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Recent Submissions
Advanced graphene–MXene–black phosphorus multilayered metasurface sensor for high-sensitivity terahertz brain tumor detection
(AIP Advances, 2026-03-11) Wekalao, Jacob; Elsayed, Hussein A.; Alqhtani, Haifa A.; Almawgani, Abdulkarem H. M; Gumaih, Hussein S.; Adam, Yousif S.; Mehaney, Ahmed; Ochen, William
In this research, we present a multilayer metasurface sensor design integrating graphene, MXene, black phosphorus, and gold for the ultrasensitive detection of brain tumor biomarkers in liquid biopsy samples. The hierarchical structure consists of a MXene-coated rectangular resonator, a black phosphorus-coated square resonator, a gold-coated circular ring, and a graphene-based circular substrate. This architecture was systematically optimized through comprehensive numerical simulations using COMSOL Multiphysics 6.3, integrated with machine learning frameworks. The proposed sensor demonstrates an outstanding sensitivity of 2308 GHz/RIU across a physiologically relevant refractive index range (1.3333–1.4833), significantly outperforming current state-of-the-art devices. Performance analysis identifies an optimal sensing regime at RI = 1.3425, achieving a figure of merit of 20.79 RIU−1 and a detection limit as low as 0.079 RIU. Detailed investigations of the transmission spectra under varying graphene chemical potentials (0.1–0.9 eV), incident angles (0○ –80○ ), and geometric modifications of the resonators reveal highly tunable sensing behavior. Furthermore, Random Forest Regression models achieve predictive accuracies of 85%–100%, enabling reliable estimation of sensor performance across diverse operating conditions. Collectively, these results establish a solid foundation for employing advanced 2D material–based metasurfaces in minimally invasive and early-stage brain tumor diagnostics, thereby advancing the capabilities of next-generation liquid biopsy technologies.
Production of typeface using the long-horns of Ankole cattle: a case of Mbarara municipality
(Kyambogo University (Unpublished work), 2024-08) Himbisa, Nimrod
The purpose of this study was to develop typeface from the long-horns of Ankole cattle with the aim of preserving the Ankole heritage through their creations. The objectives of the study were to; examine the long-horned Ankole cattle of Mbarara, explore ideas for creating long-horned Ankole typeface and develop typeface from long-horned Ankole cattle. The study had a population of 13 respondents who provided information through interviews and analysing documents in the possession. The study was qualitative and used descriptive approach. The findings indicate that long-horned Ankole cattle had numerous characteristics suitable for the creation of typeface, providing wide range of options to fully develop and create typefaces. The use of manual and digital process was essential in the refinement of the final characters. The findings could impact graphic designers by introducing a unique, culturally enriched typeface that can be used in various design applications. The study highlights how integrating cultural elements into typeface design using an exploratory research design can enhance the visual identity and storytelling aspects of graphic design projects. By creating typeface that embody the distinct features of the Ankole long-horned cattle, designers can add a layer of cultural significance and authenticity to their work. The study also recommends exploring other characteristics of the long-horned Ankole cattle for typeface creation, further expanding the variety of culturally inspired typeface available for use in the graphic design industry
Terahertz plasmonic metasurface sensor with graphene–CNT–copper integration for enhanced glucose sensing performance
(Indian J Phys, 2026-02-16) Wekalao, J; Elsayed, H A; Bin-Jumah, M; Almawgani, A H M; Gumaih, H S; Adam, Y S; Mehaney, A; Rajakannu, A; Muheki, J
This study presents a simplified terahertz biosensor that synergistically integrates graphene, carbon nanotubes, and copper to achieve an enhanced glucose sensing performance. Meanwhile, our sensing platform consists of a centrally positioned square resonator functionalized with carbon nanotubes, coupled to two copper-modified rectangular resonators lithographically patterned on a silicon dioxide substrate. The numerical findings based on the well-known Finite element method simulations performed in COMSOL Multiphysics identify an optimal operating frequency of 0.58 THz, delivering a maximum sensitivity of 1000 GHzRIU-1 over a refractive index range of 1.335–1.347 RIU. Additionally, our biosensor demonstrates strong performance metrics, including a quality factor (Q-factor) of 8.391, a figure of merit (FOM) of 14.493 RIU-1 , and a detection limit of 0.133. moreover, the machine learning analysis based on Polynomial regression technique is considered to validate the analytical consistency and operational robustness of the device, achieving predictive accuracies exceeding 90% under the variations of both graphene chemical potential and incident angle of the propagating electromagnetic waves. In this regard, we believe that, the combination of high sensitivity, predictive stability, and resilience to multi-parameter perturbations establishes the X-configuration architecture as a competitive platform for
glucose biosensing. Moreover, the multi-material engineering strategy constitutes a meaningful advancement in terahertz biosensor design by exploiting complementary physicochemical properties within an optimized X-shaped geometry to enhance functional performance.
Tackling workplace sexual harassment
(Institute of Development Studies, 2022-05-23) Oosterom, Marjoke; Huq, Lopita; Namuggala, Victoria; Nazneen, Sohela; Nankindu,Prosperous; Sultan, Maheen; Sultana, Asifa; Azim, Firdous
Employment is believed to be a crucial avenue for women’s empowerment, yet widespread workplace sexual harassment undermines this in many countries. Young and unmarried women from poor backgrounds are particularly at risk, but workplace sexual harassment is often overlooked in debates on decent jobs for youth. Based on case study research with factory and domestic workers in Bangladesh and Uganda, this briefing explains how social and gender norms constrain young women’s voices and agency in response to sexual harassment. It offers recommendations towards developing the laws, mechanisms and culture needed to reduce workplace sexual harassment and empower young women in their work.
Machine learning–enhanced tunable terahertz metasurface sensor with a hybrid multi-resonator architecture for highsensitivity mino acid detection
(Optical and Quantum Electronics, 2026-02-28) Muheki, Jonas; Ahmed, Ashour M.; Ali, M. K. M.; Elsayed, Hussein A.; Kabarokole, Pelluce; Wekalao, Jacob; Mehaney, Ahmed; Rajakannu, Amuthakkannan
Accurate amino acid detection is essential for biomedical diagnostics, clinical monitoring, and biochemical research; however, conventional analytical techniques are often constrained by complex sample preparation, high operational costs, and limited real-time capability. Terahertz (THz) metasurface sensors provide a promising label-free and nonionizing alternative, yet their performance is frequently hindered by weak light–matter interaction and design trade-offs between sensitivity and fabrication feasibility.
In this work, a hybrid THz metasurface sensor is proposed, integrating graphene, gold (Au), silver (Ag), copper (Cu), and tungsten disulfide (WS₂) within a hierarchical multiresonator configuration comprising square, circular ring, and L-shaped resonators fabricated on a SiO₂ substrate. The proposed architecture exploits synergistic plasmonic–dielectric coupling and strong near-field confinement to enhance sensitivity to refractive index perturbations induced by amino acid analytes, while maintaining a geometrically simplified structure to ensure manufacturability.
Numerical simulations demonstrate excellent sensing performance, achieving a maximum sensitivity of 1000 GHz/RIU, a peak figure of merit (FOM) of 50 RIU⁻1 , and a strong linear relationship (R2=0.96243) between resonance frequency shift and analyte refractive index. Furthermore, machine learning (ML) models are employed to predict and optimize sensor behavior, yielding near-perfect accuracy (R2>0.9995) for variations in
graphene chemical potential (0.1–0.9 eV) and circular resonator dimensions (5.5–7.5 µm).
The proposed integration of hybrid materials, multi-resonator metasurface design, and ML-driven optimization effectively addresses key challenges in THz biosensing, enabling rapid, sensitive, and scalable amino acid detection for both point-of-care diagnostics and advanced biochemicalresearch.