiomyopathy is characterized by an earlier stage of glycosphingolipid accumulation and a later one of hypertrophy. Morphological and functional aspects are not specific in the echocardiographic evaluation of Anderson–Fabry disease. Cardiac magnetic resonance with tissue characterization capability is an accurate technique for the differential diagnosis of LVH. Progress in imaging techniques has improved the diagnosis and staging of FD-related cardiac disease: a decreased myocardial T1 value is specific of FD. Late gadolinium enhancement is typical of the later stage of cardiac involvement but as in other cardiomyopathy is also valuable to predict the outcome and cardiac response to therapy.
Successful aging of musicians: Preservation of sensorimotor regions aids audiovisual speech-in-noise perception

Musicianship can mitigate age-related declines in audiovisual speech-in-noise perception. We tested whether this benefit originates from functional preservation or functional compensation by comparing fMRI responses of older musicians, older nonmusicians, and young nonmusicians identifying noise-masked audiovisual syllables. Older musicians outperformed older nonmusicians and showed comparable performance to young nonmusicians. Notably, older musicians retained similar neural specificity of speech representations in sensorimotor areas to young nonmusicians, while older nonmusicians showed degraded neural representations. In the same region, older musicians showed higher neural alignment to young nonmusicians than older nonmusicians, which was associated with their training intensity. In older nonmusicians, the degree of neural alignment predicted better performance. In addition, older musicians showed greater activation in frontal-parietal, speech motor, and visual motion regions and greater deactivation in the angular gyrus than older nonmusicians, which predicted higher neural alignment in sensorimotor areas. Together, these findings suggest that musicianship-related benefit in audiovisual speech-in-noise processing is rooted in preserving youth-like representations in sensorimotor regions.
Echocardiography in cardioembolic stroke prevention

Abstract Stroke is a leading cause of mortality and disability, and cardiac embolism accounts for one-third of all ischaemic strokes. Thirty per cent of strokes are cryptogenic. In this setting, echocardiography is essential in the diagnosis, treatment, and prevention of embolic stroke of undetermined source since it is a widely available, safe, and inexpensive tool. Transthoracic echocardiography and transoesophageal echocardiography, furthermore, are proven to change therapeutic management leading to initiation of anti-coagulation, anti-microbial therapy, patent foramen ovale (PFO) closure, or cardiac tumour resection. The most common cardioembolic sources include left atrial appendage thrombus, left ventricular thrombus, vegetations in endocarditis, paradoxical embolization in PFO, prosthesis thrombosis, and intracardiac tumours. Although the presence of a cardioembolic source only represents a risk factor for an ischaemic stroke, it could not assure the certain or the unique cause of the event. The purpose of this review is to underline the importance of echocardiography and overview the main sources of cardiac embolism and the echocardiographic features.
Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection? A population-level view in the EHR-based RECOVER program

Abstract Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies.
Pseudoframes for Subspaces
with Applications

AbstractA notion of pseudoframes for subspaces (PFFS) is defined and characterized in a separable Hilbert space H. PFFS functions in a manner of a frame for a subspace X in H. Yet none of the pair of sequences {xn} and {x*n} is necessarily contained in X. This gives rise to attractive properties that center around the flexibility. A necessary and sufficient characterization of PFFSs is provided. Analytical formulae for the constructions of PFFSs in two directions are derived. Examples are considered. Some insight relationships of an PFFS for X and a frame of X are also observed thanks to a private communication with Casazza. Further applications of PFFSs are also discussed.
Cardiac magnetic resonance in ischemic cardiomyopathy: present role and future directions

Abstract Ischemic cardiomyopathy is a significant cause of mortality and morbidity, with peculiar needs for accurate diagnostic and prognostic characterization. Cardiac magnetic resonance (CMR) can help to satisfy these requirements by allowing a comprehensive evaluation of myocardial function, perfusion and tissue composition, with a demonstrated utility in guiding clinical management of patients with known or suspected ischemic cardiomyopathy. When compared with alternative non-invasive imaging modalities, such as stress echocardiography and nuclear techniques, CMR is able to provide accurate (function and perfusion) or peculiar (tissue characterization) information on cardiac pathophysiology, while avoiding exposition to ionizing radiations and overcoming limitations related to the quality of the imaging window. In particular, stress perfusion CMR showed to be accurate, safe, cost-effective, and clinically valuable as a non-invasive test for detecting severity and distribution of myocardial ischemia. In many circumstances, however, local availability of the technique, together with procedural costs, and scanning and post-processing time duration still limit the use of CMR in clinical routine. In the current review, we focused on clinical applications of CMR in ischemic cardiomyopathy. The consolidated role of the technique is described by illustrating both standard and advanced sequences that constitute the current body of a dedicated CMR examination. Ongoing developments and potential future diagnostic and prognostic applications of CMR when assessing ischemic cardiomyopathy are also discussed, with a focus on artificial intelligence-based implementations proposed for refining the efficiency of CMR analysis and reporting.
Scarring/arrhythmogenic cardiomyopathy

Abstract The designation of ‘arrhythmogenic cardiomyopathy’ reflects the evolving concept of a heart muscle disease affecting not only the right ventricle (ARVC) but also the left ventricle (LV), with phenotypic variants characterized by a biventricular (BIV) or predominant LV involvement (ALVC). Herein, we use the term ‘scarring/arrhythmogenic cardiomyopathy (S/ACM)’ to emphasize that the disease phenotype is distinctively characterized by loss of ventricular myocardium due to myocyte death with subsequent fibrous or fibro-fatty scar tissue replacement. The myocardial scarring predisposes to potentially lethal ventricular arrhythmias and underlies the impairment of systolic ventricular function. S/ACM is an ‘umbrella term’ which includes a variety of conditions, either genetic or acquired (mostly post-inflammatory), sharing the typical ‘scarring’ phenotypic features of the disease. Differential diagnoses include ‘non-scarring’ heart diseases leading to either RV dilatation from left-to-right shunt or LV dilatation/dysfunction from a dilated cardiomyopathy. The development of 2020 upgraded criteria (‘Padua criteria’) for diagnosis of S/ACM reflected the evolving clinical experience with the expanding spectrum of S/ACM phenotypes and the advances in cardiac magnetic resonance (CMR) imaging. The Padua criteria aimed to improve the diagnosis of S/ACM by incorporation of CMR myocardial tissue characterization findings. Risk stratification of S/ACM patients is mostly based on arrhythmic burden and ventricular dysfunction severity, although other ECG or imaging parameters may have a role. Medical therapy is crucial for treatment of ventricular arrhythmias and heart failure. Implantable cardioverter defibrillator (ICD) is the only proven life-saving treatment, despite its significant morbidity because of device-related complications and inappropriate shocks. Selection of patients who can benefit the most from ICD therapy is one of the most challenging issues in clinical practice.
Comparative study of finite wordlength effects in shift and delta operator parametrizations

The sensitivity of transfer functions is analyzed with respect to finite wordlength effect errors in the implementation of the coefficients of both shift operator and delta operator parametrizations. Both the absolute sensitivity, naturally connected to fixed point arithmetic, and the relative sensitivity, naturally connected to floating point arithmetic, are analyzed. In both cases, but particularly the latter, the delta operator parametrizations are shown to produce better sensitivity properties. <<ETX>>
Absolute Spectral Energy Distributions in Stars

The importance of measuring absolute energy distributions of stars was realized more than thirty years ago. At that time the main emphasis was on the comparison of fluxes from stars with those from suitable black-body sources on the Earth. In Germany extensive work of this kind was carried out by Kienle (1); Kienle, Strassl & Wempe (2); and Kienle, Wempe & Beileke (3). In England work was done at Greenwich by Dyson et al. (4), and by Greaves, Davidson & Martin (5). Williams (6, 7, 8), and Hall (9, 10, 11) did similar work in the United States. In France the early work was by Arnulf et al. (12). This work, apart from that of Hall, was all done by photographic techniques which were very difficult because of the large range in intensity which had to be covered and the difficulty of making accurate plate calibrations. There have been many comparisons of the results of these workers, the most recent one being that of Code (13). The importance of this work has been discussed and emphasized by Kienle (14), Barbier & Chalonge (15, 16), and Unsold (17). During the last ten years techniques for computing accurate model atmospheres have improved greatly and theoretical emergent fluxes are now available for stars of almost all temperatures and gravities. This development has again emphasized the need both for accurate absolute calibration of the fluxes from stars and for data on large numbers of stars.
The Application of Chain Code Sum in the Edge form Analysis

This dissertation expands on a new algorithm, which has the function of analyzing edge form with the chain code. By the introduction of the concepts of relative chain code and absolute chain code, we proposed a simple and direct algorithm to compute chain code sum(average chain code). We found that tangent direction(slope) of edge point can be figured by the absolute chain code sum of three sequential points and curvature of edge can be figured by the difference of chain code sum between the three sequential points ingoing and outgoing. Furthermore, we provided the criterion distinguishing edge inflexion and sleek curve section and the method computing inaccurately curvature radius and approximate perimeter. In the end of the paper, we introduced the use method with cell edge hollow repairing and overlap or conglutination cell segmenting for example. This algorithm has proved high speed and has a good effect of cell segmention on more than twenty groups of conglutinate and absent cells which are gathered from three kinds of cells.
Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT

Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Recent deep learning-based approaches can yield accurate scatter estimates quickly, yet full MC simulation is still required to generate scatter estimates as ground truth labels for all training data. Here we propose a physics-guided weakly supervised training framework for fast and accurate scatter estimation in quantitative SPECT by using a $100\times $ shorter MC simulation as weak labels and enhancing them with deep neural networks. Our weakly supervised approach also allows quick fine-tuning of the trained network to any new test data for further improved performance with an additional short MC simulation (weak label) for patient-specific scatter modelling. Our method was trained with 18 XCAT phantoms with diverse anatomies / activities and then was evaluated on 6 XCAT phantoms, 4 realistic virtual patient phantoms, 1 torso phantom and 3 clinical scans from 2 patients for 177Lu SPECT with single / dual photopeaks (113, 208 keV). Our proposed weakly supervised method yielded comparable performance to the supervised counterpart in phantom experiments, but with significantly reduced computation in labeling. Our proposed method with patient-specific fine-tuning achieved more accurate scatter estimates than the supervised method in clinical scans. Our method with physics-guided weak supervision enables accurate deep scatter estimation in quantitative SPECT, while requiring much lower computation in labeling, enabling patient-specific fine-tuning capability in testing.
Mixed emotional variants of gratitude: antecedent situations, cognitive appraisals, action tendencies, and psychosocial outcomes

ABSTRACT This research provides an exploratory investigation of whether gift/help-receiving contexts that elicit mixed emotional variants of gratitude can be distinguished from typical gratitude-eliciting situations in their associated appraisals, action tendencies, and psychosocial effects. We examined 473 participants (159 males, 312 females, 2 others; M age = 31.07) using a one-way four-conditions between-subjects experiment. Participants were randomly assigned to complete recall tasks describing four different gratitude-eliciting situations. Emotions, cognitive appraisals, action tendencies, and general psychosocial outcomes were assessed. Relative to a control condition involving receiving a gift or help (gift/help condition), receiving something at the expense of a benefactor (benefactor-inconvenience condition) elicited gratitude-guilt; receiving something with an expectation of return (return-favour condition) elicited gratitude-disappointment and gratitude-anger; while receiving a disliked gift or receiving assistance that made things worse (backfire condition) primarily elicited gratitude-disappointment while also eliciting gratitude-anger and gratitude-guilt. Each condition was differentiable from control in their appraisals, action tendencies, and psychosocial effects. Notably, contexts which elicited mixed emotional variants of gratitude were characterised by the co-occurrence of conflicting appraisals such as pleasantness and unpleasantness or goal-congruence and goal-incongruence. Additionally, the return-favour and backfire conditions were most dissimilar from control, and were associated with the most negative action tendencies and psychosocial outcomes.
Hydrogen Emission from Low Column Density Gas: Case C

With modern detectors it is now possible to image dilute gas near powerful sources of ionizing radiation. This note concerns hydrogen emission expected from such gas. Hydrogen recombination lines are usually said to be formed under either Case A or Case B conditions. Case B occurs when the neutral hydrogen column density is large enough for Lyman lines to be optically thick. They undergo multiple scatterings and are eventually degraded into a Balmer line and Lyα or two‐photon emission. Case A occurs when the neutral hydrogen column density is small enough for Lyman lines to be optically thin and so freely escape the cloud. Optical and infrared hydrogen lines are weaker in Case A than Case B since a significant fraction of the energy escapes as Lyman lines. Numerical simulations presented here show that when a photoionized cloud is optically thin in the Lyman lines its optical and infrared emission is not described by Case A. These lines will always be enhanced by continuum pumping unless the continuum source contains strong Lyman absorption lines. Continuum fluorescence in the Lyman lines will usually be competitive with recombination since the integrated continuous oscillator strength of the Lyman continuum is of order that of the Lyman lines. The line spectrum produced by a low column density cloud is mainly determined by the spectrum of the incident radiation field and the Lyman line optical depth. This situation was defined in the original literature as “Case C. ” It was not developed because the central stars of nebulae might have strong Lyman absorption lines, and so little pumping occurs in the interstellar case. This effect will be generally important for lower column density clouds in extragalactic sources, where Lyman lines are seldom in absorption. The purpose of this note is to draw attention to Case C and to motivate more precise calculations of emission in this limit.