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This is the final technical report for DOE Grant DE-SC001934 from the years 2018--2025. The report describes briefly Berkeley's antihydrogen and plasma physics research as part of the ALPHA Collaboration.
The SIMBER project is centered around advancing the state-of-the-art in the science of modelling of the human heart and leveraging the collaborations between leading research groups at the University of California Berkeley (UC Berkeley), the Lawrence Berkeley National Laboratory (Berkeley Lab), and Simula Research Laboratory (Simula). In particular, the following areas of expertise are shared and expanded through this project: “heart-on-chip” experimental systems from UC Berkeley, mathematical modelling of the heart from Simula, and supercomputing software from Simula and Berkeley Lab. This intersection of expertise is already enabling the development of novel tools and knowledge that produce more accurate models of the human heart in both health and disease, which in turn are leading to drug screening technologies that make cardiac drug development faster, cheaper and more humane.
The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accelerator complex, detectors and physics for a future muon collider. In 2023, European Commission support was obtained for a design study of a muon collider (MuCol) [3]. This project started on 1st March 2023, with work-packages aligned with the overall muon collider studies. In preparation of and during the 2021-22 U.S. Snowmass process, the muon collider project parameters, technical studies and physics performance studies were performed and presented in great detail. Recently, the P5 panel [4] in the U.S. recommended a muon collider R&D, proposed to join the IMCC and envisages that the U.S. should prepare to host a muon collider, calling this their "muon shot". In the past, the U.S. Muon Accelerator Programme (MAP) [5] has been instrumental in studies of concepts and technologies for a muon collider.
Building on the current program's success and driven by new physics challenges, the NA61/SHINE Collaboration proposes to continue measuring hadron production properties in reactions induced by hadron and ion beams after CERN Long Shutdown 3. These measurements are of significant interest to the heavy-ion, cosmic-ray, and neutrino physics communities and will focus on: - Investigating hadron production in the light-ion systems to explore the diagram of high-energy nuclear collisions, and to obtain new insight into the unexpected violation of isospin (flavor) symmetry recently observed by the experiment; - Measuring charm-anticharm correlations to gain unique insights into the production locality of charm and anticharm quark pairs; - Examining strangeness and multi-strangeness production to improve our understanding of the early Universe's evolution and neutron star formation; - Measuring cross sections relevant for cosmic-ray measurements, significantly boosting searches for new physics in our Galaxy; - Conducting hadron production measurements with proton, pion, and kaon beams for neutrino physics, enhancing the precision of hadron production data needed for initial neutrino flux predictions in neutrino oscillation experiments; - Measuring hadron production processes relevant for understanding the flux of atmospheric neutrinos, as well as neutrinos and muons from spallation sources. To achieve these objectives, a detector upgrade and a beam upgrade are required, with data-taking planned for the period 2029-2032 and beyond.
Africa is a critical source of biomass burning (BB) aerosols, and its importance is increasing. The African Combustion Aerosol Collaborative Intercomparison Analysis (ACACIA) Pilot Project set to optically characterize BB aerosol generated from sub-Saharan African fuels. We used a photoacoustic spectrometer as a reference instrument to determine the multiple-scattering correction factor C λ for an AE33 aethalometer at three wavelengths, which produced weighted mean values of C 370 =3.69, C 470 =5.65, and C 520 =6.39. C λ increased with wavelength and C 370 was statistically independent of the others, suggesting a single C λ is insufficient, especially in BB scenarios. While a dependence of C λ on burning state was not found, C λ was shown to strongly relate to particle single scattering albedo (SSA, ω). When Cλ was plotted against SSA, values slowly rose at low SSA values, followed by a sharp rise around an SSA of ∼ 0.9; indicating a larger correction needed for less absorbing aerosol. A number of functions operating on either SSA or C λ were explored and the best function was -C λ /(1-C λ )=Aω+B. This is an important parametrization of C λ specifically geared towards BB aerosol from African fuels under different aging states, and is of particular importance for future field work in that continent. An Ångström matrix plot shows that African BB aerosol can have values more akin to dust, which demonstrates that these fuels are distinct in their wavelength dependence from more typical BB aerosol. Lastly, we examined the mass extinction and absorbance cross sections for BB aerosol generated for the same fuels with two different tube furnace setups. Not only is this combustion method flexible, it was found to be reproducible between labs.
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.
Nearly 200 years have passed since the first marine fungus, collected from the shores of North Africa, was described. In that time, marine mycologists have continued to observe, describe, and study fungi in every marine ecosystem examined. Nevertheless, fungi remain functionally “dark matter” of the ocean, presenting a grand opportunity to unravel their roles in ecosystem processes. This report outlines the discussion among participants of the second occasional meeting of marine mycologists at Asilomar, California, in March 2024, in which a diverse and interdisciplinary consortium of researchers enumerated the most pressing, and often basic, unanswered questions in marine fungi. We report on the questions facing the field of marine mycology, identify challenges in addressing those questions, and propose concrete and practical solutions for obtaining their answers. A common thread is the need for increasing cross talk and collaboration between mycologists and oceanographers that would present opportunities for readers to participate in a rapidly growing field.
This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on ~30 m range gates, stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, below range, ran out of signal, cloud-topped). Cloud Base Height (Haar-gradient detection): 15 min estimates of cloud-base height (m) with a cloud-detection quality flag (0–3: none, low, moderate, high). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (2.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution, with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science
This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science
This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.1), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science
A collaborative research program covering a variety of topics of biomechanics and biomedical engineering within the fields of cardiovascular dynamics, respiration, bone elasticity and vestibular physiology is described. The goals of the research were to promote: (1) a better understanding of the mechanical behavior of the circulatory system and its control mechanisms; (2) development of noninvasive methods of measuring the changes in the mechanical properties of blood vessels and other cardiovascular parameters in man; (3) application of these noninvasive methods to examine in man the physiological effects of environmental changes, including earth-simulated gravitational changes; and (4) development of in-flight methods for studying the events which lead to post-flight postural hypotension.
The results of a collaborative study to define both the neutron flux and the spectrum more precisely and to develop a dosimetry package that can be flown quickly to altitude for solar flare events are described. Instrumentation and analysis techniques were used which were developed to measure accelerator-produced radiation. The instruments were flown in the Ames Research Center high altitude aircraft. Neutron instrumentation consisted of Bonner spheres with both active and passive detector elements, threshold detectors of both prompt-counter and activation-element types, a liquid scintillation spectrometer based on pulse-shape discrimination, and a moderated BF3 counter neutron monitor. In addition, charged particles were measured with a Reuter-Stokes ionization chamber system and dose equivalent with another instrument. Preliminary results from the first series of flights at 12.5 km (41,000 ft) are presented, including estimates of total neutron flux intensity and spectral shape and of the variation of intensity with altitude and geomagnetic latitude.
The U.S.S.R. cooperative space efforts with other Socialist countries dating back to 1957 are reviewed. The Interkosmos program, which is divided into three series of satellites (solar, ionospheric and magnetospheric), is discussed as well as the Prognoz, Kosmos, Soyuz, and Molniya spacecraft. Collaboration with France, India, Sweden, and the United States is mentioned.
A cooperative advanced digital research experiment (CADRE) was established by the National Aeronautics and Space Administration (NASA) and the Royal Aircraft Establishment (RAE), in which nonlinear control algorithms developed by the RAE were tested on the F-8C digital fly-by-wire (DFBW) aircraft based at the Dryden Flight Research Facility. In the initial phase of the collaboration, some variable-gain algorithms, referred to collectively as variable integral control to optimize response (VICTOR) algorithms, were fight tested. With VICTOR, various measures available within the control system are used to vary gains and time-constants within the closed loop and thereby enhance the control capability of the system, while reducing the adverse effects of sensor noise on the control surfaces. A review of design procedures for VICTOR and results of preliminary flight tests are presented. the F-8C aircraft is operated in the remotely augmented vehicle (RAV) mode, with the control laws implemented as FORTRAN programs on a ground-based computer. Pilot commands and sensor information are telemetered to the ground, where the data are processed to form surface commands which are then telemetered to the ground, where the data are processed to form surface commands which are then telemetered back to the aircraft. The RAV mode represents a single-string (simplex) system and is therefore vulnerable to a hardover since comparison monitoring is not possible. Hence, extensive error checking is conducted on both the ground and airborne computers to prevent the development of potentially hazardous situations. Experience with the RAV monitoring and validation procedures is described.
Project Cassini is concerned with a potential collaborative mission to Saturn and Titan. The project has been the subject of a joint ESA/NASA Technical Assessment Study from April 1984 to July 1985. The spacecraft consists of a Saturn Orbiter and a Titan entry Probe. Science objectives with respect to Titan include a determination of the abundances of atmospheric constituents and isotope ratios, a study of the distribution of trace gases, cloud physics, and a determination of the state of the surface. Other science objectives are related to Saturn, the rings, icy satellites, the magnetosphere of Saturn, and asteroids. Attention is given to mission design, the spacecraft, and future prospects.
A new earth-crossing asteroid of the Aten type (orbit smaller than earth's) was discovered on August 30, 1984 at Palomar. The asteroid, designated 1984 QA, is the fourth known member of the Aten type and the first discovered since 1978. The discovery of this object was the highlight of a collaboration between the JPL Asteroid Search Team and an ESA scientist, and demonstrates one aspect of an ongoing joint search effort with other Schmidt observers.
The field of theoretical space physics offers a unique opportunity to Latin American scientists for collaborative participation in NASA programs where the greatly increased complexity of both experimental observations and theoretical simulations requires in-depth comparisons between theory and observational data. The key problem areas identified by NASA for aggressive work in the decade of the 1990s are the nature of flows and turbulence, acceleration and transport of particles, the coupling of microphysics and macrophysics, the coupling of local and global dynamics, and nonclassical plasmas.
A collaborative rain-observation experiment using an airborne rain radar was conducted between Communications Research Laboratory (CRL) and Goddard Space Flight Center (GSFC)/NASA. CRL provided an airborne rain-radar/radiometer system and GSFC/NASA provided a NASA P3-A aircraft. Airborne or spaceborne rain-radar echoes have large sea or land-surface echoes. These surface echoes yield rain-estimation algorithms using rain attenuation. The experiment demonstrated the potential of the rain-estimation techniques using rain attenuation.