BUE Scholar (The British University in Egypt)
Not a member yet
4435 research outputs found
Sort by
A preference for dynamical phantom dark energy using one-parameter model with Planck, DESI DR1 BAO and SN data
No full textBaryon Acoustic Oscillation (BAO) provides a powerful tool to measure cosmic expansion and consequently the nature of the Dark Energy (DE). Recent precise BAO measurements by Dark Energy Spectroscopic Instrument data release 1 (DESI DR1), when combined with Cosmic Microwave Background (CMB) data from Planck and Supernovae of Type Ia (SN Ia), favor evolving dark energy over cosmological constant. This result is strongly related to the assumed priors on the Chevallier–Polarski–Linder (CPL) parametrization of DE. We test another parametrization which introduces two free parameters n and , only n is independent. Thus, it reduces the parameter space compared to the CPL model, which derives a more robust preference for evolving DE, if any. The model potentially produces three cosmological scenarios according to the values of its parameters. For n=3, the CDM model is recovered, quintessence for \u3c 3, and phantom for \u3e3. In the present study, we test the model on the background level, and, to our knowledge for the first time, on the linear perturbation level. Bayesian evidence analysis shows a weak preference (ln≤1.8) for dynamical DE in the phantom regime over the cosmological constant DE using Planck, DESI, and PantheonPlus & SH0ES data, similarly the AIC analysis supports dynamical DE scenario for the same data. The model predicts current phantom DE ,0=−1.073±0.032 and 0=70.9±1.4 km/s/Mpc when Planck+DESI data is used, which decreases the tension with 0 local measurements to 1.2 level
Residual stress and distortion analysis in WAAM steel blocks: A comparative study of build strategies
No full textBuild strategies can influence the mechanical and microstructural properties of wire and arc additively manufactured (WAAM) parts, hence, numerical models were used in this study to investigate the residual stresses and distortions in steel blocks fabricated through WAAM. A new plugin, SimuPrint, was developed for Rhino-Grasshopper, providing a seamless link to ABAQUS, enabling control over the build strategy during the simulation of the printing process. Three build strategies were considered: bead-wise alternating x-direction (Zx), layer-wise alternating x and y direction (XY), and layer-wise alternating x-direction (XX). Results indicated that the Zx strategy conceded lower distortions and stable von-Mises stresses compared to the other strategies. Furthermore, experimental validation conducted revealed that the Zx strategy produced steel blocks with the highest average yield (∼525.4 MPa) and ultimate (∼621 MPa) strengths compared to its counterparts. These findings highlight the effect of build strategy in optimizing the performance of WAAM-fabricated steel components
Enhanced energy harvesting from NF-PVDF piezoelectric material for wearable electronics: I– V characterization and charge-discharge performance
No full textThis study explores the utilization of fabricated piezoelectric polyvinylidene fluoride nanofiber (NF-PVDF) materials in wearable electronic sensing applications by investigating their current-voltage ( I − V ) characteristics under controlled ultra-low-frequency excitation forces. The results demonstrate a significant power harvesting capability, achieving an output power of 0.12 µW/mm2 at an operating point of 5.04 V and 7.7 µA. Additionally, the piezoelectric harvester was integrated into a charging-discharge circuit alongside a rectifier capacitor and a typical IoT wearable sensor, leveraging the advantages of a flexible substrate. Experimental measurements of the charging and discharging curves confirm the effective energy management of the system, indicating a robust potential for deployment in real-world sensing applications. These findings highlight the promising application of NF-PVDF in sustainable energy harvesting for next-generation wearable technologies
Multivariate Skew Normal Independent Nonlinear Mixed Model for Longitudinal Data
No full textThe multivariate nonlinear mixed effects models (MNLMM) have received increasing attention due to their flexibility in analyzing and modeling multivariate longitudinal data. In the framework of MNLMM, the random effects and within-subject errors are assumed to be normally distributed for mathematical tractability and computational simplicity. However, such assumption might not offer robust inference if the data, even after being transformed, exhibit skewness. In this paper, we propose a multivariate skew normal independent nonlinear mixed model (MSNI-NLMM) constructed by assuming a multivariate skew normal independent distribution for the random effects and a multivariate normal independent distribution for the random errors. We develop a new model which can flexibly handle asymmetric, unbalanced, and irregularly observed multivariate longitudinal data. Also, we present two different iterative algorithms for maximum likelihood estimation of the MSNI-NLMM. They are the penalized nonlinear least squares coupled to the multivariate linear mixed effects (PNLS-MLME) procedure and the pseudo-data expectation conditional maximization (ECM) algorithm. The proposed approaches are illustrated through an application to ACTG 315 data and a simulation study
The Impact of Russian-Ukrainian Conflict on International Financial Markets: A Comparative Analysis of Oil-importing and Oil-exporting Countries
No full textThis paper aims to examine the effect of the Russian–Ukrainian conflict on international financial markets. The authors investigate the impact of oil price fluctuations on stock markets’ performance in oilimporting versus oil-exporting countries in the period 2017–2023, pre and during the Russian–Ukrainian conflict
Sustainable TiO₂/sludge ceramic waste nanocomposite for high-efficiency Photodegradation of rhodamine B
No full textPhotocatalytic degradation of organic dyes presents a sustainable pathway for wastewater remediation; however, the high cost of conventional catalysts like TiO₂ limits their scalability. This study introduces a cost-effective and eco-friendly approach using industrial sludge ceramic waste (SCW), a hazardous byproduct rich in oxides like SiO₂, Al₂O₃, and CaO, as a useful co-catalyst with TiO₂ nanoparticles. The TiO₂/20wt%SCW composite shown remarkable photodegradation efficiency of 98.6 % for Rhodamine B under UV irradiation, comparable to pure TiO₂ (99.55 %) but at 20 % lower material cost. Structural and surface analysis revealed that SCW incorporation preserved the anatase phase, induced crystallographic strain (XRD), and introduced Ti4+/3+ and Ca2+ surface species (XPS), both of which promoted charge separation. The engineered composite also exhibited a reduced bandgap of 2.96 eV (from 3.2 eV for pristine TiO₂), and a BET surface area of 133.27 m2/g, facilitating enhanced light absorption and dye adsorption. This work demonstrates a novel dual valorization strategy—remediating dye pollutants while repurposing ceramic waste—and offers a viable model for designing low-cost, high-performance photocatalysts through waste-derived bandgap and surface engineering
Does ultrasound guidance during arthrocentesis in women with disc displacement without reduction reduce procedure time and improve outcomes? A randomized clinical trial
No full textIntroduction: The goal of using ultrasound-guided (USG) arthrocentesis is to reduce number of needle insertion attempts, which is hypothesized to reduce procedure time, postoperative pain, and consequently, limitation in range of motion. Purpose: The objective of this study was to compare the therapeutic and operative efficiency of USG Single-Puncture Arthrocentesis (SPA) Type 2 and SPA Type 2 arthrocentesis without ultrasound guidance in the treatment of temporomandibular joint (TMJ) internal derangement (ID) “disc displacement without reduction (DDWOR).” Materials and methods: A double-blinded prospective randomized clinical trial (RCT) was conducted from December 2022 to December 2023 at Ain Shams University Hospital. It enrolled females with a mean age of 27.00 ± 3.70 years with DDWOR and failed conservative treatment, excluding those with malocclusion, parafunctional habits, systemic diseases, psychological disorders or requiring special needs. In the study, 40 female patients with DDWOR were randomly divided into a control group (SPA Type 2 arthrocentesis) and an intervention group (USG SPA Type 2 arthrocentesis). Patients were assessed for needle insertion attempts as the primary outcome. procedure time, pain measured using visual analogue scale (VAS), and maximum mouth opening (MMO) were also assessed. Follow-up was conducted at 4, 8, and 12 weeks. Patients with differences in age and gender, malocclusion, parafunctional habits, systemic diseases, or psychological disorders were excluded. Results: The intervention group had fewer needle insertion attempts (1.6 vs. 2.9) and shorter procedure time (11.75 vs. 16 min, p \u3c 0.001). Pain scores (p = 0.846) and maximum mouth opening (p = 0.341) showed no statistically significant differences after 12 weeks. Data were summarized as mean, SD, median, and IQR, with normality assessed by examining the distribution and using the Shapiro-Wilk test. Non-parametric variables were compared using the Mann-Whitney U test. Linear mixed models were assessed via residual plots, Q-Q plots, Shapiro-Wilk, Breusch-Pagan, and VIF tests. Fixed effects were analyzed with ANOVA or Wald Chi-Square tests, followed by Tukey’s post-hoc comparisons. Analyses were conducted using R 4.5.0. Conclusions: USG SPA Type 2 arthrocentesis demonstrated improved procedural efficiency, evidenced by fewer needle insertion attempts and shorter procedure duration. However, it did not result in statistically significant differences in therapeutic outcomes, including pain reduction or maximum mouth opening (MMO). Further research is warranted to determine whether ultrasound guidance provides additional clinical benefits beyond technical facilitatio
A new multiple image encryption algorithm using hyperchaotic systems, SVD, and modified RC5
No full textSecure image encryption is critical for protecting sensitive data such as satellite imagery, which is pivotal for national security and environmental monitoring. However, existing encryption methods often face challenges such as vulnerability to traffic analysis, limited randomness, and insufficient resistance to attacks. To address these gaps, this article proposes a novel multiple image encryption (MIE) algorithm that integrates hyperchaotic systems, Singular Value Decomposition (SVD), counter mode RC5, a chaos-based Hill cipher, and a custom S-box generated via a modified Blum Blum Shub (BBS) algorithm. The proposed MIE algorithm begins by merging multiple satellite images into an augmented image, enhancing security against traffic analysis. The encryption process splits the colored image into RGB channels, with each channel undergoing four stages: additive confusion using a memristor hyperchaotic key transformed by SVD, RC5 encryption in counter mode with XOR operations, Hill cipher encryption using a 6D hyperchaotic key and invertible matrices mod 256, and substitution with a custom S-box generated by a modified BBS. Experimental results demonstrate the proposed algorithm’s superior encryption efficiency, enhanced randomness, and strong resistance to cryptanalytic, differential, and brute-force attacks. These findings highlight the MIE algorithm’s potential for securing satellite imagery in real-time applications, ensuring confidentiality and robustness against modern security threats
Experimentally Driven Numerical Model of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using a New Figure of Merit
No full textThis study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)- based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure of merit (FOM) of 0.99 compared to 0.62, thanks to its superior electrical conductivity and high surface area, which facilitates enhanced charge transfer and electrochemical reactions. The optimized sensor configurations reveal optimal parameters for LIG-PANI and CNT-PANI, underscoring the tradeoffs between conductivity and overall sensor performance. Notably, the CNT-PANI composite exhibits the highest sensitivity of 2778 μA·mM−1·cm−2 and the lowest LOD of 0.09 μM, making it a promising candidate for glucose detection in clinical applications. This work highlights the importance of power consumption in sensor design, with all configurations operating at 0.232 mW, and sets a new benchmark for future glucose monitoring technologies. Finally, the study illustrated a clinical investigation to verify the selectivity and sensitivity of PANI toward various molar concentrations of glucose
Assessing Public vs. Professionals’ Aesthetic Preferences of Public Art Initiatives in Informal Areas: The Case of the Ring Road in Cairo, Egypt
No full textInformal areas exist worldwide, in which they are considered a global challenge, affecting cities image, as they are characterized by high populations, dense buildings, and poor infrastructure, among other aspects that turn them into low-quality-living, unsafe, ugly pockets in cities. The research argues that public art, as a powerful tool, can (re)image, represent, and revitalize informal areas and improve the quality of life for their residents. The research investigates public perception of art in Cairo\u27s informal areas from different perspectives and how diverse groups perceive and value public art as a tool for enhancing informal areas that aims to inform urban planning, design, and public art initiatives. Through a mix of quantitative and qualitative research methods relying on the results of an achieved design competition, including interviews with competition jurors, user surveys, and competition jurors ratings, this study explores how different approaches influence the design and implementation of public art. The analysis of the collected data sheds light on the factors shaping public perception and the potential impact of public art on urban transformation. These include cultural resonance, aesthetic appeal, visibility, feasibility, and environmental integration