University of Vermont
  • Burlington, VT, United States
Recent publications
Compared with large-scale physical batteries, aggregated and coordinated generic energy storage (GES) resources provide low-cost, but uncertain, flexibility for power grid operations. While GES can be characterized by different types of uncertainty, the literature mostly focuses on decision-independent uncertainties (DIUs), such as exogenous stochastic disturbances caused by weather conditions. Instead, this manuscript focuses on newly-introduced decision-dependent uncertainties (DDUs) and considers an optimal GES dispatch that accounts for uncertain available state-of-charge (SoC) bounds that are affected by incentive signals and discomfort levels. To incorporate DDUs, we present a novel chance-constrained optimization (CCO) approach for the day-ahead economic dispatch of GES units. Two tractable methods are presented to solve the proposed CCO problem with DDUs: (i) a robust reformulation for general but incomplete distributions of DDUs, and (ii) an iterative algorithm for specific and known distributions of DDUs. Furthermore, reliability indices are introduced to verify the applicability of the proposed approach with respect to the reliability of the response of GES units. Simulation-based analysis shows that the proposed methods yield conservative, but credible, GES dispatch strategies and reduced penalty cost by incorporating DDUs in the constraints and leveraging data-driven parameter identification. This results in improved availability and performance of coordinated GES units.
Mating and sociosexual behaviors of cetaceans are challenging to study in nature because most species spend only brief periods of time at the surface and most copulation and courtship occurs underwater. Recent advancements in technology have enabled a new perspective on these behaviors. Drones, or unoccupied aerial systems, have revolutionized studies of marine mammals by providing unparalleled aerial perspectives on the behaviors of whales, porpoises, and dolphins, including their use for investigating questions concerning the sexual behaviors and mating habits of species in near-surface waters. Drones offer numerous benefits over traditional boat- and land-based observational methods for studying mating in free-swimming cetaceans, including the ability to continuously film in high resolution for fine-scale tracking of activity and mating behaviors at and near the water’s surface. This paper outlines various ways in which drone data can be used to understand mating in cetaceans, including novel drone-based video observations of six species of dolphins and whales. These examples illustrate specific sociosexual and mating behaviors and how drone-based data can be used to address questions about the diversity of sexual behaviors and mating strategies. The use of drones is improving opportunities to investigate the fitness advantages of mating tactics and their evolutionary drivers.
Quality of life is at the center of decisions about tourism planning and development for residents of host communities. Stakeholders are affected in different ways by tourism development, as some stakeholders may see an increase in their quality of life, others may experience a decrease in quality of life, and still others may experience mixed impacts. Understanding diverse perspectives of stakeholders and how they are affected by tourism development is critical for constructively engaging stakeholders in planning, but designing an effective strategy is not straightforward. Several techniques exist to engage stakeholders, ranging from information dissemination to public meetings to task forces. Case studies of participatory modeling workshops, training and technical assistance, and surveys and focus groups illustrate the effectiveness of different techniques applied in different situations. Challenges to constructively engage stakeholders include resistance among stakeholder sets, ensuring equity and fairness, problematic relationships among institutions, communication issues, lack of time and money, and difficulty defining and measuring quality of life. To address these challenges, researchers are working closely with practitioners to expand the body of knowledge and practical tools available for engaging stakeholders and assessing quality of life indicators for residents of host communities.
This section offers a muestra—a sampling or display—of major works of Latin American digital poetry. Authored by experts in the field, these 25 short entries analyze the canon of digital poetry from Latin America. Each entry consists of: (1) a technical description of the work; (2) a brief contextualization of the work (referencing typologies, generational schema, and taxonomies); (3) an analysis of the e-poetics of the digital work; (4) minimal (e-) bibliography (about the author/in general); and (5) QR codes linking to the author’s work. This “sample” of trends in Latin American digital poetics is not meant to be exhaustive; rather, it seeks to situate some key features of these emergent forms in larger computational, literary, and cultural contexts.
Purpose of Review Electrification efforts will change electric demand patterns, but must be made beneficial to the deployment of renewable generation. To ensure this, we need intelligent coordination of millions of resulting distributed energy resources (DERs). We provide an overview of challenges and opportunities associated with intelligent electrification as a means to enable decarbonization and clean energy. Summary Intelligent electrification can bring value to the grid and consumers, but depends on its implementation and cyber-physical coordination architecture to manage consumer quality of service (QoS), grid services, and grid reliability. We also review and discuss challenges with getting intelligent electrification efforts to scale. Recent Findings We find that many methods already exist for coordinating DERs to deliver valuable grid services, but that practical implementation barriers exist regarding feedback control, integrating grid data, and deploying intelligent electrification at scale. In addition, accurately characterizing and maximizing the available flexibility of a fleet of DERs is an open technical problem.
Because children learn habits from observing their parents, we assessed the top-of-the-mind beliefs held by parents about "drinking plain water in front of their preschool child during lunch one day this coming weekend." We recruited a convenience sample of 34 Mexican parents from daycares in Guadalajara and conducted a content analysis. Main advantage identified was getting healthier, followed by being a good example for the child. Few parents identified disadvantages. Most reported to have at least one approver within their families. The most frequent facilitator was "having it," while "not having it" was the main barrier.
The sporadic occurrence of unusually enhanced mental clarity before death has been documented over time and cultures, and reported in patients with and without neurodegenerative diseases, psychiatric disorders, and other neurocognitive deficits, as well as those with nonterminal and terminal conditions. Using a purposive sampling method via existing professional networks, clinical presentations of terminal lucidity in pediatric populations, as witnessed by pediatric oncologists and medical personnel, were solicited. We document clinical presentations suggestive of terminal lucidity in children, which were compiled by their attending physician at two large tertiary pediatric hospitals. Unanticipated and unexplained changes in mental clarity, verbal communication, and/or physical capability in the days and hours before the death of the pediatric patients were observed. Each patient's medical condition should not have allowed for such changes. The phenomenon known as terminal lucidity provides a conceptual framework for these deviations, although more systematic documentation and clinical research is required before definitive conclusions can be drawn.
This study examined whether children exposed to adversity would exhibit lower epigenetic age acceleration in the context of improved parenting. Children with developmental delays and externalizing behavior problems ( N = 62; M age = 36.26 months; 70.97% boys, 29.03% girls; 71% Latinx, 22.6% Black) were drawn from a larger randomized controlled trial (RCT), which randomized them to receive Internet-delivered parent–child interaction therapy (iPCIT; n = 30) or community referrals as usual (RAU; n = 32). Epigenetic age acceleration was estimated with the pediatric buccal epigenetic clock, using saliva. Adversity was assessed using parent, family, and neighborhood-level cumulative-risk indicators. Adversity interacted with Time 2 (T2) observations of positive and negative-parenting practices to predict epigenetic age acceleration 1.5 years later, regardless of treatment assignment. Children exposed to more adversity displayed lower epigenetic age acceleration when parents evidenced increased positive ( b = −0.15, p = .001) and decreased negative ( b = −0.12, p = .01) parenting practices.
For anyone wanting to tackle an environmental problem in their neighborhood but do not know where to start, this book can help. In this handbook, the author shares proven strategies needed to step up and get meaningful action done. From designing a pilot study to managing contentious public meetings and more, the author walks the reader through the essentials of effective place-based environmental efforts. Among the tools found here are worksheets to kickstart brainstorming, appendixes that demystify jargon you might encounter, and illuminating, real-life examples. Down-to-earth and stimulating, the book is a launchpad for those ready to make a difference now.
We present structural models for three different amyloid fibril polymorphs prepared from amylin20−29 (sequence SNNFGAILSS) and amyloid-β25−35 (Aβ25−35) (sequence GSNKGAIIGLM) peptides. These models are based on amide C=O bond and Ramachandran ψ-dihedral angle data from Raman spectroscopy, which were used structural constraintsto guide molecular dynamics (MD) simulations. The resulting structural models indicate that the basic structural motif of amylin20−29 and Aβ25−35 fibrils are extended β-strands. Our data indicates that amylin20−29 forms both antiparallel and parallel β-sheet fibril polymorphs, while Aβ25−35 forms a parallel β-sheet fibril structure. Overall, our work lays the foundation for using Raman spectroscopy in conjunction with MD simulations to determine detailed molecular-level structural models of amyloid fibrils in a manner that complements gold-standard techniques such as solid-state NMR and cryogenic electron microscopy.
Introduction The scope of primary care increasingly encompasses patient behavioral health problems, manifest typically through depression screening and treatment. Although substance use is highly comorbid with depression, it is not commonly identified and addressed in the primary care context. This study aimed to examine the association between the likelihood of substance use disorder and increased depression severity, both cross-sectionally and longitudinally, among a sample of 2409 patients from 41 geographically dispersed and diverse primary care clinics across the US. Methods This is secondary analysis of data obtained from a multi-site parent study of integrated behavioral health in primary care, among patients with both chronic medical and behavioral health conditions. Patient reported outcome surveys were gathered from patients at 3 time points. The primary care practices were blind to which of their patients completed surveys. Included were standardized measures of depression severity (Patient Health Questionnaire—9) [PHQ-9] and substance use disorder likelihood (Global Appraisal of Individual Needs—Short Screener [GSS]). Results Four percent of the study population screened positive for substance use disorder. PHQ-9 scores indicated depression among 43% of all patients. There was a significant association between the likelihood of substance use disorder and depression initially, at a 9-month follow-up, and over time. These associations remained significant after adjusting for age, gender, race, ethnicity, education, income, and other patient and contextual characteristics. Conclusions The findings suggest that substance use disorder is associated with depression severity cross-sectionally and over time. Primary care clinics and health systems might consider implementing substance use screening in addition to the more common screening strategies for depression. Especially for patients with severe depression or those who do not respond to frontline depression treatments, the undermining presence of a substance use disorder should be explored.
Group I alkoxides are highly active precatalysts in the heterodehydrocoupling of silanes and amines to afford aminosilane products. The broadly soluble and commercially available KOtAmyl was utilized as the benchmark precatalyst for this transformation. Challenging substrates such as anilines were found to readily couple primary, secondary, and tertiary silanes in high conversions (> 90%) after only 2 h at 40 °C. Traditionally challenging silanes such as Ph3SiH were also easily coupled to simple primary and secondary amines under mild conditions, with reactivity that rivals many rare earth and transition‐metal catalysts for this transformation. Preliminary evidence suggests the formation of hypercoordinated intermediates, but radicals were detected under catalytic conditions, indicating a mechanism that is rare for Si–N bond formation.
Because the manual counting of soybean ( Glycine max ) plants, pods, and seeds/pods is unsuitable for soybean yield predictions, alternative methods are desired. Therefore, the objective was to determine if satellite remote sensing ⁻ based artificial intelligence (AI) models could be used to predict soybean yield. In the study, multiple remote sensing ⁻ based AI models were developed for soybean growth stage ranging from VE/VC (plant emergence) to R6/R7 (full seed to beginning maturity). The ability of the Deep Neural Network (DNN), Support Vector Machine (SVM), Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), and AdaBoost to predict soybean yield, based on blue, green, red, and near infrared reflectance data collected by the PlanetScope satellite at 6 growth stages, was determined. Remote sensing and soybean yield monitor data from 3 different fields in two years (2019 and 2021) were aggregated into 24,282 grid cells that had the dimensions of 10 by 10m. A comparison across models showed that the DNN outperformed the other models. Moreover, as crops matured from VE/VC to R4/R5, the R ² value of the models increased from 0.26 to over 0.70. These findings indicate that remote sensing data collected at different growth stages can be combined for soybean yield predictions. Moreover, additional work needs to be conducted to assess the model's ability to predict soybean yield with vegetation indices (VI) data for fields not used to train the model. This article is protected by copyright. All rights reserved
Group I alkoxides are highly active precatalysts in the heterodehydrocoupling of silanes and amines to afford aminosilane products. The broadly soluble and commercially available KOtAmyl was utilized as the benchmark precatalyst for this transformation. Challenging substrates such as anilines were found to readily couple primary, secondary, and tertiary silanes in high conversions (> 90%) after only 2 h at 40 °C. Traditionally challenging silanes such as Ph3SiH were also easily coupled to simple primary and secondary amines under mild conditions, with reactivity that rivals many rare earth and transition-metal catalysts for this transformation. Preliminary evidence suggests the formation of hypercoordinated intermediates, but radicals were detected under catalytic conditions, indicating a mechanism that is rare for Si–N bond formation.
Until 2022, Vermont was one of the few US states that did not have an Environmental Justice (EJ) policy. In 2016, the Vermont Department of Environmental Conservation (DEC) initiated a process to create an EJ policy based on an agreement with the US Environmental Protection Agency (EPA). A coalition of academics, non-profit organization leaders, legal experts, and community-based partners formed in response to the DEC’s initial approach because it lacked a robust process to center the voices of the most vulnerable Vermonters. The coalition developed a mixed-method, community-based approach to ask, “What does EJ look like in Vermont?” This article reports the door-to-door survey portion of that broader research effort. The survey of 569 Vermont residents purposively sampled sites of likely environmental harm and health concerns and sites with existing relationships with activists and community organizations engaged in ongoing EJ struggles. The survey results use logistic regression to show that non-white respondents in the sites sampled were significantly more likely to be renters, to report exposures to mold, to have trouble paying for food and electricity, to lack access to public transportation, were less likely to own a vehicle, to have a primary care doctor, and reported higher rates of Lyme disease than white respondents. Our findings contribute to EJ theory regarding the co-productive relationship between environmental privilege and environmental harms within the context of persistent characterizations of Vermont as an environmental leader with abundant environmental benefits.
Developmental theories suggest that exposure to early life adversity (ELA) alters developing emotional response systems, predicting risk for psychopathology across the life span. The present study examines whether negative emotionality (NE), a trait-like measure of emotionality that develops during early childhood, mediates the association between ELA and psychopathology in a representative sample of 917 preschoolers (Mage = 3.84). Additionally, we explored whether cognitive control, which supports attentional focusing and inhibition and has been identified as a transdiagnostic protective factor, moderates the impact of heightened emotionality following adversity on psychopathology risk. We utilized parent report of adversity, psychopathology, and NE and parent report and task-based measures of cognitive control. Structural equation modeling of cross-sectional data revealed that NE partially mediated the link between ELA and psychopathology symptoms. Moreover, parent-reported cognitive control buffered this link such that the effect of ELA on psychopathology through NE was stronger in children with low versus high cognitive control. These results identify elevated NE as one mechanism linking ELA and psychopathology, specifically among children with poorer top-down control, informing our understanding of key risk and protective factors among adversity-exposed children.
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5,752 members
Osama F Harraz
  • Department of Pharmacology
Timothy Stickle
  • Department of Psychological Science
Diane M Jaworski
  • Department of Neurological Sciences
Erika Miles Edwards
  • Department of Mathematics and Statistics
Peter Dodds
  • Department of Mathematics and Statistics
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