Woodwardsloth3730

nd better advising patients with TSFs on severity of injuries.

TSFs after MVCs, mechanical falls, falls from height, and MCCs presented with a predictable pattern of injuries and were rarely an isolated injury. This cross-sectional data may help spine and trauma surgeons better understand patterns of injury associated with TSFs, with the hope of preventing missed injuries and better advising patients with TSFs on severity of injuries.The relevant dynamics underlying COVID-19 waves is described from an amplitude space perspective. To this end, the amplitude dynamics of infected populations is considered in different stages of epidemic waves. Eigenvectors and their corresponding amplitudes are derived analytically for low-dimensional models and by means of computational methods for high-dimensional models. It is shown that the amplitudes of all eigenvectors as functions of time can be tracked through the diverse stages of COVID-19 waves featuring jumps at the stage boundaries. In particular, it is shown that under certain circumstances the initial, outbreak stage and the final, subsiding stage of an epidemic wave are primarily determined by the unstable eigenvector of the initial stage and its corresponding remnant vector of the final stage. see more The corresponding amplitude captures most of the dynamics of the emerging and subsiding epidemics such that the problem at hand effectively becomes one dimensional leading to a dramatic reduction of the complexity of the problem at hand. Explicitly demonstrated for the first-wave COVID-19 epidemics of the year 2020 in the state of New York and Pakistan are given.The forecasting of the nature and dynamics of emerging coronavirus (COVID-19) pandemic has gained a great concern for health care organizations and governments. The efforts aim to to suppress the rapid and global spread of its tentacles and also control the infection with the limited available resources. The aim of this work is to employ real data set to propose and analyze a compartmental discrete time COVID-19 pandemic model with non-linear incidence and hence predict and control its outbreak through dynamical research. The Basic Reproduction Number ( R 0 ) is calculated analytically to study the disease-free steady state ( R 0 0 are quite effective in reducing the COVID-19 infections in India or any country. The fitting and predictive capability of the proposed discrete-time system are presented for relishing the effect of disease through stability analysis using real data sets.This paper considers a nonlinear dynamical model of an ecosystem, which has been established through combining the classical Lotka-Volterra model with the classic SIR model. This nonlinear system consists of a generalist predator that subsists on two prey species in which disease is becoming endemic in one of them. The dynamical analysis methods prove that the system has a chaotic attractor and extreme multistability behavior, where there are infinitely many attractors that coexist under certain conditions. The occurrence of extreme multistability demonstrates the high sensitivity of the system for the initial conditions, which means that tiny changes in the original prey species could enlarge and be widespread, and that could confirm through studying the complexity of the time series of the system's variables. Simulation results of the sample entropy algorithm show that the changes in the system's variables expand over time. It is reasonable now to consider the endemic in the prey species of the system could evolve to be pandemic such as COVID-19. Consequently, our results could provide a foresight about the unpredictability of the COVID-19 outbreak in its original host species as well as after the transmission to other species such as humans.Non-human primates (NHPs) are particularly relevant as preclinical models for SARS-CoV-2 infection and nuclear imaging may represent a valuable tool for monitoring infection in this species. We investigated the benefit of computed X-ray tomography (CT) and [18F]-FDG positron emission tomography (PET) to monitor the early phase of the disease in a large cohort (n = 76) of SARS-CoV-2 infected macaques. Following infection, animals showed mild COVID-19 symptoms including typical lung lesions. CT scores at the acute phase reflect the heterogeneity of lung burden following infection. Moreover, [18F]-FDG PET revealed that FDG uptake was significantly higher in the lungs, nasal cavities, lung-draining lymph nodes, and spleen of NHPs by 5 days postinfection compared to pre-infection levels, indicating early local inflammation. The comparison of CT and PET data from previous COVID-19 treatments or vaccines we tested in NHP, to this large cohort of untreated animals demonstrated the value of in vivo imaging in preclinical trials.[This corrects the article DOI 10.1140/epja/s10050-021-00614-5.].

Risk perceptions and precaution-taking against COVID-19 are affected by individuals' health status, psychosocial vulnerabilities and cultural dimensions. This cross-sectional study investigates risk perceptions associated with COVID-19 and specifically the problem- and emotion-focused health precautions of older, culturally and linguistically diverse (CALD) South Australians.

Cross-sectional research involving self-administration of an online survey. Participants were CALD adults living in South Australia, aged 60 years and above (n = 155). Multi-indicator surveys were analyzed using Stata/MP version 13.0 and multiple linear regression models fitted to examine associations between risk perceptions and problem- and emotion-focused health precautions.

Dread risk returned the highest mean score; COVID-19 was perceived as a catastrophe. Mean scores for fear showed that participants were worried about COVID-19 and scared of becoming infected. Participants followed health advice as they were worried [β 0.15; pare risk perception and health response patterns across countries and cultural groupings.

This local study has global implications. It showed that COVID-19 has psychosocial and environmental implications for older CALD adults. When many CALD populations have existing vulnerabilities to intersecting disadvantage, cultural-tailoring of interventions and pandemic response plans may buffer the effects of compounding disaster. Larger studies are needed to compare risk perception and health response patterns across countries and cultural groupings.This study presents the Auditory Cortex ResNet (AUCO ResNet), it is a biologically inspired deep neural network especially designed for sound classification and more specifically for Covid-19 recognition from audio tracks of coughs and breaths. Differently from other approaches, it can be trained end-to-end thus optimizing (with gradient descent) all the modules of the learning algorithm mel-like filter design, feature extraction, feature selection, dimensionality reduction and prediction. This neural network includes three attention mechanisms namely the squeeze and excitation mechanism, the convolutional block attention module, and the novel sinusoidal learnable attention. The attention mechanism is able to merge relevant information from activation maps at various levels of the network. The net takes as input raw audio files and it is able to fine tune also the features extraction phase. In fact, a Mel-like filter is designed during the training, thus adapting filter banks on important frequencies. AUCO ResNet has proved to provide state of art results on many datasets. Firstly, it has been tested on many datasets containing Covid-19 cough and breath. This choice is related to the fact that that cough and breath are language independent, allowing for cross dataset tests with generalization aims. These tests demonstrate that the approach can be adopted as a low cost, fast and remote Covid-19 pre-screening tool. The net has also been tested on the famous UrbanSound 8K dataset, achieving state of the art accuracy without any data preprocessing or data augmentation technique.

Treatment of metastatic cancer patients with multiple repeat courses of radiotherapy has become more frequent due to their improved overall survival. However, very little is known about their long-term outcome. This analysis reports on the quality-of-life, hematologic toxicity, patient-reported experiences and satisfaction, and psychological distress of cancer patients treated with multiple repeat radiotherapy.

All patients treated with ≥5 courses of radiotherapy between 2011 and 2019 at the Department of Radiation Oncology, University Hospital Zurich (USZ) were screened for this study. A course of radiotherapy was defined as all treatment sessions to one anatomical site under one medical indication. All patients completed two questionnaires EORTC QLQ-C30 questionnaire for quality-of-life and a questionnaire evaluating psychological distress and patient-reported experiences. Hematologic toxicities were assessed via a recent blood sample.

Of n=33 patients treated with ≥5 radiotherapy courses and being alobserved. These data indicate the need to further investigate the effects of multiple courses of radiotherapy in chronic cancer patients.

Patient-reported experiences and satisfaction of long-term cancer patients treated with multiple repeat radiotherapy are positive. However, increased levels of fatigue and significantly reduced hemoglobin and lymphocyte levels were observed. These data indicate the need to further investigate the effects of multiple courses of radiotherapy in chronic cancer patients.The single-station microtremor horizontal-to-vertical spectral ratio (MHVSR) method was initially proposed to retrieve the site amplification function and its resonance frequencies produced by unconsolidated sediments overlying high-velocity bedrock. Presently, MHVSR measurements are predominantly conducted to obtain an estimate of the fundamental site frequency at sites where a strong subsurface impedance contrast exists. Of the earthquake site characterization methods presented in this special issue, the MHVSR method is the furthest behind in terms of consensus towards standardized guidelines and commercial use. The greatest challenges to an international standardization of MHVSR acquisition and analysis are (1) the what - the underlying composition of the microtremor wavefield is site-dependent, and thus, the appropriate theoretical (forward) model for inversion is still debated; and (2) the how - many factors and options are involved in the data acquisition, processing, and interpretation stages. This paper reviews briefly a historical development of the MHVSR technique and the physical basis of an MHVSR (the what). We then summarize recommendations for MHVSR acquisition and analysis (the how). Specific sections address MHVSR interpretation and uncertainty assessment.Crises-such as the COVID-19 pandemic-bring about myriad problems in magnitude (severity), dynamism (quality), and urgency (timing). Collaborative models that bring together actors from both the public and private sector have thus emerged for institutionalized and community-based crisis response. Such models aim particularly to reach vulnerable, hard-to-reach communities, such as racialized immigrant communities that are among those disproportionately impacted at times of crisis. This paper presents a case study of a community-based, cross-sectoral collaborative formed to respond to the COVID-19 pandemic and specifically targeting immigrant communities. Findings inform a conceptual framework that illustrates the integration of two spheres of service crisis supports, characterized by a short-term approach, broad-based reach and general objectives; and settlement supports, characterized by their long-term approach, trust relations and targeted objectives, such as language supports and culturally appropriate outreach.