Is Australia Ready for Autonomous Vehicles? Examining the Factors Influencing AV Adoption through Expert Interviews

As Autonomous Vehicles (AVs) on public roads today becomes an increasingly realistic possibility, there is growing need to better understand the factors that will facilitate their successful introduction. This study focuses specifically on Australia and investigates various micro and macro environmental factors that may either hinder or support their adoption in the country. The study comprised 18 in-depth interviews with experts from both the public and private sectors who possess direct experience working with AVs. These experts provided valuable insights into several areas, including the legislation and regulations governing AV use, the technical and infrastructure requirements necessary for safe operation on public roads, and the importance of public sentiment in driving AV adoption and introduction. Based on the study’s findings, an integrated framework has been developed to identify and classify the key factors related to AV adoption, as well as their interrelatedness with each other. This framework seeks to guide the development of national strategies to accommodate the necessary political, legal, and social adjustments required for the successful implementation of AVs

Reproduction of Endangered Big-Headed Turtle, \u3cem\u3ePlatysternon megacephalum\u3c/em\u3e (Reptilia: Testudines: Platysternidae)

The big-headed turtle (Platysternon megacephalum) is heavily harvested to support tremendous demands from food and pet markets, and thus its ecology remains poorly understood. The presence of self-sustaining populations in Hong Kong (22°09’-22°37’N, 113°50’-114°30’E) provides important opportunities to advance our understanding of this species. We employed mark-recapture surveying, radio-tracking of two gravid females, and directed streamside searches to document the reproductive ecology of the species between September 2009 and June 2011 in Hong Kong. We found seven gravid females between 20-27 June 2010 and 2011, and which subsequently oviposited on average three eggs (range 2-8), with mean length and width of 36 mm and 21 mm, in early July. There was positive correlation between the size of females and clutch sizes. We found one clutch in leaf litter 1.6 m away from the stream, which hatched between 14 to 18 October. The incubation period was estimated to be between 103 and 110 days. The results of this study provide important information to formulate conservation plan for this endangered species

Colección José Arencibia [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte, 201

Reproduction of endangered Big-headed Turtle, Platysternon megacephalum (Reptilia: Testudines: Platysternidae)

The big-headed turtle (Platysternon megacephalum) is heavily harvested to support tremendous demands from food and pet markets, and thus its ecology remains poorly understood. The presence of self-sustaining populations in Hong Kong (22°09’-22°37’N, 113°50’-114°30’E) provides important opportunities to advance our understanding of this species. We employed mark-recapture surveying, radio-tracking of two gravid females, and directed streamside searches to document the reproductive ecology of the species between September 2009 and June 2011 in Hong Kong. We found seven gravid females between 20-27 June 2010 and 2011, and which subsequently oviposited on average three eggs (range 2-8), with mean length and width of 36 mm and 21 mm, in early July. There was positive correlation between the size of females and clutch sizes. We found one clutch in leaf litter 1.6 m away from the stream, which hatched between 14 to 18 October. The incubation period was estimated to be between 103 and 110 days. The results of this study provide important information to formulate conservation plan for this endangered species

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease