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At least 451 records · Page 25

Direction of impact for explainable risk assessment modeling

Abstract Several graphical indicators have been recently introduced to help analysts visualize the marginal effects of inputs in complex models. The insights derived from such tools may help decision‐makers and risk analysts in designing interventions. However, we know little about the adequacy and consistency of different indicators. This work investigates popular marginal effect indicators to understand whether they yield indications consistent with the properties of the quantitative model under inspection. Specifically, we examine the notions of monotonicity, Lipschitz, and concavity consistency. Surprisingly, only PD functions satisfy all these notions of consistency. However, when selecting the indicators, in addition to consistency, analysts need to consider the risk of model extrapolation. For situations where such risk is under control, we utilize individual conditional expectations together with PD plots. Two applications, on a NASA space risk assessment model and a susceptible exposed infected recovered (SEIR) model for the COVID‐19 pandemic illustrate the insights obtained from these indicators.

Mathematical Methods In Social Sciences↗

WE-AB-204-02: Molecular-Imaging Based Assessment of Liver Complications for Yttrium-90 Microsphere Treatments: Can Existing NTCP Models Explain Clinical Outcomes?

Purpose: To evaluate weather the current radiobiological models can predict the normal liver complications of radioactive Yttrium-90 ({sup 90}Y) selective-internal-radiation-treatment (SIRT) for metastatic liver lesions based on the post-infusion {sup 90}Y PET images. Methods: A total of 20 patients with metastatic liver tumors treated with SIRT that received a post-infusion {sup 90}Y-PET/CT scan were analyzed in this work. The 3D activity distribution of the PET images was converted into a 3D dose distribution via a kernel convolution process. The physical dose distribution was converted into the equivalent dose (EQ2) delivered at 2 Gy based on the linear-quadratic (LQ) model considering the dose rate effect. The biological endpoint of this work was radiation-induce liver disease (RILD). The NTCPs were calculated with four different repair-times (T1/2-Liver-Repair= 0,0.5,1.0,2.0 hr) and three published NTCP models (Lyman-external-RT, Lyman 90Y-HCC-SIRT, parallel model) were compared to the incidence of RILD of the recruited patients to evaluate their ability of outcome prediction. Results: The mean normal liver physical dose (avg. 51.9 Gy, range 31.9–69.8 Gy) is higher than the suggested liver dose constraint for external beam treatment (∼30 Gy). However, none of the patients in our study developed RILD after the SIRT. The estimated probability of ‘no patient developing RILD’ obtained from the two Lyman models are 46.3% to 48.3% (T1/2-Liver-Repair= 0hr) and <1% for all other repair times. For the parallel model, the estimated probability is 97.3% (0hr), 51.7% (0.5hr), 2.0% (1.0hr) and <1% (2.0hr). Conclusion: Molecular-images providing the distribution of {sup 90}Y enable the dose-volume based dose/outcome analysis for SIRT. Current NTCP models fail to predict RILD complications in our patient population, unless a very short repair-time for the liver is assumed. The discrepancy between the Lyman {sup 90}Y-HCC-SIRT model predicted and the clinically observed outcomes further demonstrates the need of an NTCP model specific to the metastatic liver SIRT.

60 APPLIED LIFE SCIENCES↗

Dramatic performance of Clostridium thermocellum explained by its wide range of cellulase modalities

Clostridium thermocellum is the most efficient microorganism for solubilizing lignocellulosic biomass known to date. Its high cellulose digestion capability is attributed to efficient cellulases consisting of both a free-enzyme system and a tethered cellulosomal system wherein carbohydrate active enzymes (CAZymes) are organized by primary and secondary scaffoldin proteins to generate large protein complexes attached to the bacterial cell wall. This study demonstrates that C. thermocellum also uses a type of cellulosomal system not bound to the bacterial cell wall, called the “cell-free” cellulosomal system. The cell-free cellulosome complex can be seen as a “long range cellulosome” because it can diffuse away from the cell and degrade polysaccharide substrates remotely from the bacterial cell. The contribution of these two types of cellulosomal systems in C. thermocellum was elucidated by characterization of mutants with different combinations of scaffoldin gene deletions. The primary scaffoldin, CipA, was found to play the most important role in cellulose degradation by C. thermocellum , whereas the secondary scaffoldins have less important roles. Additionally, the distinct and efficient mode of action of the C. thermocellum exoproteome, wherein the cellulosomes splay or divide biomass particles, changes when either the primary or secondary scaffolds are removed, showing that the intact wild-type cellulosomal system is necessary for this essential mode of action. As a result, this new transcriptional and proteomic evidence shows that a functional primary scaffoldin plays a more important role compared to secondary scaffoldins in the proper regulation of CAZyme genes, cellodextrin transport, and other cellular functions.

09 BIOMASS FUELS↗

Unusual behavior of cuprates explained by heterogeneous charge localization

The discovery of high-temperature superconductivity in cuprates ranks among the major scientific milestones of the past half century, yet pivotal questions regarding the complex phase diagram of these materials remain unanswered. Generally thought of as doped charge-transfer insulators, these complex oxides exhibit pseudogap, strange-metal, superconducting, and Fermi liquid behavior with increasing hole-dopant concentration. Motivated by recent experimental observations, here we introduce a phenomenological model wherein exactly one hole per planar copper-oxygen unit is delocalized with increasing doping and temperature. The model is percolative in nature, with parameters that are highly consistent with experiments. It comprehensively captures key unconventional experimental results, including the temperature and the doping dependence of the pseudogap phenomenon, the strange-metal linear temperature dependence of the planar resistivity, and the doping dependence of the superfluid density. The success and simplicity of the model greatly demystify the cuprate phase diagram and point to a local superconducting pairing mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Low-frequency lattice phonons in halide perovskites explain high defect tolerance toward electron-hole recombination

Low-cost solution-based synthesis of metal halide perovskites (MHPs) invariably introduces defects in the system, which could form Shockley-Read-Hall (SRH) electron-hole recombination centers detrimental to solar conversion efficiency. Here, we investigate the nonradiative recombination processes due to native point defects in methylammonium lead halide (MAPbI 3 ) perovskites using ab initio nonadiabatic molecular dynamics within surface-hopping framework. Regardless of whether the defects introduce a shallow or deep band state, we find that charge recombination in MAPbI 3 is not enhanced, contrary to predictions from SRH theory. We demonstrate that this strong tolerance against defects, and hence the breakdown of SRH, arises because the photogenerated carriers are only coupled with low-frequency phonons and electron and hole states overlap weakly. Both factors appreciably decrease the nonadiabatic coupling. We argue that the soft nature of the inorganic lattice with small bulk modulus is key for defect tolerance, and hence, the findings are general to other MHPs.

Science & Technology - Other Topics↗

Resonance-stabilized hydrocarbon-radical chain reactions may explain soot inception and growth

Mystery surrounds the transition from gas-phase hydrocarbon precursors to terrestrial soot and interstellar dust, which are carbonaceous particles formed under similar conditions. Although polycyclic aromatic hydrocarbons (PAHs) are known precursors to high-temperature carbonaceous-particle formation, the molecular pathways that initiate particle formation are unknown. We present experimental and theoretical evidence for rapid molecular clustering–reaction pathways involving radicals with extended conjugation. These radicals react with other hydrocarbon species to form covalently bound complexes that promote further growth and clustering by regenerating resonance-stabilized radicals through low-barrier hydrogen-abstraction and hydrogen-ejection reactions. Such radical–chain reaction pathways may lead to covalently bound clusters of PAHs and other hydrocarbons that would otherwise be too small to condense at high temperatures, thus providing the key mechanistic steps for rapid particle formation and surface growth by hydrocarbon chemisorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microbial Functional Responses Explain Alpine Soil Carbon Fluxes under Future Climate Scenarios

Soil microorganisms are sensitive to temperature in cold ecosystems, but it remains unclear how microbial responses are modulated by other important climate drivers, such as precipitation changes. Here, we examine the effects of six in situ warming and/or precipitation treatments in alpine grasslands on microbial communities, plants, and soil carbon fluxes. These treatments differentially affected soil carbon fluxes, gross primary production, and microbial communities. Variations of soil CO 2 and CH 4 fluxes across all sites significantly (r > 0.70, P < 0.050) correlated with relevant microbial functional abundances but not bacterial or fungal abundances. Given tight linkages between microbial functional traits and ecosystem functionality, we conclude that future soil carbon fluxes in alpine grasslands can be predicted by microbial carbon-degrading capacities.

54 ENVIRONMENTAL SCIENCES↗

Wide-blocky veins explained by dependency of crystal growth rate on fracture surface type: Insights from phase-field modeling

Vein microstructures contain a wealth of information on coupled chemical and mechanical processes of fracturing, fluid transport, and crystal growth. Numerical simulations have been used for exploring the factors controlling the development of vein microstructures; however, they have not been quantitatively validated against natural veins. Here we combined phase-field modeling with microtextural analysis of previously unexplained wide-blocky calcite veins in natural limestone and of the fresh fracture surface in this limestone. Results show that the wide-blocky vein textures can only be reproduced if ~10%–20% of crystals grow faster than the rest. This fraction corresponds to the amount of transgranularly broken grains that were observed on the experimental fracture surfaces, which are dominantly intergranular. We hypothesize that transgranular fractures allow faster growth of vein minerals due to the lack of clay coatings and other nucleation discontinuities that are common along intergranular cracks. Our simulation results show remarkable similarity to the natural veins and reproduce the nonlinear relationship between vein crystal width and vein aperture. This allows accurate simulations of crystal growth processes and related permeability evolution in fractured rocks.

Geology↗

Molecular Reaction Imaging of a Surface Recombination Process Explains Performance Variation Among Smooth MoS 2 Photoelectrodes

Transition metal dichalcogenides (TMD) such as WSe 2 and MoS 2 are highly efficient and stable light absorbers in TMD∣I − ,I 3 − ∣Pt liquid junction solar cells. It is generally accepted that TMD crystals with a large fraction of exposed edge sites exhibit lower power conversion efficiencies (PCEs) than apparently smooth crystals. However, one open question is why does the PCE vary significantly from one crystal to another? Answering this critical question could lead to robust syntheses for high quality and uniform TMD samples. In this work, we apply nanoscale photoelectrochemical microscopy techniques to study n-type TMD nanoflake∣I − ,I 3 − ∣Pt cells. Using a combination of near-diffraction-limited photocurrent mapping and molecular reaction imaging techniques, we reveal a previously hidden surface recombination process: photogenerated holes in hidden p-type domains travel micron-scale distances parallel to the solid/liquid interface and preferentially react with iodide at step-edges. The overall efficiency of the nanoflake, as evidenced from whole nanoflake-level photoelectrochemical measurements, is dictated by the size, efficiency, and location of n- and p-type domains. Furthermore, these results provide a unifying view of efficiency losses in smooth TMD photoelectrodes and open the possibility to design electrode architectures that leverage the long-range lateral charge transport property for photoelectrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Human-Centered and Explainable Artificial Intelligence in Nuclear Operations

Nuclear power plants in the United States are critical to the nation’s energy security, accounting for 20% of all electricity produced for the power grid. As energy needs grow, 100 gigawatts of additional nuclear power will be necessary by 2050, more than double the current capacity. Realizing this target requires cutting-edge technology like artificial intelligence (AI) and machine learning (ML) that can bring about significant increases in the level of automation. Human-centered AI (HCAI) is a combination of human-centered design (human factors, human-in-the-loop, etc.) with AI/ML to help produce an efficient and reliable system with full consideration for human engagement. This paper provides a comprehensive and novel discussion of HCAI considerations in nuclear power, introducing unique applications for the existing fleet as well as new advanced reactor designs. We include real-life use cases of AI applications to work management processes at nuclear power sites and highlight lessons learned for HCAI.

Hall, Anna↗

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗

Data for Soil Fertility Management for Sustainable Miscanthus × giganteus Production: Increased Tiller Weight from Nitrogen Management Explains Yield Gains in Aged Miscanthus

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha−1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha−1, resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha−1, forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m−2) and tiller weight (g tiller−1) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

miscanthus↗

Pleiotropic Effects of Immune Responses Explain Variation in the Prevalence of Fibroproliferative Diseases

Many diseases are differentially distributed among human populations. Differential selection on genetic variants in ancestral environments that coincidentally predispose to disease can be an underlying cause of these unequal prevalence patterns. Selected genes may be pleiotropic, affecting multiple phenotypes and resulting in more than one disease or trait. Patterns of pleiotropy may be helpful in understanding the underlying causes of an array of conditions in a population. For example, several fibroproliferative diseases are more prevalent and severe in populations of sub-Saharan ancestry. We propose that this disparity is due to selection for an enhanced Th2 response that confers resistance to helminthic infections, and concurrently increases susceptibility to fibrosis due to the profibrotic action of Th2 cytokines. Many studies on selection of Th2-related genes for host resistance to helminths have been reported, but the pleiotropic impact of this selection on the distribution of fibrotic disorders has not been explicitly investigated. We discuss the disproportionate occurrence of fibroproliferative diseases in individuals of African ancestry and provide evidence that adaptation of the immune system has shaped the genetic structure of these human populations in ways that alter the distribution of multiple fibroproliferative diseases.

59 BASIC BIOLOGICAL SCIENCES↗