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At least 505 records · Page 28

Planning for Resilient Power Distribution Systems using Risk-Based Quantification and Q-Learning

Grid hardening is one of the most effective approaches that reduce the component failures and restoration efforts thus increasing the resilience of the power systems against extreme events. However, hardening and upgrading the entire system is prohibitively expensive and hence the optimal design of a distribution network is challenging. This paper adopted a reinforcement learning algorithm to identify the optimal hardening strategy to enhance the resilience of power distribution systems. Adopting the Q-learning algorithm as the reinforcement learning technique, we found the sequential optimal action for hardening measures to enhance the grid's resilience for the given budget. To identify the optimal strategy through Q-learning, Conditional Value at Risk (CVaR) is used as a rewarding metric. A study on the IEEE 123-bus test feeder validate the effectiveness of the proposed model and show how to effectively allocate budget limited resources to plan a resilient power distribution network.

Paul, Shuva↗

Dielectron production at midrapidity at low transverse momentum in peripheral and semi-peripheral Pb–Pb collisions at ${\sqrt{s}}_{\textrm{NN}}$ = 5.02 TeV

The first measurement of the e + e – pair production at low lepton pair transverse momentum (p T,ee ) and low invariant mass (m ee ) in non-central Pb–Pb collisions at ${\sqrt{s}}_{\textrm{NN}}$ = 5.02 TeV at the LHC is presented. The dielectron production is studied with the ALICE detector at midrapidity (|η e | < 0.8) as a function of invariant mass (0.4 ≤ m ee < 2.7 GeV/c 2 ) in the 50–70% and 70–90% centrality classes for p T,ee < 0.1 GeV/c, and as a function of p T,ee in three m ee intervals in the most peripheral Pb–Pb collisions. Below a p T,ee of 0.1 GeV/c, a clear excess of e + e – pairs is found compared to the expectations from known hadronic sources and predictions of thermal radiation from the medium. The m ee excess spectra are reproduced, within uncertainties, by different predictions of the photon–photon production of dielectrons, where the photons originate from the extremely strong electromagnetic fields generated by the highly Lorentz-contracted Pb nuclei. Lowest-order quantum electrodynamic (QED) calculations, as well as a model that takes into account the impact-parameter dependence of the average transverse momentum of the photons, also provide a good description of the p T,ee spectra. The measured $\sqrt{\left\langle {p}_{\textrm{T},\textrm{ee}}^2\right\rangle }$ of the excess p T,ee spectrum in peripheral Pb–Pb collisions is found to be comparable to the values observed previously at RHIC in a similar phase-space region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effects of Desiccation and Freezing on Microbial Ionizing Radiation Survivability: Considerations for Mars Sample Return

Increasingly, national space agencies are expanding their goals to include Mars exploration with sample return. To better protect Earth and its biosphere from potential extraterrestrial sources of contamination, as set forth in the Outer Space Treaty of 1967, international efforts to develop planetary protection measures strive to understand the danger of cross-contamination processes in Mars sample return missions. We aim to better understand the impact of the martian surface on microbial dormancy and survivability. Radiation resistance of microbes is a key parameter in considering survivability of microbes over geologic times on the frigid, arid surface of Mars that is bombarded by solar and galactic cosmic radiation. We tested the influence of desiccation and freezing on the ionizing radiation survival of six model microorganisms: vegetative cells of two bacteria (Deinococcus radiodurans, Escherichia coli) and a strain of budding yeast (Saccharomyces cerevisiae); and vegetative cells and endospores of three Bacillus bacteria (B. subtilis, B. megaterium, B. thuringiensis). Desiccation and freezing greatly increased radiation survival of vegetative polyploid microorganisms when applied separately, and when combined, desiccation and freezing increased radiation survival even more so. Thus, the radiation survival threshold of polyploid D. radiodurans cells can be extended from the already high value of 25 kGy in liquid culture to an astonishing 140 kGy when the cells are both desiccated and frozen. However, such synergistic radioprotective effects of desiccation and freezing were not observed in monogenomic or digenomic Bacillus cells and endospores, which are generally sterilized by 12 kGy. This difference is associated with a critical requirement for survivability under radiation, that is, repair of genome damage caused by radiation. Deinococcus radiodurans and S. cerevisiae accumulate similarly high levels of the Mn antioxidants that are required for extreme radiation resistance, as do endospores, though they greatly exceed spores in radioresistance because they contain multiple identical genome copies, which in D. radiodurans are joined by persistent Holliday junctions. We estimate ionizing radiation survival limits of polyploid DNA-based life-forms to be hundreds of millions of years of background radiation while buried in the martian subsurface. Our findings imply that forward contamination of Mars will essentially be permanent, and backward contamination is a possibility if life ever existed on Mars.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding Resilience Valuation for Energy Systems: An Overview of the NREL-NYSERDA Research Collaboration

Energy resilience has become a national priority as Americans experience more power outages attributed to climate change, extreme weather, and cyber events. Energy system owners and operators recognize that they must prepare differently for outages today than they did in the past. Decision makers at all levels face unique challenges and opportunities in effectively and equitably executing a transition to more resilient power systems. The New York State Energy Research and Development Authority (NYSERDA) recently added resilience to its mission statement. The authority engaged with the National Renewable Energy Laboratory (NREL) in a collaborative effort to: 1) understand options for measuring and valuing resilience investment benefits, and 2) inform how resilience could be operationalized across NYSERDA initiatives and program areas.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Looking at supersymmetric black holes for a very long time

We study correlation functions for extremal supersymmetric black holes. It is necessary to take into account the strongly coupled nature of the boundary supergraviton mode. We consider the case with {\cal N}=2 supercharges which is the minimal amount of supersymmetry needed to give a large ground state degeneracy, separated from the continuum. Using the exact solution for this theory we derive formulas for the two point function and we also give integral expressions for any n n -point correlator. These correlators are time independent at large times and approach constant values that depend on the masses and couplings of the bulk theory. We also explain that in the non-supersymmetric case, the correlators develop a universal time dependence at long times. This paper is the longer companion paper of arXiv:2207.00407.

79 ASTRONOMY AND ASTROPHYSICS↗

Scalable electrified cementitious materials production and recycling

The production of Portland cement, the industry-standard cement, contributes ~8% of global CO 2 emissions through fossil-fuel heating and decomposition of limestone (the primary cement raw material). Decarbonization, e.g., via direct electrification, of this 200-year-old liming routine is extremely challenging at the industry scale. We propose a scalable electrochemical decarbonization approach to circumvent the limestone use by switching to carbon-free calcium silicates from abundant minerals and recycled concrete. Water electrolysis produces protons and hydroxides to drive a pH gradient that accelerates Ca 2+ ion leaching from calcium silicates and captures atmospheric CO 2 to form carbon-negative CaCO 3 , which serves as the feedstock for cement manufacturing or as the carbon-mineralized product for cement substitution with permanent carbon storage. Value-added co-products amorphous silica and green H 2 further enhance cement performance and supplant fossil fuels for net-zero transition, respectively. The products readily meet present-day regulatory standards and demands, and the approach readily synergizes with business-as-usual cement manufacturing and concrete construction, which are important for upscaling and structural safety, promising ready reception by the public and industries. Blended Portland cement produced through our approach with carbon-negative CaCO 3 and silica demonstrates enhanced resilience and achieves carbon neutrality or negativity when incorporating storage or circulation of CO 2 from cement plant flue gas, respectively. This low-cost, electrochemical cement production approach using abundant ubiquitous raw materials enables electrification, transition to clean fuel, and decarbonization at a gigaton scale.

36 MATERIALS SCIENCE↗

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗

Gamma-radiation-induced negative nonlinear absorption in quartz glass

The effect of ionizing radiation on the nonlinear optical properties of materials needs to be considered for applications that employ high-power laser pulses in extreme radiation environments. The Heraeus Infrasil302 optical quartz glass was irradiated by gamma rays, and its nonlinear absorption was measured using the open-aperture Z-scan technique with nanosecond laser pulses. Irradiation results in a negative nonlinear absorption coefficient whose magnitude increases with irradiation dose. Nonlinear absorption coefficients of -0.78, -1.14, -1.29, and -1.88~ × ~10 -13 m/W are measured for gamma doses of 600 krad, 1.2 Mrad, 3.6 Mrad, and 10 Mrad, respectively. Thermal annealing restores the optical properties of quartz-glass to their unirradiated values. It is suggested that metallic impurities introduced by the manufacturing process have a role in inducing saturated absorption in irradiated quartz glass, which manifests as negative nonlinear absorption coefficient, and is demonstrated by comparing Infrasil302 quartz results to equivalent irradiated measurements for Spectrosil2000 quartz.

07 ISOTOPE AND RADIATION SOURCES↗

Transforming ESM Physical Parameterization Development Using Machine Learning Trained on Global Cloud-Resolving Models and Process Observations

ESMs robustly predict that 21st century greenhouse warming will slowly increase global mean precipitation, rapidly increase extreme precipitation, and increase subtropical drought. ESMs agree less about precipitation trends and extremes over particular land regions critical to human societies, e. g. in semi-arid regions such as California or the Sahel, or in wetter climates prone to monsoonal rainfall (e. g. southeast Asia) or to tropical cyclones and flooding from mesoscale convective systems (e. g. the southeastern U.S.) Deep convective parameterizations and poor representation of orography and complex vegetated land surfaces contribute to this inter-model spread; clouds, aerosols and sea-surface temperature biases are also key. Reducing regional precipitation projection uncertainty has enormous planning value for water supplies, land use, wildfire, hydropower, flood control, etc. IPCC-class ESMs are making painfully slow progress on this.

54 ENVIRONMENTAL SCIENCES↗

Variable Resource Resilience: How Systems Experience Increased Resilience from Variable and Hybrid Resources

Variable resources like wind and solar are often seen as detriments to system resilience rather than benefits because they may not be available with the capacities or services required during a high-impact low-frequency (HILF) event, whether that is a physical threat, natural disaster, or cyber attack. However, resilience goals and metrics are inadequate for electric energy delivery systems with inverter-based resources. Examination of this topic reveals that renewable resources are well suited to combat many resilience hazards due to local resource availability. Metrics that demonstrate the resilience value of variable resources are presented and categorized for resource (wind, solar, storage, hybrid) and installation type (bulk utility scale, behind-the-meter, front-of-the-meter, isolated). Distributed and hybrid systems can further enhance resilience benefits my maximizing resource potential for a locality. A case study demonstrating quantitative resilience benefits from wind alone is provided for St. Mary's, AK, which concludes that hundreds of thousands of dollars are saved by the addition of a wind turbine in the face of realistic fuel shortage and extreme winter weather scenarios.

17 WIND ENERGY↗

Intense windstorms in the northeastern United States

Abstract. Windstorms are a major natural hazard in many countries. The objective of this study is to identify and characterize intense windstorms during the last 4 decades in the US Northeast and determine both the sources of cyclones responsible for these events and the manner in which those cyclones differ from the cyclone climatology. The windstorm detection is based on the spatial extent of locally extreme wind speeds at 100 m height from the ERA5 reanalysis database. During the top 10 windstorms, wind speeds exceed their local 99.9th percentile over at least one-third of land-based ERA5 grid cells in this high-population-density region of the USA. Maximum sustained wind speeds at 100 m during these windstorms range from 26 to over 43 ms−1, with wind speed return periods exceeding 6.5 to 106 years (considering the top 5 % of grid cells during each storm). Property damage associated with these storms, with inflation adjusted to January 2020, ranges from USD 24 million to over USD 29 billion. Two of these windstorms are linked to decaying tropical cyclones, three are Alberta clippers, and the remaining storms are Colorado lows. Two of the 10 re-intensified off the east coast, leading to development of nor'easters. These windstorms followed frequently observed cyclone tracks but exhibit maximum intensities as measured using 700 hPa relative vorticity and mean sea level pressure that is 5–10 times the mean values for cyclones that followed similar tracks over this 40-year period. The time evolution of wind speeds and concurrent precipitation for those windstorms that occurred after the year 2000 exhibit good agreement with in situ ground-based and remote sensing observations, plus storm damage reports, indicating that the ERA5 reanalysis data have a high degree of fidelity for large, damaging windstorms such as these. A larger pool of the top 50 largest windstorms exhibit evidence of only weak serial clustering, which is in contrast to the relatively strong serial clustering of windstorms in Europe.

58 GEOSCIENCES↗

Utilisation of flavonoids from Lycium barbarum L. leaves cross‐linked with whey protein for the stabilisation and delivery of β ‐carotene emulsions

Summary Although β ‐carotene is an essential nutrient for the maintenance of human health, it is insoluble in water and extremely unstable, which limits its application. Here, we prepared a stable emulsification system of whey protein (WP)‐ Lycium barbarum L. leaves flavonoids (LBLF) complex as a carrier to load β ‐carotene. The rheological properties, antioxidant properties and stability of emulsion were studied, and the effects of emulsion on the biological retention of β ‐carotene and stability were investigated. The results indicate that, compared with WP, the WP‐LBLF emulsion has smaller particles, a smaller creaming index, and significantly enhanced chemical stability under light and heat treatment conditions. The thiobarbituric acid value of the WP‐LBLF emulsion (0.031 ± 0.016 mg/kg) was dramatically lower than that of the WP emulsion (0.045 ± 0.012 mg/kg) ( P < 0.05). In the simulated gastrointestinal digestion experiment, the retention rate of β ‐carotene was higher in WP‐LBLF emulsion. Additionally, the WP‐LBLF emulsion loaded with β ‐carotene has good salt tolerance and heat stability. In our study, WP‐LBLF was used as an emulsifier to load β ‐carotene emulsion to improve its bioavailability and stability, which provides a new preparation and application method for a complex functional emulsifier.

Fan, Yanli↗

Probabilistic picture for particle number densities in stretched tips of the branching Brownian motion

Abstract In the framework of a stochastic picture for the one-dimensional branching Brownian motion, we compute the probability density of the number of particles near the rightmost one at a time T , that we take very large, when this extreme particle is conditioned to arrive at a predefined position x T chosen far ahead of its expected position m T . We recover the previously conjectured fact that the typical number density of particles at a distance Δ to the left of the lead particle, when both Δ and are large, is smaller than the mean number density by a factor proportional to , where ζ is a constant that was so far undetermined. Our picture leads to an expression for the probability density of the particle number, from which a value for ζ may be inferred.

Physics↗

A Data Quality-Aware Framework to Reliably Forecast Photovoltaic Generation and Consumer Load for an Improved Resilience of Microgrids

Photovoltaic (PV) power and consumer load forecasting plays a critical role to ensure operational resilience of the electric grid. Most data-driven forecasting algorithms rely heavily on the continuous availability of good quality data for periodic training and validation. When deployed at the grid’s edge, prolonged disruptions to communications during extreme events degrade data quality. Factors such as missing observations, epistemic uncertainties, data drift, and concept drift are manifestations of data quality that impact the generalization of such field-deployed forecasting models. Currently, there exists no mechanism in the literature to dynamically switch between models under varying degrees of data quality as quantified by certain metrics for each factor highlighted above. This paper addresses this shortcoming by conceptually introducing a data qualityaware framework for reliable PV generation and consumer load forecasting. The framework’s design incorporates components of missing values, divergence tests, and continuous monitoring of generalization performance to detect changes in data quality caused by communications disruptions and trigger specific classes of forecasting models grouped under three use cases (UC1- UC3). As a first step towards validating this framework, real data collected from an actual field microgrid system is used to demonstrate the viability of the three use cases. Results show that the performance is the best in UC1 with an unadjusted R-square value of 0.954, followed by 0.939 for UC2 and 0.757 for UC3.

Sundararajan, Aditya↗

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗

High-order limiting methods using maximum principle bounds derived from the Boltzmann equation I: Euler equations

The use of limiting methods for high-order numerical approximations of hyperbolic conservation laws generally requires defining an admissible region/bounds for the solution. In this work, we present a novel approach for computing solution bounds and limiting for the Euler equations through the kinetic representation provided by the Boltzmann equation, which allows for extending limiters designed for linear advection directly to the Euler equations. Given an arbitrary set of solution values to compute bounds over (e.g., numerical stencil) and a desired linear advection limiter, the proposed approach yields an analytic expression for the admissible region of particle distribution function values, which may be numerically integrated to yield a set of bounds for the density, momentum, and total energy. Further, these solution bounds are shown to preserve positivity of density/pressure/internal energy and, when paired with a limiting technique, can robustly resolve strong discontinuities while recovering high-order accuracy in smooth regions without any ad hoc corrections (e.g., relaxing the bounds). This approach is demonstrated in the context of an explicit unstructured high-order discontinuous Galerkin/flux reconstruction scheme for a variety of difficult problems in gas dynamics, including cases with extreme shocks and shock-vortex interactions. Furthermore, this work presents a foundation for limiting techniques for more complex macroscopic governing equations that can be derived from an underlying kinetic representation for which admissible solution bounds are not well-understood.

42 ENGINEERING↗

Chemically Recyclable Analogs of Styrene–Butadiene Copolymers Enabling Perfectly Linear Ethylene–Styrene Materials with Random Phenyl Distribution

Copolymerization of cyclopentene (CP) and 4-phenylcyclopentene (4PCP) at a full range of comonomer feed ratios is reported using Ru-based ring-opening metathesis polymerization (ROMP) yielding homogeneous copolymers analogous to poly(styrene-ran-1,4-butadiene) and poly(ethylene-ran-styrene) copolymers following hydrogenation under mild conditions. In all cases, total monomer conversions of 86%–92% yielded copolymers with compositions within 4% of monomer feeds. Analysis of equilibrium copolymerization thermodynamics, rarely performed on two cycloolefin monomers with low ring strain energies, provides rational design strategies for negotiating two monomers with different equilibrium monomer concentrations. Inverse-gated decoupled 13 C NMR analysis of dyad sequences on the resulting copolymer microstructures concludes a near-random distribution of comonomer units. The copolymers produced from ROMP have number-average molar masses up to 60 kg mol –1 , moderate dispersities (1.5 ± 0.1), and high trans olefin content (86% ± 2%) while glass-transitions temperatures follow the Fox equation and span the full range between homopolymer extremities of PCP (−96 °C) and P4PCP (17 °C). Unlike most prevulcanized elastomers, these materials undergo facile chemical recycling to monomer, producing complete ring-closing metathesis depolymerization (RCMD) of the polymer back to the CP comonomers. Quantitative olefin hydrogenation produced perfectly linear polyethylene with 4%–16% of the backbone carbons containing a phenyl pendant, analogous to ES copolymers with up to 71.5% w/w styrene units but with random distribution of the aromatic pendants. Thermal properties of these materials are discussed, which span from semicrystalline to amorphous, and with T g values notably less than the reported ES copolymer analogs at similar compositions.

animal feed↗

Innovations Toward the Valorization of Plastics Waste

Plastics are an extremely important class of materials that are prevalent in all facets of society; however, their widespread use over time, combined with limited end-of-life strategies, has led to increasing levels of waste accumulation. Although currently considered a burden, plastics waste is potentially an untapped feedstock for numerous chemical and manufacturing processes. In this study, we discuss the state of the art of approaches for valorization of plastics waste from a materials research perspective, including previous efforts to utilize plastics waste and recent innovations that have opportunities to add significant value. Although additional progress is necessary, we present several diverse capabilities and strategies for valorization that, when brought together, address end-of-life challenges for plastics at every stage of design and product consumption. In short, a materials research–based framework offers a unique perspective to address the urgent issues posed by plastics, unlocking the potential of polymers and plastics waste.

36 MATERIALS SCIENCE↗