A posteriori error bounds for the block-Lanczos method for matrix function approximation

We extend the error bounds from [SIMAX, Vol. 43, Iss. 2, pp. 787-811 (2022)] for the Lanczos method for matrix function approximation to the block algorithm. Numerical experiments suggest that our bounds are fairly robust to changing block size and have the potential for use as a practical stopping criteria. Further experiments work towards a better understanding of how certain hyperparameters should be chosen in order to maximize the quality of the error bounds, even in the previously studied block-size one case

SpinView: General Interactive Visual Analysis Tool for Multiscale Computational Magnetism

Multiscale magnetic simulations, including micromagnetic and atomistic spin dynamics simulations, are widely used in the study of complex magnetic systems over a wide range of spatial and temporal scales. The advances in these simulation technologies have generated considerable amounts of data. However, a versatile and general tool for visualization, filtering, and denoising this data is largely lacking. To overcome these limitations, we have developed SpinView, a general interactive visual analysis tool for graphical exploration and data distillation. Combined with dynamic filters and a built-in database, it is possible to generate reproducible publication-quality images, videos, or portable interactive webpages within seconds. Since the basic input to SpinView is a vector field, it can be directly integrated with any spin dynamics simulation tool. With minimal effort on the part of the user, SpinView delivers a simplified workflow, speeds up analysis of complex datasets and trajectories, and enables new types of analysis and insight. SpinView is available from https://mxjk851.github.io/SpinView

Deformer: Dynamic Fusion Transformer for Robust Hand Pose Estimation

Accurately estimating 3D hand pose is crucial for understanding how humans interact with the world. Despite remarkable progress, existing methods often struggle to generate plausible hand poses when the hand is heavily occluded or blurred. In videos, the movements of the hand allow us to observe various parts of the hand that may be occluded or blurred in a single frame. To adaptively leverage the visual clue before and after the occlusion or blurring for robust hand pose estimation, we propose the Deformer: a framework that implicitly reasons about the relationship between hand parts within the same image (spatial dimension) and different timesteps (temporal dimension). We show that a naive application of the transformer self-attention mechanism is not sufficient because motion blur or occlusions in certain frames can lead to heavily distorted hand features and generate imprecise keys and queries. To address this challenge, we incorporate a Dynamic Fusion Module into Deformer, which predicts the deformation of the hand and warps the hand mesh predictions from nearby frames to explicitly support the current frame estimation. Furthermore, we have observed that errors are unevenly distributed across different hand parts, with vertices around fingertips having disproportionately higher errors than those around the palm. We mitigate this issue by introducing a new loss function called maxMSE that automatically adjusts the weight of every vertex to focus the model on critical hand parts. Extensive experiments show that our method significantly outperforms state-of-the-art methods by 10%, and is more robust to occlusions (over 14%).Comment: In ICCV 2023. Project: https://fuqichen1998.github.io/Deformer

Genetic-tunneling driven energy optimizer for spin systems

A long-standing and difficult problem in, e.g., condensed matter physics is how to find the ground state of a complex many-body system where the potential energy surface has a large number of local minima. Spin systems containing complex and/or topological textures, for example spin spirals or magnetic skyrmions, are prime examples of such systems. We propose here a genetic-tunneling-driven variance-controlled optimization approach, and apply it to two-dimensional magnetic skyrmionic systems. The approach combines a local energy-minimizer backend and a metaheuristic global search frontend. The algorithm is naturally concurrent, resulting in short user execution time. We find that the method performs significantly better than simulated annealing (SA). Specifically, we demonstrate that for the Pd/Fe/Ir(111) system, our method correctly and efficiently identifies the experimentally observed spin spiral, skyrmion lattice and ferromagnetic ground states as a function of external magnetic field. To our knowledge, no other optimization method has until now succeeded in doing this. We envision that our findings will pave the way for evolutionary computing in mapping out phase diagrams for spin systems in general

Auxin response factor 6A regulates photosynthesis, sugar accumulation, and fruit development in tomato.

Auxin response factors (ARFs) are involved in auxin-mediated transcriptional regulation in plants. In this study, we performed functional characterization of SlARF6A in tomato. SlARF6A is located in the nucleus and exhibits transcriptional activator activity. Overexpression of SlARF6A increased chlorophyll contents in the fruits and leaves of tomato plants, whereas downregulation of SlARF6A decreased chlorophyll contents compared with those of wild-type (WT) plants. Analysis of chloroplasts using transmission electron microscopy indicated increased sizes of chloroplasts in SlARF6A-overexpressing plants and decreased numbers of chloroplasts in SlARF6A-downregulated plants. Overexpression of SlARF6A increased the photosynthesis rate and accumulation of starch and soluble sugars, whereas knockdown of SlARF6A resulted in opposite phenotypes in tomato leaves and fruits. RNA-sequence analysis showed that regulation of SlARF6A expression altered the expression of genes involved in chlorophyll metabolism, photosynthesis and sugar metabolism. SlARF6A directly bound to the promoters of SlGLK1, CAB, and RbcS genes and positively regulated the expression of these genes. Overexpression of SlARF6A also inhibited fruit ripening and ethylene production, whereas downregulation of SlARF6A increased fruit ripening and ethylene production. SlARF6A directly bound to the SAMS1 promoter and negatively regulated SAMS1 expression. Taken together, these results expand our understanding of ARFs with regard to photosynthesis, sugar accumulation and fruit development and provide a potential target for genetic engineering to improve fruit nutrition in horticulture crops

Design of 2D Skyrmionic Metamaterial Through Controlled Assembly

Despite extensive research on magnetic skyrmions and antiskyrmions, a significant challenge remains in crafting nontrivial high-order skyrmionic textures with varying, or even tailor-made, topologies. We address this challenge, by focusing on a construction pathway of skyrmionics metamaterial within a monolayer thin film and suggest several promising lattice-like, flakes-like, and cell-like skyrmionic metamaterials that are surprisingly stable. Central to our approach is the concept of 'simulated controlled assembly', in short, a protocol inspired by 'click chemistry' that allows for positioning topological magnetic structures where one likes, and then allowing for energy minimization to elucidate the stability. Utilizing high-throughput atomistic-spin-dynamic (ASD) simulations alongside state-of-the-art AI-driven tools, we have isolated skyrmions (topological charge Q=1), antiskyrmions (Q=-1), and skyrmionium (Q=0). These entities serve as foundational 'skyrmionic building blocks' to forming reported intricate textures. In this work, two key contributions are introduced to the field of skyrmionic systems. First, we present a novel method for integrating control assembly protocols for the stabilization and investigation of topological magnets, which marks a significant advancement in the ability to explore new skyrmionic textures. Second, we report on the discovery of skyrmionic metamaterials, which shows a plethora of complex topologies that are possible to investigate theoretically and experimentally

Metaheuristic conditional neural network for harvesting skyrmionic metastable states

We present a metaheuristic conditional neural-network-based method aimed at identifying physically interesting metastable states in a potential energy surface of high rugosity. To demonstrate how this method works, we identify and analyze spin textures with topological charge $Q$ ranging from 1 to $-13$ (where antiskyrmions have $Q<0$) in the Pd/Fe/Ir(111) system, which we model using a classical atomistic spin Hamiltonian based on parameters computed from density functional theory. To facilitate the harvest of relevant spin textures, we make use of the newly developed Segment Anything Model (SAM). Spin textures with $Q$ ranging from $-3$ to $-6$ are further analyzed using finite-temperature spin-dynamics simulations. We observe that for temperatures up to around 20\,K, lifetimes longer than 200\,ps are predicted, and that when these textures decay, new topological spin textures are formed. We also find that the relative stability of the spin textures depend linearly on the topological charge, but only when comparing the most stable antiskyrmions for each topological charge. In general, the number of holes (i.e., non-self-intersecting curves that define closed domain walls in the structure) in the spin texture is an important predictor of stability -- the more holes, the less stable is the texture. Methods for systematic identification and characterization of complex metastable skyrmionic textures -- such as the one demonstrated here -- are highly relevant for advancements in the field of topological spintronics

Tuning skyrmions in B20 compounds by 4d and 5d doping

Skyrmion stabilization in novel magnetic systems with the B20 crystal structure is reported here, primarily based on theoretical results. The focus is on the effect of alloying on the 3d sublattice of the B20 structure by substitution of heavier 4d and 5d elements, with the ambition to tune the spin-orbit coupling and its influence on magnetic interactions. State-of-the-art methods based on density functional theory are used to calculate both isotropic and anisotropic exchange interactions. Significant enhancement of the Dzyaloshinskii-Moriya interaction is reported for 5d-doped FeSi and CoSi, accompanied by a large modification of the spin stiffness and spiralization. Micromagnetic simulations coupled to atomistic spin-dynamics and ab initio magnetic interactions reveal a helical ground state and field-induced skyrmions for all these systems. Especially small skyrmions $\sim$50 nm are predicted for Co$_{0.75}$Os$_{0.25}$Si, compared to $\sim$148 nm for Fe$_{0.75}$Co$_{0.25}$Si. Convex-hull analysis suggests that all B20 compounds considered here are structurally stable at elevated temperatures and should be possible to synthesize. This prediction is confirmed experimentally by synthesis and structural analysis of the Ru-doped CoSi systems discussed here, both in powder and in single-crystal forms.Comment: 18 pages, 21 figures, 9 table

Induction of Mycobacterium Tuberculosis Lipid-Specific T Cell Responses by Pulmonary Delivery of Mycolic Acid-Loaded Polymeric Micellar Nanocarriers

Mycolic acid (MA), a major lipid component of Mycobacterium tuberculosis (Mtb) cell wall, can be presented by the non-polymorphic antigen presenting molecule CD1b to T cells isolated from Mtb-infected individuals. These MA-specific CD1b-restricted T cells are cytotoxic, produce Th1 cytokines, and form memory populations, suggesting that MA can be explored as a potential subunit vaccine candidate for TB. However, the controlled elicitation of MA-specific T cell responses has been challenging due to difficulties in the targeted delivery of lipid antigens and a lack of suitable animal models. In this study, we generated MA-loaded micellar nanocarriers (MA-Mc) comprised of self-assembled poly(ethylene glycol)-bl-poly(propylene sulfide; PEG-PPS) copolymers conjugated to an acid sensitive fluorophore to enhance intracellular delivery of MA to phagocytic immune cells. Using humanized CD1 transgenic (hCD1Tg) mice, we found these nanobiomaterials to be endocytosed by bone marrow-derived dendritic cells (DCs) and localized to lysosomal compartments. Additionally, MA-Mc demonstrated superior efficacy over free MA in activating MA-specific TCR transgenic (DN1) T cells in vitro. Following intranasal immunization, MA-Mc were primarily taken up by alveolar macrophages and DCs in the lung and induced activation and proliferation of adoptively transferred DN1 T cells. Furthermore, intranasal immunization with MA-Mc induced MA-specific T cell responses in the lungs of hCD1Tg mice. Collectively, our data demonstrates that pulmonary delivery of MA via PEG-PPS micelles to DCs can elicit potent CD1b-restricted T cell responses both in vitro and in vivo and MA-Mc could be explored as subunit vaccines against Mtb infection