A data augmentation methodology for training machine/deep learning gait recognition algorithms

There are several confounding factors that can reduce the accuracy of gait recognition systems. These factors can reduce the distinctiveness, or alter the features used to characterise gait; they include variations in clothing, lighting, pose and environment, such as the walking surface. Full invariance to all confounding factors is challenging in the absence of high-quality labelled training data. We introduce a simulation-based methodology and a subject-specific dataset which can be used for generating synthetic video frames and sequences for data augmentation. With this methodology, we generated a multi-modal dataset. In addition, we supply simulation files that provide the ability to simultaneously sample from several confounding variables. The basis of the data is real motion capture data of subjects walking and running on a treadmill at different speeds. Results from gait recognition experiments suggest that information about the identity of subjects is retained within synthetically generated examples. The dataset and methodology allow studies into fully-invariant identity recognition spanning a far greater number of observation conditions than would otherwise be possible

Automated Top View Registration of Broadcast Football Videos

In this paper, we propose a novel method to register football broadcast video frames on the static top view model of the playing surface. The proposed method is fully automatic in contrast to the current state of the art which requires manual initialization of point correspondences between the image and the static model. Automatic registration using existing approaches has been difficult due to the lack of sufficient point correspondences. We investigate an alternate approach exploiting the edge information from the line markings on the field. We formulate the registration problem as a nearest neighbour search over a synthetically generated dictionary of edge map and homography pairs. The synthetic dictionary generation allows us to exhaustively cover a wide variety of camera angles and positions and reduce this problem to a minimal per-frame edge map matching procedure. We show that the per-frame results can be improved in videos using an optimization framework for temporal camera stabilization. We demonstrate the efficacy of our approach by presenting extensive results on a dataset collected from matches of football World Cup 2014

Mucoepidermoid Carcinoma Of Thyroid Gland: A Rare Case Report

Introduction: Mucoepidermoid carcinoma is a common neoplasm of the salivary gland but can also occur in other sites like oesophagus, breast, lungs, pancreas, etc .In thyroid gland it is very uncommon or rare and is said to be of low grade indolent neoplasm. In literature few cases have been reported.Case report: 43 year old female presented with progressive midline swelling since 20 years with alteration in voice since two months. CT revealed heterogeneous enhancing lesion of 35x50x37 mm in left lobe of thyroid. FNAC revealed epithelial malignancy. Total thyroidectomy was done and specimen sent for histopathology.Result: Microscopically the tumor showed cells arranged in follicular and trabecular pattern. These tumors cells were of columnar and mucin producing type arranged in glandular pattern. Some of the cells show squamous metaplastic changes. These glands or follicles lack colloid. Final diagnosis of mucoepidermoid carcinoma of thyroid was given.Conclusion: Mucoepidermoid Carcinomaof thyroid is low grade neoplasm which extends into  ajjacent tissue by local infiltration and unlikely to metastasize, hence progress is good. It can also have agressive behaviour and hence a through search to be done histologically and also rule out other metastatic lesions

Chondrosarcoma of the anterior chest wall: surgical resection and reconstruction, our institutional experience

Primary chest wall tumours are not very common. Chondrosarcomas is most common tumour arising from the chest wall. It occurs more often during the third and fourth decade of life. Chondrosarcomas are resistant to conventional chemotherapy and radiotherapy. Wide margin surgical excision remains the best available treatment approach. For chondrosarcomas involving the chest wall, surgical excision may result in chest wall defects that may require reconstruction to obliterate dead space, restore chest wall rigidity, preserve respiratory mechanics, maintain pulmonary function, protect intrathoracic organs, provide soft tissue coverage and minimize deformity. In this article we present a series of 3 cases of chondrosarcoma of anterior chest wall managed at government Royapettah hospital, Kilpauk medical college, Chennai. A 71-year-old male patient, a case of 22×20 cm giant chondrosarcoma arising from anterior left chest wall involving 2nd to 8th ribs. We did wide local excision and reconstruction of chest wall with a synthetic bone cement (methyl methacrylate) construct, sandwiched between two layers of polypropylene mesh.  A 38-year-old male patient, a case of 8×6 cm chondrosarcoma of left anterior chest wall involving 9th rib, we did wide excision of tumor along with 8th, 9th, 10th ribs and defect reconstructed with prolene mesh.  A 37-year-old male patient, a case of 5×4 cm chondrosarcoma arising from left 4th rib. We did wide excision along with 4th rib and primary closure. Patients with chondrosarcomas generally have a good prognosis when optimally diagnosed and treated. Our case series is interesting due to the different sizes of chondrosarcomas at presentation, which are managed differently. Complete resection with wide surgical margin remains the best available treatment, but post resection chest wall reconstruction is posing a great surgical challenge

WOUND HEALING CONCEPTS: CONTEMPORARY PRACTICES AND FUTURE PERSPECTIVES

The advancements in the development of wound dressings have seen tremendous growth in the past few decades. Wound healing approach has majorly shifted from dry healing to moist healing. There has been a significant advancement in our understanding of the underlying physiology involved in wound healing and the associated systemic factors having a direct or indirect influence on the healing. This has resulted in the development of wound dressings designed to treat specific types of wounds. The present review discusses the physiology of wound healing, followed by different factors that contribute to healing. The advancements in wound dressings with their merits and limitations, newer approaches in wound care i.e., hyperbaric oxygen, negative pressure therapy, skin substitutes and role of growth factors in wound healing, have been highlighted. In addition, more recent approaches for effective wound care like smart devices with sensing, reporting and responding functions are discussed

Antenatal exposure to household air pollution and its association with increased risk of retinopathy

Background: Household air pollution (HAP) has been implicated in endothelial dysfunction and systemic inflammation which are the underlying mechanisms for retinopathy of prematurity (ROP). Objective: The study aims to estimate the incidence of ROP and its risk factors, specifically exploring antenatal exposure to HAP due to the use of traditional stoves/chullah as a risk factor for ROP. Methods: This cross-sectional observational study was conducted at a neonatal intensive care unit (NICU) of tertiary care hospital in Nagpur, India. Screening for ROP was done in 196 hospitalized preterm neonates discharged from NICU for a period of23 months in between December 2012 and October 2014. Mothers were considered as exposed to HAP if there was predominant use of chullah or open fire using wood, charcoal, crop waste, etc., for household cooking activities during her pregnancy and if cooking was done in the same room as the living room. Results: The incidence of any ROP in preterm neonates of mothers who were exposed to high polluting fuels (HPFs) antenatally was 51% as compared to 30% among those exposed to low polluting fuels. Those pregnant women who cooked outdoors or in a separate room had significantly lesser chances of developing ROP. Multivariateanalysis showed that environmental factors such as smoking in the household and usage of HPFs while cooking in the living room of the house (odds ratio 10.15; 95% confidence interval [1.3, 79.43]) increased the risk of developing ROP, after adjusting for other risk factors. In our study population, exposure to smoking and HAP were associated with higher risks of developing ROP, independent of covariates. Conclusion: Effective interventions to a committed and determined intersectoral coordination toward the promotion of public health are the need of the hour

Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks

Partial differential equations formalise the understanding of the behaviour of the physical world that humans acquire through experience and observation. Through their numerical solution, such equations are used to model and predict the evolution of dynamical systems. However, such techniques require extensive computational resources and assume the physics are prescribed \textit{a priori}. Here, we propose a neural network capable of predicting the evolution of a specific physical phenomenon: propagation of surface waves enclosed in a tank, which, mathematically, can be described by the Saint-Venant equations. The existence of reflections and interference makes this problem non-trivial. Forecasting of future states (i.e. spatial patterns of rendered wave amplitude) is achieved from a relatively small set of initial observations. Using a network to make approximate but rapid predictions would enable the active, real-time control of physical systems, often required for engineering design. We used a deep neural network comprising of three main blocks: an encoder, a propagator with three parallel Long Short-Term Memory layers, and a decoder. Results on a novel, custom dataset of simulated sequences produced by a numerical solver show reasonable predictions for as long as 80 time steps into the future on a hold-out dataset. Furthermore, we show that the network is capable of generalising to two other initial conditions that are qualitatively different from those seen at training time