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Articles 69631 - 69660 of 294545

Full-Text Articles in Physical Sciences and Mathematics

Bisindolylmaleimide Ix: A Novel Anti-Sars-Cov2 Agent Targeting Viral Main Protease 3clpro Demonstrated By Virtual Screening Pipeline And In-Vitro Validation Assays, Yash Gupta, Dawid Maciorowski, Samantha E. Zak, Krysten A. Jones, Rahul S. Kathayat, Saara-Anne Azizi, Raman Mathur, Catherine M. Pearce, David J. Ilc, Hamza Husein, Andrew S. Herbert, Ajay Bharti, Brijesh Rathi, Ravi Durvasula, Daniel P. Becker, Bryan C. Dickinson, John M. Dye, Prakasha Kempaiah Nov 2021

Bisindolylmaleimide Ix: A Novel Anti-Sars-Cov2 Agent Targeting Viral Main Protease 3clpro Demonstrated By Virtual Screening Pipeline And In-Vitro Validation Assays, Yash Gupta, Dawid Maciorowski, Samantha E. Zak, Krysten A. Jones, Rahul S. Kathayat, Saara-Anne Azizi, Raman Mathur, Catherine M. Pearce, David J. Ilc, Hamza Husein, Andrew S. Herbert, Ajay Bharti, Brijesh Rathi, Ravi Durvasula, Daniel P. Becker, Bryan C. Dickinson, John M. Dye, Prakasha Kempaiah

Chemistry: Faculty Publications and Other Works

SARS-CoV-2, the virus that causes COVID-19 consists of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs/compounds. We targeted seven proteins with enzymatic activities known to be essential at different stages of the viral cycle including PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2′-O-MT. For virtual screening, energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard (Schrodinger LLC 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs and investigational molecules (n = …

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Estimated Amounts And Rates Of Carbon Mobilized By Landsliding In Old-Growth Temperate Forests Of Se Alaska, Bryce A. Vascik, Adam M. Booth, Brian Buma, Matteo Berti Nov 2021

Estimated Amounts And Rates Of Carbon Mobilized By Landsliding In Old-Growth Temperate Forests Of Se Alaska, Bryce A. Vascik, Adam M. Booth, Brian Buma, Matteo Berti

Geology Faculty Publications and Presentations

Landslides, a forest disturbance, mobilize carbon (C) sequestered in vegetation and soils. Mobilized C is deposited either onto hillslopes or into the water, sequestering C from and releasing C to the atmosphere at different time scales. The C-dense old-growth temperate forests of SE Alaska are a unique location to quantify C mobilization rate by frequent landslides that often evolve into saturated moving masses known as debris flows. In this study, the amount of C mobilized by debris flows over historic time scales was estimated by combining a landslide inventory with maps of modeled biomass and soil carbon. We analyzed SE …

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On Lexicographic Proof Rules For Probabilistic Termination, Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Petr Novotný, Jiří Zárevucký, Dorde Zikelic Nov 2021

On Lexicographic Proof Rules For Probabilistic Termination, Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Petr Novotný, Jiří Zárevucký, Dorde Zikelic

Research Collection School Of Computing and Information Systems

We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stochastic extension of classical imperative programs. Lexicographic ranking functions provide a sound and practical approach for termination of non-probabilistic programs, and their extension to probabilistic programs is achieved via lexicographic ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous work have a limitation that impedes their automation: all of their components have to be non-negative in all reachable states. This might result in LexRSM not existing even for simple terminating programs. Our contributions are twofold: First, we introduce a generalization of LexRSMs which allows for some components …

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Towards Enriching Responses With Crowd-Sourced Knowledge For Task-Oriented Dialogue, Yingxu He, Lizi Liao, Zheng Zhang, Tat-Seng Chua Nov 2021

Towards Enriching Responses With Crowd-Sourced Knowledge For Task-Oriented Dialogue, Yingxu He, Lizi Liao, Zheng Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Task-oriented dialogue agents are built to assist users in completing various tasks. Generating appropriate responses for satisfactory task completion is the ultimate goal. Hence, as a convenient and straightforward way, metrics such as success rate, inform rate etc., have been widely leveraged to evaluate the generated responses. However, beyond task completion, there are several other factors that largely affect user satisfaction, which remain under-explored. In this work, we focus on analyzing different agent behavior patterns that lead to higher user satisfaction scores. Based on the findings, we design a neural response generation model EnRG. It naturally combines the power of …

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Learning Knowledge-Enriched Company Embeddings For Investment Management, Gary Ang, Ee-Peng Lim Nov 2021

Learning Knowledge-Enriched Company Embeddings For Investment Management, Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Relationships between companies serve as key channels through which the effects of past stock price movements and news events propagate and influence future price movements. Such relationships can be implicitly found in knowledge bases or explicitly represented as knowledge graphs. In this paper, we propose KnowledgeEnriched Company Embedding (KECE), a novel multi-stage attentionbased dynamic network embedding model combining multimodal information of companies with knowledge from Wikipedia and knowledge graph relationships from Wikidata to generate company entity embeddings that can be applied to a variety of downstream investment management tasks. Experiments on an extensive set of real-world stock prices and news …

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Adaptive Posterior Knowledge Selection For Improving Knowledge-Grounded Dialogue Generation, Weichao Wang, Wei Gao, Shi Feng, Ling Chen, Daling Wang Nov 2021

Adaptive Posterior Knowledge Selection For Improving Knowledge-Grounded Dialogue Generation, Weichao Wang, Wei Gao, Shi Feng, Ling Chen, Daling Wang

Research Collection School Of Computing and Information Systems

In open-domain dialogue systems, knowledge information such as unstructured persona profiles, text descriptions and structured knowledge graph can help incorporate abundant background facts for delivering more engaging and informative responses. Existing studies attempted to model a general posterior distribution over candidate knowledge by considering the entire response utterance as a whole at the beginning of decoding process for knowledge selection. However, a single smooth distribution could fail to model the variability of knowledge selection patterns over different decoding steps, and make the knowledge expression less consistent. To remedy this issue, we propose an adaptive posterior knowledge selection framework, which sequentially …

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Span-Level Emotion Cause Analysis With Neural Sequence Tagging, Xiangju Li, Wei Gao, Shi Feng, Daling Wang, Shafiq Joty Nov 2021

Span-Level Emotion Cause Analysis With Neural Sequence Tagging, Xiangju Li, Wei Gao, Shi Feng, Daling Wang, Shafiq Joty

Research Collection School Of Computing and Information Systems

This paper addresses the task of span-level emotion cause analysis (SECA). It is a finer-grained emotion cause analysis (ECA) task, which aims to identify the specific emotion cause span(s) behind certain emotions in text. In this paper, we formalize SECA as a sequence tagging task for which several variants of neural network-based sequence tagging models to extract specific emotion cause span(s) in the given context. These models combine different types of encoding and decoding approaches. Furthermore, to make our models more "emotionally sensitive'', we utilize the multi-head attention mechanism to enhance the representation of context. Experimental evaluations conducted on two …

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From Community Search To Community Understanding: A Multimodal Community Query Engine, Zhao Li, Pengcheng Zou, Xia Chen, Shichang Hu, Peng Zhang, Yumou Zhou, Bingsheng He, Yuchen Li, Xing Tang Nov 2021

From Community Search To Community Understanding: A Multimodal Community Query Engine, Zhao Li, Pengcheng Zou, Xia Chen, Shichang Hu, Peng Zhang, Yumou Zhou, Bingsheng He, Yuchen Li, Xing Tang

Research Collection School Of Computing and Information Systems

In this demo, we present an online multi-modal community query engine (MQE1 ) on Alibaba’s billion-scale heterogeneous network. MQE has two distinct features in comparison with existing community query engines. Firstly, MQE supports multimodal community search on heterogeneous graphs with keyword and image queries. Secondly, to facilitate community understanding in real business scenarios, MQE generates natural language descriptions for the retrieved community in combination with other useful demographic information. The distinct features of MQE benefit many downstream applications in Alibaba’s e-commerce platform like recommendation. Our experiments confirm the effectiveness and efficiency of MQE on graphs with billions of edges.

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Leap: Leakage-Abuse Attack On Efficiently Deployable, Efficiently Searchable Encryption With Partially Known Dataset, Jianting Ning, Xinyi Huang, Geong Sen Poh, Jiaming Yuan, Yingjiu Li, Jian Weng, Robert H. Deng Nov 2021

Leap: Leakage-Abuse Attack On Efficiently Deployable, Efficiently Searchable Encryption With Partially Known Dataset, Jianting Ning, Xinyi Huang, Geong Sen Poh, Jiaming Yuan, Yingjiu Li, Jian Weng, Robert H. Deng

Research Collection School Of Computing and Information Systems

Searchable Encryption (SE) enables private queries on encrypted documents. Most existing SE schemes focus on constructing industrialready, practical solutions at the expense of information leakages that are considered acceptable. In particular, ShadowCrypt utilizes a cryptographic approach named “efficiently deployable, efficiently searchable encryption” (EDESE) that reveals the encrypted dataset and the query tokens among other information. However, recent attacks showed that such leakages can be exploited to (partially) recover the underlying keywords of query tokens under certain assumptions on the attacker’s background knowledge. We continue this line of work by presenting LEAP, a new leakageabuse attack on EDESE schemes that can …

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Flip & Slack – Active Flipped Classroom Learning With Collaborative Slack Interactions, Kyong Jin Shim, Gottipati Swapna, Yi Meng Lau Nov 2021

Flip & Slack – Active Flipped Classroom Learning With Collaborative Slack Interactions, Kyong Jin Shim, Gottipati Swapna, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Active flipped classroom learning is stipulated with faculty structuring the activities involving constructive interactions, either formal or informal. Sharing ideas and responding to ideas improve the cognitive skills of the students. Encouraging peers to contribute to class activities and respecting peers contribute to the development of affective skills. We present an integrated platform for cognitive and affective skills development. A flipped classroom arrangement allows the faculty to focus more on in-class activities such as programming and lab exercises to support active learning in computing courses. We share the design of an innovative flipped classroom model integrated with Slack and present …

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K-Sums Clustering: A Stochastic Optimization Approach, Zhao Wan-Lei, Shi Ying Lan, Run-Qing Chen, Chong-Wah Ngo Nov 2021

K-Sums Clustering: A Stochastic Optimization Approach, Zhao Wan-Lei, Shi Ying Lan, Run-Qing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In this paper, we revisit the decades-old clustering method k-means. The egg-chicken loop in traditional k-means has been replaced by a pure stochastic optimization procedure. The optimization is undertaken from the perspective of each individual sample. Different from existing incremental k-means, an individual sample is tentatively joined into a new cluster to evaluate its distance to the corresponding new centroid, in which the contribution from this sample is accounted. The sample is moved to this new cluster concretely only after we find the reallocation makes the sample closer to the new centroid than it is to the current one. Compared …

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Automating Developer Chat Mining, Shengyi Pan, Lingfeng Bao, Xiaoxue Ren, Xin Xia, David Lo, Shanping Li Nov 2021

Automating Developer Chat Mining, Shengyi Pan, Lingfeng Bao, Xiaoxue Ren, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Online chatrooms are gaining popularity as a communication channel between widely distributed developers of Open Source Software (OSS) projects. Most discussion threads in chatrooms follow a Q&A format, with some developers (askers) raising an initial question and others (respondents) joining in to provide answers. These discussion threads are embedded with rich information that can satisfy the diverse needs of various OSS stakeholders. However, retrieving information from threads is challenging as it requires a thread-level analysis to understand the context. Moreover, the chat data is transient and unstructured, consisting of entangled informal conversations. In this paper, we address this challenge by …

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Automating User Notice Generation For Smart Contract Functions, Xing Hu, Zhipeng Gao, Xin Xia, David Lo, Xiaohu Yang Nov 2021

Automating User Notice Generation For Smart Contract Functions, Xing Hu, Zhipeng Gao, Xin Xia, David Lo, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Smart contracts have obtained much attention and are crucial for automatic financial and business transactions. For end-users who have never seen the source code, they can read the user notice shown in end-user client to understand what a transaction does of a smart contract function. However, due to time constraints or lack of motivation, user notice is often missing during the development of smart contracts. For endusers who lack the information of the user notices, there is no easy way for them to check the code semantics of the smart contracts. Thus, in this paper, we propose a new approach …

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Stock Market Trend Forecasting Based On Multiple Textual Features: A Deep Learning Method, Zhenda Hu, Zhaoxia Wang, Seng-Beng Ho, Ah-Hwee Tan Nov 2021

Stock Market Trend Forecasting Based On Multiple Textual Features: A Deep Learning Method, Zhenda Hu, Zhaoxia Wang, Seng-Beng Ho, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Stock market trend forecasting is a valuable and challenging research task for both industry and academia. In order to explore the influence of stock news information on the stock market trend, a textual embedding construction method is proposed to encode multiple textual features, including topic features, sentiment features, and semantic features extracted from stock news textual content. In addition, a deep learning method is designed by using financial data and multiple textual features obtained from multiple news textual embeddings for short-term stock market trend prediction. For evaluation, extensive experiments on real stock market data are conducted. The experimental results illustrate …

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Sofi: Reflection-Augmented Fuzzing For Javascript Engines, Xiaoyu He, Xiaofei Xie, Yuekang Li, Jianwen Sun, Feng Li, Wei Zou, Yang Liu, Lei Yu, Jianhua Zhou, Wenchang Shi, Wei Huo Nov 2021

Sofi: Reflection-Augmented Fuzzing For Javascript Engines, Xiaoyu He, Xiaofei Xie, Yuekang Li, Jianwen Sun, Feng Li, Wei Zou, Yang Liu, Lei Yu, Jianhua Zhou, Wenchang Shi, Wei Huo

Research Collection School Of Computing and Information Systems

JavaScript engines have been shown prone to security vulnerabilities, which can lead to serious consequences due to their popularity. Fuzzing is an effective testing technique to discover vulnerabilities. The main challenge of fuzzing JavaScript engines is to generate syntactically and semantically valid inputs such that deep functionalities can be explored. However, due to the dynamic nature of JavaScript and the special features of different engines, it is quite challenging to generate semantically meaningful test inputs.We observed that state-of-the-art semantic-aware JavaScript fuzzers usually require manually written rules to analyze the semantics for a JavaScript engine, which is labor-intensive, incomplete and engine-specific. …

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Self-Supervised Multi-Class Pre-Training For Unsupervised Anomaly Detection And Segmentation In Medical Images, Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh Nov 2021

Self-Supervised Multi-Class Pre-Training For Unsupervised Anomaly Detection And Segmentation In Medical Images, Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh

Research Collection School Of Computing and Information Systems

Unsupervised anomaly detection (UAD) that requires only normal (healthy) training images is an important tool for enabling the development of medical image analysis (MIA) applications, such as disease screening, since it is often difficult to collect and annotate abnormal (or disease) images in MIA. However, heavily relying on the normal images may cause the model training to overfit the normal class. Self-supervised pre-training is an effective solution to this problem. Unfortunately, current self-supervision methods adapted from computer vision are sub-optimal for MIA applications because they do not explore MIA domain knowledge for designing the pretext tasks or the training process. …

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Information Technology And Organizational Learning: Managing Behavioral Change In The Digital Age By Arthur M. Langer, Siu Loon Hoe Nov 2021

Information Technology And Organizational Learning: Managing Behavioral Change In The Digital Age By Arthur M. Langer, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

As the world battles yet another crisis because of the spread of COVID-19, the idea of digitalization brings about a whole new meaning. Many professionals and information technology (IT) managers have remarked that the spread of the coronavirus has accelerated the pace of digital transformation much more so than any effort put forth by C-suite executives. While it is true that most organizations do not accept new technology readily because of embedded legacy systems, changing the corporate cultures does play an important role in affecting the rate of IT adoption. Very often, leaders and senior executives focus on the technological …

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Exploratory Data Mining Techniques (Decision Tree Models) For Examining The Impact Of Internet-Based Cognitive Behavioral Therapy For Tinnitus: Machine Learning Approach, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah Nov 2021

Exploratory Data Mining Techniques (Decision Tree Models) For Examining The Impact Of Internet-Based Cognitive Behavioral Therapy For Tinnitus: Machine Learning Approach, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical & Statistical Sciences Faculty Publications

Background: There is huge variability in the way that individuals with tinnitus respond to interventions. These experiential variations, together with a range of associated etiologies, contribute to tinnitus being a highly heterogeneous condition. Despite this heterogeneity, a “one size fits all” approach is taken when making management recommendations. Although there are various management approaches, not all are equally effective. Psychological approaches such as cognitive behavioral therapy have the most evidence base. Managing tinnitus is challenging due to the significant variations in tinnitus experiences and treatment successes. Tailored interventions based on individual tinnitus profiles may improve outcomes. Predictive models of treatment …

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Rooting Out Genetic Structure Of Invasive Wild Pigs In Texas, Anna M. Mangan, Antoinette J. Piaggio, Michael J. Bodenchuk, Courtney F. Pierce, Timothy J. Smyser Nov 2021

Rooting Out Genetic Structure Of Invasive Wild Pigs In Texas, Anna M. Mangan, Antoinette J. Piaggio, Michael J. Bodenchuk, Courtney F. Pierce, Timothy J. Smyser

United States Department of Agriculture Wildlife Services: Staff Publications

Invasive wild pigs (Sus scrofa), also called feral swine or wild hogs, are recognized as among the most destructive invasive species in the world. Throughout the United States, invasive wild pigs have expanded rapidly over the past 40 years with populations now established in 38 states. Of the estimated 6.9 million wild pigs distributed throughout the United States, Texas supports approximately 40% of the population and similarly bears disproportionate ecological and economic costs. Genetic analyses are an effective tool for understanding invasion pathways and tracking dispersal of invasive species such as wild pigs and have been used recently …

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Generating Music With Sentiments, Chunhui Bao Nov 2021

Generating Music With Sentiments, Chunhui Bao

Dissertations and Theses Collection (Open Access)

In this thesis, I focus on the music generation conditional on human sentiments such as positive and negative. As there are no existing large-scale music datasets annotated with sentiment labels, generating high-quality music conditioned on sentiments is hard. I thus build a new dataset consisting of the triplets of lyric, melody and sentiment, without requiring any manual annotations. I utilize an automated sentiment recognition model (based on the BERT trained on Edmonds Dance dataset) to "label'' the music according to the sentiments recognized from its lyrics. I then train the model of generating sentimental music and call the method Sentimental …

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Nutrient Cycling In Tropical And Temperate Coastal Waters: Is Latitude Making A Difference?, Christian Lønborg, Moritz Müller, Edward C. V. Butler, Shan Jiang, Seng Keat Ooi, Dieu Huong Trinh, Pui Yee Wong, Suryati M. Ali, Chun Cui, Wee Boon Siong, Erik S. Yando, Daniel A. Friess, Judith A. Rosentreter, Bradley D. Eyre, Patrick Martin Nov 2021

Nutrient Cycling In Tropical And Temperate Coastal Waters: Is Latitude Making A Difference?, Christian Lønborg, Moritz Müller, Edward C. V. Butler, Shan Jiang, Seng Keat Ooi, Dieu Huong Trinh, Pui Yee Wong, Suryati M. Ali, Chun Cui, Wee Boon Siong, Erik S. Yando, Daniel A. Friess, Judith A. Rosentreter, Bradley D. Eyre, Patrick Martin

Biological Sciences Faculty Publications

Tropical coastal waters are highly dynamic and amongst the most biogeochemically active zones in the ocean. This review compares nitrogen (N) and phosphorus (P) cycles in temperate and tropical coastal waters. We review the literature to identify major similarities and differences between these two regions, specifically with regards to the impact of environmental factors (temperature, sunlight), riverine inputs, groundwater, lateral fluxes, atmospheric deposition, nitrogen fixation, organic nutrient cycling, primary production, respiration, sedimentary burial, denitrification and anammox. Overall, there are some similarities but also key differences in nutrient cycling, with differences relating mainly to temperature, sunlight, and precipitation amounts and patterns. …

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Effects Of Sesame Consumption On Inflammatory Biomarkers In Humans: A Systematic Review And Meta-Analysis Of Randomized Controlled Trials, Shabnam Rafiee, Roghaye Faryabi, Mohammad Ali Zareian, Jessie Hawkins, Nitin Shivappa Mbbs, Mph, Ph.D., Laila Shirbeigi Nov 2021

Effects Of Sesame Consumption On Inflammatory Biomarkers In Humans: A Systematic Review And Meta-Analysis Of Randomized Controlled Trials, Shabnam Rafiee, Roghaye Faryabi, Mohammad Ali Zareian, Jessie Hawkins, Nitin Shivappa Mbbs, Mph, Ph.D., Laila Shirbeigi

Faculty Publications

Objectives. Existing evidence produces conflicting findings regarding the effect of sesame intake on inflammatory biomarkers; thisknowledge gap has yet to be met through systematic review and meta-analysis. )is meta-analysis of randomized, controlledclinical trials (RCTs) was conducted to evaluate the effects of sesame consumption on markers of inflammation in humans. Methods. PubMed, Scopus, and the Cochrane Database of Systematic Reviews were searched through August 2020 to identify relevant papers for inclusion. Using the random-effects model, data were evaluated as weighted mean differences (WMD) with 95% confidence intervals (CI). Cochrane’s Q and I-squared (I2) tests were used to …

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Next-Generation Ensemble Projections Reveal Higher Climate Risks For Marine Ecosystems, Derek P. Tittensor, Camilla Novaglio, Cheryl S. Harrison, Ryan F. Heneghan, Nicolas Barrier, Daniele Bianchi, Laurent Bopp, Andrea Bryndum-Buchholz, Gregory L. Britten, Matthias Büchner Nov 2021

Next-Generation Ensemble Projections Reveal Higher Climate Risks For Marine Ecosystems, Derek P. Tittensor, Camilla Novaglio, Cheryl S. Harrison, Ryan F. Heneghan, Nicolas Barrier, Daniele Bianchi, Laurent Bopp, Andrea Bryndum-Buchholz, Gregory L. Britten, Matthias Büchner

School of Earth, Environmental, & Marine Sciences Faculty Publications

Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation …

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Apportioning Deformation Among Depth Intervals In An Aquifer System Using Insar And Head Data, Ryan G. Smith, Hossein Hashemi, Jingyi Chen, Rosemary Knight Nov 2021

Apportioning Deformation Among Depth Intervals In An Aquifer System Using Insar And Head Data, Ryan G. Smith, Hossein Hashemi, Jingyi Chen, Rosemary Knight

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Land surface subsidence due to excessive groundwater pumping is an increasing concern in California, USA. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique for measuring centimeter-to-millimeter surface deformation at 10-100 m spatial resolution. Here, a data-driven approach that attributes deformation to individual depth intervals within an aquifer system by integrating head data acquired from each of three screened intervals in a monitoring well with InSAR surface deformation measurements was developed. The study area was the Colusa Basin in northern Central Valley. To reconstruct the surface deformation history over the study area, 13 ALOS-PALSAR scenes acquired between 2006 and …

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Focus On Sustainable Cities: Urban Solutions Toward Desired Outcomes, M. Georgescu, M. Arabi, Winston T. L. Chow, E. Mack, K. C. Seto Nov 2021

Focus On Sustainable Cities: Urban Solutions Toward Desired Outcomes, M. Georgescu, M. Arabi, Winston T. L. Chow, E. Mack, K. C. Seto

Research Collection School of Social Sciences

Urbanization represents the single most impactful and long-lasting transformation of the Earth system since the dawn of civilization. Cities are simultaneously locations of innovation, social connectivity, and wealth, but they also create local-to-global environmental degradation and socioeconomic disparities. For example, food provision for cities has required significant land-use change and fertilizer input, has altered regional climate, biogeochemical cycles, and degraded marine and landscapes through biodiversity loss, algal blooms and fish kills. To maintain urban livelihoods and the provision of goods and services, cities require vast amounts of energy (e.g. to provide access to transport, cooling systems), which are massive producers …

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New Methods For Assessing The Sustainability Of Wood-Burning Energy Facilities, Sarah Mittlefehldt, Erin Bunting, Emily Huff, Joseph Welsh, Robert Goodwin Nov 2021

New Methods For Assessing The Sustainability Of Wood-Burning Energy Facilities, Sarah Mittlefehldt, Erin Bunting, Emily Huff, Joseph Welsh, Robert Goodwin

Journal Articles

Methods to assess wood-based bioenergy projects have tended to focus on technological and physical constraints. Less is known about how longer-term environmental, economic, and social systems—the three pillars of sustainable development—have influenced technological development in the context of woody biomass energy. This research offers new methods for assessing the sustainability of wood-based energy projects by combining spatial analysis, semi-structured interviews, and archival data analysis. By integrating quantitative and qualitative methods, this project offers ways to understand how social and environmental dynamics from the past shape technological development in the future. A propensity analysis of biomass energy plants in Michigan, USA …

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System Identification Through Lipschitz Regularized Deep Neural Networks, Elisa Negrini, Giovanna Citti, Luca Capogna Nov 2021

System Identification Through Lipschitz Regularized Deep Neural Networks, Elisa Negrini, Giovanna Citti, Luca Capogna

Mathematics Sciences: Faculty Publications

In this paper we use neural networks to learn governing equations from data. Specifically we reconstruct the right-hand side of a system of ODEs x˙(t)=f(t,x(t)) directly from observed uniformly time-sampled data using a neural network. In contrast with other neural network-based approaches to this problem, we add a Lipschitz regularization term to our loss function. In the synthetic examples we observed empirically that this regularization results in a smoother approximating function and better generalization properties when compared with non-regularized models, both on trajectory and non-trajectory data, especially in presence of noise. In contrast with sparse regression approaches, since neural networks …

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Microgrid Design And Component Replacement Analysis, Jose Trinidad Reyes Nov 2021

Microgrid Design And Component Replacement Analysis, Jose Trinidad Reyes

Open Access Theses & Dissertations

This study focuses on developing specific methods that can be friendly applied to obtain efficient usage and maintenance of electricity production in a micro-grid used in a residence or stand-alone building to determine long-term component replacement strategies for aging components. After designing the best option to produce electricity by installing green energies such as photovoltaic panels and their proper devices such as inverters and batteries, this work has developed electric power reliability models to approximate the most efficient component replacement accurately. Due to the nature of the components of this study, repair time is not a substantial part of the …

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Engaging Residents In Policy And Planning For Sea Level Rise: Application Of The Action-Oriented Stakeholder Engagement For A Resilient Tomorrow (Asert) Framework, Juita-Elena (Wie) Yusuf, J. Gail Nicula, Daniel P. Richards, Ogechukwu Agim, Michelle Covi, Khairul A. Anuar Nov 2021

Engaging Residents In Policy And Planning For Sea Level Rise: Application Of The Action-Oriented Stakeholder Engagement For A Resilient Tomorrow (Asert) Framework, Juita-Elena (Wie) Yusuf, J. Gail Nicula, Daniel P. Richards, Ogechukwu Agim, Michelle Covi, Khairul A. Anuar

School of Public Service Faculty Publications

This chapter describes the application of the Action-oriented Stakeholder Engagement for a Resilient Tomorrow (ASERT) framework for communicating with and engaging both residents and community stakeholders in their localities’ efforts to prepare for and to respond to flooding and sea level rise. The application of ASERT incorporates communication, education/learning, and gamification elements that can be embedded into community meetings. We describe the way in which ASERT community meetings are designed (1) to provide an inclusive and engaging process that will allow residents to participate in their city’s resilience efforts; (2) to provide information about resilience in an environment that encourages …

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Communicating And Co-Producing Information With Stakeholders: Examples Of Participatory Mapping Approaches Related To Sea Level Rise Risks And Impacts, Pragati Rawat, Khairul A. Anua, Juita-Elena (Wie) Yusuf, Jon Derek Loftis, Ren-Neasha Blake Nov 2021

Communicating And Co-Producing Information With Stakeholders: Examples Of Participatory Mapping Approaches Related To Sea Level Rise Risks And Impacts, Pragati Rawat, Khairul A. Anua, Juita-Elena (Wie) Yusuf, Jon Derek Loftis, Ren-Neasha Blake

School of Public Service Faculty Publications

This chapter discusses practical approaches for using participatory mapping as a tool to visualize and communicate sea level rise (SLR) and climate change risks, to share information about the vulnerability to, and threats of, climate change, and to co-produce knowledge with stakeholders. The examples presented in this chapter are from demonstrated applications in communities in Virginia (USA) that involve participatory mapping and that utilize a web-Geographic Information System (GIS). The web-GIS is innovatively combined with other technologies and participatory processes to create low-cost high-tech approaches so that even people with little to no knowledge of GIS can interact with maps …

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