Search Results (168)

This study is the first to investigate the performance of ultraviolet germicidal irradiation (UVGI) in underfloor air distribution (UFAD) systems. A simplified mathematical model is developed to predict airborne pathogen transport and inactivation by upper room UVGI in UFAD spaces. The proposed model is substantiated for the SARS-CoV-2 virus as a simulated pathogen through a comprehensive computational fluid dynamics methodology validated against published experimental data of upper room UVGI and UFAD flows. Simulations show an 11% decrease in viral concentration within the upper irradiated zone when a 15 W louvered germicidal lamp is utilized. Finally, a case study on Mycobacterium tuberculosis (M. tuberculosis) bacteria is carried out using the validated simplified model to optimize the use of return air and UVGI implementation, ensuring acceptable indoor air quality and enhanced energy efficiency. Results reveal that the UFAD-UVGI system may consume up to 13.6% less energy while keeping the occupants at acceptable levels of M. tuberculosis concentration and UV irradiance when operated with 26% return air and a UVGI output of 72 W. Full article

In order to achieve 0.1 m resolution and fully polarimetric observation capabilities for airborne SAR systems, the adoption of stepped-frequency modulation waveform combined with the polarization time-division transmit/receive (T/R) technique proves to be an effective technical approach. Considering the issue of range resolution degradation and paired echoes caused by multichannel amplitude–phase mismatch in fully polarimetric airborne SAR with 0.1 m resolution, an amplitude–phase error estimation algorithm based on echo data is proposed in this paper. Firstly, the subband amplitude spectrum correction curve is obtained by the statistical average of the subband amplitude spectrum. Secondly, the paired-echo broadening function is obtained by selecting high-quality sample points after single-band imaging and the nonlinear phase error within the subbands is estimated via Sinusoidal Frequency Modulation Fourier Transform (SMFT). Thirdly, based on the minimum entropy criterion of the synthesized compressed pulse image, residual linear phase errors between subbands are quickly acquired. Finally, two-dimensional cross-correlation of the image slice is utilized to estimate the positional deviation between polarization channels. This method only requires high-quality data samples from the echo data, then rapidly estimates both intra-band and inter-band amplitude/phase errors by using SMFT and the minimum entropy criterion, respectively, with the characteristics of low computational complexity and fast convergence speed. The effectiveness of this method is verified by the imaging results of the experimental data. Full article

Detecting airborne viruses using an integrated aerosol sampling detection device is of great significance in epidemic prevention and control. Most of the applicable aerosol samplers have a flow rate of less than 1000 L/min, which is insufficient for application in large public spaces. Recent research, on the other hand, has revealed the advantages of microfluidic chip-based LAMP–CRISPR in airborne virus detection; however, this promising detection method has yet to be integrated with an aerosol sampler. Herein, we present an aerosol sampling and microfluidic chip-based detection (ASMD) device that couples a high-flow-rate aerosol sampling (HFAS) system with a microfluidic LAMP–CRISPR detection (MLCD) chip for surveilling airborne viruses, as represented by SARS-CoV-2. The HFAS system achieved a 6912 L/min flow rate while retaining a satisfactory collection efficiency, and achieved an enrichment ratio of 1.93 × 10⁷ that facilitated subsequent detection by the MLCD chip. The MLCD chip integrates the whole LAMP–CRISPR procedure into a single chip and is compatible with the HFAS system. Environmental detection experiments show the feasibility of the ASMD device for aerosol sampling and detection. Our ASMD device is a promising tool for large space aerosol detection for airborne virus surveillance. Full article

Airborne respiratory viruses (e.g., influenza, respiratory syncytial virus (RSV), and SARS-CoV-2) continue to pose a serious threat to global public health due to their ability to spread through multiple transmission pathways. Among these, aerosol transmission stands out as a key route, particularly in enclosed environments. However, current monitoring systems have major limitations in sensitivity, standardization, and high time resolution. This study provides a summary of the latest information on the monitoring technologies for respiratory virus aerosols. It discusses the technical and ethical challenges in real-world applications. In addition, this study proposes practical solutions and future development pathways. The aim of this study is to provide theoretical support for building a dynamic, precise, and effective early warning system for monitoring variants of airborne respiratory viruses Full article

Background/Objectives: Airborne viral diseases pose a health risk, due to which there is a growing interest in developing filter materials capable of capturing fine particles containing virions from the air and that also have a virucidal effect. Nanofiber membranes made of poly(vinylidene fluoride) dissolved in N,N-dimethylacetamide and functionalized with copper, silver, and zinc nanoclusters were fabricated via electrospinning. This study aims to evaluate and compare the virucidal effects of nanofibers functionalized with metal nanoclusters against the human influenza A virus A/WSN/1933 (H1N1) and SARS-CoV-2. Methods: A comprehensive characterization of materials, including X-ray diffraction, scanning electron microscopy, microwave plasma atomic emission spectroscopy, thermogravimetric analysis, contact angle measurements, nitrogen sorption analysis, mercury intrusion porosimetry, filtration efficiency, and virucidal tests, was used to understand the interdependence of the materials’ physical characteristics and biological effects, as well as to determine their suitability for application as antiviral materials in air filtration systems. Results: All the filter materials tested demonstrated very high particle filtration efficiency (≥98.0%). The material embedded with copper nanoclusters showed strong virucidal efficacy against the SARS-CoV-2 alpha variant, achieving an approximately 1000-fold reduction in infectious virions within 12 h. The fibrous nanowire polymer functionalized with zinc nanoclusters was the most effective material against the human influenza A virus strain A/WSN/1933 (H1N1). Conclusions: The materials with Cu nanoclusters can be used with high efficiency to passivate and kill the SARS-CoV-2 alpha variant virions, and Zn nanoclusters modified activated porous membranes for killing human influenza A virus A7WSN/1933 (H1N1) virions. Full article

Airborne synthetic aperture radar (SAR) serves as critical battlefield reconnaissance equipment, yet it remains vulnerable to electromagnetic interference (EMI) in combat environments, leading to image-quality degradation. To address this challenge, this study proposes an EMI-effect prediction framework for airborne SAR electromagnetic environments, based on the Newton–Raphson-based optimization (NRBO) and XGBoost algorithms. The methodology enables interference-level prediction through electromagnetic signal parameters obtained from reconnaissance operations, providing operational foundations with which SAR systems can mitigate the impacts of EMI. A laboratory-based airborne SAR EMI test system was developed to establish mapping relationships between EMI signal parameters and SAR imaging performance degradation. This experimental platform facilitated EMI-effect investigations across diverse interference scenarios. An evaluation methodology for SAR image degradation caused by EMI was formulated, revealing the characteristic influence patterns of different interference signals in the context of SAR imagery. The NRBO–XGBoost framework was established through algorithmic integration of Newton–Raphson search principles with trap avoidance mechanisms from the Newton–Raphson optimization algorithm, optimizing the XGBoost hyperparameters. Utilizing the developed test system, comprehensive EMI datasets were constructed under varied interference conditions. Comparative experiments demonstrated the NRBO–XGBoost model’s superior accuracy and generalization performance relative to conventional prediction approaches. Full article

Multi-input Multi-output Synthetic Aperture Radar (MIMO-SAR) systems significantly improve the performance of traditional SAR systems by providing more system freedom. However, in the working mode of the simultaneous transceiver, each receiving antenna will receive the scattered echoes of all transmitting antennas, resulting in the overlapping of echo data and serious related interference, which becomes the main obstacle to the further development and application of MIMO-SAR system. Therefore, achieving effective echo separation is the key technical challenge faced by the MIMO-SAR system. Space–time coding (STC) uses multiple dimensions, such as space, time, and frequency. Through the process of encoding and decoding in these dimensions, channel information can be obtained, and echo separation can be realized. STC is suitable for MIMO-SAR system on different platforms, such as airborne, and has wide applicability. When the traditional scheme uses STC as a coding scheme, it is generally limited by the two-dimensional sending and receiving matrix of Alamouti code. To solve this problem, a new STC scheme based on complex orthogonal matrix design is proposed in this paper. The scheme can form a multidimensional orthogonal STC matrix, recover the superposed signal by echo decoding, and improve the echo signal-to-noise ratio (SNR) of MIMO-SAR. In addition, the use of orthogonal frequency division multiplexing (OFDM) waveform can further reduce cross-correlation interference to achieve effective separation of MIMO-SAR echoes. The effectiveness of the waveform scheme is verified by numerical experiments. Full article

Video Synthetic Aperture Radar (ViSAR) operates by continuously monitoring regions of interest to produce sequences of SAR imagery. The detection and tracking of ground-moving targets, through the analysis of their radiation properties and temporal variations relative to the background environment, represents a significant area of focus and innovation within the SAR research community. In this study, some key challenges in ViSAR systems are addressed, including the abundance of low-confidence shadow detections, high error rates in multi-target data association, and the frequent fragmentation of tracking trajectories. A multi-target tracking algorithm for ViSAR that utilizes re-identification (ReID) features and a multi-stage data association process is proposed. The algorithm extracts high-dimensional ReID features using the Dense-Net121 network for enhanced shadow detection and calculates a cost matrix by integrating ReID feature cosine similarity with Intersection over Union similarity. A confidence-based multi-stage data association strategy is implemented to minimize missed detections and trajectory fragmentation. Kalman filtering is then employed to update trajectory states based on shadow detection. Both simulation experiments and actual data processing experiments have demonstrated that, in comparison to two traditional video multi-target tracking algorithms, DeepSORT and ByteTrack, the newly proposed algorithm exhibits superior performance in the realm of ViSAR multi-target tracking, yielding the highest MOTA and HOTA scores of 94.85% and 92.88%, respectively, on the simulated spaceborne ViSAR data, and the highest MOTA and HOTA scores of 82.94% and 69.74%, respectively, on airborne field data. Full article

Traditional single-channel Synthetic Aperture Radar (SAR) cannot achieve high-resolution and wide-swath (HRWS) imaging due to the constraint of the minimum antenna area. Distributed HRWS SAR can realize HRWS imaging and also possesses the resolution ability in the height dimension by arranging multiple satellites in the elevation direction. Nevertheless, due to the excessively high pulse repetition frequency (PRF) of the distributed SAR system, range ambiguity will occur in large detection scenarios. When directly performing 3D-imaging processing on SAR images with range ambiguity, both focused point clouds and blurred point clouds will exist simultaneously in the generated 3D point clouds, which affects the quality of the generated 3D-imaging point clouds. To address this problem, this paper proposes a 3D blur suppression method for HRWS blurred images, which estimates and eliminates defocused point clouds based on focused targets. The echoes with range ambiguity are focused in the near area and the far area, respectively. Then, through image registration, amplitude and phase correction, and height-direction focusing, the point clouds in the near area and the far area are obtained. The strongest points in the two sets of point clouds are iteratively selected to estimate and eliminate the defocused point clouds in the other set of point clouds until all the ambiguity is eliminated. Simulation experiments based on airborne measured data verified the capability to achieve HRWS 3D blur suppression of this method. Full article

Airborne transmission has been implicated as a major route for the spread of microorganisms, causing infectious disease outbreaks worldwide. This has been emphasized by the recent COVID-19 pandemic, caused by the SARS-CoV-2 virus. There is thus an unmet need to develop technologies that arrest the spread of airborne infectious diseases by inactivating viruses in the air. In this study, the efficacy of two commercially available air ionizer systems for inactivating the bacteriophage MS2, which has been utilized as a surrogate of SARS-CoV-2 as well as a surrogate of noroviruses, was assessed. An experimental test apparatus similar to an HVAC duct system was utilized for the efficacy testing. Each of the two ionizer devices was challenged with viral aerosols of the bacteriophage MS2. The results indicate that the two ionizers were able to reduce the concentration of bacteriophage MS2 virus in the air by 82.02% and 81.72%, respectively. These results point to the efficacy of these ionizer devices in inactivating airborne microorganisms and thus making them an important tool in arresting the spread of infectious diseases. More studies are needed to assess their efficacy against other important airborne viruses such as influenza and strains of the SARS-CoV-2 virus. Full article

The efficient acquisition and processing of large-scale terrain data has always been a focal point in the field of photogrammetry. Particularly in complex mountainous regions characterized by clouds, terrain, and airspace environments, the window for data collection is extremely limited. This paper investigates the use of airborne millimeter-wave InSAR systems for efficient terrain mapping under such challenging conditions. The system’s potential for technical application is significant due to its minimal influence from cloud cover and its ability to acquire data in all-weather and all-day conditions. Focusing on the key factors in airborne InSAR data acquisition, this study explores advanced route planning and ground control measurement techniques. Leveraging radar observation geometry and global SRTM DEM data, we simulate layover and shadow effects to formulate an optimal flight path design. Additionally, the study examines methods to reduce synchronous ground control points in mountainous areas, thereby enhancing the rapid acquisition of terrain data. The results demonstrate that this approach not only significantly reduces field work and aviation costs but also ensures the accuracy of the mountain surface data generated by airborne millimeter-wave InSAR, offering substantial practical application value by reducing field work and aviation costs while maintaining data accuracy. Full article

Terahertz-band squint synthetic aperture radars (SARs) can obtain high-resolution images and have application potential in airborne radar systems. However, airborne radars usually have a large squint, which has led to traditional SAR algorithms no longer being applicable to airborne SARs. Additionally, terahertz radar imaging systems are more susceptible to the error induced by the platform’s motion. This paper proposes a motion compensation method for terahertz SAR imaging with a large squint angle. First, the signal model of motion compensation is derived, and the processing flow of imaging and motion compensation is detailed. Second, some simulations and experiments are conducted, and the results are reported. The results indicate that the proposed method can effectively correct the motion errors, and the signal model and processing flow are verified. Full article

In recent years, drone-based Synthetic Aperture Radar (SAR) systems have emerged as flexible and cost-efficient solutions for detecting changes in the Earth’s surface, retrieving topographic data, or detecting ground displacement processes in localized areas, among other applications. These systems offer a unique combination of short and versatile revisit times and flexible acquisition geometries that are not achievable with space-borne, airborne, or ground-based SAR sensors. However, due to platform limitations and flight stability issues, they also present significant challenges regarding instrument design and data processing, particularly when generating interferometric repeat-pass datasets. This paper demonstrates the feasibility of repeat-pass interferometry using a Ku-band drone-based SAR system. The system integrates a dual-channel Ku-band Frequency Modulated Continuous Wave (FMCW) radar with cross-track single-pass interferometric capabilities, mounted on a drone platform. The proposed repeat-pass interferometric processing chain leverages an accurate Digital Elevation Model (DEM), generated from the single-pass interferograms, to precisely coregister the entire stack of acquisitions, thereby producing repeat-pass interferograms free from residual motion errors. The results underscore the potential of this system and the processing chain proposed for generating multi-temporal repeat-pass stacks suitable for repeat-pass applications. Full article

Considering the presence of airborne viruses, there is a need for renovation in refuse chutes, regarded as the first step in recycling household waste in buildings. This study aimed to revise the design of existing refuse chutes in light of the challenging experiences in waste management and public health during the coronavirus pandemic. This research primarily focused on the risks posed by various types of coronaviruses, such as the novel coronavirus (COVID-19) and acute respiratory syndrome (SARS and SARS-CoV), on stainless steel surfaces, with evidence of their survival under certain conditions. Refuse chutes are manufactured from stainless steel to resist the corrosive effects of waste. In examining the existing studies, it was observed that Casanova et al. and Chowdhury et al. found that the survival time of coronaviruses on stainless steel surfaces decreases as the temperature increases. Based on these studies, mechanical revisions have been made to the sanitation system of the refuse chute, thus increasing the washing water temperature. Additionally, through mechanical improvements, an automatic solution spray entry is provided before the intake doors are opened. Furthermore, to understand airflow and clarify flow parameters related to airborne infection transmission on residential floors in buildings equipped with refuse chutes, a computational fluid dynamics (CFD) analysis was conducted using a sample three-story refuse chute system. Based on the simulation results, a fan motor was integrated into the system to prevent pathogens from affecting users on other floors through airflow. Thus, airborne pathogens were periodically expelled into the atmosphere via a fan shortly before the intake doors were opened, supported by a PLC unit. Additionally, the intake doors were electronically interlocked, ensuring that all other intake doors remained locked while any single door was in use, thereby ensuring user safety. In a sample refuse chute, numerical calculations were performed to evaluate parameters such as the static suitability of the chute body thickness, static compliance of the chute support dimensions, chute diameter, chute thickness, fan airflow rate, ventilation duct diameter, minimum rock wool thickness for human contact safety, and the required number of spare containers. Additionally, a MATLAB code was developed to facilitate these numerical calculations, with values optimized using the Fmincon function. This allowed for the easy calculation of outputs for the new refuse chute systems and enabled the conversion of existing systems, evaluating compatibility with the new design for cost-effective upgrades. This refuse chute design aims to serve as a resource for readers in case of infection risks and contribute to the literature. The new refuse chute design supports the global circular economy (CE) model by enabling waste disinfection under pandemic conditions and ensuring cleaner source separation and collection for recycling. Due to its adaptability to different pandemic conditions including pathogens beyond coronavirus and potential new virus strains, the designed system is intended to contribute to the global health framework. In addition to the health measures described, this study calls for future research on how evolving global health conditions might impact refuse chute design. Full article

The Italian sporting event ‘XIV Convittiadi’ involving students at boarding schools took place in Molise region, central Italy, in April 2022. The study describes the public health protocol with specific countermeasures developed for the event, including testing, isolation, and contact tracing during the COVID-19 pandemic, and reports the main related findings. There were 590 Italian white participants, with 514 athletes (mean age 13.6 ± 1.6 years) and 76 accompanying teachers/guardians (50 ± 8.7 years) of 21 boarding schools from different Italian regions. During the event, 1281 antigenic swabs were performed, and twelve COVID-19 cases were promptly identified due to active screening, involving ten (83.3%) athletes and two (16.7%) accompanying teachers. Among the infected athletes, 83.3% complained mild symptoms, either before or after the ascertained positivity, and 40% had received primary cycle vaccination and booster, or only completed the primary course. The enhanced surveillance and contact tracing activities allowed identifying 34 participants as close contacts who were subjected to a daily follow-up that revealed only four (11.8%) as infected. Since in mass gathering events public health risk is not clear and could not be available through the traditional surveillance systems, increased monitoring activities are necessary. The practical approach implemented for this event was valuable for SARS-CoV-2 control and case management either among participants, or the host country population, suggesting its application to other airborne communicable diseases. Full article