Compact metamaterial-based single/double-negative/near-zero index resonator for 5G sub-6 GHz wireless applications.

The concept, performance, and analyses of distinctive, miniaturized metamaterial (MTM) unit cell addressing the forthcoming Sub 6 GHz 5G applications are presented in this paper. Two circular split-ring resonators (CSRR) with two parallel rectangular copper elements in front of the design and a slotted square element in the background make up the suggested metamaterial. It has a line segment with tunable features that is positioned in the center of the little ring copper structure. The suggested design offers a significant operating frequency band of 220 MHz together with a resonance of transmission coefficient S21 at 3.5 GHz. Furthermore, in two (z & x) principal axes of wave propagation, wide-range achievement, single/double-negative (S/DNG) refractive index, negative permittivity, and near-zero permeability properties were demonstrated. Through varying central slotted-strip line length, resonance frequencies can be selectively altered. Moreover, the metamaterial has overall dimensions of 9 × 9 mm2 and is composed on a Rogers 5880 RT substrate. In order to create the suggested MTM's equivalent circuit, which shows similar coefficient of transmission (S21), a proposed design's numerical simulation is carried out in the CST micro-wave studio. This simulation is after that put to comparison with manufacturing of the design.

Dumbbell shaped structure loaded modified circular ring resonator based perfect metamaterial absorber for S, X and Ku band microwave sensing applications.

In this paper, a new metamaterial absorber (MMA) is presented that exhibits peak absorptions at 3.26 GHz, 11.6 GHz, and 17.13 GHz within S, X, and Ku bands. The unit cell of the proposed MMA is constructed on an FR4 substrate having an electrical dimension of 0.144λ × 0.144λ, where wavelength, λ is calculated at the lowest absorption frequency. The unique structural design of the unit cell consists of two concentric copper rings with which dumbbell-shaped structures are attached. The rotating symmetrical structural design of this MMA provides around 93.8%, 96.47%, and 99.95% peak absorptance in the mentioned frequencies, which is invariable with the change of incident angle as well as polarization angle. The metamaterial properties of the proposed absorber are studied along with the surface current analysis. The MMA shows single negative behaviour and it also exhibits high-quality factors (Q factor) of 21.73, 41.42, and 51.90 at maximum absorptance frequencies. The MMA is analysed by it's equivalent circuit to understand the resonance phenomenon, which is verified through simulation in Advanced Design Systems (ADS) software. The testing is done on the developed prototype of the proposed MMA. Measurement results are in close proximity to the simulation results. Due to its high Q factor, high EMR, and insensitivity to polarization and angle of incidence, it can be utilized as a part of miniaturized microwave device. In addition, the proposed MMA can exhibit high sensing performance and flexibility to differentiate different oils in S, X, and Ku bands.

SRR inspired inversion symmetry-shaped left-handed metamaterial with a high effective medium ratio for ASR and WLAN applications.

This study developed a metamaterial-inspired split-ring resonator (SRR) based inversion symmetry-shaped structure for airport surveillance radar and local area wireless network applications. The proposed device exhibited suitability for S- and C-band applications, featuring distinct resonance peaks at 2.8 and 4.9 GHz, respectively. The two-layer double negative metamaterial unit cell comprises a copper-based resonator, patch, and a low-loss substrate material known as Rogers RT5800 with a thickness of 1.575 mm. The 8 × 8 mm2 structure unit cell was identified with an effective medium ratio (EMR) of 13.4 at the resonance peak of 2.8 GHz. With the alteration of the metamaterial unit cell structure, the electric field, surface current distribution, magnetic field, and design evolution were observed, analysed, and investigated in this study. Meanwhile, the retrieved data from the reflection and transmission coefficients from CST Microwave Studio were validated using the Ansys High-Frequency Structure Simulator (HFSS) software. A Vector Network Analyzer (VNA) further measured the numerical results. Based on the findings, the proposed novel double negative metamaterial device is suitable for radar communication and satellite applications, especially airport surveillance radar (ASR) and wireless local area network (WLAN), due to its high EMR at the desired resonance frequency.

Development of double-layer metamaterial with high effective medium ratio values for S- and C-band applications.

This study introduces a compact double negative metamaterial (DNM) composed of three split rings connected slab resonator (TSRCSR) based double-layer design with a high 13.9 EMR (effective medium ratio) value. A double-layer patch is introduced to achieve the novel double negative properties, including negative behaviours of effective medium parameters, including refractive index, permittivity, and permeability with a high effective medium ratio for the miniaturised size of the introduced unconventional material that is highly suitable for microwave S and C band covering applications. The popular low-loss Rogers RT5880 (thickness 1.575 mm) substrate and copper resonator materials are utilized to develop the metamaterial unit cell that offers triple resonance between frequencies from 1 to 8 GHz. Therefore, the proposed metamaterial exhibits resonance peaks at 2.75, 5.2, and 6.3 GHz, suitable for radar, communication satellite, and long-distance telecommunication applications, respectively. The commercially available simulator known as Computer Simulation Technology (CST) is adopted to develop and simulate the 8 × 8 mm2 metamaterial design. The simulation results of the introduced TSRCSR design structure were verified by adopting the Ansys High-Frequency Structure Simulator (HFSS). Furthermore, it was then proved with the help of equivalent circuit model findings gained from the Advanced Design Structure (ADS) software. On the other hand, the analytical results were further validated by measuring the TSRCSR design utilizing a Vector Network Analyzer (VNA). These analyses become one of the novelties of this work, where the compact TSRCSR metamaterial successfully gained small discrepancies in transmission coefficient values when compared to both analytical and measurement results. The proposed metamaterial is highly suggested for communication devices for its extensive effective characteristics and compactness.

High isolation 16-port massive MIMO antenna based negative index metamaterial for 5G mm-wave applications.

A 16-port massive Multiple-Input-Multiple-Output (mMIMO) antenna system featuring a high gain and efficiency is proposed for millimeter-wave applications. The antenna system consists of 64 elements with a total size of 17 λo × 2.5λo, concerning the lowest frequency. Each 2 × 2 (radiating patch) subarray is designed to operate within the 25.5-29 GHz frequency range. The antenna's performance in terms of isolation, gain, and efficiency has been significantly improved by utilizing the proposed unique double and epsilon negative (DNG/ENG) metamaterials. The array elements are positioned on top of a Rogers RT5880 substrate, with ENG metamaterial unit cells interposed in between to mitigate coupling effects. Additionally, the DNG metamaterial reflector is positioned at the rear of the antenna to boost the gain. As a result, the metamaterial-based mMIMO antenna offers lower measured isolation reaching 25 dB, a maximum gain of 20 dBi and an efficiency of up to 99%. To further analyze the performance of the MIMO antenna, the diversity gain and enveloped correlation coefficient are discussed in relation to the MIMO parameters.

Advancement in total hip implant: a comprehensive review of mechanics and performance parameters across diverse novelties.

The UK's National Joint Registry (NJR) and the American Joint Replacement Registry (AJRR) of 2022 revealed that total hip replacement (THR) is the most common orthopaedic joint procedure. The NJR also noted that 10-20% of hip implants require revision within 1 to 10 years. Most of these revisions are a result of aseptic loosening, dislocation, implant wear, implant fracture, and joint incompatibility, which are all caused by implant geometry disparity. The primary purpose of this review article is to analyze and evaluate the mechanics and performance factors of advancement in hip implants with novel geometries. The existing hip implants can be categorized based on two parts: the hip stem and the joint of the implant. Insufficient stress distribution from implants to the femur can cause stress shielding, bone loss, excessive micromotion, and ultimately, implant aseptic loosening due to inflammation. Researchers are designing hip implants with a porous lattice and functionally graded material (FGM) stems, femur resurfacing, short-stem, and collared stems, all aimed at achieving uniform stress distribution and promoting adequate bone remodeling. Designing hip implants with a porous lattice FGM structure requires maintaining stiffness, strength, isotropy, and bone development potential. Mechanical stability is still an issue with hip implants, femur resurfacing, collared stems, and short stems. Hip implants are being developed with a variety of joint geometries to decrease wear, improve an angular range of motion, and strengthen mechanical stability at the joint interface. Dual mobility and reverse femoral head-liner hip implants reduce the hip joint's dislocation limits. In addition, researchers reveal that femoral headliner joints with unidirectional motion have a lower wear rate than traditional ball-and-socket joints. Based on research findings and gaps, a hypothesis is formulated by the authors proposing a hip implant with a collared stem and porous lattice FGM structure to address stress shielding and micromotion issues. A hypothesis is also formulated by the authors suggesting that the utilization of a spiral or gear-shaped thread with a matched contact point at the tapered joint of a hip implant could be a viable option for reducing wear and enhancing stability. The literature analysis underscores substantial research opportunities in developing a hip implant joint that addresses both dislocation and increased wear rates. Finally, this review explores potential solutions to existing obstacles in developing a better hip implant system.

Demographic and Clinical Characteristics of Persons With Spinal Cord Injury in Bangladesh: Database for the International Spinal Cord Injury Community Survey 2023.

The study aims to explore the demographic and clinical characteristics of persons with spinal cord injury (SCI) in Bangladesh. A total of 3035 persons with SCI spanning from 2018 to 2022 were included in this cross-sectional study. Information about demographic and clinical variables was obtained from the medical records and verified through telephone calls to ensure accuracy and consistency. Approximately half (48.30%) of the study participants were located in Dhaka Division. The average age of persons with SCI was 38.3 years, with a standard deviation of 15.9 years, and the largest proportion (33.4%) fell within the age range of 18-30 years. Males outnumbered females by nearly 2.5 times. In the study, 59.6% had suffered traumatic injuries, whereas 40.4% had SCI attributable to disease-related causes; 58.1% were diagnosed with tetraplegia and 40.1% with paraplegia. Fall from height (42.1%) and road traffic trauma (27%) were the most common causes of traumatic injuries. Degenerative myelopathy (41.1%) was the most frequent cause of non-traumatic SCI, followed by tumors (27.7%) and tuberculosis (TB; 14.8%). Both traumatic (58.3%) and degenerative (56.7%) causes of SCI commonly affected the cervical spine, whereas TB (24.4%) and tumors (47.5%) had a higher incidence of affecting the dorsal spine. In the absence of a registry or national database for patients with SCI in Bangladesh, this study would serve as representative data for future studies.

H-shaped modifiers loaded mirror symmetric resonator based double negative metamaterial for multi-band wireless communications.

In this article, a unique metamaterial (MTM) structure is presented that exhibits four resonances of transmission coefficient (S21) that fall into S, X, and Ku bands. The MTM design is initiated on a Rogers (RT5880) substrate with an electrical dimension of 0.088 λ × 0.088 λ (λ is calculated at 3.424 GHz). The resonating patch contains four quartiles connected by a central metallic strip. The placement of each quartile is such that the whole resonator is mirror symmetric about the vertical axis. Two H-shaped modifiers connect two quartiles of each vertical half of the resonator. These H-shaped modifiers form the resonance cavity in its vicinity, and thus help significantly to orient the overall resonances of the proposed MTM at 3.424 GHz, 10 GHz, 14.816 GHz, and 16.848 GHz. The resonance phenomena are examined through equivalent circuit modeling and verified in Advanced Design Software (ADS). Metamaterial properties of the proposed MTM are extracted and it exhibits negative permittivity, permeability, and refractive index. The prototype of the MTM is fabricated and measurement is taken. The measured S21 shows a close similarity with the simulated result. Moreover, effective medium ratio (EMR) is calculated for the proposed MTM and a high EMR of 10.95 is obtained that expresses its compactness. This compact MTM with negative permittivity, permittivity, and refractive index can be important component for improving the performance of the miniaturized devices for multi-band wireless communication systems.

SoccerNet: A Gated Recurrent Unit-based model to predict soccer match winners.

Winning football matches is the major goal of all football clubs in the world. Football being the most popular game in the world, many studies have been conducted to analyze and predict match winners based on players' physical and technical performance. In this study, we analyzed the matches from the professional football league of Qatar Stars League (QSL) covering the matches held in the last ten seasons. We incorporated the highest number of professional matches from the last ten seasons covering from 2011 up to 2022 and proposed SoccerNet, a Gated Recurrent Unit (GRU)-based deep learning-based model to predict match winners with over 80% accuracy. We considered match- and player-related information captured by STATS platform in a time slot of 15 minutes. Then we analyzed players' performance at different positions on the field at different stages of the match. Our results indicated that in QSL, the defenders' role in matches is more dominant than midfielders and forwarders. Moreover, our analysis suggests that the last 15-30 minutes of match segments of the matches from QSL have a more significant impact on the match result than other match segments. To the best of our knowledge, the proposed model is the first DL-based model in predicting match winners from any professional football leagues in the Middle East and North Africa (MENA) region. We believe the results will support the coaching staff and team management for QSL in designing game strategies and improve the overall quality of performance of the players.

The Horizontal Rain-Cell Span and Wind Impact on Multisite Diversity Scheme in a Tropical Region during El-Niño and La-Niña.

Site diversity is the most effective way to recover a signal lost during heavy downpours, especially in tropical regions since other mitigation techniques such as adaptive power control and code modulation may be unreliable during such. Duplicated links at diverse sites are deployed, and the least-attenuated signal of either site will be routed to the prime site for further operation. Since the deployment is costly, a diversity-gain model is used to estimate the appropriateness of selected sites. Diversity gain is known to depend on site-separation distance and elevation angle and, optionally, baseline angle and signal frequency, based on the region of research. In addition to these factors, the horizontal rain-cell span and the wind's impact on the gain are ongoing investigations, especially in tropical regions. This article presented the rain analysis from the year 2014 to mid-July 2017 at eight sites in the Gombak and Sepang districts of Malaysia to investigate the dependency relevancies. The rain rates were then used to predict the attenuation using the ITU-R P.618-13 rain-attenuation model, and the inter- and cross-district gain characteristics were evaluated. The observation of diurnal rain during the northeast seasons yielded that the northeast wind stimulates intense rain at locations along its direction, thus, extending the horizontal rain-cell span to 15 km distant from a host. Meanwhile, sites located at 5 km distant, slightly perpendicular to the wind direction, and from 90° to 180° from due north of the host, experience less rain. The baseline angle variation establishes nonimpact to the gain and lengthening the site-separation distance presented equal chances to the shorter span towards diversity-gain increment. The research outcome is necessary to formulate a more reliable diversity-gain model to be used in the industry.

Excess mortality during the COVID-19 pandemic (2020-2021) in an urban community of Bangladesh.

Measuring COVID-19-related mortality is vital for making public health policy decisions. The magnitude of COVID-19-related mortality is largely unknown in low- and middle-income countries (LMICs), including Bangladesh, due to inadequate COVID-19 testing capacity and a lack of robust civil registration and vital statistics systems. Even with the lack of data, cemetery-based death records in LMICs may provide insightful information on potential COVID-19-related mortality rates; nevertheless, there is a dearth of research employing cemetery-based death records. This study aimed to assess the excess mortality during the COVID-19 pandemic in an urban setting in Bangladesh using a cemetery-based death registration dataset. A total of 6,271 deaths recorded between January 2015 and December 2021 were analysed using a Bayesian structural time series model. Exploratory analysis found that the average monthly number of deaths was 69 during the pre-COVID-19 period (January 2015-February 2020), but significantly increased to 92 during the COVID-19 period (March 2020-December 2021). The increase in male deaths was twice as large as the increase in female deaths. Model-based results were not statistically significant (relative effect 17%, 95% credible interval: -18%, 57%), but there was an overall increasing trend during the COVID-19 period, and specific months or shorter periods had a substantial increase. This first-of-its-kind study in Bangladesh has assessed the excess mortality in an urban community during the COVID-19 pandemic. Cemetery-based death registration appears to aid in tracking population mortality, especially in resource-limited countries where collecting data on the ground is challenging during crisis periods; however, additional large-scale research is required.

Broadband near unity absorption meta-structure for solar thermophotovoltaic systems and optical window applications.

Developing a meta-structure with near-unity absorbance in the visible and infrared spectra for solar energy harvesting, photodetection, thermal imaging, photo-trapping, and optical communications is a long-term research challenge. This research presents a four-layered (insulator-metal-insulator-metal) meta-structure unit cell that showed a peak absorbance of 99.99% at 288-300 nm and the average absorbance of 99.18% over the 250-2000 nm wavelength range in TE and TM modes, respectively. The symmetric pattern of the resonator layer shows polarization insensitivity with an average absorption of 99.18% in both TE and TM modes. Furthermore, the proposed design shows a wide incident angle stability up to ≤60 degrees in both TE and TM modes. The proposed structure also exhibits negative index properties at 288-300 nm and 1000-2000 nm, respectively. The negative index properties of the proposed design generate an anti-parallel surface current flow in the ground and resonator layers, which induces magnetic and electric field resonance and increases absorption. The performance of the proposed design is further validated by the interference theory model and a zero value for the polarization conversion ratio (PCR). The electric field E, magnetic field H, and current distribution are analyzed to explain the absorption mechanism of the proposed meta-structure unit cell. It also exhibits the highest photo-thermal conversion efficiency of 99.11%, demonstrating the viability of the proposed design as a solar absorber. The proposed design promises potentially valuable applications such as solar energy harvesting, photodetection, thermal imaging, photo-trapping, and optical communications because of its decent performance.

A Deep Learning-Based Approach Towards Simultaneous Localization of Optic Disc and Fovea from Retinal Fundus Images.

In this work, we propose a multi-task learning-based approach towards the localization of optic disc and fovea from human retinal fundus images using a deep learning-based approach. Formulating the task as an image-based regression problem, we propose a Densenet121-based architecture through an extensive set of experiments with a variety of CNN architectures. Our proposed approach achieved an average mean absolute error of only 13pixels (0.04%), mean squared error of 11 pixels (0.005%), and a root mean square error of only 0.02 (13%) on the IDRiD dataset.

Optical Disc Segmentation from Retinal Fundus Images Using Deep Learning.

The optical disc in the human retina can reveal important information about a person's health and well-being. We propose a deep learning-based approach to automatically identify the region in human retinal images that corresponds to the optical disc. We formulated the task as an image segmentation problem that leverages multiple public-domain datasets of human retinal fundus images. Using an attention-based residual U-Net, we showed that the optical disc in a human retina image can be detected with more than 99% pixel-level accuracy and around 95% in Matthew's Correlation Coefficient. A comparison with variants of UNet with different encoder CNN architectures ascertains the superiority of the proposed approach across multiple metrics.

Double-negative metamaterial square enclosed Q.S.S.R For microwave sensing application in S-band with high sensitivity and Q-factor.

Metamaterials have gained much attention due to their exciting characteristics and potential uses in constructing valuable technologies. This paper presents a double negative square resonator shape metamaterial sensor to detect the material and its thickness. An innovative double-negative metamaterial sensor for microwave sensing applications is described in this paper. It has a highly sensitive Q-factor and has good absorption characteristics approximately equal to one. For the metamaterial sensor, the recommended measurement is 20 by 20 mm. Computer simulation technology (C.S.T.) microwave studios are used to design the metamaterial structure and figure out its reflection coefficient. Various parametric analyses have been performed to optimize the design and size of the structure. The experimental and theoretical results are shown for a metamaterial sensor that is attached to five different materials such as, Polyimide, Rogers RO3010, Rogers RO4350, Rogers RT5880, and FR-4. A sensor's performance is evaluated using three different thicknesses of FR-4. There is a remarkable similarity between the measured and simulated outcomes. The sensitivity values for 2.88 GHz and 3.5 GHz are 0.66% and 0.19%, respectively, the absorption values for both frequencies are 99.9% and 98.9%, respectively, and the q-factor values are 1413.29 and 1140.16, respectively. In addition, the figure of merit (FOM) is analyzed, and its value is 934.18. Furthermore, the proposed structure has been tested against absorption sensor applications for the purpose of verifying the sensor's performance. With a high sense of sensitivity, absorption, and Q-factor, the recommended sensor can distinguish between thicknesses and materials in various applications.

Brain Tumor Segmentation and Classification from Sensor-Based Portable Microwave Brain Imaging System Using Lightweight Deep Learning Models.

Automated brain tumor segmentation from reconstructed microwave (RMW) brain images and image classification is essential for the investigation and monitoring of the progression of brain disease. The manual detection, classification, and segmentation of tumors are extremely time-consuming but crucial tasks due to the tumor's pattern. In this paper, we propose a new lightweight segmentation model called MicrowaveSegNet (MSegNet), which segments the brain tumor, and a new classifier called the BrainImageNet (BINet) model to classify the RMW images. Initially, three hundred (300) RMW brain image samples were obtained from our sensors-based microwave brain imaging (SMBI) system to create an original dataset. Then, image preprocessing and augmentation techniques were applied to make 6000 training images per fold for a 5-fold cross-validation. Later, the MSegNet and BINet were compared to state-of-the-art segmentation and classification models to verify their performance. The MSegNet has achieved an Intersection-over-Union (IoU) and Dice score of 86.92% and 93.10%, respectively, for tumor segmentation. The BINet has achieved an accuracy, precision, recall, F1-score, and specificity of 89.33%, 88.74%, 88.67%, 88.61%, and 94.33%, respectively, for three-class classification using raw RMW images, whereas it achieved 98.33%, 98.35%, 98.33%, 98.33%, and 99.17%, respectively, for segmented RMW images. Therefore, the proposed cascaded model can be used in the SMBI system.