Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates.

We assess which waters the Clean Water Act protects and how Supreme Court and White House rules change this regulation. We train a deep learning model using aerial imagery and geophysical data to predict 150,000 jurisdictional determinations from the Army Corps of Engineers, each deciding regulation for one water resource. Under a 2006 Supreme Court ruling, the Clean Water Act protects two-thirds of US streams and more than half of wetlands; under a 2020 White House rule, it protects less than half of streams and a fourth of wetlands, implying deregulation of 690,000 stream miles, 35 million wetland acres, and 30% of waters around drinking-water sources.

Research priorities for improving menstrual health across the life-course in low- and middle-income countries.

Background: Research on menstrual health is required to understand menstrual needs and generate solutions to improve health, wellbeing, and productivity. The identification of research priorities will help inform where to invest efforts and resources.

Objectives: To identify research priorities for menstrual health across the life-course, in consultation with a range of stakeholder groups from a variety of geographic regions, and to identify if menstrual health research priorities varied by expertise.

Valuing improvements in the ecological integrity of local and regional waters using the biological condition gradient.

Scientific knowledge related to quantifying the monetized benefits for landscape-wide water quality improvements does not meet current regulatory and benefit-cost analysis needs in the United States. In this study we addressed this knowledge gap by incorporating the Biological Condition Gradient (BCG) as a water quality metric into a stated preference survey capable of estimating the total economic value (use and nonuse) for aquatic ecosystem improvements. The BCG is grounded in ecological principles and generalizable and transferable across space.

Cas12a2 elicits abortive infection through RNA-triggered destruction of dsDNA.

Bacterial abortive-infection systems limit the spread of foreign invaders by shutting down or killing infected cells before the invaders can replicate. Several RNA-targeting CRISPR-Cas systems (that is, types III and VI) cause abortive-infection phenotypes by activating indiscriminate nucleases. However, a CRISPR-mediated abortive mechanism that leverages indiscriminate DNase activity of an RNA-guided single-effector nuclease has yet to be observed.

Positioning Diverse Type IV Structures and Functions Within Class 1 CRISPR-Cas Systems.

Type IV CRISPR systems encode CRISPR associated (Cas)-like proteins that combine with small RNAs to form multi-subunit ribonucleoprotein complexes. However, the lack of Cas nucleases, integrases, and other genetic features commonly observed in most CRISPR systems has made it difficult to predict type IV mechanisms of action and biological function. Here we summarize recent bioinformatic and experimental advancements that collectively provide the first glimpses into the function of specific type IV subtypes.

Menstrual health: a definition for policy, practice, and research.

The term "menstrual health" has seen increased use across advocacy, programming, policy, and research, but has lacked a consistent, self-contained definition. As a rapidly growing field of research and practice a comprehensive definition is needed to (1) ensure menstrual health is prioritised as a unified objective in global health, development, national policy, and funding frameworks, (2) elucidate the breadth of menstrual health, even where different needs may be prioritised in different sectors, and (3) facilitate a shared vocabulary through which stakeholders can communicate across silos to share learning. To achieve these aims, we present a definition of menstrual health developed by the Terminology Action Group of the Global Menstrual Collective.

Direct electromagnetic coupling for non-invasive measurements of stability in simulated fracture healing.

Diagnostic monitoring and prediction of bone fracture healing is critical for the detection of delayed union or non-union and provides the requisite information as to whether therapeutic intervention or timely revision are warranted. A promising approach to monitor fracture healing is to measure the mechanical load-sharing between the healing callus and the implanted hardware used for internal fixation. The objectives of this study were to evaluate a non-invasive measurement system in which an antenna electromagnetically couples with the implanted hardware to sense deflections of the hardware due to an applied load and to investigate the efficacy of the system to detect changes in mechanical load-sharing in an ex vivo fracture healing model.

Comparison of manual and automated image analysis techniques for characterization of fission gas pores in irradiated U-Mo fuels.

Irradiation of low enriched uranium-molybdenum fuel results in the production and agglomeration of fission gas bubbles that can potentially lead to fuel failure. Manual point volume fraction counting in accordance with ASTME562 standard has been historically used to conduct pore size distribution analysis. While effective, the manual methodology is not efficient and therefore not feasible for the characterization of several fuel plates in a timely manner.

The low but uncertain measured benefits of US water quality policy.

US investment to decrease pollution in rivers, lakes, and other surface waters has exceeded $1.9 trillion since 1960, and has also exceeded the cost of most other US environmental initiatives. These investments come both from the 1972 Clean Water Act and the largely voluntary efforts to control pollution from agriculture and urban runoff.

Air pollution and visitation at U.S. national parks.

Hundreds of millions of visitors travel to U.S. national parks every year to visit America's iconic landscapes.

Analysis and comparison of focused ion beam milling and vibratory polishing sample surface preparation methods for porosity study of U-Mo plate fuel for research and test reactors.

Uranium-Molybdenum (U-Mo) low enriched uranium (LEU) fuels are a promising candidate for the replacement of high enriched uranium (HEU) fuels currently in use in a high power research and test reactors around the world. Contemporary U-Mo fuel sample preparation uses focused ion beam (FIB) methods for analysis of fission gas porosity. However, FIB possess several drawbacks, including reduced area of analysis, curtaining effects, and increased FIB operation time and cost.