Learning to Address Health Inequality in the United States with a Bayesian Decision Network

Life-expectancy is a complex outcome driven by genetic, socio-demographic, environmental and geographic factors. Increasing socio-economic and health disparities in the United States are propagating the longevity-gap, making it a cause for concern. Earlier studies have probed individual factors but an integrated picture to reveal quantifiable actions has been missing. There is a growing concern about a further widening of healthcare inequality caused by Artificial Intelligence (AI) due to differential access to AI-driven services. Hence, it is imperative to explore and exploit the potential of AI for illuminating biases and enabling transparent policy decisions for positive social and health impact. In this work, we reveal actionable interventions for decreasing the longevity-gap in the United States by analyzing a County-level data resource containing healthcare, socio-economic, behavioral, education and demographic features. We learn an ensemble-averaged structure, draw inferences using the joint probability distribution and extend it to a Bayesian Decision Network for identifying policy actions. We draw quantitative estimates for the impact of diversity, preventive-care quality and stable-families within the unified framework of our decision network. Finally, we make this analysis and dashboard available as an interactive web-application for enabling users and policy-makers to validate our reported findings and to explore the impact of ones beyond reported in this work.Comment: 8 pages, 4 figures, 1 table (excluding the supplementary material), accepted for publication in AAAI 201

Inter Process Communication and Prioritization to Enable Desktop Advertisement Mechanism

This research paper tries to bring in a new concept of desktop advertising mechanism by synchronization it with the running processes and the data on users’ side. The proposed approach shall be based on inter process communication interaction, scheduling, prioritization, desktop crawling and system calls. The running process status and data will be fetched by the proposed process, which will then seek relevant information with the remote ad server and display the advertisements fetched based on keywords on user side

A Review: Herbal Remedies Used For The Treatment of Mouth Ulcer

The mouth ulcer often caused pain and discomfort and may alter the person choice of food while healing occurs. The two most common oral  ulceration are Local trauma and Aphthous stomatitis. This review focuses on the causes of mouth ulcer, factors responsible for the mouth ulcer. As we know herbal medicine is the main stay of primary healthcare because of better culture acceptability, better compatability with human body and lesser side effects. This review summarises about the drugs used for the treatment of mouth ulcer which are Aloe vera, Guava, Capsicum annum, Papaya, Glycyrrhiza glabra, Turmeric, Noni fruit along with their Biological source, Family, Morphology, Chemical constituents and Uses

Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media

Claim span identification (CSI) is an important step in fact-checking pipelines, aiming to identify text segments that contain a checkworthy claim or assertion in a social media post. Despite its importance to journalists and human fact-checkers, it remains a severely understudied problem, and the scarce research on this topic so far has only focused on English. Here we aim to bridge this gap by creating a novel dataset, X-CLAIM, consisting of 7K real-world claims collected from numerous social media platforms in five Indian languages and English. We report strong baselines with state-of-the-art encoder-only language models (e.g., XLM-R) and we demonstrate the benefits of training on multiple languages over alternative cross-lingual transfer methods such as zero-shot transfer, or training on translated data, from a high-resource language such as English. We evaluate generative large language models from the GPT series using prompting methods on the X-CLAIM dataset and we find that they underperform the smaller encoder-only language models for low-resource languages.Comment: EMNLP 2023 (main

mOKB6: A Multilingual Open Knowledge Base Completion Benchmark

Automated completion of open knowledge bases (Open KBs), which are constructed from triples of the form (subject phrase, relation phrase, object phrase), obtained via open information extraction (Open IE) system, are useful for discovering novel facts that may not be directly present in the text. However, research in Open KB completion (Open KBC) has so far been limited to resource-rich languages like English. Using the latest advances in multilingual Open IE, we construct the first multilingual Open KBC dataset, called mOKB6, containing facts from Wikipedia in six languages (including English). Improving the previous Open KB construction pipeline by doing multilingual coreference resolution and keeping only entity-linked triples, we create a dense Open KB. We experiment with several models for the task and observe a consistent benefit of combining languages with the help of shared embedding space as well as translations of facts. We also observe that current multilingual models struggle to remember facts seen in languages of different scripts.Comment: camera-ready version for ACL 202

A cross-sectional study of factors affecting seasonality in bipolar disorder

Background. Researchers have evinced interest in the effect of seasonal variations on mood and behavioural patterns in affective disorders.  Objective. To study seasonality in bipolar disorder (BD) patients and also the factors affecting this seasonality.  Method. Forty-nine patients with BD in euthymic phase were recruited and analysed using the Seasonal Pattern Assessment Questionnaire and Morningness-Eveningness Questionnaire.  Results. Most of the patients were morning types but chronotype had no influence on seasonality. Age of patient and number of episodes were the most important factors affecting seasonality in BD.  Conclusion. Seasonality and its influencing factors must be considered while managing bipolar disorder

Size versus stability in the marriage problem

Given an instance I of the classical Stable Marriage problem with Incomplete preference lists (smi), a maximum cardinality matching can be larger than a stable matching. In many large-scale applications of smi, we seek to match as many agents as possible. This motivates the problem of finding a maximum cardinality matching in I that admits the smallest number of blocking pairs (so is “as stable as possible”). We show that this problem is NP-hard and not approximable within n1−ε, for any ε>0, unless P=NP, where n is the number of men in I. Further, even if all preference lists are of length at most 3, we show that the problem remains NP-hard and not approximable within δ, for some δ>1. By contrast, we give a polynomial-time algorithm for the case where the preference lists of one sex are of length at most 2. We also extend these results to the cases where (i) preference lists may include ties, and (ii) we seek to minimize the number of agents involved in a blocking pair

An Analytical Study of Rumoured Tweets by Using Twitter Data

Earlier when the internet was not there, rumours were spread by word of mouth technique but in this era of technology where we have social networking sites like twitter, rumours can be spread easily and quickly and a situation of panic can arise. Twitter is an American online news and social networking service on which users finds the latest news and world events faster. It is used for communication, interaction withpeople, announcement of event etc. from breaking news to sports, politics and everyday interests, one can find this service very addictive and an easy way to gather information about a certain event. Businesses can also use it to build their own brands and for marketing. But the founders of twitter like jack Dorsey forgot one thing that every coin has two sides. While twitter is a great way to interact with the masses, it is also a home of spammers. Spamming is a very common thing on twitter. Spammers create twitter accounts to perform a variety of tasks like posting links with unrelated tweets and the speed at which these fake and malicious misinformation spread on twitter in a real-time emergencies always causing a huge flood of tweets on twitter. In this paper, we demonstrated an analytical study of those rumoured tweets by twitter data. Using some of the rumoured tweets posted during the Chennai flood in 2015 and some non-rumoured tweets, we trained a classifier. The ability to track rumours and predict their outcomes have many applications for journalists, emergency services, and thereforehelp in minimizing the impact of false and fake information on this twitter platform

DESIGN AND PERFORMANCE VERIFICATION OF NEWLY DEVELOPED DISPOSABLE STATIC DIFFUSION CELL FOR DRUG DIFFUSION/PERMEABILITY STUDIES

Objectives: The present study describes a disposable static diffusion cell for in vitro diffusion studies to achieve better results as compared to well existing Franz diffusion cell (FDC) in terms of the absence of bubbles, variable receptor compartment, ease of handling, and faster results.Materials and Methods: The cell consists of a cup-shaped donor compartment made of semi permeable that could be either cellophane membrane or, animal skin fitted to a rigid frame, which is supported on a plastic plate that contains a hole for the sample withdrawal. The receptor compartment is a separate unit, and it could be any container up to 500ml volume capacity. The most preferred receptor compartment is glass beaker. In the present study, goatskin was used as semi-permeable membrane and verification of its performance was carried out through diffusion studies using gel formulations of one each of the four-selected biopharmaceutical classification system (BCS) class drugs. Metronidazole, diclofenac sodium, fluconazole, and sulfadiazine were used as model drugs for BCS Class I, II, III, and IV, respectively.Results: The newly developed diffusion cell (NDDC) was found to provide faster and more reproducible results as compared to FDC. At the time interval of 24 h, the cell was found to exhibit a higher diffusion of metronidazole, diclofenac sodium, fluconazole, and sulfadiazine by 0.65, 0.65, 0.32, and 0.81 folds, respectively. The faster release obtained with NDDC was attributed to a larger surface area of skin as compared to that in FDC.Conclusion: It was concluded that better reproducibility of results could be achieved with NDDC