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At least 19 records

Overview of RFID Applications Utilizing Neural Networks

As Radio Frequency Identification (RFID) methods continue to evolve to higher levels of complexity, one form of machine learning is making its appearance. The use of Neural Networks (NN) in the RFID field is steadily increasing, and in the fields of localization and activity recognition, promising results are being shown from a variety of research. RFID applications fall primarily under two types of problems including regression and classification. We analyze RIFD localization techniques which fall under regression, and activity recognition which falls under classification. Many works don’t classify themselves as activity recognition methods, but because they fall under the classification category, we still consider them as activity recognition techniques. This research overviews the Neural Network models in the localization field based on whether they can perform independently of the environment in which they were tested. For activity recognition and accessory fields, the major methods involve tag-based and tag-free approaches. In conclusion, after the models are surveyed, a comparison study is given to examine what may be the cause for increased accuracy between different Neural Network models.

42 ENGINEERING↗

Robustness of topological persistence in knowledge distillation for wearable sensor data

Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.

97 MATHEMATICS AND COMPUTING↗

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Diversity in the Common Fold: Structural Insights into Class D β-Lactamases from Gram-Negative Pathogens

Class D β-lactamases (DBLs) represent a major threat to antibiotic efficacy by hydrolyzing β-lactam drugs, including last-resort carbapenems, thereby driving antimicrobial resistance in Gram-negative bacteria. The enzymes share a structurally conserved two-domain α/β architecture with seven active-site motifs and three flexible extended loops (the P-loop, Ω-loop, and newly designated B-loop) that surround the active site. While each of these loops is known to influence enzyme function, their coordinated roles have not been fully elucidated. To investigate the significance of their interplay, we compared the sequences and crystal structures of 40 DBLs from clinically relevant Gram-negative pathogens and performed molecular dynamics simulations on selected representatives. Combined structural and dynamical analyses revealed a strong correlation between B-loop architecture and carbapenemase activity in the pathogens Klebsiella and Acinetobacter, particularly regarding loop length and spatial organization. These findings emphasize the B-loop’s critical contribution, in concert with the P- and Ω-loops, in tuning active site versatility, substrate recognition, catalytic activity, and structural stability. A deeper understanding of how these motifs and loops govern DBL function may inform the development of novel antibiotics and inhibitors targeting this class of enzymes.

antibiotic resistance↗

Transcriptomic and Proteomic Insights into Host Immune Responses in Pediatric Severe Malarial Anemia: Dysregulation in HSP60-70-TLR2/4 Signaling and Altered Glutamine Metabolism

Severe malarial anemia (SMA, Hb < 6.0 g/dL) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission zones. This study explored the entire expressed human transcriptome in whole blood from 66 Kenyan children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25), focusing on host immune response networks. RNA-seq analysis revealed 6862 differentially expressed genes, with equally distributed up-and down-regulated genes, indicating a complex host immune response. Deconvolution analyses uncovered leukocytic immune profiles indicative of a diminished antigenic response, reduced immune priming, and polarization toward cellular repair in SMA. Weighted gene co-expression network analysis revealed that immune-regulated processes are central molecular distinctions between non-SMA and SMA. A top dysregulated immune response signaling network in SMA was the HSP60-HSP70-TLR2/4 signaling pathway, indicating altered pathogen recognition, innate immune activation, stress responses, and antigen recognition. Validation with high-throughput gene expression from a separate cohort of Kenyan children (n = 50) with varying severities of malarial anemia (n = 38 non-SMA and n = 12 SMA) confirmed the RNA-seq findings. Proteomic analyses in 35 children with matched transcript and protein abundance (n = 19 non-SMA and n = 16 SMA) confirmed dysregulation in the HSP60-HSP70-TLR2/4 signaling pathway. Additionally, glutamine transporter and glutamine synthetase genes were differentially expressed, indicating altered glutamine metabolism in SMA. This comprehensive analysis underscores complex immune dysregulation and novel pathogenic features in SMA.

Microbiology↗

Mineral dissolution by dimeric complexes

Mineral dissolution is typically thought to occur by the detachment of monomeric building blocks of the crystal structure, although direct evidence is rare. Using in situ high-speed atomic force microscopy to examine step-edge retreat dynamics at high resolution, we report that the dissolution of gibbsite in alkaline solutions occurs mainly by the release of aluminate dimers, which subsequently dissociate into the monomeric species that dominate the solution. Here, the observed dissolution anisotropy is readily explained by this mechanism, which was further supported by density functional tight-binding simulations of detachment activation energies. Recognition that such polynuclear dissolution mechanisms exist may enable an improved understanding of processes regulating mineral dissolution rates in nature and industry.

atomic force microscopy↗

Quantifying Operational Drivers of Multimodal Biometric Verification in Aerial Surveillance

Multimodal biometric verification is increasingly applied across operational contexts ranging from close-range security cameras and building-mounted surveillance to long-range ground sensors and unmanned aerial system (UAS) imagery. Variations in acquisition conditions—such as image resolution, viewing geometry, and motion artifacts—pose significant challenges for cross-domain algorithmic generalization. This study evaluates two independent multimodal biometric verification systems developed under the Intelligence Advanced Research Projects Activity (IARPA) Biometric Recognition and Identification at Altitude and Range (BRIAR) program, comparing performance on close-range and aerial datasets. Close-range video served as a baseline to quantify the decline in verification performance on aerial footage. The dataset included six UAS platforms, spanning small quadcopters at 10m altitude to medium-sized fixed-wing aircraft at 360m. Mixed-effects logistic regression identified image resolution (head and body pixel counts), head height, sensor characteristics, and algorithm selection as primary determinants of verification success, whereas demographic attributes and mission gait were not significant predictors. Activity type and collection site influenced performance in close-range data but had negligible impact on UAS imagery. These results clarify modality-specific strengths and limitations and highlight opportunities to enhance cross-domain biometric verification.

Peluso, Alina [ORNL] (ORCID:0000000328950406)↗

A minimal complex of KHNYN and zinc-finger antiviral protein binds and degrades single-stranded RNA

Detecting viral infection is a key role of the innate immune system. The genomes of some RNA viruses have a high CpG dinucleotide content relative to most vertebrate cell RNAs, making CpGs a molecular marker of infection. The human zinc-finger antiviral protein (ZAP) recognizes CpG, mediates clearance of the foreign CpG-rich RNA, and causes attenuation of CpG-rich RNA viruses. While ZAP binds RNA, it lacks enzymatic activity that might be responsible for RNA degradation and thus requires interacting cofactors for its function. One of these cofactors, KHNYN, has a predicted nuclease domain. Using biochemical approaches, we found that the KHNYN NYN domain is a single-stranded RNA ribonuclease that does not have sequence specificity and digests RNA with or without CpG dinucleotides equivalently in vitro. We show that unlike most KH domains, the KHNYN KH domain does not bind RNA. Indeed, a crystal structure of the KH region revealed a double-KH domain with a negatively charged surface that accounts for the lack of RNA binding. Rather, the KHNYN C-terminal domain (CTD) interacts with the ZAP RNA-binding domain (RBD) to provide target RNA specificity. We define a minimal complex composed of the ZAP RBD and the KHNYN NYN-CTD and use a fluorescence polarization assay to propose a model for how this complex interacts with a CpG dinucleotide-containing RNA. In the context of the cell, this module would represent the minimum ZAP and KHNYN domains required for CpG-recognition and ribonuclease activity essential for attenuation of viruses with clusters of CpG dinucleotides.

Yeoh, Zoe C. (ORCID:0000000226949068)↗

Depletion of the Protein Hydration Shell with Increasing Temperature Observed by Small-Angle X-ray Scattering and Molecular Simulations

The hydration shell is an integral part of proteins since it plays key roles in conformational transitions, molecular recognition, and enzymatic activity. While the dynamics of the hydration shell have been described by spectroscopic techniques, the structure of the hydration shell remains less understood due to the lack of hydration shell-sensitive structural probes with high spatial resolution. We combined temperature-ramp small-angle X-ray scattering (T-ramp SAXS) from 255 to 335 K with molecular simulations to demonstrate that the hydration shells of the IgG-binding domain of Protein G (GB3) and the villin headpiece are remarkably temperature-sensitive. For proteins in the folded state, T-ramp SAXS data and explicit-solvent SAXS predictions consistently demonstrate decays of protein contrasts and radii of gyration with increasing temperature, which are shown to reflect predominantly temperature-sensitive, depleting hydration shells. The depletion is caused not merely by enhanced disorder within the hydration shells but also by partial displacements of surface-coordinated water molecules. Together, T-ramp SAXS and explicit-solvent SAXS calculations provide a novel structural view of the protein hydration shell, which underlies temperature-dependent processes such as cold denaturation, thermophoresis, or biomolecular phase separation.

electron density↗

The molecular basis of Human FN3K mediated phosphorylation of glycated substrates

Abstract Glycation, a non-enzymatic post-translational modification occurring on proteins, can be actively reversed via site-specific phosphorylation of the fructose-lysine moiety by FN3K kinase, to impact the cellular function of the target protein. A regulatory axis between FN3K and glycated protein targets has been associated with conditions like diabetes and cancer. However, the molecular basis of this relationship has not been explored so far. Here, we determined a series of crystal structures of HsFN3K in the apo-state, and in complex with different nucleotide analogs together with a sugar substrate mimic to reveal the features important for its kinase activity and substrate recognition. Additionally, the dynamics in sugar substrate binding during the kinase catalytic cycle provide important mechanistic insights into HsFN3K function. Our structural work provides the molecular basis for rational small molecule design targeting FN3K.

Science & Technology - Other Topics↗

A ligand discovery toolbox for the WWE domain family of human E3 ligases

The WWE domain is a relatively under-researched domain found in twelve human proteins and characterized by a conserved tryptophan-tryptophan-glutamate (WWE) sequence motif. Six of these WWE domain-containing proteins also contain domains with E3 ubiquitin ligase activity. The general recognition of poly-ADP-ribosylated substrates by WWE domains suggests a potential avenue for development of Proteolysis-Targeting Chimeras (PROTACs). Here, we present novel crystal structures of the HUWE1, TRIP12, and DTX1 WWE domains in complex with PAR building blocks and their analogs, thus enabling a comprehensive analysis of the PAR binding site structural diversity. Furthermore, we introduce a versatile toolbox of biophysical and biochemical assays for the discovery and characterization of novel WWE domain binders, including fluorescence polarization-based PAR binding and displacement assays, 15 N-NMR-based binding affinity assays and 19 F-NMR-based competition assays. Through these assays, we have characterized the binding of monomeric iso -ADP-ribose ( iso -ADPr) and its nucleotide analogs with the aforementioned WWE proteins. Finally, we have utilized the assay toolbox to screen a small molecule fragment library leading to the successful discovery of novel ligands targeting the HUWE1 WWE domain.

59 BASIC BIOLOGICAL SCIENCES↗

Structures of vertebrate R2 retrotransposon complexes during target-primed reverse transcription and after second-strand nicking

R2 retrotransposons are site-specific eukaryotic non–long terminal repeat retrotransposons that copy and paste into gene loci encoding ribosomal RNAs. Recently, we demonstrated that avian A-clade R2 proteins achieve efficient and precise insertion of transgenes into their native safe-harbor loci in human cells. The features of A-clade R2 proteins that support gene insertion are not well characterized. Here, we report high-resolution cryo–electron microscopy structures of two vertebrate A-clade R2 proteins at the initiation of target-primed reverse transcription and after cDNA synthesis and second-strand nicking. Using biochemical and cellular assays, we illuminate the basis for high selectivity of template use and unique roles for each of the three zinc-finger domains in nucleic acid recognition. Reverse transcriptase active site architecture is reinforced by an unanticipated insertion motif specific to vertebrate A-clade R2 proteins. Our work provides the first insights into A-clade R2 protein structure during gene insertion and may enable future improvement and adaptation of R2-based systems for precise transgene insertion.

Science & Technology - Other Topics↗

Interactions between molecular-scale biogeochemical processes and hyporheic exchange for understanding coupled Fe-S-C cycling in iron-rich riparian wetlands (Final Technical Report)

Riparian wetlands are dynamic interfaces that exert strong control over water quality, contaminant mobility, and greenhouse gas emissions. These systems are characterized by hyporheic exchange between oxic surface water and anoxic groundwater, which generates steep redox gradients and promotes spatially and temporally variable microbial activity. Despite growing recognition of tightly coupled iron (Fe), sulfur (S), and carbon (C) cycling in these environments, the mechanisms governing these interactions—particularly under low-sulfate freshwater conditions—remain poorly constrained. This project developed a mechanistic understanding of how hydrologic variability and microbial processes interact to control Fe–S–C cycling in iron-rich riparian wetlands. Using a multi-scale and multi-method approach integrating field observations, geochemical and spectroscopic analyses, metagenomics, and reactive transport modeling, we demonstrate that “cryptic” sulfur cycling—rapid sulfur transformations involving intermediate-valence species—plays a dominant and previously underrecognized role in freshwater wetlands. These processes persist despite low sulfate concentrations and significantly influence iron reduction, carbon mineralization, and methane dynamics. The results show that cryptic sulfur cycling enhances dissolved Fe 2+ production, regulates methane concentrations, and is strongly controlled by climate-driven hydrologic fluxes. By linking hydroclimate, subsurface flow, and biogeochemical reactions, this work provides a predictive framework for understanding how wetland systems respond to environmental change, with direct implications for water quality and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗

The HHV-6B U20 glycoprotein binds ULBP1, masking it from recognition by NKG2D and interfering with natural killer cell activation

Human Herpesvirus 6B (HHV-6B) impedes host immune responses by downregulating class I MHC molecules (MHC-I), hindering antigen presentation to CD8+ T cells. Downregulation of MHC-I disengages inhibitory receptors on natural killer (NK) cells, resulting in activation and killing of the target cell if NK cell activating receptors such as NKG2D have engaged stress ligands upregulated on the target cells. Previous work has shown that HHV-6B downregulates three MHC-like stress ligands MICB, ULBP1, and ULBP3, which are recognized by NKG2D. The U20 glycoprotein of the related virus HHV-6A has been implicated in the downregulation of ULBP1, but the precise mechanism remains undetermined. We set out to investigate the role of HHV-6B U20 in modulating NK cell activity. We used HHV-6B U20 expressed as a recombinant protein or transduced into target cells, as well as HHV-6B infection, to investigate binding interactions with NK cell ligands and receptors and to assess effects on NK cell activation. Small-angle X-ray scattering was used to align molecular models derived from machine-learning approaches. We demonstrate that U20 binds directly to ULBP1 with sub-micromolar affinity. Transduction of U20 decreases NKG2D binding to ULBP1 at the cell surface but does not decrease ULBP1 protein levels, either at the cell surface or in toto. HHV-6B infection and soluble U20 have the same effect. Transduction of U20 blocks NK cell activation in response to cell-surface ULBP1. Structural modeling of the U20 – ULBP1 complex indicates some similarities to the m152-RAE1γ complex.

60 APPLIED LIFE SCIENCES↗

Melatonin-Induced Modulation of Cholesterol-Enriched Model Neuronal Membranes

Melatonin, a hormone primarily produced by the brain’s pineal gland, not only regulates circadian rhythms, but also influences the structural and biophysical properties of neuronal membranes. Its amphiphilic nature enables direct incorporation into lipid bilayers and preferential interactions with cholesterol-rich lipid rafts, critical hubs for cellular signaling and membrane organization. Despite increasing recognition of its membrane activity, the molecular basis of melatonin’s interactions with coexisting liquid-ordered (L o ) and liquid-disordered (L d ) phases remains unclear. Here, in this study, we combine small-angle neutron scattering (SANS) and all-atom molecular dynamics simulations to examine model neuronal membranes composed of DSPC, DOPC, POPC, and cholesterol. Our results show that melatonin preserves domain morphology while adopting distinct orientations within the bilayer and at the membrane interface, allowing both lateral and transmembrane bridging across lipid phases. These findings establish the molecular underpinnings of melatonin’s modulation of membrane heterogeneity and provide strong support for its receptor-independent actions.

atomistic simulations↗

Nicotinamide Cofactor Biomimetics: Design and Structure Activity Relationships

Biocatalysis is an attractive methodology due to its sustainable metrics, combined with its vaunted regio-, chemo-, and stereoselectivity. Among biocatalysts, oxidoreductases catalyze redox transformations on a wide variety of substrates and are thus particularly attractive for synthetic applications. Many oxidoreductases depend on nicotinamide-based cofactors; however, the high cost and poor atom economy of such cofactors can negate the advantage of biosynthetic processes. The native cofactors (i.e., NADH or NADPH) can be replaced by nicotinamide cofactor biomimetics (NCBs) to address these issues. Additionally, NCBs can enhance enzyme activity due to structures with expanded redox properties. These capabilities open possibilities for reactivity and biorthogonality. Thus, the field has responded with new NCB structures, including variation in their electronic and molecular recognition properties. This perspective focuses on structure-activity relationships of simple NCBs, including their function, stability, and other properties, along with methods for their regeneration in biosynthesis.

agricultural chemistry↗

Feed status and skin injury modulate immunopathology, global gene expression, and survival in channel catfish during virulent Aeromonas hydrophila infection

Introduction VirulentAeromonas hydrophilais a major pathogen in channel catfish (Ictalurus punctatus), that causes motileAeromonassepticemia and significant economic losses. We investigated the effect of feeding status and skin integrity on the host immune response, disease survival, and gastrointestinal pathology following a vAh challenge. Methods Using a bath immersion model, channel catfish were divided into four treatment groups: fin clipped and fed (FCF), fin clipped but not fed (FCN), not fin clipped but fed (NCF), and not fin clipped nor fed (NCN) alongside non-challenged control groups The FCF and NCF groups were fed 2 h prior to the challenge, but the FCN and NCN groups were not. Survival analysis, histopathological assessment, and RNA sequencing were conducted across groups at different time intervals throughout the vAh challenge. Results Survival rates were lowest in the FCF and FCN groups (30% and 23% survival, respectively), suggesting that both feeding and skin damage contributed to disease severity. Histopathological analyses revealed more severe intestinal and gastric lesions in fed groups, characterized by epithelial necrosis, hemorrhage, and edema. Transcriptomic analysis among the groups identified significant differentially expressed genes associated with inflammation, apoptosis, and metabolic stress, with notable upregulation of interleukin 1-beta (il-1β), and complement C3 (c3). Gene ontology enrichment highlighted distinct immune activation patterns between fed and unfed groups, with enhanced pathogen recognition and pro-inflammatory responses in unfed fish. Discussion These findings suggest feeding prior to infection may exacerbate disease pathology, potentially by creating a physiological state conducive to facilitate pathogen proliferation and dampened early immune responses, whereas short-term fasting appears to promote early immune activation. This study provides novel insights into the complex interplay between feed status, physical injury, and immune response to vAh infection.

Immunology↗

Nucleic Acid-Based Detection Protease Activity

Proteases include clinically relevant markers for clotting disorders, certain cancers as well as toxins. Assays for protease activity often use designed peptides mimicking natural substrates and detection with colorometric and fluorescence-based detection that is difficult to multiplex without expensive and resource demanding instruments. This work demonstrates detection of proteolytic activity using PCR and sequencing-readable reporter molecules. The assay development focused on binding the constructed peptide-oligonucleotide chimera to immobilized streptavidin. Thrombin, an essential component of the clotting cascade, was used as a model system for testing peptide substrate recognition and release of a designed oligonucleotide for detection. Detection of protease activity was demonstrated in a concentration-dependent manner using MALDI-MS, RT-PCR and DNA sequencing.

Wunschel, David S [Pacific Northwest National Labo↗