DyST: Towards Dynamic Neural Scene Representations on Real-World Videos

Visual understanding of the world goes beyond the semantics and flat structure of individual images. In this work, we aim to capture both the 3D structure and dynamics of real-world scenes from monocular real-world videos. Our Dynamic Scene Transformer (DyST) model leverages recent work in neural scene representation to learn a latent decomposition of monocular real-world videos into scene content, per-view scene dynamics, and camera pose. This separation is achieved through a novel co-training scheme on monocular videos and our new synthetic dataset DySO. DyST learns tangible latent representations for dynamic scenes that enable view generation with separate control over the camera and the content of the scene.Comment: Project website: https://dyst-paper.github.io

DORSal: Diffusion for Object-centric Representations of Scenes et al

Recent progress in 3D scene understanding enables scalable learning of representations across large datasets of diverse scenes. As a consequence, generalization to unseen scenes and objects, rendering novel views from just a single or a handful of input images, and controllable scene generation that supports editing, is now possible. However, training jointly on a large number of scenes typically compromises rendering quality when compared to single-scene optimized models such as NeRFs. In this paper, we leverage recent progress in diffusion models to equip 3D scene representation learning models with the ability to render high-fidelity novel views, while retaining benefits such as object-level scene editing to a large degree. In particular, we propose DORSal, which adapts a video diffusion architecture for 3D scene generation conditioned on frozen object-centric slot-based representations of scenes. On both complex synthetic multi-object scenes and on the real-world large-scale Street View dataset, we show that DORSal enables scalable neural rendering of 3D scenes with object-level editing and improves upon existing approaches.Comment: Project page: https://www.sjoerdvansteenkiste.com/dorsa

Sensitivity of Slot-Based Object-Centric Models to their Number of Slots

Self-supervised methods for learning object-centric representations have recently been applied successfully to various datasets. This progress is largely fueled by slot-based methods, whose ability to cluster visual scenes into meaningful objects holds great promise for compositional generalization and downstream learning. In these methods, the number of slots (clusters) $K$ is typically chosen to match the number of ground-truth objects in the data, even though this quantity is unknown in real-world settings. Indeed, the sensitivity of slot-based methods to $K$, and how this affects their learned correspondence to objects in the data has largely been ignored in the literature. In this work, we address this issue through a systematic study of slot-based methods. We propose using analogs to precision and recall based on the Adjusted Rand Index to accurately quantify model behavior over a large range of $K$. We find that, especially during training, incorrect choices of $K$ do not yield the desired object decomposition and, in fact, cause substantial oversegmentation or merging of separate objects (undersegmentation). We demonstrate that the choice of the objective function and incorporating instance-level annotations can moderately mitigate this behavior while still falling short of fully resolving this issue. Indeed, we show how this issue persists across multiple methods and datasets and stress its importance for future slot-based models

Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames

Automatically discovering composable abstractions from raw perceptual data is a long-standing challenge in machine learning. Recent slot-based neural networks that learn about objects in a self-supervised manner have made exciting progress in this direction. However, they typically fall short at adequately capturing spatial symmetries present in the visual world, which leads to sample inefficiency, such as when entangling object appearance and pose. In this paper, we present a simple yet highly effective method for incorporating spatial symmetries via slot-centric reference frames. We incorporate equivariance to per-object pose transformations into the attention and generation mechanism of Slot Attention by translating, scaling, and rotating position encodings. These changes result in little computational overhead, are easy to implement, and can result in large gains in terms of data efficiency and overall improvements to object discovery. We evaluate our method on a wide range of synthetic object discovery benchmarks namely CLEVR, Tetrominoes, CLEVRTex, Objects Room and MultiShapeNet, and show promising improvements on the challenging real-world Waymo Open dataset.Comment: Accepted at ICML 2023. Project page: https://invariantsa.github.io

Bonding mechanism from the impact of thermally sprayed solid particles

Power particles are mainly in solid state prior to impact on substrates from high velocity oxy-fuel (HVOF) thermal spraying. The bonding between particles and substrates is critical to ensure the quality of coating. Finite element analysis (FEA) models are developed to simulate the impingement process of solid particle impact on substrates. This numerical study examines the bonding mechanism between particles and substrates and establishes the critical particle impact parameters for bonding. Considering the morphology of particles, the shear-instability–based method is applied to all the particles, and the energy-based method is employed only for spherical particles. The particles are given the properties of widely used WC-Co powder for HVOF thermally sprayed coatings. The numerical results confirm that in the HVOF process, the kinetic energy of the particle prior to impact plays the most dominant role in particle stress localization and melting of the interfacial contact region. The critical impact parameters, such as particle velocity and temperature, are shown to be affected by the shape of particles, while higher impact velocity is required for highly nonspherical powder

Development and validation of a prognostic score for long-term transplant-free survival in autoimmune hepatitis type 1

Background No prognostic score is currently available for long-term survival in autoimmune hepatitis (AIH) patients. Objective The aim of this study was to develop and validate such a prognostic score for AIH patients at diagnosis. Methods The prognostic score was developed using uni- & multivariate Cox regression in a 4-center Dutch cohort and validated in an independent 6-center Belgian cohort. Results In the derivation cohort of 396 patients 19 liver transplantations (LTs) and 51 deaths occurred (median follow-up 118 months; interquartile range 60-202 months). In multivariate analysis age (hazard ratio [HR] 1.045; p < 0.001), non-caucasian ethnicity (HR 1.897; p = 0.045), cirrhosis (HR 3.266; p < 0.001) and alanine aminotransferase level (HR 0.725; p = 0.003) were significant independent predictors for mortality or LT (C-statistic 0.827; 95% CI 0.790-0.864). In the validation cohort of 408 patients death or LT occurred in 78 patients during a median follow-up of 74 months (interquartile range: 25-142 months). Predicted 5-year event rate did not differ from observed event rate (high risk group 21.5% vs. 15.7% (95% CI: 6.3%-24.2%); moderate risk group 5.8% versus 4.3% (95% CI: 0.0%-9.1%); low risk group 1.9% versus 5.4% (95% CI: 0.0%-11.4%); C-statistic 0.744 [95% CI 0.644-0.844]). Conclusions A Dutch-Belgian prognostic score for long-term transplant-free survival in AIH patients at diagnosis was developed and validated

Atrial fibrillatory rate as predictor of recurrence of atrial fibrillation in horses treated medically or with electrical cardioversion

Background The recurrence rate of atrial fibrillation (AF) in horses after cardioversion to sinus rhythm (SR) is relatively high. Atrial fibrillatory rate (AFR) derived from surface ECG is considered a biomarker for electrical remodelling and could potentially be used for the prediction of successful AF cardioversion and AF recurrence. Objectives Evaluate if AFR was associated with successful treatment and could predict AF recurrence in horses. Study design Retrospective multicentre study. Methods Electrocardiograms (ECG) from horses with persistent AF admitted for cardioversion with either medical treatment (quinidine) or transvenous electrical cardioversion (TVEC) were included. Bipolar surface ECG recordings were analysed by spatiotemporal cancellation of QRST complexes and calculation of AFR from the remaining atrial signal. Kaplan-Meier survival curve and Cox regression analyses were performed to assess the relationship between AFR and the risk of AF recurrence. Results Of the 195 horses included, 74 received quinidine treatment and 121 were treated with TVEC. Ten horses did not cardiovert to SR after quinidine treatment and AFR was higher in these, compared with the horses that successfully cardioverted to SR (median [interquartile range]), (383 [367-422] vs 351 [332-389] fibrillations per minute (fpm), P < .01). Within the first 180 days following AF cardioversion, 12% of the quinidine and 34% of TVEC horses had AF recurrence. For the horses successfully cardioverted with TVEC, AFR above 380 fpm was significantly associated with AF recurrence (hazard ratio = 2.4, 95% confidence interval 1.2-4.8, P = .01). Main limitations The treatment groups were different and not randomly allocated, therefore the two treatments cannot be compared. Medical records and the follow-up strategy varied between the centres. Conclusions High AFR is associated with failure of quinidine cardioversion and AF recurrence after successful TVEC. As a noninvasive marker that can be retrieved from surface ECG, AFR can be clinically useful in predicting the probability of responding to quinidine treatment as well as maintaining SR after electrical cardioversion

Attitudes and delivering brief interventions for heavy drinking in primary health care: analyses from the ODHIN five country cluster randomized factorial trial

Contains fulltext : 170028.pdf (publisher's version ) (Open Access)In this paper, we test path models that study the interrelations between primary health care provider attitudes towards working with drinkers, their screening and brief advice activity, and their receipt of training and support and financial reimbursement. Study participants were 756 primary health care providers from 120 primary health care units (PHCUs) in different locations throughout Catalonia, England, The Netherlands, Poland, and Sweden. Our interventions were training and support and financial reimbursement to providers. Our design was a randomized factorial trial with baseline measurement period, 12-week implementation period, and 9-month follow-up measurement period. Our outcome measures were: attitudes of individual providers in working with drinkers as measured by the Short Alcohol and Alcohol Problems Perception Questionnaire; and the proportion of consulting adult patients (age 18+ years) who screened positive and were given advice to reduce their alcohol consumption (intervention activity). We found that more positive attitudes were associated with higher intervention activity, and higher intervention activity was then associated with more positive attitudes. Training and support was associated with both positive changes in attitudes and higher intervention activity. Financial reimbursement was associated with more positive attitudes through its impact on higher intervention activity. We conclude that improving primary health care providers' screening and brief advice activity for heavy drinking requires a combination of training and support and on-the-job experience of actually delivering screening and brief advice activity

Translating shared decision-making into health care clinical practices: Proof of concepts

Background: There is considerable interest today in shared decision-making (SDM), defined as a decision-making process jointly shared by patients and their health care provider. However, the data show that SDM has not been broadly adopted yet. Consequently, the main goal of this proposal is to bring together the resources and the expertise needed to develop an interdisciplinary and international research team on the implementation of SDM in clinical practice using a theory-based dyadic perspective. Methods: Participants include researchers from Canada, US, UK, and Netherlands, representing medicine, nursing, psychology, community health and epidemiology. In order to develop a collaborative research network that takes advantage of the expertise of the team members, the following research activities are planned: 1) establish networking and on-going communication through internet-based forum, conference calls, and a bi-weekly e-bulletin; 2) hold a two-day workshop with two key experts (one in theoretical underpinnings of behavioral change, and a second in dyadic data analysis), and invite all investigators to present their views on the challenges related to the implementation of SDM in clinical practices; 3) conduct a secondary analyses of existing dyadic datasets to ensure that discussion among team members is grounded in empirical data; 4) build capacity with involvement of graduate students in the workshop and online forum; and 5) elaborate a position paper and an international multi-site study protocol. Discussion: This study protocol aims to inform researchers, educators, and clinicians interested in improving their understanding of effective strategies to implement shared decision-making in clinical practice using a theory-based dyadic perspective

The effect of different cardiovascular risk presentation formats on intentions, understanding and emotional affect: a randomised controlled trial using a web-based risk formatter (protocol)

Background The future risk of heart disease can be predicted with increasing precision. However, more research is needed into how this risk is conveyed and presented. The aim of this study is to compare the effects of presenting cardiovascular risk in different formats on individuals' intention to change behaviour to reduce risk, understanding of risk information and emotional affect. Methods/design A randomised controlled trial comprising four arms, with a between subjects design will be performed. There will be two intervention groups and two control groups. The first control comprises a pre-intervention questionnaire and presents risk in a bar graph format. The second control presents risk in a bar graph format without pre-intervention questionnaire. These two control groups are to account for the potential Hawthorne effect of thinking about cardiovascular risk before viewing actual risk. The two intervention groups comprise presenting risk in either a pictogram or metonym format (image depicting seriousness of having a myocardial infarction). 800 individuals' aged between 45 and 64 years, who have not been previously diagnosed with heart disease and have access to a computer with internet, will be given a link to a website comprising a risk calculator and electronic questionnaires. 10-year risk of having a coronary heart disease event will be assessed and presented in one of the three formats. A post-intervention questionnaire will be completed after viewing the risk format. Main outcome measures are (i) intention to change behaviour, (ii) understanding of risk information, (iii) emotional affect and (iv) worry about future heart disease. Secondary outcomes are the sub-components of the theory of planned behaviour: attitudes, perceived behavioural control and subjective norms. Discussion Having reviewed the literature, we are not aware of any other studies which have used the assessment of actual risk, in a trial to compare different graphical cardiovascular risk presentation formats. This trial will provide data about which graphical cardiovascular risk presentation format is most effective in encouraging behaviour change to reduce cardiovascular risk. Trial registration Current Controlled Trials ISRCTN9131931