Intensive Care Nurses' Knowledge of Radiation Safety and Their Behaviors Towards Portable Radiological Examinations

Background: Radiological examinations for patients who are hospitalized at intensive care units are usually performed using portable radiography devices. However they may require knowledge and safety precautions of nurses. Objectives: The aim of the study was to investigate ICU nurses’ knowledge of radiation safety and their behaviors towards portable radiological examinations. Materials and Methods: In total, 44 intensive care nurses were recruited for this cross-sectional descriptive study using census sampling during April and May 2014. The study setting was at intensive care units of Shahid Beheshti Hospital of Kashan, Iran. An eleven-item questionnaire and a five-item checklist were used for evaluating nurses’ radiation protection knowledge and behaviors, respectively. An expert panel consisting of ten nursing and radiology faculty members confirmed the content validity of the questionnaire and the checklist. Moreover, a Geiger-Müller counter was used for measuring ionizing radiation during portable radiological examinations. Study data were analyzed using the SPSS software version 13.0. Mean, standard deviation, frequency and one-sample t test were used for description of the data. The level of significance was set at below 0.05. Results: The mean of participants’ radiation protection knowledge was 4.77 ± 1.38. The most prevalent radiation protection behavior of nurses was leaving the intensive care unit during portable radiological examinations. Only 6.8% of nurses stayed at the nursing station during radiological examinations. The highest dose of radiation was 0.11 micro Sievert per hour (μSv/h), which was much lower than the highest permitted level of radiation exposure i.e. 0.25 μSv/h. Conclusions: Portable radiological examinations did not expose healthcare providers to high doses of ionizing radiation. Nurses’ radiation protection knowledge was limited and hence, they require in-service education programs

Outline of the SECOQC Quantum-Key-Distribution Network in Vienna

A Quantum Key Distribution (QKD) network is currently implemented in Vienna by integrating seven QKD-Link devices that connect five subsidiaries of SIEMENS Austria. We give an architectural overview of the network and present the enabling QKD-technologies, as well as the novel QKD network protocols.Comment: 10 pages, 5 figure

Deep learning-based vehicle behaviour prediction for autonomous driving applications : a review

Behaviour prediction function of an autonomous vehicle predicts the future states of the nearby vehicles based on the current and past observations of the surrounding environment. This helps enhance their awareness of the imminent hazards. However, conventional behavior prediction solutions are applicable in simple driving scenarios that require short prediction horizons. Most recently, deep learning-based approaches have become popular due to their promising performance in more complex environments compared to the conventional approaches. Motivated by this increased popularity, we provide a comprehensive review of the state-of-the-art of deep learning-based approaches for vehicle behavior prediction in this article. We firstly give an overview of the generic problem of vehicle behavior prediction and discuss its challenges, followed by classification and review of the most recent deep learning-based solutions based on three criteria: input representation, output type, and prediction method. The article also discusses the performance of several well-known solutions, identifies the research gaps in the literature and outlines potential new research directions

A participatory process for modelling green infrastructure implementation in London

Cities face the interlinked challenges of transforming environmental quality, sustainability, population health and health equity. There is increasing interest in green infrastructure in connection with these challenges. In order to go beyond an understanding of the effects of green infrastructure and develop an understanding of how policymakers should think about it, we need to capture potential interactions and be aware of possible unintended consequences. In our research, we applied a systems-thinking approach: integrating participatory engagements, qualitative system dynamics modelling, and an assessment framework in order to address the challenge. This allowed us to see multiple dynamics between the prioritisation of policymakers, different types of green infrastructure, and environmental and health outcomes. It also made us ask different and more integrated questions, and suggested a methodology for addressing the challenge of transforming cities

Analysis of cyber risk and associated concentration of research (ACR)² in the security of vehicular edge clouds

Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS

Using quantum key distribution for cryptographic purposes: a survey

The appealing feature of quantum key distribution (QKD), from a cryptographic viewpoint, is the ability to prove the information-theoretic security (ITS) of the established keys. As a key establishment primitive, QKD however does not provide a standalone security service in its own: the secret keys established by QKD are in general then used by a subsequent cryptographic applications for which the requirements, the context of use and the security properties can vary. It is therefore important, in the perspective of integrating QKD in security infrastructures, to analyze how QKD can be combined with other cryptographic primitives. The purpose of this survey article, which is mostly centered on European research results, is to contribute to such an analysis. We first review and compare the properties of the existing key establishment techniques, QKD being one of them. We then study more specifically two generic scenarios related to the practical use of QKD in cryptographic infrastructures: 1) using QKD as a key renewal technique for a symmetric cipher over a point-to-point link; 2) using QKD in a network containing many users with the objective of offering any-to-any key establishment service. We discuss the constraints as well as the potential interest of using QKD in these contexts. We finally give an overview of challenges relative to the development of QKD technology that also constitute potential avenues for cryptographic research.Comment: Revised version of the SECOQC White Paper. Published in the special issue on QKD of TCS, Theoretical Computer Science (2014), pp. 62-8

VRSTNN : visual-relational spatio-temporal neural network for early hazardous event detection in automated driving systems

Reliable and early detection of hazardous events is vital for the safe deployment of automated driving systems. Yet, it remains challenging as road environments can be highly complex and dynamic. State-of-the-art solutions utilise neural networks to learn visual features and temporal patterns from collision videos. However, in this paper, we show how visual features alone may not provide the essential context needed to detect early warning patterns. To address these limitations, we first propose an input encoding that captures the context of the scene. This is achieved by formulating a scene as a graph to provide a framework to represent the arrangement, relationships and behaviours of each road user. We then process the graphs using graph neural networks to identify scene context from: 1) the collective behaviour of nearby road users based on their relationships and 2) local node features that describe individual behaviour. We then propose a novel visual-relational spatiotemporal neural network (VRSTNN) that leverages multi-modal processing to understand scene context and fuse it with the visual characteristics of the scene for more reliable and early hazard detection. Our results show that our VRSTNN outperforms stateof- the-art models in terms of accuracy, F1 and false negative rate on a real and synthetic benchmark dataset: DOTA and GTAC

Investigation of Mutations of Exon 11-A of BRCA1 Gene in Women with Breast Cancer in the Northwest of Iran

BACKGROUND AND OBJECTIVE: Breast cancer is the most common cancer in women, which is associated with genetic changes such as mutations in carcinogenic genes and tumor suppressor genes. One of the most important tumor suppressor genes involved in breast cancer is the BRCA1 gene. The mutation in this gene is a common occurrence in human breast cancer. The purpose of this study is to investigate the mutations of exon 11-A of BRCA1 gene in women with breast cancer in the northwest of Iran. METHODS: In this descriptive study, blood sample were collected form 40 patients with breast cancer whose cancer was diagnosed before the age of 40 years and the exon 11-A of BRCA1 gene was examined using PCR and direct sequencing methods to detect mutations. Sequencing results were analyzed using Chromas software. FINDING: In the present study, a nonsynonymous mutation was reported as a new mutation of BRCA1 gene for the first time: Ala584Thr mutation was also observed in two samples. The mutations of codon 694 (Ser694Ser) showed a higher incidence (52.5%). Other mutations were observed in codons 693, 356, 486, 550 and 628. CONCLUSION: Based on the results of this study, mutations and polymorphisms of exon 11 of BRCA1 gene were observed for the first time in the northwestern population of Iran. One new case of mutation was observed in exon 11-A of BRCA1 gene

Complex Urban Systems for Sustainability and Health: A structured approach to support the development and implementation of city policies for population and planetary health

Context: The multi-disciplinary and multi-partner CUSSH project (Complex Urban Systems for Sustainability and Health) seeks to support cities to take transformative action towards population and planetary health goals. Rationale: As all cities are complex systems with unique contexts and priorities, our approach is to engage with partner cities in a participatory process to build a shared understanding of relevant systems that will inform the development and implementation of new city policies. Description: Six partner cities were selected to represent larger and smaller cities from across the global spectrum of income: London (UK) and Rennes (France) in Europe, Nairobi and Kisumu in Kenya, and Beijing and Ningbo in China. In each setting we are engaging stakeholders in a broadly similar structured approach that integrates evidence gathering and modelling, participatory engagement framework, and ongoing tracking and evaluation. In addition, we are developing a working theory of change in each setting to explain how and why the chosen policies may work. Achievements: Our city engagement to date has focused on indoor air pollution (Nairobi), green infrastructure (London) and GHG emissions (Rennes), where findings highlighted not only multiple pathways by which policy interventions could affect health, but also potential counter-intuitive influences and tensions, and synergistic opportunities for solving both sustainability and health problems