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Very recently, increasing attention has been focused on non-Abelian topological charges, e.g., the quaternion group Q 8 . Different from Abelian topological band insulators, these systems involve multiple entangled bulk bandgaps and support nontrivial edge states that manifest the non-Abelian topological features. Furthermore, a system with an even or odd number of bands will exhibit a significant difference in non-Abelian topological classification. To date, there has been scant research investigating even-band non-Abelian topological insulators. Here, we both theoretically explore and experimentally realize a four-band PT (inversion and time-reversal) symmetric system, where two new classes of topological charges as well as edge states are comprehensively studied. We illustrate their difference in the four-dimensional (4D) rotation sense on the stereographically projected Clifford tori. We show the evolution of the bulk topology by extending the 1D Hamiltonian onto a 2D plane and provide the accompanying edge state distributions following an analytical method. Our work presents an exhaustive study of four-band non-Abelian topological insulators and paves the way towards other even-band systems. Non-Abelian topological insulators receive increasing attention due to entangled bulk bandgaps different from Abelian counterparts. Here, the authors realize two new classes of topological charges characterizing of a four-band non-Abelian topological insulator.

In the last few decades, topological phase 1 – 11 has emerged as a new classification of matter states beyond the Ginzburg–Landau symmetry-breaking paradigm. The underlying global invariant is usually well characterized by integers, such as Chern numbers or winding numbers—the Abelian charges 12 – 15 . Very recently, researchers proposed the notion of non-Abelian topological charges 16 – 19 , which possess non-commutative and fruitful braiding structures with multiple (more than one) bandgaps tangled together. Here we experimentally observe the non-Abelian topological charges in a time-reversal and inversion-symmetric transmission line network. The quaternion-valued non-Abelian topological charges are clearly mapped onto an eigenstate-frame sphere. Moreover, we find a non-Abelian quotient relation that provides a global perspective on the distribution of edge/domain-wall states. Our work opens the door towards characterization and manipulation of non-Abelian topological charges, which may lead to interesting observables such as trajectory-dependent Dirac/Weyl node collisions in two-dimensional systems 16 , 17 , 20 , admissible nodal line configurations in three dimensions 16 , 19 , 20 , and may provide insight into certain strongly correlated phases of twisted bilayer graphene 21 . Non-Abelian topological charges and edge states in a PT-symmetric transmission line network are experimentally observed, and a non-Abelian quotient relation for the bulk–edge correspondence is found.

The visualization of the spatial distributions of gases from various sources is essential to understanding the composition, localization, and behavior of these gases. In this study, an inkjet-printed localized surface plasmon resonance (LSPR) subpixel gas sensor array was developed to visualize the spatial distributions of gases and to differentiate between acetic acid, geraniol, pentadecane, and cis-jasmone. The sensor array, which integrates gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and fluorescent pigments, was positioned 3 cm above the gas source. Hyperspectral imaging was used to capture the LSPR spectra across the sensor array, and these spectra were then used to construct gas information matrices. Principal component analysis (PCA) enabled effective classification of the gases and localization of their sources based on observed spectral differences. Heat maps that visualized the gas concentrations were generated using the mean squared error (MSE) between the sensor responses and reference spectra. The array identified and visualized the four gas sources successfully, thus demonstrating its potential for gas localization and detection applications. The study highlights a straightforward, cost-effective approach to gas sensing and visualization, and in future work, we intend to refine the sensor fabrication process and enhance the detection of complex gas mixtures.

Novel classical wave phenomenon analogs of the quantum spin Hall effect are mostly based on the construction of pseudo-spins. Here we show that the non-trivial topology of a system can also be realized using orbital angular momentum through a coupling between the angular momentum and the wave vector. The idea is illustrated with a tight-binding model and experimentally demonstrated with a transmission line network. We show experimentally that even a very small network cluster exhibits angular momentum-dependent one-way topological edge states, and their properties can be described in terms of local Chern numbers. Our work provides a new mechanism to realize counterparts of the quantum spin Hall effect in classical waves and may offer insights for other systems. Here, the authors show that a system can exhibit angular momentum-dependent topological properties through angular-momentum-orbital coupling and provide a proof-of-principle experimental demonstration using a transmission line network.

The hybrid skin-topological effect (HSTE) has recently been proposed as a mechanism where topological edge states collapse into corner states under the influence of the non-Hermitian skin effect (NHSE). However, directly observing this effect is challenging due to the complex frequencies of eigenmodes. In this study, we experimentally observe HSTE corner states using synthetic complex frequency excitations in a transmission line network. We demonstrate that HSTE induces asymmetric transmission along a specific direction within the topological band gap. Besides HSTE, we identify corner states originating from non-chiral edge states, which are caused by the unbalanced effective onsite energy shifts at the boundaries of the network. Furthermore, our results suggest that whether the bulk interior is Hermitian or non-Hermitian is not a key factor for HSTE. Instead, the HSTE states can be realized and relocated simply by adjusting the non-Hermitian distribution at the boundaries. Our research has deepened the understanding of a range of issues regarding HSTE, paving the way for advancements in the design of non-Hermitian topological devices. Hybrid skin-topological effect (HSTE) is a new phenomenon involving the interplay between non-Hermitian skin effects and topological edge states. Here, the authors highlight the key role of boundary configurations and experimentally observe HSTE states using synthetic complex frequencies.

Soybean relies on symbiotic nitrogen fixation (SNF) to support sustainable agriculture. In this study, we conducted a comprehensive analysis of the GmMYB transcription factor subfamily 20, with a focus on GmMYB62a and GmMYB62b. Phylogenetic and structural analyses revealed that these genes are evolutionarily conserved among legumes and possess distinct domain architectures. Expression profiling and GUS staining showed that GmMYB62a and GmMYB62b are constitutively expressed in nodules. Functional analyses revealed that loss of GmMYB62s function significantly reduced nodule density, while overexpression promoted nodulation. Transcriptomic analysis (RNA-seq) further demonstrated that GmMYB62s regulate key pathways, including hormone signaling, immune responses, and cell wall metabolism, thereby coordinating symbiotic interactions. Collectively, our findings identify GmMYB62a and GmMYB62b as critical molecular regulators of nodulation in soybean, providing promising targets for improving symbiotic nitrogen fixation efficiency in legume crops.

Background Periprosthetic joint infection leads to significant morbidity and mortality after total knee arthroplasty. Preoperative and perioperative risk prediction and assessment tools are lacking in Asia. This study developed the first machine learning model for individualized prediction of periprosthetic joint infection following primary total knee arthroplasty in this demographic. Methods A retrospective analysis was conducted on 3,483 primary total knee arthroplasty (81 with periprosthetic joint infection) from 1998 to 2021 in a Chinese tertiary and quaternary referral academic center. We gathered 60 features, encompassing patient demographics, operation-related variables, laboratory findings, and comorbidities. Six of them were selected after univariate and multivariate analysis. Five machine learning models were trained with stratified 10-fold cross-validation and assessed by discrimination and calibration analysis to determine the optimal predictive model. Results The balanced random forest model demonstrated the best predictive capability with average metrics of 0.963 for the area under the receiver operating characteristic curve, 0.920 for balanced accuracy, 0.938 for sensitivity, and 0.902 for specificity. The significant risk factors identified were long operative time (OR, 9.07; p  = 0.018), male gender (OR, 3.11; p  < 0.001), ASA > 2 (OR, 1.68; p  = 0.028), history of anemia (OR, 2.17; p  = 0.023), and history of septic arthritis (OR, 4.35; p  = 0.030). Spinal anesthesia emerged as a protective factor (OR, 0.55; p  = 0.022). Conclusion Our study presented the first machine learning model in Asia to predict periprosthetic joint infection following primary total knee arthroplasty. We enhanced the model’s usability by providing global and local interpretations. This tool provides preoperative and perioperative risk assessment for periprosthetic joint infection and opens the potential for better individualized optimization before total knee arthroplasty.

Topological states are useful because they are robust against disorder and imperfection. In this study, we consider the effect of disorder and the breaking of parity symmetry on a topological network system in which the edge states are protected by Chern numbers. In the absence of periodicity, the local Chern number is adopted to characterize the topological features of the network. Our numerical results show that the local Chern number and the edge states are very robust against onsite disorder as long as the gap of the bulk state continuum remains open and survives even when the bulk band gap is closed. Breaking the parity symmetry can destroy the quantization of local Chern numbers, compromising the existence of edge modes. We observed non-integer local Chern number peaks that are non-zero inside the bulk bands but these non-zero non-integral local Chern numbers are not associated with the existence of robust edge states.

Recently, the hybrid skin-topological effect (HSTE), in which the topological modes localize at corners, has attracted significant research interest. While most relevant studies are carried out in ordered systems, the interplay between disorder and the HSTE remains unexplored. Here we investigate a type of HSTE induced by the topological Anderson transition, termed as the hybrid skin-topological-Anderson effect (HSTAE). The HSTAE modes maintain localization characteristics as the model size increases and the localized position can be modulated by the on-site gain/loss. Furthermore, our analysis reveals that disorder not only extends the range of topologically non-trivial phases, but also causes the deformation of gapless phase regions. This work explores the interplay between topological Anderson insulators and non-Hermitian effects, opening up potential applications in non-Hermitian topological devices. Recently, the hybrid skin-topological effect (HSTE), in which the topological modes localize at corners, has attracted significant interest, but its interplay with disorder remains unexplored. Here, the authors demonstrate a topological Anderson transition and deformation of the gapless phase by introducing disorder into the non-Hermitian Haldane model, termed as the hybrid skin-topological-Anderson effect.