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Theory of Faradaically Modulated Redox Active Electrodes for Electrochemically Mediated Selective Adsorption Processes
No full textElectrochemically mediated selective adsorption is an emerging electrosorption technique that utilizes Faradaically enhanced redox active electrodes, which can adsorb ions not only electrostatically, but also electrochemically. The superb selectivity (>100) of this technique enables selective removal of toxic or high-value target ions under low energy consumption. Here, we develop a general theoretical framework to describe the competitive electrosorption phenomena involving multiple ions and surface-bound redox species. The model couples diffusion, convection and electromigration with competitive surface adsorption reaction kinetics, consistently derived from non-equilibrium thermodynamics. To optimize the selective removal of the target ions, design criteria were derived analytically from physically relevant dimensionless groups and time scales, where the propagation of the target anion’s concentration front is the limiting step. Detailed computational studies are reported for three case studies that cover a wide range of inlet concentration ratios between the competing ions. And in all three cases, target anions in the electrosorption cell forms a self-sharpening reaction-diffusion wave front. Based on the model, a three-step stop-flow operation scheme with a pure stripping solution of target anions is proposed that optimizes the ion adsorption performance and increases the purity of the regeneration stream to almost 100%, which is beneficial for downstream processing
Integrating Functional Knowledge into Protein Design: A Novel Approach to Tokenization and Noise Injection for Function-Aware Protein Language Models
No full textDesigning novel proteins with specific biological functions remains a fundamental challenge in computational biology. While recent advances in protein language models have enabled powerful sequence-based representations, most models, including state-of-the-art systems like ESM3, fall short in effectively encoding functional context during protein generation. In this work, we present a multimodal protein co-design framework that conditions sequence generation on fine-grained functional annotations, specifically leveraging residue-level Gene Ontology (GO) term labels on sequences from the UniRef100 database. By explicitly associating functional signals with residue elements of proteins, our model learns to generate function-conditioned protein sequences that are biologically plausible and semantically consistent. Unlike prior approaches, which treat function as a secondary feature or a classification task, our method focuses on joint reasoning over function and sequence during the design process. This closes a critical gap in the current landscape of protein design tools, offering a scalable and generalizable approach to co-designing protein sequences with user-specified functional profiles.M.Eng
China’s Potential Lessons from Ukraine for Conflict over Taiwan
No full textWhat lessons for a conflict over Taiwan might China be learning from Russia’s invasion of Ukraine and the global responses to the war? And what are the strategic implications of these lessons? To answer these questions, I examine how the war in Ukraine may be shaping China’s assessments of the political, military and economic costs of military action against Taiwan, and how these assessments may influence China’s decision to use force against Taiwan
On the normalization of open-closed string amplitudes
No full textWe use the factorization constraints of open-closed string field theory to determine the signs and normalizations of general string amplitudes with both open and closed string external states. The normalization of all amplitudes is controlled by the genus, the number of boundaries, the number of open and closed string insertions, the string coupling and the D-brane tension. The challenge with signs arises because the relevant moduli spaces are not complex manifolds and have no obvious orientation. We deal with this by fixing a specific convention for the sign of the integration measure over the moduli space and adopting a consistent prescription for the ordering of operators and ghost insertions inside correlators
The Psyche Light Elements Investigation
No full textLight elements, such as C, S, Si, O, C, and H, are thought to be present in Earth’s liquid-Fe outer core. These elements lower melting temperatures, thereby allowing the core to remain in liquid state at high pressure and influencing magnetic and geodynamic processes. However, the identity and abundance of the light elements in the cores of terrestrial planets and how they were delivered to these cores is not well known. The NASA Psyche mission will travel to and explore (16) Psyche, which may be the metal-rich core of a differentiated planetesimal exposed by collisional stripping. If so, the Psyche mission could provide a direct assessment of the light element content of an asteroidal core, allowing comparisons to the inferred composition of planetary cores and the parent bodies of the magmatic iron group meteorites. In particular, Earth’s high-pressure core formed gradually (over ∼100 Myr), in a multistage process, under increasingly oxidizing conditions, whereas the cores of planetesimals formed quickly (within 10 Myr) at low pressure, likely in chemical equilibrium with their mantles. The trace element systematics and mineral composition of magmatic iron meteorites indicate the presence of C, P, and S in planetesimal cores prior to solidification. Such elements would have played a role in core dynamics, including dynamo generation. Their low solubility combined with the immiscibility of their mineral precipitates would have resulted in their separation from Fe upon crystallization and their eruption onto the surface of a stripped core (via ferrovolcanism). The Psyche spacecraft will detect their elemental, mineral, and magnetic signatures with the payload instruments, which include a Gamma Ray and Neutron Spectrometer, a Multispectral Imager, and a Magnetometer. Additional constraints on interior composition and processes influenced by light elements will be provided by Psyche’s gravity and geomorphology investigations. We provide a brief introduction to the topic of light elements along with prospects for (16) Psyche. While we emphasize core formation processes, we also consider other possibilities for the origin and evolution of this metal-rich body
Robust Biharmonic Skinning Using Geometric Fields
No full textBounded bihramonic weights are a popular tool used to rig and deform characters for animation, to compute reduced-order simulations, and to define feature descriptors for geometry processing. They necessitate tetrahedralizing the volume bounded by the surface, introducing the possibility of meshing artifacts or tetrahedralization failure. We introduce a mesh-free and robust automatic skinning technique that generates weights comparable to the current state of the art, but works reliably even on open surfaces, triangle soups, and point clouds where current methods fail. We achieve this through the use of a specialized Lagrangian representation enabled by the advent of hardware ray-tracing, which circumvents the need for finite elements while optimizing the biharmonic energy and enforcing boundary conditions. The flexibility of our formulation allows us to integrate artistic control through weight painting during the optimization. We offer a thorough qualitative and quantitative evaluation of our method
Advancing Biosecurity in the Age of AI: Integrating Novel Detection, Suppression, and Evaluation Approaches
No full textCivilization confronts a growing challenge: advancing transformative biological science while safeguarding against catastrophic misuse, a tension amplified by the rapid convergence between biology and artificial intelligence. The COVID-19 pandemic starkly revealed our vulnerabilities to self-replicating, exponential biological phenomena, yet current defenses remain dangerously inadequate—often blind to novel pathogens until too late and lacking barriers against rapid airborne transmission. This thesis argues that robust biosecurity enables, rather than hinders, progress, and advances three key defensive capabilities. First, it evaluates blood metagenomics for pathogen-agnostic surveillance, reanalyzing public datasets to quantify viral signatures and guide the implementation of much-needed early-warning systems sensitive to novel pathogens. Second, it advances far-UVC, a type of ultraviolet between 200-235 nm, for continuous indoor air disinfection, critically assessing its safety profile through an international expert review and establishing research priorities essential for deploying this vital physical defense against airborne threats. Third, it develops rigorous methodologies for evaluating AI's rapidly evolving biological capabilities, benchmarking frontier models across diverse tasks to track progress, reveal limitations in current assessments, and guide responsible innovation in this powerful dual-use technology. Collectively, these contributions help accelerate technologies to mitigate biological risks, thereby helping secure the conditions for continued, beneficial advancement of biology in the age of AI.S.M
Simultaneous 3D quantitative magnetization transfer imaging and susceptibility mapping
No full textPurpose: Introduce a unified acquisition and modeling strategy to simul-taneously quantify magnetization transfer (MT), tissue susceptibility ()and T∗2 .
Theory and Methods: Magnetization transfer is induced through the appli-cation of off-resonance irradiation between excitation and acquisition of anRF-spoiled gradient-echo scheme, where free pool spin–lattice relaxation (TF1 ),macromolecular proton fraction (f ) and magnetization exchange rate (kF ) werecalculated by modeling the magnitude of the MR signal using a binary spin-bathMT model with B+1 inhomogeneity correction via Bloch-Siegert shift. Simultane-ously, a multi-echo acquisition is incorporated into this framework to measurethe time evolution of both signal magnitude and phase, which was further mod-eled for estimating T∗2 and tissue susceptibility. In this work, we demonstratethe feasibility of this new acquisition and modeling strategy in vivo on the braintissue.
Results: In vivo brain experiments were conducted on five healthy subjects tovalidate our method. Utilizing an analytically derived signal model, we simul-taneously obtained 3D TF1 , f , kF , and T∗2 maps of the whole brain. Our resultsfrom the brain regional analysis show good agreement with those previouslyreported in the literature, which used separate MT and QSM methods.Conclusion: A unified acquisition and modeling strategy based on an analyticalsignal model that fully leverages both the magnitude and phase of the acquiredsignals was demonstrated and validated for simultaneous MT, susceptibility andT∗2 quantification that are free from B+1 bias
Small radius inclusive jet production at the LHC through NNLO+NNLL
No full textThe study of hadronic jets and their substructure at hadronic colliders is crucial for improving our understanding of QCD, and searching for new physics. As such, there has been a significant effort to improve their theoretical description. In the small radius limit, inclusive jet production exhibits a universal factorization, enabling the resummation of logarithms which greatly stabilizes theoretical predictions. In this paper, we show how to combine a recently introduced framework for small-R resummation with the Stripper subtraction formalism for fragmentation, enabling next-to-next-to-leading order calculations of small-R inclusive jet production for a wide variety of processes at the LHC. We extract the two-loop constants for the jet functions, enabling for the first time next-to-next-to-leading logarithmic resummation matched to next-to-next-to-leading order perturbative calculation. We compare with CMS data for small-R jet production, and find that our results greatly improve the accuracy of the predictions at small-R, and stabilize the perturbative convergence and error estimates at larger R. Our approach is applicable to a wide class of jet substructure observables exhibiting similar factorization theorems, opening the door to an NNLO jet substructure program at the LHC
Gender gaps in South Korea’s labour market: children explain most of the gender employment gap, but little of the gender wage gap
No full textSouth Korea’s gender wage and employment gaps are among the largest in the OECD. Using labour force survey data over 2010–19, we estimate gender wage and employment gaps, and child earnings penalties, for women aged 25–54. We show (i) that the large gender gaps in South Korea’s labour market are mostly not a function of differential sorting by gender along education, occupation, or industry lines, (ii) that caring for children (and, perhaps increasingly, for the elderly) is the major factor inhibiting women’s labour force participation, and (iii) that large gender wage gaps exist even for women without care responsibilities. These findings suggest that improving opportunities for work–family balance is crucial to helping increase women’s labour force participation, but may do little to close gender wage gaps: other major obstacles also appear to stand in the way of Korean women’s full inclusion in the labour force