Explore the vast range of titles available.

The recently developed dual-phase (DP) non-equiatomic Fe 50 Mn 30 Co 10 Cr 10 (at.%) high-entropy alloy (HEA) showed much higher strength and ductility compared to the single-phase equiatomic Fe 20 Mn 20 Ni 20 Co 20 Cr 20 (at.%) HEA at room temperature. Herein we probe the cryogenic mechanical properties of the non-equiatomic DP-HEA with different grain sizes and compare with the equiatomic single-phase HEA. Our results show that the cryogenic ultimate tensile strengths of the coarse-grained (∼ 200 µm) and fine-grained (∼ 4 µm) DP-HEAs reach up to 1,133 and 1,342 MPa, respectively, which are significantly higher than that of the equiatomic single-phase HEAs with similar grain sizes. Furthermore, the fine-grained DP-HEA shows substantial improvement in both strength and ductility compared to the coarse-grained counterparts at cryogenic temperatures. Microstructural analysis reveals that the enhanced mechanical properties of the DP-HEA at cryogenic temperatures are attributed to a more extensive displacive transformation from the face-centered cubic (FCC) matrix into the hexagonal close-packed (HCP) phase compared to that at room temperature. Specifically, the HCP phase fraction in tensile tested fine-grained DP-HEAs increases from ∼ 39% to ∼ 79% with decreasing temperature from 298 to 77 K. The enhanced transformation behavior is enabled by the reduced stacking fault energy of the material with the decrease of deformation temperatures. The resulting outstanding combination of strength and ductility further suggests that the DP-HEAs are promising candidates as structural materials for cryogenic applications.

Summer streamflow variations strongly affect water supply reliability and ecological functioning of western U.S. (WUS) streams. Traditional snow‐based forecasts of summer streamflow are becoming less accurate with warming‐induced reductions in winter snow accumulation. This reflects a rising importance of competing runoff‐generating processes in controlling summer streamflow variations, primarily an increasing role of rainfall in contrast to snowmelt. Here, based on a snowmelt‐rainfall tracking algorithm applied to two hydrological models, we show that cool‐season rainfall provides an important volumetric contribution to summer streamflow for many WUS streams in the current climate, and this contribution will increase under climate warming, especially in years with warm snow droughts and abnormally dry summers. We also show that seasonal rainfall (warm‐/cool‐seasons) dominates the variability of summer streamflow across ∼70% area of WUS. We show that an increasing warm‐season rainfall contribution to summer streamflow (largely replacing snowmelt) results in reduced summer streamflow predictability. Plain Language Summary Summer streamflow is a critical water resource in the generally dry summers of the western U.S. (WUS), and is routinely forecasted using spring snowpack and/or winter total precipitation as primary predictors. However, climate warming leads to reduced snowpacks, exacerbates summer low flows, and reduces the accuracy of snow‐based summer streamflow forecasts. On the other hand, the role of winter rainfall as a control on summer streamflow increases in a warmer climate. Here, we explicitly quantify the contributions from cool‐season rainfall, warm‐season rainfall, and snowmelt to summer streamflow across the WUS, and how they change under a uniformly 1°C warmer climate. We show that the cool‐season rainfall contribution to summer streamflow increases under warming across WUS, especially in streams that currently have low‐to‐moderate snow contributions to runoff, and in years with anomalously warm winters and/or dry summers. We also show that the warm‐season rainfall contribution to summer streamflow increases widely, especially in the southern interior of WUS in a warmer climate, and that increasing warm‐season rainfall contribution to summer streamflow (largely replacing snowmelt) results in reduced summer streamflow predictability. Key Points The cool‐season rainfall contribution to summer streamflow is greatest in low‐elevation coastal streams with dry summers Climate warming leads to an increased contribution of seasonal rainfall to summer streamflow as spring snowmelt contributions decline Summer streamflow predictability declines with reduced snowmelt and increased warm‐season rainfall contribution in a warmer climate

The unluckiest star orbits a supermassive black hole elliptically. Every time it reaches the pericenter, it shallowly enters the tidal radius and gets partially tidally disrupted, producing a series of flares. Confirmation of a repeated partial tidal disruption event (pTDE) requires not only evidence to rule out other types of transients but also proof that only one star is involved, as TDEs from multiple stars can also produce similar flares. In this Letter, we report the discovery of a repeated pTDE, AT 2022dbl. In a quiescent galaxy at z = 0.0284, two separate optical/UV flares have been observed in 2022 and 2024 with no bright X-ray, radio, or mid-infrared counterparts. Compared to the first flare, the second flare has a similar blackbody temperature of ∼26,000 K, slightly lower peak luminosity, and slower rise and fall phases. Compared to the Zwicky Transient Facility TDEs, their blackbody parameters and light-curve shapes are all similar. The spectra taken during the second flare show a steeper continuum than the late-time spectra of the previous flare, consistent with a newly risen flare. More importantly, the possibility of two independent TDEs can be largely ruled out because the optical spectra taken around the peak of the two flares exhibit highly similar broad Balmer, N iii, and possible He ii emission lines, especially the extreme ∼4100 Å emission lines. This represents the first robust spectroscopic evidence for a repeated pTDE, which can soon be verified by observing the third flare, given its short orbital period.

Parkinson's disease (PD) has become the fastest-growing neurological disease worldwide. This network meta-analysis evaluated the efficacy of transcranial stimulation combined with four rehabilitation approaches for improving gait and motor function in Parkinson's disease. We systematically searched seven databases: PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wanfang. Data from 23 randomized controlled trials (  = 669 patients) were analyzed using a frequentist network meta-analysis approach. Primary outcomes included gait parameters (velocity, cadence, stride length) and motor function (Timed Up and Go test, Unified Parkinson's Disease Rating Scale Part III). Statistical analyses incorporated the Surface Under the Cumulative Ranking curve rankings and sensitivity analyses. (1) For gait outcomes, Dual-Task Training showed optimal efficacy for improving stride length (SUCRA = 100%) and velocity (86.5%), while Exercise Rehabilitation best improved cadence (100%). (2) For motor function, Conventional Rehabilitation demonstrated superior improvement in the Timed Up and Go test (100%), and Dual-Task Training showed advantages in Unified Parkinson's Disease Rating Scale Part III scores (85.1%). All combined interventions significantly outperformed the control groups (  < 0.05), and sensitivity analyses confirmed the robustness of these findings. The results support the use of personalized rehabilitation strategies: Dual-Task Training for patients with stride deficits and prominent motor symptoms, Exercise Rehabilitation for cadence improvement, and Conventional Rehabilitation for enhancing general mobility. These findings provide evidence-based guidance for optimizing neurorehabilitation protocols in the management of Parkinson's disease.

•Pearson correlation and PCA regression are optimized for structural covariance.•SA-CV has higher global and regional covariance similarity than CT-CV and CT-SA.•SA contributes more to CV covariance than CT.•Age and sex affect structural covariance and only age affects similarity. Structural covariance refers to the concurrent changes in one morphological measure between two brain regions. Structural covariance of cortical morphological measures such as cortical thickness (CT), surface area (SA), and cortical volume (CV) have been applied to identify brain structural differences between patients with neuropsychiatric disorders and healthy controls. However, the precise relationships between structural covariance patterns of different cortical measures remain largely unknown. Here, we optimized the preprocessing and calculation approaches of structural covariances and investigated both global (whole-brain-level) and regional (brain-region-level) structural covariance similarities between CT, SA, and CV in 35,580 individuals. We found that Pearson correlation outperformed partial correlation due to generating fewer negative correlations of uncertain biological significance and principal component regression outperformed the regressions of total intracranial volume and respective global measures in removing global effects and reducing negative correlations. We observed that both global and regional covariance similarities of SA-CV were much higher than those of CT-CV and CT-SA, although they were influenced by the selection of atlases and covariance values. We also found age and sex effects on structural covariances and age effects on covariance similarities. The higher SA-CV covariance similarities than CT-CV indicates that SA contributes more to CV covariance than CT, although CV is derived from both CT and SA. The lack of CT-SA covariance similarities suggests that CT and SA have different covariance patterns and should be used in combination in structural covariance studies.

Ulcerative colitis (UC) is an immune-related inflammatory bowel disease, with its underlying mechanisms being a central area of clinical research. O-GlcNAcylation plays a critical role in regulating immunity progression and the occurrence of inflammatory diseases and tumors. Yet, the mechanism of O-GlcNAc-associated colitis remains to be elucidated . To this end, the transcriptional and clinical data of GSE75214 and GSE92415 from the GEO database was hereby examined, and genes MUC1, ADAMTS1, GXYLT2, and SEMA5A were found to be significantly related to O-GlcNAcylation using machine learning methods. Based on the four hub genes, two UC subtypes were built. Notably, subtype B might be prone to developing colitis-associated colorectal cancer (CAC). This study delved into the role of intestinal glycosylation changes, especially the O-GlcNAcylation, and forged a foundation for further research on the occurrence and development of UC. Overall, understanding the role of O-GlcNAcylation in UC could have significant implications for diagnosis and treatment, offering valuable insights into the disease’s progression.

The fracture toughness and fatigue crack growth behavior of two as-vacuum arc cast high-entropy alloys (HEAs) (Al 0.2 CrFeNiTi 0.2 and AlCrFeNi 2 Cu) were determined. A microstructure examination of both HEA alloys revealed a two-phase structure consisting of body-centered cubic (bcc) and face-centered cubic (fcc) phases. The notched and fatigue precracked toughness values were in the range of those reported in the literature for two-phase alloys but significantly less than recent reports on a single phase fcc-HEA that was deformation processed. Fatigue crack growth experiments revealed high fatigue thresholds that decreased significantly with an increase in load ratio, while Paris law slopes exhibited metallic-like behavior at low R with significant increases at high R . Fracture surface examinations revealed combinations of brittle and ductile/dimpled regions at overload, with some evidence of fatigue striations in the Paris law regime.

Ongoing runoff declines in the Colorado River Basin have been shown to be predominately driven by decreasing albedo from warming‐driven snow‐cover loss, especially in late‐spring (hereafter snowmelt‐radiation feedback). Here, we explore the feedback's impact on annual runoff sensitivity to warming across the western U.S. (WUS) using hydrologic model simulations. For 1°C uniform warming, we show that runoff is most sensitive to warming in modestly snow‐covered, interior mountain headwaters, especially the Rocky Mountains. Runoff sensitivities are most associated with the snowmelt‐radiation feedback in basins with runoff coefficients between 0.2 and 0.6, where runoff sensitivity increases with more snow and lower winter temperature. In aggregate, ∼48% of WUS runoff sensitivity is attributable to the snowmelt‐radiation feedback and is especially pronounced in the warming‐sensitive river basins (annual runoff decreases >5%/°C). We also show that the feedback's impact decreases with increasing temperature, which has unresolved implications for streamflow declines in a less‐snow future. Plain Language Summary Regional climate warming is driving strong runoff changes in the western U.S. (WUS), especially the Upper Colorado River Basin (UCRB). Previous work showed that warming‐related snow cover reductions lead to more solar radiation absorption and evapotranspiration, which largely explain ongoing runoff declines in UCRB. Here, we assess the impact of this snowmelt‐radiation feedback on warming‐induced runoff changes across WUS. In a warmer world, we find that the largest annual runoff sensitivities are in the interior mountainous WUS with modest snow cover. The snowmelt‐radiation feedback explains over half of the warming‐induced runoff changes in warming‐sensitive WUS basins and about half of WUS' overall runoff sensitivity. In areas influenced by the snowmelt‐radiation feedback, both runoff sensitivity and the feedback's contribution become smaller with higher temperatures, suggesting a potentially slower rate of streamflow decline as temperatures rise in a warmer future. Key Points Snowmelt‐radiation feedback accounts for ∼1/2 of warming‐driven runoff decline across the Western U.S. (WUS) Runoff sensitivities are most linked to snowmelt‐radiation feedback in river basins with runoff coefficients in the range 0.2–0.6 Runoff sensitivities to warming are largest in modestly snow‐covered, interior mountainous parts of WUS, especially the Rocky Mountains

In this work, we investigated the mechanical behavior of a low-cost Zr51.9Cu23.3Ni10.5Al14.3 (at. %) metallic glass ribbon prepared with industrial-grade material through the melt-spinning method. The ribbons have good appearances and almost no defects. The mechanical behavior associated with the corresponding microstructure of the ribbon was tested at different strain rates. Striation and veining patterns were observed in the crack propagation zone and the fast fracture zone. The results show that the tensile strength of the ribbons exceeds 1 GPa. Therefore, they are considered to have good potential for industrial applications. This study could contribute to the preparation of low-cost bulk metallic glass.

Hydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS. Measurement(s) vegetation characteristics • soil characteristics • elevation Technology Type(s) satellite imaging • soil sampling • digital curation Factor Type(s) geographic location Sample Characteristic - Environment vegetation layer • soil Sample Characteristic - Location global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14869500