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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Model acetylcholinesterase‐Fc fusion glycoprotein biotechnology system for the manufacture of an organophosphorus toxicant bioscavenging countermeasure

Abstract Organophosphate (OP) toxicants remain an active threat to public health and to warfighters in the military. Current countermeasures require near immediate administration following OP exposure and are reported to have controversial efficacies. Acetylcholinesterase (AChE) fused to the human immunoglobulin 1 (IgG1) Fc domain (AChE‐Fc) is a potential bioscavenger for OP toxicants, but a reproducible AChE‐Fc biomanufacturing strategy remains elusive. This report is the first to establish a comprehensive laboratory‐scale bioprocessing strategy that can reproducibly produce AChE‐Fc and AChE(W86A)‐Fc which is a mutated AChE protein with reduced enzymatic activity. Characterization studies revealed that AChE‐Fc and AChE(W86A)‐Fc are N ‐glycosylated dimeric fusion glycoproteins but only AChE‐Fc had the capability to bind to paraoxon (a model OP). This AChE‐Fc fusion glycoprotein bioprocessing strategy can be leveraged during industrial biomanufacturing development, while the research‐grade AChE‐Fc proteins can be used to determine the potential clinical relevance of the countermeasure against OP toxicants.

Biel, Thomas G.↗
DOE OSTI2023

Development of LpxH Inhibitors Chelating the Active Site Dimanganese Metal Cluster of LpxH

Abstract Despite the widespread emergence of multidrug‐resistant nosocomial Gram‐negative bacterial infections and the major public health threat it brings, no new class of antibiotics for Gram‐negative pathogens has been approved over the past five decades. Therefore, there is an urgent medical need for developing effective novel antibiotics against multidrug‐resistant Gram‐negative pathogens by targeting previously unexploited pathways in these bacteria. To fulfill this crucial need, we have been investigating a series of sulfonyl piperazine compounds targeting LpxH, a dimanganese‐containing UDP‐2,3‐diacylglucosamine hydrolase in the lipid A biosynthetic pathway, as novel antibiotics against clinically important Gram‐negative pathogens. Inspired by a detailed structural analysis of our previous LpxH inhibitors in complex with K. pneumoniae LpxH ( Kp LpxH), here we report the development and structural validation of the first‐in‐class sulfonyl piperazine LpxH inhibitors, JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ), that achieve chelation of the active site dimanganese cluster of Kp LpxH. The chelation of the dimanganese cluster significantly improves the potency of JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ). We expect that further optimization of these proof‐of‐concept dimanganese‐chelating LpxH inhibitors will ultimately lead to the development of more potent LpxH inhibitors for targeting multidrug‐resistant Gram‐negative pathogens.

Pharmacology & Pharmacy↗
DOE OSTI2020

Countermeasures for Preventing and Treating Opioid Overdose

The only medication available currently to prevent and treat opioid overdose (naloxone) was approved by the US Food and Drug Administration (FDA) nearly 50 years ago. Due to its pharmacokinetic and pharmacodynamic properties, naloxone has limited utility under some conditions and would not be effective to counteract mass casualties involving large-scale deployment of weaponized synthetic opioids. To address shortcomings of current medical countermeasures for opioid toxicity, a trans-agency scientific meeting was convened by the US National Institute of Allergy and Infectious Diseases/National Institutes of Health (NIAID/NIH) on August 6 and 7, 2019, to explore emerging alternative approaches for treating opioid overdose in the event of weaponization of synthetic opioids. The meeting was initiated by the Chemical Countermeasures Research Program (CCRP), was organized by NIAID, and was a collaboration with the National Institute on Drug Abuse/NIH (NIDA/NIH), the FDA, the Defense Threat Reduction Agency (DTRA), and the Biomedical Advanced Research and Development Authority (BARDA). This paper provides an overview of several presentations at that meeting that discussed emerging new approaches for treating opioid overdose, including the following: (1) intranasal nalmefene, a competitive, reversible opioid receptor antagonist with a longer duration of action than naloxone; (2) methocinnamox, a novel opioid receptor antagonist; (3) covalent naloxone nanoparticles; (4) serotonin (5-HT)1A receptor agonists; (5) fentanyl-binding cyclodextrin scaffolds; (6) detoxifying biomimetic “nanosponge” decoy receptors; and (7) antibody-based strategies. These approaches could also be applied to treat opioid use disorder.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Phototunable Lignin Plastics to Enable Recyclability

The accumulation of non-degradable petrochemical plastics imposes a significant threat to the environment and ecosystems. We addressed this challenge by designing a new type of phototunable plastics based on the unique lignin chemistry to enable readily end-life recycling. The advanced material design leveraged the efficient photocatalytic lignin depolymerization by ZnO nanoparticles to build lignin-polymethyl methacrylate (PMMA)-ZnO blends. We first demonstrated the highly effective phototunable lignin depolymerization in the complex polymer blend matrix and explored the molecular mechanisms. The technical barriers of mechanical property and recycling processing were then addressed by a new blend design with lignin core grafted with PMMA polymer. The new process has resulted in a new type of PMMA-g-lignin blend, which significantly improved the mechanical properties, making it comparable to PMMA alone. More importantly, the mechanical properties of the UV-treated blend decreased drastically in the new design, whereas the properties did not reduce in the non-grafted blends upon UV exposure. The results highlighted that the new blend design based on graftization maximized the impact of lignin depolymerization on blend structure and recyclability. Based on the results, we developed a process integrating UV and alkaline treatments to recycle PMMA for plastics and fractionated lignin for bioconversion or other applications in the new phototunable plastics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modelling of nanometer scale dust grains in tokamak

Dust poses a serious threat to tokamak operation and safety. It is important to study the behaviour of dust grains under tokamak's discharge conditions, which depends heavily on their size and charge. Existing simulations mainly address issues on dust grains with radii larger than 1 μm, in which case, the drift effect due to electromagnetic fields can be safely ignored. For nanometer scale dust grains, however, the drift effect becomes significant and a new model based on guiding-centre system needs to be established. In this work, the NDS has been done under BOUT++ framework. The simulation contains two parts. Part one, NDS evaluates the charging and ablation processes of the dust grains. In the second part, the guiding-centre orbits of dust particles are tracked in tokamak plasmas, whose parameters are obtained from BOUT++, a highly desirable C++ code package for performing parallel plasma fluid simulations with an arbitrary number of equations in 3D curvilinear coordinates. The orbit of nanodust dynamics is described by guiding centre equations for simplicity, and these equations are numerically solved by conventional fourth-order Runge Kutta method. Simulations provide results such as trajectories and evolutions of dust particles with different sizes and velocities for different tokamak geometries. Results show tungsten dust grains with a radius of a few nanometers launched from outer midplane will oscillate before totally ablated in C-Mod. The oscillation in this case is driven by the ion drag force. Larger Nanodust with a radius of 100 nm, on the contrary, cannot be completely constrained by the electromagnetic field. In conclusion, the high plasma temperature and density in the seperatrix region causes severe dust ablation, resulting in total ablation within several ms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north-central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Inadvertent Hatchery Rainbow Trout Oncorhynchus mykiss Discovered in Native Westslope Cutthroat Trout Oncorhynchus clarkii lewisi Habitat: A Cautionary Tale

Abstract Fish hatcheries across North America release billions of fish into the wild every year to augment harvest opportunities in sport, commercial, and tribal fisheries, as well as to recover depressed populations. Despite these benefits, wild fish populations may be negatively affected when hatchery fish compete and/or hybridize with native species. Native Westslope Cutthroat Trout Oncorhynchus clarkii lewisi have decreased by 90% across their historic range; however, the Flathead River in Montana is a rangewide stronghold for these imperiled fish. The primary threat to Westslope Cutthroat Trout is hybridization with invasive Rainbow Trout O. mykiss, which leads to hybrid swarm formation and genomic extinction. We collected Rainbow Trout in Mill Creek, a tributary of the Flathead River, downstream from a hatchery that produces the species, and used otolith 87Sr/86Sr to determine whether individual fish were inadvertently introduced from the hatchery. Differences in 87Sr/86Sr among water samples from Mill Creek and the marine-derived hatchery food provided high-classification accuracy to determine the natal origins of Mill Creek Rainbow Trout. We found that 83 of the 106 Rainbow Trout collected (78%) were of hatchery origin. Otolith microstructure analysis indicated these fish had been in Mill Creek for ~1–32 weeks prior to capture. Our results illustrate the utility of otolith 87Sr/86Sr to identify hatchery fish in natural habitats and point to a source of invasive Rainbow Trout that pose conservation risks to native fishes in the drainage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Supercell precipitation contribution to the United States hydroclimate

Abstract This research seeks to understand simulated supercell precipitation characteristics across the conterminous United States (CONUS) using high‐resolution, convection‐permitting, dynamically downscaled simulations for three 15‐year epochs. Epochs include a historical end‐of‐20th‐century period (1990–2005) and two end‐of‐21st‐century (2085–2100) scenarios for intermediate and pessimistic greenhouse gas concentration trajectories. Simulated updraft helicity, which measures the corkscrew flow within a storm's updraft, is used as a proxy for supercells. An algorithm tracks and catalogues updraft helicity swaths that, when buffered, are used to acquire simulated precipitation from supercells. The historical epoch provides a baseline climatology of supercell precipitation for a contemporary climate, which is then compared against the two future epochs to assess how supercell precipitation may change during the 21st century. Despite their relatively small size, supercells provide critical precipitation to the Wheat and Corn Belts, large expanses of CONUS pasture and rangeland, regional aquifers and several large river basins. Many areas in the central CONUS receive upwards of 3%–6% of their annual and 5%–8% of their warm‐season precipitation from these storms. Results suggest that precipitation contribution from supercells will decrease in the future across most of the High Plains and Central and Northern Great Plains with robust increases likely across the south‐central and Southeast regions. Supercell precipitation rates are expected to increase for large portions of the CONUS by the end‐of‐the‐21st‐century, suggesting a growing threat for flash floods from these storms as they become more efficient precipitation producers. This research provides an initial perspective on the magnitude of supercell precipitation and potential changes to this important hydrologic input to assist water‐sensitive industries, private and public insurance markets, agriculture entities, as well as inform plans to mitigate and build resilience to rapid environmental and societal change.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

One hundred priority questions for advancing seagrass conservation in Europe

Societal Impact Statement Seagrass ecosystems are of fundamental importance to our planet and wellbeing. Seagrasses are marine flowering plants, which engineer ecosystems that provide a multitude of ecosystem services, for example, blue foods and carbon sequestration. Seagrass ecosystems have largely been degraded across much of their global range. There is now increasing interest in the conservation and restoration of these systems, particularly in the context of the climate emergency and the biodiversity crisis. The collation of 100 questions from experts across Europe could, if answered, improve our ability to conserve and restore these systems by facilitating a fundamental shift in the success of such work. Summary Seagrass meadows provide numerous ecosystem services including biodiversity, coastal protection, and carbon sequestration. In Europe, seagrasses can be found in shallow sheltered waters along coastlines, in estuaries & lagoons, and around islands, but their distribution has declined. Factors such as poor water quality, coastal modification, mechanical damage, overfishing, land‐sea interactions, climate change and disease have reduced the coverage of Europe’s seagrasses necessitating their recovery. Research, monitoring and conservation efforts on seagrass ecosystems in Europe are mostly uncoordinated and biased towards certain species and regions, resulting in inadequate delivery of critical information for their management. Here, we aim to identify the 100 priority questions, that if addressed would strongly advance seagrass monitoring, research and conservation in Europe. Using a Delphi method, researchers, practitioners, and policymakers with seagrass experience from across Europe and with diverse seagrass expertise participated in the process that involved the formulation of research questions, a voting process and an online workshop to identify the final list of the 100 questions. The final list of questions covers areas across nine themes: Biodiversity & Ecology; Ecosystem services; Blue carbon; Fishery support; Drivers, Threats, Resilience & Response; Monitoring & Assessment; Conservation & Restoration; Governance, Policy & Management; and Communication. Answering these questions will fill current knowledge gaps and place European seagrass onto a positive trajectory of recovery.

Nordlund, Lina Mtwana↗
DOE OSTI2024

Invasive wild pig ( Sus scrofa ) diets on barrier islands in the southeastern United States

BACKGROUND: Biological invasions are a leading cause of reductions in global biodiversity. Islands are particularly sensitive to invasions, which often result in cascading impacts throughout island communities. Wild pigs (Sus scrofa) are globally invasive and pose threats to numerous taxa and ecosystems, particularly for islands where they have contributed to declines of many endemic species. However, the impacts of wild pig diet on the flora and fauna remain understudied in many island systems. RESULTS: We used DNA metabarcoding of wild pig fecal samples to quantify the seasonal diet composition of wild pigs on three barrier islands in the southeastern United States. Wild pigs exhibited a diverse diet dominated by plants, but also including marine and terrestrial animals. The diet composition of plants varied seasonally and between islands. Consumption of invertebrates also changed seasonally, with a shift to coastal invertebrates, particularly crabs, in spring and summer. Vertebrates were found in <10% of samples, but spanned broad taxa including amphibians, fish, mammals, and reptiles. Species consumed by wild pigs indicate that wild pigs use a variety of habitats within barrier islands for foraging, including maritime forests, saltmarshes, and beaches. CONCLUSIONS: An observed shift to beach foraging during sea turtle nesting season suggests wild pigs have potential to hinder nesting success on islands without established management programs. These findings provide insight into the diverse diets of wild pigs on barrier islands and highlight the need for removal of wild pigs from sensitive island ecosystems because of their potential impacts to native plant and animal communities. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Molecular Evolution of the H5 and H7 Highly Pathogenic Avian Influenza Virus Haemagglutinin Cleavage Site Motif

ABSTRACT Avian influenza viruses are ubiquitous in the Anatinae subfamily of aquatic birds and occasionally spill over to poultry. Infection with low pathogenicity avian influenza viruses generally leads to subclinical or mild clinical disease. In contrast, highly pathogenic avian influenza viruses emerge from low pathogenic forms and can cause severe disease associated with extraordinarily high mortality rates. Here, we describe the natural history of avian influenza virus, with a focus on H5Nx and H7Nx subtypes, and the emergence of highly pathogenic forms; we review the biology of AIV; we examine cleavage of haemagglutinin by host cell enzymes with a particular emphasis on the biochemical properties of the proprotein convertases, and trypsin and trypsin‐like proteases; we describe mechanisms implicated in the functional evolution of the haemagglutinin cleavage site motif that leads to emergence of HPAIVs; and finally, we discuss the diversity of H5 and H7 haemagglutinin cleavage site sequence motifs. It is crucial to understand the molecular attributes that drive the emergence and evolution of HPAIVs with pandemic potential to inform risk assessments and mitigate the threat of HPAIVs to poultry and human populations.

Luczo, Jasmina M. [Australian Animal Health Labora↗
DOE OSTI2024

Characterizing climate pathways using feature importance on echo state networks

The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithmic techniques for quantifying relationships between source and impact variables related to a climate event (i.e., a climate pathway) would help inform policy decisions. Data-driven deep learning models have become powerful tools for modeling highly nonlinear relationships and may provide a route to characterize climate variable relationships. In this paper, we explore the use of an echo state network (ESN) for characterizing climate pathways. ESNs are a computationally efficient neural network variation designed for temporal data, and recent work proposes ESNs as a useful tool for forecasting spatiotemporal climate data. However, ESNs are noninterpretable black-box models along with other neural networks. The lack of model transparency poses a hurdle for understanding variable relationships. We address this issue by developing feature importance methods for ESNs in the context of spatiotemporal data to quantify variable relationships captured by the model. We conduct a simulation study to assess and compare the feature importance techniques, and we demonstrate the approach on reanalysis climate data. In the climate application, we consider a time period that includes the 1991 volcanic eruption of Mount Pinatubo. This event was a significant stratospheric aerosol injection, which acts as a proxy for an anthropogenic stratospheric aerosol injection. Furthermore, we are able to use the proposed approach to characterize relationships between pathway variables associated with this event that agree with relationships previously identified by climate scientists.

black-box models↗
DOE OSTI2024

Genome‐wide association studies on resistance to powdery mildew in cultivated emmer wheat

Abstract Powdery mildew, caused by the fungal pathogenBlumeria graminis(DC.) E. O. Speer f. sp.triticiEm. Marchal (Bgt), is a constant threat to global wheat (Triticum aestivumL.) production. Although ∼100 powdery mildew (Pm) resistance genes and alleles have been identified in wheat and its relatives, more is needed to minimizeBgt’s fast evolving virulence. In tetraploid wheat (Triticum turgidumL.), wild emmer wheat [T. turgidumssp.dicoccoides(Körn. ex Asch. & Graebn.) Thell.] accessions from Israel have contributed manyPmresistance genes. However, the diverse genetic reservoirs of cultivated emmer wheat [T. turgidumssp.dicoccum(Schrank ex Schübl.) Thell.] have not been fully exploited. In the present study, we evaluated a diverse panel of 174 cultivated emmer accessions for their reaction toBgtisolateOKS(14)‐B‐3‐1and found that 66% of accessions, particularly those of Ethiopian (30.5%) and Indian (6.3%) origins, exhibited high resistance. To determine the genetic basis ofBgtresistance in the panel, genome‐wide association studies were performed using 46,383 single nucleotide polymorphisms (SNPs) from genotype‐by‐sequencing and 4331 SNPs from the 9K SNP Infinium array. Twenty‐five significant SNP markers were identified to be associated withBgtresistance, of which 21 SNPs are likely novel loci, whereas four possibly represent emmer derivedPm4a,Pm5a,PmG16, andPm64. Most novel loci exhibited minor effects, whereas three novel loci on chromosome arms 2AS, 3BS, and 5AL had major effect on the phenotypic variance. This study demonstrates cultivated emmer as a rich source of powdery mildew resistance, and the resistant accessions and novel loci found herein can be utilized in wheat breeding programs to enhanceBgtresistance in wheat.

Genetics & Heredity↗
DOE OSTI2024

Vadose zone flushing of fertilizer tracked by isotopes of water and nitrate

Abstract A substantial fraction of nitrogen (N) fertilizer applied in agricultural systems is not incorporated into crops and moves below the rooting zone as nitrate (NO 3 − ). Understanding mechanisms for soil N retention below the rooting zone and leaching to groundwater is essential for our ability to track the fate of added N. We used dual stable isotopes of nitrate (δ 15 N–NO 3 − and δ 18 O–NO 3 − ) and water (δ 18 O–H 2 O and δ 2 H–H 2 O) to understand the mechanisms driving nitrate leaching at three depths (0.8, 1.5, and 3.0 m) of an irrigated corn field sampled every 2 weeks from 2016 to 2020 in the southern Willamette Valley, Oregon, USA. Distinct periods of high nitrate concentrations with lower δ 15 N–NO 3 − values indicated that a portion of that nitrate was from recent fertilizer applications. We used a mixing model to quantify nitrate fluxes associated with recently added fertilizer N versus older, legacy soil N during these “fertilizer signal periods.” Nitrate leached below 3.0 m in these periods made up a larger proportion of the total N leached at that depth (∼52%) versus the two shallower depths (∼13%–16%), indicating preferential movement of recently applied fertilizer N through the deep soil into groundwater. Further, N associated with recent fertilizer additions leached more easily when compared to remobilized legacy N. A high volume of fall and winter precipitation may push residual fertilizer N to depth, potentially posing a larger threat to groundwater than legacy N. Optimizing fertilizer N additions could minimize fertilizer losses and reduce nitrate leaching to groundwater.

Agriculture↗
DOE OSTI2021

A Sparse-Grid Probabilistic Scheme for Approximation of the Runaway Probability of Electrons in Fusion Tokamak Simulation

Runaway electrons (RE) generated during magnetic disruptions present a major threat to the safe operation of plasma nuclear fusion reactors. A critical aspect of understanding RE dynamics is to calculate the runaway probability, i.e., the probability that an electron in the phase space will runaway on, or before, a prescribed time. Such probability can be obtained by solving the adjoint equation of the underlying Fokker-Planck equation that controls the electron dynamics. In this effort, we present a sparse-grid probabilistic scheme for computing the runaway probability. The key ingredient of our approach is to represent the solution of the adjoint equation as a conditional expectation, such that discretizing the differential operator reduces to the approximation of a set of integrals. Adaptive sparse grid interpolation is utilized to approximate the map from the phase space to the runaway probability. The main novelties of this effort are the integration of the sparse-grid method into the probabilistic numerical scheme for computing escape probability, and the application of the proposed method in computing RE probabilities. Two numerical examples are given to illustrate that the proposed method can achieve O(Δt) convergence, and that the local anisotropic adaptive refinement strategy (M. Stoyanov, Adaptive sparse grid construction in a context of local anisotropy and multiple hierarchical parents. In: Sparse Grids and Applications-Miami 2016, Springer, Berlin, 2018, pp. 175–199) can effectively handle the sharp transition layer between the runaway and non-runaway regions.

Yang, Minglei↗
DOE OSTI2023

Transferable Adversarial Attack on 3D Object Tracking in Point Cloud

3D point cloud object tracking has recently witnessed considerable progress relying on deep learning. Such progress, however, mainly focuses on improving tracking accuracy. The risk, especially considering that deep neural network is vulnerable to adversarial perturbations, of a tracker being attacked is often neglected and rarely explored. In order to attract attentions to this potential risk and facilitate the study of robustness in point cloud tracking, we introduce a novel transferable attack network (TAN) to deceive 3D point cloud tracking. Specifically, TAN consists of a 3D adversarial generator, which is trained with a carefully designed multi-fold drift (MFD) loss. The MFD loss considers three common grounds, including classification, intermediate feature and angle drifts, across different 3D point cloud tracking frameworks for perturbation generation, leading to high transferability of TAN for attack. In our extensive experiments, we demonstrate the proposed TAN is able to not only drastically degrade the victim 3D point cloud tracker, \ie, P2B, but also effectively deceive other unseen state-of-the-art approaches such as BAT and M^2Track, posing a new threat to 3D point cloud tracking.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Security Assessment of an LBP16-Protocol-Based Computer Numerical Control Machine

Subtractive manufacturing systems, specifically, computer numerical control machines, have revolutionized the manufacturing industry. Computer numerical control machining is the preferred method for producing finished parts due to its efficiency, speed and suitability for high-volume production. Securing computer numerical control machines is a priority. Compromises or disruptions of these machines can result in significant downtime, loss of productivity and financial loss. This study examines the vulnerabilities and risks associated with computer numerical control machines, in particular, systems utilizing the LBP16 protocol for controller-machine communications. The study reveals that an adversary can execute cyber-physical attacks such as sabotage and denial of service. The potential security threats emphasize the importance of implementing robust security measures to mitigate the cyber risks to computer numerical control machines.

Forihat, Yahya [Virginia Commonwealth University, ↗