Reflections on the Concomitants of the Restrictive Visitation Policy During the COVID-19 Pandemic: An Ubuntu Perspective

Caregiving is a prominent concept in the Ubuntu philosophy, and caring and visitation of the sick is regarded as an example of Ubuntu. The restrictive visitation policy adopted in the hospitals during the coronavirus disease 2019 (COVID-19) pandemic affected the exhibition of this concept among patients, nurses, and families. The narrative inquiry was used to explore the reflections of the participants on the impact caused by the non-visitation policy experienced during the first and second waves of the COVID-19 pandemic in South Africa. The narrative inquiry approach allowed the participants to tell their story as it is unique to them. The study used purposive sampling technique to select five participants for the webinar. Three themes emerged from the narrated stories which are 1) moral anguish of the caregivers; 2) mental health instability, and 3) erosion of trust in health care practitioners (HCPs). The non-visitation hospital policy was intended to reduce the danger of spreading COVID-19 within and outside the hospital; however, the care provided was devoid of the values of Ubuntu such as mutual respect, relational, responsibility, reciprocity, and interconnectedness. In retrospect, a case-by-case application of the policy would reduce the non-desirable effect of the policy on the patients, nurses, and patients' family members.

Comparison of Riverbed Changes between Sediment Budget Analysis with Measured Data and River Survey: Case Application to Part of Geumgang

Sediment measurement data are utilized as basic data for various river plans and research. The aim of this study is to compare between sediment budget analysis and riverbed monitoring results. The spatial range was from the Gongju-si (Gemganggyo) station to the Buyeo-gun (Baekjegyo) station in Geumgang, and the temporal range in this study was from 2011 to 2016. The estimated change in riverbed amount using the sediment budget analysis was 2,430,243 tons for sediments loaded over six years in the section. The analyzed riverbed changes sedimentation using the riverbed monitoring method were 2,165,146 tons based on the low level and 3,055,489 tons based on the flood level. Based on the riverbed monitoring performance, the relative errors in the sediment budget analysis results through sediment measurements were 10.9% and -25.7% for the low water and flood levels, respectively.

Sampling CASE Application for the Quality Control of Published Natural Product Structures

Structure elucidation with NMR correlation data is dicey, as there is no way to tell how ambiguous the data set is and how reliably it will define a constitution. Many different software tools for computer assisted structure elucidation (CASE) have become available over the past decades, all of which could ensure a better quality of the elucidation process, but their use is still not common. Since 2011, WebCocon has integrated the possibility to generate theoretical NMR correlation data, starting from an existing structural proposal, allowing this theoretical data then to be used for CASE. Now, WebCocon can also read the recently presented NMReDATA format, allowing for uncomplicated access to CASE with experimental data. With these capabilities, WebCocon presents itself as an easily accessible Web-Tool for the quality control of proposed new natural products. Results of this application to several molecules from literature are shown and demonstrate how CASE can contribute to improve the reliability of Structure elucidation with NMR correlation data.

Hybrid Method for Simulation of a Fractional COVID-19 Model with Real Case Application

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9 April to 2 June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders.

Mapping Compound Databases to Disease Maps—A MINERVA Plugin for CandActBase

The MINERVA platform is currently the most widely used platform for visualizing and providing access to disease maps. Disease maps are systems biological maps of molecular interactions relevant in a certain disease context, where they can be used to support drug discovery. For this purpose, we extended MINERVA’s own drug and chemical search using the MINERVA plugin starter kit. We developed a plugin to provide a linkage between disease maps in MINERVA and application-specific databases of candidate therapeutics. The plugin has three main functionalities; one shows all the targets of all the compounds in the database, the second is a compound-based search to highlight targets of specific compounds, and the third can be used to find compounds that affect a certain target. As a use case, we applied the plugin to link a disease map and compound database we previously established in the context of cystic fibrosis and, herein, point out possible issues and difficulties. The plugin is publicly available on GitLab; the use-case application to cystic fibrosis, connecting disease maps and the compound database CandActCFTR, is available online.