Search Results (68)

Life evolved under a persistent 1 g field that is continuous, ubiquitous, and directionally structured. Here, we synthesize evidence across evolutionary biology, mechanobiology, and genome architecture to propose gravity as a mechanical boundary condition that helped canalize the emergence of complex multicellularity. Order-of-magnitude considerations indicate that gravity-derived hydrostatic loads can fall within force/pressure regimes relevant to nuclear and chromatin mechanosensitivity when transmitted through adhesion–cytoskeleton–LINC–lamina coupling. Comparative genomic and imaging frameworks suggest that complex animals increasingly rely on volumetric genome organization (packing domains and higher-order 3D architectures) that supports durable transcriptional memory and stable differentiated cell identities. Integrating these concepts with altered-gravity experiments, we argue that microgravity and hypergravity perturb chromatin topology and region-level transcription in rapid, largely reversible patterns consistent with a mechanically defined 1 g reference state. We advance a boundary-condition thesis: gravity is not a sole driver but a stable reference that likely contributed to the evolvability and long-term robustness of mechanogenomic architectures required for high-dimensional differentiation and tissue homeostasis. Full article

To address the challenges posed by the strong uncertainty of high-proportion renewable energy sources (RES) to the secure and stable operation of distributed real-time power dispatch (D-RTPD) in new-type power systems, this paper proposes an integrated solution combining a neighborhood feature aggregation-based graph attention network (NFA-GAT) and multi-agent deep deterministic policy gradient (MADDPG). First, the D-RTPD problem is modeled as a decentralized partially observable Markov decision process (Dec-POMDP), which effectively captures the stochastic game characteristics of multi-regional agents and the partial observability of grid states. Second, the NFA-GAT is designed to enhance agents’ perception of grid operating states: by introducing a spatial discount factor, it realizes rational aggregation of multi-order neighborhood information while modeling the attenuation of electrical quantity influence with topological distance. Third, a prior-guided mechanism is integrated into the MADDPG framework to eliminate constraint-violating actions by setting their actor logits to negative infinity, improving training efficiency and strategy reliability. Simulation validations on the IEEE 118-bus test system (75.2% RES installed capacity ratio) show that the proposed method achieves efficient training convergence. Compared with the multi-layer perceptron (MLP) structure, it attains higher cumulative reward values and scenario win rates. When compared with traditional model-driven (ADMM) and data-driven (Q-MIX) methods, the proposed method balances solution efficiency, operational safety (98.7% maximum line load rate, zero power flow violation rate), and economic performance ($12,845 daily dispatch cost), providing a reliable technical support for D-RTPD under high-proportion RES integration. Full article

The manipulation of vector beams (VBs) with longitudinally variant polarization states is an important research topic and has potential applications in classical and quantum fields. In this study, we propose a half-wave plate dielectric metasurface composed of two interleaved sub-metasurfaces to generate longitudinally separated dual-channel vectorial structured light fields. The propagation and Pancharatnam–Berry phases are employed to construct hyperbolic, helical, and opposite gradient phases for focusing wavefronts, generating circularly polarized (CP) vortices, and deflecting CP vortices with the same chirality in opposite directions. Consequently, dual-channel higher-order or hybrid-order Poincaré (HOP or HyOP) beams are generated along the optical axis under elliptically polarized illumination, and their polarization states evolve along an arbitrary pair of antipodal meridians on the HOP or HyOP sphere by varying the ellipticity of the incident light, the propagation-phase topological charge, and the rotation order of the meta-atom. The consistency between the theoretical and simulated results demonstrates the feasibility and practicability of the proposed method. This study is significant for compact, integrated, and multifunctional optical devices, and provides an innovative strategy to extend optical field manipulation from two-dimensional to three-dimensional space. Full article

Sex chromosome imbalance is a genetic challenge in species with unequal X-chromosome numbers. Organisms have developed distinct strategies to control this imbalance through a process called dosage compensation. These strategies include X-chromosome inactivation in mammals mediated by the XIST long noncoding RNA and proteins recruited by XIST, and X-linked hypertranscription in male Drosophila driven by the Male-Specific Lethal (MSL) complex. In Caenorhabditis elegans, gene expression is downregulated from each of the two X chromosomes of hermaphrodites by half, thereby matching the levels in XO males. This is mediated by a specialized condensin-containing protein complex, the Dosage Compensation Complex (DCC). In all cases, the chromatin states on the sex chromosomes must be first established and then maintained for the entire lifetime of the organism. Although mammals and nematodes both use repression to achieve dosage compensation, the mechanisms are very different. Here, we summarize recent advances on how repressive chromatin states are established and maintained, with a focus on contrasting C. elegans dosage compensation to XIST-mediated X-chromosome inactivation. We review how specialized chromosome topology, repressive chromatin modifications, and higher-order nuclear architecture are established and maintained to achieve sex-specific regulation of the X chromosomes and highlight key outstanding questions and future research directions. Full article

Traditional non-negative matrix factorization (NMF) faces challenges when dealing with complex data, primarily characterized by sensitivity to noise, neglect of data geometric structure, and inability to effectively utilize supervised information. To address these limitations, this paper proposes a class-driven robust non-negative matrix factorization with dual-hypergraph regularization (CRNMFDH) framework. The core contributions of this framework include the following: Firstly, the design of a novel dual-hypergraph regularization term that symmetrically captures and preserves the higher-order geometric structures of both the sample space and feature space, establishing a mutually reinforcing topological relationship between them. Secondly, an introduction of a class-driven mechanism to effectively integrate label information into the decomposition process, significantly enhancing the discriminative capability of the low-dimensional representations. Finally, the employment of a loss function based on correntropy to replace the traditional Euclidean distance, thereby enhancing the model’s robustness against noise and outliers. Extensive experiments across nine datasets demonstrate that CRNMFDH significantly outperforms existing state-of-the-art algorithms in multiple clustering evaluation metrics and noise robustness, providing an effective new solution for complex data clustering tasks. Full article

We investigate the role of single-ion anisotropy in stabilizing higher-order skyrmion crystal phases in centrosymmetric magnets under D_3d symmetry. Using a classical spin model that incorporates both a local single-ion anisotropy arising from the two-dimensional crystal symmetry and a D_3d-type magnetic anisotropy originating from the D_3d point-group symmetry, we perform simulated annealing calculations to explore the ground-state spin configurations. We find that a skyrmion crystal with a skyrmion number of two is stabilized over a wide range of parameters of single-ion anisotropy and D_3d-type anisotropy. We also show that the skyrmion core position shifts from an interstitial site to an on-site location as the magnitude of the easy-axis single-ion anisotropy increases. Furthermore, we demonstrate that the magnetic field drives a variety of topological phase transitions depending on the sign and magnitude of the single-ion and D_3d-type anisotropies. These results provide a possible microscopic understanding of how complex topological spin textures can be stabilized in centrosymmetric D_3d magnets, suggesting that multiple phases with topological spin textures could emerge even in the absence of the Dzyaloshinskii–Moriya interaction. Full article

Modulating boundary conditions offers a powerful approach to generate and control topological defects, which govern the structure and dynamics of liquid crystals. Here, we employ Langevin dynamics simulations to study defect structure formation in two-dimensional colloidal liquid crystals confined within a square cavity whose walls undergo periodic oscillation. The spatial topology of the driving boundary from single-side to global four-wall actuation directly sets the symmetry of energy input, which in turn determines its spatial gradient and distribution. By controlling boundary vibrations through amplitude and frequency, we demonstrate the emergence of novel steady-state patterns and transformations between distinct defect structures, identified via the local order parameter. Four-wall oscillation generates richer structural diversity due to its higher spatial symmetry. Structural transitions are quantified by tracking a global director angle under two driving regimes: varying amplitude at fixed frequency (f = 2.0), and varying frequency at fixed amplitude (A = 1.0). Our results establish that the manner of energy injection determined by the choice of boundary motion mode governs the emergent defect architectures, providing a general route to engineer non-equilibrium phases under confinement. Full article

Background: Autism Spectrum Disorder (ASD) is a type of neurodevelopmental disorder, and its exact causes are currently unknown. Neuroimaging research suggests that its clinical features are closely linked to alterations in brain functional network connectivity, yet the specific patterns and mechanisms underlying these abnormalities require further clarification. Methods: We recruited 36 children with ASD and 36 age- and sex-matched typically developing (TD) controls. Resting-state EEG data were used to construct static and dynamic low- and high-order functional networks across four frequency bands (δ, θ, α, β). Graph-theoretical metrics (clustering coefficient, characteristic path length, global efficiency, local efficiency) and state entropy were applied to characterize network topology and dynamic transitions between integration and segregation. Additionally, between-frequency networks were built for six band pairs (δ-θ, δ-α, δ-β, θ-α, θ-β, α-β), and network global measures quantified cross-frequency interactions. Results: Low-order networks in ASD showed increased δ and β connectivity but decreased θ and α connectivity. High-order networks demonstrated increased δ connectivity, reduced α connectivity, and mixed alterations in θ and β. Graph-theoretical analysis revealed pronounced α-band topological disruptions in ASD, reflected by a lower clustering coefficient and efficiency and higher characteristic path length in both low- and high-order networks. Dynamic analysis showed no significant entropy changes in low-order networks, while high-order networks exhibited time- and frequency-specific abnormalities, particularly in δ and α (0.5 s window) and δ (6 s window). Between-frequency analysis showed enhanced β-related coupling in low-order networks but widespread reductions across all band pairs in high-order networks. Conclusions: Young children with ASD exhibit coexisting hypo- and hyper-connectivity, disrupted network topology, and abnormal temporal dynamics. Integrating hierarchical, dynamic, and cross-frequency analyses offers new insights into ASD neurophysiology and potential biomarkers. Full article

As a multi-switching power electronic circuit with complex variable topology, the three-level active neutral point clamped (ANPC) converter is a complex system with strong coupling and low linearity. It has numerous high-speed switching devices, a large number of switch states, and a high matrix dimension. Modeling each switch will undoubtedly further increase the circuit size. While in real-time simulation, updating all states of the model to produce outputs within a single time step results in a significant computational load, causing an increasing consumption of FPGA hardware resources as the number of switches and circuit size grow. In order to solve this problem, the current common practice is to decompose the entire complex power electronic system into smaller serial subsystems for modeling. The overall modeling approach for small circuits can be achieved, but when the size of the circuit increases, the overall modeling complexity and difficulty are increased or even impossible to achieve. Decoupling power electronic circuits with this decomposition into subsystem modeling not only reduces the matrix dimension and simplifies the modeling process, but also improves the computational efficiency of the real-time simulator. However, this inevitably generates simulation delays between different subsystems, leading to numerical oscillations. In an effort to overcome this challenge, this paper adopts the method of parallel computation after subsystem partitioning. There is no one-beat delay between different subsystems, and there is no loss of accuracy, which can improve the numerical stability of the modeling and can effectively reduce the step length of real-time simulation and alleviate the problem of real-time simulation resource consumption. In addition, to address the problems of low accuracy due to the traditional forward Euler method as a solver and the possibility of significant errors at some moments, this paper uses a modified prediction correction method to solve the discrete mathematical model, which provides higher accuracy as well as higher stability. And, different from the traditional control method, this paper uses an improved FCS-MPC strategy to control the switching transients of the ANPC model, which achieves a very good control effect. Finally, a simulation step size of less than 60 ns is successfully realized by empirical demonstration on the Speedgoat test platform. Meanwhile, the accuracy of our model can be objectively evaluated by comparing it with the simulation results of the Matlab Simpower system. Full article

Real-world constrained optimization problems often are highly nonlinear and present non-convex design spaces. Metaheuristic algorithms (MHOAs) are naturally suited to solving real-world optimization problems in view of their global optimization capability, but may require too many analyses to complete the optimization process. Hybrid methods enhance searching by combining two or more algorithms to better balance exploration and exploitation. Elitist strategies may be utilized to generate high-quality trial designs, yet with no guarantee that each new design always improves the current best record. In order to solve these issues and minimize the number of analyses, this study presents the novel HALSGWJA (Hybrid Approximate Line Search Grey Wolf JAYA) algorithm. HALSGWJA combined grey wolf optimizer (GWO) and JAYA (two powerful MHOAs still attracting optimization experts), enhanced by approximate line search. HALSGWJA utilized approximate gradient information to perform line searches, providing descent directions with respect to the current best record. This results in a complete renewal of the current population and a much higher probability of improving all individuals with respect to the previous iteration. The proposed HALSGWJA algorithm was successfully tested on 20 real-world mechanical engineering problems: (i) the CEC2020 test suite of 19 real-world mechanical engineering examples with up to 30 optimization variables and 86 nonlinear constraints and (ii) the optimal crashworthiness design of a vehicle subject to side impact with 11 optimization variables and 10 highly nonlinear constraints. Sizing and topology optimization problems, as well as problems with discrete variables, were considered. Remarkably, HALSGWJA outperformed 18 other state-of-the-art metaheuristic algorithms in the CEC2020 problems and 25 other algorithms in the crashworthiness design problem. HALSGWJA practically converged to target optima in all test cases (the largest penalty on target optimized cost was only 0.0263% in problem 13 of the CEC2020 library). Furthermore, it obtained in many cases 0 or nearly 0 standard deviation on optimized cost. Lastly, HALSGWJA always ranked first in terms of computational speed, requiring fewer analyses than its competitors and exhibiting, in most cases, a moderate dispersion on the number of analyses entailed by the optimization process. Full article

We investigate the stability of higher-order skyrmion crystals with large topological charges in the presence of crystal-dependent magnetic anisotropies. Focusing on the competition between two types of bond-dependent anisotropy allowed by $D_{3\mathrm{d}}$ crystalline symmetry on a two-dimensional triangular lattice, we systematically construct a low-temperature magnetic phase diagram using simulated annealing. Our analysis reveals that the stability of the higher-order skyrmion crystal with skyrmion number of two is strongly controlled by the relative sign of the bond-dependent anisotropy to the $D_{3\mathrm{d}}$-type anisotropy: a positive anisotropy, which favors spin oscillations perpendicular to the ordering wave vector, enhances its stability, whereas a negative anisotropy, favoring oscillations parallel to the ordering wave vector, suppresses it and instead stabilizes a topologically trivial double-Q state. We further examine the field evolution of these phases under an out-of-plane magnetic field and show that distinct types of skyrmion crystals with the skyrmion number of one emerge in the intermediate-field regime. These results highlight that the competition between different magnetic anisotropies in crystalline systems is a key factor governing the stability of both zero-field and field-induced skyrmion crystals. Full article

Non-Hermitian photonic crystals offer a versatile platform for observing exotic phenomena, including the non-Hermitian skin effect and higher-order topological phases. In this work, we construct non-Hermitian photonic crystals by embedding balanced gain and loss into a magneto-optical photonic medium. Within the associated supercell, we demonstrate the emergence of second-order topological corner states whose degeneracies are selectively lifted by non-Hermitian effects, while others remain protected. Remarkably, the bulk states exhibit strong unidirectional localization toward a single corner, providing unambiguous evidence of the non-Hermitian skin effect. The coexistence of higher-order corner states and the NHSE within the same photonic platform reveals an intricate interplay between crystalline symmetry and non-Hermitian topology. Beyond its fundamental intrigue, our approach offers a versatile means of engineering and controlling the non-Hermitian skin effect in realistic photonic architectures, paving the way for applications in topological nanolasers, robust light localization, and quantum photonic emulators. Full article

Hyperedge prediction is crucial for uncovering higher-order relationships in complex systems but faces core challenges, including unmodeled node influence heterogeneity, overlooked hyperedge order effects, and data sparsity. This paper proposes Order propagation Fusion Self-supervised learning for Hyperedge prediction (OFSH) to address these issues. OFSH introduces a hyperedge order propagation mechanism that dynamically learns node importance weights and groups neighbor hyperedges by order, applying max–min pooling to amplify feature distinctions. To mitigate data sparsity, OFSH incorporates a key node-guided augmentation strategy with adaptive masking, preserving core high-order semantics. It identifies topological hub nodes based on their comprehensive influence and employs adaptive masking probabilities to generate augmented views preserving core high-order semantics. Finally, a triadic contrastive loss is employed to maximize cross-view consistency and capture invariant semantic information under perturbations. Extensive experiments on five public real-world hypergraph datasets demonstrate significant improvements over state-of-the-art methods in AUROC and AP. Full article

Topological photonics has provided revolutionary ideas for the design of next-generation photonic devices due to its unique light transmission properties. This paper proposes a honeycomb photonic crystal structure based on a mirror-symmetric interface and numerically simulates the precise manipulation of topological edge states and the robust excitation of high-order topological corner states in this structure. Specifically, two honeycomb photonic crystals with non-trivial topological properties form an interface through mirror-symmetric stitching. Continuous adjustment of the spacing between their coupling pillars can induce the closure and reopening of topological edge state energy bands, accompanied by significant band inversion, revealing the dynamic process of topological phase transitions. Furthermore, zero-dimensional high-order topological corner states are observed at the junction of boundaries with different topological properties. Their localized field strengths are strictly confined and exhibit strong robustness against structural defects. This study not only provides a new mechanism for the local symmetry manipulation of topological edge states but also lays a foundation for the design of high-order topological photonic crystals and the practical application of topological photonic devices. Full article

The topological phase of matter brings extra inspiration for efficient light manipulation. Here, we propose two-parameter tunable topological transitions based on distorted Kagome photonic crystals. By selecting specific splicing boundaries, we successfully visualize several diverse types of robust edge states and corner states. Through introducing optical vortices with tunable orbital angular momentum, we demonstrate the directional excitation of multi-dimensional topological states as needed. Furthermore, we have studied the coupling effects of multi-dimensional photonic states and the modulation of source in three typical areas. This work provides an instructive avenue for manipulating light in integrated topological photonic devices. Full article