Surface Reflectance Research Articles

Performance Assessment of Landsat-9 Atmospheric Correction Methods in Global Aquatic Systems

The latest satellite in the Landsat series, Landsat-9, was successfully launched on 27 September 2021, equipped with the Operational Land Imager-2 (OLI-2) sensor, continuing the legacy of OLI/Landsat-8. To evaluate the uncertainties in water surface reflectance derived from OLI-2, this study conducts a comprehensive performance assessment of six atmospheric correction (AC) methods—DSF, C2RCC, iCOR, L2gen (NIR-SWIR1), L2gen (NIR-SWIR2), and Polymer—using in-situ measurements from 14 global sites, including 13 AERONET-OC stations and 1 MOBY station, collected between 2021 and 2023. Error analysis shows that L2gen (NIR-SWIR1) (RMSE ≤ 0.0017 sr−1, SA = 6.33°) and L2gen (NIR-SWIR2) (RMSE ≤ 0.0019 sr−1, SA = 6.38°) provide the best results across four visible bands, demonstrating stable performance across different optical water types (OWTs) ranging from clear to turbid water. Following these are C2RCC (RMSE ≤ 0.0030 sr−1, SA = 5.74°) and Polymer (RMSE ≤ 0.0027 sr−1, SA = 7.76°), with DSF (RMSE ≤ 0.0058 sr−1, SA = 11.33°) and iCOR (RMSE ≤ 0.0051 sr−1, SA = 12.96°) showing the poorest results. By comparing the uncertainty and consistency of Landsat-9 (OLI-2) with Sentinel-2A/B (MSI) and S-NPP/NOAA20 (VIIRS), results show that OLI-2 has similar uncertainties to MSI and VIIRS in the blue, blue-green, and green bands, with RMSE differences within 0.0002 sr−1. In the red band, the OLI-2 uncertainties are lower than those of MSI but higher than those of VIIRS, with an RMSE difference of about 0.0004 sr−1. Overall, OLI-2 data processed using L2gen provide reliable surface reflectance and show high consistency with MSI and VIIRS, making it suitable for integrating multi-satellite observations to enhance global coastal water color monitoring.

Optothermal trapping of microparticles near an absorbing reflective film with an annular beam.

Optothermal manipulation technologies trap and manipulate microparticles under a light-controlled temperature gradient. In this paper, we demonstrate the possibilities of optothermal trap, which is generated by an annular beam irradiating on an absorbing reflective film to capture the microparticles. The particles are subjected to thermal and optical gradient forces. First, we investigate the particle trapping near a non-absorbing reflective surface to understand the action of the optical force of annular beam. The results show that the optical force cannot trap the particles near a reflective surface. Second, an annular beam is generated by Gaussian beam shaping with the aid of axicons, which is then used to irradiate and heat a gold film to create an optothermal trap. The induced thermal gradient and thermal convection can bind the particles in the center of the annular spot. The trapping stiffness of the optothermal trap is 8.1 ± 2.9 fN/μm at a laser power of 100 mW.

Minimum solar tracking system for a Fresnel lens-based LCPV

The aim of the work is to study a low concentration photovoltaic (LCPV) system based on a Fresnel lens with a plano-concave lens and reflective surfaces. The proposed system is aimed at working with single-junction polycrystalline silicon solar cells with a wider reception angle which reduces the energy consumption of the solar tracking system. A software for multiphysics simulations COMSOL was used to simulate the proposed LCPV system with a maximum concentration ratio (6.5), and calculations were carried out to determine the relative position of the lenses from the solar cell. The proposed LCPV system achieves higher acceptance angle (±9.1°) and concentration acceptance angle product (0.447) compared to the conventional LCPV system (±3.1°, 0.153). Calculations of the power consumption of a dual-axis solar tracker using the proposed optical system show a reduction in power consumption of 21% in azimuth, 37% in altitude, and 27% overall when using the proposed optical system.

Investigation on the integrated characteristics of n-decane/air rotating detonation combustor and supersonic turbine

In this study, the two-dimensional numerical simulations are conducted to study the flow field characteristics, turbine performance and loss mechanism of integrated system of rotating detonation combustor and supersonic turbine under two different directions of detonation wave propagation. The results indicate that the propagation direction of RDW affects the incident angle between OSW and guide vanes, resulting in different operating modes for aligned and unaligned modes. OSW in the turbine cascade undergoes the leading-edge shock, blade surface reflection and trailing edge diffraction. The backward-propagating rake-type shock envelope is formed due to leading-edge shock of the rotor. In misaligned mode, the stator has higher damping of both pressure and temperature. The stator significantly improves the circumferential uniformity of both velocity and pressure, particularly when operating in aligned mode. The total pressure loss in aligned mode is less, therefore the turbine achieves higher rim work and efficiency. The viscosity is one of the main sources of loss in the flow field. The reflected shock waves at the leading edge of the rotor and in the stator cascade are the primary factors contributing to the leading-edge vortices on the stator vanes.

An advanced dorsiventral leaf radiative transfer model for simulating multi-angular and spectral reflection: Considering asymmetry of leaf internal and surface structure

Understanding the optical properties of dorsiventral leaves and quantifying leaf biochemical traits through physical models are important for interpreting canopy radiative transfer and monitoring plant growth. Previous models, such as the dorsiventral leaf model (DLM), have effectively accounted for the inner asymmetry of the leaf but neglected the asymmetry of surface structures between the upper and lower epidermis. In this study, we found marked differences in bidirectional reflectance factors (BRF) between the adaxial and abaxial surfaces of leaves under multi-angular measurements due to surface structural distinctions. To address this asymmetry in both internal and surface leaf structures, we subsequently proposed an advanced DLM model (MADLM) for simulating both multi-angular and spectral BRF of two leaf sides, linking the angular reflection of leaf adaxial and abaxial sides to surface structural parameters (roughness and refractive index) based on microfacet theory. Results show that MADLM accurately simulates multi-angular and spectral BRF for both sides of dorsiventral leaves, and yields satisfactory retrieval accuracy of leaf traits from all observation geometries. For close-range hyperspectral imaging applications, we further introduced a simplified version, sMADLM, which characterizes the surface reflection of two leaf sides in terms of the product of a leaf-side dependent parameter and the wavelength-dependent Fresnel factor. The sMADLM improves the mapping accuracy of leaf biochemical traits by effectively reducing the surface reflection effects in dorsiventral leaves. The MADLM and sMADLM deepen our understanding of the optical properties of dorsiventral leaves and provide practical methods for retrieving leaf biochemical traits via optical remote sensing.

Integration of VIS–NIR Spectroscopy and Multivariate Technique for Soils Discrimination Under Different Land Management

Proximal sensing has become increasingly popular due to developments in soil observation technologies and the demands of timely information gathering through contemporary methods. By utilizing the morphological, physical, and chemical characteristics of representative pedogenetic profiles established in various soils of the Sohag governorate, Egypt, the current research addresses the characterization of surface reflectance spectra and links them with the corresponding soil classification. Three primary areas were identified: recently cultivated, old cultivated, and bare soils. For morphological analysis, a total of 25 soil profiles were chosen and made visible. In the dark room, an ASD Fieldspec portable spectroradiometer (350–2500 nm) was used to measure the spectrum. Based on how similar their surface spectra were, related soils were categorized. Ward’s method served as the basis for the grouping. Despite the fact that the VIS–NIR spectra of the surface soils from various land uses have a similar reflectance shape, it is still possible to compare the soil reflectance curves and the effects of the surface soils. As a result, three groups of soil curves representing various land uses were observed. Cluster analysis was performed on the reflectance data in four ranges (350–750, 751–1150, 1151–1850, and 1851–2500 nm). The groups derived from the soil surface ranges of 350–750 nm and 751–1150 nm were not the same as those derived from the ranges of 1151–1850 nm and 1851–2500 nm. The last two categories are strikingly comparable to various land uses with marginally similar features. Based on the ranges of 1151–1850 nm and 1851–2500 nm in surface spectral data, the dendrogram effectively separated and combined the profiles into two separate clusters. These clusters matched different land uses exactly. The results can be used to promote the widespread usage of in situ hyperspectral data sets for the investigation of various soil characteristics.

Assessing road construction effects on turbidity in adjacent water bodies using Sentinel-1 and Sentinel-2

Road construction significantly affects water resources by introducing contaminants, fragmenting habitats, and degrading water quality. This study examines the use of Remote Sensing (RS) data of Sentinel-1 (S1) and Senitnel-2 (S2) in Google Earth Engine (GEE) to do spatio-temporal analysis of turbidity in adjacent water bodies during the construction and operation of the E18 Arendal-Tvedestrand highway in southeastern Norway from 2017 to 2021. S1 radiometric data helped delineate water extents, while S2-Top of Atmosphere (TOA) multispectral data, corrected using the Modified Atmospheric correction for INland waters (MAIN), used to estimate turbidity levels. To ensure a comprehensive time series of RS data, we utilized S2-TOA data corrected with the MAIN algorithm rather than S2-Bottom Of Atmosphere (BOA) data. We validated the MAIN algorithm's accuracy against GLORIA (Global Observatory of Lake Responses to Interventions and Drivers) observations of surface water reflectance in lakes, globally. Subsequently, the corrected S2 data is used to calculate turbidity using the Novoa and Nechad retrieval algorithms and compared with GLORIA turbidity observations. Findings indicate that the MAIN algorithm adequately estimates water-leaving surface reflectance (Pearson correlation > 0.7 for wavelengths between 490 and 705 nm) and turbidity (Pearson correlation > 0.6 for both algorithms), determining Nechad as the more effective algorithm. In this regard, we used S2 corrected images with MIAN to estimate turbidity in the study area and evaluated with local gauge data and observational reports. Results indicate that the proposed framework effectively captures trends and patterns of turbidity variation in the study area. Findings verify that road construction can increase turbidity in adjacent water bodies and emphasis the employing RS data in cloud platforms like GEE can provide insights for effective long-term water quality management strategies during construction and operation phases.

Solar Ultraviolet Radiation Exposure Among Opencast Miners in Namibia with the Use of Electronic Dosimeters: A Feasibility Study.

Importance: The lack of information on exposure of opencast mineworkers to solar ultraviolet radiation, a group I carcinogen, was addressed. The feasibility of using electronic dosimeters in the determination of exposure to solar ultraviolet radiation was investigated. Objective: The objective of the study was to determine the feasibility of measuring the occupational exposure of opencast mineworkers to solar ultraviolet radiation using electronic dosimeters. Design: The study followed a cross‑sectional design. Setting: Measurements were carried out at two opencast diamond mining operations hereafter referred to as site A and B, located in the Karas region of Namibia. Participants: Workers from all four outdoor occupations (bedrock, engineering, metallurgy and security) were recruited to participate in the study. Measurements: The study was conducted over four days at each site during winter (site A: 28 June to 4 July 2018 and site B: 6-11 July 2018) in the Karas region of Namibia with 28 consenting workers taking part. The AlGaN photodiode‑based electronic dosimeters were worn above clothing on the dorsal wrists (one) and two placed on the horizontal, unshaded area from 08:00 to 16:00 for the measurement of personal and ambient solar ultraviolet radiation, respectively. Historical meteorological data for the measurement period were obtained from Solcast and Ozone Monitoring Instrument (OMI) NASA. Results: Overall, clear skies and surface reflectivity of 0.19 were observed for both study sites. The mean ultraviolet indices were 2.43 (0.06-4.51) and 2.24 (0.09-4.88) for site A and B, respectively. Findings of valid measurements from nine participants showed the mean total daily personal solar ultraviolet radiation exposure of 1.9 ± 1.0 (1.01-1.57) standard erythemal dose (SED) for site A and 3.4 ± 2.6 (3.39-7.28) SED for site B. Conclusions and Relevance: Personal solar ultraviolet radiation exposure above the occupational exposure limit (OEL) demonstrated the need to include the winter season in planning for protective measures for skin and eyes, since workers are at risk of excessive exposure to solar ultraviolet radiation.

Locating Strong Electromagnetic Pulses Recorded by a Single Satellite with Cluster Analysis and Worldwide Lightning Location Network Observations

The integration of satellite-borne and ground-based global lightning location networks offers a better perspective to study lightning processes and their evolutionary characteristics within thunderstorm clouds, thereby bolstering the predictive capabilities for severe weather phenomena. Currently, the satellite-borne network is in the preliminary testing phase with a single satellite. The geographic locations of single-satellite detection events primarily rely on synchronous information from coincident ground-based network events; this method is called synchronous locating (SCL). However, variations in detection-frequency bands and system capabilities prevent this method from accurately locating more than a mere 10% of events. To address this limitation, this paper introduces a cluster-analysis-based strategy, utilizing the observations from the Worldwide Lightning Location Network (WWLLN), termed the cluster analysis locating (CAL) method. The CAL method’s performance, influenced by the density-based spatial clustering of applications with noise (DBSCAN), the K-means, and the mean shift algorithms, is examined. Subsequently, an advanced version, mean shift denoised (MSDN)-CAL, is proposed, demonstrating marked improvements in location accuracy and reliability over the other CAL methods. The satellite-borne wideband electromagnetic pulse detector (WEMPD), orbiting at an altitude of approximately 500 km with a 97.5° inclination, captured 1061 strong electromagnetic pulses (EMPs). Among these, trans-ionospheric single pulses (TISPs) and trans-ionospheric pulse pairs (TIPPs) constituted 21.30% and 78.70%, respectively. Using the MSDN-CAL method successfully determines the geographic locations for 81.15% (861 out of 1061) of the events. This success rate represents an approximate eightfold enhancement over the SCL method. The arithmetic mean, geometric mean, and standard deviation of the two-dimensional range deviation of the locating results between the MSDN-CAL method versus the WWLLN-SCL (or the Guangdong-Hong Kong-Macao Lightning Location System (GHMLLS)-SCL) method are 51.06 (176.26) km, 16.17 (92.53) km, and 100.95 (174.79) km, respectively. Furthermore, it has been possible to estimate the occurrence altitudes for 81.92% (684 out of 835) of the TIPP events. The altitude deviations, as determined by comparing them with the GHMLLS-SCL method’s locating results, exhibit an arithmetic mean of 2.08 km, a geometric mean of 1.30 km, and a standard deviation of 2.26 km. The outcomes of this research establish a foundation for deeper investigation into the origins of various event types, their seasonal variations, and their geographical distribution patterns. Moreover, they pave the way for utilizing a single satellite to measure global surface reflectance, thus contributing valuable data for meteorological and atmospheric studies.

In Situ Surface-Enhanced Infrared Absorption Spectroscopy to Explore the Stability of Electrolyte in Nonaqueous Lithium Oxygen Batteries

Tetraethylene glycol dimethyl ether (TEGDME) decomposition on the Au electrode surface is studied using in situ attenuated total reflectance surface enhanced infrared absorption spectroscopy (ATR-SEIRAS). Due to the weak solvation of TEGDME, the superoxide intermediate (LiO2/O2−) of the discharge process rapidly gains electrons on the electrode surface to generate Li2O2. Furthermore, alkyl radical, formed by LiO2/O2− extracting hydrogen from ether, undergoes oxidative decomposition reactions to form by-products. During the charge process, amorphous film-like Li2O2 obtained from surface-phase mechanism oxidizes in the low potential range of 3–3.4 V, while the oxidation potential of large-sized crystal Li2O2 particles obtained from solution-phase mechanism is above 3.4 V. Besides, TEGDME is intrinsically unstable and can decompose at 3.8 V even the solution is saturated with argon, indicating that the degradation of ether-based electrolyte is inevitable during the cycling process. This work confirms the feasibility of ATR-SEIRAS in probing the reaction mechanism and electrolyte stability of lithium oxygen batteries, and provides direct spectroscopic evidence for subsequent optimization of electrolyte components.

A Lightweight Ultra‐Wideband Metasurface Microwave Absorber

AbstractWideband microwave absorbers hold significant importance in both civilian and military fields. In this paper, a lightweight ultra‐wideband metasurface microwave absorber that covers a frequency range from the ultrahigh‐frequency band to Ku band is presented. The absorber consists of three layers of periodically arranged fourfold rotationally symmetric indium tin oxide (ITO) patterned structures and a reflective surface at the bottom layer separated by polymethacrylimide (PMI) spacers. Such a design enables the absorber to achieve a lightweight construction. The experimental results demonstrate that the absorber exhibits an absorptivity >90% in the 1.3–13.3 GHz band, with a corresponding fractional bandwidth of up to 164.4%. Additionally, the designed absorber features a remarkably lightweight performance with volume density relative to wavelength (VDRW) of just 6.71 mg cm−3. Furthermore, attributed to its fourfold rotationally symmetric design, the absorber also exhibits polarization insensitivity and excellent angular stability. These unique properties render the proposed wideband absorber highly suitable for a variety of practical applications after reasonable adjustment and optimization.

An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making

The design of an Active Reflective Surface Control System (ARCS) is a complex engineering task involving multidimensional and multi-criteria constraints. This paper proposes a novel methodological approach for ARCS design and optimization by integrating Axiomatic Design (AD) and Multi-Criteria Decision Making (MCDM) techniques. Initially, a structured design plan is formulated within the axiomatic design framework. Subsequently, four MCDM methods—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Entropy Weight Method (EWM), Multi-Criteria Optimization and Compromise Solution (VIKOR), and the integrated TOPSIS–Grey Relational Analysis (GRA) approach—are used to evaluate and compare the alternative solutions. Additionally, fuzzy information axioms are used to calculate the total information content for each alternative to identify the optimal design. A case study is conducted, selecting the optimal actuator for a 5 m diameter scaled model of the Five-hundred-meter Aperture Spherical radio Telescope (FAST), followed by digital control experiments on the chosen actuator. Based on the optimal design scheme, an ARCS prototype is constructed, which accelerates project completion and substantially reduces trial-and-error costs.

Dokładność modelu BIM z chmury punktów dla obiektu wykonanego w technologii szklanej

Mapping glass objects in 3D space has long raised doubts as to the possibility of obtaining data, and as to the accuracy of that data. The basics of terrestrial laser scanning technology and the principles of the physics of light propagation in the environment of transparent and reflective surfaces, as a rule, contradict the technological possibility of a faithful mapping thereof. Although Building Information Modelling (BIM) of existing objects based on data from terrestrial laser scanning is an increasingly common practice, it is recognized, nevertheless, that the accuracy of the model is primarily reflected in the accuracy of the point cloud obtained as a result of scanning. The article discusses the possibilities of developing a BIM model of an object made in glass technology, based on data obtained with the method of terrestrial laser scanning. The subject of the study was the glazed façade of the complex of buildings belonging to the University of Agriculture in Krakow. The study on the fidelity of mapping glazed surfaces included the acquisition and processing of the point cloud, 3D modelling of the object using the Revit software, and the analysis of the accuracy of mapping the existing status in comparison with architectural design and construction documentation. Based on the research, the possibility of using the BIM process was assessed using TLS data in the process of recreating the geometry of an object made in glass technology. The results of the study showed a significant convergence of the façade model geometry with the actual course of the structure, which, however, can be attributed to the development methodology, i.e. the accuracy of 3D data acquisition, the registration process, the filtration procedure, the method of parametric modelling of the façade structure itself, and ultimately fitting three-layer glazing into the model of that structure.

StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal

This work addresses the challenge of high-quality surface normal estimation from monocular colored inputs (i.e., images and videos), a field which has recently been revolutionized by repurposing diffusion priors. However, previous attempts still struggle with stochastic inference, conflicting with the deterministic nature of the Image2Normal task, and costly ensembling step, which slows down the estimation process. Our method, StableNormal, mitigates the stochasticity of the diffusion process by reducing inference variance, thus producing "Stable-and-Sharp" normal estimates without any additional ensembling process. StableNormal works robustly under challenging imaging conditions, such as extreme lighting, blurring, and low quality. It is also robust against transparent and reflective surfaces, as well as cluttered scenes with numerous objects. Specifically, StableNormal employs a coarse-to-fine strategy, which starts with a one-step normal estimator (YOSO) to derive an initial normal guess, that is relatively coarse but reliable, then followed by a semantic-guided refinement process (SG-DRN) that refines the normals to recover geometric details. The effectiveness of StableNormal is demonstrated through competitive performance in standard datasets such as DIODE-indoor, iBims, ScannetV2 and NYUv2, and also in various downstream tasks, such as surface reconstruction and normal enhancement. These results evidence that StableNormal retains both the "stability" and "sharpness" for accurate normal estimation. StableNormal represents a baby attempt to repurpose diffusion priors for deterministic estimation. To democratize this, code and models have been publicly available in hf.co/Stable-X.

LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives

Large garages are ubiquitous yet intricate scenes that present unique challenges due to their monotonous colors, repetitive patterns, reflective surfaces, and transparent vehicle glass. Conventional Structure from Motion (SfM) methods for camera pose estimation and 3D reconstruction often fail in these environments due to poor correspondence construction. To address these challenges, we introduce LetsGo, a LiDAR-assisted Gaussian splatting framework for large-scale garage modeling and rendering. We develop a handheld scanner, Polar, equipped with IMU, LiDAR, and a fisheye camera, to facilitate accurate data acquisition. Using this Polar device, we present the GarageWorld dataset, consisting of eight expansive garage scenes with diverse geometric structures, which will be made publicly available for further research. Our approach demonstrates that LiDAR point clouds collected by the Polar device significantly enhance a suite of 3D Gaussian splatting algorithms for garage scene modeling and rendering. We introduce a novel depth regularizer that effectively eliminates floating artifacts in rendered images. Additionally, we propose a multi-resolution 3D Gaussian representation designed for Level-of-Detail (LOD) rendering. This includes adapted scaling factors for individual levels and a random-resolution-level training scheme to optimize the Gaussians across different resolutions. This representation enables efficient rendering of large-scale garage scenes on lightweight devices via a web-based renderer. Experimental results on our GarageWorld dataset, as well as on ScanNet++ and KITTI-360, demonstrate the superiority of our method in terms of rendering quality and resource efficiency.

Colorful Diffuse Intrinsic Image Decomposition in the Wild

Intrinsic image decomposition aims to separate the surface reflectance and the effects from the illumination given a single photograph. Due to the complexity of the problem, most prior works assume a single-color illumination and a Lambertian world, which limits their use in illumination-aware image editing applications. In this work, we separate an input image into its diffuse albedo, colorful diffuse shading, and specular residual components. We arrive at our result by gradually removing first the single-color illumination and then the Lambertian-world assumptions. We show that by dividing the problem into easier sub-problems, in-the-wild colorful diffuse shading estimation can be achieved despite the limited ground-truth datasets. Our extended intrinsic model enables illumination-aware analysis of photographs and can be used for image editing applications such as specularity removal and per-pixel white balancing.

A Novel Multi-Sensor Nonlinear Tightly-Coupled Framework for Composite Robot Localization and Mapping.

Composite robots often encounter difficulties due to changes in illumination, external disturbances, reflective surface effects, and cumulative errors. These challenges significantly hinder their capabilities in environmental perception and the accuracy and reliability of pose estimation. We propose a nonlinear optimization approach to overcome these issues to develop an integrated localization and navigation framework, IIVL-LM (IMU, Infrared, Vision, and LiDAR Fusion for Localization and Mapping). This framework achieves tightly coupled integration at the data level using inputs from an IMU (Inertial Measurement Unit), an infrared camera, an RGB (Red, Green and Blue) camera, and LiDAR. We propose a real-time luminance calculation model and verify its conversion accuracy. Additionally, we designed a fast approximation method for the nonlinear weighted fusion of features from infrared and RGB frames based on luminance values. Finally, we optimize the VIO (Visual-Inertial Odometry) module in the R3LIVE++ (Robust, Real-time, Radiance Reconstruction with LiDAR-Inertial-Visual state Estimation) framework based on the infrared camera's capability to acquire depth information. In a controlled study, using a simulated indoor rescue scenario dataset, the IIVL-LM system demonstrated significant performance enhancements in challenging luminance conditions, particularly in low-light environments. Specifically, the average RMSE ATE (Root Mean Square Error of absolute trajectory Error) improved by 23% to 39%, with reductions from 0.006 to 0.013. At the same time, we conducted comparative experiments using the publicly available TUM-VI (Technical University of Munich Visual-Inertial Dataset) without the infrared image input. It was found that no leading results were achieved, which verifies the importance of infrared image fusion. By maintaining the active engagement of at least three sensors at all times, the IIVL-LM system significantly boosts its robustness in both unknown and expansive environments while ensuring high precision. This enhancement is particularly critical for applications in complex environments, such as indoor rescue operations.

Performance Analysis of Reflective Intelligent Surface Assisted Bidirectional Full‐Duplex Communication Systems Over Nakagami‐m$$ m $$ Fading Channels

ABSTRACTIn this paper, a passive reflective intelligent surface (RIS) assisted bidirectional full‐duplex (FD) wireless system in a realistic Nakagami‐ fading with reflective elements and two source nodes is proposed. The source nodes are equipped with dual antennas for FD mode transmission and reception. The primary cause of degradation in the performance of the FD system is self‐interference, which can be reduced by increasing the number of reflective elements on the meta‐surface. Analytical expressions have been derived for the proposed RIS‐aided bidirectional FD wireless systems in terms of outage probability and bit error rate (BER). Numerical results show that doubling the number of reflecting elements considerably improves the outage performance of the proposed system in terms of signal‐to‐noise ratio (SNR) compared with RIS‐assisted half‐duplex (HD) mode. Additionally, different modulation schemes have been employed to evaluate the BER performance of the proposed system. The accuracy of analytical expressions is validated by matching Monte Carlo with analytical simulations.

A paper-based colorimetric point-of-care testing kit using novel two-dimensional CuBO2 nanoplates for the efficient detection of Vitamin C and fabrication of a highly sensitive optical sensor

This work explores the development of a colorimetric on-spot testing kit and the fabrication of an optical sensor to efficiently detect Vitamin C(VC) using novel 2D-CuBO2 nanoplates, a vital marker for health and disease diagnostics. Although CuBO2 exhibits promising properties in various fields, including transparent conducting domains, its application toward sensing remains unexplored. Here, the authors report the primary utilization of 2D- CuBO2 as a potential candidate for sensing, specifically VC. The 2D-CuBO2 is synthesized through a one-pot sol-gel process followed by comprehensive characterization using various analytical techniques. The investigation of the effect of pH on the selective detection of VC was identified to be at a pH of 7. A paper-based sensor and device prototype for the on-spot detection is fabricated, calibrated, and analysed, showcasing the platform's sensitivity and a high degree of selectivity. The development of color can be attributed to the interaction of electromagnetic waves at the surface and interface of VC-modified aggregated CuBO2 nanoplates and, thereby, changes in the surface reflectivity leading to an observable color change. Optical sensing significantly improved the detection limit by several orders (LoD:130 nM) with a linear range of 10 μM to 10 mM.

Multi-Intelligent Reflecting Surfaces and Artificial Noise-Assisted Cell-Free Massive MIMO Against Simultaneous Jamming and Eavesdropping.

In a cell-free massive multiple-input multiple-output (MIMO) system without cells, it is assumed that there are smart jammers and disrupters (SJDs) that attempt to interfere with and eavesdrop on the downlink communications of legitimate users. A secure transmission scheme based on multiple intelligent reflecting surfaces (IRSs) and artificial noise (AN) is proposed. First, an access point (AP) selection strategy based on user location information is designed, which aims to determine the set of APs serving users. Then, a joint optimization framework based on the block coordinate descent (BCD) algorithm is constructed, and a non-convex optimization solution based on the univariate function optimization and semi-definite relaxation (SDR) is proposed with the aim of maximising the minimum achievable secrecy rate for users. By solving the univariate function maximisation problem, the multi-variable coupled non-convex problem is transformed into a solvable convex problem, obtaining the optimal AP beamforming, AN matrix and IRS phase shift matrix. Specifically, in a single-user scenario, the scheme of multiple intelligent reflecting surfaces combined with artificial noise can improve the user's achievable secrecy rate by about 11% compared to the existing method (single intelligent reflective surface combined with artificial noise) and about 2% compared to the scheme assisted by multiple intelligent reflecting surfaces without artificial noise assistance.