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Wang, Qihua, and Ninghui Li. "Satisfiability and Resiliency in Workflow Authorization Systems." ACM Transactions on Information and System Security 13, no. 4 (December 2010): 1–35. http://dx.doi.org/10.1145/1880022.1880034.
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Boughrous, Monsef, and Hanan El Bakkali. "A Workflow Criticality-Based Approach to Bypass the Workflow Satisfiability Problem." Security and Communication Networks 2021 (October 25, 2021): 1–15. http://dx.doi.org/10.1155/2021/3330923.
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Workflow management systems are very important for any organization to manage and model complex business processes. However, significant work is needed to keep a workflow resilient and secure. Therefore, organizations apply a strict security policy and enforce access control constraints. As a result, the number of available and authorized users for the workflow execution decreases drastically. Thus, in many cases, such a situation leads to a workflow deadlock situation, where there no available authorized user-task assignments for critical tasks to accomplish the workflow execution. In the literature, this problem has gained interest of security researchers in the recent years, and is known as the workflow satisfiability problem (WSP). In this paper, we propose a new approach to bypass the WSP and to ensure workflow resiliency and security. For this purpose, we define workflow criticality, which can be used as a metric during run-time to prevent WSP. We believe that the workflow criticality value will help workflow managers to make decisions and start a mitigation solution in case of a critical workflow. Moreover, we propose a delegation process algorithm (DP) as a mitigation solution that uses workflow instance criticality, delegation, and priority concepts to find authorized and suitable users to perform the critical task with low-security risks.
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Tavana, Madjid, Timothy E. Busch, and Eleanor L. Davis. "Modeling Operational Robustness and Resiliency with High-Level Petri Nets." International Journal of Knowledge-Based Organizations 1, no. 2 (April 2011): 17–38. http://dx.doi.org/10.4018/ijkbo.2011040102.
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Military operations are highly complex workflow systems that require careful planning and execution. The interactive complexity and tight coupling between people and technological systems has been increasing in military operations, which leads to both improved efficiency and a greater vulnerability to mission accomplishment due to attack or system failure. Although the ability to resist and recover from failure is important to many systems and processes, the robustness and resiliency of workflow management systems has received little attention in literature. The authors propose a novel workflow modeling framework using high-level Petri nets (PNs). The proposed framework is capable of both modeling structure and providing a wide range of qualitative and quantitative analysis. The concepts of self-protecting and self-healing systems are captured by the robustness and resiliency measures proposed in this study. The proposed measures are plotted in a Cartesian coordinate system; a classification scheme with four quadrants (i.e., possession, preservation, restoration, and devastation) is proposed to show the state of the system in terms of robustness and resiliency. The authors introduce an overall sustainability index for the system based on the theory of displaced ideals. The application of the methodology in the evaluation of an air tasking order generation system at the United States Air Force is demonstrated.
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Tavana, Madjid, Timothy E. Busch, and Eleanor L. Davis. "Fuzzy Multiple Criteria Workflow Robustness and Resiliency Modeling with Petri Nets." International Journal of Knowledge-Based Organizations 1, no. 4 (October 2011): 72–90. http://dx.doi.org/10.4018/ijkbo.2011100105.
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The increasing complexity and tight coupling between people and computer systems in military operations has led to improved efficiency, as well as greater vulnerability due to system failure. Careful management of workflow systems can minimize operational vulnerability in command and control. Tavana et al. (2011) developed a workflow management framework capable of both modeling structure and providing a wide range of quantitative analysis with high-level Petri nets (PNs). The framework is based on a sustainability index that captures the concepts of self-protecting and self-healing systems. This index uses crisp numerical values to measure the robustness and resiliency of the system. However, the observed values of data in real-world military operations are often imprecise or vague. These inexact data can be represented by fuzzy numbers to reflect the decision makers’ intuition and subjective judgments. In this paper, the authors extend this model to a fuzzy framework by proposing a new fuzzy workflow modeling system with PNs. The new model plots the fuzzy robustness and resiliency measures in a Cartesian coordinate system and derives an overall fuzzy sustainability index for the system based on the theory of displaced ideals. The proposed model also considers multiple criteria to produce this fuzzy index.
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Thurzo, Andrej, Filip Kočiš, Bohuslav Novák, Ladislav Czako, and Ivan Varga. "Three-Dimensional Modeling and 3D Printing of Biocompatible Orthodontic Power-Arm Design with Clinical Application." Applied Sciences 11, no. 20 (October 18, 2021): 9693. http://dx.doi.org/10.3390/app11209693.
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Three-dimensional (3D) printing with biocompatible resins offers new competition to its opposition—subtractive manufacturing, which currently dominates in dentistry. Removing dental material layer-by-layer with lathes, mills or grinders faces its limits when it comes to the fabrication of detailed complex structures. The aim of this original research was to design, materialize and clinically evaluate a functional and resilient shape of the orthodontic power-arm by means of biocompatible 3D printing. To improve power-arm resiliency, we have employed finite element modelling and analyzed stress distribution to improve the original design of the power-arm. After 3D printing, we have also evaluated both designs clinically. This multidisciplinary approach is described in this paper as a feasible workflow that might inspire application other individualized biomechanical appliances in orthodontics. The design is a biocompatible power-arm, a miniature device bonded to a tooth surface, translating significant bio-mechanical force vectors to move a tooth in the bone. Its design must be also resilient and fully individualized to patient oral anatomy. Clinical evaluation of the debonding rate in 50 randomized clinical applications for each power-arm-variant showed significantly less debonding incidents in the improved power-arm design (two failures = 4%) than in the original variant (nine failures = 18%).
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Sasser, Caroline Welles, Michael D. Wolcott, Kathryn A. Morbitzer, and Stephen F. Eckel. "Lessons learned from pharmacy learner and educator experiences during early stages of COVID-19 pandemic." American Journal of Health-System Pharmacy 78, no. 10 (February 22, 2021): 872–78. http://dx.doi.org/10.1093/ajhp/zxab076.
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Abstract Purpose To explore pharmacy learner (eg, resident, fellow) and educator (eg, residency program director, preceptor) experiences and lessons learned during the coronavirus disease 2019 (COVID-19) pandemic. Methods In May 2020, attendees of the virtual Research in Education and Practice Symposium (REPS) were invited to participate in two 1-hour networking sessions. During these sessions, participants completed individual and group reflection exercises where they were asked questions about their experiences during the initial stages of the COVID-19 pandemic. Participants who volunteered submitted their responses through an electronic survey application. Anonymous responses were coded using thematic analysis to address the research questions. Results Sixty-eight and 38 participants, respectively, attended the 2 networking discussions. Participant-identified professional impacts of the COVID-19 crisis included unexpected learning experiences, greater adaptability, workflow and learning interruptions, and decreased productivity. Personal impacts included a greater focus on well-being, physical and social isolation, and changes in travel plans. Participants noted positive and negative emotions including acceptance, encouragement, anxiety, stress, and frustration. The main lessons learned focused on adaptability, gratitude, and empathy. Participants shared that they wished they would have known the anticipated duration of the pandemic, associated workflow changes, and reliance on technology prior to the start of the pandemic. In addition, they predicted that pharmacy practice will require changes to workflow flexibility, training expectations, the pharmacist’s role, and organizational structure. Conclusion The COVID-19 pandemic has positively and negatively impacted the professional and personal lives of pharmacy learners and educators, with the most notable impacts being in the areas of well-being and adaptability. Future research should explore the experiences of other workforce personnel and evaluate the long-term impact on pharmacy practice, patient outcomes, and workforce well-being and resiliency.
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Xu, Zexuan, Rebecca Serata, Haruko Wainwright, Miles Denham, Sergi Molins, Hansell Gonzalez-Raymat, Konstantin Lipnikov, J. David Moulton, and Carol Eddy-Dilek. "Reactive transport modeling for supporting climate resilience at groundwater contamination sites." Hydrology and Earth System Sciences 26, no. 3 (February 11, 2022): 755–73. http://dx.doi.org/10.5194/hess-26-755-2022.
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Abstract. Climate resilience is an emerging issue at contaminated sites and hazardous waste sites, since projected climate shifts (e.g., increased/decreased precipitation) and extreme events (e.g., flooding, drought) could affect ongoing remediation or closure strategies. In this study, we develop a reactive transport model (Amanzi) for radionuclides (uranium, tritium, and others) and evaluate how different scenarios under climate change will influence the contaminant plume conditions and groundwater well concentrations. We demonstrate our approach using a two-dimensional (2D) reactive transport model for the Savannah River Site F-Area, including mineral reaction and sorption processes. Different recharge scenarios are considered by perturbing the infiltration rate from the base case as well as considering cap-failure and climate projection scenarios. We also evaluate the uranium and nitrate concentration ratios between scenarios and the base case to isolate the sorption effects with changing recharge rates. The modeling results indicate that the competing effects of dilution and remobilization significantly influence pH, thus changing the sorption of uranium. At the maximum concentration on the breakthrough curve, higher aqueous uranium concentration implies that sorption is reduced with lower pH due to remobilization. To better evaluate the climate change impacts in the future, we develop the workflow to include the downscaled CMIP5 (Coupled Model Intercomparison Project) climate projection data in the reactive transport model and evaluate how residual contamination evolves through 2100 under four climate Representative Concentration Pathway (RCP) scenarios. The integration of climate modeling data and hydrogeochemistry models enables us to quantify the climate change impacts, assess which impacts need to be planned for, and therefore assist climate resiliency efforts and help guide site management.
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Collins, Rhonda. "COVID-19: Nurses have responded, now it is time to support them as we move forward." Healthcare Management Forum 33, no. 5 (August 20, 2020): 190–94. http://dx.doi.org/10.1177/0840470420953297.
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The inspiration for The American Nurse Project, Dr. Rhonda Collins, DNP, RN, FAAN, is Chief Nursing Officer for Vocera Communications. Every year around Nurses Week, Dr. Collins publishes a report examining important issues that impact the nursing profession worldwide. Her 2020 CNO report looks at many of the challenges impacting nurses before, during, and after COVID-19—highlighting the mental anguish and physical burdens that COVID-19 has placed on nurses and other frontline healthcare workers as they put themselves in harm’s way to protect others. Dr. Collins examines the foundation of cognitive science and outlines a three-point strategy to guide hospital and nurse leaders moving forward as they strive to support staff members: lightening clinicians’ cognitive load by addressing the difference between documentation and communication, relieving the burden of adapting to multiple systems by giving clinicians control over how they communicate, and providing clinicians with clear, contextual, just-in-time information—using software to enhance workflow, not distract from it. During these unprecedented times, health leaders can honour nurses by providing them with the tools to help strengthen resiliency and healing from this crisis.
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Ackerman, Aidan, Jonathan Cave, Chien-Yu Lin, and Kyle Stillwell. "Computational modeling for climate change: Simulating and visualizing a resilient landscape architecture design approach." International Journal of Architectural Computing 17, no. 2 (May 16, 2019): 125–47. http://dx.doi.org/10.1177/1478077119849659.
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Coastlines are changing, wildfires are raging, cities are getting hotter, and spatial designers are charged with the task of designing to mitigate these unknowns. This research examines computational digital workflows to understand and alleviate the impacts of climate change on urban landscapes. The methodology includes two separate simulation and visualization workflows. The first workflow uses an animated particle fluid simulator in combination with geographic information systems data, Photoshop software, and three-dimensional modeling and animation software to simulate erosion and sedimentation patterns, coastal inundation, and sea level rise. The second workflow integrates building information modeling data, computational fluid dynamics simulators, and parameters from EnergyPlus and Landsat to produce typologies and strategies for mitigating urban heat island effects. The effectiveness of these workflows is demonstrated by inserting design prototypes into modeled environments to visualize their success or failure. The result of these efforts is a suite of workflows which have the potential to vastly improve the efficacy with which architects and landscape architects use existing data to address the urgency of climate change.
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Carwana, Matthew, Taylor Ricci, Alesia DiCicco, Ethan Ponton, Damian Duffy, Rebecca Courtemanche, William Lau, Tanjot Singh, and Christine Loock. "96 Impact and Feasibility of a Pediatric Social Determinants of Health Questionnaire: A Pilot Mixed-Methods Study." Paediatrics & Child Health 27, Supplement_3 (October 1, 2022): e45-e46. http://dx.doi.org/10.1093/pch/pxac100.095.
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Abstract Background Social determinants of health (SDoH)—which are factors such as socioeconomic status (SES), access to transportation, food and housing security, disability and social supports—have been shown to influence up to 50% of health in patients. The project team developed a SDoH Questionnaire which evolved into what is now referred to as BEARS (Barriers to Care, Economic Factors, Adversity, Resiliency, Social Capital). Part of the BEARS Questionnaire includes an optional section for inquiring about Adverse Childhood Experiences (ACEs). Objectives The primary purpose of this study was to evaluate the impact and feasibility of the BEARS Questionnaire. Additional objectives were to assess the utility and functionality of the BEARS Questionnaire as a social history-taking tool, including the cumulative ACEs questions, and obtain suggestions for improvement of the tool. Design/Methods This was a mixed methods pilot study that consisted of quantitative surveys and qualitative structured interviews with clinicians who had experience using the BEARS Questionnaire. Descriptive statistics were performed on all survey results. Thematic analysis was performed on clinician interviews with recurrent themes being identified through iterative analysis and tagged quotations. Results 15 clinicians completed the quantitative survey and five took part in a qualitative interview. Study participants included surgeons, pediatricians, speech language pathologists, social workers and nurse clinicians. The BEARS Questionnaire changed clinician practice by increasing the frequency and breadth of social screening in their patients and optimizing care to fit their patients’ social context. Participants described the BEARS as an effective screening tool for SDoH and ACEs that was feasible to implement into their clinic workflow. Three themes emerged from our interviews: (1) Thorough social history taking highlights family resiliency and improves clinician-patient rapport, (2) Screening for ACEs is acceptable and feasible in a safe clinical environment, and (3) Social screening is feasible in a busy clinical environment and there is room for improvement. Conclusion This study highlights the importance of social screening in pediatric patients and their families, and how using a social screening tool allows providers to tailor care for a patients’ social context. The BEARS Questionnaire is feasible to implement within the context of a busy clinic. Finally, despite being a sensitive topic, an ACEs questionnaire can be incorporated when done in a trauma-informed way, and in the context of a longitudinal therapeutic relationship.
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Crampton, Jason, Gregory Gutin, Daniel Karapetyan, and Rémi Watrigant. "The bi-objective workflow satisfiability problem and workflow resiliency1." Journal of Computer Security 25, no. 1 (March 16, 2017): 83–115. http://dx.doi.org/10.3233/jcs-16849.
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Wu, Danny T. Y., Lindsey Barrick, Mustafa Ozkaynak, Katherine Blondon, and Kai Zheng. "Principles for Designing and Developing a Workflow Monitoring Tool to Enable and Enhance Clinical Workflow Automation." Applied Clinical Informatics 13, no. 01 (January 2022): 132–38. http://dx.doi.org/10.1055/s-0041-1741480.
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Abstract Background Automation of health care workflows has recently become a priority. This can be enabled and enhanced by a workflow monitoring tool (WMOT). Objectives We shared our experience in clinical workflow analysis via three cases studies in health care and summarized principles to design and develop such a WMOT. Methods The case studies were conducted in different clinical settings with distinct goals. Each study used at least two types of workflow data to create a more comprehensive picture of work processes and identify bottlenecks, as well as quantify them. The case studies were synthesized using a data science process model with focuses on data input, analysis methods, and findings. Results Three case studies were presented and synthesized to generate a system structure of a WMOT. When developing a WMOT, one needs to consider the following four aspects: (1) goal orientation, (2) comprehensive and resilient data collection, (3) integrated and extensible analysis, and (4) domain experts. Discussion We encourage researchers to investigate the design and implementation of WMOTs and use the tools to create best practices to enable workflow automation and improve workflow efficiency and care quality.
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Safi, Mariam, Bettina Ravnborg Thude, Frans Brandt, and Robyn Clay-Williams. "The resilient potential behaviours in an Internal Medicine Department: Application of resilience assessment grid." PLOS ONE 17, no. 10 (October 17, 2022): e0276178. http://dx.doi.org/10.1371/journal.pone.0276178.
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Background The healthcare system is frequently subject to unpredictable conditions such as organisational changes and pandemics. In order to perform as required under these conditions (i.e. exhibiting resilient behaviour), it is necessary to know the current position of the organisation with respect to the four resilient potentials i.e. respond, monitor, learn and anticipate. The study aimed to understand and assess resilient performance of an Internal Medicine Department in a public hospital in Denmark using the resilience assessment grid (RAG). Methods A modified Delphi method was used to develop the context specific RAG, using interviews to generate items, two rounds of expert panel reviews and pilot testing the developed RAG questionnaire. The four sets of structured RAG questions were tested and revised until satisfactory face and content validity for application was achieved. The final version of the RAG (28-item Likert scale) questionnaire was sent electronically to 87 healthcare professionals (clinicians and managers) in January 2021 and 2022. The data was statistically analysed and illustrated in radar charts to assist in interpreting the resilience profiles. Results While the resilience profiles in 2021 and 2022 were similar, the scores in 2022 were slightly lower for some of the sub-indicators. The results indicate areas for improvement, especially related to the Internal Medicine Department’s potential to respond and learn. The results from the RAG were presented to the chief clinical consultants and managers to identify initiatives for quality improvement and for planning a new workflow at the Internal Medicine Department. Conclusion The RAG is a managerial tool to assess the potential resilient performance of the organisation in respect to the four resilience potentials, i.e., responding, monitoring, learning, and anticipating. It can be used to construct the resilience profile of the system over time to manage organisational changes.
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Yang, Yifan, S. Thomas Ng, Frank J. Xu, Martin Skitmore, and Shenghua Zhou. "Towards Resilient Civil Infrastructure Asset Management: An Information Elicitation and Analytical Framework." Sustainability 11, no. 16 (August 16, 2019): 4439. http://dx.doi.org/10.3390/su11164439.
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It is rather difficult for the stakeholders to understand and implement the resilience concept and principles in the infrastructure asset management paradigm, as it demands quality data, holistic information integration and competent data analytics capabilities to identify infrastructure vulnerabilities, evaluate and predict infrastructure adaptabilities to different hazards, as well as to make damage restoration and resilience improvement strategies and plans. To meet the stakeholder’s urgent needs, this paper proposes an information elicitation and analytical framework for resilient infrastructure asset management. The framework is devised by leveraging the best practices and processes of integrated infrastructure asset management and resilience management in the literature, synergizing the common elements and critical concepts of the two paradigms, ingesting the state-of-the-art interconnected infrastructure systems resilience analytical approaches, and eliciting expert judgments to iteratively improve the derived framework. To facilitate the stakeholders in implementing the framework, two use case studies are given in this paper, depicting the detailed workflow for information integration and resilience analytics in infrastructure asset management. The derived framework is expected to provide an operational basis to the quantitative resilience management of civil infrastructure assets, which could also be used to enhance community resilience.
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Xie, Fei, Jun Yan, and Jun Shen. "A Novel PageRank-Based Fault Handling Strategy for Workflow Scheduling in Cloud Data Centers." International Journal of Web Services Research 18, no. 4 (October 2021): 1–26. http://dx.doi.org/10.4018/ijwsr.2021100101.
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Unexpected faults result in unscheduled cloud outage, which negatively affects the completion of workflow tasks in the cloud. This paper presents a novel PageRank-based fault handling strategy to rescue workflow tasks at the faulty data center. The proposed approach uses a holistic view and considers the task attributes, the timeline scenario, and the overall cloud performance. A priority assignment system is developed based on the modified PageRank algorithm to prioritise workflow tasks. A min-max normalization method is applied to select the target data center and match the timeline at this data center. Additionally, a dynamic PageRank-constrained task scheduling algorithm is proposed to generate the task scheduling solution. The simulation results show that the proposed approach can achieve better fault handling performance, measured by task resilience ratio, workflow resilience ratio, and workflow continuity ratio in both the traditional 3-replica and the image backup cloud environment.
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Nguyên, Toàn, Laurentiu Trifan, and Jean-Antoine Désidéri. "Resilient workflows for computational mechanics platforms." IOP Conference Series: Materials Science and Engineering 10 (June 1, 2010): 012015. http://dx.doi.org/10.1088/1757-899x/10/1/012015.
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Anderson, J. E., A. J. Ross, J. Back, M. Duncan, P. Snell, A. Hopper, and P. Jaye. "Beyond ‘find and fix’: improving quality and safety through resilient healthcare systems." International Journal for Quality in Health Care 32, no. 3 (February 28, 2020): 204–11. http://dx.doi.org/10.1093/intqhc/mzaa007.
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Abstract Objective The aim was to develop a method based on resilient healthcare principles to proactively identify system vulnerabilities and quality improvement interventions. Design Ethnographic methods to understand work as it is done in practice using concepts from resilient healthcare, the Concepts for Applying Resilience Engineering model and the four key activities that are proposed to underpin resilient performance—anticipating, monitoring, responding and learning. Setting Accident and Emergency Department (ED) and the Older People’s Unit (OPU) of a large teaching hospital in central London. Participants ED—observations 104 h, and 14 staff interviews. OPU—observations 60 h, and 15 staff interviews. Results Data were analysed to identify targets for quality improvement. In the OPU, discharge was a complex and variable process that was difficult to monitor. A system to integrate information and clearly show progress towards discharge was needed. In the ED, patient flow was identified as a complex high-intensity activity that was not supported by the existing data systems. The need for a system to integrate and display information about both patient and organizational factors was identified. In both settings, adaptive capacity was limited by the absence of systems to monitor the work environment. Conclusions The study showed that using resilient healthcare principles to inform quality improvement was feasible and focused attention on challenges that had not been addressed by traditional quality improvement practices. Monitoring patient and workflow in both the ED and the OPU was identified as a priority for supporting staff to manage the complexity of the work.
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Lohr, Chaelynne E., Kelly R. B. Sporer, Kelsey A. Brigham, Laura A. Pavliscak, Matelyn M. Mason, Andrew Borgman, Vickie J. Ruggiero, Tasia M. Taxis, Paul C. Bartlett, and Casey J. Droscha. "Phenotypic Selection of Dairy Cattle Infected with Bovine Leukemia Virus Demonstrates Immunogenetic Resilience through NGS-Based Genotyping of BoLA MHC Class II Genes." Pathogens 11, no. 1 (January 15, 2022): 104. http://dx.doi.org/10.3390/pathogens11010104.
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Characterization of the bovine leukocyte antigen (BoLA) DRB3 gene has shown that specific alleles associate with susceptibility or resilience to the progression of bovine leukemia virus (BLV), measured by proviral load (PVL). Through surveillance of multi-farm BLV eradication field trials, we observed differential phenotypes within seropositive cows that persist from months to years. We sought to develop a multiplex next-generation sequencing workflow (NGS-SBT) capable of genotyping 384 samples per run to assess the relationship between BLV phenotype and two BoLA genes. We utilized longitudinal results from milk ELISA screening and subsequent blood collections on seropositive cows for PVL determination using a novel BLV proviral load multiplex qPCR assay to phenotype the cows. Repeated diagnostic observations defined two distinct phenotypes in our study population, ELISA-positive cows that do not harbor detectable levels of provirus and those who do have persistent proviral loads. In total, 565 cows from nine Midwest dairy farms were selected for NGS-SBT, with 558 cows: 168 BLV susceptible (ELISA-positive/PVL-positive) and 390 BLV resilient (ELISA-positive/PVL-negative) successfully genotyped. Three BoLA-DRB3 alleles, including one novel allele, were shown to associate with disease resilience, *009:02, *044:01, and *048:02 were found at rates of 97.5%, 86.5%, and 90.3%, respectively, within the phenotypically resilient population. Alternatively, DRB3*015:01 and *027:03, both known to associate with disease progression, were found at rates of 81.1% and 92.3%, respectively, within the susceptible population. This study helps solidify the immunogenetic relationship between BoLA-DRB3 alleles and BLV infection status of these two phenotypic groupings of US dairy cattle.
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Kim, Hyunjoo, Yaakoub el-Khamra, Ivan Rodero, Shantenu Jha, and Manish Parashar. "Autonomic Management of Application Workflows on Hybrid Computing Infrastructure." Scientific Programming 19, no. 2-3 (2011): 75–89. http://dx.doi.org/10.1155/2011/940242.
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In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints. The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.
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Watson, C. Scott, John R. Elliott, Susanna K. Ebmeier, María Antonieta Vásquez, Camilo Zapata, Santiago Bonilla-Bedoya, Paulina Cubillo, et al. "Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador." Natural Hazards and Earth System Sciences 22, no. 5 (May 20, 2022): 1699–721. http://dx.doi.org/10.5194/nhess-22-1699-2022.
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Abstract. Greenspaces within broader ecosystem-based disaster risk reduction (Eco-DRR) strategies provide multiple benefits to society, biodiversity, and addressing climate breakdown. In this study, we investigated urban growth, its intersection with hazards, and the availability of greenspace for disaster risk reduction (DRR) in the city of Quito, Ecuador, which experiences multiple hazards including landslides, floods, volcanoes, and earthquakes. We used satellite data to quantify urban sprawl and developed a workflow incorporating high-resolution digital elevation models (DEMs) to identify potential greenspaces for emergency refuge accommodation (DRR greenspace), for example, following an earthquake. Quito's historical urban growth totalled ∼ 192 km2 for 1986–2020 and was primarily on flatter land, in some cases crossed by steep ravines. By contrast, future projections indicate an increasing intersection between easterly urbanisation and steep areas of high landslide susceptibility. Therefore, a timely opportunity exists for future risk-informed planning. Our workflow identified 18.6 km2 of DRR greenspaces, of which 16.3 km2 intersected with potential sources of landslide and flood hazards, indicating that hazard events could impact potential “safe spaces”. These spaces could mitigate future risk if designated as greenspaces and left undeveloped. DRR greenspace overlapped 7 % (2.5 km2) with municipality-designated greenspace. Similarly, 10 % (1.7 km2) of municipality-designated “safe space” for use following an earthquake was classified as potentially DRR suitable in our analysis. For emergency refuge, currently designated greenspaces could accommodate ∼ 2 %–14 % (depending on space requirements) of Quito's population within 800 m. This increases to 8 %–40 % considering all the potential DRR greenspace mapped in this study. Therefore, a gap exists between the provision of DRR and designated greenspace. Within Quito, we found a disparity between access to greenspaces across socio-economic groups, with lower income groups having less access and further to travel to designated greenspaces. Notably, the accessibility of greenspaces was high overall with 98 % (2.3 million) of Quito's population within 800 m of a designated greenspace, of which 88 % (2.1 million) had access to potential DRR greenspaces. Our workflow demonstrates a citywide evaluation of DRR greenspace potential and provides the foundation upon which to evaluate these spaces with local stakeholders. Promoting equitable access to greenspaces, communicating their multiple benefits, and considering their use to restrict propagating development into hazardous areas are key themes that emerge for further investigation.
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Platt, Lisa Sundahl, and Ann Fronczek. "Using a Fuzzy Framework for applying King’s Theory of Goal Attainment to Improve Hospital Acquired Infection Resilience." Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 9, no. 1 (September 2020): 275–84. http://dx.doi.org/10.1177/2327857920091037.
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This article explores techniques for estimating Hospital Acquired Infection prevention potential through strategic nursing care delivery design and applied fuzzy frameworks. To achieve this, it evaluates the use of Fuzzy Logic directed by King’s Theory of Nursing Goal Attainment for developing a HAI resilience process model. The purpose of this model is to estimate the performance of environment of care safety based on the ability of nurses to moderate risk and respond adaptively to certain types of hospital-onset infections through strategic workflow design. The aim of this proposed approach would be to help nurses and infection control specialists in healthcare settings better understand what accessible Systems Science-based frameworks may be instrumental for analyzing and forecasting infection control systems improvement. The benefit of using Fuzzy Frameworks in nursing workflow and environment of care planning is that it allows for the leveraging of crystalized intelligence nursing staff have about their patient demography and unit-based workflow. This process allows nurse work designers to introduce and test targeted process or physical improvement strategies that make sense for their unique circumstances while providing better insight into how these interventions may work holistically with all relevant environment of care operations. This approach is made more powerful when guided by trusted optimal nursing theoretical perspectives such as King’s Theory of Goal Attainment.
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Lista, Maria Jose, Pedro M. Matos, Thomas J. A. Maguire, Kate Poulton, Elena Ortiz-Zapater, Robert Page, Helin Sertkaya, et al. "Resilient SARS-CoV-2 diagnostics workflows including viral heat inactivation." PLOS ONE 16, no. 9 (September 15, 2021): e0256813. http://dx.doi.org/10.1371/journal.pone.0256813.
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There is a worldwide need for reagents to perform SARS-CoV-2 detection. Some laboratories have implemented kit-free protocols, but many others do not have the capacity to develop these and/or perform manual processing. We provide multiple workflows for SARS-CoV-2 nucleic acid detection in clinical samples by comparing several commercially available RNA extraction methods: QIAamp Viral RNA Mini Kit (QIAgen), RNAdvance Blood/Viral (Beckman) and Mag-Bind Viral DNA/RNA 96 Kit (Omega Bio-tek). We also compared One-step RT-qPCR reagents: TaqMan Fast Virus 1-Step Master Mix (FastVirus, ThermoFisher Scientific), qPCRBIO Probe 1-Step Go Lo-ROX (PCR Biosystems) and Luna® Universal Probe One-Step RT-qPCR Kit (Luna, NEB). We used primer-probes that detect viral N (EUA CDC) and RdRP. RNA extraction methods provided similar results, with Beckman performing better with our primer-probe combinations. Luna proved most sensitive although overall the three reagents did not show significant differences. N detection was more reliable than that of RdRP, particularly in samples with low viral titres. Importantly, we demonstrated that heat treatment of nasopharyngeal swabs at 70°C for 10 or 30 min, or 90°C for 10 or 30 min (both original variant and B 1.1.7) inactivated SARS-CoV-2 employing plaque assays, and had minimal impact on the sensitivity of the qPCR in clinical samples. These findings make SARS-CoV-2 testing portable in settings that do not have CL-3 facilities. In summary, we provide several testing pipelines that can be easily implemented in other laboratories and have made all our protocols and SOPs freely available at https://osf.io/uebvj/.
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Hamati, Mary C., Atlee Witt, Michaele Francesco Corbisiero, Michael Tuffiash, and Kenneth J. Hunt. "Tracking Patient Reported Outcomes in Orthopaedic Surgical Patients at a Single Institution." Foot & Ankle Orthopaedics 7, no. 1 (January 2022): 2473011421S0022. http://dx.doi.org/10.1177/2473011421s00225.
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Category: Ankle; Other Introduction/Purpose: As the American healthcare system evolves into a value-based reimbursement model, emphasis on tracking and reporting healthcare outcomes has expounded. Patient reported outcome Measures (PROMs) are exceedingly valuable to orthopedists as a means to measure improvement and satisfy regulatory requirements. The NIH Patient-Reported Outcomes Measurement Information System (PROMIS) surveys are favored due to their accessibility, efficiency, and minimal floor and ceiling effects. Furthermore, they have been shown to predict outcomes after orthopedic surgeries. Psychosocial factors have also become increasingly important in predicting surgical outcomes. We aim to report the development and implementation of an institutional PRO data collection platform, including PRO completion rates and improvements in PROs for patients undergoing orthopaedic surgery. Methods: We implemented a secure, HIPAA compliant, automated and EHR integrated, institutional platform to collect PROMs using a cloud-based tool. Patients undergoing surgery by sports medicine and foot and ankle surgeons were included and organized into four surgical pathways: (1) foot and ankle, (2) sports-knee, (3) sports-hip, and (4) sports-shoulder. PROMIS Physical Function (PF), PROMIS Pain interference (PI), site-specific (foot and ankle, knee, hip, and shoulder) Single Assessment Numeric Evaluation (SANE), and the brief resiliency scale (BRS) were collected at the patient's pre-operative visit. The PROMIS and SANE surveys were again collected at 3-, 6-, and 12-month post-operative visits. Surveys were disseminated automatically and patients were able to complete PROMs onsite on secure tablets or remotely through their personal device. Primary outcomes included compliance rates, baseline PRO scores, and change in scores at the various post-operative timepoints for patients in the four surgical pathways. Results: More than 6,000 patients were included, with majority of patients from the sports-knee (47%), followed by sports- shoulder (27%), foot and ankle (23%), and sports-hip (4%) pathways. Average completion rate was highest at the pre-operative timepoint for all pathways (81%), with completion rates of 62% at 50% at 6 months and 45% at 12MO. Compliance rates were lowest highest in the foot and ankle pathway at 12 months (62%). Average baseline scores for all patients were 40.8 for PROMIS PF, 61.1 PROMIS PI, 41 SANE, and 3.9 for BRS. Baseline scores didn't significantly vary between the surgical pathways. Scores improved for all patient pathways at all timepoints for PROMIS PF, PI and SANE PROMs (Table 1). No workflow disruptions were noted for survey administration. Conclusion: Tracking PROs using an automated platform is feasible in orthopaedic clinics. Compliance rates are very good and dependent on provider, staff, and patient buy-in. Patients undergoing surgery had an average baseline PROMIS PI scores >=1 standard deviation from the normal population and all scores improved after surgery. Importantly, statistical significance doesn't always reflect minimum clinically important differences (MCIDs). MCIDs for PROMIS PF and PI have been reported to fall between 5-10 points depending on range of values and methods of calculation. Further investigation into outcomes by procedure type and patient factors is warranted to identify predictive factors of surgical outcomes.
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Xu, Jinwen, and Yi Qiang. "Spatial Assessment of Community Resilience from 2012 Hurricane Sandy Using Nighttime Light." Remote Sensing 13, no. 20 (October 15, 2021): 4128. http://dx.doi.org/10.3390/rs13204128.
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Quantitative assessment of community resilience is a challenge due to the lack of empirical data about human dynamics in disasters. To fill the data gap, this study explores the utility of nighttime lights (NTL) remote sensing images in assessing community recovery and resilience in natural disasters. Specifically, this study utilized the newly-released NASA moonlight-adjusted SNPP-VIIRS daily images to analyze spatiotemporal changes of NTL radiance in Hurricane Sandy (2012). Based on the conceptual framework of recovery trajectory, NTL disturbance and recovery during the hurricane were calculated at different spatial units and analyzed using spatial analysis tools. Regression analysis was applied to explore relations between the observed NTL changes and explanatory variables, such as wind speed, housing damage, land cover, and Twitter keywords. The result indicates potential factors of NTL changes and urban-rural disparities of disaster impacts and recovery. This study shows that NTL remote sensing images are a low-cost instrument to collect near-real-time, large-scale, and high-resolution human dynamics data in disasters, which provide a novel insight into community recovery and resilience. The uncovered spatial disparities of community recovery help improve disaster awareness and preparation of local communities and promote resilience against future disasters. The systematical documentation of the analysis workflow provides a reference for future research in the application of SNPP-VIIRS daily images.
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Tinte, Morena M., Kekeletso H. Chele, Justin J. J. van der Hooft, and Fidele Tugizimana. "Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview." Metabolites 11, no. 7 (July 8, 2021): 445. http://dx.doi.org/10.3390/metabo11070445.
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Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.
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Tayeen, Abu Saleh Md, Thanh Hai Nguyen, Van Duc Nguyen, and Enrico Pontelli. "Design and Implementation of Phylotastic, a Service Architecture for Evolutionary Biology." International Journal of Software Engineering and Knowledge Engineering 30, no. 10 (October 2020): 1525–50. http://dx.doi.org/10.1142/s0218194020500382.
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Access and reuse of authoritative phylogenetic knowledge have been a longstanding challenges in the evolutionary biology community — leading to a number of research efforts (e.g. focused on interoperation, standardization of formats, and development of minimum reporting requirements). The Phylotastic project was launched to provide an answer to such challenges — as an architectural concept collaboratively designed by evolutionary biologists and computer scientists. This paper describes the first comprehensive implementation of the Phylotastic architecture, based on an open platform for Web services composition. The implementation provides a portal, which composes Web services along a fixed collection of workflows, as well as an interface to allow users to develop novel workflows. The Web services composition is guided by automated planning algorithms and built on a Web services registry and an execution monitoring engine. The platform provides resilience through seamless automated recovery from failed services.
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Winckers, Laurent A., Chris T. Evelo, Egon L. Willighagen, and Martina Kutmon. "Investigating the Molecular Processes behind the Cell-Specific Toxicity Response to Titanium Dioxide Nanobelts." International Journal of Molecular Sciences 22, no. 17 (August 30, 2021): 9432. http://dx.doi.org/10.3390/ijms22179432.
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Some engineered nanomaterials incite toxicological effects, but the underlying molecular processes are understudied. The varied physicochemical properties cause different initial molecular interactions, complicating toxicological predictions. Gene expression data allow us to study the responses of genes and biological processes. Overrepresentation analysis identifies enriched biological processes using the experimental data but prompts broad results instead of detailed toxicological processes. We demonstrate a targeted filtering approach to compare public gene expression data for low and high exposure on three cell lines to titanium dioxide nanobelts. Our workflow finds cell and concentration-specific changes in affected pathways linked to four Gene Ontology terms (apoptosis, inflammation, DNA damage, and oxidative stress) to select pathways with a clear toxicity focus. We saw more differentially expressed genes at higher exposure, but our analysis identifies clear differences between the cell lines in affected processes. Colorectal adenocarcinoma cells showed resilience to both concentrations. Small airway epithelial cells displayed a cytotoxic response to the high concentration, but not as strongly as monocytic-like cells. The pathway-gene networks highlighted the gene overlap between altered toxicity-related pathways. The automated workflow is flexible and can focus on other biological processes by selecting other GO terms.
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Ferreira da Silva, Rafael, Rosa Filgueira, Ewa Deelman, Erola Pairo-Castineira, Ian M. Overton, and Malcolm P. Atkinson. "Using simple PID-inspired controllers for online resilient resource management of distributed scientific workflows." Future Generation Computer Systems 95 (June 2019): 615–28. http://dx.doi.org/10.1016/j.future.2019.01.015.
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Usynin, Dmitrii, Daniel Rueckert, Jonathan Passerat-Palmbach, and Georgios Kaissis. "Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning." Proceedings on Privacy Enhancing Technologies 2022, no. 1 (November 20, 2021): 274–90. http://dx.doi.org/10.2478/popets-2022-0014.
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Abstract In this study, we aim to bridge the gap between the theoretical understanding of attacks against collaborative machine learning workflows and their practical ramifications by considering the effects of model architecture, learning setting and hyperparameters on the resilience against attacks. We refer to such mitigations as model adaptation. Through extensive experimentation on both, benchmark and real-life datasets, we establish a more practical threat model for collaborative learning scenarios. In particular, we evaluate the impact of model adaptation by implementing a range of attacks belonging to the broader categories of model inversion and membership inference. Our experiments yield two noteworthy outcomes: they demonstrate the difficulty of actually conducting successful attacks under realistic settings when model adaptation is employed and they highlight the challenge inherent in successfully combining model adaptation and formal privacy-preserving techniques to retain the optimal balance between model utility and attack resilience.
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Lenert, Matthew C., Michael E. Matheny, and Colin G. Walsh. "Prognostic models will be victims of their own success, unless…" Journal of the American Medical Informatics Association 26, no. 12 (September 3, 2019): 1645–50. http://dx.doi.org/10.1093/jamia/ocz145.
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Abstract Predictive analytics have begun to change the workflows of healthcare by giving insight into our future health. Deploying prognostic models into clinical workflows should change behavior and motivate interventions that affect outcomes. As users respond to model predictions, downstream characteristics of the data, including the distribution of the outcome, may change. The ever-changing nature of healthcare necessitates maintenance of prognostic models to ensure their longevity. The more effective a model and intervention(s) are at improving outcomes, the faster a model will appear to degrade. Improving outcomes can disrupt the association between the model’s predictors and the outcome. Model refitting may not always be the most effective response to these challenges. These problems will need to be mitigated by systematically incorporating interventions into prognostic models and by maintaining robust performance surveillance of models in clinical use. Holistically modeling the outcome and intervention(s) can lead to resilience to future compromises in performance.
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Rodríguez-Pascual, Manuel, Christos Kanellopoulos, Antonio Juan Rubio-Montero, Diego Darriba, Ognjen Prnjat, David Posada, and Rafael Mayo-García. "Adapting Reproducible Research Capabilities to Resilient Distributed Calculations." International Journal of Grid and High Performance Computing 8, no. 1 (January 2016): 58–69. http://dx.doi.org/10.4018/ijghpc.2016010105.
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Nowadays, computing calculations are becoming more and more demanding due to the huge pool of resources available. This demand must be satisfied in terms of computational efficiency and resilience, which is compromised in distributed and heterogeneous platforms. Not only this, data obtained are often either reused by other researchers or recalculated. In this work, a set of tools to overcome the problem of creating and executing fault tolerant distributed applications on dynamic environments is presented. Such a set also ensures the reproducibility of the performed experiments providing a portable, unattended and resilient framework that encapsulates the infrastructure-dependent operations away from the application developers and users, allowing performing experiments based on Open Access data repositories. In this way, users can seamlessly search and lately access datasets that can be automatically retrieved as input data into a code already integrated in the proposed workflow. Such a search is based on metadata standards and relies on Persistent Identifiers (PID) to assign specific repositories. The applications profit from Distributed Toolbox, a framework devoted to the creation and execution of distributed applications and includes tools for unattended cluster and grid execution, where a total fault tolerance is provided. By decoupling the definition of the remote tasks from its execution and control, the development, execution and maintenance of distributed applications is significantly simplified with respect to previous solutions, increasing their robustness and allowing running them on different computational platforms with little effort. The integration with Open Access databases and employment of PIDs for long-lasting references ensures that the data related to the experiments will persist, closing a complete research circle of data access/processing/storage/dissemination of results.
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Glas, Hanne, Ivan Rocabado, Steven Huysentruyt, Edith Maroy, Danitza Salazar Cortez, Kobe Coorevits, Philippe De Maeyer, and Greet Deruyter. "Flood Risk Mapping Worldwide: A Flexible Methodology and Toolbox." Water 11, no. 11 (November 13, 2019): 2371. http://dx.doi.org/10.3390/w11112371.
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Flood risk assessments predict the potential consequences of flooding, leading to more effective risk management and strengthening resilience. However, adequate assessments rely on large quantities of high-quality input data. Developing regions lack reliable data or funds to acquire them. Therefore, this research has developed a flexible, low-cost methodology for mapping flood hazard, vulnerability and risk. A generic methodology was developed and customized for freely available data with global coverage, enabling risk assessment worldwide. The default workflow can be enriched with region-specific information when available. The practical application is assured by a modular toolbox developed on GDAL and PCRASTER. This toolbox was tested for the catchment of the river Moustiques, Haiti, for which several flood hazard maps were developed. Then, the toolbox was used to create social, economic and physical vulnerability maps. These were combined with the hazard maps to create the three corresponding flood risk maps. After creating these with the default data, more detailed information, gathered during field work, was added to verify the results of the basic workflow. These first tests of the developed toolbox show promising results. The toolbox allows policy makers in developing countries to perform reliable flood risk assessments and generate the necessary maps.
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Supasri, Kanoknate M., Manoj Kumar, Mano J. Mathew, Bethany Signal, Matthew P. Padula, David J. Suggett, and Peter J. Ralph. "Evaluation of Filter, Paramagnetic, and STAGETips Aided Workflows for Proteome Profiling of Symbiodiniaceae Dinoflagellate." Processes 9, no. 6 (June 2, 2021): 983. http://dx.doi.org/10.3390/pr9060983.
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The integrity of coral reef ecosystems worldwide rests on a fine-tuned symbiotic interaction between an invertebrate and a dinoflagellate microalga from the family Symbiodiniaceae. Recent advances in bottom-up shotgun proteomic approaches and the availability of vast amounts of genetic information about Symbiodiniaceae have provided a unique opportunity to better understand the molecular mechanisms underpinning the interactions of coral-Symbiodiniaceae. However, the resilience of this dinoflagellate cell wall, as well as the presence of polyanionic and phenolics cell wall components, requires the optimization of sample preparation techniques for successful implementation of bottom-up proteomics. Therefore, in this study we compare three different workflows—filter-aided sample preparation (FASP), single-pot solid-phase-enhanced sample preparation (SP3), and stop-and-go-extraction tips (STAGETips, ST)—to develop a high-throughput proteotyping protocol for Symbiodiniaceae algal research. We used the model isolate Symbiodinium tridacnidorum. We show that SP3 outperformed ST and FASP with regard to robustness, digestion efficiency, and contaminant removal, which led to the highest number of total (3799) and unique proteins detected from 23,593 peptides. Most of these proteins were detected with ≥2 unique peptides (73%), zero missed tryptic peptide cleavages (91%), and hydrophilic peptides (>70%). To demonstrate the functionality of this optimized SP3 sample preparation workflow, we examined the proteome of S. tridacnidorum to better understand the molecular mechanism of peridinin-chlorophyll-protein complex (PCP, light harvesting protein) accumulation under low light (LL, 30 μmol photon m−2 s−1). Cells exposed to LL for 7 days upregulated various light harvesting complex (LHCs) proteins through the mevalonate-independent pathway; proteins of this pathway were at 2- to 6-fold higher levels than the control of 120 μmol photon m−2 s−1. Potentially, LHCs which were maintained in an active phosphorylated state by serine/threonine-protein kinase were also upregulated to 10-fold over control. Collectively, our results show that the SP3 method is an efficient high-throughput proteotyping tool for Symbiodiniaceae algal research.
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Lu, Xinzheng, Qingle Cheng, Zhen Xu, Yongjia Xu, and Chujin Sun. "Real-Time City-Scale Time-History Analysis and Its Application in Resilience-Oriented Earthquake Emergency Responses." Applied Sciences 9, no. 17 (August 24, 2019): 3497. http://dx.doi.org/10.3390/app9173497.
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The resilience of cities has received worldwide attention. An accurate and rapid assessment of seismic damage, economic loss, and post-event repair time can provide an important reference for emergency rescue and post-earthquake recovery. Based on city-scale nonlinear time-history analysis (THA) and regional seismic loss prediction, a real-time city-scale time-history analysis method is proposed in this work. In this method, the actual ground motion records obtained from seismic stations are input into the building models of the earthquake-stricken area, and the nonlinear time-history analysis of these models is subsequently performed using a high-performance computing platform. The seismic damage to the buildings in the target region subjected to this earthquake is evaluated according to the analysis results. The economic loss and repair time of the earthquake-stricken areas are calculated using the engineering demand parameters obtained from the time-history analysis. A program named, “Real-time Earthquake Damage Assessment using City-scale Time-history analysis” (“RED-ACT” for short) was developed to automatically implement the above workflow. The method proposed in this work has been applied in many earthquake events, and provides a useful reference for scientific decision making for earthquake disaster relief, which is of great significance to enhancing the resilience of earthquake-stricken areas.
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Nyerges, Timothy, John A. Gallo, Steven D. Prager, Keith M. Reynolds, Philip J. Murphy, and WenWen Li. "Synthesizing Vulnerability, Risk, Resilience, and Sustainability into VRRSability for Improving Geoinformation Decision Support Evaluations." ISPRS International Journal of Geo-Information 10, no. 3 (March 18, 2021): 179. http://dx.doi.org/10.3390/ijgi10030179.
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This paper synthesizes vulnerability, risk, resilience, and sustainability (VRRS) in a way that can be used for decision evaluations about sustainable systems, whether such systems are called coupled natural–human systems, social–ecological systems, coupled human–environment systems, and/or hazards influencing global environmental change, all considered geospatial open systems. Evaluations of V-R-R-S as separate concepts for complex decision problems are important, but more insightful when synthesized for improving integrated decision priorities based on trade-offs of V-R-R-S objectives. A synthesis concept, called VRRSability, provides an overarching perspective that elucidates Tier 2 of a previously developed four-tier framework for organizing measurement-informed ontology and epistemology for sustainability information representation (MOESIR). The new synthesis deepens the MOESIR framework to address VRRSability information representation and clarifies the Tier 2 layer of abstraction. This VRRSability synthesis, composed of 13 components (several with sub-components), offers a controlled vocabulary as the basis of a conceptual framework for organizing workflow assessment and intervention strategies as part of geoinformation decision support software. Researchers, practitioners, and machine learning algorithms can use the vocabulary results for characterizing functional performance relationships between elements of geospatial open systems and the computing technology systems used for evaluating them within a context of complex sustainable systems.
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Marmolejo-Martínez-Artesero, Sara, Caty Casas, and David Romeo-Guitart. "Endogenous Mechanisms of Neuroprotection: To Boost or Not to Be." Cells 10, no. 2 (February 10, 2021): 370. http://dx.doi.org/10.3390/cells10020370.
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Postmitotic cells, like neurons, must live through a lifetime. For this reason, organisms/cells have evolved with self-repair mechanisms that allow them to have a long life. The discovery workflow of neuroprotectors during the last years has focused on blocking the pathophysiological mechanisms that lead to neuronal loss in neurodegeneration. Unfortunately, only a few strategies from these studies were able to slow down or prevent neurodegeneration. There is compelling evidence demonstrating that endorsing the self-healing mechanisms that organisms/cells endogenously have, commonly referred to as cellular resilience, can arm neurons and promote their self-healing. Although enhancing these mechanisms has not yet received sufficient attention, these pathways open up new therapeutic avenues to prevent neuronal death and ameliorate neurodegeneration. Here, we highlight the main endogenous mechanisms of protection and describe their role in promoting neuron survival during neurodegeneration.
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Vetter, Michael. "MODEL-BASED SECURITY ANALYSIS OF FPGA DESIGNS THROUGH REINFORCEMENT LEARNING." Acta Polytechnica 59, no. 5 (November 1, 2019): 518–26. http://dx.doi.org/10.14311/ap.2019.59.0518.
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Finding potential security weaknesses in any complex IT system is an important and often challenging task best started in the early stages of the development process. We present a method that transforms this task for FPGA designs into a reinforcement learning (RL) problem. This paper introduces a method to generate a Markov Decision Process based RL model from a formal, high-level system description (formulated in the domain-specific language) of the system under review and different, quantified assumptions about the system’s security. Probabilistic transitions and the reward function can be used to model the varying resilience of different elements against attacks and the capabilities of an attacker. This information is then used to determine a plausible data exfiltration strategy. An example with multiple scenarios illustrates the workflow. A discussion of supplementary techniques like hierarchical learning and deep neural networks concludes this paper.
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HUNG, PATRICK C. K., KAMALAKAR KARLAPALEM, and JAMES GRAY. "LEAST PRIVILEGE SECURITY IN CAPBASED-AMS." International Journal of Cooperative Information Systems 08, no. 02n03 (June 1999): 139–68. http://dx.doi.org/10.1142/s0218843099000083.
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Workflow systems are becoming very popular and are being used to support many of the day to day activities in large organizations. One of the major problems with workflow systems is that they often use heterogeneous and distributed hardware and software systems to execute a given activity. This gives rise to decentralized security policies and mechanisms, which, in order to enable activity execution, give too many privileges (for accessing resources like documents) to the agents (humans or systems) for executing the work. We develop the concept of least priviledge, wherein the set of agents are given just enough privileges to complete the given activities. We develop our concepts in the context of CapBasED-AMS (Capability-based and Event-driven Activity Management System). The CapBasED-AMS deals with the management and execution of activities. An activity consists of multiple inter-dependent tasks (atomic activities, each executed by a single agent) that need to be coordinated, scheduled and executed by a set of agents. We formalize the concept of least privilege security and present algorithms to statically assign least privilege assignment to the agents. Further, we develop the concept of dynamic least privilege enforcement, wherein an agent is given its privileges only during the duration of the task for which those privileges were assigned. We also develop the concept of dynamic evolution of least privileges by taking into consideration the changes in the way resources are accessed by the agents in executing their tasks. Finally, we address the trade-off between resilience to agent failure and least privilege.
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Sánchez-Carballido, Sergio, Orti Senderos, Marcos Nieto, and Oihana Otaegui. "Semi-Automatic Cloud-Native Video Annotation for Autonomous Driving." Applied Sciences 10, no. 12 (June 23, 2020): 4301. http://dx.doi.org/10.3390/app10124301.
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An innovative solution named Annotation as a Service (AaaS) has been specifically designed to integrate heterogeneous video annotation workflows into containers and take advantage of a cloud native highly scalable and reliable design based on Kubernetes workloads. Using the AaaS as a foundation, the execution of automatic video annotation workflows is addressed in the broader context of a semi-automatic video annotation business logic for ground truth generation for Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADAS). The document presents design decisions, innovative developments, and tests conducted to provide scalability to this cloud-native ecosystem for semi-automatic annotation. The solution has proven to be efficient and resilient on an AD/ADAS scale, specifically in an experiment with 25 TB of input data to annotate, 4000 concurrent annotation jobs, and 32 worker nodes forming a high performance computing cluster with a total of 512 cores, and 2048 GB of RAM. Automatic pre-annotations with the proposed strategy reduce the time of human participation in the annotation up to 80% maximum and 60% on average.
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Spiegelhalter, T., and L. C. Werner. "Methods for In-Silico Environmental Resilience, 2018 to 2100." IOP Conference Series: Earth and Environmental Science 1078, no. 1 (September 1, 2022): 012139. http://dx.doi.org/10.1088/1755-1315/1078/1/012139.
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Abstract The research focuses on Genetic Water-Energy-Food Nexus Design Research Scenarios for Miami’s Greater Islands. The Paris Agreement - 21st international Conference of Parties (COP 21) to the United Nations Framework Convention on Climate Change (UNFCCC) supports professional and municipal architecture and urban design practice emphasizing greenhouse gas reductions and carbon-neutral city planning and operations. In this respect, Miami benefits through multiple large-scale grants focusing on strategic solutions to combat and adapt to the effects of global warming, sea-level rise, flooding, hurricane impacts, and salt-water intrusion [1]. This paper presents research findings funded by a four-year transdisciplinary research project CRUNCH by EU agencies and the US-National Science Foundation in partnership with nineteen partners from six countries. It illuminates two transdisciplinary methods to produce bio-inspired infrastructural, architectural, and urban scale scenarios from 2018 to 2100. The silico-oriented research location is in Miami, proposing a trans-locational application envisaged in Berlin. The first method is based on parametric-algorithmic, generative design research workflows. The second utilizes synthetic biology through bio-scripting in collaboration with Autodesk. Both methods merge through the integration of cloud-based artificial intelligence and machine learning simulation engines. The research goals are to support international governments regarding sustainability master plans, and secondly, to raise and increase awareness towards urgent and societal relevant resilience topics for the future of human habitats. Scenario simulations are generated by the Florida International University (FIU) Miami research team at the Urban Living Lab (ULL), the GIS department, and two coastal cities in Miami Dade with low-lying areas. The ULL’s research sectors include green-blue infrastructures to combat sea-level rise, synthetic biology scripting, robotic urban farming, local food production and hydroponics, mixed renewable energy design. In addition, and carbon-neutral power generation with adaptive infrastructure projects that support the local and regional Food-Energy-Water Nexus.
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Kinney, Ashley, Quyen Bui, Jane Hodding, and Jennifer Le. "Pharmacy Dashboard: An Innovative Process for Pharmacy Workload and Productivity." Hospital Pharmacy 52, no. 3 (March 2017): 198–206. http://dx.doi.org/10.1310/hpj5203-198.
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Background Innovative approaches, including LEAN systems and dashboards, to enhance pharmacy production continue to evolve in a cost and safety conscious health care environment. Furthermore, implementing and evaluating the effectiveness of these novel methods continues to be challenging for pharmacies. Objective To describe a comprehensive, real-time pharmacy dashboard that incorporated LEAN methodologies and evaluate its utilization in an inpatient Central Intravenous Additives Services (CIVAS) pharmacy. Methods Long Beach Memorial Hospital (462 adult beds) and Miller Children's and Women's Hospital of Long Beach (combined 324 beds) are tertiary not-for-profit, community-based hospitals that are served by one CIVAS pharmacy. Metrics to evaluate the effectiveness of CIVAS were developed and implemented on a dashboard in real-time from March 2013 to March 2014. Results The metrics that were designed and implemented to evaluate the effectiveness of CIVAS were quality and value, financial resilience, and the department's people and culture. Using a dashboard that integrated these metrics, the accuracy of manufacturing defect-free products was ≥99.9%, indicating excellent quality and value of CIVAS. The metric for financial resilience demonstrated a cost savings of $78,000 annually within pharmacy by eliminating the outsourcing of products. People and value metrics on the dashboard focused on standard work, with an overall 94.6% compliance to the workflow. Conclusion A unique dashboard that incorporated metrics to monitor 3 important areas was successfully implemented to improve the effectiveness of CIVAS pharmacy. These metrics helped pharmacy to monitor progress in real-time, allowing attainment of production goals and fostering continuous quality improvement through LEAN work.
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Angelats, E., J. Soriano-González, M. Fernández-Tejedor, and C. Alcaraz. "COMBINED FLOODING AND WATER QUALITY MONITORING DURING SHORT EXTREME EVENTS USING SENTINEL 2: THE CASE STUDY OF GLORIA STORM IN EBRO DELTA." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (May 17, 2022): 361–68. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-361-2022.
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Abstract. Short extreme events have significant impact on landscape and ecosystems in low-lying and exposed areas such as deltaic systems. In this context, this paper proposes a combined methodology for the mapping and monitoring of the flooding and water quality dynamics of coastal areas under extreme storms from Sentinel 2 imagery. The proposed methodology has been applied in a coastal bay of the Ebro Delta (Catalonia, NE Spain) to evaluate jointly the impact of Gloria storm (January 2020) in land-flooding and water quality. The experimental results show that the Gloria storm had a strong morphological impact and altered the water quality (chl-a) dynamics. The results show a recovery in terms of water quality after some weeks but in contrast the coastal morphology did not show the same degree of resilience. This paper is the first step of an overall goal that is to set the bases in a long term, for a workflow for rapid response and continuous monitoring of storm effects in coastal areas and/or highly valuable ecosystems such as the Ebro Delta.
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Rist, Florian, Doreen Gabriel, Jennifer Mack, Volker Steinhage, Reinhard Töpfer, and Katja Herzog. "Combination of an Automated 3D Field Phenotyping Workflow and Predictive Modelling for High-Throughput and Non-Invasive Phenotyping of Grape Bunches." Remote Sensing 11, no. 24 (December 10, 2019): 2953. http://dx.doi.org/10.3390/rs11242953.
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In grapevine breeding, loose grape bunch architecture is one of the most important selection traits, contributing to an increased resilience towards Botrytis bunch rot. Grape bunch architecture is mainly influenced by the berry number, berry size, the total berry volume, and bunch width and length. For an objective, precise, and high-throughput assessment of these architectural traits, the 3D imaging sensor Artec® Spider was applied to gather dense point clouds of the visible side of grape bunches directly in the field. Data acquisition in the field is much faster and non-destructive in comparison to lab applications but results in incomplete point clouds and, thus, mostly incomplete phenotypic values. Therefore, lab scans of whole bunches (360°) were used as ground truth. We observed strong correlations between field and lab data but also shifts in mean and max values, especially for the berry number and total berry volume. For this reason, the present study is focused on the training and validation of different predictive regression models using 3D data from approximately 2000 different grape bunches in order to predict incomplete bunch traits from field data. Modeling concepts included simple linear regression and machine learning-based approaches. The support vector machine was the best and most robust regression model, predicting the phenotypic traits with an R2 of 0.70–0.91. As a breeding orientated proof-of-concept, we additionally performed a Quantitative Trait Loci (QTL)-analysis with both the field modeled and lab data. All types of data resulted in joint QTL regions, indicating that this innovative, fast, and non-destructive phenotyping method is also applicable for molecular marker development and grapevine breeding research.
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Lercari, Nicola, Denise Jaffke, Arianna Campiani, Anaïs Guillem, Scott McAvoy, Gerardo Jiménez Delgado, and Alexandra Bevk Neeb. "Building Cultural Heritage Resilience through Remote Sensing: An Integrated Approach Using Multi-Temporal Site Monitoring, Datafication, and Web-GL Visualization." Remote Sensing 13, no. 20 (October 15, 2021): 4130. http://dx.doi.org/10.3390/rs13204130.
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In the American West, wildfires and earthquakes are increasingly threatening the archaeological, historical, and tribal resources that define the collective identity and connection with the past for millions of Americans. The loss of said resources diminishes societal understanding of the role cultural heritage plays in shaping our present and future. This paper examines the viability of employing stationary and SLAM-based terrestrial laser scanning, close-range photogrammetry, automated surface change detection, GIS, and WebGL visualization techniques to enhance the preservation of cultural resources in California. Our datafication approach combines multi-temporal remote sensing monitoring of historic features with legacy data and collaborative visualization to document and evaluate how environmental threats affect built heritage. We tested our methodology in response to recent environmental threats from wildfire and earthquakes at Bodie, an iconic Gold Rush-era boom town located on the California and Nevada border. Our multi-scale results show that the proposed approach effectively integrates highly accurate 3D snapshots of Bodie’s historic buildings before/after disturbance, or post-restoration, with surface change detection and online collaborative visualization of 3D geospatial data to monitor and preserve important cultural resources at the site. This study concludes that the proposed workflow enhances the monitoring of at-risk California’s cultural heritage and makes a call to action to employ remote sensing as a pathway to advanced planning.
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Mei, Yueli, Xiuyun Guo, Zhihao Chen, and Yingzhi Chen. "An Effective Mechanism for the Early Detection and Containment of Healthcare Worker Infections in the Setting of the COVID-19 Pandemic: A Systematic Review and Meta-Synthesis." International Journal of Environmental Research and Public Health 19, no. 10 (May 13, 2022): 5943. http://dx.doi.org/10.3390/ijerph19105943.
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The COVID-19 pandemic has exposed healthcare workers (HCWs) to serious infection risks. In this context, the proactive monitoring of HCWs is the first step toward reducing intrahospital transmissions and safeguarding the HCW population, as well as reflecting the preparedness and response of the healthcare system. As such, this study systematically reviewed the literature on evidence-based effective monitoring measures for HCWs during the COVID-19 pandemic. This was followed by a meta-synthesis to compile the key findings, thus, providing a clearer overall understanding of the subject. Effective monitoring measures of syndromic surveillance, testing, contact tracing, and exposure management are distilled and further integrated to create a whole-process monitoring workflow framework. Taken together, a mechanism for the early detection and containment of HCW infections is, thus, constituted, providing a composite set of practical recommendations to healthcare facility leadership and policy makers to reduce nosocomial transmission rates while maintaining adequate staff for medical services. In this regard, our study paves the way for future studies aimed at strengthening surveillance capacities and upgrading public health system resilience, in order to respond more efficiently to future pandemic threats.
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Brédif, M., L. Caraffa, M. Yirci, and P. Memari. "PROVABLY CONSISTENT DISTRIBUTED DELAUNAY TRIANGULATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 195–202. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-195-2020.
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Abstract. This paper deals with the distributed computation of Delaunay triangulations of massive point sets, mainly motivated by the needs of a scalable out-of-core surface reconstruction workflow from massive urban LIDAR datasets. Such a data often corresponds to a huge point cloud represented through a set of tiles of relatively homogeneous point sizes. This will be the input of our algorithm which will naturally partition this data across multiple processing elements. The distributed computation and communication between processing elements is orchestrated efficiently through an uncentralized model to represent, manage and locally construct the triangulation corresponding to each tile. Initially inspired by the star splaying approach, we review the Tile& Merge algorithm for computing Distributed Delaunay Triangulations on the cloud, provide a theoretical proof of correctness of this algorithm, and analyse the performance of our Spark implementation in terms of speedup and strong scaling in both synthetic and real use case datasets. A HPC implementation (e.g. using MPI), left for future work, would benefit from its more efficient message passing paradigm but lose the robustness and failure resilience of our Spark approach.
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Krassakis, Pavlos, Andreas Karavias, Evangelia Zygouri, Christos Roumpos, Georgios Louloudis, Konstantina Pyrgaki, Nikolaos Koukouzas, Thomas Kempka, and Dimitris Karapanos. "GIS-Based Assessment of Hybrid Pumped Hydro Storage as a Potential Solution for the Clean Energy Transition: The Case of the Kardia Lignite Mine, Western Greece." Sensors 23, no. 2 (January 4, 2023): 593. http://dx.doi.org/10.3390/s23020593.
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Planned decommissioning of coal-fired plants in Europe requires innovative technical and economic strategies to support coal regions on their path towards a climate-resilient future. The repurposing of open pit mines into hybrid pumped hydro power storage (HPHS) of excess energy from the electric grid, and renewable sources will contribute to the EU Green Deal, increase the economic value, stabilize the regional job market and contribute to the EU energy supply security. This study aims to present a preliminary phase of a geospatial workflow used to evaluate land suitability by implementing a multi-criteria decision making (MCDM) technique with an advanced geographic information system (GIS) in the context of an interdisciplinary feasibility study on HPHS in the Kardia lignite open pit mine (Western Macedonia, Greece). The introduced geospatial analysis is based on the utilization of the constraints and ranking criteria within the boundaries of the abandoned mine regarding specific topographic and proximity criteria. The applied criteria were selected from the literature, while for their weights, the experts’ judgement was introduced by implementing the analytic hierarchy process (AHP), in the framework of the ATLANTIS research program. According to the results, seven regions were recognized as suitable, with a potential energy storage capacity from 1.09 to 5.16 GWh. Particularly, the present study’s results reveal that 9.27% (212,884 m2) of the area had a very low suitability, 15.83% (363,599 m2) had a low suitability, 23.99% (550,998 m2) had a moderate suitability, 24.99% (573,813 m2) had a high suitability, and 25.92% (595,125 m2) had a very high suitability for the construction of the upper reservoir. The proposed semi-automatic geospatial workflow introduces an innovative tool that can be applied to open pit mines globally to identify the optimum design for an HPHS system depending on the existing lower reservoir.
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Zhang, Shihao, Junhe Tan, Junhang Liu, Jiaqi Wang, and Ata Tara. "Suitability Prediction and Enhancement of Future Water Supply Systems in Barwon Region in Victoria, Australia." Land 11, no. 5 (April 23, 2022): 621. http://dx.doi.org/10.3390/land11050621.
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Intensive agricultural production accompanied by the climate change impacts in post-Colonial rural landscapes have continuously increased the demand for water resources and coastal areas, showing an unprecedented water supply crisis. By taking extreme weather conditions and rainfall events for future trends, a resilient water storage facility for the landscape requires the collaborative approach of natural systems and simulation modelling techniques to develop sustainable future scenarios. In this study, an ecological suitability model is used to identify potential sites for the construction of multi-purpose dams. As part of the model structure, multi factors are classified using the patterns of changing landscapes, and then weighted overlay analysis is conducted on a Geographic Information System (GIS) platform. Compared to previous studies, this paper derives its principal impact parameters and projections based on historical land cover information. The suitability maps that are generated visually guide the geographical location of the multi-purpose dams and indicate the areas from highly suitable to least suitable, clarifying the possibility of building blue infrastructure alongside the waterways in west-central Barwon. The workflow proposes a resilient water system based on existing land characteristics and measures that future water storage capacity will be a valid increase of approximately 1.5 times. This strategy alleviates water scarcity during the dry season to benefit traditional agricultural activities. Digital calculations are utilized to demonstrate the feasibility of the experimental results, providing a methodology for regulating the distribution and supply of river flows throughout the year while retaining runoff in a hierarchical pattern at precipitation periods.
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Shah, Amika, Milena Guessi, Sahr Wali, Patrick Ware, Michael McDonald, Mary O'Sullivan, Juan Duero Posada, Heather Ross, and Emily Seto. "The Resilience of Cardiac Care Through Virtualized Services During the COVID-19 Pandemic: Case Study of a Heart Function Clinic." JMIR Cardio 5, no. 1 (May 5, 2021): e25277. http://dx.doi.org/10.2196/25277.
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Background Virtual care has historically faced barriers to widespread adoption. However, the COVID-19 pandemic has necessitated the rapid adoption and expansion of virtual care technologies. Although the intense and prolonged nature of the COVID-19 pandemic has renewed people’s interest in health systems resilience, which includes how services adapt or transform in response to shocks, evidence regarding the role of virtual care technologies in health systems resilience is scarce. Objective At Toronto General Hospital in Ontario, Canada, the rapid virtualization of cardiac care began on March 9, 2020, as a response to the pandemic. The objective of this study was to understand people’s experiences with and the barriers and facilitators of the rapid virtualization and expansion of cardiac care resulting from the pandemic. Methods A single-case study was conducted with 3 embedded units of analysis. Patients, clinicians, and staff were recruited purposively from an existing mobile, phone-based telemonitoring program at a heart function clinic in Toronto, Canada. Individual, semistructured phone interviews were conducted by two researchers and transcribed verbatim. An inductive thematic analysis at the semantic level was used to analyze transcripts and develop themes. Results A total of 29 participants were interviewed, including patients (n=16), clinicians (n=9), and staff (n=4). The following five themes were identified: (1) patient safety as a catalyst for virtual care adoption; (2) piecemeal virtual care solutions; (3) confronting new roles and workloads; (4) missing pieces in virtual care; and (5) the inequity paradox. The motivation to protect patient safety and a piecemeal approach to virtual care adoption facilitated the absorptive and adaptive resilience of cardiac care during the COVID-19 pandemic. However, ad hoc changes to clinic roles and workflows, challenges in building relationships through remote methods, and widened inequities were barriers that threatened virtual care sustainment. Conclusions We contend that sustaining virtual care hinges upon transformative actions (rather than adaptive actions) that strengthen health systems so that they can face the dynamic and emergent challenges associated with COVID-19 and other shocks. Based on the barriers and facilitators we identified, we present the lessons we learned and recommend transformations for sustaining virtual care during and beyond the COVID-19 pandemic.
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Wu, Zhiqiang, Yuankai Wang, Wei Gan, Yixuan Zou, Wen Dong, Shiqi Zhou, and Mo Wang. "A Survey of the Landscape Visibility Analysis Tools and Technical Improvements." International Journal of Environmental Research and Public Health 20, no. 3 (January 18, 2023): 1788. http://dx.doi.org/10.3390/ijerph20031788.
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Visual perception of the urban landscape in a city is complex and dynamic, and it is largely influenced by human vision and the dynamic spatial layout of the attractions. In return, landscape visibility not only affects how people interact with the environment but also promotes regional values and urban resilience. The development of visibility has evolved, and the digital landscape visibility analysis method allows urban researchers to redefine visible space and better quantify human perceptions and observations of the landscape space. In this paper, we first reviewed and compared the theoretical results and measurement tools for spatial visual perception and compared the value of the analytical methods and tools for landscape visualization in multiple dimensions on the principal of urban planning (e.g., complex environment, computational scalability, and interactive intervention between computation and built environment). We found that most of the research was examined in a static environment using simple viewpoints, which can hardly explain the actual complexity and dynamic superposition of the landscape perceptual effect in an urban environment. Thus, those methods cannot effectively solve actual urban planning issues. Aiming at this demand, we proposed a workflow optimization and developed a responsive cross-scale and multilandscape object 3D visibility analysis method, forming our analysis model for testing on the study case. By combining the multilandscape batch scanning method with a refined voxel model, it can be adapted for large-scale complex dynamic urban visual problems. As a result, we obtained accurate spatial visibility calculations that can be conducted across scales from the macro to micro, with large external mountain landscapes and small internal open spaces. Our verified approach not only has a good performance in the analysis of complex visibility problems (e.g., we defined the two most influential spatial variables to maintain good street-based landscape visibility) but also the high efficiency of spatial interventions (e.g., where the four recommended interventions were the most valuable), realizing the improvement of intelligent landscape evaluations and interventions for urban spatial quality and resilience.