Background Since the onset of the COVID-19 pandemic, there has been a global effort to develop vaccines that protect against COVID-19. Individuals who are fully vaccinated are far less likely to contract and therefore transmit the virus to others. Researchers have found that the internet and social media both play a role in shaping personal choices about vaccinations. Objective This study aims to determine whether supplementing COVID-19 vaccine uptake forecast models with the attitudes found in tweets improves over baseline models that only use historical vaccination data. Methods Daily COVID-19 vaccination data at the county level was collected for the January 2021 to May 2021 study period. Twitter’s streaming application programming interface was used to collect COVID-19 vaccine tweets during this same period. Several autoregressive integrated moving average models were executed to predict the vaccine uptake rate using only historical data (baseline autoregressive integrated moving average) and individual Twitter-derived features (autoregressive integrated moving average exogenous variable model). Results In this study, we found that supplementing baseline forecast models with both historical vaccination data and COVID-19 vaccine attitudes found in tweets reduced root mean square error by as much as 83%. Conclusions Developing a predictive tool for vaccination uptake in the United States will empower public health researchers and decisionmakers to design targeted vaccination campaigns in hopes of achieving the vaccination threshold required for the United States to reach widespread population protection.
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The COVID-19 pandemic has resulted in schools and universities worldwide shifting from face-to-face learning (F2F) to Online Distance Learning (ODL), and Malaysia is no exception. However, ODL has resulted in many challenges that students and lecturers have had to go through, and teaching English is no exception. This study has three aims; to analyse the student’s perception of learning the English language subjects through online classes, to identify the student’s challenges in learning the English subjects, and to discuss what can be improved, as well as the directions of improvement to make learning the English language subjects through online classes easier and more accessible to all. The ninety-nine respondents in this study are students taking pre-diploma and diploma courses in UiTM Sarawak. The study implements the survey research method whereby questionnaires were distributed to pre-diploma and diploma students during week 13 and week 14 of the March-August 2021 semester via Google Form. The findings were extracted, and results were analysed. The study revealed key differences in students’ perception, challenges, and improvement in making learning English language subjects through online classes easier, bearable, and accessible to all. Implications of the study are also presented and discussed.
Single chain antibodies are used as powerful tool to detect interacting antigen proteins because of their small size, better solubility, strong binding affinity and stability. These small antibodies have access to nonimmunogenic antigenic sites, 1 which otherwise remain buried in the scaffold. In laboratories, single chain antibodies are produced by recombinant antibody technology in which the variable heavy chain (vH) and variable light chains (vL) specific genes are amplified and cloned in a phagemid vector. The nanobodies are expressed on the surface of the phage as fusion proteins and are able to interact with antigen present in its vicinity. The first naturally occurring single chain antibodies were discovered in camel (Camelus dromedarius) and classified as "camelid". 2 These nanobodies naturally lacked the light chains. The heavy chain of the nanobodies contains the antigen binding sites that is referred as vHH (to distinguish it from vH). 3 Until recently, vH antibodies were considered to be the smallest intact antigen-binding fragment (∼15 kilo daltons). 3 Cloning of vHH region from an immunized Llama (Lama glama) in a phagemid vector facilitated the construction of the antibody library and biopanning (screening). The development and screening of these antibodies are used to isolate specific antigen binding clones, which belong to various enzymes including lysozyme, amylase, carbonic anhydrase and lactamase. 4
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