Sarcasm Detection on Text for Political Domain— An Explainable Approach

In the era of social media, a large volume of data is generated by applications such as the industrial internet of things, IoT, Facebook, Twitter, and individual usage. Artificial intelligence and big data tools plays an important role in devising mechanisms for handling this vast volume of data as per the required usage of data to form important information from this unstructured data. When the data is publicly available on the internet and social media, it is imperative to treat the data carefully to respect the sentiments of the individuals. In this paper, the authors have attempted to solve three problems for treating the data using AI and data science tools, weighted statistical methods, and explainability of sarcastic comments. The first objective of this research study is sarcasm detection, and the next objective is to apply it to a domain-specific political Reddit dataset. Moreover, the last is to predict sarcastic words using counterfactual explainability. The textare extracted from the self-annotated Reddit corpus dataset containing 533 million comments written in English language, where 1.3 million comments are sarcastic. The sarcasm detection based model uses a weighted average approach and deep learning models to extract information and provide the required output in terms of content classification. Identifying sarcasm from a sentence is very challenging when the sentence has content that flips the polarity of positive sentiment into negative sentiment. This cumbersome task can be achieved with artificial intelligenceand machine learningalgorithms that train the machine and assist in classifying the required content from the sentences to keep the social media posts acceptable to society. There should be a mechanism to determine the extent to which the model's prediction could be relied upon. Therefore, the explination of the prediction is essential. We studied the methods and developed a model for detecting sarcasm and explaining the prediction. Therefore, the sarcasm detection model with explainability assists in identifying the sarcasmfrom the reddit post and its sentiment score to classify given textcorrectly. The F1-score of 75.75% for sarcasm and 80% for the explainability model proves the robustness of the proposed model

The influence of hydrogen peroxide and histamine on lung permeability and translocation of iridium nanoparticles in the isolated perfused rat lung

BACKGROUND: Translocation of ultrafine particles (UFP) into the blood that returns from the lungs to the heart has been forwarded as a mechanism for particle-induced cardiovascular effects. The objective of this study was to evaluate the role of the endothelial barrier in the translocation of inhaled UFP from the lung into circulation. METHODS: The isolated perfused rat lung (IPRL) was used under negative pressure ventilation, and radioactive iridium particles (18 nm, CMD, (192)Ir-UFP) were inhaled during 60 minutes to achieve a lung burden of 100 – 200 μg. Particle inhalation was done under following treatments: i) control perfusion, ii) histamine (1 μM in perfusate, iii) luminal histamine instillation (1 mM), and iv) luminal instillation of H(2)O(2). Particle translocation to the perfusate was assessed by the radioactivity of (192)Ir isotope. Lung permeability by the use of Tc(99m)-labeled diethylene triamine pentaacetic acid (DTPA). In addition to light microscopic morphological evaluation of fixed lungs, alkaline phosphatase (AKP) and angiotensin converting enzyme (ACE) in perfusate were measured to assess epithelial and endothelial integrity. RESULTS: Particle distribution in the lung was homogenous and similar to in vivo conditions. No translocation of Ir particles at negative pressure inhalation was detected in control IPL, but lungs pretreated with histamine (1 μM) in the perfusate or with luminal H(2)O(2 )(0.5 mM) showed small amounts of radioactivity (2–3 % dose) in the single pass perfusate starting at 60 min of perfusion. Although the kinetics of particle translocation were different from permeability for (99m)Tc-DTPA, the pretreatments (H(2)O(2), vascular histamine) caused similar changes in the translocation of particles and soluble mediator. Increased translocation through epithelium and endothelium with a lag time of one hour occurred in the absence of epithelial and endothelial damage. CONCLUSION: Permeability of the lung barrier to UFP or nanoparticles is controlled both at the epithelial and endothelial level. Conditions that affect this barrier function such as inflammation may affect translocation of NP

Echocardiography findings in COVID-19 patients admitted to intensive care units: a multi-national observational study (the ECHO-COVID study)

Purpose: Severely ill patients affected by coronavirus disease 2019 (COVID-19) develop circulatory failure. We aimed to report patterns of left and right ventricular dysfunction in the first echocardiography following admission to intensive care unit (ICU). Methods: Retrospective, descriptive study that collected echocardiographic and clinical information from severely ill COVID-19 patients admitted to 14 ICUs in 8 countries. Patients admitted to ICU who received at least one echocardiography between 1st February 2020 and 30th June 2021 were included. Clinical and echocardiographic data were uploaded using a secured web-based electronic database (REDCap). Results: Six hundred and seventy-seven patients were included and the first echo was performed 2 [1, 4] days after ICU admission. The median age was 65 [56, 73] years, and 71% were male. Left ventricle (LV) and/or right ventricle (RV) systolic dysfunction were found in 234 (34.5%) patients. 149 (22%) patients had LV systolic dysfunction (with or without RV dysfunction) without LV dilatation and no elevation in filling pressure. 152 (22.5%) had RV systolic dysfunction. In 517 patients with information on both paradoxical septal motion and quantitative RV size, 90 (17.4%) had acute cor pulmonale (ACP). ACP was associated with mechanical ventilation (OR > 4), pulmonary embolism (OR > 5) and increased PaCO2. Exploratory analyses showed that patients with ACP and older age were more likely to die in hospital (including ICU). Conclusion: Almost one-third of this cohort of critically ill COVID-19 patients exhibited abnormal LV and/or RV systolic function in their first echocardiography assessment. While LV systolic dysfunction appears similar to septic cardiomyopathy, RV systolic dysfunction was related to pressure overload due to positive pressure ventilation, hypercapnia and pulmonary embolism. ACP and age seemed to be associated with mortality in this cohort

Radio-diagnosis of fecoliths and its non-surgical management in dogs

Two cases with a history of cessation of feces for 2 weeks, depression, lethargy and anorexia in two different dogs; a Labrador male and a Doberman female, were presented. On physical examination, abdominal distension along with intense pain was observed. Blood samples were collected from the dogs for hematological and biochemical analyses. The examination revealed an increased percentage of packed cell volume (PCV). By radiological examination, radiopaque material was seen in the large intestinal tract. The condition was suggestive of fecolith. The cases were managed by means of non-surgical management. Through an 11-day long medicinal treatment, the dogs recovered uneventfully. Keywords: Case report, dog, fecolith, non-surgical management

A survey on the management of new onset atrial fibrillation in critically ill patients with septic shock

International audienc