Limited Transmission Research Articles

Resource construction of intelligent design based on artificial intelligence bio-perception in the protection of intangible cultural heritage

The protection of intangible cultural heritage (ICH) is not only respect and protection for traditional culture, but also plays a vital role in cultural inheritance, social identity, historical memory, economic development, and innovative vitality. With the rapid advancement of globalization and modernization, ICH is also facing unprecedented challenges. However, the traditional protection of ICH has problems such as focusing on static physical protection, insufficient information storage, limited transmission, insufficient modern transformation and innovation, excessive restoration of traditional elements and conservative protection. In response to the above problems, this paper designs an ICH resource construction system based on artificial intelligence (AI) biological perception. It can perceive ICH data through multimodal biology, store and reproduce it, perform feature analysis based on biological emotions and emotional interactions, capture the inheritance logic and emotional connotation of culture, and drive the digital modeling of ICH resources with intelligent design. Dynamic ICH content can be superimposed on real scenes to facilitate education and dissemination, and personalized ICH story content can be recommended based on user preferences to enhance the display and dissemination capabilities of ICH. The results show that the system uses multimodal perception and stores more than 100,000 ICH data items in four major categories and multiple subcategories, and designs a unique interactive tag cloud for users to choose from. When making recommendations for users, it recommends 200 ICH contents to users from the sorted list simultaneously, and the proportion of users clicking on the recommendations reaches 85%, while also achieving the widespread dissemination of ICH in Asia. Compared with traditional ICH protection, this study has achieved efficient digital storage of ICH content, strong modern conversion, and ease of acceptance by users. The scope of dissemination is also wider. This shows that the use of AI and biosensing technology in ICH protection is effective and can contribute to better preservation, publicity and promotion of ICH.

Multifunctional Nanozyme with Aptamer-Based Ratiometric Fluorescent and Colorimetric Dual Detection of Prostate-Specific Antigen.

The adsorption of DNA probes onto nanomaterials represents a promising bioassay technique, generally employing fluorescence or catalytic activity to generate signals. A significant challenge is maintaining the catalytic activity of chromogenic catalysts during detection while enhancing accuracy by overcoming the limitations of single-signal transmission. This article presents an innovative multimodal analysis approach that synergistically combines the oxidase-like activity of Fe-N-C nanozyme (Fe-NC) with red fluorescent carbon quantum dots (R-CQDs), further advancing the dual-mode analysis method utilizing R-CQDs@Fe-NC. In this system, R-CQDs integrate with Fe-NC to provide a steady reference red fluorescence signal, while Fe-NC serves as the catalytic active site. The adsorption of 6-carboxyfluorescein-labeled aptamers (FAM-apt) significantly enhanced the electron transfer capability of R-CQDs@Fe-NC, enhancing its catalytic performance and resulting in increased oxidation of 3,3',5,5'-tetramethylbenzidine (TMB). Concurrently, the green fluorescence of FAM-apt diminishes due to energy competition, photoinduced electron transfer, and the internal filtration effect by R-CQDs@Fe-NC, while the red fluorescence from R-CQDs@Fe-NC remains stable. Upon recognizing and binding to prostate-specific antigen (PSA), FAM-apt detaches from the surface of R-CQDs@Fe-NC. This leads to simultaneous variations in both the fluorescence signal of the system and the colorimetric signal of TMB. Based on these properties, a colorimetric/fluorescence dual-mode detection method for PSA was established, with detection limits of 0.054 and 0.16 ng/mL, respectively. Furthermore, a smartphone-based sensing device facilitated rapid and convenient detection. This study presents a multisignal output sensing strategy and a simple capillary sensing device, presenting a promising approach for PSA diagnostic analysis and the potential detection of other biomarkers.

Research on Assembly Robots Based on Flexible Control Technology

Industrial robots play a vital role in modern production automation, especially in improving production efficiency and reducing labor costs. However, traditional robot position control methods often have difficulty coping with complex assembly tasks, especially in changing environments. To solve this problem, flexible control technology has emerged, which can dynamically adjust the state of the robot according to the force applied by the external environment, thereby effectively avoiding rigid collisions and improving the accuracy and safety of the robot. This paper summarizes recent research on force-aware control in scenarios of shaft-hole assembly, including improvements to traditional force-position hybrid control and the introduction of intelligent control principles. This technique has significantly improved the efficiency and success rate of the alignment and loading phases. However, the high cost of force-aware control and data transmission limitations remain challenges. Future research should focus on improving system flexibility, expanding application scope and optimizing the underlying hardware to drive robotics towards intelligence and refinement

Inter-Institutional Dynamics and Impact of Fluconazole-Resistant Candida parapsilosis.

Infections with fluconazole-resistant Candida parapsilosis have been increasing in Israeli hospitals with unclear implications for patient outcomes. To determine the frequency, mechanisms, molecular epidemiology, and outcomes of azole-resistant C. parapsilosis bloodstream infections in four hospitals in Israel. C. parapsilosis bloodstream isolates were collected at four hospitals in central Israel during varying periods from 2005 to 2022. Antifungal susceptibility testing was done using CLSI broth microdilution. Risk factors for fluconazole resistance were investigated using logistic regression. ERG11 gene sequencing was performed on all isolates. Genetic relatedness was determined using multilocus microsatellite genotyping. Clinical cure, microbiological eradication, and mortality rates were compared between fluconazole-susceptible and resistant isolates. A total of 192 patient-specific C. parapsilosis isolates were analysed. Resistance to fluconazole and voriconazole was detected in 80 (41%) and 14 (7.2%) isolates, respectively. The ERG11 Y132F substitution was found in 91% of fluconazole-resistant and 1% of fluconazole-susceptible isolates. Increasing age, intensive care hospitalisation, haemodialysis, and recent exposure to antibiotics were risk factors for fluconazole-resistant C. parapsilosis. Distinct but related genotypes predominated at each centre, indicating extensive dissemination within hospitals and limited transmission among them. Fluconazole resistance was associated with increased likelihood of microbiological failure but no significant difference in clinical cure and mortality. We found high rates of fluconazole resistance in C. parapsilosis, attributable to nosocomial spread of hospital-specific clones bearing the Y132F substitution. Fluconazole resistance was associated with a higher risk of microbiological but not clinical failure. Strategies to limit nosocomial transmission of C. parapsilosis are needed.

Enhanced constant extinction angle control for subsequent commutation failure in LCC‐HVDC

AbstractTo mitigate subsequent commutation failure (SCF) in line‐commutated converter‐based high‐voltage direct current transmission systems, the response and limitations of the control system are analysed. The results reveal that due to the prolonged negative deviation of the extinction angle during recovery, the integral output of the proportional–integral controller in constant extinction angle (CEA) significantly reduces the advanced firing angle order, even below normal operating angle. This directly leads to a delayed transition between control strategies and diminishes the effectiveness of CEA. Furthermore, the influence of fault severity, fault type, and AC system strength on SCF is examined. Based on these findings, an enhanced CEA control method to suppress SCF is proposed. By setting an expected firing angle and adaptively adjusting the integral parameter, the control strategy switching moment can be advanced, improving the CEA's control margin and enhancing capability. Moreover, introducing a notch filter reduces firing angle fluctuations and strengthens CEA's ability to suppress SCF. Finally, the theoretical analysis and the effectiveness of the proposed optimization method are validated.

Optimized Dynamic Deployment of UAVs in Maritime Networks with Route Prediction

The limited coverage of terrestrial base stations and the limited transmission distance and onboard resources of satellite communications make it difficult to ensure the quality of communication services for marine users by relying only on satellites and terrestrial base stations. In contrast, UAVs, as flexible mobile communication nodes, have the capacity for dynamic deployment and real-time adjustment. They can effectively make up for the communication blind spots of traditional satellites and ground base stations in the marine environment, especially in the vast and unpredictable marine environment. Considering the mobility of maritime users, one can effectively reduce the communication delay and optimize the deployment scheme of UAVs by predicting their sailing trajectories in advance, thus enhancing the communication service quality. Therefore, this paper proposes a communication coverage model based on mobile user route prediction and a UAV dynamic deployment algorithm (RUDD). It aims to optimize the coverage efficiency of the maritime communication network, minimize the communication delay, and effectively reduce the energy consumption of UAVs. In this algorithm, the RUDD algorithm employs a modified Long Short-Term Memory (LSTM) network to predict the maritime user’s trajectory, utilizing its strengths in processing time-series data to provide accurate predictions. The prediction results are then used to guide the Proximal Policy Optimization (PPO) algorithm for the dynamic deployment of UAVs. The PPO algorithm can optimize the deployment strategy in dynamic environments, improve communication coverage, and reduce energy consumption. Simulation results show that the proposed algorithm can complement the existing satellite and terrestrial networks well in terms of coverage, with a communication coverage rate of more than 95%, which significantly improves the communication quality of marine users in areas far from land and beyond the reach of traditional networks, and enhances network reliability and user experience.

A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batteryless IoT Networks

The rapid advancement of Internet of Things (IoT) networks has revolutionized modern connectivity by integrating many low-power devices into various applications. As IoT networks expand, the demand for energy-efficient, batteryless devices becomes increasingly critical for sustainable future networks. These devices play a pivotal role in next-generation IoT applications by reducing the dependence on conventional batteries and enabling continuous operation through energy harvesting capabilities. However, several challenges hinder the widespread adoption of batteryless IoT devices, including the limited transmission range, constrained energy resources, and low spectral efficiency in IoT receivers. To address these limitations, reconfigurable intelligent surfaces (RISs) offer a promising solution by dynamically manipulating the wireless propagation environment to enhance signal strength and improve energy harvesting capabilities. In this paper, we propose a novel deep reinforcement learning (DRL) algorithm that optimizes the phase shifts of RISs to maximize the network’s achievable rate while satisfying IoT devices’ energy harvesting constraints. Our DRL framework leverages a novel six-dimensional chimp optimization algorithm (6DChOA) to fine-tune the hyper-parameters, ensuring efficient and adaptive learning. The proposed 6DChOA-DRL algorithm optimizes RIS phase shifts to enhance the received power of IoT devices while mitigating interference from direct and RIS-cascaded links. The simulation results demonstrate that our optimized RIS design significantly improves energy harvesting and achievable data rates under various system configurations. Compared to benchmark algorithms, our approach achieves higher gains in harvested power, an improvement in the data rate at a transmit power of 20 dBm, and a significantly lower root mean square error (RMSE) of 0.13 compared to 3.34 for standard RL and 6.91 for the DNN, indicating more precise optimization of RIS phase shifts.

Emergence of terbinafine-resistant Trichophyton indotineae in Ontario, Canada, 2014-2023.

Trichophyton indotineae is an emerging fungal pathogen capable of causing extensive recalcitrant dermatophytosis exacerbated by frequently retained terbinafine resistance. Cases of dermatophytosis due to T. indotineae have increased dramatically in India in recent years. Other countries have reported imported infection cases, causing public health concerns over the potential global spread of this drug-resistant pathogen. We describe T. indotineae from 47 clinical cases in Ontario, Canada, from 2014 to 2023, based on 50 isolates received by the provincial public health laboratory. Although detected in Ontario as early as 2014, cases increased sharply in 2022-2023. The majority of cases were found in 20 to 64-year-olds (83.0%). Cases from 2022 to 2023 were noted in only 8 of 34 public health units, clustering in large urban centers. Based on genomic epidemiology, Ontario isolates were genetically similar to isolates from other countries. Neither temporal nor geographic clustering based on country or public health unit was observed, suggesting Ontario cases represented recent introductions from endemic regions, although limited local transmission cannot be ruled out. Genome diversity (4.4 × 10-6) was extremely low, consistent with the hypothesized recent emergence and clonal population structure of T. indotineae. Most (71.4%) cases were terbinafine-resistant, with isolates exhibiting either the L393F/L393S (n = 3) or F397L (n = 27) squalene epoxidase substitution. Decreased susceptibility to itraconazole or voriconazole was found among 23.7% of isolates and was frequently associated with CYP51B gene duplication. Terbinafine-resistant T. indotineae infections are escalating in Ontario, meriting enhanced laboratory detection methods and public health efforts to increase the awareness of recalcitrant dermatophytoses in order to promptly initiate appropriate treatment and control transmission.IMPORTANCECases of dermatophytosis caused by emerging pathogen Trichophyton indotineae are increasing worldwide. Many are resistant to first-line treatment option terbinafine, resulting in difficult-to-treat cases. We describe the emergence of cases of T. indotineae infections in Ontario, Canada. The incidence in primarily urban centers increased dramatically in 2022-2023, with a large percentage of isolates resistant to terbinafine. Decreased susceptibility to azoles was also observed for some isolates, raising concern over the potential evolution of multi-drug resistance. Ontario T. indotineae isolates were genetically similar to those from disparate locales worldwide, signifying the global nature of this public health concern. Together with other reports, this study serves to raise public health awareness to promote better laboratory detection procedures, prompt appropriate treatment of recalcitrant dermatophytoses, and inform infection prevention and control measures.

On the Surface Hardening of Zinc Sulfide Windows by Gallium Sulfide.

This study examines the effect of gallium doping on the phase transformation, transmission, and hardness of commercial multispectral-grade ZnS specimens exposed to Ga2S3 vapor. Using secondary ion mass spectrometry, we show that Ga diffusion extends into the subsurface down to several tens of microns. X-ray diffraction patterns reveal minimal to no precipitation of wurtzite, resulting in limited infrared transmission loss after treatment. We report a monotonic increase in Vickers surface microhardness with increasing Ga concentration, reaching values more than double those of untreated windows. Future work will focus on optimizing this process and evaluating its effectiveness in enhancing the durability of ZnS windows under harsh environmental conditions.

Advanced data augmentation techniques coupled with enhanced particle swarm optimization for predicting total phosphorus concentrations in limited transmission spectra samples: A case study on the Yangtze River

Accurate prediction of total phosphorus concentration in water bodies is crucial for effective water pollution control and management. However, obtaining real-world water samples presents challenges such as being costly, time-consuming, or difficult. To boost prediction accuracy, this study introduces novel methodologies integrating advanced data augmentation techniques with enhanced optimization algorithms. In the data augmentation techniques, we employ a novel Oversampling Nearest Neighbor Generative Adversarial Network (ONNGAN) to augment the collected sample data, thereby mitigating issues arising from poor model training due to insufficient sample numbers. Regarding the enhanced particle swarm optimization, we introduce the Ant Colony Cooperative Particle Swarm Optimization (ACCPSO) algorithm, which enhances traditional particle swarm optimization by incorporating several strategic improvements. These enhancements reduce the likelihood of the algorithm getting stuck in local optima and accelerate its convergence speed. The ACCPSO algorithm is employed to automatically optimize the hyperparameter combinations for a Convolutional Neural Network (CNN), and the optimized CNN is then used to predict total phosphorus concentrations in water bodies. By combining these two advanced algorithms, we can more effectively explore the complex nonlinear relationships in transmission spectrum data, thereby enhancing prediction accuracy. The experimental results indicate that, following data augmentation, the ACCPSO-CNN model achieves an R2 of 0.9773, an RMSE of 0.0018, and an MAE of 0.0005, outperforming other benchmark models such as Support Vector Regression and Partial Least Squares Regression across all evaluation metrics. In summary, our research provides a powerful and practical tool for water quality monitoring and pollution control, offering broad application prospects.

Design and implementation of wireless power transfer device

Abstract. Magnetic coupled resonant radio energy transmission (WPT) technology utilizes the coupling of the magnetic fields of the transmitting and receiving coils and wirelessly transmits energy through electromagnetic induction, greatly expanding the applications of power equipment in special environments. The technology uses the magnetic field coupling between the transmitting coil and the receiving coil to realize the wireless transmission of energy through electromagnetic induction. This method breaks the limitation of traditional wire transmission and greatly expands the application potential of power equipment in various special environments. In this paper, an efficient, stable and long-distance wireless charging device is designed and realized. In order to improve transmission efficiency, two-coil configuration with series-series structure is adopted, and its equivalent circuit model is established by circuit theory and Kirchhoff's law. Therefore, a new radio energy transmission device based on single chip microcomputer is designed, including PWM signal generator, level matching circuit, high frequency inverter circuit and other key parts. Expressions for transmission efficiency and output power are derived from equation analysis and power-on experiments performed on a physical device. In addition, the effects of transmission frequency, load impedance and transmission distance on the performance are investigated.

Differentiation and quantification of bovine and pork gelatin using UPLC-QTOF and ATR-FTIR spectroscopy: Addressing challenges in mixed gelatin analysis and detection

The amino acid sequence dictates protein folding and spatial structure, essential for understanding their behavior. Gelatin, important in industry and biomedicine, demands accurate source authentication due to ethical and dietary concerns. This study explores differentiating and quantifying bovine and pork gelatin using UPLC-QTOF and ATR-FTIR spectroscopy. UPLC-QTOF identified distinct ions for pure bovine (m/z + 962.1471, NRLHFFK) and pork gelatin (m/z + 653.0289, YNEVK) but struggled with mixed gelatins due to protein-protein interactions altering peptide ion profiles. ATR-FTIR was employed to leverage ethanol's differential effects on gelatin's amide bands for quantifying pork gelatin contamination in bovine gelatin. The method showed a strong linear correlation (R2 = 0.9994) with contamination levels and amide band transmission, with detection and quantification limits of 0.85 and 2.85 mg/100 mg, respectively. It effectively identified pork gelatin in halal candy, with recovery rates from 50.05 % to 103.69 %, highlighting ATR-FTIR's potential for accurate gelatin analysis.

Clipper: Online Joint Client Sampling and Power Allocation for Wireless Federated Learning

Communication overhead is a main bottleneck in federated learning (FL) especially in the wireless environment due to the limited data rate and unstable radio channels. The communication challenge necessitates holistic selection of participating clients that accounts for both the computation needs and communication cost, as well as judicious allocation of the limited transmission resource. Meanwhile, the random unpredictable nature of both the training data samples and the communication channels requires an online optimization approach that adapts to the changing system state over time. In this work, we consider a general framework of online joint client sampling and power allocation for wireless FL under time-varying communication channels. We formulate it as a stochastic network optimization problem that admits a Lyapunov-typed solution approach. This leads to per-training-round subproblems with a special bi-convex structure, which we leverage to propose globally optimal solutions, culminating in a meta algorithm that provides strong performance guarantees. We further study three specific FL problems covering multiple scenarios, namely with IID or non-IID data, whether robustness against data drift is required, and with unbiased or biased client sampling. We derive detailed algorithms for each of these problems. Simulation with standard classification tasks demonstrate that the proposed communication-aware algorithms outperform their counterparts under a wide range of learning and communication scenarios.

Characterization of H5N1 avian influenza virus isolated from bird in Russia with the E627K mutation in the PB2 protein

Currently A(H5Nx) avian influenza viruses are globally widespread and continue to evolve. Since their emergence in 2020 novel highly pathogenic avian influenza A(H5N1) clade 2.3.4.4b reassortant viruses have become predominant in the world and caused multiple infections in mammals. It was shown that some of A(H5N1) viruses mostly isolated from mammals contain an E627K mutation in the PB2 protein which can lead to adaptation of influenza viruses to mammalian cells. In 2023 in Russia we have isolated two highly pathogenic avian influenza A(H5N1) clade 2.3.4.4b viruses from birds one of which contained an E627K mutation in the PB2 protein. This virus had increased virulence in mice. Limited airborne transmission of the virus with the PB2-E627K mutation was observed between ferrets, in which infectious virus was detected in the nasal washings of the three of the twelve recipient ferrets, and clinical symptoms of the disease were observed in one case. Both viruses showed dominant binding to avian-type sialoside receptors, which was most likely the reason for the limited transmissibility. Thus, this study indicates a possible limited increase in the pandemic potential of A(H5N1) 2.3.4.4b viruses and highlights the importance of continuous avian influenza surveillance for pandemic preparedness and response.

Approximation-based adaptive two-bit-triggered bipartite tracking control for nonlinear networked MASs subject to periodic disturbances

PurposeThis paper aims to investigate the problem of adaptive bipartite tracking control in nonlinear networked multi-agent systems (MASs) under the influence of periodic disturbances. It considers both cooperative and competitive relationships among agents within the MASs.Design/methodology/approachIn response to the inherent limitations of practical systems regarding transmission resources, this paper introduces a novel approach. It addresses both control signal transmission and triggering conditions, presenting a two-bit-triggered control method aimed at conserving system transmission resources. Additionally, a command filter is incorporated to address the problem of complexity explosion. Furthermore, to model the uncertain nonlinear dynamics affected by time-varying periodic disturbances, this paper combines Fourier series expansion and radial basis function neural networks. Finally, the effectiveness of the proposed methodology is demonstrated through simulation results.FindingsBased on neural networks and command filter control method, an adaptive two-bit-triggered bipartite control strategy for nonlinear networked MASs is proposed.Originality/valueThe proposed control strategy effectively addresses the challenges of limited transmission resources, nonlinear dynamics and periodic disturbances in networked MASs. It guarantees the boundedness of all signals within the closed-loop system while also ensuring effective bipartite tracking performance.

Investigation of metal-insulator-metal waveguides with elliptical-nanodisk resonator for high contrast ratio all-optical logic gates

Abstract This research focuses on the design and analysis of all-optical Exclusive OR(XOR), NOT, and OR logic gates based on metal-insulator-metal waveguides with elliptical-nanodisk resonators. The functionality of the proposed optical logic gates is determined by constructive and deconstructive signals which are applied to the input ports and control ports. To show the logic 0 (low) and logic 1 (high) output states, the limit of threshold transmission is 1.775 × 10−13 ∼0. The transmission (T) and contrast ratio (CR) are obtained to present the performance of the optical logic gates via the method of finite-difference time-domain. The maximum transmission is reached for the OR gate as 1.38 and the highest contrast ratio is 124.75 dB for the XOR and NOT logic gates. The designed logic devices are promising for improving more efficient optical signal information processing devices.

Assessment of Cooling Conditions of Thermoplastic Insulation and Uniformity of Breakdown Strength for Medium-Voltage Direct Current Extruded Cable Insulation

Research has been conducted on medium-voltage direct current (MVDC) to address the limited transmission capacity of existing AC power transmission lines and to achieve efficient integration of renewable energy sources. Another method to increase the transmission capacity is to raise the maximum allowable temperature of the power cable. The maximum allowable temperature for cross-linked polyethylene (XLPE) in commercial power cables is 90 °C. Polypropylene (PP) is considered as an alternative material. PP has a maximum allowable temperature of 110 °C and possesses thermoplastic properties, making it environmentally friendly. However, PP may not ensure uniformity of the insulation layer depending on the extrusion process, including cooling conditions. This study aimed to determine the applicability of MVDC cables by assessing the uniformity of the insulation layer of extruded cables, considering the cooling conditions of PP in specimens. For the cooling conditions, ambient air, cooling press, and water cooling were evaluated for DC breakdown strength. Furthermore, the uniformity of the breakdown strength of the insulation layer, which was divided into sections such as conductor and sheath, was evaluated for commercial PP, XLPE, and the developed PP cables. This study aims to provide a comprehensive analysis of the DC BD strength of PP under various cooling conditions and emphasize the importance of uniformity in extruded cable sections.

Overcoming the Rayleigh Backscattering Limit of Same-Wavelength Bidirectional Transmission Using Phase-Sensitive Amplification

Overcoming the Rayleigh Backscattering Limit of Same-Wavelength Bidirectional Transmission Using Phase-Sensitive Amplification

Optical networking that exploits massive wavelength/spectrum and spatial parallelisms

As DWDM transmission offers enhanced wavelength/spectrum parallelism, the capacity of optical networks has been substantially increased. Due to the theoretical capacity limit of C-band transmission over single-mode fibers, research into new frequency bands and parallel fibers has become very active. However, the hardware scale of current optical cross-connect nodes will explode with greater wavelength/spectrum and spatial parallelism. Three optical node/network architectures are presented in this paper that take advantage of one or both of these parallelism technologies. These architectures will provide a baseline for cost-effective and bandwidth-abundant future optical networks based on massive parallelism.

Dairy cows inoculated with highly pathogenic avian influenza virus H5N1

Highly pathogenic avian influenza (HPAI) H5N1 haemagglutinin clade 2.3.4.4b was detected in the USA in 2021. These HPAI viruses caused mortality events in poultry, wild birds and wild mammals. On 25 March 2024, HPAI H5N1 clade 2.3.4.4b was confirmed in a dairy cow in Texas in response to a multistate investigation into milk production losses1. More than 200 positive herds were identified in 14 US states. The case description included reduced feed intake and rumen motility in lactating cows, decreased milk production and thick yellow milk2,3. The diagnostic investigation revealed viral RNA in milk and alveolar epithelial degeneration and necrosis and positive immunoreactivity of glandular epithelium in mammary tissue. A single transmission event, probably from birds, was followed by limited local transmission and onward horizontal transmission of H5N1 clade 2.3.4.4b genotype B3.13 (ref. 4). Here we sought to experimentally reproduce infection with genotype B3.13 in Holstein yearling heifers and lactating cows. Heifers were inoculated by an aerosol respiratory route and cows by an intramammary route. Clinical disease was mild in heifers, but infection was confirmed by virus detection, lesions and seroconversion. Clinical disease in lactating cows included decreased rumen motility, changes to milk appearance and production losses. Infection was confirmed by high levels of viral RNA detected in milk, virus isolation, lesions in mammary tissue and seroconversion. This study provides the foundation to investigate additional routes of infection, pathogenesis, transmission and intervention strategies.