Green Urban (RE) Generation: A Research and Practice Methodology to Better Implement Green Urban Infrastructure Solutions

Green Urban Infrastructure Solutions (GUIS) are becoming more and more popular globally. Recent research reveals the environmental benefits derived from GUIS as well as their contribution to climate change adaptation. However, the urgent need for GUIS in order to meet the Paris Agreement, has not translated into an easy implementation thereof. This paper proposes a circular design methodology (CDM) where the combination of research and practice contributes to minimize both current skepticism and barriers when implementing GUIS. It includes a community engagement process to better understand their sensitivity and build consensus on GUIS. Additionally, GUIS are implemented, in a series of pilot projects and specific research is applied to comprehend the environmental benefits derived from these GUIS. The paper argues that GUIS represent a significant opportunity to respond to climate change risks as well as to achieve other urban benefits; however, in order to overcome existing barriers and skepticism, the proposed CDM reaches for more consensual urban solutions and drives uptake and implementation of GUIS, contributing to move from pilot project to common practice.

Veracity assessment by single and multi-source identification algorithms during the crisis

Social networks have become a popular communication tool for information sharing. Twitter offers access to data and provides a significant opportunity to analyze data. During pandemics, Twitter becomes a big source for the dispersal of unverified information. In social media, it is difficult to find the sources of rumors. To tackle this problem the authors have developed a hybrid rumor centrality algorithm for rumor source detection in social networks. The authors propose an S-RSI algorithm for identifying a single rumor centre and an M-RSI algorithm for identifying the propagations of multiple rumor centres in the thread of conversation. The proposed rumor centrality algorithm efficiently predicts the rumor disseminating possibilities in a conversation tree with the aid of graph theoretical approach. The authors have evaluated the performance of the algorithms on the PHEME dataset containing seven real-time event conversational trees based on the tweet messages. The results show that the proposed is best suitable in finding the rumor source centre with a high probability in social media during a crisis.

Expert Advisory System for Production Surveillance and Optimization Assisted by Artificial Intelligence

Petroleum Engineers are usually responsible for 50-200 wells. The wells in highly instrumented fields generate 10-20 measurements every few seconds. This makes it difficult to be on top of every well, every day. This challenge carries a significant opportunity cost, therefore the surveillance process requires automation by implementing surveillance-by-exception. Faster identification of problems is great, but not enough unless the required activities are executed in a timely manner. The ability to execute quickly and safely requires a well-structured coordination effort between the different disciplines involved in field operations. In line with ADNOC Digital Transformation strategy, the solution described in this paper intends to couple surveillance by exception (a Petroleum Engineering workflow) with field operations execution (a multi-disciplinary set of workflows in the field). The integration is achieved by creating a simple yet robust action tracking system, and feeding it automatically with new opportunities, so that it is kept up to date. Automatic diagnosis becomes opportunities. Opportunities become activities. Activities are assigned, executed and closed. All activities are tracked on a high level, which provides insights and visibility to all parties on who is doing what, when and how to close the opportunity. The surveillance by exception engine consumes real time measurements from the historian. It then runs a set of soft sensors using full physics, reduced order models, proxy and data driven machine learning models, which utilize most of the measurements. The measured and calculated values are then fed to an expert system, which automatically diagnoses the wells and creates tickets with recommendations to the production engineer. The engineer reviews the ticket and forwards to field operations for execution. The log of activities enables a direct measure of operational effectiveness. This paper describes the philosophy of the system, how it works, lessons learned and the results of implementation across 6 oilfields and 600+ wells in Abu Dhabi.

Temperature measurement methods in an experimental setup during bone drilling: A brief review on the comparison of thermocouple and infrared thermography

Predicting thermal response in orthopedic surgery or dental implantation remains a significant challenge. This study aims to find an effective approach for measuring temperature elevation during a bone drilling experiment by analyzing the existing methods. Traditionally thermocouple has frequently been used to predict the bone temperature in the drilling process. However, several experimental studies demonstrate that the invasive method using thermocouple is impractical in medical conditions and preferred the thermal infrared (IR) camera as a non-invasive method. This work proposes a simplified experimental model that uses the thermocouple to determine temperature rise coupled with the thermal image source approach. Furthermore, our new method provides a significant opportunity to calibrate the thermal IR camera by finding out the undetected heat elevation in a workpiece depth.

Possibility of Using Wind and Solar Sources for Electric Power Generation on Serbian Opencast Coal Mines

The rapid technology advancement and the significant decline of investment costs in wind and solar energy generation have opened up a significant opportunity to build these facilities on closed opencast mines or mines in the phase of closure around the world, where large available areas are almost ideal for such projects. In that sense, it is necessary to give an analysis of the possible application of wind and/or solar energy production in the Republic of Serbia’s mines, as well as the dynamics of such a generally ambitious and long-term project with conceptual solutions.

CMALT 2011 and 2021: Personal narratives for professional recognition

Professional recognition through Certified Membership of the Association for Learning Technology (CMALT) provides a significant opportunity for all those who use learning technologies to be acknowledged for their experience, capabilities, and practice. The CMALT portfolio requires a personal narrative that presents description, critical reflection, and evidence of professional practice. Through an experiential lens, this paper considers three facets of the authors’ CMALT experiences a decade apart—how the portfolios as personal narratives encouraged reflection on practice; the commonalities in the technology themes presented in those portfolios; and how reflective coaching contributed to the benefits of applying for CMALT.

Citizen science in cities: an overview of projects focused on urban Australia

Citizen science offers a unique opportunity to connect urban-dwellers with the often hidden natural world upon their doorsteps and to contribute to authentic research that increases knowledge of urban ecology and biodiversity. With the majority of Australia’s population residing in large cities, this diverse potential pool of participants in science creates a significant opportunity to increase the spatial and temporal scale of research. Herein, we provide an overview of Australian urban citizen science projects based on an analysis of the projects listed in the Australian Citizen Science Association’s Citizen Science Project Finder. We draw out key features (such as those with research questions specific to cities such as reintroduction and persistence of species in urban environments) from urban citizen science projects that make them suitable for the urban environment and use these features to suggest recommendations for further expansion and development of this important subset of projects. We conclude that the number and diversity of urban citizen science projects is relatively low in Australia, and advocate for an increase in initiatives that can tap into a large pool of potential participants for the benefit of science and society.

Abstract 9764: Prevalence of Inappropriate Defibrillation Attempts During Pediatric In-Hospital Cardiac Arrest

Introduction: Shockable rhythms (ventricular fibrillation [VF] and ventricular tachycardia [VT]) occur in <25% of pediatric in-hospital cardiac arrest (IHCA) events, yet the prevalence of inappropriate defibrillation attempts for non-VF/VT rhythms is unknown. We aim to describe the prevalence of inappropriate shocks across a large, multi-national pediatric cardiac arrest network. Methods: We included children <18y reported to the pedi atric RES uscitation- Q uality (pediRES-Q) network from 2015-2019 with complete defibrillator files who received defibrillation attempts during IHCA (ZOLL R-Series, MA). Two pediatric cardiologists independently classified rhythms immediately prior to shock as: 1) appropriate (VF or wide complex ≥ 150/min), 2) indeterminate (narrow complex ≥150/min or wide complex 100-149/min), or 3) inappropriate (asystole, sinus, narrow complex <150/min, or wide complex <100/min). Rhythms that were undecipherable due to artifact were excluded from analysis (n=22). Disagreements were resolved by arbitration and consensus. Results: Of 896 IHCA events, 124 (14%) had defibrillation attempts. A total of 303 shocks were delivered: 87 (29%) in age <1y, 84 (28%) in 1-8y, and 132 (44%) in 9-17y. Of shocks delivered, 206 (68%) were appropriate, 12 (4%) indeterminate, and 85 (28%) inappropriate. There was no difference in inappropriate shock delivery by age category: <1y (24/87, 28%), 1-8y (26/84, 31%), 9-17y (35/132, 27%) ( p =0.4). Conclusions: Across a multi-national pediatric cardiac arrest network, a large proportion (28%) of defibrillation attempts were inappropriate, suggesting significant opportunity for improvement in rhythm identification in pediatric cardiac arrest. There was no difference in inappropriate shock delivery across age groups. Figure 1. Representation of rhythm classification and appropriateness of defibrillation attempts with exemplar rhythms.

Green Criminology–Law Interdisciplinarity Towards Multispecies Justice: The Case of Wildlife Trafficking in Vietnam

Green criminology provides a significant opportunity for interdisciplinary engagement to address the many environmental problems of the twenty-first century that are too complex to be solved through a single disciplinary lens. Hall (2014) has called for increased collaboration between green criminologists and legal scholars while also acknowledging that this form of interdisciplinarity is more challenging than for more traditional forms of criminology. This paper adopts Hall’s call as a starting point for a critical exploration of two areas that offer ground for collaboration: positioning analyses of environmental harm within wider regulatory frameworks and considering the ways human and non-human victims interact with ‘the mechanisms of justice’ to exercise ‘environmental rights’ (Hall 2014: 105). We examine these areas drawing on the case of wildlife trafficking in Vietnam. We argue that ‘multispecies justice’ presents a useful framework to progress green criminology–law collaborations in the Vietnamese and other contexts.

Facing Adversity during Graduate Medical Training: The Concept of ‘Coping Intelligence’

Effective coping strategies are of great importance for trainees actively navigating the challenges and stresses of graduate medical education (GME). Although there is increasing emphasis on the concept of emotional intelligence (EI) in medical curricula, the range of behavioral skills learned in typical EI training may not be sufficient when dealing with extreme stress – something that healthcare students in general, and GME trainees as a subset, continue to struggle with. Under the conditions of extreme stress, multiple competing priorities and high cognitive load, even those with excellent command of EI skills may not be able to universally maintain sufficient emotional control. This, in turn, exposes a significant opportunity for further understanding and development in this dynamically evolving area of investigation. Increasing amount of research suggests that a unique skill set exists, known as ‘coping intelligence’ (CI), that may help fill the gap under the conditions of extreme stress and significantly elevated cognitive load. This chapter will discuss CI as a unique and novel concept, further exploring the possibility of introducing this new construct into the realm of GME.