Establishing a telemedicine program for interventional radiology: a study of patient opinion and experience

PURPOSEThe COVID-19 pandemic forced healthcare officials to implement new policies, such as the use of virtual consultations over office-based medical appointments, to reduce the transmission of the virus. The purpose of this study is to quantitatively compare patients’ experiences with virtual outpatient telemedicine encounters at a single academic institution in Interventional Radiology (IR) and in-person visits during the course of the COVID-19 pandemic. METHODSThe TeleENT Satisfaction Questionnaire and the Medical Communication Competence Scale (MCCS) were used to survey patients’ satisfaction with both in-person and virtual office visits. RESULTSNinety respondents (38 in-person, 52 virtual) acknowledged numerous benefits of virtual visits versus in-person office visits including reductions in time, cost, and potential viral transmission risk during the COVID-19 pandemic. No statistically significant difference was noted, based on a Likert scale from 1 to 7, between in-person and virtual visits (all p > 0.05) for scheduling related factors. No statistically significant difference was noted in any of the MCCS subscales between the two cohorts in regards to medical information communication (all p > 0.05). A majority of patients with virtual encounters (82.7%) stated that it was easy to obtain an electronic device for use during the telemedicine visit, and 73.1% of patients felt that setting up the telemedicine encounter was easy.CONCLUSIONThis study demonstrates that telemedicine is an acceptable alternative to in-office appointments and could increase access to IR care outside of the traditional physician-patient interaction. With telemedicine visits, patients can communicate their concerns and obtain information from the doctor with noninferior communication compared to in-person visits

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Dezinformace a Projekt Pegasus: Případová studie Indie

This thesis analyses the mainstream media's reporting around Pegasus spyware in India and the subsequent formation of revisionist networks showing solidarity with news circulated by mainstream media on social media. This research on news media coverage of misinformation spread around Project Pegasus in India classifies and clusters misinformation supplied by the mainstream media through their reporting. Next, the thesis explores the emergence of revisionist social media networks from such coverage as a response to the call to action in the mass media. The case study method allows the author to offer focused insights into the misinformed mass media's coverage of the issue. K means clustering is used to identify different narratives in the news report dataset, followed by text mining using Voyant Tools to summarise the narratives. Social Media Analysis is done to identify and bring forth the revisionist hashtags deployed by the mainstream media to further their narrative. The findings of the project highlight that considerable parts of the population are aware of notable misinformation around Pegasus spyware. However, this understanding did not translate into the call for action by the media houses across social media (Twitter). The weak correlation between Indian media reports and social media...Department of Security StudiesKatedra bezpečnostních studiíFaculty of Social SciencesFakulta sociálních vě

Misinformation & Pegasus Project: Case study of India

This thesis analyses the mainstream media's reporting around Pegasus spyware in India and the subsequent formation of revisionist networks showing solidarity with news circulated by mainstream media on social media. This research on news media coverage of misinformation spread around Project Pegasus in India classifies and clusters misinformation supplied by the mainstream media through their reporting. Next, the thesis explores the emergence of revisionist social media networks from such coverage as a response to the call to action in the mass media. The case study method allows the author to offer focused insights into the misinformed mass media's coverage of the issue. K means clustering is used to identify different narratives in the news report dataset, followed by text mining using Voyant Tools to summarise the narratives. Social Media Analysis is done to identify and bring forth the revisionist hashtags deployed by the mainstream media to further their narrative. The findings of the project highlight that considerable parts of the population are aware of notable misinformation around Pegasus spyware. However, this understanding did not translate into the call for action by the media houses across social media (Twitter). The weak correlation between Indian media reports and social media..

Stability analysis of Al2O3/water nanofluids

This paper presents the stability analysis of Al2O3/water nanofluid. The stability is investigated with the help of zeta potential and visual inspection methods. The effects of pH and sonication time for the stability of nanofluids are studied in detail. The visual inspection method is used to calculate the stability period of nanofluids. The zeta potential is directly related to stability period of nanofluids; higher the absolute value of zeta potential, higher the stability period. The stability is also analysed by using sodium dodecyl sulphate, a surfactant, with respect to the time elapsed after the preparation of nanofluids

Egalitarian Transient Service Composition in Crowdsourced IoT Environment

The Crowdsourced IoT Service (CIS) market is inherently different from other service markets, e.g., web services and cloud. The CIS market is dominated by transient services as both consumers and providers are dynamic in space and time. Consumer requests are usually long-term and demand continuity in service provision. We propose a novel egalitarian transient service composition framework from the CIS market perspective. We apply a Dynamic Bayesian Network to model the dynamic service provision behavior of the providers. The proposed framework transforms the composition of transient services into a multi-objective temporal optimization, i.e., providing continuous services to the maximum number of consumers, and minimizing the consumers\u27 cost of service usages over a long-term period. We incorporate a Pareto-based genetic algorithm to enable the fair distribution of services among the consumers. Experimental results prove the efficiency of the proposed approach in terms of continuous availability of service as well as fair distribution among consumers

An Optimization Ontology for Goal Modelling Frameworks

Enterprises are driven by specific business objectives which should be delivered in the best possible manner within constrained business environments. In this paper, we propose a new ontology for goal modeling frameworks that enables enterprises to formally capture the business objectives and constraints associated with business goals as an optimization problem. We associate optimization problems with goals in such a manner that the solutions to the problems at the lower levels of the goal decomposition tree can be combined to obtain the solution for goals higher up in the tree. As a proof-of-concept, we have developed a web-based supply chain configuration management tool, deployed over the Ethereum blockchain, that relies on the Google OR-tools API to find optimal solutions. The interface allows the user to specify business objectives and constraints and then provides the best possible supply chain configuration that optimizes the business objectives

Inhibiting Extracellular Cathepsin D Reduces Hepatic Steatosis in Sprague–Dawley Rats ^†

Dietary and lifestyle changes are leading to an increased occurrence of non-alcoholic fatty liver disease (NAFLD). Using a hyperlipidemic murine model for non-alcoholic steatohepatitis (NASH), we have previously demonstrated that the lysosomal protease cathepsin D (CTSD) is involved with lipid dysregulation and inflammation. However, despite identifying CTSD as a major player in NAFLD pathogenesis, the specific role of extracellular CTSD in NAFLD has not yet been investigated. Given that inhibition of intracellular CTSD is highly unfavorable due to its fundamental physiological function, we here investigated the impact of a highly specific and potent small-molecule inhibitor of extracellular CTSD (CTD-002) in the context of NAFLD. Treatment of bone marrow-derived macrophages with CTD-002, and incubation of hepatic HepG2 cells with a conditioned medium derived from CTD-002-treated macrophages, resulted in reduced levels of inflammation and improved cholesterol metabolism. Treatment with CTD-002 improved hepatic steatosis in high fat diet-fed rats. Additionally, plasma levels of insulin and hepatic transaminases were significantly reduced upon CTD-002 administration. Collectively, our findings demonstrate for the first time that modulation of extracellular CTSD can serve as a novel therapeutic modality for NAFLD