Communications engineering最新文献

{"title":"Multi-band ultrathin reflective metasurface for linear and circular polarization conversion in Ku, K, and Ka bands","authors":"Humayun Zubair Khan, Abdul Jabbar, Jalil ur Rehman Kazim, Masood Ur Rehman, Muhammad Ali Imran, Qammer H. Abbasi","doi":"10.1038/s44172-024-00266-5","DOIUrl":"10.1038/s44172-024-00266-5","url":null,"abstract":"Linear polarization (LP) and circular polarization (CP) holds paramount importance in Ku, K, and Ka bands for satellite based communication, and remote sensing applications. Satellite based remote sensing applications face challenges like atmospheric attenuation, noise & interference, and signal degradation. Moreover, satellite based communication application demands CP in two distinct, non-adjacent frequency bands with orthogonal polarizations at greater oblique angles, considering the unpredictable incidence angles of electromagnetic (EM) waves. Addressing these challenges, an innovative metasurface polarization converter is proposed to operate efficiently across the Ku-band (13.5–18.0 GHz), K-band (18.0–26.5 GHz), and Ka-band (26.5–38.5 GHz) frequency ranges. The converter achieves left-handed circular polarization (LHCP) in the Ku- and Ka-bands within the frequency ranges of 14.57–15.65 GHz and 27.47–33.85 GHz for y-polarized incident EM waves. Additionally, it provides right-handed circular polarization (RHCP) in the K- and Ka-bands at 17.27–23.92 GHz and 35.87–38.32 GHz for y-polarized incident EM waves. The LP conversion ratio exceeds 95% in the frequency bands of 15.97–16.85 GHz, 24.70–26.65 GHz, and 34.37–35.45 GHz for y-polarized, LHCP, and RHCP incident EM waves, respectively. The metasurface exhibits robust performance up to incidence angles of 45 degrees under oblique conditions. Experimental validation using traditional board-circuit manufacturing demonstrates close agreement between measured co- and cross-polarized reflection coefficients and simulations in the 13.5–18 GHz, and 24–38.5 GHz frequency range. Thin metasurface with a thickness of only 0.64 = 0.013λo mm, the proposed design outperforms existing studies in the literature, establishing its competitive edge in terms of structure and performance. Humayun Zubair Khan and colleagues design a thin and efficient metasurface for polarisation conversion. Their solution can operate to up to 45-degree incidence angles and is suitable for satellite communications which use separated frequency bands with orthogonal circularly polarised waves.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00266-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building-block-flow computational model for large-eddy simulation of external aerodynamic applications","authors":"Gonzalo Arranz, Yuenong Ling, Sam Costa, Konrad Goc, Adrián Lozano-Durán","doi":"10.1038/s44172-024-00278-1","DOIUrl":"10.1038/s44172-024-00278-1","url":null,"abstract":"Computational fluid dynamics is an essential tool for accelerating the discovery and adoption of transformative designs across multiple engineering disciplines. Despite its many successes, no single approach consistently achieves high accuracy for all flow phenomena of interest, primarily due to limitations in the modeling assumptions. Here, we introduce a closure model for wall-modeled large-eddy simulation to address this challenge. The model, referred to as the Building-block Flow Model (BFM), rests on the premise that a finite collection of simple flows encapsulates the essential missing physics necessary to predict more complex scenarios. The BFM is designed to: (1) predict multiple flow regimes, (2) unify the closure model at solid boundaries and the rest of the flow, (3) ensure consistency with numerical schemes and gridding strategies by accounting for numerical errors, (4) be directly applicable to arbitrary complex geometries, and (5) be scalable to model additional flow physics in the future. The BFM is utilized to predict key quantities in five cases, including an aircraft in landing configuration, demonstrating similar or superior capabilities compared to previous state-of-the-art models. The design of BFM opens up new opportunities for developing closure models that can accurately represent various flow physics across different scenarios. Arranz and colleagues introduce a closure model for computational fluid dynamics. Their approach is implemented using artificial neural networks. It predicts multiple flow conditions, is directly applicable to complex geometries, and ensures consistency with numerical schemes.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00278-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An experimental system for detection and localization of hemorrhage using ultra-wideband microwaves with deep learning","authors":"Eisa Hedayati, Fatemeh Safari, George Verghese, Vito R. Ciancia, Daniel K. Sodickson, Seena Dehkharghani, Leeor Alon","doi":"10.1038/s44172-024-00259-4","DOIUrl":"10.1038/s44172-024-00259-4","url":null,"abstract":"Stroke is a leading cause of mortality and disability. Emergent diagnosis and intervention are critical, and predicated upon initial brain imaging; however, existing clinical imaging modalities are generally costly, immobile, and demand highly specialized operation and interpretation. Low-energy microwaves have been explored as a low-cost, small form factor, fast, and safe probe for tissue dielectric properties measurements, with both imaging and diagnostic potential. Nevertheless, challenges inherent to microwave reconstruction have impeded progress, hence conduction of microwave imaging remains an elusive scientific aim. Herein, we introduce a dedicated experimental framework comprising a robotic navigation system to translate blood-mimicking phantoms within a human head model. An 8-element ultra-wideband array of modified antipodal Vivaldi antennas was developed and driven by a two-port vector network analyzer spanning 0.6–9.0 GHz at an operating power of 1 mW. Complex scattering parameters were measured, and dielectric signatures of hemorrhage were learned using a dedicated deep neural network for prediction of hemorrhage classes and localization. An overall sensitivity and specificity for detection >0.99 was observed, with Rayleigh mean localization error of 1.65 mm. The study establishes the feasibility of a robust experimental model and deep learning solution for ultra-wideband microwave stroke detection. Eisa Hedayati, Fatemeh Safari and colleagues use an array of ultra-wideband microwave antennas to locate the haemorrhages in a human head phantom. The results of the measurements are processed by the deep neural network algorithm to classify the digital signatures for efficient detection and localization.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00259-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142143872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Localization and recognition of human action in 3D using transformers","authors":"Jiankai Sun, Linjiang Huang, Hongsong Wang, Chuanyang Zheng, Jianing Qiu, Md Tauhidul Islam, Enze Xie, Bolei Zhou, Lei Xing, Arjun Chandrasekaran, Michael J. Black","doi":"10.1038/s44172-024-00272-7","DOIUrl":"10.1038/s44172-024-00272-7","url":null,"abstract":"Understanding a person’s behavior from their 3D motion sequence is a fundamental problem in computer vision with many applications. An important component of this problem is 3D action localization, which involves recognizing what actions a person is performing, and when the actions occur in the sequence. To promote the progress of the 3D action localization community, we introduce a new, challenging, and more complex benchmark dataset, BABEL-TAL (BT), for 3D action localization. Important baselines and evaluating metrics, as well as human evaluations, are carefully established on this benchmark. We also propose a strong baseline model, i.e., Localizing Actions with Transformers (LocATe), that jointly localizes and recognizes actions in a 3D sequence. The proposed LocATe shows superior performance on BABEL-TAL as well as on the large-scale PKU-MMD dataset, achieving state-of-the-art performance by using only 10% of the labeled training data. Our research could advance the development of more accurate and efficient systems for human behavior analysis, with potential applications in areas such as human-computer interaction and healthcare. Jiankai Sun, Michael J. Black and colleagues present a benchmark for human movement analysis. Their transformer-based approach, LocATe, learns to perform both temporal action localization and recognition.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11372174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidisciplinary approaches in electronic nicotine delivery systems pulmonary toxicology: emergence of living and non-living bioinspired engineered systems","authors":"Kambez H. Benam","doi":"10.1038/s44172-024-00276-3","DOIUrl":"10.1038/s44172-024-00276-3","url":null,"abstract":"Technology-based platforms offer crucial support for regulatory agencies in overseeing tobacco products to enhance public health protection. The use of electronic nicotine delivery systems (ENDS), such as electronic cigarettes, has surged exponentially over the past decade. However, the understanding of the impact of ENDS on lung health remains incomplete due to scarcity of physiologically relevant technologies for evaluating their toxicity. This review examines the societal and public health impacts of ENDS, prevalent preclinical approaches in pulmonary space, and the application of emerging Organ-on-Chip technologies and bioinspired robotics for assessing ENDS respiratory toxicity. It highlights challenges in ENDS inhalation toxicology and the value of multidisciplinary bioengineering approaches for generating reliable, human-relevant regulatory data at an accelerated pace. Kambez Benam reviews preclinical approaches to assess lung health impacts of e-cigarettes, highlighting limitations of current strategies in capturing 3D lung architecture and inhalation mechanics. The review article emphasizes the promise of Organs-on-Chips and Bioinspired Robotics.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11372223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography","authors":"Xihan Ma, Mousa Moradi, Xiaoyu Ma, Qinggong Tang, Moshe Levi, Yu Chen, Haichong K. Zhang","doi":"10.1038/s44172-024-00264-7","DOIUrl":"10.1038/s44172-024-00264-7","url":null,"abstract":"Optical coherence tomography (OCT) can be used to image microstructures of human kidneys. However, current OCT probes exhibit inadequate field-of-view, leading to potentially biased kidney assessment. Here we present a robotic OCT system where the probe is integrated to a robot manipulator, enabling wider area (covers an area of 106.39 mm by 37.70 mm) spatially-resolved imaging. Our system comprehensively scans the kidney surface at the optimal altitude with preoperative path planning and OCT image-based feedback control scheme. It further parameterizes and visualizes microstructures of large area. We verified the system positioning accuracy on a phantom as 0.0762 ± 0.0727 mm and showed the clinical feasibility by scanning ex vivo kidneys. The parameterization reveals vasculatures beneath the kidney surface. Quantification on the proximal convoluted tubule of a human kidney yields clinical-relevant information. The system promises to assess kidney viability for transplantation after collecting a vast amount of whole-organ parameterization and patient outcomes data. Xihan Ma and colleagues expand the field-of-view for optical coherence tomography using a robotic manipulator to control the probe. They achieve high position precision in ex vivo demonstration.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11368928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks","authors":"Nageswara Lalam, Sandeep Bukka, Hari Bhatta, Michael Buric, Paul Ohodnicki, Ruishu Wright","doi":"10.1038/s44172-024-00274-5","DOIUrl":"10.1038/s44172-024-00274-5","url":null,"abstract":"The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications. Nageswara Lalam and colleagues demonstrate a multiparameter distributed optical fibre sensing. They employ the wavelength multiplexing technique in Brillouin and Rayleigh scattering with the deep neural networks and achieve an improved performance of strain, temperature and vibration detection.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00274-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142091208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer numerical control knitting of high-resolution mosquito bite blocking textiles","authors":"Bryan Holt, Kyle Oswalt, Alexa England, Richard Murphy, Isabella Owens, Micaela Finney, Natalie Wong, Sushil Adhikari, James McCann, John Beckmann","doi":"10.1038/s44172-024-00268-3","DOIUrl":"10.1038/s44172-024-00268-3","url":null,"abstract":"Mosquitoes and other biting arthropods transmit diseases worldwide, causing over 700,000 deaths each year, and costing about 3 billion USD annually for Aedes species alone. Insect vectored diseases also pose a considerable threat to agricultural animals. While clothing could provide a simple solution to vector-borne diseases, modern textiles do not effectively block mosquito bites. Here we have designed three micro-resolution knitted structures, with five adjustable parameters that can block mosquito bites. These designs, which exhibit significant bite reduction were integrated into a computer numerical control knitting robot for mass production of bite-blocking garments with minimal human labor. We then quantified the comfort of blocking garments. Our knits enable individuals to protect themselves from insects amidst their day-to-day activities without impacting the environment. Bryan Holt, Kyle Oswalt and colleagues design the mosquito bite-proof knitting pattern. Their approach can be implemented in programmable knitting robots for mass production.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00268-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142082743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low frequency ultrasound elicits broad cortical responses inhibited by ketamine in mice","authors":"Linli Shi, Christina Mastracchio, Ilyas Saytashev, Meijun Ye","doi":"10.1038/s44172-024-00269-2","DOIUrl":"10.1038/s44172-024-00269-2","url":null,"abstract":"The neuromodulatory effects of >250 kHz ultrasound have been well-demonstrated, but the impact of lower-frequency ultrasound, which can transmit better through air and the skull, on the brain is unclear. This study investigates the biological impact of 40 kHz pulsed ultrasound on the brain using calcium imaging and electrophysiology in mice. Our findings reveal burst duration-dependent neural responses in somatosensory and auditory cortices, resembling responses to 12 kHz audible tone, in vivo. In vitro brain slice experiments show no neural responses to 300 kPa 40 kHz ultrasound, implying indirect network effects. Ketamine fully blocks neural responses to ultrasound in both cortices but only partially affects 12 kHz audible tone responses in the somatosensory cortex and has no impact on auditory cortex 12 kHz responses. This suggests that low-frequency ultrasound’s cortical effects rely heavily on NMDA receptors and may involve mechanisms beyond indirect auditory cortex activation. This research uncovers potential low-frequency ultrasound effects and mechanisms in the brain, offering a path for future neuromodulation. Dr Ye and colleagues investigate the biological impact low-frequency ultrasound pulses can have on the cortex of mice. They observe pulse duration dependent neural responses and find that ketamine can block parameter-dependent brain responses at certain frequencies.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00269-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142082744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manifold-based approach for neural network robustness analysis","authors":"Ali Sekmen, Bahadir Bilgin","doi":"10.1038/s44172-024-00263-8","DOIUrl":"10.1038/s44172-024-00263-8","url":null,"abstract":"It is important to understand the mathematical foundations of neural networks and to include robustness in model evaluation. Here, we introduce algorithms based on manifold curvature estimation to assess neural network robustness. These algorithms rely solely on training data and do not require regular or adversarial test data. Initially, a metric is proposed to measure the curvature of discrete data manifolds by introducing weighted angles concept between subspaces. Following this, a robustness measure is introduced that is independent of network architecture or model parameters. Lastly, two additional methods are introduced, utilizing curvature estimation of special manifolds formed by using gradient vectors between output and input network layers, alongside manifold curvature estimation. A comprehensive evaluation is provided on multiple network models using the CIFAR-10 dataset. Manifold geometry-based robustness analysis may lead to the development of not only accurate but also robust neural network models. Bahadir Bilgin and Ali Sekmen build the framework for examining the post-training robustness of the neural network. Their method estimates the data curvature on the output layer and does not require knowledge of the black-box topology.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00263-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142045344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}