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At least 1,063 records · Page 59

TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring

Abstract Densely distributed sensor networks can revolutionize environmental observations by providing real-time data with an unprecedented spatiotemporal resolution. However, field deployments often pose unique challenges in terms of power provisions and wireless connectivity. We present a framework for wirelessly connected distributed sensor arrays for near-surface temperature and/or deformation monitoring. Our research focuses on a novel time division duplex implementation of the LoRa protocol, enabling battery powered base stations and avoiding collisions within the network. In order to minimize transmissions and improve battery life throughout the network, we propose a dedicated delta encoding algorithm that utilizes the spatial and temporal similarity in the acquired data sets. We implemented the developed technologies in a AA battery powered hardware platform that can be used as a wireless data logger or base station, and we conducted an assessment of the power consumption. Without data compression, the projected battery life for a data logger is 4.74 years, and a wireless base stations can last several weeks or months depending on the amount of network traffic. The delta encoding algorithm can further improve this battery life with a factor of up to 3.50. Our results demonstrate the viability of the proposed methods for low-power environmental wireless sensor networks.

54 ENVIRONMENTAL SCIENCES↗

Outcomes and Conclusions from the 2022 AM Bench Measurements, Challenge Problems, Modeling Submissions, and Conference

The Additive Manufacturing Benchmark Test Series (AM Bench) provides rigorous measurement data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM Bench includes extensive in situ and ex situ measurements, simulation challenges for the AM modeling community, and a corresponding conference series. In 2022, the second round of AM Bench measurements, challenge problems, and conference were completed, focusing primarily upon laser powder bed fusion (LPBF) processing of metals, and both material extrusion processing and vat photopolymerization of polymers. In all, more than 100 people from 10 National Institute of Standards and Technology (NIST) divisions and 21 additional organizations were directly involved in the AM Bench 2022 measurements, data management, and conference organization. The international AM community submitted 138 sets of blind modeling simulations for comparison with the in situ and ex situ measurements, up from 46 submissions for the first round of AM Bench in 2018. Analysis of these submissions provides valuable insight into current AM modeling capabilities. The AM Bench data are permanently archived and freely accessible online. The AM Bench conference also hosted an embedded workshop on qualification and certification of AM materials and components.

36 MATERIALS SCIENCE↗

Electrostatic dust remediation for future exploration of the Moon

Dust accumulation is one of the critical issues that must be mitigated on in-situ lunar explorations because an in-situ probe is exposed to small dust particles, which are easily attached to it, during its operations. The Lunar Dust Science Definition Team is organized by the Jet Propulsion Lab/California Institute of Technology through NASA’s Biological and Physical Sciences Division to define key science questions and assess dust remediation techniques. Here, we assess three electrostatic remediation technology concepts: electrostatic dust shield; surface electrostatically collecting dust, later called attractive surface; and electron beam — plasma jet inducing electrostatic dust lofting from a surface. We qualitatively investigate their maturity by defining six operational factors: Time and location; Amount of dust removal; Contamination of target surfaces; Operation duration; Installation; and Safety. In addition to these techniques, we discuss a supporting system that loads dust particles onto a test article to examine dust removal efficiency. Here, the results show that further development increases the maturity of all the technologies. While laboratory and theoretical demonstrations reported whether each technology robustly work on the Moon, which hosts a complex, heterogeneous dust environment, we find that it is still uncertain if this is the case because none has been tested in the lunar environment. Particularly, operation duration and safety are critical to be addressed further on both laboratory and spaceflight scales.

42 ENGINEERING↗

Transcription initiation as a control point in plastid gene expression

The extensive processing and protein-assisted stabilization of transcripts have been taken as evidence for a viewpoint that the control of gene expression had shifted entirely in evolution from transcriptional in the bacterial endosymbiont to posttranscriptional in the plastid. This suggestion is however at odds with many observations on plastid gene transcription. Chloroplasts of flowering plants and mosses contain two or more RNA polymerases with distinct promoter preference and division of labor for the coordinated synthesis of plastid RNAs. Plant and algal plastids further possess multiple nonredundant sigma factors that function as transcription initiation factors. The controlled accumulation of plastid sigma factors and modification of their activity by sigma-binding proteins and phosphorylation constitute additional transcriptional regulatory strategies. Plant and algal plastids also contain dedicated one- or two-component transcriptional regulators. Finally, transcription initiation thus continues to form a critical control point at which varied developmental and environmental signals intersect with plastid gene expression.

59 BASIC BIOLOGICAL SCIENCES↗

Partners for life: building microbial consortia for the future

We report new technologies have allowed researchers to better design, build, and analyze complex consortia. These developments are fueling a wider implementation of consortium-based bioprocessing by leveraging synthetic biology, delivering on the field’s multitudinous promises of higher efficiencies, superior resiliency, augmented capabilities, and modular bioprocessing. Here we chronicle current progress by presenting a range of screening, computational, and biomolecular tools enabling robust population control, efficient division of labor, and programmatic spatial organization; furthermore, we detail corresponding advancements in areas including machine learning, biocontainment, and standardization. Additionally, we show applications in myriad sectors, including medicine, energy and waste sustainability, chemical production, agriculture, and biosensors. Concluding remarks outline areas of growth that will promote the utilization of complex community structures across the biotechnology spectrum.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative multiplexed analysis of gene and protein expression patterns in Yarrowia lipolytica

In this report, we present coordinated observations of protein and mRNA transcript counts at the single-cell level in the oleaginous yeast model Yarrowia lipolytica. The transcription factor Xbp1p regulates entry into a quiescent state, representing a shift of resources to sequestration of nutrients rather than cell division. We observed the responses of wild-type and Δxbp1 cells to protein (by fluorescence) and transcript quantification and localization at both single-cell and population-averaged levels. Data were collected via single-molecule fluorescence in situ hybridization (smFISH) and qPCR under nitrogen depletion, a condition that drives lipid accumulation. These techniques reveal a complex and heterogeneous population of Xbp1p dynamics and downstream regulation. Our findings highlight the need for single-cell resolution analyses to describe cellular dynamics and regulatory processes.

Yarrowia lipolytica↗

Molecular pathways for learning in the single-cell Stentor coeruleus

The single-cell Stentor coeruleus contracts in response to mechanical taps but habituates and learns to ignore the taps after repeated stimulation. Here, we explored the molecular changes that occur during the formation of this cellular memory in order to improve our understanding of non-synaptic learning. We impaired cellular protein synthesis with cycloheximide and puromycin and found that, contrary to the effects of such treatments on metazoa, these drugs accelerate habituation and prolong memory retention in Stentor . Exploratory proteomic and transcriptomic analyses identified candidate proteins and genes that changed over the course of habituation and response recovery, pointing toward the regulation of Stentor learning by calcium signaling and protein phosphorylation. Building on these results, we found that using RNA interference to knock down the calcium-binding, EF-hand domain-containing protein SteCoe_6763 accelerated habituation. Furthermore, increased extracellular calcium improved Stentor learning, while treatment with kinase and phosphatase inhibitors impaired learning. In particular, KN-93, a drug known to inhibit calcium/calmodulin-dependent kinase II and voltage-gated calcium channels, decreased both the rate and extent of habituation in Stentor , similar to its effects on learning in metazoa. We also discovered that habituation memory can be maintained in progeny following cell division. Taken together, these results suggest that response recovery in Stentor requires new protein synthesis and that memory formation involves the modification of delocalized mechanoreceptors by phosphorylation and calcium signaling. This is consistent with our previous model of Stentor learning, in which habituation occurs through the inactivation of cell-surface receptors.

CaMKII↗

Synchrotron-based X-ray fluorescence microscopy mapping the ionome of a toxic freshwater cyanobacterium

Harmful algal blooms (HABs) pose a major environmental concern across the globe. In abundance, cyanobacteria, or so-called green-blue algae can produce extremely dangerous cyanotoxins that harm humans and animals. This study focused on the mapping and distribution of intracellular macro-and micronutrients of the widespread freshwater cyanobacteria Microcystis aeruginosa (M. aeruginosa). Towards a better understanding of trace metal uptake and homeostasis throughout the cell cycle, we quantitatively mapped the spatial distribution of the elements P, K, Fe, Ca, Zn, Mn, and Cu across the ultrastructure of frozen-hydrated single cells using state-of-theart X-ray nanofluorescence imaging at the Advanced Photon Source (APS) at Argonne National Laboratory. Further, bulk cellular nutrient and trace metal content correlated well with the total intracellular elemental content in individual cells obtained by quantitative synchrotron X-ray fluorescence measurements. Multi-dimensional mappings showed P and K atoms colocalized as discrete semicircular hotspots that were analyzed with respect to their stoichiometry. Elevated Cu and Ca concentrations were detected along division plane of cells. P and K were found to have similar spatial elemental distribution with about 65% and 69% of the total cellular P and K, respectively, located at the hotspots. The P and K colocalization were refined further using nanotomography, showing a K envelope surrounding the P core. Inorganic P and organic P compounds were specified using solution-state 31 P nuclear magnetic resonance (NMR) spectroscopy from M. aeruginosa. Of the total extracted P determined by 31 P NMR spectroscopy, 47% were found to be nucleotides while only 11% were polyphosphates. Multimodal X-ray imaging provides a better understanding of intracellular biochemical processes in cyanobacteria, helping us monitor and combat an emerging environmental threat.

31P NMR spectroscopy↗

Scalable Generation of High-fidelity Synthetic Population Ensembles

Used within social simulations, synthetic population ensembles enable uncertainty quantification (UQ) methods for obtaining more robust model inference and prediction. A synthetic population ensemble is a series of plausible virtual reconstructions of an area’s population at the granularity of people and residences, generated stochastically to preserve privacy of the source population survey’s respondents. In this paper, we demonstrate the production of large synthetic population ensembles for the U.S. via Oak Ridge National Laboratory’s UrbanPop framework to support modeling of high spatial resolution energy affordability metrics from nationwide social surveys in collaboration with the fusionACS project. The study involves two scenarios: creating ensembles for (1) 17 U.S. metropolitan areas in 2019 and (2) full U.S. Census Divisions in 2023, with each scenario consisting of 41 population instances (a base realization and 40 replicates). To accomplish this task at scale, we configured an integrated system within a research cloud, comprised of virtual containerizations, GPU-enhanced functionality, and orchestrated deployments of UrbanPop’s maturing Likeness Python ecosystem. Results demonstrate we maintained high-fidelity approximations of residential totals by areas of interest and the demographic characteristics of neighborhoods while reducing manual workflow burdens. Finally, we discuss plans to fine-tune and further develop our automated workflows for truly distributed job orchestration to increase computational efficiency, as well as provide an outlook for broadening applications of the ensembles.

Cluster computing↗

Regulatory Considerations in the Development of Radiation-Drug Combinations

Radiation therapy remains a fundamental treatment for patients with cancer. Despite an increasing number of targeted molecular therapies that are US Food and Drug Administration (FDA)-approved for the treatment of patients with metastatic disease, there has been very little progress made in terms of drugs used concurrently with radiation. This article reviews the existing regulatory framework in which cancer drugs may be developed for use in combination with radiation therapy from the perspective of the FDA. To briefly summarize: (1) nonclinical studies are a critical first step to ensure that drugs are safe for use in humans; however, additional nonclinical studies of a drug with radiation may not be required before a clinical trial in combination with radiation as long as the safety profile of the drug has been characterized in humans. The FDA determines the quality of evidence required before studying a drug in combination with radiation on a case-by-case basis. (2) Although often impractical to consider late toxicities during dose-escalation, late adverse events should be captured and taken into consideration when determining the final dose and schedule to take forward during drug development. (3) There are a number of expedited programs for cancer drug development, including accelerated approval, a conditional approval that allows for use of earlier clinical endpoints when the data suggests a clinically meaningful improvement over available therapy. (4) The Agency encourages sponsors to discuss their development plan with the appropriate FDA review division in formal regulatory meetings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

FtsZ-mediated fission of a cuboid bacterial symbiont

Less than a handful of cuboid and squared cells have been described in nature, which makes them a rarity. Here, we show how Candidatus Thiosymbion cuboideus, a cube-like gammaproteobacterium, reproduces on the surface of marine free-living nematodes. Immunostaining of symbiont cells with an anti-fimbriae antibody revealed that they are host-polarized, as these appendages exclusively localized at the host-proximal (animal-attached) pole. Moreover, by applying a fluorescently labeled metabolic probe to track new cell wall insertion in vivo, we observed that the host-attached pole started septation before the distal one. Similarly, Ca. T. cuboideus cells immunostained with an anti-FtsZ antibody revealed a proximal-to-distal localization pattern of this tubulin homolog. Although FtsZ has been shown to arrange into squares in synthetically remodeled cuboid cells, here we show that FtsZ may also mediate the division of naturally occurring ones. This implies that, even in natural settings, membrane roundness is not required for FtsZ function.

59 BASIC BIOLOGICAL SCIENCES↗

A physics informed model for the prediction of surface energies and the shape of metal particles

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a physics informed method to predict the total energy of metal-based systems across a wide range of configurations. Our method has been tested against density functional theory (DFT) calculations for late transition metals. This method enables on-the-fly surface energy predictions based on the fundamental of materials property and allows for the Wulff construction of metal particles for a random number of elemental atoms and without the need for DFT calculations. By making a division between atoms in the different layers of the model system, we can improve the accuracy of the model, suggesting a dissimilarity between the electronic structure due to an alternating compression and expansion of atomic layers. We find that our model accurately and effectively provides valuable insights into the distribution and stability of nanoparticles.

Mandal, Shyama Charan (ORCID:0000000245882874)↗

The Sporadic History of Rubidium and its Role in Corrosion of Steel Related to Nuclear Material Storage

The influence of rubidium (Rb), both in its metallic and oxidized states, on the corrosion resistance of steels has direct relevance to the storage of radioactive Kr-85 containing nuclear materials. Kr-85 undergoes a ß-decay to generate stable, metallic Rb. The literature to date is sparse, contained primarily in company reports and divisive as to whether Rb metal, or its oxides, can lead to corrosion of steel materials. In both the direct storage of Kr-85 and used nuclear fuel that will contain Kr-85, if Rb is corrosive then continual decay of the Kr-85 will generate an increasingly corrosive environment for the steel canister it is stored in. This review was written to consolidate the known data to date on Rb corrosion of steels to identify consistencies, contradictions and remaining gaps in our understanding of the Rb : steel system.

krypton, corrosion, steel, Rubidium↗

Leveraging explainable AI to characterize floating-point exceptions in linear solvers

Linear solver packages are central to many scientific, engineering, and machine learning applications. When floating-point exceptions occur in these solvers, e.g., division by zero or overflow, numerical results are compromised and become unreliable. Existing static and dynamic analysis tools can detect such exceptions, but they do not explain why the exceptions occur in terms of the solver inputs. Here, we present a study to characterize the inputs that cause numerical exceptions in linear solver packages. Our approach uses explainable AI (XAI) to find the most relevant characteristics of input matrices that explain the occurrence of exceptions in the solvers. Since training data in this domain is scarce, we perform extensive data gathering and data augmentation to obtain exception-inducing inputs. Our approach uses a repair strategy on the features blamed by XAI to validate that such features indeed explain the exceptions. We compare the LIME and SHAP XAI techniques using a dozen matrix features with three classifiers. We evaluate the approach on three widely used linear solver packages and find that some input characteristics can explain the occurrence of exceptions 100% of the time, in specific solvers and preconditioners.

Explainable AI↗

A metal-ceramic coaxial cable with multipoint Fabry-Pérot interferometers for monitoring distributed high temperature

A metal ceramic coaxial cable (MCCC) sensor containing multiple Fabry-Pérot interferometers (FPIs) has been designed, fabricated, and evaluated for measuring distributed high temperatures. The MCCC sensor demonstrated here consists of stainless steel tube and wire conductors, alumina tube insulator, and three pairs of air gap reflectors distributed along the cable. The multipoint sensor operation is realized by the joint time-frequency domain technique, which combines the functions of time-domain reflectometry and frequency division multiplexing to enable the measurement of spatially distributed temperature. The 3-point MCCC-FPI sensor has been demonstrated for distributed temperature measurements between 250 and 550 °C and operability up to 1000 °C. The sensor offers high sensitivity of >0.18 MHz/°C with a measurement resolution of 1 Hz and reasonably small high temperature measurement error range of ±3 °C.

42 ENGINEERING↗

Simplifying activations with linear approximations in neural networks

A key step in Neural Networks is activation. Among the different types of activation functions, sigmoid, tanh, and others involve the usage of exponents for calculation. From a hardware perspective, exponential implementation implies the usage of Taylor series or repeated methods involving many addition, multiplication, and division steps, and as a result are power-hungry and consume many clock cycles. We implement a piecewise linear approximation of the sigmoid function as a replacement for standard sigmoid activation libraries. This approach provides a practical alternative by leveraging piecewise segmentation, which simplifies hardware implementation and improves computational efficiency. In this paper, we detail piecewise functions that can be implemented using linear approximations and their implications for overall model accuracy and performance gain. Our results show that for the DenseNet, ResNet, and GoogLeNet architectures, the piecewise linear approximation of the sigmoid function provides faster execution times compared to the standard TensorFlow sigmoid implementation while maintaining comparable accuracy. Specifically, for MNIST with DenseNet, accuracy reaches 99.91% (Piecewise) vs. 99.97% (Base) with up to 1.31x speedup in execution time. For CIFAR-10 with DenseNet, accuracy improves to 98.97% (Piecewise) vs. 99.40% (Base) while achieving 1.24x faster execution. Similarly, for CIFAR-100 with DenseNet, the accuracy is 97.93% (Piecewise) vs. 98.39% (Base), with a 1.18x execution time reduction. These results confirm the proposed method’s capability to efficiently process large-scale datasets and computationally demanding tasks, offering a practical means to accelerate deep learning models, including LSTMs, without compromising accuracy.

Activation function↗

Density scaling approximation for Monte-Carlo simulations of radioactive plumes

The release of radioactive gas into the atmosphere can diffuse into large volumes of air downwind from the point of release. The extent of radioactivity can cover thousands of cubic meters of air. For such large volumes, the weather models used to predict the down-wind distribution of the plume and the radiation transport models used to predict the radiation reaching ground-level from the plume can take tens of hours of computer time on multi-node institutional High-Performance Computing facilities. In this paper we focus on the radiation transport aspect of plume modeling. Here, we describe a phenomenological method for approximating the amounts of radiation that reach ground level from large volumes of a static radioactive plume that can be calculated on a stand-alone personal computer in much shorter computation times than those usually needed for such large volume evaluations. We refer to this method as the Density Scaling Approximation (DSA). Its ability to approximate ground-level count rates of large plumes comes from using a small-plume volume with a scaled-up value of air density to simulate the same number of scatterings that occur during transport in larger plume volumes at normal air density. We demonstrate the DSA by using a 100 m-diameter air-filled hemispherical dome geometry with a uniform volumetric activity of 135 Xe gas throughout the air-filled volume. The DSA for a larger dome diameter is obtained by evaluating the 100 m dome with an air density scaled up by the linear ratio of the larger diameter to the 100 m diameter. We find that this approximation works well for dome diameters up to 1200 m – the largest diameter studied and a size more than sufficient for accounting for all the radiation from 135 Xe. Moreover, most of our DSA results can be calculated over 500 times faster than corresponding full-sized geometry with normal air density. To help evaluate the accuracy of the DSA and gain insight into how well it can reproduce different regions of the spectra, we use three, easily understood regions of interest to compare the DSA results to the full-sized geometry at normal air density results. These regions are the full-energy peak, the region of single-Compton scattering, and the region of multiple-Compton scattering. We show how the dominance of the Compton scattering mechanism determines this division and thus provides insight into how Compton scattering is manifested in spectra from photon scattering through air in general, and how well the DSA approximation works.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Codes and standards for ceramic composite core materials for High Temperature Reactor applications

Fiber-reinforced ceramic matrix composites are attractive for high-temperature nuclear applications due to excellent thermal and mechanical properties as well as reasonable-to-outstanding radiation resistance. Over the past 20 years, the use of ceramic matrix composite applications expanded to many commercial non-nuclear industries as fabrication and application of the technologies mature. The ASME Boiler Pressure Vessel Code, under Section III Division 5, provides the design and construction rules for High Temperature Reactor components. It published the first rules for ceramic matrix composites to be used for reactor core components. The rules lay out the quality requirements together with the design and materials criteria for the use and application of silicon carbide- and carbon-based matrix material technologies. As with the established graphite rules, the ceramic composite material rules are structured in Subsection HH (from Section III), that addresses the criteria for class SN nonmetallic core components. The code rules rely heavily on the development and publication of standards for composite specification, classification, and testing of mechanical, thermal, and other properties. These test methods are developed in ASTM Committee C28 on Advanced Ceramics, with a current focus on ceramic composite tubes. This article describes the detail of the composites code, the design methodology and similarities to the graphite code, the guidance for the development of specifications for ceramic composites (for nuclear applications) including recent standard developments, and it mentions the next steps to support licensing aspects by validating the code with benchmarking data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗