Digital Commons Network^™

Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …

Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Proposes a Decentralized and Coordinated Voltage and Frequency (V-F) Control Framework for Islanded Microgrids, with Full Consideration of the Limited Capacity of Distributed Energy Resources (DERs) and V-F Dependent Load. First, the Concept of DER Inadequacy is Illustrated with the Challenges It Poses. Then, a Decentralized and Coordinated Control Framework is Proposed to Regulate the Output of Inverter-Based Generations and Reallocate Limited DER Capacity for V-F Control. the Control Framework is Composed of a Power Regulator and a V-F Regulator, Which Generates the Supplementary Signals for the Primary Controller. the Power Regulator Regulates the Output of Grid-Forming Inverters …

Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

We Propose a Deep Learning Approach to Segment the Skin Lesion in Dermoscopic Images. the Proposed Network Architecture Uses a Pretrained Efficient Net Model in the Encoder and Squeeze-And-Excitation Residual Structures in the Decoder. We Applied This Approach on the Publicly Available International Skin Imaging Collaboration (ISIC) 2017 Challenge Skin Lesion Segmentation Dataset. This Benchmark Dataset Has Been Widely Used in Previous Studies. We Observed Many Inaccurate or Noisy Ground Truth Labels. to Reduce Noisy Data, We Manually Sorted All Ground Truth Labels into Three Categories — Good, Mildly Noisy, and Noisy Labels. Furthermore, We Investigated the Effect of Such …

Inverter Pq Control With Trajectory Tracking Capability For Microgrids Based On Physics-Informed Reinforcement Learning, Buxin She, Fangxing Li, Hantao Cui, Hang Shuai, Oroghene Oboreh-Snapps, Rui Bo, Nattapat Praisuwanna, Jingxin Wang, Leon M. Tolbert

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing penetration of inverter-based resources (IBRs) calls for an advanced active and reactive power (PQ) control strategy in microgrids. To enhance the controllability and flexibility of the IBRs, this paper proposed an adaptive PQ control method with trajectory tracking capability, combining model-based analysis, physics-informed reinforcement learning (RL), and power hardware-in-the-loop (HIL) experiments. First, model-based analysis proves that there exists an adaptive proportional-integral controller with time-varying gains that can ensure any exponential PQ output trajectory of IBRs. These gains consist of a constant factor and an exponentially decaying factor, which are then obtained using a model-free deep reinforcement learning approach …

Datasets From: Application Of Aerial Insar To Measure Glacier Elevations, Bryce Glenn, Andrew G. Fountain, Delywn Moller

Geology Faculty Datasets

In September 2016 NASA flew an interferometric synthetic aperture radar (GLISTIN) over most of the glacier-covered regions of the coterminous USA for the purpose of mapping the surface elevation of the glaciers. Where multiple passes were flown over the same ground track, the data were mosaiced together to improve data coverage and elevation accuracy. These data are to be used with elevations collected by past and future efforts to calculate volume change of glaciers.

The data were the basis for:

Glenn, Bryce Allen, "Assessing Airborne Radar to Map Glacier Elevations in Alpine Terrain Including Estimated Glacier Volume Change …

Bidirectional Asymmetric Clllc Resonant Dc-Dc Converter For Onboard Electric Vehicle Chargers, Angshuman Sharma, Alvaro Cardoza, Kartikeya J.P. Veeramraju, Oroghene Oboreh-Snapps, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Bidirectional CLLLC resonant dc-dc converters with an asymmetric tank can narrow the switching frequency bandwidth required to meet the asymmetric voltage gains in the two directions of power flow. Consequently, higher power density and efficiency may be feasible. in this paper, a CLLLC resonant converter with asymmetric primary and secondary capacitances is investigated for charging and discharging the next-generation 900 V traction battery of an electric vehicle. First, a new voltage gain equation is formulated using the First Harmonic Approximation. Then, the proposed gain equation is used to design the asymmetric resonant tank. the effects of asymmetric capacitances on the …

Retracted: A Robust Integrated Approach For Optimal Management Of Power Networks Encompassing Wind Power Plants, Aliasghar Baziar, Mohammad Reza Akbarizadeh, Amin Hajizadeh, Mousa Marzband, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper basically concentrates on providing some significant steps for congestion management of the power systems based on an interval-Based robust chance constrained transmission switching (IBRCC-TS) approach for decreasing the congestion of the system while increasing the robustness of the system against uncertainties of the wind turbines. However, the utilization of TS approach in the power system is a severe challenge, since there is no limitation over the switching rate during a certain timespan in the network as well as the power switches' failure uncertainty. Besides, the frequent switching by the TS method decreases the switch maintenance and puts the …

Futures On Dry Ground: Anthropology And Coastal Planning, Theodore Hilton, Sheehan Moore

Publications and Research

Around the world, governments, industry, and other actors are creating plans to save coasts from environmental crisis. Louisiana is one prominent example: levees and other measures protect oil and gas infrastructure from inundation as the wetlands buffer rapidly erodes—in large part due to that same industry. The state’s primary answer to land loss is a $50 billion Coastal Master Plan. To illuminate such responses in Louisiana and globally, this article reviews emerging literature and frames an anthropology of coastal planning around three themes: (1) novel orientations toward time and space, (2) the reproduction of power and capital in the name …

Molecular Mechanism Behind The Safe Immunostimulatory Effect Of Withania Somnifera, Kriti Kalpana, Shen Yap, Moriya Tsuji, Akira Kawamura

Publications and Research

Withania somnifera (L.) Dunal (family Solanaceae) is a medicinal plant known for, among many pharmacological properties, an immune boosting effect. Our recent study revealed that its key immunostimulatory factor is lipopolysaccharide of plant-associated bacteria. This is peculiar, because, although LPS can elicit protective immunity, it is an extremely potent pro-inflammatory toxin (endotoxin). However, W. somnifera is not associated with such toxicity. In fact, despite the presence of LPS, it does not trigger massive inflammatory responses in macrophages. To gain insights into the safe immunostimulatory effect of W. somnifera, we conducted a mechanistic study on its major phytochemical constituent, …

Changes To Sea Surface Temperatures And Vertical Wind Shear And Their Influence On Tropical Cyclone Activity In The Caribbean And The Main Developing Region, Keneshia Hibbert, Equisha Glenn, Thomas M. Smith, Jorge E. González-Cruz

Publications and Research

Sea surface temperatures and vertical wind shear are essential to tropical cyclone formation. TCs need warm SSTs and low shear for genesis. Increasing SSTs and decreasing VWS influences storm development. This work analyzes SST and VWS trends for the Caribbean, surrounding region, and the Atlantic hurricane main developing region from 1982–2020. Storm intensity increases significantly during this period. Annual and seasonal trends show that regional SSTs in the MDR are warming annually at 0.0219 °C yr⁻¹ and, per season, 0.0280 °C yr⁻¹. Simultaneously, VWS decreases during the late rainfall season, at 0.056 m/s yr⁻¹ in the …

Structure–Activity Relationship Studies On 6-Chloro-1-Phenylbenzazepines Leads To The Identification Of A New Dopamine D1 Receptor Antagonist, Rajan Giri, Hari K. Namballa, Vishwashiv Emogaje, Wayne W. Harding

Publications and Research

The 1-phenylbenzazepine template has yielded a number of D1R-like ligands, which, though useful as pharmacological tools, have significant drawbacks in terms of selectivity versus D5R as well as pharmacokinetic behavior. A number of 1-phenylbenzazepines contain a 6-chloro functional group, but extensive SAR studies around the 6-chloro-1-phenylbenzazepine framework have not been reported in the literature. To further understand the tolerance of the 6-chloro-1-phenylbenzazepine template for various substituent groups towards affinity and selectivity at D1R, we synthesized two series of analogs with structural variations at the C-7, C-8, N-3, C-3′ and C-4′ positions. The series 2 analogs differed from …

Ecological Niche Comparison Among Closely Related Tree Species Of Lauraceae Using Climatic And Edaphic Data, Laura J. Giraldo-Kalil, Gonzalo E. Pinilla Buitrago, Andrés Lira-Noriega, Francisco Lorea-Hernández, Juan Núñez-Farfán

Publications and Research

ABSTRACT:

Edaphic specialization is considered to promote ecological differentiation among closely related species of Damburneya (Lauraceae) occurring in sympatry. However, little is known about the effects of soil and other key environmental factors like climate on the ecological niche and distribution of these tree species. Here, we assessed the role of climate and soil on niche divergence and potential distribution of four Damburneya species whose distributions span Central America and Mexico. We performed ecological niche modeling with MaxEnt using three sets of environmental data: climatic-only, edaphic-only, and a combination of both, to characterize species niches and suitable distribution areas. Niche …

Hamiltonian Structure Of 2d Fluid Dynamics With Broken Parity, Gustavo Machado Monteiro, Alexander G. Abanov, Sriram Ganeshan

Publications and Research

Isotropic fluids in two spatial dimensions can break parity symmetry and sustain transverse stresses which do not lead to dissipation. Corresponding transport coefficients include odd viscosity, odd torque, and odd pressure. We consider an isotropic Galilean invariant fluid dynamics in the adiabatic regime with momentum and particle density conservation. We find conditions on transport coefficients that correspond to dissipationless and separately to Hamiltonian fluid dynamics. The restriction on the transport coefficients will help identify what kind of hydrodynamics can be obtained by coarse-graining a microscopic Hamiltonian system. Interestingly, not all parity-breaking transport coefficients lead to energy conservation and, generally, the …

Inclusive Random Sampling In Graphs And Networks, Yitzchak Novick, Amotz Bar-Noy

Publications and Research

It is often of interest to sample vertices from a graph with a bias towards higher-degree vertices. One well-known method, which we call random neighbor or RN, involves taking a vertex at random and exchanging it for one of its neighbors. Loosely inspired by the friendship paradox, the method is predicated on the fact that the expected degree of the neighbor is greater than or equal to the expected degree of the initial vertex. Another method that is actually perfectly analogous to the friendship paradox is random edge, or RE, where an edge is sampled at random, and then one …

Logic As Applied Mathematics — With Particular Application To The Notion Of Logical Form, Graham Priest

Publications and Research

The word ‘logic’ has many senses. Here we will understand it as meaning an account of what follows from what and why. With contemporary methodology, logic in this sense – though it may not always have been thought of in this way – is a branch of applied mathematics. This has various implications for how one understands a number of issues concerning validity. In this paper I will explain this perspective of logic, and explore some of its consequences with respect to the notion of logical form.

Fabrication And Errors In The Bibliographic Citations Generated By Chatgpt, William H. Walters, Esther Isabelle Wilder

Publications and Research

Although chatbots such as ChatGPT can facilitate cost-effective text generation and editing, factually incorrect responses (hallucinations) limit their utility. This study evaluates one particular type of hallucination: fabricated bibliographic citations that do not represent actual scholarly works. We used ChatGPT-3.5 and ChatGPT-4 to produce short literature reviews on 42 multidisciplinary topics, compiling data on the 636 bibliographic citations (references) found in the 84 papers. We then searched multiple databases and websites to determine the prevalence of fabricated citations, to identify errors in the citations to non-fabricated papers, and to evaluate adherence to APA citation format. Within this set of documents, …

Lead Induced Differences In Bone Properties In Osteocalcin +/+ And −/− Female Mice, G. Yildirim, W. C. Budell, O. Berezovska, S. Yagerman, S. S. Maliath, P. Mastrokostas, S. Tommasini, T. L. Dowd

Publications and Research

Lead (Pb) toxicity is a major health problem and bone is the major reservoir. Lead is detrimental to bone, affects bone remodelingand is associated with elderly fractures. Osteocalcin (OC) affects bone remodeling, improves fracture resistance and decreases with age and in some diseases. The effect of lead in osteocalcin depleted bone is unknown and of interest. We compared bone mineral properties of control and Pb exposed (from 2 to 6 months) femora from female adult C57BL6 OC+/+ and OC−/− mice using Fourier Transform Infrared Imaging (FTIRI), Micro-computed tomography (uCT), bone biomechanical measurements and serum turnover markers (P1NP, CTX). Lead significantly …

Aligning Retrograde Nuclear Cluster Orbits With An Active Galactic Nucleus Accretion Disc, Syeda S. Nasim, Gaia Fabj, Freddy Caban, Amy Secunda, K. E. Saavik Ford, Barry Mckernan, Jillian M. Bellovary, Nathan W. C. Leigh, Wladimir Lyra

Publications and Research

Stars and stellar remnants orbiting a supermassive black hole (SMBH) can interact with an active galactic nucleus (AGN) disc. Over time, prograde orbiters (inclination i < 90°) decrease inclination, as well as semimajor axis (a) and eccentricity (e) until orbital alignment with the gas disc (‘disc capture’). Captured stellar-origin black holes (sBH) add to the embedded AGN population that drives sBH–sBH mergers detectable in gravitational waves using LIGO–Virgo–KAGRA or sBH–SMBH mergers detectable with Laser Interferometer Space Antenna. Captured stars can be tidally disrupted by sBH or the SMBH or rapidly grow into massive ‘immortal’ stars. Here, we investigate the behaviour of polar and retrograde orbiters …

Astrophysics With The Laser Interferometer Space Antenna, Pau Amaro-Seoane, Jeff Andrews, Manuel Arca Sedda, Abbas Askar, Quentin Baghi, Razvan Balasov, Imre Bartos, Simone S. Bavera, Jillian Bellovary, Christopher P. L. Berry, Emanuele Berti, Stefano Bianchi, Laura Blecha, Stéphane Blondin, Tamara Bogdanović, Samuel Boissier, Matteo Bonetti, Silvia Bonoli, Elisa Bortolas, Katelyn Breivik, Pedro R. Capelo, Laurentiu Caramete, Federico Cattorini, Maria Charisi, Sylvain Chaty, Xian Chen, Martyna Chruślińska, Alvin J. K. Chua, Ross Church, Monica Colpi, Daniel D’Orazio, Camilla Danielski, Melvyn B. Davies, Pratika Dayal, Alessandra De Rosa, Andrea Derdzinski, Kyriakos Destounis, Massimo Dotti, Ioana Duţan, Irina Dvorkin, Gaia Fabj, Thierry Foglizzo, Saavik Ford, Jean-Baptiste Fouvry, Alessia Franchini, Tassos Fragos, Chris Fryer, Massimo Gaspari, Davide Gerosa, Luca Graziani, Paul Groot, Melanie Habouzit, Daryl Haggard, Zoltan Haiman, Wen-Biao Han, Alina Istrate, Peter H. Johansson, Fazeel Mahmood Khan, Tomas Kimpson, Kostas Kokkotas, Albert Kong, Valeriya Korol, Kyle Kremer, Thomas Kupfer, Astrid Lamberts, Shane Larson, Mike Lau, Dongliang Liu, Nicole Lloyd-Ronning, Giuseppe Lodato, Alessandro Lupi, Chung-Pei Ma, Tomas Maccarone, Ilya Mandel, Alberto Mangiagli, Michela Mapelli, Stéphane Mathis, Lucio Mayer, Sean Mcgee, Barry Mckernan, M. Coleman Miller, David F. Mota, Matthew Mumpower, Syeda S. Nasim, Gijs Nelemans, Scott Noble, Fabio Pacucci, Francesca Panessa, Vasileios Paschalidis, Hugo Pfister, Delphine Porquet, John Quenby, Angelo Ricarte, Friedrich K. Röpke, John Regan, Stephan Rosswog, Ashley Ruiter, Milton Ruiz, Jessie Runnoe, Raffaella Schneider, Jeremy Schnittman, Amy Secunda, Alberto Sesana, Naoki Seto, Lijing Shao, Stuart Shapiro, Carlos Sopuerta, Nicholas C. Stone, Arthur Suvorov, Nicola Tamanini, Tomas Tamfal, Thomas Tauris, Karel Temmink, John Tomsick, Silvia Toonen, Alejandro Torres-Orjuela, Martina Toscani, Antonios Tsokaros, Caner Unal, Verónica Vázquez-Aceves, Rosa Valiante, Maurice Van Putten, Jan Van Roestel, Christian Vignali, Marta Volonteri, Kinwah Wu, Ziri Younsi, Shenghua Yu, Silvia Zane, Lorenz Zwick, Fabio Antonini, Vishal Baibhav, Enrico Barausse, Alexander Bonilla Rivera, Marica Branchesi, Graziella Branduardi-Raymont, Kevin Burdge, Srija Chakraborty, Jorge Cuadra, Kristen Dage, Benjamin Davis, Selma E. De Mink, Roberto Decarli, Daniela Doneva, Stephanie Escoffier, Poshak Gandhi, Francesco Haardt, Carlos O. Lousto, Samaya Nissanke, Jason Nordhaus, Richard O’Shaughnessy, Simon Portegies Zwart, Adam Pound, Fabian Schussler, Olga Sergijenko, Alessandro Spallicci, Daniele Vernieri, Alejandro Vigna-Gómez

Publications and Research

The Laser Interferometer Space Antenna (LISA) will be a transformative experiment for gravitational wave astronomy, and, as such, it will offer unique opportunities to address many key astrophysical questions in a completely novel way. The synergy with ground-based and space-born instruments in the electromagnetic domain, by enabling multi-messenger observations, will add further to the discovery potential of LISA. The next decade is crucial to prepare the astrophysical community for LISA’s first observations. This review outlines the extensive landscape of astrophysical theory, numerical simulations, and astronomical observations that are instrumental for modeling and interpreting the upcoming LISA datastream. To this aim, …

Feeling Analogue: Using Modular Synthesizers, Designing Synthesis Communities, Eliot Bates

Publications and Research

When Harald Bode nominally invented the modular synthesiser in 1960, it was not yet clear whether it was a musical instrument or a less-defined form of studio-sited audio technology (Subotnik 1970). Much of the technology, from the interface design to the specific parts, was shared with nonmusical test and measurement equipment. Sixty years later, hardware modular synthesis is used not just for musical creation but for noise, sound art and data sonification/visualization. Through an ethnographic study of the design and use of the Eurorack modular synthesis format, and of modular synthesis maker and user communities spread through North America, Europe …

An Equivalence Checking Framework For Agile Hardware Design, Yanzhao Wang, Fei Xie, Zhenkun Yang, Pascuale Cocchini, Jin Yang

Computer Science Faculty Publications and Presentations

Agile hardware design enables designers to produce new design iterations efficiently. Equivalence checking is critical in ensuring that a new design iteration conforms to its specification. In this paper, we introduce an equivalence checking framework for hardware designs represented in HalideIR. HalideIR is a popular intermediate representation in software domains such as deep learning and image processing, and it is increasingly utilized in agile hardware design.We have developed a fully automatic equivalence checking workflow seamlessly integrated with HalideIR and several optimizations that leverage the incremental nature of agile hardware design to scale equivalence checking. Evaluations of two deep learning accelerator …

The Role Of Preprocessing For Word Representation Learning In Affective Tasks, Nastaran Babanejad, Heidar Davoudi, Ameeta Agrawal, Manos Papagelis

Computer Science Faculty Publications and Presentations

Affective tasks, including sentiment analysis, emotion classification, and sarcasm detection have drawn a lot of attention in recent years due to a broad range of useful applications in various domains. The main goal of affect detection tasks is to recognize states such as mood, sentiment, and emotions from textual data (e.g., news articles or product reviews). Despite the importance of utilizing preprocessing steps in different stages (i.e., word representation learning and building a classification model) of affect detection tasks, this topic has not been studied well. To that end, we explore whether applying various preprocessing methods (stemming, lemmatization, stopword removal, …

An Improved Lower Bound For Sparse Reconstruction From Subsampled Walsh Matrices, Jaroslaw Blasiok, Patrick Lopatto, Kyle Luh, Jake Marcinek, Shravas Rao

Computer Science Faculty Publications and Presentations

We give a short argument that yields a new lower bound on the number of uniformly and independently subsampled rows from a bounded, orthonormal matrix necessary to form a matrix with the restricted isometry property. We show that a matrix formed by uniformly and independently subsampling rows of an N ×N Walsh matrix contains a K-sparse vector in the kernel, unless the number of subsampled rows is Ω(KlogKlog(N/K)) — our lower bound applies whenever min(K,N/K) > logC N. Containing a sparse vector in the kernel precludes not only the restricted isometry property, but more generally the application of those matrices for …

Learned Compressive Representations For Single-Photon 3d Imaging, Felipe Gutierrez-Barragan, Fangzhou Mu, Andrei Ardelean, Atul Ingle, Claudio Bruschini, Edoardo Charbon, Yin Li, Mohit Gupta, Andreas Velten

Computer Science Faculty Publications and Presentations

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that encodes distances along the time axis. As the spatio-temporal resolution of the histogram tensor increases, the in-pixel memory requirements and output data rates can quickly become impractical. To overcome this limitation, we propose a family of linear compressive representations of histogram tensors that can be computed efficiently, in an online fashion, as a matrix operation. We design practical lightweight compressive representations …

Rdkg: A Reinforcement Learning Framework For Disease Diagnosis On Knowledge Graph, Shipeng Guo, Kunpeng Liu, Pengfei Wang, Weiwei Dai, Yi Du, Yuanchun Zhou, Wenjuan Cui

Computer Science Faculty Publications and Presentations

Automatic disease diagnosis from symptoms has attracted much attention in medical practices. It can assist doctors and medical practitioners in narrowing down disease candidates, reducing testing costs, improving diagnosis efficiency, and more importantly, saving human lives. Existing research has made significant progress in diagnosing disease but was limited by the gap between interpretability and accuracy. To fill this gap, in this paper, we propose a method called Reinforced Disease Diagnosis on Knowlege Graph (RDKG). Specifically, we first construct a knowledge graph containing all information from electronic medical records. To capture informative embeddings, we propose an enhanced knowledge graph embedding method …

Does Variability In Recognition Memory Scale With Mean Memory Strength Or Encoding Variability In The Uvsd Model?, Rory W. Spanton, Christopher J. Berry

School of Psychology

The unequal variance signal detection (UVSD) model of recognition memory assumes that the variance of old item memory strength (σo) is typically greater than that of new items. It has been suggested that this old item variance effect can be explained by the encoding variability hypothesis. However, Spanton and Berry (2020) failed to find evidence for this account, suggesting that σo may simply scale with mean memory strength ( d) in the UVSD model. Experiments 1 and 2 examined the effects of encoding variability and strength scaling on old item variance by creating conditions in which mean memory strength and …

Coastal Groundwater-Dependent Ecosystems Are Falling Through Policy Gaps, Madeleine Dyring, Melissa M. Rohde, Ray Froend, Harald Hofmann

Research outputs 2022 to 2026

Coastal groundwater-dependent ecosystems (GDEs), such as wetlands, estuaries and nearshore marine habitats, are biodiversity hotspots that provide valuable ecosystem services to society. However, coastal groundwater and associated ecosystems are under threat from groundwater exploitation and depletion, as well as climate change impacts from sea-level rise and extreme flood and drought events. Despite many well-intentioned policies focused on sustainable groundwater use and species protection, coastal GDEs are falling through gaps generated by siloed policies and as a result, are declining in extent and ecological function. This study summarized then examined policies related to the management of coastal groundwater and connected ecosystems …

Flaws In The Methodologies For Organic Carbon Analysis In Seagrass Blue Carbon Soils, Oscar Serrano, Ines Mazarrasa, James W. Fourqurean, Eduard Serrano, Jeffrey Baldock, Jonathan Sanderman

Research outputs 2022 to 2026

The ability to accurately measure organic carbon (OC) in marine sediments or soils is overall taken for granted in scientific communities, yet this seemingly mundane task remains a methodological challenge when the soil matrix contains calcium carbonate (CaCO3), creating inaccuracies in Blue Carbon estimates. Here, we compared five common methods combining acidification, combustion, and wet oxidation pre-treatments for determination of OC in sediments and soils containing CaCO3 based on the analyses of artificial soil mixtures made of different OC and CaCO3 contents, and multiple soils from Australian seagrass cores. The results obtained showed that methods involving acidification pre-treatment entailed −17 …

Measuring What Matters In Healthcare: A Practical Guide To Psychometric Principles And Instrument Development, Katina Swan, Renee Speyer, Martina Scharitzer, Daniele Farneti, Ted Brown, Virginie Woisard, Reinie Cordier

Research outputs 2022 to 2026

The provision of quality healthcare relies on scales and measures with robust evidence of their psychometric properties. Using measurement instruments with poor reliability, validity, or feasibility, or those that are not appropriate for the target diagnostic group or construct/dimension under consideration, may be unfavorable for patients, unproductive, and hinder empirical advancement. Resources from the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) group can assist in identifying and developing psychometrically sound measures. The COSMIN initiative is the only international, research-based practice taxonomy and methodological guidelines for measurement in healthcare. This manuscript aims to provide an accessible introduction …

Development Of A Scoring Tool For Australian Rural Food Retail Environments, Tracy L. Schumacher, Carissa A. Alderton, Leanne J. Brown, Susan Heaney, Laura Alston, Katherine Kent, Stephanie L. Godrich

Research outputs 2022 to 2026

Current tools scoring the healthiness of food retail outlets do not reflect outlets found in rural locations. This study aimed to adapt pre-existing Australian scoring tools to represent non-metropolitan areas. Rural nutrition experts were identified, and a modified Delphi technique was used to adapt two pre-existing, food-scoring tools in five iterative stages. Stages included identifying all relevant outlets, providing a description and score for each, ensuring consistency between outlet scores and pre-existing, metro-centric tools, and providing instructions for correct use. Six rural nutrition experts were identified and engaged in the modified Delphi technique. The final tool consisted of 12 categories …