Home-based physical therapy with an interactive computer vision system

In this paper, we present ExerciseCheck. ExerciseCheck is an interactive computer vision system that is sufficiently modular to work with different sources of human pose estimates, i.e., estimates from deep or traditional models that interpret RGB or RGB-D camera input. In a pilot study, we first compare the pose estimates produced by four deep models based on RGB input with those of the MS Kinect based on RGB-D data. The results indicate a performance gap that required us to choose the MS Kinect when we tested ExerciseCheck with Parkinson’s disease patients in their homes. ExerciseCheck is capable of customizing exercises, capturing exercise information, evaluating patient performance, providing therapeutic feedback to the patient and the therapist, checking the progress of the user over the course of the physical therapy, and supporting the patient throughout this period. We conclude that ExerciseCheck is a user-friendly computer vision application that can assist patients by providing motivation and guidance to ensure correct execution of the required exercises. Our results also suggest that while there has been considerable progress in the field of pose estimation using deep learning, current deep learning models are not fully ready to replace RGB-D sensors, especially when the exercises involved are complex, and the patient population being accounted for has to be carefully tracked for its “active range of motion.”Published versio

A Study of the Abrasive Waterjet Machining Process for Carbon Fibre-Reinforced Polymers

Following a comprehensive literature review on the progress of abrasive waterjet (AWJ) machining, an experimental study of the AWJ machining of carbon fibre-reinforced polymers (CFRPs) of various thicknesses was conducted, showing that clean cuts can be achieved with good processing rates. The effect of process parameters on the machined kerf and hole characteristics is amply discussed in the thesis. It was demonstrated that AWJ machining is a good process for thick CFRPs that other processes may be unable to cut. However, material delamination in the form of edge pop-up in the jet entry and push-out at the jet exit caused by the initial pure waterjet impact of an AWJ piercing operation was observed. It was experimentally shown that using a steel mask on top of the workpiece can eliminate pop-up delamination, while push-out delamination at the jet exit can be reduced or eliminated by proper process parameters. However, the mechanisms involved require further investigation. Mathematical models for predicting the major machining performance indicators were developed using dimensional and regression analysis. Experimental verification confirms that the predictive models are reasonable and reliable for assisting in the planning of AWJ machining processes. A computational model is developed and verified experimentally to study the interaction between a pure waterjet and CFRPs. The behaviour of the waterjet is modelled using the smoothed particle hydrodynamics method while the CFRP is modelled by finite element using a continuum damage material model and cohesive zone method. A computational study using the developed model reveals that the material pop-up delamination is initiated due to the material’s elastic response to a rapid release of shock pressure to stagnation pressure and the traverse shear stresses induced by the downward bending of the laminated layers. The pure waterjet impact causes flow divergence and a hydro wedging effect between the material plies, which propagates the delamination. The delamination magnitude is found to increase initially with waterjet pressure up to a threshold after which a change in pressure does not affect the pop-up delamination significantly. The smallest pop-up delamination area occurs on the [0]12 laminate, followed by the [0/45/90/-45/0/45]s and [0/90]3s laminate. It is also found that the push-out loading towards the jet exit and the hydro wedging effect act jointly to result in push-out delamination

Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data

The implicit bias towards solutions with favorable properties is believed to be a key reason why neural networks trained by gradient-based optimization can generalize well. While the implicit bias of gradient flow has been widely studied for homogeneous neural networks (including ReLU and leaky ReLU networks), the implicit bias of gradient descent is currently only understood for smooth neural networks. Therefore, implicit bias in non-smooth neural networks trained by gradient descent remains an open question. In this paper, we aim to answer this question by studying the implicit bias of gradient descent for training two-layer fully connected (leaky) ReLU neural networks. We showed that when the training data are nearly-orthogonal, for leaky ReLU activation function, gradient descent will find a network with a stable rank that converges to $1$, whereas for ReLU activation function, gradient descent will find a neural network with a stable rank that is upper bounded by a constant. Additionally, we show that gradient descent will find a neural network such that all the training data points have the same normalized margin asymptotically. Experiments on both synthetic and real data backup our theoretical findings.Comment: 55 pages, 7 figures. In NeurIPS 202

Three Essays on Opacity, Corporate Governance, and Credit Ratings

In the first essay, utilizing a more recent and expanded 20-year sample 1991-2010 of dual-rated bonds issued, I confirm Morgan\u27s (2002) finding that banks are relatively more opaque than nonbanks. The likelihood of a rating split is higher, and the magnitude of the rating gap is larger, for banks than nonnbanks. Moreover, rating agency disagreements are more significant for banks with relatively higher loan and trading securities holdings and maintain lower capital, and for banks engaged in mortgage securitization. Importantly, I find that rating agency disagreements reflect market proxies of information uncertainty. Further, opacity makes external financing more costly. Equity returns surrounding new bond issues are significantly negative on average, and notably lower, when information uncertainty is higher and for banks compared to nonbanks. In the second essay I investigate how corporate governance is related to bank opacity and how bank opacity is related to systematic and systemic risk. It is well known that opaque assets lead to higher systematic risk, which contributes to higher systemic risk. Banks by nature hold a large percentage of opaque assets, but the decision to hold such assets is partly endogenous. Results show that banks with relatively weak corporate governance hold a larger share of opaque assets. Consequently, they operate further along the risk-return frontier and have higher exposure to systemic risk. At the margin, strong corporate governance at publicly traded U.S. banking organizations reduces financial instability. In the third essay I examine if the rating agencies sacrifice the rating timeliness for the sake of rating stability. Credit rating agencies argue that markets expect them to issue stable ratings. Examining equity market reactions around CreditWatch events in 2002-2005, I find that the pursuit of stable rating may have reduced the timeliness of rating changes. Abnormal equity returns of a firm prior to being listed on CreditWatch are effective predictors of the ultimate change in rating that occurs when the firm is listed. Equity markets exhibit no reaction when a firm is delisted from CreditWatch, suggesting information about the rating change is already reflected in equity prices at the time of delisting

Show and Write: Entity-aware Article Generation with Image Information

Many vision-language applications contain long articles of text paired with images (e.g., news or Wikipedia articles). Prior work learning to encode and/or generate these articles has primarily focused on understanding the article itself and some related metadata like the title or date it was written. However, the images and their captions or alt-text often contain crucial information such as named entities that are difficult to be correctly recognized and predicted by language models. To address this shortcoming, this paper introduces an ENtity-aware article Generation method with Image iNformation, ENGIN, to incorporate an article's image information into language models. ENGIN represents articles that can be conditioned on metadata used by prior work and information such as captions and named entities extracted from images. Our key contribution is a novel Entity-aware mechanism to help our model better recognize and predict the entity names in articles. We perform experiments on three public datasets, GoodNews, VisualNews, and WikiText. Quantitative results show that our approach improves generated article perplexity by 4-5 points over the base models. Qualitative results demonstrate the text generated by ENGIN is more consistent with embedded article images. We also perform article quality annotation experiments on the generated articles to validate that our model produces higher-quality articles. Finally, we investigate the effect ENGIN has on methods that automatically detect machine-generated articles

Studies on the toxicokinetics of intragastricallyadministered paracetamol, aminophenazone, caffeine and chlorphenamine maleate tablets in rats

Purpose: To study the toxicokinetics of paracetamol (PCT), aminophenazone (ACP), caffeine (CFN) and chlorphenamine maleate (CPM) tablets after a single oral gavage, and after oral gavage for 14 consecutive days in rats. Methods: Eighty Sprague Dawley (SD) rats (half male, half female) were randomly divided into 4 groups with 20 rats in each group. Half of the rats were used for the toxicokinetic test after a single oral gavage of PCT, ACP, CFN and CPM tablets, while rats in the other half were used for the toxicokinetic tests after oral gavage for 14 consecutive days. The doses of the four groups were set as 0, 0.5, 1 and 2 tablets/kg body weight, respectively. Blood was taken from the rats and the plasma concentration of paracetamol was determined. Results: There was a significant difference in AUC0-∞ between male and female rats at single oral gavage of 2 tablets/kg of each of the drugs. The exposure amount of PCT (AUC0~t, AUC0-∞ and Cmax) increased with increase in dose, and showed a good linear relationship after a single intragastric administration of each drug, and after 14 consecutive days of intragastric administration at low, medium and high doses. Conclusion: The amount of PCT to which SD rats are exposed after a single intragastric administration of PCT, ACP, CFN and CPM tablets is lower in male than in female rats. However, no significant gender difference in exposure results when these drugs are given intragastrically for 14 consecutive days

3D multimodal dataset and token-based pose optimization

N00014-19-1-2571 - Department of Defense/ONRhttps://www.cs.bu.edu/faculty/betke/papers/Patel-etal-CV4Animals-CVPR-2022.pdfPublished versio

Controlling the 2D magnetism of CrBr3_3 by van der Waals stacking engineering

The manipulation of two-dimensional (2D) magnetic order is of significant importance to facilitate future 2D magnets for low-power and high-speed spintronic devices. Van der Waals stacking engineering makes promises for controllable magnetism via interlayer magnetic coupling. However, directly examining the stacking order changes accompanying magnetic order transitions at the atomic scale and preparing device-ready 2D magnets with controllable magnetic orders remain elusive. Here, we demonstrate effective control of interlayer stacking in exfoliated CrBr$_3$ via thermally assisted strain engineering. The stable interlayer ferromagnetic (FM), antiferromagnetic (AFM), and FM-AFM coexistent ground states confirmed by the magnetic circular dichroism measurements are realized. Combined with the first-principles calculations, the atomically-resolved imaging technique reveals the correlation between magnetic order and interlay stacking order in the CrBr$_3$ flakes unambiguously. A tunable exchange bias effect is obtained in the mixed phase of FM and AFM states. This work will introduce new magnetic properties by controlling the stacking order, and sequence of 2D magnets, providing ample opportunities for their application in spintronic devices.Comment: 7 pages, 4 figure

Long Range Interaction Models and Yangian Symmetry

The generalized Sutherland-Romer models and Yan models with internal spin degrees are formulated in terms of the Polychronakos' approach and RTT relation associated to the Yang-Baxter equation in consistent way. The Yangian symmetry is shown to generate both models. We finally introduce the reflection algebra K(u) to the long range models.Comment: 13 pages, preprint of Nankai Institute of Mathematics ( Theoretical Physics Division ), published in Physical Review E of 1995. For hard copy, write to Prof. Mo-lin GE directly. Do not send emails to this accoun

Myeloid cell-derived LL-37 promotes lung cancer growth by activating Wnt/β-catenin signaling

Rationale: Antimicrobial peptides, such as cathelicidin LL-37/hCAP-18, are important effectors of the innate immune system with direct antibacterial activity. In addition, LL-37 is involved in the regulation of tumor cell growth. However, the molecular mechanisms underlying the functions of LL-37 in promoting lung cancer are not fully understood. Methods: The expression of LL-37 in the tissues and sera of patients with non-small cell lung cancer was determined through immunohistological, immunofluorescence analysis, and enzyme-linked immunosorbent assay. The animal model of wild-type and Cramp knockout mice was employed to evaluate the tumorigenic effect of LL-37 in non-small cell lung cancer. The mechanism of LL-37 involving in the promotion of lung tumor growth was evaluated via microarray analyses, recombinant protein treatment approaches in vitro, tumor immunohistochemical assays, and intervention studies in vivo. Results: LL-37 produced by myeloid cells was frequently upregulated in primary human lung cancer tissues. Moreover, its expression level correlated with poor clinical outcome. LL-37 activated Wnt/β-catenin signaling by inducing the phosphorylation of protein kinase B and subsequent phosphorylation of glycogen synthase kinase 3β mediated by the toll-like receptor-4 expressed in lung tumor cells. LL-37 treatment of tumor cells also decreased the levels of Axin2. In contrast, it elevated those of an RNA-binding protein (tristetraprolin), which may be involved in the mechanism through which LL-37 induces activation of Wnt/β-catenin. Conclusion: LL-37 may be a critical molecular link between tumor-supportive immune cells and tumors, facilitating the progression of lung cancer