Refugio Incident SCAT Operations for Santa Barbara and Ventura Counties Case Study

2017 ◽  
Vol 2017 (1) ◽  
pp. 2017048
Author(s):  
Jennifer Gold ◽  
Mia Roberts ◽  
Michael Connell ◽  
Melissa Boggs ◽  
Keith Posekian ◽  
...  

The Refugio Incident occurred May 19, 2015 along the Gaviota coastline in Santa Barbara County, California. The spill impacted many miles of shoreline and a variety of habitat types. Habitats impacted included exposed wave-cut platforms, man-made structures, cobble, fine-grained sand and boulder beaches. Because of the large scale response, Shoreline Clean-up Assessment Technique (SCAT) surveys were utilized to provide a more systematic assessment of impacted shorelines following a standardized approach. SCAT packets were created to document the progression of clean-up and to direct the Operations Section on where, what, and how to clean the shoreline. One difficulty with this response was that the spill occurred along a dynamic shoreline that constantly changed; and the response was in an area with known significant natural oil seepage. Photographic monitoring points were established throughout the impact area which showed dramatic changes along the coastline throughout the response. A few months into the response, sand and kelp accumulated along the shoreline covering up the incident oil making it difficult to complete the clean-up. SCAT maps were created to make sure that impacted areas that had been previously documented as needing to be cleaned were eventually addressed once the sand eroded from these areas. There was about a two month long time frame where the beach appeared to be clean because of the natural buildup of sand and kelp that covered some of the contamination. The SCAT maps helped to direct the Operations Section by visually identifying specific areas within each segment that still needed cleaning. During a large scale oil spill response when many miles of coastline are impacted in a dynamic environment, it is important to document in a systematic way all field observations so all areas impacted are eventually addressed. This provides the response and the Unified Command with direction and guidance to remediate the spill while taking into account a Net Environmental Benefit Analysis to ensure the established clean-up endpoints are met.

2015 ◽  
Vol 15 (4) ◽  
pp. 583-592 ◽  
Author(s):  
Jing Yu ◽  
Xianwen Bao ◽  
Yang Ding ◽  
Wei Zhang ◽  
Lingling Zhou

2020 ◽  
Vol 12 (18) ◽  
pp. 3053 ◽  
Author(s):  
Thorsten Hoeser ◽  
Felix Bachofer ◽  
Claudia Kuenzer

In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by investigating aggregated classes. The increase in data with a very high spatial resolution enables investigations on a fine-grained feature level which can help us to better understand the dynamics of land surfaces by taking object dynamics into account. To extract fine-grained features and objects, the most popular deep-learning model for image analysis is commonly used: the convolutional neural network (CNN). In this review, we provide a comprehensive overview of the impact of deep learning on EO applications by reviewing 429 studies on image segmentation and object detection with CNNs. We extensively examine the spatial distribution of study sites, employed sensors, used datasets and CNN architectures, and give a thorough overview of applications in EO which used CNNs. Our main finding is that CNNs are in an advanced transition phase from computer vision to EO. Upon this, we argue that in the near future, investigations which analyze object dynamics with CNNs will have a significant impact on EO research. With a focus on EO applications in this Part II, we complete the methodological review provided in Part I.


Author(s):  
Ahmadreza Faghih Imani ◽  
Chris Harding ◽  
Siva Srikukenthiran ◽  
Eric J. Miller ◽  
Khandker Nurul Habib

Smartphones offer a potential alternative to collect high-quality information on the travel patterns of individuals without burdening the respondents with reporting every detail of their travel. Smartphone apps have recently become a common tool for travel survey data collection around the world, especially for multiday surveys. However, there still exists a lack of systematic assessment of issues related to smartphone app-based surveys, such as the impact of app design or the recruitment method on the collected data. Through a large-scale experiment (named the City Logger), this paper assesses the data produced by the City Logger app, to better understand recruitment avenues (targeted invitation versus crowdsourcing), and examine differences in respondents’ travel behavior recruited through crowdsourcing methods. The paper also examines how app design, and particularly the user input method for trip validation, influences participants’ responses. The results indicate that, while crowdsourcing recruitment is promising, it might not yet be the best way to capture a true representation of the population. For app design, a combination of real-time and travel diary approaches is recommended. An ideal app would prompt users real-time and create a travel diary, so users can validate, edit, or delete the recorded information.


During the grain growing months of May-July, the mean temperature on the Canadian prairies has cooled down by 2ºC in the last 30 years. The cooling appears to be most certainly linked to diminishing solar activity as the Sun approaches a Grand Solar Minimum in the next decade or so. This cooling has led to a reduction in Growing Degree Days (GDDs) and has also impacted the precipitation pattern. The GDDs in conjunction with mean temperature and precipitation are important parameters for the growth of various grains (wheat, barley, canola etc.) on the prairies. In this study, we investigate the impact of declining GDDs and associated temperature and precipitation patterns on Prairie grain yields and quality. Our analysis shows that there has been a loss of about 100 GDDs over the time frame of 1985-2019. The loss in GDDs is also linked to some of the large-scale Atmosphere-Ocean parameters like the Pacific Decadal Oscillation (PDO), North Pacific Index (NPI) and Arctic Oscillation (AO). Our analysis suggests grain yield and quality could be significantly impacted in the coming years as solar activity continues to diminish.


2022 ◽  
Vol 16 (2) ◽  
pp. 1-29
Author(s):  
Kai Wang ◽  
Jun Pang ◽  
Dingjie Chen ◽  
Yu Zhao ◽  
Dapeng Huang ◽  
...  

Exploiting the anonymous mechanism of Bitcoin, ransomware activities demanding ransom in bitcoins have become rampant in recent years. Several existing studies quantify the impact of ransomware activities, mostly focusing on the amount of ransom. However, victims’ reactions in Bitcoin that can well reflect the impact of ransomware activities are somehow largely neglected. Besides, existing studies track ransom transfers at the Bitcoin address level, making it difficult for them to uncover the patterns of ransom transfers from a macro perspective beyond Bitcoin addresses. In this article, we conduct a large-scale analysis of ransom payments, ransom transfers, and victim migrations in Bitcoin from 2012 to 2021. First, we develop a fine-grained address clustering method to cluster Bitcoin addresses into users, which enables us to identify more addresses controlled by ransomware criminals. Second, motivated by the fact that Bitcoin activities and their participants already formed stable industries, such as Darknet and Miner , we train a multi-label classification model to identify the industry identifiers of users. Third, we identify ransom payment transactions and then quantify the amount of ransom and the number of victims in 63 ransomware activities. Finally, after we analyze the trajectories of ransom transferred across different industries and track victims’ migrations across industries, we find out that to obscure the purposes of their transfer trajectories, most ransomware criminals (e.g., operators of Locky and Wannacry) prefer to spread ransom into multiple industries instead of utilizing the services of Bitcoin mixers. Compared with other industries, Investment is highly resilient to ransomware activities in the sense that the number of users in Investment remains relatively stable. Moreover, we also observe that a few victims become active in the Darknet after paying ransom. Our findings in this work can help authorities deeply understand ransomware activities in Bitcoin. While our study focuses on ransomware, our methods are potentially applicable to other cybercriminal activities that have similarly adopted bitcoins as their payments.


2021 ◽  
pp. 096228022110370
Author(s):  
Edwin van Leeuwen ◽  
Frank Sandmann ◽  

Social distancing is an important public health intervention to reduce or interrupt the sustained community transmission of emerging infectious pathogens, such as severe acute respiratory syndrome-coronavirus-2 during the coronavirus disease 2019 pandemic. Contact matrices are typically used when evaluating such public health interventions to account for the heterogeneity in social mixing of individuals, but the surveys used to obtain the number of contacts often lack detailed information on the time individuals spend on daily activities. The present work addresses this problem by combining the large-scale empirical data of a social contact survey and a time-use survey to estimate contact matrices by age group (0--15, 16--24, 25–44, 45–64, 65+ years) and daily activity (work, schooling, transportation, and four leisure activities: social visits, bar/cafe/restaurant visits, park visits, and non-essential shopping). This augmentation allows exploring the impact of fewer contacts when individuals reduce the time they spend on selected daily activities as well as when lifting such restrictions again. For illustration, the derived matrices were then applied to an age-structured dynamic-transmission model of coronavirus disease 2019. Findings show how contact matrices can be successfully augmented with time-use data to inform the relative reductions in contacts by activity, which allows for more fine-grained mixing patterns and infectious disease modelling.


Author(s):  
Wan Iqmal Faezy Wan Zalnidzam ◽  
Hasmaini Mohamad ◽  
Nur Ashida Salim ◽  
Hazlie Mokhlis ◽  
Zuhaila Mat Yasin

The increasing penetration of electric vehicle (EV) at distribution system is expected in the near future leading to rising demand for power consumption. Large scale uncoordinated charging demand of EVs will eventually threatens the safety operation of the distribution network. Therefore, a charging strategy is needed to reduce the impact of charging. This paper proposes an optimal centralized charging schedule coordination of EV to minimize active power losses while maintaining the voltage profile at the demand side. The performance of the schedule algorithm developed using particle swarm optimization (PSO) technique is evaluated at the IEEE-33 Bus radial distribution system in a set time frame of charging period. Coordinated and uncoordinated charging schedule is then compared in terms of active power losses and voltage profile at different level of EV penetration considering 24 hours of load demand profile. Results show that the proposed coordinated charging schedule is able to achieve minimum total active power losses compared to the uncoordinated charging.


2021 ◽  
Author(s):  
Serina Chang ◽  
Mandy L. Wilson ◽  
Bryan Lewis ◽  
Zakaria Mehrab ◽  
Komal K. Dudakiya ◽  
...  

ABSTRACTSocial distancing measures, such as restricting occupancy at venues, have been a primary intervention for controlling the spread of COVID-19. However, these mobility restrictions place a significant economic burden on individuals and businesses. To balance these competing demands, policymakers need analytical tools to assess the costs and benefits of different mobility reduction measures.In this paper, we present our work motivated by our interactions with the Virginia Department of Health on a decision-support tool that utilizes large-scale data and epidemiological modeling to quantify the impact of changes in mobility on infection rates. Our model captures the spread of COVID-19 by using a fine-grained, dynamic mobility network that encodes the hourly movements of people from neighborhoods to individual places, with over 3 billion hourly edges. By perturbing the mobility network, we can simulate a wide variety of reopening plans and forecast their impact in terms of new infections and the loss in visits per sector. To deploy this model in practice, we built a robust computational infrastructure to support running millions of model realizations, and we worked with policymakers to develop an intuitive dashboard interface that communicates our model’s predictions for thousands of potential policies, tailored to their jurisdiction. The resulting decision-support environment provides policymakers with much-needed analytical machinery to assess the tradeoffs between future infections and mobility restrictions.


2020 ◽  
Vol 59 (04) ◽  
pp. 294-299 ◽  
Author(s):  
Lutz S. Freudenberg ◽  
Ulf Dittmer ◽  
Ken Herrmann

Abstract Introduction Preparations of health systems to accommodate large number of severely ill COVID-19 patients in March/April 2020 has a significant impact on nuclear medicine departments. Materials and Methods A web-based questionnaire was designed to differentiate the impact of the pandemic on inpatient and outpatient nuclear medicine operations and on public versus private health systems, respectively. Questions were addressing the following issues: impact on nuclear medicine diagnostics and therapy, use of recommendations, personal protective equipment, and organizational adaptations. The survey was available for 6 days and closed on April 20, 2020. Results 113 complete responses were recorded. Nearly all participants (97 %) report a decline of nuclear medicine diagnostic procedures. The mean reduction in the last three weeks for PET/CT, scintigraphies of bone, myocardium, lung thyroid, sentinel lymph-node are –14.4 %, –47.2 %, –47.5 %, –40.7 %, –58.4 %, and –25.2 % respectively. Furthermore, 76 % of the participants report a reduction in therapies especially for benign thyroid disease (-41.8 %) and radiosynoviorthesis (–53.8 %) while tumor therapies remained mainly stable. 48 % of the participants report a shortage of personal protective equipment. Conclusions Nuclear medicine services are notably reduced 3 weeks after the SARS-CoV-2 pandemic reached Germany, Austria and Switzerland on a large scale. We must be aware that the current crisis will also have a significant economic impact on the healthcare system. As the survey cannot adapt to daily dynamic changes in priorities, it serves as a first snapshot requiring follow-up studies and comparisons with other countries and regions.


Author(s):  
Alistair Fox

This book investigates the coming-of-age genre as a significant phenomenon in New Zealand’s national cinema, tracing its development from the 1970s to the present day. A preliminary chapter identifies the characteristics of the coming-of-age film as a genre, tracing its evolution and the influence of the French New Wave and European Art Cinema, and speculating on the role of the genre in the output of national cinemas. Through case studies of fifteen significant films, including The God Boy, Sleeping Dogs, The Scarecrow, Vigil, Mauri, An Angel at My Table, Heavenly Creatures, Once Were Warriors, Rain, Whale Rider, In My Father’s Den, 50 Ways of Saying Fabulous, Boy, Mahana, and Hunt for the Wilderpeople, subsequent chapters examine thematic preoccupations of filmmakers such as the impact of repressive belief systems and social codes, the experience of cultural dislocation, the expression of a Māori perspective through an indigenous “Fourth Cinema,” bicultural relationships, and issues of sexual identity, arguing that these films provide a unique insight into the cultural formation of New Zealanders. Given that the majority of films are adaptations of literary sources, the book also explores the dialogue each film conducts with the nation’s literature, showing how the time frame of each film is updated in a way that allows these films to be considered as a register of important cultural shifts that have occurred as New Zealanders have sought to discover their emerging national identity.


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