HandyPose and VehiPose: Pose Estimation of Flexible and Rigid Objects

Pose estimation is an important and challenging task in computer vision. Hand pose estimation has drawn increasing attention during the past decade and has been utilized in a wide range of applications including augmented reality, virtual reality, human-computer interaction, and action recognition. Hand pose is more challenging than general human body pose estimation due to the large number of degrees of freedom and the frequent occlusions of joints. To address these challenges, we propose HandyPose, a single-pass, end-to-end trainable architecture for hand pose estimation. Adopting an encoder-decoder framework with multi-level features, our method achieves high accuracy in hand pose while maintaining manageable size complexity and modularity of the network. HandyPose takes a multi-scale approach to representing context by incorporating spatial information at various levels of the network to mitigate the loss of resolution due to pooling. Our advanced multi-level waterfall architecture leverages the efficiency of progressive cascade filtering while maintaining larger fields-of-view through the concatenation of multi-level features from different levels of the network in the waterfall module. The decoder incorporates both the waterfall and multi-scale features for the generation of accurate joint heatmaps in a single stage. Recent developments in computer vision and deep learning have achieved significant progress in human pose estimation, but little of this work has been applied to vehicle pose. We also propose VehiPose, an efficient architecture for vehicle pose estimation, based on a multi-scale deep learning approach that achieves high accuracy vehicle pose estimation while maintaining manageable network complexity and modularity. The VehiPose architecture combines an encoder-decoder architecture with a waterfall atrous convolution module for multi-scale feature representation. It incorporates contextual information across scales and performs the localization of vehicle keypoints in an end-to-end trainable network. Our HandyPose architecture has a baseline of vehipose with an improvement in performance by incorporating multi-level features from different levels of the backbone and introducing novel multi-level modules. HandyPose and VehiPose more thoroughly leverage the image contextual information and deal with the issue of spatial loss of resolution due to successive pooling while maintaining the size complexity, modularity of the network, and preserve the spatial information at various levels of the network. Our results demonstrate state-of-the-art performance on popular datasets and show that HandyPose and VehiPose are robust and efficient architectures for hand and vehicle pose estimation

Citation sentence reuse behavior of scientists: A case study on massive bibliographic text dataset of computer science

Our current knowledge of scholarly plagiarism is largely based on the similarity between full text research articles. In this paper, we propose an innovative and novel conceptualization of scholarly plagiarism in the form of reuse of explicit citation sentences in scientific research articles. Note that while full-text plagiarism is an indicator of a gross-level behavior, copying of citation sentences is a more nuanced micro-scale phenomenon observed even for well-known researchers. The current work poses several interesting questions and attempts to answer them by empirically investigating a large bibliographic text dataset from computer science containing millions of lines of citation sentences. In particular, we report evidences of massive copying behavior. We also present several striking real examples throughout the paper to showcase widespread adoption of this undesirable practice. In contrast to the popular perception, we find that copying tendency increases as an author matures. The copying behavior is reported to exist in all fields of computer science; however, the theoretical fields indicate more copying than the applied fields

Multi-band Extension of the Wideband Timing Technique

The wideband timing technique enables the high-precision simultaneous estimation of Times of Arrival (ToAs) and Dispersion Measures (DMs) while effectively modeling frequency-dependent profile evolution. We present two novel independent methods that extend the standard wideband technique to handle simultaneous multi-band pulsar data incorporating profile evolution over a larger frequency span to estimate DMs and ToAs with enhanced precision. We implement the wideband likelihood using the libstempo python interface to perform wideband timing in the tempo2 framework. We present the application of these techniques to the dataset of fourteen millisecond pulsars observed simultaneously in Band 3 (300 - 500 MHz) and Band 5 (1260 - 1460 MHz) of the upgraded Giant Metrewave Radio Telescope (uGMRT) as a part of the Indian Pulsar Timing Array (InPTA) campaign. We achieve increased ToA and DM precision and sub-microsecond root mean square post-fit timing residuals by combining simultaneous multi-band pulsar observations done in non-contiguous bands for the first time using our novel techniques.Comment: Submitted to MNRA

Noise analysis of the Indian Pulsar Timing Array data release I

The Indian Pulsar Timing Array (InPTA) collaboration has recently made its first official data release (DR1) for a sample of 14 pulsars using 3.5 years of uGMRT observations. We present the results of single-pulsar noise analysis for each of these 14 pulsars using the InPTA DR1. For this purpose, we consider white noise, achromatic red noise, dispersion measure (DM) variations, and scattering variations in our analysis. We apply Bayesian model selection to obtain the preferred noise models among these for each pulsar. For PSR J1600$-$3053, we find no evidence of DM and scattering variations, while for PSR J1909$-$3744, we find no significant scattering variations. Properties vary dramatically among pulsars. For example, we find a strong chromatic noise with chromatic index $\sim$ 2.9 for PSR J1939+2134, indicating the possibility of a scattering index that doesn't agree with that expected for a Kolmogorov scattering medium consistent with similar results for millisecond pulsars in past studies. Despite the relatively short time baseline, the noise models broadly agree with the other PTAs and provide, at the same time, well-constrained DM and scattering variations.Comment: Accepted for publication in PRD, 30 pages, 17 figures, 4 table

Global Retinoblastoma Presentation and Analysis by National Income Level.

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs

The global retinoblastoma outcome study : a prospective, cluster-based analysis of 4064 patients from 149 countries

DATA SHARING : The study data will become available online once all analyses are complete.BACKGROUND : Retinoblastoma is the most common intraocular cancer worldwide. There is some evidence to suggest that major differences exist in treatment outcomes for children with retinoblastoma from different regions, but these differences have not been assessed on a global scale. We aimed to report 3-year outcomes for children with retinoblastoma globally and to investigate factors associated with survival. METHODS : We did a prospective cluster-based analysis of treatment-naive patients with retinoblastoma who were diagnosed between Jan 1, 2017, and Dec 31, 2017, then treated and followed up for 3 years. Patients were recruited from 260 specialised treatment centres worldwide. Data were obtained from participating centres on primary and additional treatments, duration of follow-up, metastasis, eye globe salvage, and survival outcome. We analysed time to death and time to enucleation with Cox regression models. FINDINGS : The cohort included 4064 children from 149 countries. The median age at diagnosis was 23·2 months (IQR 11·0–36·5). Extraocular tumour spread (cT4 of the cTNMH classification) at diagnosis was reported in five (0·8%) of 636 children from high-income countries, 55 (5·4%) of 1027 children from upper-middle-income countries, 342 (19·7%) of 1738 children from lower-middle-income countries, and 196 (42·9%) of 457 children from low-income countries. Enucleation surgery was available for all children and intravenous chemotherapy was available for 4014 (98·8%) of 4064 children. The 3-year survival rate was 99·5% (95% CI 98·8–100·0) for children from high-income countries, 91·2% (89·5–93·0) for children from upper-middle-income countries, 80·3% (78·3–82·3) for children from lower-middle-income countries, and 57·3% (52·1-63·0) for children from low-income countries. On analysis, independent factors for worse survival were residence in low-income countries compared to high-income countries (hazard ratio 16·67; 95% CI 4·76–50·00), cT4 advanced tumour compared to cT1 (8·98; 4·44–18·18), and older age at diagnosis in children up to 3 years (1·38 per year; 1·23–1·56). For children aged 3–7 years, the mortality risk decreased slightly (p=0·0104 for the change in slope). INTERPRETATION : This study, estimated to include approximately half of all new retinoblastoma cases worldwide in 2017, shows profound inequity in survival of children depending on the national income level of their country of residence. In high-income countries, death from retinoblastoma is rare, whereas in low-income countries estimated 3-year survival is just over 50%. Although essential treatments are available in nearly all countries, early diagnosis and treatment in low-income countries are key to improving survival outcomes.The Queen Elizabeth Diamond Jubilee Trust and the Wellcome Trust.https://www.thelancet.com/journals/langlo/homeam2023Paediatrics and Child Healt

Molecular generation using gated graph convolutional neural networks and reinforcement learning

The design of molecules with bespoke chemical properties has wide-ranging applications in materials science, chemistry and drug-discovery. This can be formulated as a supervised learning problem, where we first seek to encode discrete molecular graphs to continuous latent representations, and then use gradient-based optimization methods on these representations to optimize for the desired chemical properties. Recently, techniques such as Graph Convolutional Neural Networks (G-CNNs) and Message Passing Neural Networks (MPNNs) have been developed, which use deep learning methods to encode discrete graphs to continuous latent representations. In this project, we seek to attack the problem of molecular optimization with a twin- pronged approach of improving both the encoding technique and the optimization method. For this purpose, we build upon an existing state-of-the-art architecture called Junction Tree Variational Autoencoder (JT-VAE), which learns continuous latent vector representations for molecular graphs. These latent vector representations are then indirectly used for gradient-based optimization methods to improve chemical properties. JT-VAE makes use of MPNNs in its architecture. For the first part of our approach, we make use of a powerful variant of G-CNNs called, Gated-Graph Convolutional Neural Networks (GG-CNNs). We objectively demonstrate the efficacy of GG-CNNs over existing MPNN architectures in producing smooth and meaningful representations for molecular graphs. This is accomplished by replacing MPNN with GG-CNN in the JT-VAE architecture and then benchmarking their performance on various tasks. For the second part of our approach, we incorporate the reinforcement learning approach of Deep Deterministic Policy Gradient (DDPG) in the combined JT-VAE and GG-CNN architecture. Thus, we present a novel architecture incorporating GG-CNNs and DDPG on top of the JT-VAE architecture for purposes of molecular optimization. We perform all our experiments on the benchmark QM9 dataset, which contains 133,885 organic compounds having up to 9 heavy atoms.Bachelor of Engineering (Computer Science

Research Data for: Panoramic visual statistics shape retina-wide organization of receptive fields

Statistics of natural scenes are not uniform - their structure varies dramatically from ground to sky. It remains unknown whether these non-uniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. We show experimentally that, in agreement with our predictions, receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell-types

Intraventricular empyema caused by Neisseria meningitidis

Meningitis is defined as an inflammation of the protective covering of brain and spinal cord collectively called as meninges. Meningeal infection can be complicated by intraventricular empyema. There are 9 cases of intraventricular empyema described in the literature out of which only three are described to be caused by Neisseria meningitidis. We report the fourth rare case.A 61-year-old female with past medical history of diabetes and hypertension presented with the chief complaint of fever with chills and headache of 1-day duration. CT head did not reveal any acute abnormalities. Lumbar puncture was obtained and empiric IV antimicrobial agents were started. CSF analysis showed gram negative diplococci with culture growing Neisseria meningitidis suggesting meningococcal meningitis. Due to persistent headache and lethargy after complicated meningitis was suspected and MRI of brain was obtained which reflected a diagnosis of intraventricular empyema.Pyogenic ventriculitis also known as intraventricular empyema or ependymitis, is a defined as an inflammation of the ependymal lining of the cerebral ventricular system and is characterized by the presence of suppurative fluid in the ventricles. It is a health care associated complication and is often confused with meningitis due to the similar presentation. Therefore, persistent symptoms despite optimal antimicrobial therapy (therapeutic failure) should alarm the presence of pyogenic ventriculitis.This is the fourth case of intraventricular empyema reported secondary to Neisseria meningitidis. Our case reiterates that clinicians should maintain an index of suspicion for complicated meningitis in patients not responding to standard antimicrobial therapy. Keywords: Ventriculitis, Neisseria meningitidis, Intraventricular empyem

Panoramic visual statistics shape retina-wide organization of receptive fields

Statistics of natural scenes are not uniform - their structure varies dramatically from ground to sky. It remains unknown whether these non-uniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. We show experimentally that, in agreement with our predictions, receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell-types