Emergency Preparedness for the COVID-19 Pandemic: Social Determinants Predicting the Community Pharmacists’ Preparedness and Perceived Response in Malaysia

Background: Pandemic preparedness of healthcare providers helps to mitigate future threats such as spread and fatality rates, as well as the management of the disease. Pharmacists are key partners with public health agencies, and the role of community pharmacists is becoming increasingly recognised in this COVID-19 pandemic. The study aimed to explore the emergency preparedness of community pharmacists (CPs) for COVID-19. Methods: A cross-sectional study was performed among community pharmacists using cluster sampling followed by convenient sampling. A self-administered questionnaire was formulated using references from the previous literature and the WHO preparedness checklist. Descriptive analysis was undertaken for the participants’ socio-demographic characteristics. All the data collected were entered into the Statistical Package for Social Sciences version 24 (SPSS V.24), (IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM Corp.) for analysis. Results: Most of the CPs had five or fewer years of practice experience, and they had all the mandatory information relating to the needs of their communities regarding the disease. The participants knew where to acquire these resources whenever needed. They were able to recognise the signs and symptoms of the disease. Most participants felt that they were confident to provide patient education and carry out their duties during these challenging times. There was a strong position correlation between preparedness and the perceived response of the participants. Conclusion: The community pharmacists in Malaysia are prepared enough for COVID-19 pandemic management and perceive that they can respond during any unprecedented situations, such as COVID-19. Community pharmacists were aware of the challenges that they need to face in their community regarding COVID-19

GO-NeRF: Generating Virtual Objects in Neural Radiance Fields

Despite advances in 3D generation, the direct creation of 3D objects within an existing 3D scene represented as NeRF remains underexplored. This process requires not only high-quality 3D object generation but also seamless composition of the generated 3D content into the existing NeRF. To this end, we propose a new method, GO-NeRF, capable of utilizing scene context for high-quality and harmonious 3D object generation within an existing NeRF. Our method employs a compositional rendering formulation that allows the generated 3D objects to be seamlessly composited into the scene utilizing learned 3D-aware opacity maps without introducing unintended scene modification. Moreover, we also develop tailored optimization objectives and training strategies to enhance the model's ability to exploit scene context and mitigate artifacts, such as floaters, originating from 3D object generation within a scene. Extensive experiments on both feed-forward and $360^o$ scenes show the superior performance of our proposed GO-NeRF in generating objects harmoniously composited with surrounding scenes and synthesizing high-quality novel view images. Project page at {\url{https://daipengwa.github.io/GO-NeRF/}.Comment: 12 page

The ultra-low-frequency shear modes of 2-4 layer graphenes observed in their scroll structures at edges

The in-plane shear modes between neighbor-layers of 2-4 layer graphenes (LGs) and the corresponding graphene scrolls rolled up by 2-4LGs were investigated by Raman scattering. In contrast to that just one shear mode was observed in 3-4LGs, all the shear modes of 3-4LGs were observed in 3-4 layer scrolls (LSs), whose frequencies agree well with the theoretical predication by both a force-constant model and a linear chain model. In comparison to the broad width (about 12cm$^{-1}$) for the G band in graphite, all the shear modes exhibit an intrinsic line width of about 1.0 cm$^{-1}$. The local electronic structures dependent on the local staking configurations enhance the intensity of the shear modes in corresponding 2-4LSs zones, which makes it possible to observe all the shear modes. It provides a direct evidence that how the band structures of FLGs can be sensitive to local staking configurations. This result can be extended to n layer graphene (n > 4) for the understanding of the basic phonon properties of multi-layer graphenes. This observation of all-scale shear modes can be foreseen in other 2D materials with similar scroll structures.Comment: 14 pages, 5 figure

Will the Relaxation of COVID-19 Control Measures Have an Impact on the Chinese Internet-Using Public? Social Media-Based Topic and Sentiment Analysis

Objective: In December 2022, the Chinese government announced the further optimization of the implementation of the prevention and control measures of COVID-19. We aimed to assess internet-using public expression and sentiment toward COVID-19 in the relaxation of control measures in China.Methods: We used a user-simulation-like web crawler to collect raw data from Sina-Weibo and then processed the raw data, including the removal of punctuation, stop words, and text segmentation. After performing the above processes, we analyzed the data in two aspects. Firstly, we used the Latent Dirichlet Allocation (LDA) model to analyze the text data and extract the theme. After that, we used sentiment analysis to reveal the sentiment trend and the geographical spatial sentiment distribution.Results: A total of five topics were extracted according to the LDA model, namely, Complete liberalization, Resource supply, Symptom, Knowledge, and Emotional Outlet. Furthermore, sentiment analysis indicates that while the percentages of positive and negative microblogs fluctuate over time, the overall quantity of positive microblogs exceeds that of negative ones. Meanwhile, the geographical dispersion of public sentiment on internet usage exhibits significant regional variations and is subject to multifarious factors such as economic conditions and demographic characteristics.Conclusion: In the face of the relaxation of COVID-19 control measures, although concerns arise among people, they continue to encourage and support each other

A Theory and Monte Carlo Calculation on Low Energy Electron Scattering in Solids

Low energy electron scattering (LEES) courses in solids are described by using a strict theory and direct simulation method proposed in this paper: we have improved Pendry\u27s method based on the partial wave expansion, which can be applied to calculate the elastic scattering between an electron and atoms. The contributions of shell electrons, conductive electrons and plasma excitations are considered in the calculation of the inelastic scattering; electron scattering and cascade process of secondary electrons are simulated by Monte Carlo method. The secondary electron yields, the energy spectra curve and the backscattering electron coefficients for Cu were evaluated at the various energies, the theoretical results are in agreement with the Koshikawa\u27s experiments