A DATA DRIVEN APPROACH TO IDENTIFY JOURNALISTIC 5WS FROM TEXT DOCUMENTS

Textual understanding is the process of automatically extracting accurate high-quality information from text. The amount of textual data available from different sources such as news, blogs and social media is growing exponentially. These data encode significant latent information which if extracted accurately can be valuable in a variety of applications such as medical report analyses, news understanding and societal studies. Natural language processing techniques are often employed to develop customized algorithms to extract such latent information from text. Journalistic 5Ws refer to the basic information in news articles that describes an event and include where, when, who, what and why. Extracting them accurately may facilitate better understanding of many social processes including social unrest, human rights violations, propaganda spread, and population migration. Furthermore, the 5Ws information can be combined with socio-economic and demographic data to analyze state and trajectory of these processes. In this thesis, a data driven pipeline has been developed to extract the 5Ws from text using syntactic and semantic cues in the text. First, a classifier is developed to identify articles specifically related to social unrest. The classifier has been trained with a dataset of over 80K news articles. We then use NLP algorithms to generate a set of candidates for the 5Ws. Then, a series of algorithms to extract the 5Ws are developed. These algorithms based on heuristics leverage specific words and parts-of-speech customized for individual Ws to compute their scores. The heuristics are based on the syntactic structure of the document as well as syntactic and semantic representations of individual words and sentences. These scores are then combined and ranked to obtain the best answers to Journalistic 5Ws. The classification accuracy of the algorithms is validated using a manually annotated dataset of news articles

Detecting Deceptive Dark-Pattern Web Advertisements for Blind Screen-Reader Users

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users\u27 experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via a blanket filtering operation, many websites are increasingly denying access if an ad blocker is active. Moreover, ad blockers often do not filter out internal ads injected by the websites themselves. Therefore, we devised an algorithm to automatically identify contextually deceptive ads on a web page. Specifically, we built a detection model that leverages a multi-modal combination of handcrafted and automatically extracted features to determine if a particular ad is contextually deceptive. Evaluations of the model on a representative test dataset and \u27in-the-wild\u27 random websites yielded F1 scores of 0.86 and 0.88, respectively

Enabling Customization of Discussion Forums for Blind Users

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions of the conversations. As an initial step towards addressing these usability concerns, we designed PView - a browser extension that enables blind users to customize the content of forum threads in real time as they interact with these threads. Specifically, PView allows the blind users to explicitly hide any post that is irrelevant to them, and then PView automatically detects and filters out all subsequent posts that are substantially similar to the hidden post in real time, before the users navigate to those portions of the thread. In a user study with blind participants, we observed that compared to the status quo, PView significantly improved the usability, workload, and satisfaction of the participants while interacting with the forums

AutoDesc: Facilitating Convenient Perusal of Web Data Items for Blind Users

Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a ‘Query-Results’ page showing the summaries of the items, and ‘Details’ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in this regard as they predominantly focus on enabling efficient content access within a single webpage, and as such are not tailored for content distributed across multiple webpages. As an initial step towards addressing this issue, we developed AutoDesc, a browser extension that leverages a custom extraction model to automatically detect and pull out additional item descriptions from the ‘details’ pages, and then proactively inject the extracted information into the ‘Query-Results’ page, thereby reducing the amount of back-and-forth screen reader navigation between the two webpages. In a study with 16 blind users, we observed that within the same time duration, the participants were able to peruse significantly more data items on average with AutoDesc, compared to that with their preferred screen readers as well as with a state-of-the-art solution

ESTIMATION OF PHYTOCHEMICALS SCREENING AND SUN PROTECTION FACTOR (SPF) NUMBER IN COMMONLY USED ETHANOLIC FRUIT EXTRACTS

The aim of the present study is phytochemical screening and the ultraviolet absorption properties of ethanolic herbal extracts of some commonly used vegetable sources by determining the sun protection factor (spf) number. The invitro SPF number is determined according to the spectrophotomertic method described by Mansur et.al.,. Ethanolic herbal extracts were prepared and after dilution with alcoholic solutions the absorbance were recorded between 290-320 using uv-vis spectrophotometry. It was observed that all of the ethanolic herbal extract showed some UV protection capability. keywords :sun protection factor, spectrophotomertic , ethanolic extrac

Protocol for developing a core outcome set for male infertility research:an international consensus development study

Abstract STUDY QUESTION We aim to develop, disseminate and implement a minimum data set, known as a core outcome set, for future male infertility research. WHAT IS KNOWN ALREADY Research into male infertility can be challenging to design, conduct and report. Evidence from randomized trials can be difficult to interpret and of limited ability to inform clinical practice for numerous reasons. These may include complex issues, such as variation in outcome measures and outcome reporting bias, as well as failure to consider the perspectives of men and their partners with lived experience of fertility problems. Previously, the Core Outcome Measure for Infertility Trials (COMMIT) initiative, an international consortium of researchers, healthcare professionals and people with fertility problems, has developed a core outcome set for general infertility research. Now, a bespoke core outcome set for male infertility is required to address the unique challenges pertinent to male infertility research. STUDY DESIGN, SIZE, DURATION Stakeholders, including healthcare professionals, allied healthcare professionals, scientists, researchers and people with fertility problems, will be invited to participate. Formal consensus science methods will be used, including the modified Delphi method, modified Nominal Group Technique and the National Institutes of Health’s consensus development conference. PARTICIPANTS/MATERIALS, SETTING, METHODS An international steering group, including the relevant stakeholders outlined above, has been established to guide the development of this core outcome set. Possible core outcomes will be identified by undertaking a systematic review of randomized controlled trials evaluating potential treatments for male factor infertility. These outcomes will be entered into a modified Delphi method. Repeated reflection and re-scoring should promote convergence towards consensus outcomes, which will be prioritized during a consensus development meeting to identify a final core outcome set. We will establish standardized definitions and recommend high-quality measurement instruments for individual core outcomes. STUDY FUNDING/COMPETING INTEREST(S) This work has been supported by the Urology Foundation small project award, 2021. C.L.R.B. is the recipient of a BMGF grant and received consultancy fees from Exscentia and Exceed sperm testing, paid to the University of Dundee and speaking fees or honoraria paid personally by Ferring, Copper Surgical and RBMO. S.B. received royalties from Cambridge University Press, Speaker honoraria for Obstetrical and Gynaecological Society of Singapore, Merk SMART Masterclass and Merk FERRING Forum, paid to the University of Aberdeen. Payment for leadership roles within NHS Grampian, previously paid to self, now paid to University of Aberdeen. An Honorarium is received as Editor in Chief of Human Reproduction Open. M.L.E. is an advisor to the companies Hannah and Ro. B.W.M. received an investigator grant from the NHMRC, No: GNT1176437 is a paid consultant for ObsEva and has received research funding from Ferring and Merck. R.R.H. received royalties from Elsevier for a book, consultancy fees from Glyciome, and presentation fees from GryNumber Health and Aytu Bioscience. Aytu Bioscience also funded MiOXYS systems and sensors. Attendance at Fertility 2020 and Roadshow South Africa by Ralf Henkel was funded by LogixX Pharma Ltd. R.R.H. is also Editor in Chief of Andrologia and has been an employee of LogixX Pharma Ltd. since 2020. M.S.K. is an associate editor with Human Reproduction Open. K.Mc.E. received an honoraria for lectures from Bayer and Pharmasure in 2019 and payment for an ESHRE grant review in 2019. His attendance at ESHRE 2019 and AUA 2019 was sponsored by Pharmasure and Bayer, respectively. The remaining authors declare no competing interests. TRIAL REGISTRATION NUMBER Core Outcome Measures in Effectiveness Trials (COMET) initiative registration No: 1586. Available at www.comet-initiative.org/Studies/Details/1586. TRIAL REGISTRATION DATE N/A. DATE OF FIRST PATIENT’S ENROLMENT N/A

New Multiscale Characterization Methodology for Effective Determination of Isolation-Structure-Function Relationship of Extracellular Vesicles

Extracellular vesicles (EVs) have been lauded as next-generation medicines, but very few EV-based therapeutics have progressed to clinical use. Limited clinical translation is largely due to technical barriers that hamper our ability to mass produce EVs, i.e., to isolate, purify, and characterize them effectively. Technical limitations in comprehensive characterization of EVs lead to unpredicted biological effects of EVs. Here, using a range of optical and non-optical techniques, we showed that the differences in molecular composition of EVs isolated using two isolation methods correlated with the differences in their biological function. Our results demonstrated that the isolation method determines the composition of isolated EVs at single and sub-population levels. Besides the composition, we measured for the first time the dry mass and predicted sedimentation of EVs. These parameters were likely to contribute to the biological and functional effects of EVs on single cell and cell cultures. We anticipate that our new multiscale characterization approach, which goes beyond traditional experimental methodology, will support fundamental understanding of EVs as well as elucidate the functional effects of EVs in in vitro and in vivo studies. Our findings and methodology will be pivotal for developing optimal isolation methods and establishing EVs as mainstream therapeutics and diagnostics. This innovative approach is applicable to a wide range of sectors including biopharma and biotechnology as well as to regulatory agencies

A DATA DRIVEN APPROACH TO IDENTIFY JOURNALISTIC 5WS FROM TEXT DOCUMENTS

Textual understanding is the process of automatically extracting accurate high-quality information from text. The amount of textual data available from different sources such as news, blogs and social media is growing exponentially. These data encode significant latent information which if extracted accurately can be valuable in a variety of applications such as medical report analyses, news understanding and societal studies. Natural language processing techniques are often employed to develop customized algorithms to extract such latent information from text. Journalistic 5Ws refer to the basic information in news articles that describes an event and include where, when, who, what and why. Extracting them accurately may facilitate better understanding of many social processes including social unrest, human rights violations, propaganda spread, and population migration. Furthermore, the 5Ws information can be combined with socio-economic and demographic data to analyze state and trajectory of these processes. In this thesis, a data driven pipeline has been developed to extract the 5Ws from text using syntactic and semantic cues in the text. First, a classifier is developed to identify articles specifically related to social unrest. The classifier has been trained with a dataset of over 80K news articles. We then use NLP algorithms to generate a set of candidates for the 5Ws. Then, a series of algorithms to extract the 5Ws are developed. These algorithms based on heuristics leverage specific words and parts-of-speech customized for individual Ws to compute their scores. The heuristics are based on the syntactic structure of the document as well as syntactic and semantic representations of individual words and sentences. These scores are then combined and ranked to obtain the best answers to Journalistic 5Ws. The classification accuracy of the algorithms is validated using a manually annotated dataset of news articles

Assistive Technologies for People with Visual Impairments

Zoom recording of a workshop presented for Global Accessibility Awareness Day 2023. Run Time: 01:25:4