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At least 145 records · Page 8

Structural diverseness of neurons between brain areas and between cases

The cerebral cortex is composed of multiple cortical areas that exert a wide variety of brain functions. Although human brain neurons are genetically and areally mosaic, the three-dimensional structural differences between neurons in different brain areas or between the neurons of different individuals have not been delineated. Here we report a nanometer-scale geometric analysis of brain tissues of the superior temporal gyrus of schizophrenia and control cases. The results of the analysis and a comparison with results for the anterior cingulate cortex indicated that (1) neuron structures are significantly dissimilar between brain areas and that (2) the dissimilarity varies from case to case. The structural diverseness was mainly observed in terms of the neurite curvature that inversely correlates with the diameters of the neurites and spines. The analysis also revealed the geometric differences between the neurons of the schizophrenia and control cases. The schizophrenia cases showed a thin and tortuous neuronal network compared with the controls, suggesting that the neuron structure is associated with the disorder. The area dependency of the neuron structure and its diverseness between individuals should represent the individuality of brain functions.

60 APPLIED LIFE SCIENCES↗

Broken symmetries associated with a Kagome chiral charge order

Chirality, or handedness, is ubiquitous in science, from cell biology to physics, and in condensed matter can underlie exotic phases such as chiral charge density waves and chiral superconductivity. However, detecting subtle broken symmetries that define such states is challenging, leading to debate and controversy. Here, using second-order optical response, we reveal the broken symmetries of a chiral charge density wave in the Kagome lattice KV 3 Sb 5 . Polarization-dependent mid-infrared photocurrent microscopy uncovers a longitudinal, helicity-dependent photocurrent associated with the charge order, indicating broken inversion and mirror symmetries. These findings, supported by theoretical analysis, directly establish the intrinsic chiral nature of the ordered state. Moreover, the absence of a circular photogalvanic effect perpendicular to the incident light imposes stringent constraints on the point-group symmetries. Our study not only visualizes the chiral nature of the Kagome charge order, but also highlights the nonlinear photogalvanic effect as a sensitive probe for detecting subtle symmetry breakings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Symmetry instability induced by topological phase transitions

The symmetry-topology interplay dictates how to define order parameters and classify material ordered phases. However, current understanding of this interplay has been predominately approached from a one-sided perspective, with topological states being classified within the constraints imposed by specific fixed symmetries. Here, in this study, we complete this full circle by demonstrating spontaneous symmetry breaking that results from a periodic alteration of topological phases induced by light in a centrosymmetric Dirac material ZrTe 5 . The distinguishing feature is the observation of robust correlation and striking anomalies in the fluence and temperature dependence of key transport parameters. First, both shift current 𝐽 𝑠 and displacement current 𝐽 𝑑 , arising from interband transition and infrared phonon driving, respectively, along with charge carrier pumping, exhibit similar behaviors. Second, they all peak at similar low pump fluence, followed by a subsequent reduction as the fluence further increases. This behavior cannot be explained by conventional energetically allowed, direct excitations. Third, all the three observables exhibit anomalies when they approach the topological phase transition temperature. These results highlight the unique low-energy pumping behaviors in ZrTe 5 , characterized by reversible fluence dependence and a “hinge-like” interaction that connects various electronic and lattice observables, including phonons, charge carriers, and currents. Our findings, supported by model analysis, provide key insights into the fragility of crystalline (inversion) and time-reversal symmetries during the dynamics of topological phase transitions. This fragility drives spontaneous symmetry breaking, evidenced by the synchronized emergence of off-resonant infrared phonons and broken-symmetry photocurrents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Neutrino and gamma-ray emissions from NGC 1068

IceCube has recently reported the detection of ∼1–10 TeV neutrinos from the nearby active galaxy, NGC 1068. The lack of TeV-scale emission from this source suggests that these neutrinos are generated in the dense corona that surrounds NGC 1068’s supermassive black hole. In this paper, we present a physical model for this source, including the processes of pair production, pion production, synchrotron, and inverse Compton scattering. We have also performed a new analysis of Fermi-LAT data from the direction of NGC 1068, finding that the gamma-ray emission from this source is very soft but bright at energies below ∼1 GeV . Our model can predict a gamma-ray spectrum that is consistent with Fermi-LAT observations when the magnetic field within the corona of this active galactic nucleus (AGN) is quite high, namely 𝐵 ≳6 kG . To explain the observed neutrino emission, this source must accelerate protons with a total power that is comparable to its intrinsic x-ray luminosity. In this context, we consider two additional nearby active galaxies, NGC 4151 and NGC 3079, which have been identified as promising targets for IceCube.

79 ASTRONOMY AND ASTROPHYSICS↗

Ultrafast Inverse Chirality-Induced Spin Selectivity Observed by THz Emission

Chirality-induced spin selectivity (CISS) phenomena arise from an interplay among structural chirality, electron spin orientation, and charge current. Steady-state observations such as magnetoresistance offer little insight into the timescales that govern the spin-charge interconversion and often conflate interfacial and bulk phenomena. By contrast, inverse CISS involves the conversion of spin to a charge current. Using terahertz (THz) emission spectroscopy, we directly measured an ultrafast charge current due to inverse CISS with picosecond time resolution. Polarity and polarization analysis of the THz emission map the induced charge current direction upon spin injection. We found that a charge current is generated along the spin orientation that changes direction with stereochemical configuration. These observations directly demonstrate the inherent coupling between spin and charge currents in chiral systems, offering key insights into their fundamental dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP)

Anthropogenic climate change is unfolding rapidly, yet its regional manifestation can be obscured by internal variability. A primary goal of climate science is to identify the externally forced climate response from among the noise of internal variability. Separating the forced response from internal variability can be addressed in climate models by using a large ensemble to average over different possible realizations of internal variability. However, with only one realization of the real world, it is a major challenge to isolate the forced response directly in observations. In the Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP), contributors used existing and newly developed statistical and machine learning methods to estimate the forced response over 1950–2022 within individual realizations of the climate system. Participants used neural networks, linear inverse models, fingerprinting methods, and low-frequency component analysis, among other approaches. These methods were trained using large ensembles from multiple climate models and then applied to observations. Here, we evaluate method performance within large ensembles and investigate the estimates of the forced response in observations. Our results show that many different types of methods are skillful for estimating the forced response in climate models, though the relative skill of individual methods varies depending on the variable and evaluation metric. Methods with comparable skill in models can give a wide range of estimates of the forced response pattern in observations, illustrating the epistemic uncertainty in forced response estimates. ForceSMIP gives new insights into the forced response in observations, its uncertainty, and methods for its estimation.

Climate attribution↗

On the Neutrino and Gamma-Ray Emission from NGC 1068

IceCube has recently reported the detection of $\sim 1-10 \,{\rm TeV}$ neutrinos from the nearby active galaxy, NGC 1068. The lack of TeV-scale emission from this source suggests that these neutrinos are generated in the dense corona that surrounds NGC 1068's supermassive black hole. In this paper, we present a physical model for this source, including the processes of pair production, pion production, synchrotron, and inverse Compton scattering. We have also performed a new analysis of Fermi-LAT data from the direction of NGC 1068, finding that the gamma-ray emission from this source is very soft but bright at energies below $\sim 1 \, {\rm GeV}$. Our model can predict a gamma-ray spectrum that is consistent with Fermi-LAT observations, but only if the magnetic field within the corona of this active galactic nucleus (AGN) is quite high, namely $B\gtrsim 6 \, {\rm kG}$. To explain the observed neutrino emission, this source must accelerate protons with a total power that is comparable to its intrinsic X-ray luminosity. In this context, we consider two additional nearby active galaxies, NGC 4151 and NGC 3079, which have been identified as promising targets for IceCube.

79 ASTRONOMY AND ASTROPHYSICS↗

Scattering-based structural inversion of soft materials via Kolmogorov–Arnold networks

Small-angle scattering techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of closed-form expressions of scattering functions. To address these challenges, we present a machine learning framework based on the Kolmogorov–Arnold Network (KAN) for directly extracting real-space structural information from scattering spectra in reciprocal space. This model-independent, data-driven approach provides a versatile solution for analyzing intricate configurations in soft matter. By applying the KAN to lyotropic lamellar phases and colloidal suspensions—two representative soft matter systems—we demonstrate its ability to accurately and efficiently resolve structural collectivity and complexity. Here, our findings highlight the transformative potential of machine learning in enhancing the quantitative analysis of soft materials, paving the way for robust structural inversion across diverse systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local cation order and ferrimagnetism in compositionally complex spinel ferrites

We present an exploration of a family of compositionally complex cubic spinel ferrites featuring combinations of Mg, Fe, Co, Ni, Cu, Mn, and Zn cations, systematically investigating the average and local atomic structures, chemical short-range order, magnetic spin configurations, and magnetic properties. All compositions result in ferrimagnetic average structures with extremely similar local bonding environments; however, the samples display varying degrees of cation inversion and, therefore, differing apparent bulk magnetization. Additionally, first-order reversal curve analysis of the magnetic reversal behavior indicates varying degrees of magnetic ordering and interactions, including potentially local frustration. Finally, reverse Monte Carlo modeling of the spin orientation demonstrates a relationship between the degree of cation inversion and the spin collinearity. Collectively, these observations correlate with differences in synthesis procedures. This work provides a framework for understanding magnetic behavior reported for “high-entropy spinels,” revealing many are likely compositionally complex oxides with differing degrees of chemical short-range order—not meeting the community established criteria for high or medium entropy compounds. Moreover, this work highlights the importance of reporting complete sample processing histories and investigating local to long-range atomic arrangements when evaluating potential entropic mixing effects and assumed property correlations in high entropy materials.

36 MATERIALS SCIENCE↗

Experiments to Measure the Inversion Point of the Isothermal Reactivity Coefficient in a Water-Moderated Pin-Fueled Critical Assembly at Sandia

A new set of critical experiments exploring the temperature-dependence of the reactivity in a critical assembly is described. In the experiments, the temperature of the critical assembly will be varied to determine the temperature that produces the highest reactivity in the assembly. This temperature is the inversion point of the isothermal reactivity coefficient of the assembly. An analysis of relevant configurations is presented. Existing measurements are described and an analysis of these experiments presented. The overall experimental approach is described as are the modifications to the critical assembly needed to perform the experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adult weight change and premenopausal breast cancer risk: A prospective pooled analysis of data from 628,463 women

Early-adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual-level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18–24 years and other breast cancer risk factors showed that weight gain from ages 18–24 to 35–44 or to 45–54 years was inversely associated with breast cancer overall (e.g., HR per 5 kg to ages 45–54: 0.96, 95% CI: 0.95–0.98) and with oestrogen-receptor(ER)-positive breast cancer (HR per 5 kg to ages 45–54: 0.96, 95% CI: 0.94–0.98). Weight gain from ages 25–34 was inversely associated with ER-positive breast cancer only and weight gain from ages 35–44 was not associated with risk. None of these weight gains were associated with ER-negative breast cancer. Weight loss was not consistently associated with overall or ER-specific risk after adjusting for initial weight. Weight increase from early-adulthood to ages 45–54 years is associated with a reduced premenopausal breast cancer risk independently of early-adulthood weight. Biological explanations are needed to account for these two separate factors.

60 APPLIED LIFE SCIENCES↗

Chiral Teropyrenes: Synthesis, Structure, and Spectroscopic Studies

Abstract We present the inaugural synthesis of a chiral teropyrene achieved through a four‐fold alkyne benzannulation catalyzed by InCl 3 , resulting in good yields. The product underwent thorough characterization using FT‐Raman and FT‐IR spectroscopies, demonstrating a close agreement with calculated spectra. X‐ray crystallographic analysis unveiled a notable twist in the molecule‘s backbone, with an end‐to‐end twist angle of 51°, consistent with computational predictions. Experimentally determined enantiomeric inversion barriers revealed a significant energy barrier of 23 kcal/mol, facilitating the isolation of enantiomers for analysis by circular dichroism (CD) and circularly polarized luminescence (CPL) spectroscopies. These findings mark significant strides in the synthesis and characterization of chiral teropyrenes, offering insights into their structural and spectroscopic properties.

Chemistry↗

Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology

Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (a) detection/segmentation of tumor subregions and (b) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of (a) biophysical growth modeling and simulation,(b) inverse problems for model calibration, (c) these models' integration with imaging workflows, and (d) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.

60 APPLIED LIFE SCIENCES↗

Proxy-based Bayesian inversion of strain tensor data measured during well tests

Recent instrument developments have made it possible to measure the strain tensor caused by injecting or pumping fluid from aquifers or reservoirs, but the full value of these data is limited because the long runtimes of poroelastic forward models makes it impractical to use many inversion schemes. This limits the interpretation of strain data for managing the recovery of resources or storage of wastes in the subsurface. This paper describes a method of inverting deformation data using a poroelastic numerical simulator so the results can be used to manage reservoirs or aquifers. We developed a workflow designed to reduce the number of simulations sufficiently to make it feasible to use DREAMzs, an advanced Bayesian inversion method that translates the uncertainties from different sources into unbiased posterior parameter distributions and uncertainty envelopes around the field data. Using a KNN proxy model for the poroelastic simulator is key to reducing the overall computations, and the workflow includes a strategy for ensuring the proxy model results converge on the results from the simulator. The workflow is tested using an idealized example that verifies the ability to correctly identify parameters and characterize noise used to perturb the data. Field data from an injection test at an oil reservoir near Tulsa, Oklahoma, are also used to evaluate the efficacy of the workflow with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), where the results were used to characterize posterior parameter distribution and evaluate the prediction uncertainty. Furthermore, this workflow is significant because it enables strain tensor, or other geomechanical measurements to be interpreted to guide decision-making during energy and environmental processes in the subsurface.

42 ENGINEERING↗

Local atomic configurations in mechanically alloyed amorphous (FeCoNi) 70 Ti 10 B 20 powders

Here, the atomic structure of amorphous (FeCoNi) 70 Ti 10 B 20 alloy synthesized by mechanical alloying was investigated using high energy synchrotron X-ray diffraction and inverse Monte Carlo simulations of pair distribution functions. Empirical potential structure refinement indicates a chemical short-range order at the length scales of 2.1–2.5 Å via local atomic arrangements forming deformed bcc-like clusters. The structural model obtained was described by bond lengths, coordination numbers, and bond angle distribution functions determined for the first neighbor atoms by x-ray scattering supplemented with 3D Monte Carlo simulations.

36 MATERIALS SCIENCE↗

Role of self-generated magnetic fields in the inertial fusion ignition threshold

Magnetic fields spontaneously grow at unstable interfaces around hot-spot asymmetries during inertial confinement fusion implosions. Although difficult to measure, theoretical considerations and numerical simulations predict field strengths exceeding 5 kT in current National Ignition Facility experiments. Magnetic confinement of electrons then reduces the rate of hot-spot heat loss by >5%. We demonstrate this via magnetic post-processing of two-dimensional xRAGE hydrodynamic simulation data at bang time. We then derive a model for the self-magnetization, finding that it varies with the square of the hot-spot temperature and inversely with the areal density. The self-magnetized Lawson analysis then gives a slightly reduced ignition threshold. Time-dependent hot-spot energy balance models corroborate this finding, with the magnetic field quadrupling the fusion yield for near-threshold parameters. The inclusion of magnetized multi-dimensional fluid instabilities could further alter the ignition threshold and will be the subject of future work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Relocating microseismicity from downhole monitoring of the Decatur CCS site using a modified double-difference algorithm

SUMMARY The injection of CO2 at the Decatur carbon capture and storage site has generated significant microseismic activity, which occurs in distinct spatial clusters up to approximately 2.2 km from the primary injection well. Accurate and precise event locations are vital for the characterization of the microseismicity to help understand the reservoir response to the CO2 injection, whilst enabling the identification of minor faults and fractures below the resolution of conventional active seismic imaging. However, microseismic monitoring of fluid injection sites, such as Decatur, is often performed using a network of borehole sensors often from a single well. While these downhole sensors have excellent detection capabilities, their poor azimuthal coverage limits the ability to precisely determine event locations. We have developed a modified double-difference relocation algorithm suitable for both 1-D and 3-D velocity models, and which incorporates differential back azimuth observations to allow the benefits of the original double-difference algorithm to be applicable to a downhole microseismic monitoring setting. Applying the modified double-difference algorithm to the microseismicity at Decatur, we have successfully relocated 4293 events. The relocation included over 59 million observations for 757 285 event pairs, split across seven geographic regions. Despite the majority of observations being recorded in only two boreholes, with an almost identical azimuthal coverage, the results have shown to be reliable with significantly reduced residuals and low uncertainties associated with the final locations. We have analysed the residuals in terms of their association with each geographic region, data type, station and individual events, to fully appreciate their influence in the inversion and the fit of the data to the final set of event locations. For each region, the relocated seismicity has become less diffuse with improved clustering, and with newly visible linear features often orientated in a NE–SW direction. These results show the potential improvements that can be made to microseismic event locations recorded by a borehole network with a limited and variable azimuthal distribution.

58 GEOSCIENCES↗