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Abstract Next-generation gravitational wave detectors such as Cosmic Explorer, the Einstein Telescope, and LISA, demand highly accurate and extensive gravitational wave (GW) catalogs to faithfully extract physical parameters from observed signals. However, numerical relativity (NR) faces significant challenges in generating these catalogs at the required scale and accuracy on modern computers, as NR codes do not fully exploit modern GPU capabilities. In response, we extend NRPy, a Python-based NR code-generation framework, to develop NRPyEllipticGPU—a CUDA-optimized elliptic solver tailored for the binary black hole (BBH) initial data problem. NRPyEllipticGPU is the first GPU-enabled elliptic solver in the NR community, supporting a variety of coordinate systems and demonstrating substantial performance improvements on both consumer-grade and HPC-grade GPUs. We show that, when compared to a high-end CPU, NRPyEllipticGPU achieves on a high- end GPU up to a sixteenfold speedup in single precision while increasing double- precision performance by a factor of 2–4. This performance boost leverages the GPU’s superior parallelism and memory bandwidth to achieve a compute-bound application and enhancing the overall simulation efficiency. As NRPyEllipticGPU shares the core infrastructure common to NR codes, this work serves as a practical guide for developing full, CUDA-optimized NR codes. 

Nuclear actin has been implicated in regulating cell fate, differentiation, and cellular reprogramming. However, its roles in development and tissue homeostasis remain largely unknown. Here we uncover the role of nuclear actin in regulating stemness usingDrosophilaovarian germline stem cells (GSCs) as a model. We find that the localization and structure of nuclear actin is dynamic in the early germ cells. Nuclear actin recognized by anti-actin C4 is found in both the nucleoplasm and nucleolus of GSCs. The polymeric nucleoplasmic C4 pool is lost after the 2-cell stage, whereas the monomeric nucleolar pool persists to the 8-cell stage, suggesting that polymeric nuclear actin may contribute to stemness. To test this idea, we overexpressed nuclear targeted actin constructs to alter nuclear actin polymerization states in the GSCs and early germ cells. Increasing monomeric nuclear actin, but not polymerizable nuclear actin, causes GSC loss that ultimately results in germline loss. This GSC loss is rescued by simultaneous overexpression of monomeric and polymerizable nuclear actin. Together these data reveal that GSC maintenance requires polymeric nuclear actin. This polymeric nuclear actin likely plays numerous roles in the GSCs, as increasing monomeric nuclear actin disrupts nuclear architecture causing nucleolar hypertrophy, distortion of the nuclear lamina, and heterochromatin reorganization; all factors critical for GSC maintenance and function. These data provide the first evidence that nuclear actin, and in particular, its ability to polymerize, are critical for stem cell function and tissue homeostasisin vivo. 

The Sava River Basin (SRB) includes six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro), with the Sava River (SR) being a major tributary of the Danube River. The SR originates in the mountains (European Alps) of Slovenia and, because of a recent Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including hydropower (energy production), information about past (paleo) dry (drought) and wet (pluvial) periods would provide important information to water managers and planners. Recent research applying traditional regression techniques and methods developed skillful reconstructions of seasonal (April–May–June–July–August–September or AMJJAS) streamflow using tree-ring-based proxies. The current research intends to expand upon these recent research efforts and investigate developing reconstructions of seasonal (AMJJAS) precipitation applying novel Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques. When comparing the reconstructed AMJJAS precipitation datasets, the AI/ML/DL techniques statistically outperformed traditional regression techniques. When comparing the SRB AMJJAS precipitation reconstruction developed in this research to the SRB AMJJAS streamflow reconstruction developed in previous research, the temporal variability of the two reconstructions compared favorably. However, pluvial magnitudes of extreme periods differed, while drought magnitudes of extreme periods were similar, confirming drought is likely better captured in tree-ring-based proxy reconstructions of hydrologic variables. 

The Po River Basin (PRB) is Italy’s largest river system and provides a vital water supply source for varying demands, including agriculture, energy (hydropower), and water supply. The current (2022) drought has been associated with low winter–early spring (2021–2022) snow accumulation in higher elevations (European Alps) and a lack of late spring–early summer (2022) precipitation, resulting in deficit PRB streamflow. Many local scientists are now estimating a 50- to 100-year (return period) drought for 2022. Given the importance of this river system, information about past (paleo) drought and pluvial periods would provide important information to water managers and planners. Annual streamflow data were obtained for thirteen gauges that were spatially located across the PRB. The Old World Drought Atlas (OWDA) provides annual June–July–August (JJA) self-calibrating Palmer Drought Severity Index (scPDSI) data for 5414 grid points across Europe from 0 to 2012 AD. In lieu of tree-ring chronologies, this dataset was used as a proxy to reconstruct PRB regional streamflow. Singular value decomposition (SVD) was applied to PRB streamflow gauges and gridded scPDSI data for two periods of record, referred to as the short period of record (SPOR), 1980 to 2012 (33 years), and the long period of record (LPOR), 1967 to 2012 (46 years). SVD serves as both a data reduction technique, identifying significant scPDSI grid points within the selected 450 km search radius, and develops a single vector that represents the regional PRB streamflow variability. Due to the high intercorrelations of PRB streamflow gauges, the SVD-generated PRB regional streamflow vector was used as the dependent variable in regression models for both the SPOR and LPOR, while the significant scPDSI grid points (cells) identified by SVD were used as the independent variables. This resulted in two highly skillful regional reconstructions of PRB streamflow from 0 to 2012. Multiple drought and pluvial periods were identified in the paleo record that exceed those observed in the recent historical record, and several of these droughts aligned with paleo streamflow reconstructions of neighboring European watersheds. Future research will utilize the PRB reconstructions to quantify the current (2022) drought, providing a first-time paleo-perspective of drought frequency in the watershed. 

Prostaglandins (PGs), locally acting lipid signals, regulate female reproduction, including oocyte development. However, the cellular mechanisms of PG action remain largely unknown. One cellular target of PG signaling is the nucleolus. Indeed, across organisms, loss of PGs results in misshapen nucleoli, and changes in nucleolar morphology are indicative of altered nucleolar function. A key role of the nucleolus is to transcribe ribosomal RNA (rRNA) to drive ribosomal biogenesis. Here we take advantage of the robust, in vivo system of Drosophila oogenesis to define the roles and downstream mechanisms whereby PGs regulate the nucleolus. We find that the altered nucleolar morphology due to PG loss is not due to reduced rRNA transcription. Instead, loss of PGs results in increased rRNA transcription and overall protein translation. PGs modulate these nucleolar functions by tightly regulating nuclear actin, which is enriched in the nucleolus. Specifically, we find that loss of PGs results in both increased nucleolar actin and changes in its form. Increasing nuclear actin, by either genetic loss of PG signaling or overexpression of nuclear targeted actin (NLS-actin), results in a round nucleolar morphology. Further, loss of PGs, overexpression of NLS-actin or loss of Exportin 6, all manipulations that increase nuclear actin levels, results in increased RNAPI-dependent transcription. Together these data reveal PGs carefully balance the level and forms of nuclear actin to control the level of nucleolar activity required for producing fertilization competent oocytes. 

The Apalachicola–Chattahoochee–Flint (ACF) basin is arguably the most litigated interstate river system in the eastern United States. Given the complicated demands for water use within this basin, it has been difficult to ascertain if the recent multi-decadal decline in streamflow is a product of human disturbance, changing climate, natural variability, or some combination of the above factors. To overcome these challenges, we examined unimpaired streamflow and precipitation within and adjacent to the ACF basin, upstream of the Apalachicola River at Chattahoochee, and the Florida streamflow station (ARCF), which has historically been identified to be representative of hydrologic variability in the ACF basin. Several of the upstream, unimpaired, streamflow stations selected were identified in rural watersheds where land-cover changes and human disturbance were minimal during the study period. When applying a series of statistical evaluations, ARCF streamflow variability generally reflects the natural variability of the ACF basin. Additionally, unimpaired streamflow variability from the neighboring Choctawhatchee River compared favorably with ARCF variability. The recent multi-decadal decline was consistent in all records, with the 2000s being the most severe in the historic record. 

The Adige River Basin (ARB) provides a vital water supply source for varying demands including agriculture (wine production), energy (hydropower) and municipal water supply. Given the importance of this river system, information about past (paleo) drought and pluvial (wet) periods would quantity risk to water managers and planners. Annual streamflow data were obtained for four gauges that were spatially located within the upper ARB. The Old World Drought Atlas (OWDA) provides an annual June–July–August (JJA) self-calibrating Palmer Drought Severity Index (scPDSI) derived from 106 tree-ring chronologies for 5414 grid points across Europe from 0 to 2012 AD. In lieu of tree-ring chronologies, the OWDA dataset was used as a proxy to reconstruct both individual gauge and ARB regional streamflow from 0 to 2012. Principal component analysis (PCA) was applied to the four ARB streamflow gauges to generate one representative vector of regional streamflow. This regional streamflow vector was highly correlated with the four individual gauges, as coefficient of determination (R2) values ranged from 85% to 96%. Prescreening methods included correlating annual streamflow and scPDSI cells (within a 450 km radius) in which significant (p ≤ 0.01 or 99% significance) scPDSI cells were identified. The significant scPDSI cells were then evaluated for temporal stability to ensure practical and reliable reconstructions. Statistically significant and temporally stable scPDSI cells were used as predictors (independent variables) to reconstruct streamflow (predictand or dependent variable) for both individual gauges and at the regional scale. This resulted in highly skillful reconstructions of upper ARB streamflow from 0 to 2012 AD. Multiple drought and pluvial periods were identified in the paleo record that exceed those observed in the recent, historic record. Moreover, this study concurred with streamflow reconstructions in nearby European watersheds. 

Seasonal reconstructions of streamflow are valuable because they provide water planners, policy makers, and stakeholders with information on the range and variability of water resources before the observational period. In this study, we used streamflow data from five gages near the Alabama-Florida border and centuries-long tree-ring chronologies to create and analyze seasonal flow reconstructions. Prescreening methods included correlation and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that several regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with March–October streamflow, and stepwise linear regression was used to create the reconstructions. Reconstructions spanned 1203–1985, 1652–1983, 1725–1993, 1867–2011, and 1238–1985 for the Choctawhatchee, Conecuh, Escambia, Perdido, and Pascagoula Rivers, respectively, all of which were statistically skillful (R2 ≥ 0.50). The reconstructions were statistically validated using the following parameters: R2 predicted validation, the sign test, the variance inflation factor (VIF), and the Durbin–Watson (D–W) statistic. The long-term streamflow variability was analyzed for the Choctawhatchee, Conecuh, Escambia, and Perdido Rivers, and the recent (2000s) drought was identified as being the most severe in the instrumental record. The 2000s drought was also identified as being one of the most severe droughts throughout the entire reconstructed paleo-record developed for all five rivers. This information is vital for the consideration of present and future conditions within the system. 

In this paper, we evaluate the impacts of historic strong El Niño events on the coastal Mississippi-Alabama (MS-AL) hydroclimate. The normal physical association is that the increase in soil moisture, as a result of greater precipitation, is also associated with increased streamflow. When compared to the historic (1960–2015) long-term average, January through August streamflow volumes for five unimpaired streamflow gages located in coastal MS-AL exhibit an average increase of ~20% following a strong El Niño event. This overall increase was due to above-average precipitation during the winter-spring (January through April) season, with the corresponding average increase in streamflow volume for the five gages ~32%. In evaluating the temporal (monthly) variability of streamflow, we observe that the summer (June through August) season was dry following strong El Niño events, with streamflow volumes for the five gages decreasing by an average of ~21%. The agricultural industry in coastal MS-AL produces a variety of crops including cotton and peanuts. The typical planting season for these crops ends in mid-June with harvesting occurring in early September. Thus, the primary growing season for these crops is June–August. Given the lack of impoundments and irrigated lands in coastal MS-AL, the agricultural sector would be severely impacted by an El Niño driven drier summer. When evaluating the influence of the 2015–2016 El Niño on January through August 2016 streamflow, a similar pattern was observed in which high winter–spring streamflow was followed by diminished summer streamflow. 

This study reports the preliminary results from a statistical screening of tree-ring width records from the International Tree-Ring Data Bank (ITRDB), to evaluate the strength of the hydrological signal, in dendrochronological records from the Tennessee Valley. We used United States Geological Survey (USGS) streamflow data from 11 gages, within the Tennessee Valley, and regional tree-ring chronologies, to analyze the dendroclimatic potential of the region, and create seasonal flow reconstructions. Prescreening methods included correlation, date, and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that large numbers of regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with the May–June–July streamflow. Stepwise linear regression was used to create the May–June–July streamflow reconstructions. Ten of the 12 streamflow stations were considered statistically skillful (R2 ≥ 0.40). Skillful reconstructions ranged from 208 to 301 years in length, and were statistically validated using leave-one-out cross validation, the sign test, and a comparison of the distribution of low flow years. The long-term streamflow variability was analyzed for the Nolichucky, Nantahala, Emory, and South Fork (SF) Holston stations. The reconstructions revealed that while most of the Western United States (U.S.). was experiencing some of its highest flow years during the early 1900s, the Tennessee Valley region was experiencing a very low flow. Results revealed the potential benefit of using tree-ring chronologies to reconstruct hydrological variables in the Southeastern U.S., by demonstrating the ability of proxy-based reconstructions to provide useful data beyond the instrumental record.