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At least 1,099 records · Page 61

Inference for Nonparanormal Partial Correlation via Regularized Rank-Based Nodewise Regression

Abstract Partial correlation is a common tool in studying conditional dependence for Gaussian distributed data. However, partial correlation being zero may not be equivalent to conditional independence under non-Gaussian distributions. In this paper, we propose a statistical inference procedure for partial correlations under the high-dimensional nonparanormal (NPN) model where the observed data are normally distributed after certain monotone transformations. The NPN partial correlation is the partial correlation of the normal transformed data under the NPN model, which is a more general measure of conditional dependence. We estimate the NPN partial correlations by regularized nodewise regression based on the empirical ranks of the original data. A multiple testing procedure is proposed to identify the nonzero NPN partial correlations. The proposed method can be carried out by a simple coordinate descent algorithm for lasso optimization. It is easy-to-implement and computationally more efficient compared to the existing methods for estimating NPN graphical models. Theoretical results are developed to show the asymptotic normality of the proposed estimator and to justify the proposed multiple testing procedure. Numerical simulations and a case study on brain imaging data demonstrate the utility of the proposed procedure and evaluate its performance compared to the existing methods. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

97 MATHEMATICS AND COMPUTING↗

Electromagnetic and scalar diffraction by a right-angled wedge with a uniform surface impedance

The diffraction of an electromagnetic wave by a perfectly-conducting right-angled wedge with one surface covered by a dielectric slab or absorber is considered. The effect of the coated surface is approximated by a uniform surface impedance. The solution of the normally incident electromagnetic problem is facilitated by introducing two scalar fields which satisfy a mixed boundary condition on one surface of the wedge and a Neumann of Dirichlet boundary condition on the other. A functional transformation is employed to simplify the boundary conditions so that eigenfunction expansions can be obtained for the resulting Green's functions. The eigenfunction expansions are transformed into the integral representations which then are evaluated asymptotically by the modified Pauli-Clemmow method of steepest descent. A far zone approximation is made to obtain the scattered field from which the diffraction coefficient is found for scalar plane, cylindrical or sperical wave incident on the edge. With the introduction of a ray-fixed coordinate system, the dyadic diffraction coefficient for plane or cylindrical EM waves normally indicent on the edge is reduced to the sum of two dyads which can be written alternatively as a 2 X 2 diagonal matrix.

Hwang, Y. M.↗

Exotic Molecules in Space: A Coordinated Astronomical Laboratory and Theoretical Study

The past three years have been a period of great progress in our laboratory investigation of molecules of astrophysical interest-the most productive by far in the 20-year history of a research program which has led to the discovery of over 20% of the 123 known interstellar and circumstellar molecules. Most of the discoveries made during this period have been the result of the construction in late 1995 and early 1996 of a Fourier transform microwave spectrometer working in the centimeter-wave band. The sensitivity of this instrument from the moment that it was turned on has exceeded our expectations by an order of magnitude. The Table below shows the 46 new molecules which have been discovered. Most are carbon chains, the dominant type of molecule which has been found in space. Several comments with respect to these molecules should be made: 1. There are probably no mistakes in any of the identifications, since these have been confirmed by the standard, powerful assays and tests used to check spectroscopic identifications: isotopic substitution, quantum calculations of the expected molecular structures, detection of hyperfine structure, Zeeman effect, etc. 2. The radio laboratory astrophysics of the entire set is complete for the time being, in the sense that essentially all the astronomically interesting radio transitions (including hfs when present) are either directly measured or can now be calculated from the derived spectroscopic constants to better than 1 part per million (or 0.3 km s-1 in radial velocity, and often much better than that). 3. Six of the forty six new molecules have already been identified in space, in every case but one on the basis of our laboratory measurements. 4. Sensitive as they are, our laboratory techniques are far from fundamental limits on sensitivity, and 5. One of the principal motivations of our research is to close the fairly small mass and size gap, now only a factor of a few, between the smallest postulated interstellar grains and the largest identified interstellar molecules.

Thaddeus, Patrick↗

Zr 6 O 8 Node-Catalyzed Butene Hydrogenation and Isomerization in the Metal–Organic Framework NU-1000

Zirconium-based metal–organic frameworks (Zr-MOFs) have been increasingly studied over the past two decades as heterogeneous catalysts due to their synthetic tunability, well-defined nature, and chemical stability. In contrast to traditional zirconia-based heterogeneous catalysts, the community has assumed that Zr-MOFs are inert catalyst supports that do not participate directly in hydrocarbon transformations, such as olefin hydrogenation and isomerization. Here, we report that the Zr-MOF NU-1000 is capable of catalyzing olefin hydrogenation and isomerization, without any postsynthetic modifications, under a hydrogen atmosphere. We probe H 2 activation over the nodes of NU-1000 via spectroscopic and computational techniques revealing that H 2 dissociation can occur heterolytically across coordinatively unsaturated Zr sites and proximal hydroxide and μ3-oxo ligands. These results, along with catalytic experiments, suggest that H 2 activation results in node-supported zirconium hydrides capable of the hydrogenation and isomerization of 1-butene. When examining rate dependence on the partial pressure of H 2 , we observe first-order dependence for hydrogenation and half-order dependence for isomerization. Half-order H 2 rate dependence is consistent with a mechanism where both fragments of cleaved H 2 are active for 1-butene isomerization, suggesting that heterolytic cleavage generates acidic protons resulting in parallel, acid-, and hydride-catalyzed isomerization pathways. In conclusion, this work shows that Zr-MOFs have more diverse reactivity than the current literature may suggest and opens possibilities for ways in which Zr-MOFs can be used as heterogeneous catalysts and supports.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

United States Muon Collider Community White Paper for the European Strategy for Particle Physics Update

This document is being submitted to the 2024-2026 European Strategy for Particle Physics Update (ESPPU) process on behalf of the US Muon Collider community, with its preparation coordinated by the interim US Muon Collider Coordination Group. The US Muon Collider Community comprises a few hundred American scientists. The purpose of the document is to inform ESPPU about the US plans for Muon Collider research and development (R&D), explain how these efforts align with the broader international R&D initiatives, and present the US community vision for the future realization of this transformative project.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multidisciplinary Design Of Hot Composite Structures

Unified computer code developed to implement multidisciplinary approach to design and analysis of composite-material structures that must withstand high temperatures. Code modular: includes executive module communicating with and coordinating other modules performing calculations pertaining to traditionally separate disciplines like those of acoustics, structural vibrations, structural loads, and thermal effects. Essential feature, finite-element numerical simulation of relevant physical phenomena according to applicable disciplines. Same finite-element mesh used in thermal, vibrational, and structural analyses; minimizing data-preparation time and eliminating errors incurred in transforming temperatures from one finite-element mesh to another.

Chamis, Christos C.↗

Impact of Charge Voltage on Factors Influencing Capacity Fade in Layered NMC622: Multimodal X-ray and Electrochemical Characterization

Ni-rich NMC is an attractive Li-ion battery cathode due to its combination of energy density, thermal stability, and reversibility. While higher delivered energy density can be achieved with a more positive charge voltage limit, this approach compromises sustained reversibility. Improved understanding of the local and bulk structural transformations as a function of charge voltage, and their associated impacts on capacity fade are critically needed. Through simultaneous operando synchrotron X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) of cells cycled at 3–4.3 or 3–4.7 V, this study presents an in-depth investigation into the effects of voltage window on local coordination, bulk structure, and oxidation state. These measurements are complemented by ex situ X-ray fluorescence (XRF) mapping and scanning electrochemical microscopy mapping (SECM) of the negative electrode, X-ray photoelectron spectroscopy (XPS) of the positive electrode, and cell level electrochemical impedance spectroscopy (EIS). Initially, cycling between 3 and 4.7 V leads to greater delivered capacity due to greater lithium extraction, accompanied by increased structural distortion, moderately higher Ni oxidation, and substantially higher Co oxidation. Continued cycling at this high voltage results in suppressed Ni and Co redox, greater structural distortion, increased levels of transition metal dissolution, higher cell impedance, and 3× greater capacity fade.

capacity fading mechanisms↗

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS↗

Planning and Operations in Electricity Markets Under System Transformation

United States electricity markets, planning mechanisms, and operational procedures are currently evolving in concert with three key trends. First, a range of new resources—solar, wind, energy storage, hybrid co-located storage, and distributed energy—are coming online and require new solutions to ensure they are efficiently integrated into existing systems. Second, consumers now face more opportunities to participate in markets by providing demand response and engaging in two-way interactions with the grid. Third, there is an increasing need for enhanced coordination between generation and transmission planning as well as across transmission and distribution systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models

Abstract. Motivated by reducing errors in the energy budget related to enthalpy fluxes within the Energy Exascale Earth System Model (E3SM), we study several physics–dynamics coupling approaches. Using idealized physics, a moist rising bubble test case, and the E3SM's nonhydrostatic dynamical core, we consider unapproximated and approximated thermodynamics applied at constant pressure or constant volume. With the standard dynamics and physics time-split implementation, we describe how the constant-pressure and constant-volume approaches use different mechanisms to transform physics tendencies into dynamical motion and show that only the constant-volume approach is consistent with the underlying equations. Using time step convergence studies, we show that the two approaches both converge but to slightly different solutions. We reproduce the large inconsistencies between the energy flux internal to the model and the energy flux of precipitation when using approximate thermodynamics, which can only be removed by considering variable latent heats, both when computing the latent heating from phase change and when applying this heating to update the temperature. Finally, we show that in the nonhydrostatic case, for physics applied at constant pressure, the general relation that enthalpy is locally conserved no longer holds. In this case, the conserved quantity is enthalpy plus an additional term proportional to the difference between hydrostatic pressure and full pressure.

58 GEOSCIENCES↗

Thermally driven phase transitions in freestanding low-buckled silicene, germanene, and stanene

Low-buckled silicene, germanene, and stanene are group-IV graphene allotropes. They form a honeycomb lattice out of two interpenetrating (A and B) triangular sublattices that are vertically separated by a small distance Δ z . The atomic numbers Z of silicon, germanium, and tin are larger than that of carbon (Z C = 6), making them the first experimentally viable two-dimensional topological insulators. Those materials have a twice-energy-degenerate atomistic structure characterized by the buckling direction of the B sublattice with respect to the A sublattice [whereby the B atom either protrudes above (Δ z > 0) or below (Δ z < 0) the A atoms], and the consequences of that energy degeneracy on their elastic and electronic properties have not been reported thus far. Here, we uncover ferroelastic, bistable behavior on silicene, which turns into an average planar structure at about 600 K. Furthermore, the creation of electron and hole puddles obfuscates the zero-temperature spin-orbit coupling (SOC)-induced band gaps at temperatures as low as 200 K, which may discard silicene as a viable two-dimensional topological insulator for room-temperature applications. Germanene, on the other hand, never undergoes a low-buckled-to-planar two-dimensional transformation, becoming amorphous at around 675 K instead, and preserving its SOC-induced band gap despite band broadening. Stanene undergoes a transition onto a crystalline three-dimensional structure at about 300 K, preserving its SOC-induced electronic band gap up to that temperature. Unlike what is observed in silicene and germanene, stanene readily develops a higher-coordinated structure with a high degree of structural order. Furthermore, the structural phenomena are shown to have far-reaching consequences for the electronic and vibrational properties of those two-dimensional topological insulators.

36 MATERIALS SCIENCE↗

Special Section on Local and Distributed Electricity Markets

Driven by the goals of clean energy and zero carbon emissions, the power industry is undergoing significant transformations. The rapid growth of diverse distributed energy resources (DERs) at grid edge such as rooftop photovoltaics (PVs) and electric vehicles is transforming the traditional centralized power grid management to a decentralized, bottom-up, and localized control paradigm. Establishing local and distribution-level electricity markets provides an effective solution to managing large amounts of small-scale DERs. New regulations such as the recent FERC Order 2222 in the U.S. open the door to DERs in the wholesale markets. Through coordinating the local and distribution-level markets with the transmission-level wholesale market, the DERs and prosumers can trade energy and flexibility locally with each other and meanwhile provide energy, flexibility and ancillary services to the bulk power grid. During this transition, there are many new technical challenges to address, calling for innovative ideas and interdisciplinary research in this promising direction. Advanced information and communication technologies (ICT) are needed, as a key enabler, for the development and practical implementation of local and distribution electricity markets. Research into local and distribution markets is strongly interdisciplinary, involving the state of the art in power engineering, economics, and digital/information technology. A broad spectrum of contributors from universities, industry, research laboratories and policy makers is sought to develop and present solutions and technologies that will facilitate and advance practical applications and implementations of local and distribution-level electricity markets to uncover the values of DERs.

distributed energy resources↗

Review of Technical Requirements for Inverter-Based Resources in Chile

This document compares the technical requirements in the grid code of Chile (NTSyCS) against the EirGrid (Ireland transmission system operator) and National Grid Electricity System Operator (NESO) grid codes and the Institute of Electrical and Electronics Engineers (IEEE) 2800-2022 standard for conventional inverter technology at the transmission and subtransmission levels in the process of being adopted by system operators in the U.S. The document is intended to be a guide and reference for future updates of the NTSyCS, considering the local system requirements and present improvements in inverter-based resource (IBR) technology. In light of the findings of the aforementioned comparative review, this document proposes and describes the requirements for conventional IBRs that could be incorporated and updated into the Chilean grid code. The document is structured around the main grid challenges posed by the transition to an IBR-dominated grid and conventional IBRs capabilities to help address them. This document does not provide guidance on how this specification should be implemented (e.g., through a mandate or market solution).

24 POWER TRANSMISSION AND DISTRIBUTION↗

A theory of supercritical wing sections, with computer programs and examples.

Mathematical methods for the design of supercritical wings, which depend on the numerical solution of the partial differential equations of two-dimensional gas dynamics, are developed. The main contribution is a computer program for the design of shockless transonic airfoils using the hodograph transformation and analytic continuation into the complex domain. The mathematical theory is described, and a manual for users of the programs is provided. Numerical examples are given and computational results are discussed, and the computer programs themselves are listed. The analysis routine can be used to ascertain whether the profiles behave well at off-design conditions, or to smooth coordinates and obtain a desirable shape more quickly when perfectly shockless flow is not essential.

Bauer, F.↗

Catalytic Transformation of Positional Nitrophenol Isomers on Highly Active Ag/Linde‐Type A4 Zeolite: A Comparative Analysis

Abstract The catalytic transformation of ortho‐( o‐ NP), meta‐( m‐ NP) and para‐nitrophenols ( p‐ NP) by Ag nanoparticles (Ag‐NPs) stabilised on zeolite A4 (ZA4) is presented for the first time. The catalysts are prepared by microwave‐assisted synthesis (Ag/ZA4‐MW) or ion exchange (Ag/ZA4‐IE). The results indicate that the nitrophenol reduction rate depends on the molecule structure and the presence of low‐coordinated metallic Ag‐NPs (∼2 nm and sub nanometric species). Meanwhile, the reactivity tendency depends on the synthesis methodology ( m‐ NP> p‐ NP> o‐ NP and o‐ NP> m‐ NP> p‐ NP for Ag/ZA4‐MW and Ag/ZA4‐IE, respectively). The turnover frequency (TOF) values estimated for nitrophenols reduction are superior for Ag/ZA4‐MW catalyst by several orders of magnitude compared with those obtained for Ag/ZA4‐IE catalyst. In addition, the catalyst exhibits remarkable catalytic stability for the reduction of p‐ NP even after the fifth consecutive catalytic run. The presently prepared catalysts are characterised by superior catalytic activity for the reduction of nitroaromatic compounds than similar Ag‐based materials reported in the literature.

Horta‐Fraijo, Patricia↗