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The biannual U.S. Department of Energy (DOE) Wind Research and Development (R&D) Newsletter provides recent news about DOE’s Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office (WETO) R&D projects, news, and accomplishments.
Invited contribution to the ITU News Magazine – Special Edition on “Future use and applications of the Coordinated Universal Time (UTC)” a joint ITU-BIPM initiative. The ITU will produce a special edition of its ITU News Magazine that will feature the “Future use and applications of the Coordinated Universal Time (UTC)”, a joint ITU-BIPM initiative, planned for publication in March or April, 2023. The main objective of the magazine is to educate telecommunication society about existing status of UTC applications, objectives, and possible ways to resolve the leap second issues. This article on “Synchronization of electrical distribution networks” for this edition, highlighting some of the key issues that will help the understanding of the important issues that are related to the coordinated universal time (UTC) and its dissemination.
Motifs are distinctive, recurring, widely used idiom-like words or phrases, often originating from folklore, whose meaning is anchored in a narrative and have a significance as communicative devices across a wide range of media, including news, literature, and propaganda. Many motifs concisely imply a large constellation of culturally relevant information, and their broad usage suggests their cognitive importance as touchstones of cultural knowledge. As such, their detection is a step towards culturally aware natural language processing. We present GOLEM (GOld standard for Learning and Evaluation of Motifs) a dataset of English news articles, opinion pieces, and broadcast transcripts annotated for motific information. The dataset identifies 25,737 motif candidates across 34 motif types drawn from three cultural or national groups: Jewish, Irish, and Puerto Rican. The dataset contains 2,024,141 words split into 25,737 text snippets drawn from 8,073 articles. Each motif candidate is labeled according to a scheme which identifies the type of usage (motific, referential, eponymic, or unrelated), resulting in 1,743 actual motific instances in the data. Annotation was performed by individuals identifying as members of each group and achieved a Fleiss’ kappa (?) of > 0.55. In addition to the data, we demonstrate that classification of the candidate type is a challenging task for Large Language Models (LLMs) using a few-shot approach; recent models such as T5, FLAN-T5, GPT-2, and Llama 2 (7B) achieved a performance of 41% accuracy at best, where the majority class accuracy is 41% and the average chance accuracy is 27%. These data will support development of new models and approaches for detecting (and reasoning about) motific information in text.
Two conduction-cooled 915 MHz superconducting radio frequency hermetic assemblies must be safely transported from the Jefferson Lab in Newport News, VA to General Atomics in San Diego, CA for perfor-mance testing in a custom horizontal test cryostat. One hermetic assembly consists of a 2-cell 915 MHz cavity, a coaxial fundamental power coupler, and the warm-to-cold transition beam tubes. The second hermetic assembly consists of a 2-cell 915 MHz cavity only. The assemblies will be transported on a flatbed air-ride trailer over the approximate 4000 km distance. Design requirements included adequate attenuation of 4g vertical axis, 5g beamline axis, and 1.5g lateral axis shock events. The isolation system was designed using helical wire-rope isolators with modal and transient finite element analysis performed in Ansys. Results show shock attenuation of a 10 ms half-sine pulse input to < 1g in the vertical axis, < 1.5g in the beam-line axis, and < 0.5g in the lateral axis for both assem-blies at the specified design loads and all structural stresses are kept below the material yield limits. Addi-tionally, the natural frequencies of both isolation sys-tems adequately attenuate the fundamental modes of the critical structures.
This chapter presents experiments conducted at Thomas Jefferson National Accelerator Facility (Jefferson Lab), a U.S. Department of Energy national laboratory in Newport News, Virginia. There, physicists exploring the nature of matter make use of the Continuous Electron Beam Accelerator Facility (CEBAF), a DOE Office of Science user facility that enables the research of more than 1,650 scientists worldwide. CEBAF’s precise electron beams can reach energies up to 12 billion electron-volts and exhibit high degrees of polarization. Jefferson Lab’s first experiment began taking data in 1995. Since then, the facility has become a world leader in the study of quantum chromodynamics. Today, experiments are carried out simultaneously in four experimental halls, each with specialized capabilities. The primary instruments in use are focusing or large-acceptance magnetic spectrometers, many of which feature superconducting elements. Jefferson Lab’s physics program provides unprecedented insight into the particles and forces that shape the visible universe.
Environmental contamination by micro- and nanoplastics (MNPs) is well documented with potential for their increased accumulation globally. Growing public concern over environmental, ecological, and human exposure to MNPs has led to exponential increase in publications, news articles, and reports. Significant knowledge gap exists in standardized analytical methods for the identification and quantification of MNPs from real world environmental samples. Here, in this study, we report comprehensive datasets utilizing thermogravimetric analyzer (TGA) coupled to a Fourier transformed infrared spectrometer (FTIR) and a gas chromatography/mass spectrometer (GC/MS) with corresponding Raman spectral data for the most common polymers documented to be present in the environment (35 plastics of 12 polymer types), to serve as a base line reference for the identification and quantitation of MNPs. Various parameters for TGA-FTIR-GC/MS data acquisition were optimized. Commercial consumer plastic product compositions were identified using this analytical database. Case studies to showcase the utility of the method for polymer mixtures analysis is included. This dataset would serve towards the development of a collaborative, global, comprehensive, and curated public database for the identification of various MNPs and mixtures.
Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets through self-supervision. The resulting rich representations of complex systems and dynamics can be applied to many downstream applications. Therefore, advances in FMs can find uses in electric power grids, challenged by the energy transition and climate change. This paper calls for the development of FMs for electric grids. We highlight their strengths and weaknesses amidst the challenges of a changing grid. It is argued that FMs learning from diverse grid data and topologies, which we call grid foundation models (GridFMs), could unlock transformative capabilities, pioneering a new approach to leveraging AI to redefine how we manage complexity and uncertainty in the electric grid. Finally, we discuss a practical implementation pathway and road map of a GridFM-v0, a first GridFM for power flow applications based on graph neural networks, and explore how various downstream use cases will benefit from this model and future GridFMs.
The Møller polarimeter in Hall A at Jefferson Lab in Newport News, VA, has provided reliable measurements of electron beam polarization for the past two decades. Past experiments have typically required polarimetry at the 1% level of absolute uncertainty which the Møller polarimeter has delivered. However, the upcoming proposed experimental program including MOLLER and SoLID have stringent requirements on beam polarimetry precision at the level of 0.4% (The MOLLER Collaboration, 2014; The SoLID collaboration, 2019), requiring a systematic re-examination of all the contributing uncertainties. Møller polarimetry uses the double polarized scattering asymmetry of a polarized electron beam on a target with polarized atomic electrons. The target is a ferromagnetic material magnetized to align the spins in a given direction. In Hall A, the target is a pure iron foil aligned perpendicular to the beam and magnetized out of plane parallel or antiparallel to the beam direction. The acceptance of the detector is engineered to collect scattered electrons close to 90° in the center of mass frame where the analyzing power is a maximum (-7/9). One of the leading systematic errors comes from determination of the target foil polarization. Polarization of a magnetically saturated target foil requires knowledge of both the saturation magnetization and g', the electron g-factor which includes components from both spin and orbital angular momentum from which the spin fraction of magnetization is determined. Target foil polarization has been previously addressed in a 1997 publication “A precise target for Møller polarimetry” by de Bever et al. (1997) at a level of precision sufficient for experiments up to this point. Several shortcomings with the previous published value require revisiting the result prior to MOLLER. Here, we utilize the existing world data to provide a best estimate for target polarization for both nickel and iron foils including uncertainties in magnetization, high-field and temperature dependence, and fractional contribution to magnetization from orbital effects. We determine the foil electron spin polarization at 294 K to be 0.08020 ± 0.00018 (@4 T applied field) for iron and 0.018845+/-0.000053 (@2 T applied field) for nickel. Finally, we conclude with a brief discussion of additional systematic uncertainties to Møller polarimetry using this technique.
Social media has become an integral part of everyday life for many individuals, serving as a platform to express opinions, share memories and lifestyles, follow news, and adapt to social trends and norms. The wealth of user information and analytics on these platforms has facilitated the development and sale of tailored products and services, benefiting advertisers and researchers seeking survey participants. Social media advertising has demonstrated its effectiveness in reaching hard-to-reach populations. However, transport researchers have yet to capitalise on this potential fully. This paper presents our experience using social media to recruit participants for two smartphone travel surveys conducted in Australia. We demonstrate that social media recruitment and smartphone-based travel surveys are highly effective, adaptable, and can be rapidly deployed in response to research opportunities, such as during the early phase of the COVID-19 pandemic when traditional methods may be less suitable. This approach also holds great potential for travel surveys targeting the general population. This paper shares several lessons from this experiment, including our administrative approach and detailed technical instructions to utilise open-source software tools for conducting smartphone travel surveys like ours. This approach significantly reduces study costs compared to most commercial solutions.
Worldwide concern over climate change and its consequences has become a regular topic in the news. Extremes of weather appear to be more and more commonplace all over the planet. Release of man-made carbon dioxide, a greenhouse gas, has been associated with climate change, as the levels of CO 2 have continued to increase at a steady rate. In response to this change, many scientists and engineers have began research either to look at ways to sequester carbon dioxide from the atmosphere or to capture it at its source to avoid having to concentrate the CO 2 from the air. At the same time, CO 2 has been highlighted as an inexpensive C1 carbon source, and research efforts are underway to use CO 2 directly in chemical production.
The effects of ionizing radiation on materials often reduce to "bad news". Radiation damage usually leads to detrimental effects such as embrittlement, accelerated creep, phase instability, and radiation-altered corrosion. Here we report that proton irradiation decelerates intergranular corrosion of Ni-Cr alloys in molten fluoride salt at 650 °C. We demonstrate this by showing that the depth of intergranular voids resulting from Cr leaching into the salt is reduced by proton irradiation alone. Interstitial defects generated from irradiation enhance diffusion, more rapidly replenishing corrosion-injected vacancies with alloy constituents, thus playing the crucial role in decelerating corrosion. Our results show that irradiation can have a positive impact on materials performance, challenging our view that radiation damage usually results in negative effects.
This "news and views" article provides scientific context for an accepted article in this journal that examines the cost and air pollutant emission implications of reducing net CO2 emissions from New York City’s transportation sector.
China is now the world's largest source of bilateral development finance and will likely continue to play a prominent role in sovereign lending through its multi-billion-dollar Belt and Road Initiative. This paper introduces major methodological enhancements in tracking this finance: the use of an original application programming interface (API) to gathers news in multiple languages; double verification of every record to ensure every finance commitment has been formalized; and visual geo-location to trace the precise footprint of every project. The resulting dataset enables economic, environmental, and social analyses with high-precision spatial accuracy, as well as spatiotemporal monitoring by project stakeholders and enhanced planning by project managers. It covers the years 2008-2019 to enable analysis before and after the announcement of the Belt and Road Initiative. It includes 862 finance commitments, 669 of which have geographic location, to 94 countries across the world.
In recent years, the reports of Kyasanur forest disease (KFD) breaking endemic barriers by spreading to new regions and crossing state boundaries is alarming. Effective disease surveillance and reporting systems are lacking for this emerging zoonosis, hence hindering control and prevention efforts. We compared time-series models using weather data with and without Event-Based Surveillance (EBS) information, i.e., news media reports and internet search trends, to predict monthly KFD cases in humans. We fitted Extreme Gradient Boosting (XGB) and Long Short-Term Memory models at the national and regional levels. We utilized the rich epidemiological data from endemic regions by applying Transfer Learning (TL) techniques to predict KFD cases in new outbreak regions where disease surveillance information was scarce. Overall, the inclusion of EBS data, in addition to the weather data, substantially increased the prediction performance across all models. The XGB method produced the best predictions at the national and regional levels. The TL techniques outperformed baseline models in predicting KFD in new outbreak regions. Novel sources of data and advanced machine-learning approaches, e.g., EBS and TL, show great potential towards increasing disease prediction capabilities in data-scarce scenarios and/or resource-limited settings, for better-informed decisions in the face of emerging zoonotic threats.
The bonding structures of infinitene, the Chemical and Engineering News 2021 Molecule of the Year, is studied by means of oriented quasi-atomic orbitals (QUAOs) to assess the degree of aromaticity within the molecule.
The storage ring of the Advanced Photon Source (APS) will be upgraded to a fourth-generation ring after more than two decades of operation. During its operation as a 7 GeV ring, scattering beamlines have been built to support soft matter research programs to take advantage of the high flux and high energy beam provided by the ring. Further, the 6 GeV multi-bend achromat storage ring installed by the APS-Upgrade (APS-U) will provide new opportunities for the scattering beamlines. In this news, activities of those APS beamlines in conjunction with the APS-U will be briefly reviewed along with some recent technical highlights of their soft matter research programs.
The GlueX experiment is located at the Thomas Jefferson National Accelerator Facility (JLab) in Newport News, VA, USA. It features a hermetic 4π detector with excellent tracking and calorimetry capabilities. Its 9 GeV linearly polarized photon beam is produced from the 12 GeV electron beam, delivered by JLab’s Continuous Electron Beam Accelerator Facility (CEBAF), via bremsstrahlung on a thin diamond and is incident on a LH2 target. GlueX recently finished its first data taking period and published first results. The main goal of GlueX is to measure gluonic excitations of mesons. These so-called hybrid or exotic mesons are predicted by Quantum Chromodynamics (QCD) but haven’t been experimentally confirmed yet. They can have quantum numbers not accessible by ordinary quark-antiquark pairs which helps in identifying them using partial wave analysis techniques. The search for exotic mesons requires a very good understanding of photoproduction processes in a wide range of final states, one of them being pK + K - which contains many meson and baryon reactions. The Λ(1520) is a prominent hyperon resonance in this final state and is the subject of this presentation. This talk will give an introduction to the GlueX experiment and show preliminary results for the photoproduction of the Λ(1520) hyperon. The measurement of important observables like the photon beam asymmetry and spin-density matrix elements will be discussed and an outlook to possible measurements of further hyperon states in the pK + K - final state will be given.
In the hydrodynamic model description of heavy ion collisions, the final-state anisotropic flows v n are linearly related to the strengths of the multipole shape of the distribution of nucleons in the transverse plane, ε n : v n ∝ε n . The ε n , for n=1, 2, 3, 4, are sensitive to the shapes of the colliding ions, characterized by the quadrupole β 2 , octupole β 3 , and hexadecapole β 4 deformations. This sensitivity is investigated analytically and also in a Monte Carlo Glauber model. One observes a robust linear relation, $\langleε^{2}_{n}\rangle$ = $a^{'}_{n} + b^{'}_{n}β^{2}_{n}$, for events in a fixed centrality. The $\langleε^{2}_{1}\rangle$ has a contribution from β 3 and β 4 , and $\langleε^{2}_{3}\rangle$ from β 4 . In ultracentral collisions, there are little cross contributions between β 2 and ε 3 and between β 3 and ε 2 , but clear cross contributions are present in noncentral collisions. Additionally, $\langleε^{2}_{n}\rangle$ are insensitive to nonaxial shape parameters such as the triaxiality. This is good news because the measurements of v 2 , v 3 , and v 4 can be used to constrain simultaneously the β 2 , β 3 , and β 4 values. This is best done by comparing two colliding ions with similar mass numbers and therefore nearly identical $a^{'}_{n}$, to obtain a simple equation that relates the β n of the two species. Finally, this opens up the possibility to map the shape of the atomic nuclei at a timescale (<10 –24 s) much shorter than probed by low-energy nuclear structure physics (<10 –21 s), which ultimately may provide information complementary to that obtained in the nuclear structure experiments.