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Vol – 1, No. 4, April – June 2026

COMPREHENSIVE REVIEW OF MICROSTRIP FILTERS FOR GLUCOSE AND TENSION SENSING APPLICATIONS

Authors:

Shahad K. Khaleel

DOI:

Abstract:

This review paper provides a rigorous and comprehensive analysis and sets up a unified electromagnetic (EM) framework for planar microstrip resonant filters for two seemingly different but electromagnetically similar applications: non-invasive blood glucose monitoring and structural tension sensing. This work connects biochemical and mechanical tracking, studying the convergence of high-frequency planar technologies and complex material media. Four important microwave resonator topologies are analysed in detail, including Split Ring Resonators (SRR), Complementary Split Ring Resonators (CSRR), Hairpin Resonators, and Stub-Loaded Resonators (SLR). The underlying transduction physics is rigorously formulated, using the 3D vector cavity perturbation theory and conformal mapping expressions, coupled with modified first-order Cole-Cole dielectric relaxation equations. Mechanical strain deformation is explicitly linked to matrices of transmission lines to map physical elongation, Poisson’s ratio, and substrate elastomeric variations directly to resonance perturbations. Performance benchmarks are synthesized through a quantitative meta-analysis of literature covering the last five years, highlighting the basic trade-offs among near-field localization, quality factor (QL), and linear correlation coefficient (R2). In addition, we tackle some of the key engineering challenges, including the high loss tangent of human tissue, water absorption damping between 2-10 GHz, and thermal-mechanical drift cross-sensitivity. A multi-parameter calibration matrix framework, based on an isolated reference resonance peak, is described to overcome these multi-parameter interferences. Lastly, we discuss future directions for edge-computed machine learning calibration engines and passive, battery-free, chipless telemetry radio frequency identification (RFID) sensor tags for remote deployment.

Keywords:

Cavity Perturbation Theory, Complementary Split Ring Resonator (CSRR), Dielectric Characterization, Microstrip Resonator, Non-Invasive Glucose Sensing, Structural Health Monitoring (SHM), Tensile Strain Telemetry

Refference:

1. Burton, Andrew R., et al. “Fully integrated carbon nanotube composite thin film strain sensors on flexible substrates for structural health monitoring.” Smart Materials and Structures 26.9 (2017): 095052. 10.1088/1361-665X/aa8105
2. Zubair, Muhammad, et al. “A high-performance sub-THz planar antenna array for THz sensing and imaging applications.” Scientific Reports 14.1 (2024): 17030. 10.1038/s41598-024-68010-9
3. Malik, Jagannath, et al. “Minimally invasive implant type electromagnetic biosensor for continuous glucose monitoring system: In vivo evaluation.” IEEE Transactions on Biomedical Engineering 70.3 (2022): 1000-1011. 10.1109/TBME.2022.3207240
4. Juan, Carlos G., et al. “Feasibility study of portable microwave microstrip open-loop resonator for non-invasive blood glucose level sensing: Proof of concept.” Medical & Biological Engineering & Computing 57.11 (2019): 2389-2405. 10.1007/s11517-019-02030-w
5. Abdolrazzaghi, Mohammad, et al. “Noninvasive glucose sensing in aqueous
solutions using an active split-ring resonator.” IEEE Sensors Journal 21.17 (2021): 18742-18755. 10.1109/JSEN.2021.3090050
6. Sifat, Md Nahid Hasan, and Md Jahirul Islam. “Development of dual-parametric complementary split ring resonator-based microstrip patch antenna sensor for non-invasive blood glucose monitoring.” Optical and Quantum Electronics 57.12 (2025): 663. https://link.springer.com/article/10.1007/s11082-025-08594-2
7. Mechael, Sara. “Advanced Substrates for Wearable and Printed Electronics.” PhD diss., University of Windsor (Canada), 2022. https://hdl.handle.net/20.500.14776/8396
8. Watts, Kristen E., Thomas J. Blackburn, and Jeanne E. Pemberton. “Optical spectroscopy of surfaces, interfaces, and thin films: A status report.” Analytical Chemistry 91.7 (2019): 4235-4265. 10.1021/acs.analchem.9b00735
9. Dong, T. (2026). Emerging Ultrasensitive Biosensing Technologies. In Micro-Nano Systems for Biomolecule Sensing (pp. 525-565). Singapore: Springer Nature Singapore.
10. Zakaria, Ahmed A., Ahmed Allam, and Adel B. AbdelRahman. “Microwave based non-invasive blood glucose sensors: key design parameters and case-informed evaluation.” IEEE Access (2025). https://ieeexplore.ieee.org/document/11123711
11. Alam, Md Shahidul, et al. “Development of electromagnetic band gap structures in the perspective of microstrip antenna design.” International Journal of Antennas and Propagation 2013.1 (2013): 507158. 10.1155/2013/507158
12. Gonzalez, Mario, et al. “Design and implementation of flexible and stretchable systems.” Microelectronics Reliability 51.6 (2011): 1069-1076. 10.1016/j.microrel.2011.03.012
13. Daliri, Ali. “Development of microstrip patch antenna strain sensors for wireless structural health monitoring. Diss.” RMIT University, 2024. 10.25439/rmt.27581673
14. Liu, Han, and Simon Laflamme. “Large-scale reconfigurable metamaterials.” Smart Materials and Structures 34.10 (2025): 103002. 10.1088/1361-665X/ae0edf
15. Lee Hyun-jae. “Integrated Electrochemical Sensors and Actuators for Multifunctional Surgical Endoscope and Glucose Monitoring System.” Diss. Seoul National University Graduate School. 2016.
16. Zhu, Jianxiong, et al. “Artificial Intelligence of Things in Hydrogen Sensing: Toward Optic and Intelligent System.” Research 8 (2025): 0750. 10.34133/research.0750
17. Hakemi, Ghazal. “Fabrication, development and analysis of Film Bulk Acoustic Resonators on flexible polymer substrates.” (2010).
18. Liu, Q., Peng, Z., Sun, C., & Yang, H. (2026). “Recent advances in multifunctional soft robots: A materials–structures–systems co‐design perspective for synergistic integration.” FlexMat. 10.1002/flm2.70053
19. Catherall, Thomas. New Geometries for Ring Resonator Sensing. The University of Manchester (United Kingdom), 2017. https://research.manchester.ac.uk/en/studentTheses/new-geometries-for-ring-resonator-sensing/
20. Wang, Ruihua, et al. “A Review of the Structure, Performance, Fabrication, and Impacts of Application Conditions on Wearable Textile GNSS Antennas.” Textiles 5.3 (2025): 35. 10.3390/textiles5030035

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Breast Self-Examination Practices Among Undergraduate Nursing Students: An Institutional Study

Authors:

Susama Pradhan

DOI:

Abstract:

Background: Breast cancer is the most common form of cancer among women in India. Early detection plays a vital role in reducing mortality rates and improving the quality of life. Breast self-examination (BSE) is an easy and economical method for detecting any abnormalities. Nursing students play an important role as future healthcare professionals in educating people about breast cancer.

Objectives: This study was conducted to measure the knowledge and practices of BSE among the first year B.Sc. Nursing students and to establish the relationship between the two variables.

Methods: A descriptive cross-sectional study was conducted among 80 first year B.Sc. Nursing students studying at SCB College of Nursing, Cuttack. Convenience sampling technique was used for data collection. Structured questionnaire and checklist were used for data collection. Inferential and descriptive statistics were used for analysis.

Results: Findings revealed that 52.5% of the participants had insufficient knowledge about BSE and 68.75% had never performed BSE regularly. There exists a positive correlation (r= 0.42) between the scores on knowledge and practices.

Conclusion: There was a wide knowledge-practice gap found among nursing students. Recommendations include conducting workshops and practical sessions for the students.

Keywords:

Breast Self-Examination, Breast Cancer, Nursing Students, Knowledge, Practice, Awareness, Early Detection

Refference:

1. World Health Organization. “Breast Cancer.” World Health Organization, 2023. Accessed 16 May 2026.
2. Chandani, Kanishka Uttam, et al. “Awareness of Breast Cancer and Breast Self-Examination among Nursing Students.” International Journal of Community Medicine and Public Health, vol. 7, no. 4, 2020, pp. 1382–1386. 10.18203/2394-6040.ijcmph20201441.
3. Jadhav, Bhoomika N., et al. “Knowledge, Attitude, and Practice of Breast Self-Examination Is Associated with General Self-Care and Cultural Factors: A Study from Tamil Nadu, India.” BMC Women’s Health, vol. 24, 2024, article 151. 10.1186/s12905-024-02981-9.
4. Sachdeva, S., S. Mangalesh, and S. Dudani. “Knowledge, Attitude and Practices Regarding Breast Self-Examination among Indian Women.” Asian Pacific Journal of Cancer Care, vol. 6, no. 2, 2021, pp. 141–147. 10.31557/apjcc.2021.6.2.141-147
5. Paulsamy, P., S. H. Alshahrani, and A. A. Qureshi. “Breast Self-examination: Knowledge, Attitude and Practice among Female College Students. ” Journal of Pharmaceutical Research International, vol. 33, no. 43B, 2021, pp. 460–465. 10.9734/JPRI/2021/v33i43B32575.
6. Mulyani, E., M. Triharini, and T. Kusumaningrum. “The Effect of Lecture, Brainstorming, Demonstration Towards Breast Self-Examination Behavior Based on Health Belief Model.” Pediomaternal Nursing Journal, vol. 7, no. 2, 2021, pp. 87–94. 10.20473/pmnj. v7i2.27468.
7. Kaur, Ramandeep. “A Quasi Experimental Study to Evaluate the Effectiveness of Demonstration on Practice Regarding Breast Self-Examination among Girls of Selected Arts Colleges of Jalandhar, Punjab.” International Journal of Nursing Care, vol. 9, no. 1, 2021, pp. 17–20. 10.37506/ijonc. v9i1.13996
8. Prusty, Ranjan Kumar, et al. “Increasing Breast Cancer Awareness and Breast Examination Practices among Women through Health Education and Capacity Building of Primary Healthcare Providers: A Pre-Post Intervention Study in Low Socioeconomic Area of Mumbai, India.” BMJ Open, vol. 11, no. 4, 2021, e045424. 10.1136/bmjopen-2020-045424
9. Choudhary, Mamta, Sekkulandai K. Mohanasundari, and Meena Ara. “Breast Self-Examination: Knowledge, Awareness, and Practices among Females of Reproductive Age Group.” International Journal of Research in Medical Sciences, vol. 12, no. 6, 2024, pp. 1999–2003. 10.18203/2320-6012.ijrms20241548
10. Ishtiak, ASM, et al. “Knowledge, Practice and Associated Factors of Breast Self-Examination among Female University Students of Bangladesh.” Heliyon, vol. 8, no. 11, 2022, e11780. 10.1016/j.heliyon. 2022.e11780

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Discrete Fasting in Weight Loss: Metabolic Mechanisms, Clinical Outcomes, and Future Perspectives

Authors:

Ank Gabor

DOI:

Abstract:

One of the most effective dietary strategies for weight loss and improving metabolic health is known as Discrete Fasting or Intermittent Fasting (IF). Discrete fasting is different from traditional diets of continuous calorie reduction, which alternate periods of fasting with feeding, thereby promoting metabolic adaptation towards improved fat oxidation and ketone utilization. Although the beneficial effects of fasting-based treatments on body composition, insulin sensitivity, lipid metabolism and cardiovascular markers have been shown in recent clinical trials, the mechanism behind these remains unclear. The present paper includes a detailed analytical discussion on the physiological, metabolic and clinical implications of discrete fasting in weight management. A simulated comparative study is included with the paper that focuses on continuous calorie restriction, time-restricted eating and alternate day fasting. Several tables and valid graphical figures are used to illustrate the changes in body weight, body mass index, blood glucose level, body fat percentage and lipid profiles. The results show that the alternate day fast and time-restricted eating result in better metabolism than traditional calorie restricting strategies. In addition, the paper describes the mechanisms of fasting, such as ketosis, hormonal adaptations, depletion of glycogen, and autophagy. The possibilities for future applications such as AI, wearable health systems, bespoke fasting plans and digital nutrition monitoring are also discussed. The study findings indicate that discrete fasting is an effective and viable method of obesity control and metabolic optimization.

Keywords:

Discrete fasting, intermittent fasting, obesity, weight loss, insulin sensitivity, metabolism, alternate-day fasting, time-restricted eating, metabolic health

Refference:

1. M. P. Mattson, V. D. Longo, and M. Harvie, “Impact of intermittent fasting on health and disease processes,” Ageing Research Reviews, vol. 39, pp. 46–58, 2017. 10.1016/j.arr.2016.10.005.
2. K. A. Varady, “Intermittent versus daily calorie restriction: Which diet regimen is more effective for weight loss?” Obesity Reviews, vol. 12, no. 7, pp. e593–e601, 2011. 10.1111/j.1467-789X.2011.00873.x.
3. J. F. Trepanowski et al., “Effect of alternate-day fasting on weight loss, weight maintenance, and cardioprotection among metabolically healthy obese adults,” JAMA Internal Medicine, vol. 177, no. 7, pp. 930–938, 2017. 10.1001/jamainternmed.2017.0936.
4. R. E. Patterson and D. D. Sears, “Metabolic effects of intermittent fasting,” Annual Review of Nutrition, vol. 37, pp. 371–393, 2017. doi: 10.1146/annurev-nutr-071816-064634.
5. V. D. Longo and M. P. Mattson, “Fasting: Molecular mechanisms and clinical applications,” Cell Metabolism, vol. 19, no. 2, pp. 181–192, 2014. doi: 10.1016/j.cmet.2013.12.008.
6. S. D. Anton et al., “Flipping the metabolic switch: Understanding and applying the health benefits of fasting,” Obesity, vol. 26, no. 2, pp. 254–268, 2018. doi: 10.1002/oby.22065.
7. Herman, R., Trsan, J., Lipar, L., Jensterle, M., & Janez, A. (2025). Endocrine Adaptations to Prolonged Fasting: From Physiology, Clinical Uncertainties, Translational Challenges to Healthspan Implications. Nutrients, 17(24), 3949.
8. Clayton, David J., Ian Varley, and Maria Papageorgiou. “Intermittent fasting and bone health: a bone of contention?.” British Journal of Nutrition 130.9 (2023): 1487-1499. 10.1017/S0007114523000545
9. Templeman, I. (2019). The Impact of Intermittent Fasting on Energy Balance and Associated Health Outcomes (Doctoral dissertation, University of Bath).
10. Batterham, Rachel L., and David E. Cummings. “Mechanisms of diabetes improvement following bariatric/metabolic surgery.” Diabetes care 39.6 (2016): 893-901. 10.2337/dc16-0145

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The Evolution and Architecture of Agentic Open Source Intelligence

Authors:

Arunanshu Chatterjee, Anurag Roy

DOI:

Abstract:

This comprehensive review paper examines the ontological shift in Open Source Intelligence (OSINT). For decades, the field was strictly defined by the extraction of actionable intelligence from publicly accessible data, operating on a linear, highly manual pipeline that relied entirely on human cognitive processing. The advent of Agentic Artificial Intelligence (AI) fundamentally displaces this foundational paradigm. By transitioning the discipline from reactive data aggregation to proactive, autonomous execution, agentic architectures redefine the intelligence lifecycle, shifting the cognitive burden of data processing, correlation, and initial synthesis from human operators to autonomous algorithmic systems. To clarify the academic boundaries and methodological intent of this document, it must be explicitly stated that this is a comprehensive review paper rather than a presentation of singular novel empirical research. The objective of this review is to systematically aggregate, synthesize, and critically evaluate the theoretical, mathematical, and architectural state-of-the-art across the rapidly expanding domain of Agentic AI in cybersecurity and OSINT. By analyzing recent academic frameworks published across leading repositories—such as the Institute of Electrical and Electronics Engineers (IEEE), the Association for Computing Machinery (ACM), Springer, and Elsevier—this paper provides a definitive structural analysis of the current landscape. This review specifically addresses the mathematical foundations of autonomous reasoning through Bayesian probabilistic updating, constructs structural models of multi-agent collaborative topologies, evaluates the operational efficacy of specialized cybersecurity frameworks, and thoroughly examines the profound socio-technical friction generated by this paradigm shift, specifically focusing on the barrier of algorithmic trust, legal accountability deficits, and the emerging defensive imperative to track Non-Human Identities (NHIs).

Keywords:

Open Source Intelligence (OSINT), human cognitive processing, Agentic Artificial Intelligence, Bayesian probabilistic, Non-Human Identities (NHIs)

Refference:

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2. Ahmad, Ibrar, Laila Ahmad, Naila Irshad, and Muhammad Talha. 2025. “Artificial Intelligence in Autonomous Weapon Systems: Legal Accountability and Ethical Challenges.” Journal of Engineering, Science and Technological Trends 2 (1): 120–35.
3. Almeida Palmieri, Eduardo, Mohamed Chahine Ghanem, Viktor Sowinski-Mydlarz, and Dipo Dunsin. 2025. “A Framework for Embedding Generative and Agentic AI in Open Source Intelligence.” Proceedings of the 2025 7th International Conference on Blockchain Computing and Applications (BCCA), 838–44. 10.1109/bcca66705.2025.11229637.
4. Atlam, Hany F. 2025. “LLMs in Cyber Security: Bridging Practice and Education.” Big Data and Cognitive Computing 9 (7): 184. https://doi.org/10.3390/bdcc9070184.
5. Avalos, V. M., and C. Tunc. 2025. “Trust Evaluation Based on a Risk Assessment and Mitigation Framework.” Proceedings of the IEEE International Conference on Smart Internet of Things (SmartIoT), 145–52.
7. Banerjee, Tuhin, and Harpreet Singh. 2025. “Securing Non-Human Identities in Industrial IoT: A Blockchain-Based Trust Framework.” NIPES Journal of Science and Technology Research 7 (4): 228–46. 10.37933/nipes/7.4.2025.1660.
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9. Chaudhari, Harsh, Jamie Hayes, Matthew Jagielski, Ilia Shumailov, Milad Nasr, and Alina Oprea. 2025. “Cascading Adversarial Bias from Injection to Distillation in Language Models.” Proceedings of the ACM Conference on Computer and Communications Security (CCS).
10. Chaudhari, Harsh, Giorgio Severi, John Abascal, et al. 2026. “Phantom: General Trigger Attacks on Retrieval Augmented Language Generation.” ACM Transactions on AI Security and Privacy.
11. Chernikova, Alesia, Alina Oprea, Cristina Nita-Rotaru, and BaekGyu Kim. 2019. “Are Self-Driving Cars Secure? Evasion Attacks Against Deep Neural Networks for Self-Driving Cars.” IEEE Workshop on the Internet of Safe Things.
12. Dibsdale, Lucy. 2025. “Beyond Human Judgment – the Morality of Machines: A Critical Examination of the Ethical and Moral Dimensions of Autonomous and AI Weapon Systems in Modern Warfare.” Journal of Global Faultlines 12 (2): 129–49. 10.13169/jglobfaul.12.2.0002.
13. Feng, Shaohan, Wenbo Wang, Zehui Xiong, Dusit Niyato, Ping Wang, and Shaun Wang. 2021. “On Cyber Risk Management of Blockchain Networks: A Game Theoretic Approach.” IEEE Transactions on Services Computing 14 (5): 1492–504. 10.1109/TSC.2021.3054223.
14. Gangaiah, Y. K., K. Pappu, and Y. S. Thanvi. 2026. “DevSecOps-Driven Security Controls for ERP Release Pipelines.” Proceedings of the IEEE International Symposium on Digital Forensics and Security (ISDFS), 1–6.
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Comprehensive Evaluation of Tai Chi Chuan Intervention on Body Composition, Metabolic Biomarkers, and Cardiorespiratory Fitness in Obese Populations: A Randomized Controlled Trial and Mathematical Modeling Analysis

Authors:

Manal Al Rubae

DOI:

Abstract:

The global surge in obesity requires the validation of alternative, low-impact therapeutic frameworks capable of mitigating cardiorespiratory and metabolic deficiencies without inducing musculoskeletal injuries. This parallel-group randomized controlled trial over a 24-week period systematically investigates the effect of a structured Tai Chi Chuan (TCC) intervention compared to Conventional Aerobic Exercise (CAE) and a sedentary Control Group (CG) in a cohort of 150 obese adults. Whole-body dual-energy X-ray absorptiometry (DXA), cardiorespiratory metrics, lipid profiles, and circulating inflammatory markers were evaluated at baseline, 12 weeks, and 24 weeks. Simultaneously, a first-principles, non-linear, state-space bioenergetic mathematical model was formulated to map multi-joint kinematic vectors and neuromuscular co-contractions into long-term tissue-specific mass transformation trajectories. Empirically, the TCC cohort achieved a significant reduction in total fat mass (-4.26 kg) and a 12.8% reduction in visceral adipose tissue, matching the adaptations of the CAE group (-4.41 kg fat mass; 13.1% visceral adipose tissue loss). Crucially, TCC demonstrated preservation of lower-limb lean mass (+0.38 kg) and achieved an adherence rate of 94% due to reduced joint pain. Circulating hs-CRP and HOMA-IR decreased significantly by 22.4% and 26.4%, respectively, within the TCC cohort. The mathematical modeling system tracked actual mass changes with an R² accuracy of 0.942 for fat mass trajectory mapping. These findings establish that the slow-velocity, high-torque eccentric muscle loading intrinsic to TCC operates as a robust therapeutic alternative to traditional cardio exercise, validating it as a highly prescription-ready option for obesity rehabilitation frameworks.

Keywords:

Tai Chi Chuan, Visceral Adiposity, Metabolic Syndrome, Bioenergetic Shading Model, State-Space Estimation, Non-linear Muscle Torque, Clinical Optimization.

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