Displaying publications 1 - 20 of 99 in total

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  1. Fulltext YOLO and residual network for colorectal cancer cell detection and counting
    Haq I, Mazhar T, Asif RN, Ghadi YY, Ullah N, Khan MA, et al.
    Heliyon, 2024 Jan 30;10(2):e24403.
    PMID: 38304780 DOI: 10.1016/j.heliyon.2024.e24403
    The HT-29 cell line, derived from human colon cancer, is valuable for biological and cancer research applications. Early detection is crucial for improving the chances of survival, and researchers are introducing new techniques for accurate cancer diagnosis. This study introduces an efficient deep learning-based method for detecting and counting colorectal cancer cells (HT-29). The colorectal cancer cell line was procured from a company. Further, the cancer cells were cultured, and a transwell experiment was conducted in the lab to collect the dataset of colorectal cancer cell images via fluorescence microscopy. Of the 566 images, 80 % were allocated to the training set, and the remaining 20 % were assigned to the testing set. The HT-29 cell detection and counting in medical images is performed by integrating YOLOv2, ResNet-50, and ResNet-18 architectures. The accuracy achieved by ResNet-18 is 98.70 % and ResNet-50 is 96.66 %. The study achieves its primary objective by focusing on detecting and quantifying congested and overlapping colorectal cancer cells within the images. This innovative work constitutes a significant development in overlapping cancer cell detection and counting, paving the way for novel advancements and opening new avenues for research and clinical applications. Researchers can extend the study by exploring variations in ResNet and YOLO architectures to optimize object detection performance. Further investigation into real-time deployment strategies will enhance the practical applicability of these models.
  2. Fulltext Exploring Patient Safety Culture: A Study of Community Pharmacies in Karachi, Pakistan
    Khatri SA, Ahmad R, Osama M, Khan K, Khan MA, Ishaqui A, et al.
    Cureus, 2024 Jan;16(1):e52135.
    PMID: 38344495 DOI: 10.7759/cureus.52135
    Background Community pharmacies are integral to the healthcare system, actively contributing to patient safety through accurate dispensing, education, collaboration, monitoring, and the implementation of safety protocols. Their accessibility and role as medication experts make them key partners in promoting positive health outcomes for individuals and communities. Objective The current study will evaluate the patient safety culture (PSC) among community pharmacies in Karachi, Pakistan. Additionally, this study will measure the association between patient safety culture in community pharmacies and the demographic characteristics of the pharmacy staff. Methods A cross-sectional survey of pharmacy staff was conducted using a survey instrument developed by the US Agency for Healthcare Research and Quality (AHRQ). Demographic variables and assessments of safety culture in pharmacies were studied. The data were analyzed using descriptive statistics. Results Among the 102 participants, positive responses ranged from 30% to 87.5%. The highest positive response was for the dimension "mistakes in communication" (86.3%), followed by "communication across shifts" (82.2%) and "communication openness" (81.7%). The dimensions "overall perceptions of patient safety" and "response to mistakes" had the lowest positive responses (56.0% and 60.9%, respectively). Furthermore, many staff did not regularly record the errors, even if they impacted the practices. Conclusion There was an overall unfavorable perception of patient safety culture among the surveyed pharmacies of Karachi, Pakistan. However, the communication dimensions showed the highest positive response. There is a strong need to improve the overall perception of patient safety among the staff and develop an optimistic response to mistakes.
  3. Pyrolytic conversion of human hair to fuel: performance evaluation and kinetic modelling
    Krishnakumar P, Sundaramurthy S, Baredar P, Suresh A, Khan MA, Sharma G, et al.
    Environ Sci Pollut Res Int, 2023 Dec;30(60):125104-125116.
    PMID: 37099105 DOI: 10.1007/s11356-023-26991-6
    There are several environmental and human health impacts if human hair waste is not adequately disposed of. In this study, pyrolysis of discarded human hair was carried out. This research focused on the pyrolysis of discarded human hair under controlled environmental conditions. The effects of the mass of discarded human hair and temperature on bio-oil yield were studied. The proximate and ultimate analyses and calorific values of disposed of human hair, bio-oil, and biochar were determined. Further, chemical compounds of bio-oil were analyzed using a gas chromatograph and a mass spectrometer. Finally, the kinetic modeling and behavior of the pyrolysis process were characterized through FT-IR spectroscopy and thermal analysis. Based on the optimized mass of disposed of human hair, 250 g had a better bio-oil yield of 97% in the temperature range of 210-300 °C. The different parameters of bio-oil were: pH (2.87), specific gravity (1.17), moisture content (19%), heating value (19.34 MJ/kg), and viscosity (50 CP). C (56.4%), H (6.1%), N (0.16%), S (0.01%), O (38.4%), and Ash (0.1%) were discovered to be the elemental chemical composition of bio-oil (on a dry basis). During breakdown, the release of different compounds like hydrocarbons, aldehydes, ketones, acids, and alcohols takes place. According to the GC-MS results, several amino acids were discovered in the bio-oil, 12 abundant in the discarded human hair. The FTIR and thermal analysis found different concluding temperatures and wave numbers for functional groups. Two main stages are partially separated at about 305 °C, with maximum degradation rates at about 293 oC and 400-4140 °C, respectively. The mass loss was 30% at 293 0C and 82% at temperatures above 293 0C. When the temperature reached 4100C, the entire bio-oil from discarded human hair was distilled or thermally decomposed.
  4. Identification of Four Novel Candidate Genes for Non-syndromic Intellectual Disability in Pakistani Families
    Ahmed I, Muzammal M, Khan MA, Ullah H, Farid A, Yasin M, et al.
    Biochem Genet, 2023 Nov 20.
    PMID: 37985543 DOI: 10.1007/s10528-023-10556-w
    Intellectual disability, a genetically and clinically varied disorder and is a significant health problem, particularly in less developed countries due to larger family size and high ratio of consanguineous marriages. In the current genetic study, we investigate and find the novel disease causative factors in the four Pakistani families with severe type of non-syndromic intellectual disability. For genetic analysis whole-exome sequencing (WES) and Sanger sequencing was performed. I-TASSER and Cluspro tools were used for Protein modeling and Protein-protein docking. Sanger sequencing confirms the segregation of novel homozygous variants in all the families i.e., c.245 T > C; p.Leu82Pro in SLC50A1 gene in family 1, missense variant c.1037G > A; p.Arg346His in TARS2 gene in family 2, in family 3 and 4, nonsense mutation c.234G > A; p.Trp78Term and missense mutation c.2200G > A; p.Asp734Asn in TBC1D3 and ANAPC2 gene, respectively. In silico functional studies have found the drastic effect of these mutations on protein structure and its interaction properties. Substituted amino acids were highly conserved and present on highly conserved region throughout the species. The discovery of pathogenic variants in SLC50A1, TARS2, TBC1D1 and ANAPC2 shows that the specific pathways connected with these genes may be important in cognitive impairment. The decisive role of pathogenic variants in these genes cannot be determined with certainty due to lack of functional data. However, exome sequencing and segregation analysis of all filtered variants revealed that the currently reported variants were the only variations from the respective families that segregated with the phenotype in the family.
  5. Fulltext Asynchronous Federated Learning for Improved Cardiovascular Disease Prediction Using Artificial Intelligence
    Khan MA, Alsulami M, Yaqoob MM, Alsadie D, Saudagar AKJ, AlKhathami M, et al.
    Diagnostics (Basel), 2023 Jul 11;13(14).
    PMID: 37510084 DOI: 10.3390/diagnostics13142340
    Healthcare professionals consider predicting heart disease an essential task and deep learning has proven to be a promising approach for achieving this goal. This research paper introduces a novel method called the asynchronous federated deep learning approach for cardiac prediction (AFLCP), which combines a heart disease dataset and deep neural networks (DNNs) with an asynchronous learning technique. The proposed approach employs a method for asynchronously updating the parameters of DNNs and incorporates a temporally weighted aggregation technique to enhance the accuracy and convergence of the central model. To evaluate the effectiveness of the proposed AFLCP method, two datasets with various DNN architectures are tested, and the results demonstrate that the AFLCP approach outperforms the baseline method in terms of both communication cost and model accuracy.
  6. Fulltext Privacy-Aware Collaborative Learning for Skin Cancer Prediction
    Ain QU, Khan MA, Yaqoob MM, Khattak UF, Sajid Z, Khan MI, et al.
    Diagnostics (Basel), 2023 Jul 04;13(13).
    PMID: 37443658 DOI: 10.3390/diagnostics13132264
    Cancer, including the highly dangerous melanoma, is marked by uncontrolled cell growth and the possibility of spreading to other parts of the body. However, the conventional approach to machine learning relies on centralized training data, posing challenges for data privacy in healthcare systems driven by artificial intelligence. The collection of data from diverse sensors leads to increased computing costs, while privacy restrictions make it challenging to employ traditional machine learning methods. Researchers are currently confronted with the formidable task of developing a skin cancer prediction technique that takes privacy concerns into account while simultaneously improving accuracy. In this work, we aimed to propose a decentralized privacy-aware learning mechanism to accurately predict melanoma skin cancer. In this research we analyzed federated learning from the skin cancer database. The results from the study showed that 92% accuracy was achieved by the proposed method, which was higher than baseline algorithms.
  7. Thermocatalytic conversion of wood-plastic composite over HZSM-5 catalysts
    Seo J, Kim H, Jeon S, Valizadeh S, Khani Y, Jeon BH, et al.
    Bioresour Technol, 2023 Apr;373:128702.
    PMID: 36740100 DOI: 10.1016/j.biortech.2023.128702
    Air gasification of the Wood-Plastic Composite (WPC) was performed over Ni-loaded HZSM-5 catalysts to generate H2-rich gas. Increasing SiO2/Al2O3 ratio (SAR) of HZSM-5 adversely affected catalytic activity, where the highest gas yield (51.38 wt%) and H2 selectivity (27.01 vol%) were acquired using 20 %Ni/HZSM-5(30) than those produced over 20 %Ni/HZSM-5(80) and 20 %Ni/HZSM-5(280). Reducing SAR was also favorably conducive to increasing the acyclic at the expense of cyclic compounds in oil products. These phenomena are attributed to enhanced acid strength and Ni dispersion of 20 %Ni/HZSM-5(30) catalyst. Moreover, catalytic activity in the terms of gas yield and H2 selectivity enhanced with growing Ni loading to 20 %. Also, the addition of promoters (Cu and Ca) to 20 %Ni/HZSM-5(30) boosted the catalytic efficiency for H2-rich gas generation. Raising temperature indicated a positive relevance with the gas yield and H2 selectivity. WPC valorization via gasification technology would be an outstanding outlook in the terms of a waste-to-energy platform.
  8. H2 generation from steam gasification of swine manure over nickel-loaded perovskite oxides catalysts
    Valizadeh S, Khani Y, Yim H, Chai S, Chang D, Farooq A, et al.
    Environ Res, 2023 Feb 15;219:115070.
    PMID: 36549497 DOI: 10.1016/j.envres.2022.115070
    In this study, nickel-loaded perovskite oxides catalysts were synthesized via the impregnation of 10%Ni on XTiO3 (X = Ce, Sr, La, Ba, Ca, and Fe) supports and employed in the catalytic steam gasification of swine manure to produce H2-rich syngas for the first time. The synthesized catalysts were characterized using BET, H2-TPR, XRD, HR-TEM, and EDX analysis. Briefly, using perovskite supports resulted in the production of ultrafine catalyst nanoparticles with a uniform dispersion of Ni particles. According to the catalytic activity test, the gas yield showed the increment as 10% Ni/LaTiO3 < 10% Ni/FeTiO3 < 10% Ni/CeTiO3 < 10% Ni/BaTiO3 < 10% Ni/SrTiO3 < 10% Ni/CaTiO3. Meanwhile, zero coke formation was achieved due to the oxygen mobility of prepared catalysts. Also, the increase in the H2 production for the applied catalysts was in the sequence as 10% Ni/CeTiO3 < 10% Ni/FeTiO3 < 10% Ni/LaTiO3 < 10% Ni/BaTiO3 < 10% Ni/SrTiO3 < 10% Ni/CaTiO3. The maximum H2 selectivity (∼48 vol%) obtained by10% Ni/CaTiO3 was probably due to the synergistic effect of Ni and Ti on enhancing the water-gas shift reaction, and Ca on creating the maximum oxygen mobility compared to other alkaline earth metals doped at the A place of perovskite. Overall, this study provides a suitable solution for enhanced H2 production through steam gasification of swine manure along with suggesting the appropriate supports to prevent Ni deactivation by lowering coke formation at the same time.
  9. A new implicit high-order iterative scheme for the numerical simulation of the two-dimensional time fractional Cable equation
    Khan MA, Alias N, Khan I, Salama FM, Eldin SM
    Sci Rep, 2023 Jan 27;13(1):1549.
    PMID: 36707653 DOI: 10.1038/s41598-023-28741-7
    In this article, we developed a new higher-order implicit finite difference iterative scheme (FDIS) for the solution of the two dimension (2-D) time fractional Cable equation (FCE). In the new proposed FDIS, the time fractional and space derivatives are discretized using the Caputo fractional derivative and fourth-order implicit scheme, respectively. Moreover, the proposed scheme theoretical analysis (convergence and stability) is also discussed using the Fourier analysis method. Finally, some numerical test problems are presented to show the effectiveness of the proposed method.
  10. Fulltext Economic costs of gender inequality in health and the labor market: India's untapped potential
    Khan A, Khan S, Khan MA, Zaman K, Khan HUR, Rosman ASB, et al.
    Front Public Health, 2023;11:1067940.
    PMID: 36794076 DOI: 10.3389/fpubh.2023.1067940
  11. Fulltext Factors affecting repurchase intention of organic food among generation Z (Evidence from developing economy)
    Bhutto MY, Khan MA, Sun C, Hashim S, Khan HT
    PLoS One, 2023;18(3):e0281527.
    PMID: 36961791 DOI: 10.1371/journal.pone.0281527
    Organic food has gained much importance due to consumers' rising environmental and health concerns. Purchase intention of organic food has been explored widely, but the repurchase intention of organic food has gained little attention among researchers. So, it has become important to explore repurchase intention among generation Z; a generation considered more educated and aware of rising environmental concerns. Generation Z is more tech-savvy and brand conscious, so its impact on repurchase intention through consumer satisfaction has been explored. The data in this paper was collected from 400 respondents through a structured questionnaire in Islamabad, Pakistan. We used the PLS-SEM approach for data analysis and results; we found that social media influence and brand purchase impact brand awareness and positively impact brand awareness on consumer satisfaction. Moreover, it is also found that consumer satisfaction positively impacts the repurchase intention of organic food. Our study found that Generation Z has a strong social media influence, so marketers' managers must consider and address the issues when consumers consider social media for their concerns and suggestion.
  12. Fulltext Antibody-drug conjugates: the paradigm shifts in the targeted cancer therapy
    Aggarwal D, Yang J, Salam MA, Sengupta S, Al-Amin MY, Mustafa S, et al.
    Front Immunol, 2023;14:1203073.
    PMID: 37671162 DOI: 10.3389/fimmu.2023.1203073
    Cancer is one of the deadliest diseases, causing million of deaths each year globally. Conventional anti-cancer therapies are non-targeted and have systemic toxicities limiting their versatile applications in many cancers. So, there is an unmet need for more specific therapeutic options that will be effective as well as free from toxicities. Antibody-drug conjugates (ADCs) are suitable alternatives with the right potential and improved therapeutic index for cancer therapy. The ADCs are highly precise new class of biopharmaceutical products that covalently linked a monoclonal antibody (mAb) (binds explicitly to a tumor-associated surface antigen) with a customized cytotoxic drug (kills cancer cells) and tied via a chemical linker (releases the drug). Due to its precise design, it brings about the target cell killing sparing the normal counterpart and free from the toxicities of conventional chemotherapy. It has never been so easy to develop potential ADCs for successful therapeutic usage. With relentless efforts, it took almost a century for scientists to advance the formula and design ADCs for its current clinical applications. Until now, several ADCs have passed successfully through preclinical and clinical trials and because of proven efficacy, a few are approved by the FDA to treat various cancer types. Even though ADCs posed some shortcomings like adverse effects and resistance at various stages of development, with continuous efforts most of these limitations are addressed and overcome to improve their efficacy. In this review, the basics of ADCs, physical and chemical properties, the evolution of design, limitations, and future potentials are discussed.
  13. Fulltext Knowledge, attitudes, and practices regarding Crimean-Congo hemorrhagic fever among general people: A cross-sectional study in Pakistan
    Jamil H, Din MFU, Tahir MJ, Saqlain M, Hassan Z, Khan MA, et al.
    PLoS Negl Trop Dis, 2022 Dec;16(12):e0010988.
    PMID: 36480553 DOI: 10.1371/journal.pntd.0010988
    BACKGROUND: Crimean-Congo hemorrhagic fever (CCHF) continues to pose a serious threat to the fragile healthcare system of Pakistan with a continuous increase of morbidity and mortality. The present study aimed to assess the knowledge, attitudes, and practices regarding CCHF among general people who resided in Pakistan.

    METHODS: An online cross-sectional survey design was applied, and a convenience sampling technique was used to recruit 1039 adult people from Pakistan. Data were collected from September 08 to October 12, 2021. The questionnaire consisted of a total of 32 questions in four parts assessing socio-demographics, as well as knowledge, attitudes, and practices regarding CCHF. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS), and logistic regression analyses were performed to determine the factors associated with good knowledge, positive attitudes, and good practices.

    RESULTS: Alarmingly, 51.5% of participants heard about CCHF infection before administering the survey. Among these, 20.2%, 33.3%, and 48.2% of the study participants had demonstrated good knowledge, positive attitudes, and good practices, respectively. Binary logistic regression analysis revealed that education and income status had a significant impact on knowledge and attitudes (p<0.05). Similarly, the mean attitude scores differed significantly by age, education, and income status (p<0.05).

    CONCLUSIONS: The findings reflected inadequate levels of knowledge, attitudes, and practices regarding CCHF among general people in Pakistan which may regard as lower than expected. As CCHF is a highly contagious disease, it's urgent to initiate a comprehensive approach to handle the situation before it spreads further in Pakistan.

  14. Fulltext Self-medication dilemma in dengue fever
    Khan MA, Tahir MJ, Ameer MA, Nawaz RA, Asghar MS, Ahmed A
    Public Health Pract (Oxf), 2022 Dec;4:100298.
    PMID: 36570398 DOI: 10.1016/j.puhip.2022.100298
    This paper focuses on the trends of self-medication practices in treating symptoms that may lead to fatal complications in dengue. As dengue is a viral infection with increasing incidence, decision regarding its treatment is mostly affected by public health believes and practices to self-treat the condition by different home remedies, over-the-counter (OTC) drugs or using outdated prescription drugs that proved beneficial in the past experience. Poverty, lack of education, and poor access to health facilities pave the way for making such decisions. Future complications can be averted by raising awareness, counseling the patients and dispensing of pharmaceuticals with strict monitoring.
  15. Fulltext Illuminating the Molecular Intricacies of Exosomes and ncRNAs in Cardiovascular Diseases: Prospective Therapeutic and Biomarker Potential
    Khan FB, Uddin S, Elderdery AY, Goh KW, Ming LC, Ardianto C, et al.
    Cells, 2022 Nov 18;11(22).
    PMID: 36429092 DOI: 10.3390/cells11223664
    Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide. Accumulating evidences have highlighted the importance of exosomes and non-coding RNAs (ncRNAs) in cardiac physiology and pathology. It is in general consensus that exosomes and ncRNAs play a crucial role in the maintenance of normal cellular function; and interestingly it is envisaged that their potential as prospective therapeutic candidates and biomarkers are increasing rapidly. Considering all these aspects, this review provides a comprehensive overview of the recent understanding of exosomes and ncRNAs in CVDs. We provide a great deal of discussion regarding their role in the cardiovascular system, together with providing a glimpse of ideas regarding strategies exploited to harness their potential as a therapeutic intervention and prospective biomarker against CVDs. Thus, it could be envisaged that a thorough understanding of the intricacies related to exosomes and ncRNA would seemingly allow their full exploration and may lead clinical settings to become a reality in near future.
  16. Fulltext A Fault Tolerant Surveillance System for Fire Detection and Prevention Using LoRaWAN in Smart Buildings
    Safi A, Ahmad Z, Jehangiri AI, Latip R, Zaman SKU, Khan MA, et al.
    Sensors (Basel), 2022 Nov 01;22(21).
    PMID: 36366109 DOI: 10.3390/s22218411
    In recent years, fire detection technologies have helped safeguard lives and property from hazards. Early fire warning methods, such as smoke or gas sensors, are ineffectual. Many fires have caused deaths and property damage. IoT is a fast-growing technology. It contains equipment, buildings, electrical systems, vehicles, and everyday things with computing and sensing capabilities. These objects can be managed and monitored remotely as they are connected to the Internet. In the Internet of Things concept, low-power devices like sensors and controllers are linked together using the concept of Low Power Wide Area Network (LPWAN). Long Range Wide Area Network (LoRaWAN) is an LPWAN product used on the Internet of Things (IoT). It is well suited for networks of things connected to the Internet, where terminals send a minute amount of sensor data over large distances, providing the end terminals with battery lifetimes of years. In this article, we design and implement a LoRaWAN-based system for smart building fire detection and prevention, not reliant upon Wireless Fidelity (Wi-Fi) connection. A LoRa node with a combination of sensors can detect smoke, gas, Liquefied Petroleum Gas (LPG), propane, methane, hydrogen, alcohol, temperature, and humidity. We developed the system in a real-world environment utilizing Wi-Fi Lora 32 boards. The performance is evaluated considering the response time and overall network delay. The tests are carried out in different lengths (0-600 m) and heights above the ground (0-2 m) in an open environment and indoor (1st Floor-3rd floor) environment. We observed that the proposed system outperformed in sensing and data transfer from sensing nodes to the controller boards.
  17. Fulltext Synthesis, characterization, molecular docking and biological evaluation of Schiff Base derivatives of cefpodoxime
    Mahmood W, Ahmad I, Khan MA, Ali Shah SA, Ashraf M, Shahzad MI, et al.
    Heliyon, 2022 Nov;8(11):e11332.
    PMID: 36387450 DOI: 10.1016/j.heliyon.2022.e11332
    Synthesis of new Cefpodoxime derivatives via Schiff Bases mechanism and the efficiency of their antimicrobial and antiviral activities were addressed. They were analyzed for structural validation by using spectroscopic techniques using FTIR, 1HNMR, and 13CNMR. Molecular docking against IBV Virus papain-like protease (PLPro) was done with Auto dock tools against compounds having excellent IC50 values against IBV (Corona Class) virus. All derivatives showed strong zone of inhibition ranges from (55 ± 2.0 to 70 ± 0.8 mm) against E. coli. Compounds 1,2,4 and 6 derivatives showed remarkable activity against Stenotrophomonas maltophilia and Serratia marcescens. But For most the newly synthesized derivatives C 1 (64 ± 1.60), C 3 (32 ± 0.80), and C 8 (64 ± 1.60) showed potential IC50 values against two variants of Corona class viruses i.e. Avian Influenza (H9) and Avian corona (IBV) viruses. The current study revealed that newly synthesized Schiff Bases possessed strong anti-viral potential. Further studies may make a breakthrough in medical sciences to tackle latest challenges such as Corona Virus Diseases.
  18. Fulltext A secure healthcare 5.0 system based on blockchain technology entangled with federated learning technique
    Rehman A, Abbas S, Khan MA, Ghazal TM, Adnan KM, Mosavi A
    Comput Biol Med, 2022 Nov;150:106019.
    PMID: 36162198 DOI: 10.1016/j.compbiomed.2022.106019
    In recent years, the global Internet of Medical Things (IoMT) industry has evolved at a tremendous speed. Security and privacy are key concerns on the IoMT, owing to the huge scale and deployment of IoMT networks. Machine learning (ML) and blockchain (BC) technologies have significantly enhanced the capabilities and facilities of healthcare 5.0, spawning a new area known as "Smart Healthcare." By identifying concerns early, a smart healthcare system can help avoid long-term damage. This will enhance the quality of life for patients while reducing their stress and healthcare costs. The IoMT enables a range of functionalities in the field of information technology, one of which is smart and interactive health care. However, combining medical data into a single storage location to train a powerful machine learning model raises concerns about privacy, ownership, and compliance with greater concentration. Federated learning (FL) overcomes the preceding difficulties by utilizing a centralized aggregate server to disseminate a global learning model. Simultaneously, the local participant keeps control of patient information, assuring data confidentiality and security. This article conducts a comprehensive analysis of the findings on blockchain technology entangled with federated learning in healthcare. 5.0. The purpose of this study is to construct a secure health monitoring system in healthcare 5.0 by utilizing a blockchain technology and Intrusion Detection System (IDS) to detect any malicious activity in a healthcare network and enables physicians to monitor patients through medical sensors and take necessary measures periodically by predicting diseases. The proposed system demonstrates that the approach is optimized effectively for healthcare monitoring. In contrast, the proposed healthcare 5.0 system entangled with FL Approach achieves 93.22% accuracy for disease prediction, and the proposed RTS-DELM-based secure healthcare 5.0 system achieves 96.18% accuracy for the estimation of intrusion detection.
  19. Fulltext A Novel Design and Development of a Strip-Fed Circularly Polarized Rectangular Dielectric Resonator Antenna for 5G NR Sub-6 GHz Band Applications
    Illahi U, Iqbal J, Irfan M, Ismail Sulaiman M, Khan MA, Rauf A, et al.
    Sensors (Basel), 2022 Jul 25;22(15).
    PMID: 35898037 DOI: 10.3390/s22155531
    In this article, a rectangular dielectric resonator antenna (RDRA) with circularly polarized (CP) response is presented for 5G NR (New Radio) Sub-6 GHz band applications. A uniquely shaped conformal metal feeding strip is proposed to excite the RDRA in higher-order mode for high gain utilization. By using the proposed feeding mechanism, the degenerate mode pair of the first higher-order, i.e., TEδ13x at 4.13 GHz and TE1δ3y, at 4.52 GHz is excited to achieve a circularly polarized response. A circular polarization over a bandwidth of ~10%, in conjunction with a wide impedance matching over a bandwidth of ~17%, were attained by the antenna. The CP antenna proposed offers a useful gain of ~6.2 dBic. The achieved CP bandwidth of the RDRA is good enough to cover the targeted 5G NR bands around 4.4−4.8 GHz, such as n79. The proposed antenna configuration is modelled and optimized using computer simulation technology (CST). A prototype was built to confirm (validate) the performance estimated through simulation. A good agreement was observed between simulated and measured results.
  20. Fulltext A review on the contamination of SARS-CoV-2 in water bodies: Transmission route, virus recovery and recent biosensor detection techniques
    Zamhuri SA, Soon CF, Nordin AN, Ab Rahim R, Sultana N, Khan MA, et al.
    Sens Biosensing Res, 2022 Jun;36:100482.
    PMID: 35251937 DOI: 10.1016/j.sbsr.2022.100482
    The discovery of SARS-CoV-2 virus in the water bodies has been reported, and the risk of virus transmission to human via the water route due to poor wastewater management cannot be disregarded. The main source of the virus in water bodies is the sewage network systems which connects to the surface water. Wastewater-based epidemiology has been applied as an early surveillance tool to sense SARS-CoV-2 virus in the sewage network. This review discussed possible transmission routes of the SARS-CoV-2 virus and the challenges of the existing method in detecting the virus in wastewater. One significant challenge for the detection of the virus is that the high virus loading is diluted by the sheer volume of the wastewater. Hence, virus preconcentration from water samples prior to the application of virus assay is essential to accurately detect traceable virus loading. The preparation time, materials and conditions, virus type, recovery percentage, and various virus recovery techniques are comprehensively discussed in this review. The practicability of molecular methods such as Polymer-Chain-Reaction (PCR) for the detection of SARS-CoV-2 in wastewater will be revealed. The conventional virus detection techniques have several shortcomings and the potential of biosensors as an alternative is also considered. Biosensing techniques have also been proposed as an alternative to PCR and have reported detection limits of 10 pg/μl. This review serves to guide the reader on the future designs and development of highly sensitive, robust and, cost effective SARS-CoV-2 lab-on-a-chip biosensors for use in complex wastewater.
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