COVID-19: Current Challenges and Future Perspectives.

[Extract] This article belongs to the Special Issue COVID-19: Current Challenges and Future Perspectives. At the time of submission for publication (7 January 2022), COVID-19, named by the World Health Organization (WHO) on 11 February 2020, had caused more than 296.5 million cases and over 5.5 million deaths with over 2.6 million new cases in the past 24 h [2]. The COVID-19 pandemic has greatly affected the capacity of health systems providing essential health care [1], but more than 9.195 billion vaccine doses have been administered as of 10 January 2021 [2]

COVID19: Current Challenges and Future Perspectives

This Special Issue focuses on recent global research on the current coronavirus (COVID-19) pandemic. The disease is caused by a novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The International Committee on Taxonomy of Viruses (ICTV) named the virus SARS-CoV-2, as it is genetically related to the coronavirus responsible for the SARS outbreak of 2003. While related, the two viruses are quite different in their behaviour. At the time of submission for publication (7 January 2022), COVID-19, named by the World Health Organization (WHO) on 11 February 2020, had caused more than 296.5 million cases and over 5.5 million deaths with over 2.6 million new cases in the past 24 h. The COVID-19 pandemic has greatly affected the capacity of health systems providing essential health care, but more than 9.195 billion vaccine doses have been administered as of 10 January 2021. There have been 22 papers published upon peer review acceptance in this Special Issue, including one editorial, twelve research papers, three review papers and seven other papers, including one perspective, two case reports, one brief report, two viewpoints and one commentary. They each contribute to a much better understanding of COVID-19

Rabies: an evidence-based approach to management

Human rabies in South Africa is largely due to infection with the classical rabies virus (genotype 1), with the yellow mongoose the commonest vector except in KwaZulu-Natal, Eastern Cape, Mpumalanga and now Limpopo provinces where the dog is predominantly responsible for most bites. Rabies is always fatal in humans but can be prevented by timeous administration of post exposure prophylaxis( PEP). This article discusses an evidence-based approach to rabies management in South Africa. South African Family Practice Vol. 49 (7) 2007: pp. 35-4

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems

Dissecting magnetar variability with Bayesian hierarchical models

Neutron stars are a prime laboratory for testing physical processes under conditions of strong gravity, high density, and extreme magnetic fields. Among the zoo of neutron star phenomena, magnetars stand out for their bursting behaviour, ranging from extremely bright, rare giant flares to numerous, less energetic recurrent bursts. The exact trigger and emission mechanisms for these bursts are not known; favoured models involve either a crust fracture and subsequent energy release into the magnetosphere, or explosive reconnection of magnetic field lines. In the absence of a predictive model, understanding the physical processes responsible for magnetar burst variability is difficult. Here, we develop an empirical model that decomposes magnetar bursts into a superposition of small spike-like features with a simple functional form, where the number of model components is itself part of the inference problem. The cascades of spikes that we model might be formed by avalanches of reconnection, or crust rupture aftershocks. Using Markov Chain Monte Carlo (MCMC) sampling augmented with reversible jumps between models with different numbers of parameters, we characterise the posterior distributions of the model parameters and the number of components per burst. We relate these model parameters to physical quantities in the system, and show for the first time that the variability within a burst does not conform to predictions from ideas of self-organised criticality. We also examine how well the properties of the spikes fit the predictions of simplified cascade models for the different trigger mechanisms.Comment: accepted for publication in The Astrophysical Journal; code available at https://bitbucket.org/dhuppenkothen/magnetron, data products at http://figshare.com/articles/SGR_J1550_5418_magnetron_data/129242

Pseudorehearsal in value function approximation

Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters

Reliable enumeration of malaria parasites in thick blood films using digital image analysis

<p>Abstract</p> <p>Background</p> <p>Quantitation of malaria parasite density is an important component of laboratory diagnosis of malaria. Microscopy of Giemsa-stained thick blood films is the conventional method for parasite enumeration. Accurate and reproducible parasite counts are difficult to achieve, because of inherent technical limitations and human inconsistency. Inaccurate parasite density estimation may have adverse clinical and therapeutic implications for patients, and for endpoints of clinical trials of anti-malarial vaccines or drugs. Digital image analysis provides an opportunity to improve performance of parasite density quantitation.</p> <p>Methods</p> <p>Accurate manual parasite counts were done on 497 images of a range of thick blood films with varying densities of malaria parasites, to establish a uniformly reliable standard against which to assess the digital technique. By utilizing descriptive statistical parameters of parasite size frequency distributions, particle counting algorithms of the digital image analysis programme were semi-automatically adapted to variations in parasite size, shape and staining characteristics, to produce optimum signal/noise ratios.</p> <p>Results</p> <p>A reliable counting process was developed that requires no operator decisions that might bias the outcome. Digital counts were highly correlated with manual counts for medium to high parasite densities, and slightly less well correlated with conventional counts. At low densities (fewer than 6 parasites per analysed image) signal/noise ratios were compromised and correlation between digital and manual counts was poor. Conventional counts were consistently lower than both digital and manual counts.</p> <p>Conclusion</p> <p>Using open-access software and avoiding custom programming or any special operator intervention, accurate digital counts were obtained, particularly at high parasite densities that are difficult to count conventionally. The technique is potentially useful for laboratories that routinely perform malaria parasite enumeration. The requirements of a digital microscope camera, personal computer and good quality staining of slides are potentially reasonably easy to meet.</p

First report of clinical presentation of a bite by a running spider, Philodromus sp. (Araneae: Philodromidae), with recommendations for spider bite management

This article describes the clinical progression of symptoms over a period of 5 days of a bite inflicted by a Philodromus sp. spider. Commonly known as ‘running spiders’, these are not considered to be harmful to humans. This report, however, is the first description of an actual bite by a member of this group of spiders showing cytotoxic envenomation. Management of the bites should be as recommended for other cytotoxic spider bites.http://www.samj.org.zaam2017Zoology and Entomolog