Single Pass Research Articles

Scalable Video Object Segmentation With Identification Mechanism.

This paper delves into the challenges of achieving scalable and effective multi-object modeling for semi-supervised Video Object Segmentation (VOS). Previous VOS methods decode features with a single positive object, limiting the learning of multi-object representation as they must match and segment each target separately under multi-object scenarios. Additionally, earlier techniques catered to specific application objectives and lacked the flexibility to fulfill different speed-accuracy requirements. To address these problems, we present two innovative approaches, Associating Objects with Transformers (AOT) and Associating Objects with Scalable Transformers (AOST). In pursuing effective multi-object modeling, AOT introduces the IDentification (ID) mechanism to allocate each object a unique identity. This approach enables the network to model the associations among all objects simultaneously, thus facilitating the tracking and segmentation of objects in a single network pass. To address the challenge of inflexible deployment, AOST further integrates scalable long short-term transformers that incorporate scalable supervision and layer-wise ID-based attention. This enables online architecture scalability in VOS for the first time and overcomes ID embeddings' representation limitations. Given the absence of a benchmark for VOS involving densely multi-object annotations, we propose a challenging Video Object Segmentation in the Wild (VOSW) benchmark to validate our approaches. We evaluated various AOT and AOST variants using extensive experiments across VOSW and five commonly used VOS benchmarks, including YouTube-VOS 2018 & 2019 Val, DAVIS-2017 Val & Test, and DAVIS-2016. Our approaches surpass the state-of-the-art competitors and display exceptional efficiency and scalability consistently across all six benchmarks. Moreover, we notably achieved the 1st position in the 3 rd Large-scale Video Object Segmentation Challenge.

Crude oil-water emulsions formed by nozzle type inflow control device

Conventional water-in-oil emulsion studies where shear energy intensity and duration are applied to achieve ‘equilibrium’ emulsion droplet properties may not represent partial emulsion conditions observed in single pass flow through Inflow Control Device (ICD) orifices. Our experiments provide data expected to improve emulsion transport models for partial emulsification processes expected in well completion and production tubulars. Development of a novel flow adaptor apparatus is described together with a laboratory homogeniser enables independent control of shear intensity and duration together with input water volume fraction. The emulsions formed are characterised with a benchtop Nuclear Magnetic Resonance spectrometer for water content and droplet size, viscosity by a rotating bob viscometer and free water/emulsion proportion by optical photography. Experimental results confirmed partial emulsification above 30% V/V, as observed in both previous ICD flow experiments and field observations. Electrical conductivity measurements of the emulsions produced indicated that partial emulsification comprising an oil external emulsion phase together with free water, rather than emulsion inversion, occurs in this system.

Process Parameters Optimization and Numerical Simulation of AlCoCrFeNi High-Entropy Alloy Coating via Laser Cladding.

The use of laser cladding technology to prepare coatings of AlCoCrFeNi high-entropy alloy holds enormous potential for application. However, the cladding quality will have a considerable effect on the properties of the coatings. In this study, considering the complex coupling relationship between cladding quality and the process parameters, an orthogonal experimental design was employed, with laser power, scanning speed, and powder feed rate as correlation factor variables, and microhardness, dilution rate, and aspect ratio as characteristic variables. The experimental data underwent gray correlation analysis to determine the effect of various process parameters on the quality of cladding. Then, the NSGA-II algorithm was used to establish a multi-objective optimization model of process parameters. Finally, the ANSYS Workbench simulation model was employed to conduct numerical simulations on a group of optimized process parameters and analyze the change rule of the temperature field. The results demonstrate that the laser cladding coating of AlCoCrFeNi high-entropy alloy with the single pass is of high quality within the determined orthogonal experimental parameters. The powder feed rate exerts the most significant influence on microhardness, while laser power has the greatest impact on dilution rate, and scanning speed predominantly affects aspect ratio. The designed third-order polynomial nonlinear regression model exhibits a high fitting accuracy, and the NSGA-II algorithm can be used for multi-objective optimization to obtain the Pareto front solution set. The numerical simulation results demonstrate that the temperature field of AlCoCrFeNi high-entropy alloy laser cladding exhibits a "comet tail" phenomenon, where the highest temperature of the molten pool is close to 3000 °C. The temperature variations in the molten pool align with the features of laser cladding technology. This study lays the groundwork for the widespread application of laser cladding AlCoCrFeNi high-entropy alloy in surface engineering, additive manufacturing, and remanufacturing. Researchers and engineering practitioners can utilize the findings from this research to judiciously manage processing parameters based on the results of gray correlation analysis. Furthermore, the outcomes of multi-objective optimization can assist in the selection of appropriate process parameters aligned with specific application requirements. Additionally, the methodological approach adopted in this study offers valuable insights applicable to the exploration of various materials and diverse additive manufacturing techniques.

Laser microdissection system based on structured light modulation dual cutting mode and negative pressure adsorption collection.

Laser microdissection technology is favored by biomedical researchers for its ability to rapidly and accurately isolate target cells and tissues. However, the precision cutting capabilities of existing laser microdissection systems are hindered by limitations in overall mechanical movement accuracy, resulting in suboptimal cutting quality. Additionally, the use of current laser microdissection systems for target acquisition may lead to tissue burns and reduced acquisition rates due to inherent flaws in the capture methods. To address these challenges and achieve precise and efficient separation and capture of cellular tissues, we integrated a digital micromirror device (DMD) into the existing system optics to modulate spatial light. This allows the system to not only implement the traditional point scanning cutting method but also utilize the projection cutting method.We have successfully cut various patterns on commonly used laser microdissection materials such as PET films and mouse tissues. Under projection cutting mode, we were able to achieve precise cutting of special shapes with a diameter of 7.5 micrometers in a single pass, which improved cutting precision and efficiency. Furthermore, we employed a negative pressure adsorption method to efficiently collect target substances. This approach not only resulted in a single-pass capture rate exceeding 90% for targets of different sizes but also enabled simultaneous capture of multiple targets, overcoming the limitations of traditional single-target capture and enhancing target capture efficiency, and avoiding potential tissue damage from lasers.In summary, the integration of the digital micromirror device into laser microdissection systems significantly enhances cutting precision and efficiency, overcoming limitations of traditional systems. This advancement demonstrates the accuracy and effectiveness of laser microdissection systems in isolating and capturing biological tissues, highlighting their potential in medical applications.

Investigations of the Laser Ablation Mechanism of PMMA Microchannels Using Single-Pass and Multi-Pass Laser Scans.

CO2 laser machining is a cost effective and time saving solution for fabricating microchannels on polymethylmethacrylate (PMMA). Due to the lack of research on the incubation effect and ablation behavior of PMMA under high-power laser irradiation, predictions of the microchannel profile are limited. In this study, the ablation process and mechanism of a continuous CO2 laser machining process on microchannel production in PMMA in single-pass and multi-pass laser scan modes are investigated. It is found that a higher laser energy density of a single pass causes a lower ablation threshold. The ablated surface can be divided into three regions: the ablation zone, the incubation zone, and the virgin zone. The PMMA ablation process is mainly attributed to the thermal decomposition reactions and the splashing of molten polymer. The depth, width, aspect ratio, volume ablation rate, and mass ablation rate of the channel increase as the laser scanning speed decreases and the number of laser scans increases. The differences in ablation results obtained under the same total laser energy density using different scan modes are attributed to the incubation effect, which is caused by the thermal deposition of laser energy in the polymer. Finally, an optimized simulation model that is used to solve the problem of a channel width greater than spot diameter is proposed. The error percentage between the experimental and simulation results varies from 0.44% to 5.9%.

Effects of Autogenous Gas Tungsten Arc Welding (GTAW) on Corrosion Resistance of Stainless Steel 316L

The autogenous manual gas tungsten arc welding (GTAW) process was used for cladding austenitic stainless steel 316L using a single pass with various contact tip-to-work distances (CTWDs). Immersion and electrochemical tests were used to evaluate the corrosion resistance of the welded specimens, and a microstructural analysis was conducted to investigate the chemical composition of the molten pool and the heat-affected zone of welding. The key findings of this study indicate that the corrosion resistance improved under a CTWD of 5 mm due to the optimal distribution of ferrite and a refined microstructure. Additionally, the highest hardness was observed in specimens with a CTWD of 3 mm, attributed to the increased ferrite content in the weld metal. As the CTWD increased, the ferrite fraction decreased, and the hardness also diminished. However, in the CTWD 7 mm case, the higher heat input influenced the microstructure and molten pool shape significantly through the Marangoni effect, resulting in a lower corrosion resistance. These results suggest that optimizing the CTWD can enhance the corrosion resistance of welded 316L stainless steel.

Human Eyes-Inspired Recurrent Neural Networks Are More Robust Against Adversarial Noises.

Humans actively observe the visual surroundings by focusing on salient objects and ignoring trivial details. However, computer vision models based on convolutional neural networks (CNN) often analyze visual input all at once through a single feedforward pass. In this study, we designed a dual-stream vision model inspired by the human brain. This model features retina-like input layers and includes two streams: one determining the next point of focus (the fixation), while the other interprets the visuals surrounding the fixation. Trained on image recognition, this model examines an image through a sequence of fixations, each time focusing on different parts, thereby progressively building a representation of the image. We evaluated this model against various benchmarks in terms of object recognition, gaze behavior, and adversarial robustness. Our findings suggest that the model can attend and gaze in ways similar to humans without being explicitly trained to mimic human attention and that the model can enhance robustness against adversarial attacks due to its retinal sampling and recurrent processing. In particular, the model can correct its perceptual errors by taking more glances, setting itself apart from all feedforward-only models. In conclusion, the interactions of retinal sampling, eye movement, and recurrent dynamics are important to human-like visual exploration and inference.

Endovascular thrombectomy first-pass reperfusion and ancillary device placement

BackgroundRecent randomized trials have demonstrated the efficacy of mechanical thrombectomy in treating acute ischemic stroke, however, further research is required to optimize this technique. We aimed to evaluate the impact...

Investigation of the effect of residual waviness formed by rail profile milling of reshaped surface on wheel-rail contact stresses and low cyclic fatigue

The rail profile milling process allows considerable thickness to be removed in a single pass. However, the residual waviness formation law after milling and its subsequent effect on rail performance remains uncertain. In this paper, the wavelength and wave height of the residual waviness are identified as the key characteristics. The relationship between milling speed and residual waviness is determined, and a numerical model of the residual waviness formed on the surface after milling is established based on the commonly used three milling speeds of 300, 600, and 1000 m/h, and its accuracy is verified using the parameters of the residual waviness detected by the milling experiments. A three-dimensional finite element analysis model of wheel-rail contact was employed to analyze the contact stresses and low fatigue cycles at a wheel load of 11.5 tons with no residual waviness on the rail profile surface and with three types of residual waviness, respectively. The results show that the residual waviness changes the wheel-rail contact position and the morphology of the contact area, reduces the maximum contact stress and increases the strain fatigue cycles. The application of elevated milling speeds reduces the wheel-rail contact stresses after milling, thereby increasing the low fatigue cycles.

Optimization of ammonia production unit using polymeric membrane: Re-design of ammonia synthesis reactor feeding strategy and methane removal

The optimization of an industrial-scale ammonia production reactor is studied in the present work by re-designing the ammonia synthesis reactor and using a membrane. After simultaneous modeling and simulation of the ammonia synthesis reactor and the membrane unit, the maximization of ammonia production rate was investigated. The simulation results for a single pass through the reactor showed that removing methane, increasing the nitrogen flow, and combining these two cases increased ammonia production efficiency by 1 %, 15 %, and 19 %, respectively. Furthermore, for the reactor with the recycle stream, the efficiency of ammonia production can be increased by 2.74 % by re-designing the feeding strategy and optimization of the reactor. For this purpose, the PFMMD–CTFE copolymer membrane with a total area of 1550 m2 is required to separate methane, and the cellulose acetate membrane with a total area of 1343.9 m2 should be used to provide the required amount of nitrogen injection.

Clasp pass moves and arrow polynomials of virtual knots

For classical knots, clasp pass moves are closely related to Vassiliev invariants of degree [Formula: see text]. Tsukamoto showed that the values of the Vassiliev invariant of degree [Formula: see text] induced from the Jones polynomial for two knots differ by [Formula: see text] or [Formula: see text], if they are related by a single clasp pass move. For virtual knots, the arrow polynomial is a generalization of the Jones polynomial and induces a Vassiliev invariant of degree [Formula: see text]. We show that the values of the Vassiliev invariant of degree [Formula: see text] induced from the arrow polynomial of two virtual knots differ by [Formula: see text] or [Formula: see text], if they are related by a single clasp pass move. We also obtain a lower bound of the distance between virtual knots by clasp pass moves.

CO2 Reduction in a Bio Mass-Paired Systems for the Production of e-Chemicals

The electrification of chemical manufacturing is an important pathway toward reduced CO2 emissions. Direct electrochemical CO2 reduction can thereby become a key technology. CO2 electrolyzers produce cathodically platform chemicals as CO, format, ethanol or ethylene. The state-of-the-art anode process is the oxygen electro evolution which suffers from high over potentials and moderate valorization. An alternative is the anodic oxidation of biomass to valorized carbonaceous products, such as the oxidation of hydroxymethylfurfural (HMF) to the biopolymer precursor 2.5-furandicarboxylic acid (FDCA).In this work we report the design of electrolyzers flow cells with paired valorization of biomass and CO2. NiNC cathode GDEs are used for CO2 reduction to CO and NiFe-LDH anodes for the HMF oxidation in a zero-gap membrane electrolyzer flow cells. We used a bipolar membrane to separate and optimize either half-cell reactions. Inside the membrane, water is dissociated and the protons will neutralize carbonates on the cathode which is beneficial for a higher CO2 utilization and single pass. So, we can report close to 95% FE and 100% utilization efficiency towards CO.On the other hand, the hydroxide will stabilize the anode pH and enable PGM-free anodes compared to AEM CO2 electrolyzer. State-of-the-art HMF oxidation is a semi-batch setup, in which the HMF containing anolyte is recycled to complete HMF depletion and utilization. This design suffered from severe mass limitations. Therefore, we modified the semi-batch process into a continuous process and made tradeoffs between faradaic efficiency and utilization. As HMF is not stable in alkaline solutions we decided that a high utilization is beneficial because the intermediates are stable and could be recycled. We can report a single pass conversion of around 70 % towards FDCA at 200 mA cm-2 at a total utilization of 90%.Figure caption: Paired continuous HMF/CO2 electrolyzer with performance parameter. Figure 1

A Tandem Photovoltaic-Electrochemical Photothermal Process for CO2 Conversion to Butene

Decarbonizing the chemicals industry requires net carbon negative technologies capable of displacing current greenhouse gas emitting processes. In particular, the generation of valuable monomers, such as butene, are currently produced by significant greenhouse gas emitting processes, including ethylene oligomerization and crude oil refining, which require high temperatures and pressures. Integrated, tandem solar fuels devices for the conversion of CO2 to ethylene, using solar-driven CO2 reduction (CO2R), combined with a photothermal reactor for ethylene oligomerization, offers a potential path to producing clean butene from CO2, using solar energy as the only driving force. A key challenge for the successful operation of a tandem photo-driven electrochemical-photothermal system is the co-design of the two processes, which are typically optimized under different operating conditions. Specifically, photo-driven electrochemical CO2R (pCO2R) reactors operate under ambient temperature and pressure conditions while thermally-driven ethylene oligomerization reactors prefer elevated temperatures (80-140 °C) and pressures (30-150 atm) to promote high activity as well as pure ethylene in the inlet stream. Operation of the tandem process under solar-driven conditions imposes additional constraints on the maximum power output of the pCO2R reactor and the maximum temperature which can be obtained in the photothermal reactor. Herein, we present an unassisted solar-driven tandem system coupling pCO2R with photothermal ethylene oligomerization for the conversion of CO2 to butene in a single pass. This work presents a critical advancement in the development of solar fuels technologies for larger hydrocarbon generation and identifies the co-design principles which must be considered for implementation of tandem, solar-driven electrochemical-thermal processes.

Efficient Ni-NC Gas Diffusion Electrodes for CO2 Electrolyzer with High Utilization Efficiencies and Single Pass Conversions Towards CO

The electrochemical CO2 reduction in membrane electrolyzer devices can become a key technology to close the anthropologic carbon cycle. For industrialisation of CO2 electrolyzers, however, performance shortcomings of today’s state-of-art electrolyzer designs and cathodes have to be addressed. Alkaline Membrane CO2 electrolyzers suffer from low utilization efficiency of CO2 due to an acid-base CO2 loss to carbonates, which limits the CO2 utilization efficiency and single pass conversion to 50% in AEM CO2-to-CO electrolyzer. Bipolar Membrane CO2 electrolyzers suffer from high cell voltage and lower Faradic efficiencies due to the acidic environment. All thoses designs suffer from layer flooding or salting events which limit the durability of the cells. New cell designs and new diagnostic tools are needed to predict, diagnose, and eliminate detrimental operating regimes of CO2 electrolyzers.In this work, we report on NiNC catalyst-based cathode GDEs for CO2 reduction to CO in a zero-gap membrane electrolyzer cell. We compare AEM and BPM cell designs. We propose the carbon crossover coefficient, CCC, as a new diagnostic analysis tool to monitor and understand through- or in-plane mass transport limitations in AEM and BPM cells. We also demonstrate how N2 bleeds can be used as diagnostic tools to recognize salting inside the electrolyzer cell.In our AEM studies, we show that sufficient CO2 access to the catalyst surface sites is important to achieve a high performance. Under near neutral conditions on the anode we report 85% FE towards CO at 300 mA cm-2 at 3.6 V with single pass conversion of 40% which is very close to the theoretical maximum. In addition, we can report high energy efficiency but only a utilization efficiency of around 50%.In our BPM studies, we show that NiNC GDEs are active and stable cathodes in zero-gap membrane electrolyzer. Protons raise the utilization efficiency as the carbonate will decompose into CO2 and water. To handle the changed electro osmotic water drag we replaced the ionomer with PTFE and could achieve 82% FE and 69% single pass conversion at 500 mA cm-2 with close to 100% CO2 utilization efficiency towards CO.We show that using a either an AEM or BPM electrolyzer design we can reach over 100h stable performance at 100 mA cm-2.Figure caption: CO2 singel pass conversion and lambda comparison of AEM and BPM CO2 reduction electrolyzer cells. Figure 1

Role of Activating Flux in Weld Bead Symmetricity during Dissimilar Metal Joining

Ferritic/martensitic steels and austenitic stainless steels are high‐strength steels, and highly recommended in high‐temperature and high‐pressure application. In general, multimetallics with different Inconel alloys are used for joining. This is quite a complex and time‐consuming procedure. The current work demonstrates the efforts made to weld 8 mm‐thick P91 steel and 316L SS plates in a single pass using activating flux tungsten inert gas (A‐TIG) welding process without any interlayers. The main challenge is to get the symmetric weld bead profile. Flux coating is optimized in terms of flux composition, coating density, and coating pattern to get the full penetration with symmetric appearance. The current work discusses the possible cause and their solution of asymmetricity during dissimilar welding. Differential flux coating density is found to be very effective in controlling the arc column shape, fluid flow, and consequently the bead geometry. High coating density is used in the P91 side compared to 316L side. Symmetric weld profile with full penetration is achieved by applying multicomponent flux (33–38% TiO2, 38–43% SiO2, 13–17% NiO, and 8–10% CuO) during A‐TIG welding.

Development of a flexible arrayed eddy current sensor with three-phase excitation for inspection of rail rolling contact fatigue cracks

A Flexible Arrayed Eddy Current (FAEC) sensor can inspect a large area in a single probe pass, which is beneficial for customizing the profile of the inspected part. This paper presents the development of a flexible arrayed eddy current sensor with three-phase excitation for inspection of Rolling Contact Fatigue (RCF) cracks in rail. The excitation coils are driven by three-phase currents that are 120° apart in phase. The induced eddy current in the conductive rail sample shifts electrically along the phase variation direction of the excitation currents. The sensor measures a small background signal to determine if there is no defect in the rail sample. Therefore, the sensor has a high relative sensitivity to defects. We study the operating principle of the sensor using a 3D finite element method (FEM) model. The numerical results demonstrate the sensor's viability for fast inspection and characterization to detect RCF defects in conductive rail steel samples.

Thermal and electrical performance evaluation of single and double pass photovoltaic-thermal solar collector with cross-flow baffles and varying transparency: A computational analysis

The present work deals with the development of a semi-transparent photovoltaic thermal (PV-T) solar collector (STPVT) through computational fluid dynamics (CFD) modelling using COMSOL Multiphysics. The study was carried out in three stages; firstly, the CFD model was developed for STPVT and validated with experimental data. Secondly, three different configurations of semi-transparent PV-T collector were investigated, i.e., single pass with PV module on top (SPC), double pass with PV module on top followed by glass cover and absorber plate (DPT), and double pass with PV module in between the glass cover and absorber plate (DPS). The absorber plate was incorporated with cross-flow baffles for improved thermal performance due to increased surface area and turbulence. The study found a thermal efficiency of 76.94 % for DPS configuration and a total heat utilisation of 289.63 W at 50 % transparency level, i.e., 2–4 times higher than other configurations. Furthermore, the DPS model was investigated for thermal and electrical performance with different PV module transparency levels (52,42,27,13 %). The DPS with 18 solar cells having 13 % transparency exhibited peak power density (8 %) at 717 W/m2 and 101.89 °C panel temperature, achieving superior thermal efficiency (84 %) and total heat utilisation (315.09 W), surpassing configurations with higher transparency.

Multi-Person Pose Regression With Distribution-Aware Single-Stage Models.

Understanding human posture is a challenging topic, which encompasses several tasks, e.g., pose estimation, body mesh recovery and pose tracking. In this article, we propose a novel Distribution-Aware Single-stage (DAS) model for the pose-related tasks. The proposed DAS model estimates human position and localizes joints simultaneously, which requires only a single pass. Meanwhile, we utilize normalizing flow to enable DAS to learn the true distribution of joint locations, rather than making simple Gaussian or Laplacian assumptions. This provides a pivotal prior and greatly boosts the accuracy of regression-based methods, thus making DAS achieve comparable performance to the volumetric-based methods. We also introduce a recursively update strategy to progressively approach the regression target, reducing the difficulty of regression and improving the regression performance. We further adapt DAS to multi-person mesh recovery and pose tracking tasks and achieve considerable performance on both tasks. Comprehensive experiments on CMU Panoptic and MuPoTS-3D demonstrate the superior efficiency of DAS, specifically 1.5 times speedup over previous best method, and its state-of-the-art accuracy for multi-person pose estimation. Extensive experiments on 3DPW and PoseTrack2018 indicate the effectiveness and efficiency of DAS for human body mesh recovery and pose tracking, respectively, which prove the generality of our proposed DAS model.

Design and assessment of tractor-driven chopping tilling and mixing machine for in-situ management of paddy straw

In many Indian regions, paddy wheat is the main crop rotation and facing the problem of straw incorporation for seed bed preparation in short period. The handling of straw in combine harvested paddy fields is a significant issue in the paddy wheat rotation. In order to solve this issue, efforts were carried out to cut paddy straw into small pieces by the newly proposed counter-rotating blades, followed by the simultaneous incorporation of a rotary tiller into the soil. Therefore, a tractor operated chopping cum tilling mixing machine was developed. In the study, three different blades (straw management system (SMS) Serrated, cutter bar and SMS plain) were tested in the terms of torque and required to chop the straw. SMS serrated blade was best suitable for the chopping mechanism as it required minimum cutting torque for the straw bunches. The developed chopping cum tilling mixing machine was tested at three different levels of forward speed (1.77, 2.3, and 3 km h−1), moisture content at three levels (35 ± 3.4, 24 ± 2.2 and 17 ± 2.6%) with fix rotary tiller rotational speed of 810 rev min−1. Optimum operating condition of the machine was obtained at a forward speed of 1.9 km h−1 and a moisture of 24%. At these optimized values, the mixing index (96%), mean weight diameter (7.9 mm), bulk density (1230 g cc−1) and fuel consumption (3 l h−1) were 96%, 7.9 mm, 1230 g cc−1 and 3.0 l h−1 respectively. The developed machine performs three operations i.e., chopping, tilling, and mixing in single pass for effective in-situ straw management.

Portable UV-C Device to Treat High Flow of Infectious Aerosols Generated during Clinical Respiratory Care.

Respiratory interventions including noninvasive ventilation, continuous positive airway pressure and high-flow nasal oxygen generated infectious aerosols may increase risk of airborne disease (SARS-CoV-2, influenza virus) transmission to healthcare workers. We developed/tested a prototype portable UV-C254 device to sterilize high flows of viral-contaminated air from a simulated patient source at airflow rates of up to 100 l/m. Our device consisted of a central quartz tube surrounded 6 high-output UV-C254 lamps, within a larger cylinder allowing recirculation past the UV-C254 lamps a second time before exiting the device. Testing was with nebulized A/PR/8/34 (H1N1) influenza virus. RNA extraction and qRT-PCR showed virus transited through the prototype. Turning on varying numbers of lamps controlled the dose of UVC. Viability experiments at low, medium and high (100 l/min) flows of contaminated gas were conducted with 6, 4, 2 and 1 lamp activated (single-pass and recirculation were tested). Our data show 5-log reduction in particle forming units from a single lamp (single- pass and recirculated conditions) at high and low flows. UVC dose at 100 l/m was calculated at 11.6 mJ/cm2 single pass and 104 mJ/cm2 recirculated. The protype device shows high efficacy in killing nebulized influenza virus in a high flow of contaminated air.