14 research outputs found

    Clinico-physiological profile of patients of pulmonary impairment after tuberculosis at a tertiary care centre

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    Background: Pulmonary tuberculosis (TB) is a unique infectious disease that more often results in permanent structural changes in the lung parenchyma. It is by virtue of these changes that the patients even after bacteriological cure continue to suffer the after effects of the disease. Objective of study was to assess the clinico-physiological profile of patients of pulmonary impairment after tuberculosis (PIAT) attending S. N. Medical College, Agra, Uttar Pradesh, India.Methods: Over the time period of 2 years, 350 patients of healed pulmonary tuberculosis were identified and studied about their clinico-physiological profile. This profile included age, sex, category of treatment, pulmonary function test pattern, exercising capacity, exercise tolerance and quality of life.Results: It was found that majority of the patients were males, >60 years of age and had taken Category-II treatment. Most of the patients were having an obstructive pattern on PFT, poor exercise tolerance and exercise capacity and a poor quality of life.Conclusions: Patients of healed pulmonary TB continue to experience respiratory symptoms owing to the permanent anatomical changes in the lung conferred by the disease

    Counterspeeches up my sleeve! Intent Distribution Learning and Persistent Fusion for Intent-Conditioned Counterspeech Generation

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    Counterspeech has been demonstrated to be an efficacious approach for combating hate speech. While various conventional and controlled approaches have been studied in recent years to generate counterspeech, a counterspeech with a certain intent may not be sufficient in every scenario. Due to the complex and multifaceted nature of hate speech, utilizing multiple forms of counter-narratives with varying intents may be advantageous in different circumstances. In this paper, we explore intent-conditioned counterspeech generation. At first, we develop IntentCONAN, a diversified intent-specific counterspeech dataset with 6831 counterspeeches conditioned on five intents, i.e., informative, denouncing, question, positive, and humour. Subsequently, we propose QUARC, a two-stage framework for intent-conditioned counterspeech generation. QUARC leverages vector-quantized representations learned for each intent category along with PerFuMe, a novel fusion module to incorporate intent-specific information into the model. Our evaluation demonstrates that QUARC outperforms several baselines by an average of 10% across evaluation metrics. An extensive human evaluation supplements our hypothesis of better and more appropriate responses than comparative systems.Comment: ACL 202

    A Search for Technosignatures Around 31 Sun-like Stars with the Green Bank Telescope at 1.15-1.73 GHz

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    We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.Comment: 20 pages, 8 figures, in press at the Astronomical Journal (submitted on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov. 17

    Management of Non-COVID Respiratory Illnesses during the COVID-19 Pandemic—A Pulmonologist’s Perspective

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    The novel coronavirus disease 2019(COVID-19) caused by the SARS-CoV-2 virus continues to wreak havoc all over the world with approximately 57,714,184 infections and 1,373,065 deaths reported to date [...

    Boerhaave Syndrome: An Unusual Cause of Bilateral Exudative Pleural Effusion

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    A 45-year-old male, security guard, chronic alcoholic, presented to us with complaints of low-grade fe-ver, recurrent vomiting, bilateral pleuritic chest pain, dry cough, and progressive breathlessness for the past 4 days [...
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