We present a new empirical vertical drift model developed using ground-based magnetometer, radar, and satellite data over equatorial latitude regions. We first implement an algorithm relating magnetometer derived equatorial electrojet (EEJ) and vertical ion plasma drift (equivalent to vertical drift within magnetic latitudes of and altitudes of about 400-550 km) from the Communications and Navigation Outage Forecasting System (C/NOFS) satellite at different longitude sectors. The relationship between EEJ and C/NOFS vertical drift is developed separately at different longitudes over the globe at coincidental times when both data sets are available. These relationships are then used to estimate continuous vertical drift at each epoch of EEJ observation over the respective longitude sectors during local daytime. The reconstructed vertical drift data are combined with global C/NOFS vertical drifts and JULIA data set to develop a global vertical drift model. Validation using Ion Velocity Meter (IVM) drifts from ICON satellite for January to August 2022 shows that our model improves vertical drift global modeling by over 20% compared to the current climatology representation.
Cyberbullying has become a significant behavioural and psychosocial challenge associated with social networking site use among university students. Although prior research recognises that cyberbullying affects individuals differently, limited empirical work has examined how gender shapes experiences, impacts, and coping strategies, particularly in Global South contexts. Grounded in stress–coping theory and gender-sensitive cyberpsychology perspectives, this study investigates gendered experiences of cyberbullying on Facebook among undergraduate students in Kenya. A convergent parallel mixed-methods design was employed, combining survey data from 3,020 students across 24 public and private universities with insights from 24 focus group discussions. Quantitative data were analysed using descriptive and inferential statistics, while qualitative data were thematically analysed to contextualise students’ lived experiences. Findings reveal that cyberbullying is widespread and distinctly gendered. Male students reported higher overall exposure, whereas female students experienced more relational and reputational forms, particularly shaming and cyberstalking. Female students also reported more severe psychological, social, and academic impacts, reflecting heightened appraisal of relational harm. In contrast, male students were more likely to experience impersonation and exposure and to downplay psychological distress. Coping strategies differed significantly: females favoured social support, counselling, and privacy-protection measures, while males relied more on avoidance, disengagement, or retaliatory responses, often perceived as less effective. The study demonstrates that cyberbullying is shaped by gendered socialisation processes and contextual factors within Kenyan higher education. It underscores the need for gender-responsive prevention and intervention strategies and contributes to a more nuanced understanding of cyberbullying in non-Western digital environments.
Abstract The paper examines the decorrelation gain achievable for M-ary Quadrature Amplitude Modulation (M-QAM) and Binary Phase-shift Keying (BPSK) schemes in spatial diversity configurations, where virtually synthesized signals are applied over Nakagami-m fading channels. The signals are embedded in additive white Gaussian noise (AWGN). The primary form of the suggested virtual signal synthesizer involves shifting the phase of the generated output signals. To obtain the decorrelation gain, an orthogonal transformation matrix is utilized. This matrix ensures energy preservation, is blind to channel correlation, and does not require explicit signal information. The aim is to generate virtual signal that would be equivalent to those received from a system with more antennas. An analytical framework is developed to assess how fading severity, diversity order, and branch correlation influence Symbol Error Rate (SER) characteristics. Monte-Carlo simulations validate the analytical results. Various antenna configurations and fading severities (m = 0.5, 1, 3, 5) are explored. Additionally, the impact of different antenna spacings (0.1, 0.2, 0.5 wavelengths) is analyzed under a uniform angle of arrival. The results indicate that decorrelation gains are obtained, with a moderate dependence on the fading severity parameter m. However, this dependence becomes negligible for higher values of m.
We present an efficient and accurate implementation of hybrid exchange-correlation (XC) functionals in the siesta code, enabling large-scale simulations based on Hartree-Fock-type exact exchange combined with strictly localized numerical atomic orbitals (NAOs). Our approach exploits a fitted representation of the NAOs in terms of Gaussian-type orbitals (GTOs), which allows for the analytical evaluation of four-center electron repulsion integrals (ERIs) via the libint library. This framework is seamlessly integrated with siesta’s real-space grid and sparse-matrix infrastructure, and is combined with multiple screening techniques to control the computational complexity. We also introduce a fully analytical formulation of hybrid-functional forces and a dynamic parallel distribution scheme that ensures excellent scalability. We validate our implementation through benchmark calculations on a broad set of systems (including semiconductors, insulators, and two-dimensional materials) and demonstrate that the HSE06 functional significantly improves the prediction of band gaps compared to PBE, in close agreement with G0W0 and experimental data. We analyze in detail the trade-offs between accuracy and computational efficiency as a function of the number of Gaussians, basis set range, and integral screening thresholds. Our results confirm that hybrid functional calculations in siesta are now feasible for large extended systems, making accurate first-principles predictions of electronic and structural properties accessible at scale.
The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) provides global Radio Occultation (RO) measurements of ionospheric total electron content (TEC), but these values are systematically underestimated relative to ground-based Global Navigation Satellite System (GNSS)-derived TEC due to the exclusion of the plasmaspheric contribution. This study presents a machine learning calibration framework that transforms COSMIC TEC into GNSS-equivalent values. Using co-located COSMIC and GNSS observations from 2006 to 2025, we developed neural network models (ROTEC-A and ROTEC-B) trained on (19 and 22) input features respectively, including COSMIC profile parameters, spatiotemporal descriptors, and optionally, solar and geomagnetic activity indices. Results show that the calibration effectively mitigates systematic underestimation, reducing mean bias from 6.97 TECU (uncalibrated COSMIC) to near zero (0.02-0.03 TECU). The calibrated products also substantially reduce skewness in residuals, yielding nearly symmetric error distributions suitable for data assimilation. Across various latitudinal, local time, and seasonal sectors, mean absolute errors were reduced by 50-75%, with the best performance at mid-latitudes and slightly elevated errors in high-latitude and equatorial regions. Although, the inclusion of solar and geomagnetic indices yielded marginal improvements, statistical tests confirmed no significant advantage over the baseline model. The operationally oriented framework outputs calibrated GNSS-equivalent TEC in near real-time, providing enhanced ionospheric monitoring capability, especially over GNSS-sparse regions such as oceans and deserts.These results demonstrate the potential of COSMIC RO data, once calibrated, to serve as a reliable complement to GNSS observations for ionospheric research, space weather monitoring, and operational applications. (c) 2026 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
