Search

During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In addition to SARS-COV-2, it can be caused by several other bacterial and viral agents. Even today, variants of SARS-COV-2 are endemic and COVID-19 cases are common in many places. The symptoms of COVID-19 are highly diverse and robust, ranging from invisible to severe respiratory failure. Current detection methods for the disease are time-consuming and expensive with low accuracy and precision. To address such situations, we have designed a framework for COVID-19 and Pneumonia detection using multiple deep learning algorithms further accompanied by a deployment scheme. In this study, we have utilized four prominent deep learning models, which are VGG-19, ResNet-50, Inception V3 and Xception, on two separate datasets of CT scan and X-ray images (COVID/Non-COVID) to identify the best models for the detection of COVID-19. We achieved accuracies ranging from 86% to 99% depending on the model and dataset. To further validate our findings, we have applied the four distinct models on two more supplementary datasets of X-ray images of bacterial pneumonia and viral pneumonia. Additionally, we have implemented a flask app to visualize the outcome of our framework to show the identified COVID and Non-COVID images. The findings of this study will be helpful to develop an AI-driven automated tool for the cost effective and faster detection and better management of COVID-19 patients. [ABSTRACT FROM AUTHOR]

To address the growing demand for sustainable agriculture practices, new technologies to boost crop productivity and soil health must be developed. In this research, we propose designing and building an agricultural rover capable of autonomous vegetable harvesting and soil analysis utilizing cutting-edge deep learning algorithms (YOLOv5). The precision and recall score of the model was 0.8518% and 0.7624% respectively. The rover uses robotics, computer vision, and soil sensing technology to perform accurate and efficient agricultural tasks. We go over the rover's hardware and software, as well as the soil analysis system and the tomato ripeness detection system using deep learning models. Field experiments indicate that this agricultural rover is effective and promising for improving crop management and soil monitoring in modern agriculture, hence achieving the UN's SDG 2 Zero Hunger goals. [ABSTRACT FROM AUTHOR]

Nanoparticles embedded in polymer matrices play a critical role in enhancing the properties and functionalities of composite materials. Detecting and quantifying nanoparticles from optical images (fixed samples-in vitro imaging) is crucial for understanding their distribution, aggregation, and interactions, which can lead to advancements in nanotechnology, materials science, and biomedical research. In this article, we propose an ensembled deep learning approach for automatic nanoparticle detection and oligomerization quantification in a polymer matrix for optical images. The majority of prior studies of nanoparticle identification and categorization of fixed samples are based on scanning electron microscopy (SEM) or transmission electron microscopy (TEM) images, which are destructive to biological imaging. However, the proposed study is based on optical images, which are susceptible to noise, low contrast, anisotropic shape, overlapping of the point spread function, plasmon coupling, and resolution limitations. In this study, we fine-tune a deep neural network architecture, YOLOv8, on a carefully annotated data set of correlated optical and SEM images of 80 nm gold nanospheres (AuNSs) of varying oligomerization states. The resultant model features a weighted average accuracy of 80.7% for quantification of AuNSs and determination of their oligomeric state, far surpassing the capabilities of existing manual image processing methods. We also demonstrate its speed and effectiveness in nanoparticle detection and oligomerization within the polymer matrix through tests on high-density uncorrelated optical images. The optical image-based quantification technique will be useful for (live samples-for in vivo imaging) analyzing nanoparticle uptake, oligomerization state, and aggregation kinetics in live cells and identifying stoichiometry of membrane protein and its interactions, nanoparticle-cell interaction, cell signaling imaging, and drug delivery., Competing Interests: The authors declare no competing financial interest., (© 2025 The Authors. Published by American Chemical Society.)

In this study we investigated a novel approach to designing a graphene metamaterial (GMM) based terahertz (THz) absorber with dual-mode functionality, tunability, and broadband absorption capabilities. The study leverages the unique properties of graphene, a material known for its exceptional electronic and optical characteristics, combined with metamaterials to achieve efficient THz absorption. Here we performed extensive simulation on four different types of configurations and found the optimized structure has the highest bandwidth of 3.8 THz and absorption over 90 %. The absorber is designed to operate in two distinct modes, enhancing its versatility for different applications in the THz spectrum. Moreover, the tunability of the absorber is a significant feature, allowing for dynamic adjustment of the absorption frequency, which is crucial for applications in THz imaging, sensing, and communication systems. The broadband nature of the absorber ensures effective performance over a wide range of frequencies, addressing the need for flexible and high-performance devices in emerging THz technologies. This work represents a significant advancement in the field of THz metamaterials, with potential implications for the development of next-generation THz devices., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Surface Plasmon Resonance (SPR) based optical biosensors are recently the most attractive sensing devices that can detect minor changes in refractive index. Multiple methods have been developed to design SPR based biosensors with high-performance and ease of fabrication. This research is about a grating based biosensor that utilizes Silver (Ag) and Titanium (Ti) to produce the SP resonance state. The structure has a resonance wavelength, which displays sensitivity to changes in the surrounding medium of the refractive index. The study has been conducted using numerical simulations, utilizing the finite-difference-time-domain (FDTD) method.The simulation results shows a sharp resonance peaks in the wavelength range of 450-700 nm with a remarkable sensitivity of 172 nm/RIU (for mode 1 at SPR peak 465 nm) and 515 nm/RIU (for mode 2 at SPR peak 585 nm), which is superior to other on-chip device. The investigation involves a comparative analysis of sensing performance, focusing on parameters like transmission, reflection, FWHM and Quality factor to measure the detection accuracy of the proposed material combination. Later, we employed this miniature biosensor device to detect hemoglobin concentrations in the blood. Our findings indicate that this developed structure has great potential for detecting any biomolecule, such as proteins, glucose, fructose, nucleic acids, and cells., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Recently, metamaterials and metasurface have gained rapidly increasing attention from researchers due to their extraordinary optical and electrical properties. Metamaterials are described as artificially defined periodic structures exhibiting negative permittivity and permeability simultaneously. Whereas metasurfaces are the 2D analogue of metamaterials in the sense that they have a small but not insignificant depth. Because of their high optical confinement and adjustable optical resonances, these artificially engineered materials appear as a viable photonic platform for biosensing applications. This review paper discusses the recent development of metamaterial and metasurface in biosensing applications based on the gigahertz, terahertz, and optical frequency domains encompassing the whole electromagnetic spectrum. Overlapping features such as material selection, structure, and physical mechanisms were considered during the classification of our biosensing applications. Metamaterials and metasurfaces working in the GHz range provide prospects for better sensing of biological samples, THz frequencies, falling between GHz and optical frequencies, provide unique characteristics for biosensing permitting the exact characterization of molecular vibrations, with an emphasis on molecular identification, label-free analysis, and imaging of biological materials. Optical frequencies on the other hand cover the visible and near-infrared regions, allowing fine regulation of light-matter interactions enabling metamaterials and metasurfaces to offer excellent sensitivity and specificity in biosensing. The outcome of the sensor's sensitivity to an electric or magnetic field and the resonance frequency are, in theory, determined by the frequency domain and features. Finally, the challenges and possible future perspectives in biosensing application areas have been presented that use metamaterials and metasurfaces across diverse frequency domains to improve sensitivity, specificity, and selectivity in biosensing applications., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

In this study, we constructed an UV-C illumination chamber using commercially available germicidal lamps and other locally available low-cost components for general-purpose biological decontamination purposes. The illumination chamber provides uniform illumination of around 1 J/cm 2 in under 5 min across the chamber. The control mechanism was developed to automate the on/off process and make it more secure minimizing health and other electrical safety. To validate the decontamination efficacy of the UV-C Illumination Chamber we performed the Geobacillus spore strip culture assay. Additionally, we performed the viral load measurement by identifying the COVID-19-specific N-gene and ORF1 gene on surgical masks. The gold standard RT-qPCR measurement was performed to detect and quantify the COVID-19-specific gene on the mask sample. The biochemical assay was conducted on the control and test group to identify the presence of different types of bacteria, and fungi before and after exposure under the illumination chamber. The findings of our study revealed satisfactory decontamination efficacy test results. Therefore, it could be an excellent device in healthcare settings as a disinfection tool for biological decontamination such as SAR-CoV-2 virus, personal protection equipment (PPE), (including n95, k95 respirators, and surgical masks), and other common pathogens., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

In this article, we report, as per our knowledge, for the first time, a thin film single junction solar cell with a metasurface absorber layer directly incorporated. We have used an interconnected dual inverted split ring resonator pattern in the InAsP absorber layer. The structure eliminated patterns of conventional metals, such as silver, aluminum, and gold, from the active layer, a common drawback in conventional solar absorbers, hindering their direct integration into solar cells. Optical simulation results show a peak ideal short circuit current density of 76.23mA/cm 2 for the meta-absorber structure under solar illumination. This current is the highest among previously reported absorbers based on Group IV materials and III-V compounds, overcoming the low solar absorption of such metasurfaces. The final proposed solar cell structure combines this meta-absorber layer with traditional efficiency enhancement methods namely anti-reflecting coating, textured back reflector, and transparent top electrode. This novel single junction structure shows a solar absorption efficiency of 97.86% and a power conversion efficiency of 30.87%, the highest for III-V solar cells. Our device proves the ability of metasurface absorber layers to produce high-efficiency solar cells and is expected to pave the way for integrating novel meta-devices into state-of-the-art photovoltaic devices, aiding the global transition towards clean energy sources.

In recent years, plasmonics has been widely employed to improve light trapping in solar cells. Silver nanospheres have been used in several research works to improve the capability of solar absorption. In this paper, we use silver pyramid-shaped nanoparticles, a noble plasmonic nanoparticle, inside thin-film silicon and InP solar cells to increase light absorption compared to previously published topologies. The proposed structure consists of a TiO 2 pyramid structure placed at the top of the surface working as an anti-reflective layer, silicon/indium phosphate as an absorption layer, silver pyramid-shaped nanoparticles incorporated inside the absorption layer, and an aluminum reflecting layer at the bottom. In this research, we used finite difference time domain (FDTD) simulation to model the thin-film solar cell (TFSC). Optimizing the shape and placement of the silver pyramids, we have achieved an efficiency of 17.08% and 18.58% using silicon and InP as the absorbing layers respectively, which is significantly better than previously reported studies. The open-circuit voltages are 0.58 V and 0.92 V respectively, which is the highest among other configurations. To conclude, the findings of this study laid the foundation to create an efficient thin-film solar cell utilizing the light-trapping mechanism of noble plasmonic nanoparticles., Competing Interests: The authors declare no competing interests., (© 2023 The Authors.)

Aqueous solutions of ultra-pure gold nanoparticles have been prepared by methods of femtosecond laser ablation from a solid target and fragmentation from already formed colloids. Despite the absence of protecting ligands, the solutions could be (1) fairly stable and poly size-dispersed; or (2) very stable and monodispersed, for the two fabrication modalities, respectively. Fluorescence quenching behavior and its intricacies were revealed by fluorescence lifetime imaging microscopy in rhodamine 6G water solution. We show that surface-enhanced Raman scattering of rhodamine 6G on gold nanoparticles can be detected with high fidelity down to micromolar concentrations using the nanoparticles. Application potential of pure gold nanoparticles with polydispersed and nearly monodispersed size distributions are discussed.