Browse Articles

Implementation of monocular visual SLAM with ARCog-NET for aerial robot swarm indoor mapping

Abstract This paper presents a real-time distributed framework for Unmanned Aerial Vehicle (UAV) swarms operating in GPS-denied indoor environments, built on the Aerial Robot Cognitive Network Architecture (ARCog-NET) cognitive architecture and enhanced with monocular visual Simultaneous Localization and Mapping (SLAM). ARCog-NET employs a multi-layered Edge-Fog-Cloud (EFC) hierarchy that supports decentralized decision-making and adaptive coordination, including dynamic path optimization. Through a novel formulation, each UAV jointly estimates its own trajectory and contributes to a shared 3D reconstruction of the environment by exchanging matched visual landmarks across the network. The system dynamically adapts navigation paths in response to operational events using reinforcement learning guided by trajectory coverage metrics and historical decision weights. A full deployment with six DJI Ryze Tello UAVs was conducted in a controlled indoor lab environment, demonstrating autonomous swarm navigation and collaborative 3D mapping. Performance was evaluated through metrics such as trajectory error, point cloud fidelity, decision convergence, and knowledge reuse rate. Results confirm that the proposed method enables scalable, autonomous SLAM and planning capabilities in real-world UAV networks, highlighting the cognitive synergy between navigation and perception in distributed aerial robotics.

Electrically and mechanically tunable Rashba splitting in SbSeI Janus layer: a density functional theory study

Systematic review and meta-analysis of electrical stimulation for quality of life in women with urinary incontinence

Automated and manual model creation workflows are equally reliable for virtual mechanical testing of ovine bone and fracture healing

Pharmacodynamics of direct oral anticoagulants associated with post-endoscopic delayed mucosal resection bleeding of colorectal neoplasms

Topological Duality: Constructing High‐Nuclearity Metal Clusters with Unleashed Active Sites for Efficient and Durable CO ₂ Electroreduction

Abstract Precise control of active sites with atomic resolution in metal nanoclusters (MNCs) presents a promising avenue for catalyst engineering towards CO 2 electroreduction. However, effective strategies to construct high‐nuclearity MNCs while balancing catalytic stability and active‐site exposure remain scarce. Herein, we propose a “topological‐duality‐driven” strategy to construct a high‐nuclearity Cu 24 Ag 54 nanocluster, featuring an octahedral {Cu 24 } shell and a double‐truncated cubic {Ag 54 } core with exposed {Ag 3 } vertices on {111} facets. Notably, the double‐truncated cubic is a previously unexplored concave polyhedron with over twice the number of {111} facets compared to conventional structures. As a catalyst for CO 2 electroreduction, Cu 24 Ag 54 delivers exceptional performance including a Faradaic efficiency for CO of ∼98%, catalytic stability exceeding 100 h, and current densities up to 750 mA cm −2 (total current 3 A), ranking among the highest values of the reported MNCs. Dedicated studies show the nested structure and increased electron delocalization underpin the catalyst durability. The facilitated electron transfer from Ag to the key intermediate *COOH and electron delocalization effect significantly reduce the energy barrier for *COOH formation by 50%. This work provides a new perspective on the potential of topological geometries in designing high‐nuclearity MNCs for highly efficient and robust CO 2 electroreduction at industrial current density.

Proposing a novel structure for the implementation of a graphene metamaterial-based tunable band pass/stop spatial THz plasmonic filter

Optimizing intervertebral disc cell metabolic phenotyping with machine learning and artificial neural networks

Perioperative outcomes of abdominal surgery in Ethiopia: a national clinical audit (2019–2024)

Temporal and spatial variation in the composition of the lichen Hypogymnia physodes from the Niepołomice Forest (Poland)

Integrating the Substituent Effect into the Wade–Mingos Rules for Dicarboranes

Abstract This work revisits the Wade–Mingos (W–M) rules in carborane chemistry by showing that substituent effects, rather than skeletal electron pairs alone, determine ground‐state architectures. We performed high‐throughput computational analysis of 74613 six‐vertex dicarboranes (C 2 B 4 R 6 ), using the newly proposed Seed and Mortise‐Tenon model, achieving a prediction accuracy of 92.8%. Through this analysis, we derived a simple substituent‐counting rule ( P  = n M  + 1.1 n H ) that incorporates substituent electronegativity via connected‐atom electronegativity (CAEN) to predict energetic stability. According to this rule, the previously underestimated trigonal‐bipyramidal isomer emerges as the global ground state in 89.1% of the cases, whereas the W–M‐predicted octahedral form accounts for only 9.1%. This inversion can be explained by electronic stabilization involving vacant orbitals of tricoordinate boron atoms. To rationalize these trends, we classified the studied carboranes into 28 domains defined by CAEN environments. Our analysis shows that substituent effects control the electronic balance between basic and acidic subfragments, a factor neglected in classical frameworks. The W–M rules fail in 27 of the 28 domains, remaining valid only for L‐CAEN substituents ( P  = 0). Collectively, these results establish a substituent‐guided design framework and showcase how data‐driven approaches can refine bonding rules in cluster chemistry.

Automatic generation and transfer of Yongju opera language using AIGC technology and style mapping

Abstract This research combines artificial intelligence generated content technology with style transfer methods to significantly improve the efficiency of generating and transmitting Yongju opera language content. To overcome fundamental challenges in traditional content creation, we first performed a comprehensive analysis of Yongju opera’s linguistic characteristics and established a multi-source dataset comprising 100 classical scripts, 50 contemporary scripts, and 500 lyric audio clips collected from the Ningbo Drama Research Institute and various opera platforms. The proposed framework features a dual-model architecture where the transformer-based conditional probabilistic generation (TFCPG) model acts as the content generator, while the conditional variational autoencoder (CVAE) functions as the style processor. The TFCPG transforms modern Chinese input into text complying with Yongju opera’s grammatical standards, and the CVAE enhances the text by incorporating dialect vocabulary and rhythmic patterns through style latent variables manipulation. Implemented in TensorFlow 1.4 with multi-task learning (batch size 32, Adam optimizer, learning rate 0.01), experimental results demonstrate that the TFCPG completes text generation in 33.32 min, representing a 56.6% reduction compared to the Transformer baseline. The model achieves a bilingual evaluation understudy (BLEU) score of 45.55 ± 1.32 ( p  < 0.01). In human evaluations, the system scored 4.35 for dialect authenticity, 4.18 for artistic expression, and 4.27 for cultural relevance. The CVAE component attained a BLEU score of 44.26 with 97.03% style transfer accuracy, exceeding the sequence to sequence (Seq2Seq) baseline by 10.28%. These comprehensive results confirm our approach’s effectiveness for Yongju opera language generation and style adaptation.

Outside Front Cover: Shape‐Matched Nonpolar Pore Surfaces Enhance Alkane Recognition Toward Natural Gas Upgrading (Angew. Chem. Int. Ed. 52/2025)

Aminative Suzuki–Miyaura Coupling: Tackling Alkyl Nucleophiles and Addressing the Viability of the Electrophile‐First Mechanism

Abstract Insertive cross‐coupling reactions provide the option of repurposing widely available coupling partners for the formation of new linkages. By confronting a major limitation of the aminative Suzuki–Miyaura methods we recently reported, we achieve a general method for the Pd‐catalyzed aminative coupling of primary and secondary alkyl boronic esters with aryl (pseudo)halides. Introducing a formal nitrene insertion into this Suzuki–Miyaura reaction diverts the outcome from the traditional C(sp 2 )─C(sp 3 ) products to the C(sp 2 )─NH─C(sp 3 ) analogues ( N ‐aryl anilines). DFT calculations and experimental mechanistic studies indicate that C─N bond formation from the electrophilic aryl component occurs first, providing further evidence for this previously hypothetical pathway. By comparison of several transition state structures, we find that C─N bond formation likely takes place through an unusual dyotropic rearrangement of a LPd(Ar)NHX complex (X = OPOPh 2 ).

Catalytic Asymmetric Aza‐[2+2] Cyclization Reaction of Simple Ketoimine

Abstract Herein, we report the first catalytic enantioselective aza‐[2+2] cyclization of simple ketoimines, thereby addressing a persistent challenge in four‐membered aza‐ring construction. While the aza‐[2+2] cyclization represents the most straightforward approach to azetidine synthesis, previous methodologies have been strictly limited to ketoimines, all with an EWG at the central reactive carbon, and predominantly employing cyclic imine substrates. Through rational design of an in situ‐generated magnesium catalytic system and systematic investigation of imine electronic effects, we have successfully developed an asymmetric protocol for simple ketoimines. This breakthrough enables efficient access to enantioenriched monocyclic azetidines with excellent stereocontrol. Moreover, a streamlined one‐pot tandem oxidation readily converts these azetidines into valuable quaternary chiral β‐lactams—privileged scaffolds that are prominent in numerous pharmaceuticals and bioactive agents. A combination of comparative studies, the calculation results of the HOMO and LUMO energies of different imines, relative control experiments, and a series of detailed NLE analysis revealed the coordination difference and the catalytic cycle. The catalytic protocol was used for the synthesis of a series of β‐lactams containing aryl or alkyl groups, as well as for pharmaceutical active molecules’ β‐lactam‐modifications. Importantly, the preliminary attempt to take advantage of the significant ring strain of β‐lactam for peptide modifications was also achieved on tryptophan.

Miniaturized broadband lowpass filter based on the integrated square dumbbell and meander structure spoof surface plasmon polaritons

Assessing the oral toxicity of acetamiprid, spinosad, cypermethrin, and pyrethrins in the invasive hornet Vespa velutina nigrithorax

Abstract The yellow-legged hornet, Vespa velutina subs. nigrithorax Buysson, 1905, is an invasive species in Europe, posing substantial ecological and economic threats. Its biology and behavior, marked by rapid reproduction and aggressive predation, endanger native insects. This has negative impacts on agriculture, biodiversity, and human safety. Effective control is therefore essential to prevent and minimize its spread and ecological impact. This study assessed the acute oral toxicity of four commercial insecticide formulations containing acetamiprid, spinosad, cypermethrin, and a mixture of natural pyrethrins as active ingredients on V. v. nigrithorax workers. Our findings indicate that acetamiprid and spinosad are the most promising compounds, with acetamiprid inducing rapid mortality at low doses, and spinosad causing both lethal and sublethal effects, potentially disrupting hornet behavior and colony viability. Given that oral exposure generally resulted in higher toxicity than contact exposure, pest control strategies should incorporate multiple exposure pathways. Further investigations are necessary to confirm efficacy under field conditions and to evaluate potential ecological risks to non-target species. Overall, this study provides critical data to improve V. v. nigrithorax control and supports the development of more effective and environmentally sustainable control strategies against this invasive species.

Pollutants Transformation During the Regeneration Process of Fluid Catalytic Cracking Catalysts

Abstract Fluid catalytic cracking (FCC) is the major process for heavy oil conversion in current refineries and is explored for the intake of renewable feedstocks, like biomass and plastic waste. Due to coke deposition, FCC catalysts undergo continuous reaction‐regeneration cycles. However, many gas pollutants are generated in the FCC regeneration process, and their emission characteristics and formation mechanisms are poorly understood. Here, we conducted stack tests of three industrial FCC units to monitor pollutant emissions. The spent catalysts were characterized to identify the carbon deposits formed. We developed a method to correlate the decomposition of carbon deposits and the formation of gas pollutants in regeneration experiments using in situ Raman spectroscopy, operando FT‐IR spectroscopy, and online gas‐phase FT‐IR spectroscopy. The evolution of coke species is significantly influenced by the oxygen content of the regeneration gas, leading to differences in emission concentration and formation temperature of various gas pollutants. The experimental results are compared with density functional theory (DFT) calculations to explain the formation of the major gas pollutants. This work is expected to advance pollutant emission prediction and control in FCC regeneration, thereby laying the foundation of future work in which different fossil‐based and renewable feedstock compositions can be compared, including their effect on gas pollutant formation.

Annealing strategy for enhancing the fracture toughness of MoSiBTiC alloys

Dynamic gated fusion network with hierarchical multi-scale attention for hyperspectral image classification