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A bstract Quantum field theories (QFT) in the presence of defects exhibit new types of anomalies which play an important role in constraining the defect dynamics and defect renormalization group (RG) flows. Here we study surface defects and their anomalies in conformal field theories (CFT) of general spacetime dimensions. When the defect is conformal, it is characterized by a conformal b -anomaly analogous to the c -anomaly of 2d CFTs. The b -theorem states that b must monotonically decrease under defect RG flows and was proven by coupling to a spurious defect dilaton. We revisit the proof by deriving explicitly the dilaton effective action for defect RG flow in the free scalar theory. For conformal surface defects preserving N = (0 , 2) supersymmetry, we prove a universal relation between the b -anomaly and the ’t Hooft anomaly for the U(1) r symmetry. We also establish the b -extremization principle that identifies the superconformal U(1) r symmetry from N = (0 , 2) preserving RG flows. Together they provide a powerful tool to extract the b -anomaly of strongly coupled surface defects. To illustrate our method, we determine the b -anomalies for a number of surface defects in 3d, 4d and 6d SCFTs. We also comment on manifestations of these defect conformal and ’t Hooft anomalies in defect correlation functions.

A bstract Conformal defects describe the universal behaviors of a conformal field theory (CFT) in the presence of a boundary or more general impurities. The coupled critical system is characterized by new conformal anomalies which are analogous to, and generalize those of standalone CFTs. Here we study the conformal a - and c -anomalies of four dimensional defects in CFTs of general spacetime dimensions greater than four. We prove that under unitary defect renormalization group (RG) flows, the defect a -anomaly must decrease, thus establishing the defect a -theorem. For conformal defects preserving minimal supersymmetry, the full defect symmetry contains a distinguished U(1) R subgroup. We derive the anomaly multiplet relations that express the defect a - and c -anomalies in terms of the defect (mixed) ’t Hooft anomalies for this U(1) R symmetry. Once the U(1) R symmetry is identified using the defect a -maximization principle which we prove, this enables a non-perturbative pathway to the conformal anomalies of strongly coupled defects. We illustrate our methods by discussing a number of examples including boundaries in five dimensions and codimension-two defects in six dimensions. We also comment on chiral algebra sectors of defect operator algebras and potential conformal collider bounds on defect anomalies.

A bstract We study correlation functions involving extended defect operators in the four- dimensional N = 4 super-Yang-Mills (SYM). The main tool is supersymmetric localization with respect to the supercharge 𝒬 introduced in [ 1 ] which computes observables in the 𝒬- cohomology. We classify general defects of different codimensions in the N = 4 SYM that belong to the 𝒬-cohomology, which form 1 -BPS defect networks. By performing the 𝒬- localization of the N = 4 SYM on the four-dimensional hemisphere, we discover a novel defect-Yang-Mills (dYM) theory on a submanifold given by the two-dimensional hemisphere and described by (constrained) two-dimensional Yang-Mills coupled to topological quantum mechanics on the boundary circle. This also generalizes to interface defects in N = 4 SYM by the folding trick. We provide explicit dictionary between defect observables in the SYM and those in the dYM, which enables extraction of general 1 16 -BPS defect network observables of the SYM from two-dimensional gauge theory and matrix model techniques. Applied to the D5 brane interface in the SU( N ) SYM, we explicitly determine a set of defect correlation functions in the large N limit and obtain precise matching with strong coupling results from IIB supergravity on AdS 5 × S 5 .

Three-dimensional (3D) reconstruction based on fringe projection profilometry (FPP) is a crucial technique for capturing surface topography in high-precision industrial manufacturing. However, overexposure phenomenon frequently occurs in captured images due to variations in object reflectance and lighting conditions, leading to reduced 3D reconstruction accuracy. This represents the most challenging issue in high dynamic range (HDR) environments. To this end, I propose a deep learning-based fringe image restoration method. It utilizes the derivative networks of U-Net to restore saturated fringes, enabling subsequent 3D reconstruction. This method significantly enhances reconstruction accuracy without requiring additional hardware or capturing multiple extra image sets for prediction. I further systematically compared the performance of three network architectures—U-Net, Res-U-Net, and SE-U-Net—in the fringe repair task, revealing their respective capabilities through quantitative experimental analysis. Comparative experiments show that all three networks in this paper can effectively repair saturated fringes, with SE-U-Net exhibiting superior performance in restoring missing regions. This study not only validates the effectiveness of deep learning for repairing saturated fringe images in HDR scenes, but also provides guidance for selecting network models in grating fringe restoration.

A bstract We study generalized discrete symmetries of quantum field theories in 1+1D generated by topological defect lines with no inverse. In particular, we describe ’t Hooft anomalies and classify gapped phases stabilized by these symmetries, including new 1+1D topological phases. The algebra of these operators is not a group but rather is described by their fusion ring and crossing relations, captured algebraically as a fusion category. Such data defines a Turaev-Viro/Levin-Wen model in 2+1D, while a 1+1D system with this fusion category acting as a global symmetry defines a boundary condition. This is akin to gauging a discrete global symmetry at the boundary of Dijkgraaf-Witten theory. We describe how to “ungauge” the fusion category symmetry in these boundary conditions and separate the symmetry-preserving phases from the symmetry-breaking ones. For Tambara-Yamagami categories and their generalizations, which are associated with Kramers-Wannier-like self-dualities under orbifolding, we develop gauge theoretic techniques which simplify the analysis. We include some examples of CFTs with fusion category symmetry derived from Kramers-Wannier-like dualities as an appetizer for the Part II companion paper.

A bstract We study generalized symmetries of quantum field theories in 1+1D generated by topological defect lines with no inverse. This paper follows our companion paper on gapped phases and anomalies associated with these symmetries. In the present work we focus on identifying fusion category symmetries, using both specialized 1+1D methods such as the modular bootstrap and (rational) conformal field theory (CFT), as well as general methods based on gauging finite symmetries, that extend to all dimensions. We apply these methods to c = 1 CFTs and uncover a rich structure. We find that even those c = 1 CFTs with only finite group-like symmetries can have continuous fusion category symmetries, and prove a Noether theorem that relates such symmetries in general to non-local conserved currents. We also use these symmetries to derive new constraints on RG flows between 1+1D CFTs.

Influenza virus infections can cause severe complications such as Acute Necrotizing Encephalopathy (ANE), which is characterised by a rapid onset of pathological inflammation following febrile infection. Heterozygous dominant mutations in the nucleoporin RANBP2/Nup358 predispose to influenza-triggered ANE1. The aim of our study was to determine whether RANBP2 plays a role in IAV-triggered inflammatory responses. We found that the depletion of RANBP2 in a human airway epithelial cell line increases IAV genomic replication by favouring the import of the viral polymerase subunits, PB1, PB2, and PA, following viral transcription and translation. Additionally, RANBP2 knockdown enhances the cytoplasmic export of viral genomic RNA (vRNA) and disrupts segment stoichiometry, which is associated with elevated production of the pro-inflammatory chemokines CXCL8, CXCL10, CCL2, CCL3, and CCL4 in human primary macrophages. Using CRISPR-Cas9 knock-in for the ANE1 disease variant RANBP2-T585M, we further demonstrate that this point mutation causes a loss-of-localisation phenotype that excludes RANBP2 from the nuclear envelope, which phenocopies RANBP2 knockdown by increasing IAV replication and driving pro-inflammatory cytokine expression following infection. Together, our results reveal that RANBP2 regulates influenza RNA replication and nuclear export, thereby restraining virus-induced hyperinflammation, and further suggest that ANE1 pathogenesis results from the impaired localisation of RANBP2 at the nuclear envelope. Influenza can cause Acute Necrotizing Encephalopathy (ANE), a rare brain inflammatory disease. This study shows that loss or mislocalisation of RANBP2, as seen with ANE-linked mutations, boosts viral replication and triggers excessive inflammation.

This study evaluates the effectiveness of Chinese doctor–patient dialogues as retrieval sources for Retrieval-Augmented Generation (RAG) in clinical question answering. Using ChatGPT-3.5 as a baseline and extending to GPT-4o and GPT-5, we compare multiple retrieval pipelines, including dense retrieval, Cross-Encoder reranking, Reciprocal Rank Fusion (RRF), and Cascade RRF→Rerank. Experimental results show that dialogue-based retrieval significantly improves generation quality relative to direct prompting (e.g., ROUGE-1-f: +12.6%, BERTScore_F1: +1.5%, p  < 0.05). Among retrieval strategies, Rerank-only provides the best accuracy–latency balance, while the cascade pipeline introduces noise and yields no additional benefit. Under identical retrieval settings, GPT-4o achieves stronger automatic metrics and 4–5× lower latency, whereas GPT-5 receives slightly higher human preference scores (+ 0.08, p  < 0.001), indicating a trade-off between efficiency and perceived coherence. Expert evaluation further confirms improvements in readability, accuracy, and authenticity (all p  < 0.001). These findings highlight that data representation and metadata structure have a greater impact on RAG performance than retrieval algorithm complexity, offering practical guidance for reliable medical QA deployment.

The discovery of graphene, the first two-dimensional (2D) material, has caused an upsurge, as this kind of material revealed a tremendous potential of application in areas such as energy storage, electronics, and gas separation. MXenes are referred to as a family of 2D transition metal carbides, carbonitrides, and nitrides. After the synthesis of Ti from Ti AlC in 2011, about 30 new compositions have been reported. These materials have been widely discussed, synthesized, and investigated by many research groups, as they have many advantages over traditional 2D materials. This review covers the structures of MXenes, discusses various synthesis routines, analyzes the properties, especially optical and electronic properties, and summarizes their applications and potential, which may give readers an overview of these popular materials.

Mutations in RanBP2 (also known as Nup358), one of the main components of the cytoplasmic filaments of the nuclear pore complex, contribute to the overproduction of acute necrotizing encephalopathy (ANE1)-associated cytokines. Here we report that RanBP2 represses the translation of the interleukin 6 ( IL6 ) mRNA, which encodes a cytokine that is aberrantly up-regulated in ANE1. Our data indicates that soon after its production, the IL6 messenger ribonucleoprotein (mRNP) recruits Argonautes bound to let-7 microRNA. After this mRNP is exported to the cytosol, RanBP2 sumoylates mRNP-associated Argonautes, thereby stabilizing them and enforcing mRNA silencing. Collectively, these results support a model whereby RanBP2 promotes an mRNP remodelling event that is critical for the miRNA-mediated suppression of clinically relevant mRNAs, such as IL6 .