Police functional adaptation to the digital or post digital age: discussions with cybercrime experts.

This article examines the challenges of functional adaptation faced by the police in response to technologically driven changes in the nature of crime. It also recounts how research under the auspices of a ‘dark web’ research project resulted in a search for an effective approach to engaging with investigators dealing with cybercrime. In doing so it tested, as a research methodology, a standard change implementation tool (problem tree analysis) from the Disaster Management and Sustainable Development (DMSD) discipline. This in turn resulted in significant consideration being given to the physical space in which that methodology is used. It presents the results of a workshop held with cybercrime investigators (not all were police officers) in terms of the importance of four key organisational and cultural issues (management, leadership and institutional ethos within the police; the risks of over-complication and exaggerated distinctions between cyber and real world policing; ethics; and knowledge, training and development) alongside the development and acquisition of new technical capabilities

Narrative literature review on incentives for primary health care team service provision: learning and working together in primary health care

Governments are encouraging team work between primary health care (PHC) providers using various incentive approaches, particularly for patients with complex and chronic illness. To date, no Australian focused literature review has been conducted considering the use of combined incentive approaches to encourage team work to inform PHC policy decision making.The research reported in this paper is a project of the Australian Primary Health Care Research Institute which is supported by a grant from the Australian Government Department of Health and Ageing under the Primary Health Care Research Evaluation and Development Strategy

Understanding service demand for mental health among Australians aged 16 to 64 years according to their possible need for treatment

ABSTRACT Background: To inform decisions about mental health resource allocation, planner

Recombinant Simian Varicella Virus-Simian Immunodeficiency Virus Vaccine Induces T and B Cell Functions and Provides Partial Protection against Repeated Mucosal SIV Challenges in Rhesus Macaques

HIV vaccine mediated efficacy, using an expanded live attenuated recombinant varicella virus-vectored SIV rSVV-SIVgag/env vaccine prime with adjuvanted SIV-Env and SIV-Gag protein boosts, was evaluated in a female rhesus macaques (RM) model against repeated intravaginal SIV challenges. Vaccination induced anti-SIV IgG responses and neutralizing antibodies were found in all vaccinated RMs. Three of the eight vaccinated RM remained uninfected (vaccinated and protected, VP) after 13 repeated challenges with the pathogenic SIVmac251-CX-1. The remaining five vaccinated and infected (VI) macaques had significantly reduced plasma viral loads compared with the infected controls (IC). A significant increase in systemic central memory CD4+ T cells and mucosal CD8+ effector memory T-cell responses was detected in vaccinated RMs compared to controls. Variability in lymph node SIV-Gag and Env specific CD4+ and CD8+ T cell cytokine responses were detected in the VI RMs while all three VP RMs had more durable cytokine responses following vaccination and prior to challenge. VI RMs demonstrated predominately SIV-specific monofunctional cytokine responses while the VP RMs generated polyfunctional cytokine responses. This study demonstrates that varicella virus-vectored SIV vaccination with protein boosts induces a 37.5% efficacy rate against pathogenic SIV challenge by generating mucosal memory, virus specific neutralizing antibodies, binding antibodies, and polyfunctional T-cell responses

A Diet With Docosahexaenoic and Arachidonic Acids as the Sole Source of Polyunsaturated Fatty Acids Is Sufficient to Support Visual, Cognitive, Motor, and Social Development in Mice

Polyunsaturated fatty acids serve multiple functions in neurodevelopment and neurocognitive function. Intravenous lipid emulsions are administered to children that are dependent on parenteral nutrition to provide the essential fatty acids needed to sustain growth and development. One of these emulsions, derived from fish-oil, is particularly poor in the traditional essential fatty acids, linoleic and alpha-linolenic acids. However, it does contain adequate amounts of its main derivatives, arachidonic acid (ARA) and docosahexaenoic acid (DHA), respectively. This skewed composition has raised concern about the sole use of fish-oil based lipid emulsions in children and how its administration can be detrimental to their neurodevelopment. Using a custom-made diet that contains ARA and DHA as a sole source of polyunsaturated fatty acids, we bred and fed mice for multiple generations. Compared to adult, chow-fed mice, animals maintained on this special diet showed similar outcomes in a battery of neurocognitive tests performed under controlled conditions. Chow-fed mice did perform better in the rotarod test for ataxia and balance, although both experimental groups showed a conserved motor learning capacity. Conversely, mice fed the custom diet rich in DHA and ARA showed less neophobia than the chow-fed animals. Results from these experiments suggest that providing a diet where ARA and DHA are the sole source of polyunsaturated fatty acids is sufficient to support gross visual, cognitive, motor, and social development in mice

Design, Analysis and Testing of a Novel Mitral Valve for Transcatheter Implantation

Mitral regurgitation is a common mitral valve dysfunction which may lead to heart failure. Because of the rapid aging of the population, conventional surgical repair and replacement of the pathological valve are often unsuitable for about half of symptomatic patients, who are judged high-risk. Transcatheter valve implantation could represent an effective solution. However, currently available aortic valve devices are inapt for the mitral position. This paper presents the design, development and hydrodynamic assessment of a novel bi-leaflet mitral valve suitable for transcatheter implantation. The device consists of two leaflets and a sealing component made from bovine pericardium, supported by a self-expanding wireframe made from superelastic NiTi alloy. A parametric design procedure based on numerical simulations was implemented to identify design parameters providing acceptable stress levels and maximum coaptation area for the leaflets. The wireframe was designed to host the leaflets and was optimised numerically to minimise the stresses for crimping in an 8 mm sheath for percutaneous delivery. Prototypes were built and their hydrodynamic performances were tested on a cardiac pulse duplicator, in compliance with the ISO5840-3:2013 standard. The numerical results and hydrodynamic tests show the feasibility of the device to be adopted as a transcatheter valve implant for treating mitral regurgitation

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages