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At least 145 records · Page 8

Assessment of the Distributed Ledger Technology for Energy Sector Industrial and Operational Applications Using the MITRE ATT&CK® ICS Matrix

In recent times, Distributed Ledger Technology (DLT) has gained significant attention for its potential application in the energy sector. Utilizing blockchain and DLT has demonstrated the ability to enhance the resilience of the electric infrastructure, which will support a more flexible infrastructure and advance grid modernization. However, the deployment of these technologies increases the overall attack surface. The MITRE ATT&CK® matrices have been developed to document an adversary’s tactics and techniques based on real-world observations. The MITRE ATT&CK® matrices provide a common taxonomy for offense and defense and have become a valuable conceptual tool across multiple cybersecurity disciplines for conveying threat intelligence, performing testing through red teaming or adversary emulation, and enhancing network and system defenses against intrusions. The MITRE ATT&CK® for Industrial Control Systems (ICS) matrix was created to provide knowledge about adversary behavior in the ICS technology domain. This study analyzes the relevance of various tactics and techniques across a seven-layer DLT engineering and cybersecurity stack, known as the DLT stack, designed by the Cybersecurity Taskforce under IEEE P2418.5 - Standard for Blockchain in Energy working group sponsored by Power and Energy Systems - Smart Buildings, Loads and Customer Systems (PES/SBLC) Technical Committee. Additionally, this paper identifies specific mitigation strategies tailored to the energy ICS environment

42 ENGINEERING↗

Advancing Energy Equity Considerations in Distribution Systems Planning

Current distribution system planning (DSP) processes do not explicitly account for energy equity considerations, such as who is most affected by power system burdens, where those burdens are concentrated, and what investments can be made to improve baseline conditions. This paper proposes an iterative framework for advancing energy equity as an objective of the DSP process, showing how measurement strategies, or metrics (informed by conceptual foundations of energy justice), can be applied to benchmark equity performance at various stages. This methodology is applied for equity-aware distributed energy resource (DER) hosting capacity analysis and outage analysis to provide critical insights on infrastructure upgrade decisions compared to a business-as-usual (BAU) case. The analysis is performed on a taxonomy feeder representing the West Coast urban/semi-urban system with augmentation of electric vehicles (EVs) and rooftop solar photovoltaic (PV) generators. The study considers disadvantaged community (DAC) and non-disadvantaged community (NDAC) load regions to enable equity-aware simulations. The results demonstrate how equity-aware planning could reveal the limitations of the traditional DSP process as DAC regions are found to have lower DER hosting capacity and higher outage vulnerability. Overall, this work provides insights on the need to incorporate energy equity as an integral part of the DSP process.

Energy Equity, Distribution System Planning, DER a↗

Enhancing Smart Home Privacy: A Tutorial on Local Differential Privacy Techniques for Frequency and Mean Estimation

The ubiquity of Internet of Things (IoT) systems has seamlessly integrated into our daily lives, particularly in smart homes where devices continuously monitor and optimize our living environments. These systems significantly contribute to home automation, energy efficiency, and overall comfort. However, this widespread connectivity poses inherent risks linked to the streaming of sensitive household data, necessitating robust privacy preservation mechanisms. This tutorial systematically examines privacy preservation through local differential privacy (LDP), with a particular focus on frequency and mean estimation techniques for smart home applications. Here, we present a comprehensive taxonomy of smart home data formats and provide detailed implementation guidance for event-based and w-event LDP mechanisms. Through practical examples using smart thermostats and HVAC systems, we demonstrate how these techniques can be effectively deployed in real-world scenarios. The tutorial concludes by examining emerging research directions, including adaptive privacy budgets and federated learning approaches, establishing a foundation for privacy-preserving smart home deployments.

Kotevska, Olivera [Oak Ridge National Laboratory (↗

Feedback and Oscillations: Constructing Feedback Systems for Root Cause Analysis of Oscillations in Power Grids

Dynamic phenomena linked to inverter-based resources (IBRs) have gained global attention. Several IBR-induced dynamics have caused bulk power system-connected wind or solar power plants to trip, and some have even led to widespread outages. In addition, many oscillations have been observed involving IBR power plants. In 2023, the IEEE Power & Energy Society (PES) IBR Subsynchronous Oscillations (SSO) task force published a journal article, “Real-World Subsynchronous Oscillation Events in Power Grids With High Penetrations of Inverter-Based Resources,” in which 19 IBR oscillation events were examined for their causation. Earlier in 2020, another PES task force article, “Definition and Classification of Power System Stability-Revisited & Extended,” authored by prominent academics, introduced converter-driven stability as a new category of stability. The international power grid industry community also took action by publishing the CIGRE Green Book, Power System Dynamic Modelling and Analysis in Evolving Networks (led by Babak Badrzadeh and Zia Emin) in 2024. In August 2024, the Energy Systems Integration Group (ESIG) released a practical guide led by Nick Miller, “Diagnosis and Mitigation of Observed Oscillations in IBR-Dominant Power System: A Practical Guide.” The goal of the guide is to assist practicing engineers in making initial judgments and conducting detailed analyses about oscillations. Finally, when addressing the classification of stability and oscillations, the guide emphasizes a causality-based taxonomy for grouping, such as voltage control-induced oscillations, synchronization-induced oscillations, and frequency or active power control-induced oscillations.

Fan, Lingling [Univ. of South Florida, Tampa, FL (↗

Application of DLT cybersecurity stack to TES applications for a scalable, cybersecure, and interoperable future

Transactive Energy Systems (TES) are expected to improve upon existing grid operations and capabilities by enabling the integration of traditional grid resources with distributed energy resources (DER). Distributed Ledger Technology or DLT (e.g., blockchain) presents itself as a viable instrument to support decentralized, autonomous, and tamper-evident applications, which can be leveraged within TES's ecosystem. DLTs can provide pertinent security controls including access controls, data immutability, and traceability in addition to other well-known advantages such as decentralization and scalability. This work demonstrates the DLT Cybersecurity stack and its applicability to TES-based use-cases/applications. The seven-layer DLT cybersecurity stack is a DLT-agnostic framework that can quickly be used to classify and group the individual needs of an application into the different processing and cybersecurity layers offered by a DLT using a common taxonomy and an architectural mapping framework. This enables application engineers to demystify and strengthen the overall security aspects of their systems while maintaining an open perspective towards features and drawbacks that may hinder their performance in real-world scenarios. The paper leverages the work performed by the IEEE P2418.5 - Blockchain for Energy Standards working group.

Blockchain, blockchain interoperability, Cybersecu↗

Identifying Adversarial Cyber-Activity in Operational Technology Environments Using Bayesian Networks

Critical infrastructure and other operational technology (OT) environments face increasing cybersecurity risks from adversarial behavior. This paper describes the development of a risk model using a Bayesian network to enhance the comprehension of observable cyber events caused by malicious activity in OT environments. The core of the Bayesian network is a process model that describes the stages of adversary behavior. The remainder of the model is based on the MITRE ATT&CK® for Industrial Control Systems (ICS) taxonomy, which includes tactics and techniques that may be used by the adversary. The observables provide evidence for adversary behavior through the intermediary technique and tactic nodes. One challenge in constructing this model is a lack of open-source data from cyber-attacks on OT systems. This paper discusses learning from limited data, the elicitation of expert opinion to construct the conditional probability tables when data is scarce, and the refinement of the most difficult conditional probabilities tables using several forms of sensitivity analyses. Finally, the Bayesian network is demonstrated using two historical case studies: the DarkSide ransomware attack on the Colonial Pipeline and the destructive cyberattack targeting the ThyssenKrupp blast furnace. Index Terms—Cybersecurity, industrial control systems, operational technology

97 - MATHEMATICS AND COMPUTING↗

A Typology of Decision-Making Tasks for Visualization

Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxonomies and typologies exist, they often focus on more granular analytical tasks that are too low-level to describe large complex decisions, which can make it difficult to reason about and design decision-support tools. In this paper, we contribute a typology of decision-making tasks that were iteratively refined from a list of design goals distilled from a literature review. Our typology is concise and consists of only three tasks: CHOOSE, ACTIVATE, and CREATE. Although decision types originating in other disciplines exist, we provide definitions for these tasks that are suitable for the visualization community. Our proposed typology offers two benefits. First, the ability to compose and hierarchically organize the tasks enables flexible and clear descriptions of decisions with varying levels of complexities. Second, the typology encourages productive discourse between visualization designers and domain experts by abstracting the intricacies of data, thereby promoting clarity and rigorous analysis of decision-making processes. We demonstrate the benefits of our typology through four case studies, and present an evaluation of the typology from semi-structured interviews with experienced members of the visualization community who have contributed to developing or publishing decision support systems for domain experts. Our interviewees used our typology to delineate the decision-making processes supported by their systems, demonstrating its descriptive capacity and effectiveness. Finally, we present preliminary findings on the usefulness of our typology for visualization design.

97 MATHEMATICS AND COMPUTING↗

Composition, Growth, Succession, and Function in the Cladophora Microbiome: Insights From Quantitative Stable Isotope Probing and NanoSIMS Imaging

The branching green macroalga Cladophora glomerata and its epiphytic microbiome dominate summer biomass in the Eel River, a Northern California river under Mediterranean (summer drought, winter rain) seasonality. Green Cladophora streamers proliferate in early summer, then change to yellow and then red-brown as epiphyte loads increase. Here, we characterised successional changes in epiphytic bacteria on Cladophora, examining both community composition and growth rates, using quantitative Stable Isotope Probing (qSIP) and 16S rRNA gene amplicon sequencing. The number of bacterial taxa increased with succession while growth rates peaked in the middle stage. NanoSIMS imaging confirmed high sulphur (S) concentrations in Cladophora cell walls relative to surrounding biomass, coinciding with a bloom of sulphur bacteria (bacteria that reduce or oxidise sulphur/sulphates). In general, relative abundances and growth rates were independent, indicating that either metric alone is insufficient for understanding how taxonomy and functional groups affect ecosystem processes. For instance, the relative abundance of nitrogen fixers peaked in the late summer when their relative growth rates were slowest. Such patterns may be driven by space competition limiting growth. Together, changes in abundance and relative growth rates suggest different limiting factors for different functional groups in the Cladophora microbiome at multiple successional stages.

Biological and medical sciences↗

taxadb: A high‐performance local taxonomic database interface

Abstract A familiar and growing challenge in ecological and evolutionary research is that of establishing consistent taxonomy when combining data from separate sources. While this problem is already well understood and numerous naming authorities have been created to address the issue, most researchers lack a fast, consistent, and intuitive way to retrieve taxonomic names. We present taxadb R package which creates a local database, managed automatically from within R, to provide fast operations on millions of taxonomic names. taxadb provides access to established naming authorities to resolve synonyms, taxonomic identifiers, and hierarchical classification in a consistent and intuitive data format. taxadb makes operation on millions of taxonomic names fast and manageable.

Norman, Kari E. A.↗

State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties

Abstract We present a state‐of‐the‐art report on time‐dependent flow topology. We survey representative papers in visualization and provide a taxonomy of existing approaches that generalize flow topology from time‐independent to time‐dependent settings. The approaches are classified based upon four categories: tracking of steady topology, reference frame adaption, pathline classification or clustering, and generalization of critical points. Our unique contributions include introducing a set of desirable mathematical properties to interpret physical meaningfulness for time‐dependent flow visualization, inferring mathematical properties associated with selective research papers, and utilizing such properties for classification. The five most important properties identified in the existing literature include coincidence with the steady case, induction of a partition within the domain, Lagrangian invariance, objectivity, and Galilean invariance.

Bujack, Roxana↗

Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization

In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. Herein we present a state–of–the–art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time–varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.

97 MATHEMATICS AND COMPUTING↗

Scalable Computation of Topological Abstractions for Scalar Data

Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial and on single machines. This paper presents the state of the art in the scalable computation of topological abstractions on scalar data, in shared memory parallel on single machines, and in distributed memory parallel on multiple machines. We highlight results for set‐based, graph‐based and complex‐based abstractions and organize the state of the art based on this taxonomy. The paper identifies parallelization and distribution techniques common in topological algorithms and highlights further areas of interest with underdeveloped efforts.

97 MATHEMATICS AND COMPUTING↗

Description of Freudenthalidium gen. nov. and Halluxium gen. nov. to Formally Recognize Clades Fr3 and H as Genera in the Family Symbiodiniaceae (Dinophyceae)

The Symbiodiniaceae are a family of marine dinoflagellates known mostly for their endosymbiotic interactions with invertebrates and protists, but facultatively and exclusively free‐living life histories in this family are also evident. A recent systematic revision of the Symbiodiniaceae replaced the clade‐based nomenclature of seven divergent lineages of “ Symbiodinium ” sensu lato with one based on formally described genera. The revised taxonomy was not extended to the whole group because type species to describe a new genus for each of the remaining clades and subclades were lacking. In an effort to characterize benthic habitats of symbiodiniaceans in sediments at Heron Island (Great Barrier Reef, Australia), we isolated >100 monoclonal Symbiodiniaceae cultures. Four of these belonged to Symbiodiniaceae ‘subclade’ Fr3, and three to Clade H, based on nucleotide sequence similarity (ITS2, LSU, cp23S, and mtCOB), representing the first cultures of these taxa. Based on these isolates, we propose two new genera: Freudenthalidium gen. nov. and Halluxium gen. nov., circumscribing Clades Fr3 and H, respectively. Three new species are described: Freudenthalidium heronense , F. endolithicum , and Halluxium pauxillum . Kofoidian tabulations of motile cells confirm previous observations that amphiesmal vesicle arrangements are generally conserved across the family. These descriptions are an important step toward completing the systematic revision of the Symbiodiniaceae. That this contribution was enabled by isolates from an endopsammic habitat highlights the potential of discovering new symbiodiniacean species in the environment, the study of which will lead to a deeper understanding of free‐living versus symbiotic life histories in this ecologically important family of dinoflagellates.

Nitschke, Matthew R.↗

The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization

Abstract Background Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. Animals No live animals were used. Methods The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence–readiness. Results VBO is an open, community-driven ontology representing over 19 500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. Conclusion and Clinical Importance The adoption of VBO as a standard for breed names in databases and veterinary electronic health records enhances veterinary data interoperability and computability, supporting precision medicine.

Veterinary Sciences↗

Genetic time traveling: sequencing old herbarium specimens, including the oldest herbarium specimen sequenced from kingdom Fungi, reveals the population structure of an agriculturally significant rust

Summary Sequencing herbarium specimens can be instrumental in answering ecological, evolutionary, and taxonomic inquiries. We developed a protocol for sequencing herbarium specimens of rust fungi (Pucciniales) and proceeded to sequence specimens ranging from 4 to 211 yr old from five different genera. We then obtained sequences from an economically important biological control agent, Puccinia suaveolens , to highlight the potential of sequencing herbarium specimens in an ecological sense and to evaluate the following hypotheses: (1) The population structure of a plant pathogen changes over time, and (2) introduced pathogens are more diverse in their native range. Our efforts resulted in sequences from 87 herbarium specimens that revealed a high level of diversity with a population structure that exhibited spatial–temporal patterns. The specimens sequenced from Europe showed more diversity than the ones from North America, uncovering an invasion pattern likely related to its European native host in North America. Additionally, to the best of our knowledge, the specimen from France collected in c. 1811 is the oldest herbarium specimen sequenced from kingdom Fungi. In conclusion, sequencing old herbarium specimens is an important tool that can be extrapolated to better understand plant–microbe evolution and to evaluate old type specimens to solidify the taxonomy of plant pathogenic fungi.

Plant Sciences↗

High-throughput genetic engineering of nonmodel and undomesticated bacteria via iterative site-specific genome integration

Efficient genome engineering is critical to understand and use microbial functions. Despite recent development of tools such as CRISPR-Cas gene editing, efficient integration of exogenous DNA with well-characterized functions remains limited to model bacteria. Here, we describe serine recombinase–assisted genome engineering, or SAGE, an easy-to-use, highly efficient, and extensible technology that enables selection marker–free, site-specific genome integration of up to 10 DNA constructs, often with efficiency on par with or superior to replicating plasmids. SAGE uses no replicating plasmids and thus lacks the host range limitations of other genome engineering technologies. We demonstrate the value of SAGE by characterizing genome integration efficiency in five bacteria that span multiple taxonomy groups and biotechnology applications and by identifying more than 95 heterologous promoters in each host with consistent transcription across environmental and genetic contexts. We anticipate that SAGE will rapidly expand the number of industrial and environmental bacteria compatible with high-throughput genetics and synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Community Structure of Arbuscular Mycorrhizal Fungi in Soils of Switchgrass Harvested for Bioenergy

We assessed the different species of beneficial fungi living in agricultural fields of switchgrass, a large grass grown for biofuels, using high-resolution DNA sequencing. Contrary to our expectations, the fungi were not greatly affected by fertilization. However, we found a positive relationship between plant productivity and the number of families of beneficial fungi at one site. Furthermore, we sequenced many species that could not be identified with existing reference databases. One group of fungi was highlighted in an earlier study for being widely distributed but of unknown taxonomy. We discovered that this group belonged to a family called Pervetustaceae , which may benefit switchgrass in stressful environments. To produce higher-yielding switchgrass in a more sustainable manner, it could help to study these undescribed fungi and the ways in which they may contribute to greater switchgrass yield in the absence of fertilization.

59 BASIC BIOLOGICAL SCIENCES↗