USES OF THE SKEW-LOGISTIC FUNCTION FOR MULTI-WAVE FUNCTIONS

The Skew-Logistic (SL) function has been proposed to model a real-life dynamic process which rises monotonically to a peak followed by a monotonic falling back. It was introduced to model the first stage of the Covid-19 pandemic to forecast its behaviour. Then, with different controls and variants, Covid-19 - rose and fell in what might be called a Multi-Wave (MW) behaviour;with waves not necessarily the same size. This paper shows how using the SL function for one wave can be easily modified to model the MW situation. We apply it to two examples. One is to Covid-19, to examine its most recent behaviour. We also apply it to climate change, the most serious issue of our time. Ensuring that the world simply achieves carbon-equality is not enough. We have to rapidly achieve carbon-negativity to prevent bringing an end to the known world. © SW 2023.All rights reserved

Research progress on photocatalysis systems for inactivation of microbial aerosol

Now in the context of the novel coronavirus pneumonia outbreak, the control and removal of microbial aerosols has once again attracted academic attention, while conventional air purification methods such as filtration, chemical agents and UV have their own defects and deficiencies. With the advantages of high efficiency, wide spectrum, green, no residue, dynamic continuous disinfection, photocatalysis has broad application prospects. In this paper, the research on the inactivation of microbial aerosols with photocatalysis system is summarized and analyzed from the aspects of the types of photocatalysts, the load of photocatalysts, the light source and the structure and operation of reactors. TiO2 or its derivative materials are selected as photocatalysts in most studies, and more novel and efficient photocatalysts should be applied. Porous, multi-channel and large surface area catalyst carriers can effectively improve the efficiency of photocatalysis system. The light source still depends on UV light, and the application of visible light needs more research. There are few studies on improving the photocatalysis system by optimizing the reactor structure, and the most commonly used is the ring reactor. Researchers have developed photocatalytic air purifiers or combined photocatalysis systems with indoor air duct systems. In the future, photocatalysis system will become an important means for indoor microbial aerosol control. © 2023 Chemical Industry Press. All rights reserved.

Modelling presymptomatic infectiousness in COVID-19

This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment model. Both models can be fitted to real data as they include parameters that can be estimated from the data. SEPIR deploys an additional presymptomatic infectious compartment, not modelled in SEIR but known to exist in COVID-19. This stage can also be fitted to data. We focus on how to fit SEPIR to a first wave of COVID. Both SEIR and SEPIR and the existing SEIR models assume a homogeneous mixing population with parameters fixed. Moreover, neither includes dynamically varying control strategies deployed against the virus. If either model is to represent more than just a single wave of the epidemic, then the parameters of the model would have to be time dependent. In view of this, we also show how reproduction numbers can be calculated to investigate the long-term overall outcome of an epidemic. © 2023 The Operational Research Society.

KDV-Explorer: A Near Real-Time Kernel Density Visualization System for Spatial Analysis

Kernel density visualization (KDV) is a commonly used visualization tool for many spatial analysis tasks, including disease outbreak detection, crime hotspot detection, and traffic accident hotspot detection. Although the most popular geographical information systems, e.g., QGIS, and ArcGIS, can also support this operation, these solutions are not scalable to generate a single KDV for datasets with million-scale data points, let alone to support exploratory operations (e.g., zoom in, zoom out, and panning operations) with KDV in near real-time (< 5 sec). In this demonstration, we develop a near real-time visualization system, called KDV-Explorer, that is built on top of our prior study on the efficient kernel density computation. Participants will be invited to conduct some kernel density analysis on three large-scale datasets (up to 1.3 million data points), including the traffic accident dataset, crime dataset and COVID-19 dataset. We will also compare the performance of our solution and the solutions in QGIS and ArcGIS.

Visualizing Hong Kong's mass transit usage under COVID-19

The COVID-19 pandemic hit the world hard. It has induced many abrupt changes, including lockdowns and business closures. Using changes in local public transit usage as proxies of mobility patterns in a typical high-density city where public transit carries >= 90% of passenger trips, this featured graphic geovisualizes to what degree human mobility patterns in Hong Kong were affected by the pandemic and related local and remote events such as the Wuhan lockdown and the Hong Kong government's 'work from home' policy, where the patterns are affected the most, and possibly by/after which event(s). The visuals show that trips to and from business and commercial districts, low- to middle-income new towns, and station areas near the checking point serving cross-border visitors/residents might be most affected.

Modelling pre-symptomatic infectiousness in covid-19

This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment model. Both models can be fitted to real data as they include parameters that can be estimated from the data. SEPIR deploys an additional pre-symptomatic (also called asymptomatic) infectious stage not in SEIR but known to exist in COVID-19. This stage can also be fitted to data. We focus on how to fit SEPIR to a first wave. Both SEPIR and the existing SEIR model assume a homogeneous mixing population with parameters fixed. Moreover neither includes dynamically varying control strategies deployed against the virus. If either model is to represent more than just a single wave of the epidemic, then the parameters of the model would have to be time dependent. In view of this we also consider how reproduction numbers can be calculated to investigate the longer term overall result of an epidemic. © 2021 SW 2021. All rights reserved.

M-Cypher: A GQL Framework Supporting Motifs

Graph databases witness the rise of Graph Query Language (GQL) in recent years, which enables non-programmers to express a graph query. However, the current solution does not support motif-related queries on knowledge graphs, which are proven important in many real-world scenarios. In this paper, we propose a GQL framework for mining knowledge graphs, named M-Cypher. It supports motif-related graph queries in an effective, efficient and user-friendly manner. We demonstrate the usage of the system by the emerging Covid-19 knowledge graph analytic tasks. © 2020 ACM.