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At least 217 records · Page 12

Initial Fulcher band observations from high resolution spectroscopy in the MAST-U divertor

High resolution D$^*_2$ Fulcher band spectroscopy was used in the MAST-U divertors during Super-X and (shorter-legged) elongated divertor density ramps with D 2 fuelling from the mid-plane high-field side. In the Super-X case, the upper divertor showed ground state rotational temperatures of the D 2 molecules increasing from ~6000 K, starting at the detachment onset, to ~9000 K during deepening detachment. This was correlated with the movement of the Fulcher emission region towards the X-point, which is in turn correlated with the movement of the ionisation source. The increase in rotational temperature occurred throughout the divertor except near the divertor entrance, where ionisation was still the dominant process. Qualitative agreement was obtained between the lower and upper divertor. Similar rotational temperatures were obtained in the elongated divertor before the detachment onset, although the increase in rotational temperature during detachment was less clearly observed as less deep detachment was obtained. The measured vibrational distribution of the upper Fulcher state does not agree with a ground state Boltzmann distribution but shows a characteristically elevated population in the ν = 2 and ν = 3 bands in particular; which is strongly correlated to the rotational temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Analysis of thermal grooving effects on vortex penetration in vapor-diffused Nb 3 Sn

While Nb 3 Sn theoretically offers better superconducting radio-frequency (RF) cavity performance (Q 0 and E acc ) to Nb at any given temperature, peak RF magnetic fields consistently fall short of the ~400 mT prediction. The relatively rough topography of vapor-diffused Nb 3 Sn is widely conjectured to be one of the factors that limit the attainable performance of Nb 3 Sn-coated Nb cavities prepared via Sn vapor diffusion. Here we investigate the effect of coating duration on the topography of vapor-diffused Nb 3 Sn on Nb and calculate the associated magnetic field enhancement and superheating field suppression factors using atomic force microscopy topographies. It is shown that the thermally grooved grain boundaries are major defects which may contribute to a substantial decrease in the achievable accelerating field. Further, the severity of these grooves increases with total coating duration due to the deepening of thermal grooves during the coating process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generation and regulation of electromagnetic pulses induced by hybrid laser pulses interacting with solid targets

In inertial confinement fusion, electromagnetic pulses (EMPs) can be produced during high-power laser interacting with solid targets, which are intimately related to laser intensity and laser energy. In this study, EMPs generated by hybrid laser pulses coupling with targets are recorded and analyzed. The results indicate that a single picosecond laser gives birth to the most intense EMPs, but they are remarkably suppressed when a nanosecond laser-shooting target is triggered before the picosecond and femtosecond laser. One possible hypothesis is proposed based on x-rays inducing pre-ablation that generates pre-plasma at the surfaces of the picosecond target and femtosecond target, leading to a sharp drop both in the energy and number of the emitting hot electrons and protons. Here, the findings will deepen our understanding of the mechanism of EMPs' generation and will also open a new avenue to regulate EMPs by hybrid laser pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of physics results from MAST upgrade towards core-pedestal-exhaust integration

Recent results from MAST Upgrade are presented, emphasising understanding the capabilities of this new device and deepening understanding of key physics issues for the operation of ITER and the design of future fusion power plants. The impact of MHD instabilities on fast ion confinement have been studied, including the first observation of fast ion losses correlated with Compressional and Global Alfvén Eigenmodes. High-performance plasma scenarios have been developed by tailoring the early plasma current ramp phase to avoid internal reconnection events, resulting in a more monotonic q profile with low central shear. The impact of m/n = 3/2, 2/1 and 1/1 modes on thermal plasma confinement and rotation profiles has been quantified, and scenarios optimised to avoid them have transiently reached values of normalised beta approaching 4.2. In pedestal and ELM physics, a maximum pedestal top temperature of ~350 eV has been achieved, exceeding the value achieved on MAST at similar heating power. Mitigation of type-I ELMs with n = 1 RMPs has been observed. Studies of plasma exhaust have concentrated on comparing conventional and Super-X divertor configurations, while X-point target, X-divertor and snowflake configurations have been developed and studied in parallel. In L-mode discharges, the separatrix density required to detach the outer divertors is approximately a factor 2 lower in the Super-X than the conventional configuration, in agreement with simulations. Detailed analysis of spectroscopy data from studies of the Super-X configuration reveal the importance of including plasma-molecule interactions and D 2 Fulcher band emission to properly quantify the rates of ionisation, plasma-molecule interactions and volumetric recombination processes governing divertor detachment. In H-mode with conventional and Super-X configurations, the outer divertors are attached in the former and detached in the latter with no impact on core or pedestal confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Permafrost thermal conditions are sensitive to shifts in snow timing

Abstract Changes in snow precipitation at high latitudes can significantly affect permafrost thermal conditions and thaw depth, potentially exposing more carbon-laden soil to microbial decomposition. A fully coupled process-based surface/subsurface thermal hydrology model with surface energy balance is used to analyze the impact of intra-annual variability in snow on permafrost thermal regime and the active layer thickness. In the four numerical scenarios considered, simulations were forced by the same meteorological data, except the snow precipitation, which was systematically altered to change timing of snowfall. The scenarios represent subtle shifts in snow timing, but the snow onset/melt days, the end of winter snowpack depth, and total annual snow precipitation are unchanged among scenarios. The simulations show that small shifts in the timing of snow accumulation can have significant effects on subsurface thermal conditions leading to active layer deepening and even talik formation when snowfall arrives earlier in the winter. The shifts in snow timing have a stronger impact on wetter regions, especially soil underneath small ponds, as compared to drained regions. This study highlights the importance of understanding potential changes in winter precipitation patterns for reliable projections of active-layer thickness in a changing Arctic climate.

54 ENVIRONMENTAL SCIENCES↗

Changes in precipitation and air temperature contribute comparably to permafrost degradation in a warmer climate

Abstract Surface energy budgets of high-latitude permafrost systems are poorly represented in Earth system models (ESMs), yet permafrost is rapidly degrading and these dynamics are critical to future carbon-climate feedback predictions. A potentially important factor in permafrost degradation neglected so far by ESMs is heat transfer from precipitation, although increases in soil temperature and thaw depth have been observed following increases in precipitation. Using observations and a mechanistic ecosystem model, we show here that increases in precipitation hasten active layer development beyond that caused by surface air warming across the North Slope of Alaska (NSA) under recent and 21st century climate (RCP8.5). Modeled active layer depth (ALD) in simulations that allow precipitation heat transfer agreed very well with observations from 28 Circumpolar Active Layer Monitoring sites (R 2 = 0.63; RMSE = 10 cm). Simulations that ignored precipitation heat transfer resulted in lower spatially-averaged soil temperatures and a 39 cm shallower ALD by 2100 across the NSA. The results from our sensitivity analysis show that projected increases in 21st century precipitation deepen the active layer by enhancing precipitation heat transfer and ground thermal conductivity, suggesting that precipitation is as important an environmental control on permafrost degradation as surface air temperature. We conclude that ESMs that do not account for precipitation heat transfer likely underestimate ALD rates of change, and thus likely predict biased ecosystem responses.

54 ENVIRONMENTAL SCIENCES↗

Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

54 ENVIRONMENTAL SCIENCES↗

Human–Earth system interactions under climate change

This special issue, titled ‘Focus on human–Earth system interactions under climate change,’ compiles cutting-edge research that deepens our understanding of the complex feedback mechanisms between anthropogenic activities and Earth system processes in the context of a changing climate (figure 1). The featured articles employ a diverse array of methodologies—including field studies, remote sensing, modeling, and socio-ecological analyses—to explore these interconnections. A unifying theme across these contributions is the imperative to bridge disciplinary divides, integrating physical Earth sciences with social sciences to fully capture the spectrum of human-Earth system interactions. Key topics addressed the impacts of human activities on natural systems, encompassing land-use change and water resource management on biogeochemistry, climate dynamics, and feedback on the climate system and socioeconomics from local to global scales under a changing climate.

Li, Huidong [Vanderbilt Univ., Nashville, TN (Unit↗

Insights into the year-round vertical distribution of chlorophyll concentration in high-latitude Arctic Ocean: implications for primary production

Climate-induced rapid changes in the Arctic Ocean, such as decreasing sea ice extent and increasing water temperature, are altering nutrient and light availability, profoundly impacting primary producer growth. However, access to the high-latitude Arctic Ocean is limited, and satellite data are primarily available only during summer, making continuous in-situ data collection challenging. We collected year-round chlorophyll-a (Chl-a) concentration data in high-latitude regions using a mooring system and performed a comparative analysis with reanalysis data. Unlike previous satellite-based studies, which typically rely on surface measurements, we used the annual vertical distribution of Chl-a. These data were applied to the vertically generalized production model to accurately estimate annual primary production. The moored Chl-a concentration data showed that phytoplankton exhibited a typical subsurface chlorophyll maximum (SCM) layer as sea ice retreated in June. Contrary to the gradually deepening SCM distribution predicted by model-based reanalysis data, the SCM layer persisted for approximately 4 months. This indicates that light and nutrient conditions within the SCM layer remained stable, sustaining continuous phytoplankton growth. Annual primary production, reflecting this vertical distribution of Chl-a concentration, was 6.85 gC m −2 yr −1 . This exceeded satellite-based estimates by at least two-fold, highlighting the significant underestimation of primary production by satellite approaches. Estimating primary production while accounting for the vertical distribution of phytoplankton and light is essential for improving ecological models to better understand carbon cycle and food web changes in the Arctic Ocean, with important implications for climate change predictions.

Arctic Ocean↗

Exploring the energy landscape of RBMs: reciprocal space insights into bosons, hierarchical learning and symmetry breaking

Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationships among these models remain largely unexplored, a gap that hinders the development of a unified theory of AI learning. In this work, we address two central challenges: clarifying the connections between different deep generative models and deepening our understanding of their learning mechanisms. We focus on Restricted Boltzmann Machines (RBMs), a class of generative models known for their universal approximation capabilities for discrete distributions. By introducing a reciprocal space formulation for RBMs, we reveal a connection between these models, diffusion processes, and systems of coupled bosons. Our analysis shows that at initialization, the RBM operates at a saddle point, where the local curvature is determined by the singular values of the weight matrix, whose distribution follows the Marc̆enko-Pastur law and exhibits rotational symmetry. During training, this rotational symmetry is broken due to hierarchical learning, where different degrees of freedom progressively capture features at multiple levels of abstraction. This leads to a symmetry breaking in the energy landscape, reminiscent of Landau’s theory. This symmetry breaking in the energy landscape is characterized by the singular values and the weight matrix eigenvector matrix. We derive the corresponding free energy in a mean-field approximation. We show that in the limit of infinite size RBM, the reciprocal variables are Gaussian distributed. Our findings indicate that in this regime, there will be some modes for which the diffusion process will not converge to the Boltzmann distribution. To illustrate our results, we trained replicas of RBMs with different hidden layer sizes using the MNIST dataset. Our findings not only bridge the gap between disparate generative frameworks but also shed light on the fundamental processes underpinning learning in deep generative models.

97 MATHEMATICS AND COMPUTING↗

Vegetation heterogeneity reflects soil thermal state and surface soil displacement in a thawing permafrost landscape

Thawing permafrost has the potential to dramatically alter the physical and ecological structure of northern landscapes. Warming of the Arctic and subsequent degradation of permafrost have created a need to assess the stability and movement of soils on hillslopes and the potential impacts on ecosystem structure. In this work, we explore the relationships among vegetation heterogeneity, soil temperature, and soil surface displacements observed from 2019 to 2022 in a watershed in the discontinuous permafrost region on the Seward Peninsula of Alaska. Vegetation heterogeneity was measured as the standard deviation (SD) of the normalized difference vegetation index (NDVI) from 3 m PlanetScope satellite imagery around each soil temperature and active layer thickness observation. Locations of observations were clustered into three soil thermal groups, warm, intermediate, and cold, based on soil temperature and active layer thickness. Average annual horizontal surface displacements were significantly lower for soils within the warm thermal group (median = 0.033 m yr −1 ) compared to soils within the cold thermal group (median = 0.090 m yr −1 ; p < 0.001). Conversely, vegetation heterogeneity was significantly higher in the warm (median = 0.014 SD NDVI; p = 0.002) and intermediate (median = 0.015 SD NDVI; p = 0.002) groups compared with the cold thermal group (median = 0.012 SD NDVI), suggesting a warming-induced shift in vegetation community complexity. Because of the observed associations of ground surface displacement rates and vegetation heterogeneity with soil thermal state, we hypothesize that warming soil conditions induce changes in the rates and patterns of hillslope erosion due to an increase in surface movement as near-surface permafrost thaws, followed by a decrease as the permafrost table deepens and excess ice content diminishes. The transition to warm soils promotes surface ecosystem transformation, shifting the dominant vegetation at the site, given the warming climatic conditions of the region. We integrated our observations of soil temperature, vegetation heterogeneity, and soil surface displacements into a conceptual model that describes the co-evolution of hillslopes and vegetation in warming permafrost environments, which is currently unrepresented in earth system models.

54 ENVIRONMENTAL SCIENCES↗

Stoichiometric Ecotoxicology for a Multisubstance World

Nutritional and contaminant stressors influence organismal physiology, trophic interactions, community structure, and ecosystem-level processes; however, the interactions between toxicity and elemental imbalance in food resources have been examined in only a few ecotoxicity studies. Integrating well-developed ecological theories that cross all levels of biological organization can enhance our understanding of ecotoxicology. In the present article, we underline the opportunity to couple concepts and approaches used in the theory of ecological stoichiometry (ES) to ask ecotoxicological questions and introduce stoichiometric ecotoxicology, a subfield in ecology that examines how contaminant stress, nutrient supply, and elemental constraints interact throughout all levels of biological organization. This conceptual framework unifying ecotoxicology with ES offers potential for both empirical and theoretical studies to deepen our mechanistic understanding of the adverse outcomes of chemicals across ecological scales and improve the predictive powers of ecotoxicology.

60 APPLIED LIFE SCIENCES↗

Seismotectonic evidence for subduction beneath the Eastern Greater Caucasus

SUMMARY We generated high-resolution 3-D seismic velocity models as well as a relocated earthquake catalogue across the eastern Greater Caucasus and Kura basins. This work was done using data from the recently upgraded Republic Seismological Survey Center's (RSSC) seismic network. We generated our tomographic images of crustal velocity structure in Azerbaijan using double-difference inversions (i.e. tomoDD and hypoDD). Earthquake catalogues from the RSSC between 2011 and 2016 were used; these catalogues include absolute arrival times of 103 288 P- and 120 952 S-wave traveltime picks for 7574 events recorded at 35 stations in Azerbaijan. Beginning with a layered, 1-D velocity model that was estimated using VELEST, we inverted simultaneously for relative location, Vp and Vs on a 3-D grid with dimensions 670 × 445 × 45 km, with a uniform grid spacing of 55 × 55 × 5 km for all of Azerbaijan. We observe that the relocated hypocentres cluster into two depth ranges, at the surface and at depth, that appear to correspond to major fault zones and the top of a subducting plate. Additionally, we note intermediate depth seismicity (∼50–60 km) beneath the Kura Basin, and a northward deepening of earthquake depths. Seismic velocities vary significantly throughout the study region; we observe very slow velocities throughout the Kura Basin between 5 and 15 km, and elevated velocities at 20–35 km. The wholesale velocity structure and seismic structure of Kura Basin strongly mirrors that of the Caspian Sea, which suggests that the geodynamics of the Caspian continue westwards into Azerbaijan. The key results of this study suggest that the northward subduction observed in the Caspian Sea continues beneath the Eastern Greater Caucasus, as well as provides evidence for active faulting along the southern margin of the mountain range.

Gunnels, Michael↗

High-resolution Bayesian spatial autocorrelation (SPAC) quasi-3-D Vs model of Utah FORGE site with a dense geophone array

SUMMARY We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2–5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ∼22° to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity.

Geochemistry & Geophysics↗

The stellar parameters and elemental abundances from low-resolution spectra – I. 1.2 million giants from LAMOST DR8

As a typical data-driven method, deep learning becomes a natural choice for analysing astronomical data. In this study, we built a deep convolutional neural network (NN) to estimate basic stellar parameters $T\rm {_{eff}}$, log g , metallicity ([M/H] and [Fe/H]) and [α/M] along with nine individual elemental abundances ([C/Fe], [N/Fe], [O/Fe], [Mg/Fe], [Al/Fe], [Si/Fe], [Ca/Fe], [Mn/Fe], and [Ni/Fe]). The NN is trained using common stars between the APOGEE survey and the LAMOST survey. We used low-resolution spectra from LAMOST survey as input, and measurements from APOGEE as labels. For stellar spectra with the signal-to-noise ratio in g band larger than 10 in the test set, the mean absolute error (MAE) is 29 K for $T\rm {_{eff}}$, 0.07 dex for log g , 0.03 dex for both [Fe/H] and [M/H], and 0.02 dex for [α/M]. The MAE of most elements is between 0.02 and 0.04 dex. The trained NN was applied to 1210 145 giants, including sub-giants, from LAMOST DR8 within the range of stellar parameters 3500 K < $T\rm {_{eff}}$ < 5500 K, 0.0 dex < log g < 4.0 dex, −2.5 dex < [Fe/H] < 0.5 dex. The distribution of our results in the chemical spaces is highly consistent with APOGEE labels and stellar parameters show consistency with external high-resolution measurements from GALAH. The results in this study allow us to further studies based on LAMOST data and deepen our understanding of the accretion and evolution history of the Milky Way. The electronic version of the value added catalog is available at http://www.lamost.org/dr8/v1.1/doc/vac.

79 ASTRONOMY AND ASTROPHYSICS↗

Interaction of N-methylmesoporphyrin IX with a hybrid left-/right-handed G-quadruplex motif from the promoter of the SLC2A1 gene

Abstract Left-handed G-quadruplexes (LHG4s) belong to a class of recently discovered noncanonical DNA structures under the larger umbrella of G-quadruplex DNAs (G4s). The biological relevance of these structures and their ability to be targeted with classical G4 ligands is underexplored. Here, we explore whether the putative LHG4 DNA sequence from the SLC2A1 oncogene promoter maintains its left-handed characteristics upon addition of nucleotides in the 5′- and 3′-direction from its genomic context. We also investigate whether this sequence interacts with a well-established G4 binder, N-methylmesoporphyrin IX (NMM). We employed biophysical and X-ray structural studies to address these questions. Our results indicate that the sequence d[G(TGG)3TGA(TGG)4] (termed here as SLC) adopts a two-subunit, four-tetrad hybrid left-/right-handed G4 (LH/RHG4) topology. Addition of 5′-G or 5′-GG abolishes the left-handed fold in one subunit, while the addition of 3′-C or 3′-CA maintains the original fold. X-ray crystal structure analyses show that SLC maintains the same hybrid LH/RHG4 fold in the solid state and that NMM stacks onto the right-handed subunit of SLC. NMM binds to SLC with a 1:1 stoichiometry and a moderate-to-tight binding constant of 15 μM−1. This work deepens our understanding of LHG4 structures and their binding with traditional G4 ligands.

Seth, Paul↗

Mechanistic studies of small molecule ligands selective to RNA single G bulges

Abstract Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated molecular dynamics simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity relationship studies and transverse relaxation measurements by nuclear magnetic resonance spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Our work deepened the understanding of RNA-small molecule interactions and integrated a new framework for the rational design of selective small-molecule RNA binders.

Biochemistry & Molecular Biology↗

The spread of technological innovations: effects of psychology, culture and policy interventions

Technological innovations drive the evolution of human societies. The success of innovations depends not only on their actual benefits but also on how potential adopters perceive them and how their beliefs are affected by their social and cultural environment. To deepen our understanding of socio-psychological processes affecting the new technology spread, we model the joint dynamics of three interlinked processes: individual learning and mastering the new technology, changes in individual attitudes towards it, and changes in individual adoption decisions. We assume that the new technology can potentially lead to a higher benefit but achieving it requires learning. We posit that individual decision-making process as well as their attitudes are affected by cognitive dissonance and conformity with peers and an external authority. Individuals vary in different psychological characteristics and in their attitudes. We investigate both transient dynamics and long-term equilibria observed in our model. We show that early adopters are usually individuals who are characterized by low cognitive dissonance and low conformity with peers but are sensitive to the effort of an external authority promoting the innovation. We examine the effectiveness of five different intervention strategies aiming to promote the diffusion of a new technology: training individuals, providing subsidies for early adopters, increasing the visibility of peer actions, simplifying the exchange of opinions between people, and increasing the effort of an external authority. We also discuss the effects of culture on the spread of innovations. Finally, we demonstrate that neglecting the cognitive forces and the dynamic nature of individual attitudes can lead to wrong conclusions about adoption of innovations. Our results can be useful in developing more efficient policies aiming to promote the spread of new technologies in different societies, cultures and countries.

99 GENERAL AND MISCELLANEOUS↗