Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Embodied Simulation to Detect Novel Object Classes Through Interaction

In this paper we present a novel method for a naive agent to detect novel objects it encounters in an interaction. We train a reinforcement learning policy on a stacking task given a known object type, and then observe the results of the agent attempting to stack various other objects based on the same trained policy. By extracting embedding vectors from a convolutional neural net trained over the results of the aforementioned stack- ing “play,” we can determine the similarity of a given object to known object types, and determine if the given object is likely dissimilar enough to the known types to be considered a novel class of object. We present the results of this method on two datasets gathered using two different policies and demonstrate what information the agent needs to extract from its environ- ment to make these novelty judgments.
Detection of Frequency-dependent Dispersion Measure toward the Millisecond Pulsar J2241–5236 from Contemporaneous Wideband Observations

Making precise measurements of pulsar dispersion measures (DMs) and applying suitable corrections for them is among the major challenges in high-precision timing programs such as pulsar timing arrays (PTAs). While the advent of wideband pulsar instrumentation can enable more precise DM measurements and thence improved timing precision, it also necessitates doing careful assessments of frequency-dependent (chromatic) DMs that were theorized by Cordes et al (2016). Here we report the detection of such an effect in broadband observations of the millisecond pulsar PSR J2241−5236, a high-priority target for current and future PTAs. The observations were made contemporaneously using the wideband receivers and capabilities now available at the Murchison Widefield Array, the upgraded Giant Metrewave Radio Telescope, and the Parkes telescopes, thus providing an unprecedentedly large frequency coverage from 80 MHz to 4 GHz. Our analysis shows the measurable changes in DM that scale with the observing frequency (ν) as δDM ∝ ν 2.5±0.1. We discuss the potential implications of such a frequency dependence in the measured DMs and the likely impact on the timing noise budget and comment on the usefulness of low-frequency observations in advancing PTA efforts.
Deep Learning Coherent Diffractive Imaging

We report the development of deep learning coherent electron diffractive imaging at sub-angstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying the trained CNNs to directly recover the phase images from electron diffraction patterns of twisted hexagonal boron nitride, monolayer graphene and a Au nanoparticle with comparable quality to those reconstructed by a conventional ptychographic method. Fourier ring correlation between the CNN and ptychographic images indicates the achievement of a spatial resolution in the range of 0.70 and 0.55 angstrom (depending on different resolution criteria). The ability to replace iterative algorithms with CNNs and perform real-time imaging from coherent diffraction patterns is expected to find broad applications in the physical and biological sciences.
Spanish Abstract Meaning Representation: Annotation of a General Corpus

Abstract Abstract Meaning Representation (AMR), originally designed for English, has been adapted to a number of languages to facilitate cross-lingual semantic representation and analysis. We build on previous work and present the first sizable, general annotation project for Spanish AMR. We release a detailed set of annotation guidelines and a corpus of 486 gold-annotated sentences spanning multiple genres from an existing, cross-lingual AMR corpus. Our work constitutes the second largest non-English gold AMR corpus to date. Fine-tuning an AMR to-Spanish generation model with our annotations results in a BERTScore improvement of 8.8%, demonstrating initial utility of our work.
MRXCAT-CDTI: A Numerical Cardiac Diffusion Tensor Imaging Phantom

Magnetic Resonance cardiac diffusion tensor imaging (cDTI) and cardiac intravoxel incoherent motion imaging enables probing of in vivo myofiber architecture and myocardial perfusion surrogates. To study the impact of experimental parameters such as resolution, off-resonances and heart-rate variations, we propose a numerical open-source framework called MRXCAT-CDTI. It allows simulating diffusion and perfusion contrast for spin-echo (SE) and stimulated echo acquisition mode (STEAM) cDTI sequences. The Fourier encoder supports in-plane and/or through-slice off-resonance effects, as well as T2* effects during single-shot image encoding. Optional lesions are included to mimic ischemic and infarcted myocardial regions. MRXCAT-CDTI allows assessing realistic influences on data acquisition, and how these affect the data encoding process and subsequent data processing. As an example, heart-rate variations lead to differences in partial saturation and relaxation of magnetization that end up in errors of 9 to 30% for cDTI angle metrics if not accounted for. For SE echo-planar cDTI, in-plane off-resonance effects more adversely affect cDTI metrics compared to through-slice off-resonances. With this work we propose an open-source MRXCAT-CDTI numerical simulation framework that offers realistic image encoding effects found in cardiac diffusion and perfusion data to systematically study influences of data encoding, reconstruction, and post-processing to promote reproducible research.
Static and spherically symmetric general relativity solutions in minimal theory of bigravity

We investigate static and spherically symmetric solutions in the Minimal Theory of Bigravity (MTBG). First, we show that a pair of Schwarzschild-de Sitter spacetimes with different cosmological constants and black hole masses written in the spatially-flat Gullstrand-Painlev\'e (GP) coordinates is a solution in the self-accelerating branch of MTBG, while it cannot be a solution in the normal branch. We then illustrate how Schwarzschild-de Sitter solutions can become compatible with the normal branch when using different coordinates. We also confirm that the self-accelerating branch of MTBG admits static and spherically symmetric general relativity solutions with matter written in the spatially-flat coordinates, including neutron stars with arbitrary matter equations of state. Finally, we show that in the self-accelerating branch nontrivial solutions are given by the Schwarzschild-de Sitter metrics written in nonstandard coordinates.
TVShowGuess: Character Comprehension in Stories as Speaker Guessing

We propose a new task for assessing machines’ skills of understanding fictional characters in narrative stories. The task, TVShowGuess, builds on the scripts of TV series and takes the form of guessing the anonymous main characters based on the backgrounds of the scenes and the dialogues. Our human study supports that this form of task covers comprehension of multiple types of character persona, including understanding characters’ personalities, facts and memories of personal experience, which are well aligned with the psychological and literary theories about the theory of mind (ToM) of human beings on understanding fictional characters during reading. We further propose new model architectures to support the contextualized encoding of long scene texts. Experiments show that our proposed approaches significantly outperform baselines, yet still largely lag behind the (nearly perfect) human performance.Our work serves as a first step toward the goal of narrative character comprehension.
Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation

Point clouds upsampling is a challenging issue to gener-ate dense and uniform point clouds from the given sparse input. Most existing methods either take the end-to-end su-pervised learning based manner, where large amounts of pairs of sparse input and dense ground-truth are exploited as supervision information; or treat up-scaling of different scale factors as independent tasks, and have to build multiple networks to handle upsampling with varying factors. In this paper, we propose a novel approach that achieves self-supervised and magnification-flexible point clouds upsampling simultaneously. We formulate point clouds upsampling as the task of seeking nearest projection points on the implicit surface for seed points. To this end, we define two implicit neural functions to estimate projection direction and distance respectively, which can be trained by two pretext learning tasks. Experimental results demonstrate that our self-supervised learning based scheme achieves competitive or even better performance than supervised learning based state-of-the-art methods. The source code is publicly available at https://github.com/xnowbzhaolsapcu.
Positioning Using Visible Light Communications: A Perspective Arcs Approach

Visible light positioning (VLP) is an accurate indoor positioning technology that uses luminaires as transmitters. In particular, circular luminaires are a common source type for VLP, which are typically treated only as point sources for positioning, while ignoring their geometry characteristics. In this paper, the arc feature of the circular luminaire and the coordinate information obtained via visible light communication (VLC) are jointly used for positioning, and a novel perspective arcs approach is proposed for VLC-enabled indoor positioning. The proposed approach does not rely on any inertial measurement unit and has no tilted angle limitation at the user. First, a VLC assisted perspective circle and arc algorithm (V-PCA) is proposed for a scenario in which a complete luminaire and an incomplete one can be captured by the user. Based on plane and solid geometry theory, the relationship between the luminaire and the user is exploited to estimate the orientation and the coordinate of the luminaire in the camera coordinate system. Then, the pose and location of the user in the world coordinate system are obtained by single-view geometry theory. Considering the cases in which parts of VLC links are blocked, an anti-occlusion VLC assisted perspective arcs algorithm (OA-V-PA) is proposed. In OA-V-PA, an approximation method is developed to estimate the projection of the luminaire’s center on the image and, then, to calculate the pose and location of the user. Simulation results show that the proposed indoor positioning algorithm can achieve a 90th percentile positioning accuracy of around 10 cm. Moreover, an experimental prototype is implemented to verify the feasibility. In the established prototype, a fused image processing method is proposed to simultaneously obtain the VLC information and the geometric information. Experimental results in the established prototype show that the average positioning accuracy is less than 5 cm for different tilted angles of the user.
Application of gap time analysis with flexible hazards to pulmonary exacerbations in the EPIC observational study

Cystic fibrosis and other chronic lung disease clinical trials often use time to first pulmonary exacerbation (PEx) or total PEx count as endpoints. The use of these outcomes may fail to capture patterns or timing of multiple exacerbations and how covariates influence the risk of future exacerbations. Analysis of gap times between PEx provides a useful framework to understand risks of subsequent events, particularly to assess if there is a temporary increase in a hazard of a subsequent PEx following the occurrence of a PEx. This may be useful for estimating the amount of time needed to follow patients after a PEx and predicting which patients are more likely to have multiple PEx. We propose a smoothed hazard for gap times to account for elevated hazards after exacerbations. A simulation study was conducted to explore model performance and was able to appropriately estimate parameters in all situations with an underlying change point with independent or correlated recurrent events. Models with different change‐point structures and trends are compared using Early Pseudomonas Infection Control (EPIC) observational study data, using a quasi‐likelihood modification of the Akaike information criterion; a model with a change‐point provided a better fit than a model without one. The analysis suggests that the change point may be 1.8 years (SE 0.09) after the end of a PEx. Models including covariates in the hazard function revealed that having one or two copies of the Δ$\Delta$ F508 mutation, female sex, and higher numbers of previous PEx were significantly associated with increased risk of another PEx.
Plasma haemolysis index and interleukine-6 for the early prediction of cardiac surgery-associated acute kidney injury. A proof-of-concept study

Introduction Haemolysis and inflammation contribute to cardiac surgery-associated acute kidney injury (CS-AKI). We aimed to assess the performance of plasma haemolysis index (HI) and interleukine-6 (IL-6) for the prediction of all-stage CS-AKI. We also assessed their ability to predict moderate-to-severe CS-AKI and to discriminate persistent from transient CS-AKI. Methods Adult patients undergoing cardiac surgery with cardiopulmonary bypass (CPB) were prospectively included. Haemolysis index and IL-6 were measured immediately after the end of CPB and 6 hours later. Correction for haemodilution relied upon changes in albuminaemia. Persistent CS-AKI was defined as a steady/increasing CS-AKI stage between the 48th and the 60th postoperative hour as compared with the worst stage observed within the 48 first hours. Results Among 82 patients, CS-AKI occurred in 37 (45%) patients. Postoperative HI and IL-6 were positively correlated to the duration of CPB (r ≤ 0.51, p ≤ 0.0003). Whether we considered isolated measurements of HI or IL-6, their indexation to haemodilution or not, their kinetics and/or their combination, the prediction of all stage CS-AKI was inaccurate (area under the receiver operating characteristic curve [AUCROC]≤ 0.68) whereas moderate-to-severe CS-AKI (6 patients only) was predicted with an honourable performance (AUCROC = 0.77 [95%CI 0.67;0.86] and 0.87 [95%CI 0.77;0.93] for HI and IL-6, respectively). The persistent/transient nature of CS-AKI was inaccurately predicted (AUCROC ≤ 0.68). Conclusions In a population in which most CS-AKI cases were mild, although they frequently (41%) persisted >48 hours, CS-AKI was inaccurately predicted by HI and/or IL-6. A better performance for moderate-to-severe CS-AKI prediction is likely. These preliminary findings are yet to be validated.
Tissue Sodium in Patients With Early Stage Hypertension: A Randomized Controlled Trial

Background Sodium (Na+) stored in skin and muscle tissue is associated with essential hypertension. Sodium magnetic resonance imaging is a validated method of quantifying tissue stores of Na+. In this study, we evaluated tissue Na+ in patients with elevated blood pressure or stage I hypertension in response to diuretic therapy or low Na+ diet. Methods and Results In a double‐blinded, placebo‐controlled trial, patients with systolic blood pressure 120 to 139 mm Hg were randomized to low sodium diet (<2 g of sodium), chlorthalidone, spironolactone, or placebo for 8 weeks. Muscle and skin Na+ using sodium magnetic resonance imaging and pulse wave velocity were assessed at the beginning and end of the study. Ninety‐eight patients were enrolled to undergo baseline measurements and 54 completed randomization. Median baseline muscle and skin Na+ in 98 patients were 16.4 mmol/L (14.9, 18.9) and 13.1 mmol/L (11.1, 16.1), respectively. After 8 weeks, muscle Na+ increased in the diet and chlorthalidone arms compared with placebo. Skin sodium was decreased only in the diet arm compared with placebo. These associations remained significant after adjustment for age, sex, body mass index, systolic blood pressure, and urinary sodium. No changes were observed in pulse wave velocity among the different groups when compared with placebo. Conclusions Diuretic therapy for 8 weeks did not decrease muscle or skin sodium or improve pulse wave velocity in patients with elevated blood pressure or stage I hypertension. Registration URL: https://www.clinicaltrials. gov; Unique identifier: NCT02236520.
Anti-inflammatory effect of ginsenoside Rg1 on LPS-induced septic encephalopathy and associated mechanism.

BACKGROUND Sepsis frequently occurs in patients after infection and is highly associated with death. Septic encephalopathy is characterized by dysfunction of the central nervous system, of which the root cause is a systemic inflammatory response. Sepsis-associated encephalopathy is a severe disease that frequently occurs in children, resulting in high morbidity and mortality. OBJECTIVES In the present study, we aim to investigate the neuroprotective mechanism of ginsenoside Rg1 in response to septic encephalopathy. METHODS Effects of ginsenoside Rg1 on septic encephalopathy were determined by cell viability, cytotoxicity, ROS responses, and apoptosis assays and histological examination of brain. Inflammatory activities were evaluated by expression levels of IL-1β, IL-6, IL-10, TNF-α, and MCP-1 using qPCR and ELISA. Activities of signaling pathways in inflammation were estimated by the production of p-Erk1/2/Erk1/2, p-JNK/JNK, p-p38/p38, p-p65/p65, and p-IkBα/IkBα using western blot. RESULTS LPS simulation resulted in a significant increase in cytotoxicity, ROS responses, and apoptosis and a significant decrease in cell viability in CTX TNA2 cells, as well as brain damage in rats. Moreover, the production of IL-1β, IL-6, IL-10, TNF-α, and MCP-1 was significantly stimulated both in CTX TNA2 cells and in the brain, which confirmed the establishment of vitro and in vivo models of septic encephalopathy. The damage and inflammatory responses induced by LPS were significantly decreased by treatment with Rg1. Western blot analyses indicated Rg1 significantly decreased the production of p-Erk1/2/Erk1/2, p-JNK/JNK, p-p38/p38, p-p65/p65, and p-IkBα/IkBα in LPS-induced CTX TNA2 cells and in the brain. CONCLUSIONS These findings suggested that Rg1 inhibited the activation of NF-κB and MAPK signaling pathways, which activate the production of proinflammatory cytokines and chemokines. The findings of this study suggest that ginsenoside Rg1 is a candidate treatment for septic encephalopathy.
Current Landscape and Future Perspectives of Abbreviated MRI for Hepatocellular Carcinoma Surveillance

While ultrasound (US) is considered an important tool for hepatocellular carcinoma (HCC) surveillance, it has limited sensitivity for detecting early-stage HCC. Abbreviated MRI (AMRI) has recently gained popularity owing to better sensitivity in its detection of early-stage HCC than US, while also minimizing the time and cost in comparison to complete contrast-enhanced MRI, as AMRI includes only a few essential sequences tailored for detecting HCC. Currently, three AMRI protocols exist, namely gadoxetic acid-enhanced hepatobiliary-phase AMRI, dynamic contrast-enhanced AMRI, and non-enhanced AMRI. In this study, we discussed the rationale and technical details of AMRI techniques for achieving optimal surveillance performance. The strengths, weaknesses, and current issues of each AMRI protocol were also elucidated. Moreover, we scrutinized previously performed AMRI studies regarding clinical and technical factors. Reporting and recall strategies were discussed while considering the differences in AMRI protocols. A risk-stratified approach for the target population should be taken to maximize the benefits of AMRI and the cost-effectiveness should be considered. In the era of multiple HCC surveillance tools, patients need to be fully informed about their choices for better adherence to a surveillance program.
Selected issues of operating 3 MW underground coal gasification installation

Experiences of operating underground coal gasification installation (UCG) are discussed in the article. The gasification experiment was conducted in active Wieczorek coal mine. The assumed maximum gasification capacity of the installation was 600 kg/h of coal, i.e. 3 MW contained in enthalpy of gas. An integrated design process was applied in preparing equipment of the UCG installation. The result was long-lasting tests (over 1400 h) of coal gasification process at nearatmospheric pressure. Gasification was conducted in a 5.4 m thick deposit with a mixture of: air and oxygen, air and CO2, air and water. Data on performance of a semi-industrial scale UCG installation were collected. The aim of the article is to present the process and selected experiences associated with operating the installation. External limitations influencing the gasification method, design of basic nodes and rules of running the process are described. The main problems encountered during the gasification process and UCG gas purification are presented.
Factors associated with readmission to alcohol and opioid detoxification in the Alaska Interior

Abstract Background and Objectives A “revolving door” of repeated admissions to detoxification treatment facilities has long plagued alcohol and drug use patients, yet few studies examine factors associated with readmission. This study examined risk factors for readmission to alcohol and opioid detoxification in a sample from the Alaska Interior. Methods Data were extracted from electronic medical records for admissions between 2012 and 2016 at an inpatient detoxification facility in Fairbanks, Alaska. Data from 1014 patients admitted for alcohol detoxification and 267 patients admitted for opioid detoxification were analyzed. The analysis employed descriptive statistics for risk factors (substance use history, adverse life experiences, and psychosocial functioning) and prevalence of readmission to either alcohol or opioid detoxification. Inferential analyses used marginal standardization to calculate differences in readmission risk by patient characteristics. Results Male, Alaska Native/American Indian, single‐never married patients, and those seeking work were at higher risk for readmission to alcohol detoxification, while those with stable housing were at reduced risk. Being single‐never married and completing detoxification treatment reduced readmission to opioid detoxification. Family involvement in detoxification reduced readmission risk for both alcohol and opioid patients. Discussion and Conclusions Further research that investigates the mechanism(s) by which family may act as a protective factor may be efficacious in eliminating the “revolving door” of detoxification. Scientific Significance This study is the first to examine both alcohol and opioid use risk and protective factors in the Alaska Interior. The results can be used in the development of interventions for subpopulations with high detoxification readmission rates.
Predictors for the detection of arrhythmia requiring pacemaker/ICD implantation—Results from a loop recorder study

There are few large studies on which factors are associated with the occurrence of arrhythmias. Implantable loop recorders (ILR) are useful in detecting arrhythmia due to prolonged and continuous ECG monitoring. Therefore, the aim of this study is to identify and evaluate clinical characteristics and ECG parameters for predicting arrhythmias requiring pacemaker/ICD implantation by analyzing a study cohort with ILR.