Life Sciences Commons^™

Strengthening Ocean Literacy: Marine Science Education And Training To Ensure Australia's Blue Future, Prue Francis, Rachel Kelly, Louise Swanson, Tanveer M. Adyel, Benjamin Arthur, Kirsten Benkendorff, Melanie J. Bishop, Helen Bostock, Marnie L. Campbell, Emma Church, Corrine Condie, Vaibhavi Dwivedi, Michelle Dyer, Matthew England, Liam Fullbrook, Charlie Huveneers, Malcolm Johnson, Brianna Le Busque, Rebecca R. Mcintosh, Amelie Meyer, Benjamin Mos, Jana Mrazova, Allyson O'Brien, Gretta T. Pecl, Amandine Schaeffer, Rebecca J. Shellock, Grant A. Smith, Scott Smithers, Ana Vila-Concejo, Graham Wood

Research outputs 2022 to 2026

This white paper sets out a national vision for advancing ocean literacy in Australia and outlines the role of marine science in fostering an informed, engaged society capable of addressing the challenges and opportunities of our changing oceans. As environmental pressures intensify, and marine resource demands increase, Australians’ capacity to engage with ocean issues, understand risks and opportunities, and participate in marine decision-making has never been more urgent. Marine science will play a central role in building ocean literacy by delivering credible, actionable science, and strengthening education and training systems that enhance understanding of, and connection to, the ocean. Our …

A Metabolite-Dependent Mechanism By Which Bifidobacterium Animalis Subsp. Lactis Promotes Bacteroides Colonization, Khashayar Shahin, Liang Wang, Zihan He, Bomin Lv, Arya Van Alin, Richard Lo-Man, Hao Wu, Philippe Sansonetti, Jean Marc Collard

Research outputs 2022 to 2026

Prokaryote-prokaryote symbiotic relationships influence interactions within microbial communities, affecting colonization, survival, and organization. Unlike competition, consortium species facilitate growth via metabolite cross-feeding. This study explored interactions between two early human gut colonizers: partially aerotolerant Bifidobacterium spp. and strict anaerobic Bacteroides spp., using omics techniques. Promotion of Bacteroides spp. growth by Bifidobacterium animalis subsp. lactis was demonstrated through co-culture experiments in anaerobic conditions. Metabolomic analysis revealed over 150 unique metabolites present in B. animalis subsp. lactis supernatants are absent in other Bifidobacterium species, including 3-hydroxycapric acid, D-alanyl-D-alanine, 2-isopropylmalic acid, and D-glucose 2-phosphate. These compounds served as nutritional substrates, including carbon and …

Crustose Coralline Algae, Algal Turfs, And Coral Reef Calcification, Sterling B. Tebbett, Scott D. Ling, David R. Bellwood, James Gahan, Alexandre C. Siqueira, Kyle Morgan

Research outputs 2022 to 2026

Crustose coralline algae (CCA) play a central role in coral reef framework consolidation and vertical accretion, yet their contribution to reef-scale calcification remains poorly quantified, particularly on reefs dominated by algal turfs. We examined how CCA calcification rates differed across ten reef sites with varying benthic composition around Lizard Island, Great Barrier Reef, Australia. Using tiles from calcification accretion units (CAUs), we quantified CCA carbonate production on light-exposed tile surfaces and related these rates to CCA cover and the Epilithic Algal Ratio (i.e. the spectrum of algal states from CCA to turf dominance), quantified on both tiles and the adjacent …

Effect Of Melatonin On Alleviating Chilling Injury In Cold-Stored ‘Kensington Pride’ Mangoes: A Comparative Evaluation Of Long Vs Short Dip Time, Mekhala Dinushi Kananke Vithana, Hafiz Muhammad Shoaib Shah, Mahmood Ul Hasan, Zora Singh

Research outputs 2022 to 2026

Mangoes (Mangifera indica L.) are notably susceptible to chilling injury (CI) when stored below 13 °C. This temperature threshold is too high for extended storage. Therefore, the influence of postharvest immersion in melatonin (MT) (50, 75, 100 µmol L^{− 1}) for 120 min on CI in ‘Kensington Pride’ mangoes kept at 5 ± 1 °C for 21 or 28 d was investigated. The most effective MT concentration was 75 µmol L^{− 1} causing 36.3% reduction in CI incidence compared to control. To facilitate adoptability in commercial practice, the influence of 120 min vs. 5- and 3-min immersions …

Sulphur Metabolism As A Key Factor In The Evolution Of Environmental Adaptation Of Acidihalobacter, Eva Vergara, Himel Nahreen Khaleque, Gonzalo Neira, Elizabeth L.J. Watkin, Jorge H. Valdés, David S. Holmes

Research outputs 2022 to 2026

This study compares predicted sulphur metabolism genes across four Acidihalobacter type strains and two metagenome-assembled genomes (MAGs), revealing genomic differences that appear to correspond to ecological specialization. Phylog-enomic analysis separates the species into two clades: clade I includes Acidihalobacter ferrooxydans from a geothermal region in Italy and the two MAGs derived from deep-sea hydrothermal vents in the Pacific Ocean, while clade II comprises Acidihalo-bacter aeolianus and Acidihalobacter prosperus from a geothermal region in Italy and Acidihalobacter yilgarnensis from a saline and acidic drainage in Australia. Variations in sulphide/quinone oxidoreductases (SQRs) across the species, in particular in Ah. ferrooxydans and Ah. …

Influence Of Rice Hull Biochar And Cedar Bark Media On Strawberry Productivity And Carbon Sequestration Potential In Hydroponic Systems, Sakalya Rajapakse, Munehiro Tanaka

Research outputs 2022 to 2026

This study evaluated the influence of rice hull biochar (RHB) and cedar bark media (CBM) as sustainable substrates for hydroponic strawberry cultivation. The total yield from virgin CBM was 413 g/plant and that from virgin RHB was 354 g/plant. Used CBM increased the yield by 4 % (429 g/plant) while used RHB increased yield by 18 % (419 g/plant) compared to the virgin, with no significant substrate differences. Fruit yields and physical properties were strongly correlated, particularly with particle density (R2 = 0.573). After 7 years of cultivation, plant residues had accumulated in both substrates. Uncarbonized carbohydrates in RHB indicated …

Harmonic Mitigation And Reactive Power Support Using Dpfc And Upfc In Grid‑Connected Solar Pv Systems: A Comparative Performance Evaluation, Abhishek Vashistha, Dharmbir Prasad, Rudra Pratap Singh

Mansoura Engineering Journal

Harmonic distortion, reactive power imbalance, and voltage instability represent major challenges regarding the power quality of grid-connected solar photovoltaic (PV) systems. Various recently developed flexible AC transmission system (FACTS) devices such as the unified power flow controller (UPFC) and distributed power flow controller (DPFC), however, have made them possible solutions but still do not provide a quantitative comparison in similar dynamic conditions. In this paper, comparative performance analysis of UPFC and DPFC in 3 MW grid connected solar PV system using Matlab Simulink is presented. The two controllers are affected by same disturbances, namely irradiance step change at t = …

Performance Enhancement Of A Fully Integrated Solar Still Using Flat Plate Collector, Reflector, And Evaporative Cooling System, Joe Patrick Gnanaraj Sundararaj, Vanthana Jeyasingh

Mansoura Engineering Journal

Water scarcity has become a major global concern due to increasing population growth, industrialization, and depletion of freshwater resources. Solar desalination is considered an eco-friendly and sustainable solution, especially for rural and off-grid regions where conventional water treatment facilities are limited. However, conventional solar stills suffer from low productivity, which restricts their practical application. In this study, a fully integrated solar still system was designed and fabricated by incorporating a flat plate collector, front-wall reflector, and passive evaporative cooling arrangement. The system was experimentally tested under natural climatic conditions over seven consecutive days to evaluate temperature variation, distillate yield, and …

A Hybrid Geoid Model For The Perlis Region, Malaysia Based On Cadastral Reference Marks And A Geometric Approach, Muhammad Aiman Haiqal Abdul Malek, Muhammad Faiz Pa’Suya, Ramazan Alpay Abbak, Ami Hassan Md Din, Noorfatekah Talib

Mansoura Engineering Journal

This study presents the development of a high-resolution local geoid model for the Perlis region, Malaysia, using a geometric approach that integrates GNSS-levelling benchmarks with Cadastral Reference Mark (CRM) data. A total of 38 GNSS-levelling benchmarks were used as reference points, while 3,725 CRMs were incorporated to significantly enhance spatial coverage for geoid modelling. Orthometric heights at the CRM points were first determined by transferring heights from the reference benchmarks using gravimetric geoid information. Subsequently, geometric geoid heights were computed from the differences between ellipsoidal and orthometric heights. Five interpolation techniques were evaluated to generate the geometric geoid surface, namely …

An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare

Mansoura Engineering Journal

The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …

Comparative Finite Element Method-Based Optimisation Of Coir Fibre Laminates: Aluminium Skins Versus Carbon Cloth Skins, Muhamed Swaleh Ahmed, Bernard Wamuti Ikua, Abel Nyakundi Mayaka

Mansoura Engineering Journal

Natural fibre composites offer a sustainable alternative to conventional composite materials. Their mechanical efficiency is influenced by laminate structure and skin material selection. This study presents a comparative finite element analysis and optimisation of coir fibre-reinforced laminates employing either aluminium skins or carbon cloth skins. COMSOL Multiphysics was used to determine their mechanical response. Optimisation was performed using the BOBYQA algorithm to enhance load sharing between the coir core and skin materials. Results indicated that aluminium-skinned laminates achieve superior compressive and flexural performance, achieving a peak compressive strength of 210 MPa and sustaining a flexural load of 0.65 kN at …

A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour

Mansoura Engineering Journal

This study proposes a machine learning–based framework that applies machine learning techniques to improve the efficiency of 5G network slicing through automated traffic classification and threshold-based load management . The proposed model optimizes resource allocation among the three standardized 5G slice types: enhanced Mobile Broadband (eMBB), ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). Two supervised learning algorithms—K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)—are trained using Quality of Service (QoS) parameters such as packet delay, loss rate, and Quality Class Identifier (QCI). Experimental evaluations were conducted on two large-scale datasets containing over 400,000 traffic instances, demonstrating that the …

Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy

Mansoura Engineering Journal

Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …

Multi-Method Energy Optimization: Linear Programming, Hmm Modeling And Arduino-Based Simulations, A.E. El-Alfy, Eman Elayat, M. A. E. Sheta

Mansoura Engineering Journal

This paper presents the simulation and optimization of hybrid energy systems integrating renewable energy and storage technologies. Linear Programming (LP) is utilized to minimize operational costs, while a Hidden Markov Model (HMM) improves reliability by accurately predicting energy flow. Hardware-in-the-loop simulation in Proteus demonstrates efficient energy trading, significantly reducing dependence on conventional sources. The results from a 24-hour analysis show that the system achieves an 87.14% load factor, indicating high efficiency in utilizing the system's rated capacity, 26.23 system reliability, and a 20% improvement in cost efficiency and enhanced sustainability, providing a robust and practical framework for hybrid energy solutions …

Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja

Mansoura Engineering Journal

Bladder cancer diagnosis demands the integration of cystoscopy, histopathology, and biomarker testing, yet the majority of AI systems continue to be modality, specific and sensitive to acquisition variations. TRIDENT, Bladder is a resolution, aware multimodal framework that we have developed to address this issue. The method combines cystoscopic lesion segmentation, whole, slide image (WSI) molecular subtype prediction, and urine miRNAclinical data through reliability, weighted fusion and a utility, aware decision policy. The endoscopic branch features a quality, gated super, resolution component, resulting in mDice 87.5, sensitivity 92.1%, precision 91.4%, boundary, F1 85.3%, and ECE 0.023 at 32 FPS. mDice on …

Green Hydrogen-Based Decarbonization Approach For Steel Industry With Hybrid Renewable Energy Sources, Raju Kumar Maurya, Dharmbir Prasad, Rudra Pratap Singh

Mansoura Engineering Journal

This work provides a micro-pilot techno-economic and environmental assessment of a green hydrogen-driven decarbonization scenario for low-carbon steel production at the capacity of 1 ton steel produced (i.e., requiring 50 kg of green hydrogen). In this work an integrated renewable energy (RE) scenario for the steel production site at Jamuria, West Bengal, India is planned to utilize solar photovoltaic (PV), wind turbines (WTs), battery storage and a diesel backup generator to meet the hydrogen production load from an electrolyzer using HOMER Pro software. The results show that the proposed micro-pilot system produces excess electricity with respect to the plant's operating …

Finite Element Analysis Of Oxygen Transport In Tissue And Capillaries With A Second Order Metabolic Consumption, Vikash Ramcharitar, Sreedhara Rao Gunakala, Reddappa Bandi, Donna M. G. Dyer, Jagdesh Ramnanan

Mansoura Engineering Journal

This study presents a numerical investigation into the oxygen transport through a Krogh-type capillary-tissue model with second-order tissue metabolism. The governing non-linear equations are solved by implementing a Galerkin finite element method with a fixed-point iteration scheme. The resulting code and solution algorithm were successfully validated against available analytical solutions for zeroth- and first-order kinetics, showing very good agreement. Numerical simulations indicated, that under the parameters investigated, relative to zeroth- and first-order kinetics, a second-order metabolism leads to less overall oxygen consumption within the tissue phase. This yields higher oxygen partial pressures at the outer tissue boundary and higher oxygen …

Elli’S Liquid Flow In A Wavy Channel With Slip Effect, Wall Properties, And Heat Transfer, P. Devaki, Yatin Sood

Mansoura Engineering Journal

The dual behavior of Elli’s fluid motivated us to work on it. The fluid behaves as both Newtonian/ non-Newtonian based on the low and high shear rates, respectively. The paper focused on the flow of Ellis fluid in a peristaltic channel with wall properties and heat transfer. The channel is symmetric in nature, and slip conditions are considered near the elastic walls. The governing equations of the flow are solved analytically using suitable boundary conditions, which yield velocity and temperature functions. The novelty of the paper is to analyze the nature of Newtonian/non-Newtonian fluids under the same conditions so that …

Intelligent Audio‑To‑Indian Sign‑Language And Sign‑To‑Audio Translation System Using Mediapipe, Tensorflow, Whisper And Google Tts, N. Pothanna, T. Kusuma, S. Haindavi, T. Sreeja, Shaik Shaheem Taj

Mansoura Engineering Journal

Communication barriers between the Deaf community and the general public remain a persistent challenge, particularly in multilingual settings where Indian Sign Language (ISL) is the primary mode of interaction. We propose a real-time bidirectional translation framework integrating MediaPipe for hand landmark extraction, a Convolutional Neural Network (CNN) classifier built with TensorFlow/Keras for gesture recognition, OpenAI Whisper for robust multilingual speech-to-text transcription, and Google TTS for naturalistic speech synthesis. The system achieves 93% classification accuracy across 35 ISL classes (alphabets A–Z and numerals 1–9) on a dataset of 42,700 images, with macro and weighted F1-scores of 0.93. Deployed as a Flask …

A Multi-Valued Fixed Point Theorem For Quasi-Contractions On A Cone Metric Space, Regina Mahadewsing, Sreedhara Rao Gunakala, Vikash Ramcharitar, Reddappa Bandi, Akhenaton Daaga, Thameem Basha H

Mansoura Engineering Journal

A set-valued (multi-valued)  mapping  assigns to each  a nonempty closed and bounded subset . Using this notion, the present work broadens classical fixed point theory by proving a fixed point theorem for multi-valued quasi-contractive mappings in cone metric spaces. The developed argument extends several earlier results that were restricted to single-valued maps and more familiar set-valued settings, thereby providing a wider analytical framework within ordered Banach-space structures. These contributions enrich fixed point theory in generalized metric environments and can be relevant to problems in nonlinear analysis and optimization

A Hybrid Object Detection And Temporal Attention Framework For Intelligent Video Surveillance, Sudheer Reddy Bandi, Eswari Vanaparthi, Yakshini Edapalli, Roshan Kavuri

Mansoura Engineering Journal

The rapid growth of urban areas has greatly heightened the need for smart video surveillance systems that can automatically process extensive amounts of CCTV footage. Traditional surveillance methods largely depend on human monitoring, which is not only inefficient but also susceptible to human mistakes, especially in intricate and crowded environments. To tackle these issues, this paper introduces a combined object detection and temporal attention for intelligent video surveillance that concurrently analyzes spatial and temporal data from video streams. The proposed system analyzes real-time CCTV footage utilising a multi-pathway frame extraction technique that includes slow, fast, and full-frame sampling to capture …

An Intuitionistic Fuzzy Hypergraph Model Enhanced ‎By Forest-Of-Walks Dynamics For Medical Image ‎Segmentation, Brinthaguru Thangaraj, Karthick Palanisamy

Mansoura Engineering Journal

The process of accurately segmenting Urolithiasis and pulmonary nodules from medical images presents significant difficulties because of three main factors which include nonuniform intensity distribution and the presence of weak object borders and the uncertainty caused by anatomical structure overlaps. The study introduces F-Zinhger as a solution to these problems through its application of the Forest of Walks technology. The method uses superpixels as fundamental elements which form a multi-scale hypergraph that establishes hyperedges through three criteria: intensity similarity, spatial proximity, and Z-intuitionistic fuzzy hesitation to capture complex contextual connections. The system incorporates a random walk-based label propagation system. The …

Mathematical Analysis Of The Slip Flow Due To A Cylinder Oscillating In Different Directions With Independent Amplitudes, Alana Sankar, Karim Rahaman

Mansoura Engineering Journal

This study examines the incompressible viscous fluid flow in an infinitely long cylinder, with slip occurring at the cylinder’s surface, undergoing longitudinal and torsional oscillations of independent amplitudes. The proposed governing equations are solved subject to the Basset slip condition. Analytical expressions for the velocity field, shear stresses, drag force on the cylinder, work done and the drag coefficient are obtained. Velocity components, drag and work done are illustrated graphically. The magnitude of the velocity increases as slip decreases and as the frequency of oscillations increases. Drag increases in both directions as the slip decreases and as the frequency of …

Underwater Image Identification Using Fuzzy Soft Planar Graph, Bhuvaneswari Natarajan Jayakar, Karthick Palanisamy

Mansoura Engineering Journal

High-attribute underwater image segmentation is fundamental to autonomous marine exploration, biodiversity monitoring, and subsea infrastructure inspection. However, underwater environments are inherently stochastic, exhibiting severe light attenuation, chromatic distortion, scattering effects, and noise, all of which significantly degrade image quality and challenge conventional computer vision techniques. Hence, Fuzzy logic which handles uncertainty and imprecision in data and Soft sets which manage parameterized information, are widely applied to underwater image analysis. Fuzzy Soft Planar Graphs (FSPGs) constitute a mathematical framework that integrates fuzzy set theory, soft set theory and planar graph structures for preserving spatial topology. The proposed methodology adopts a hybrid …

Finite Element Analysis Of Multiscale Fgm Plate Using Modified Third Order Shear Deformation Theory, Ravi Kumar, Ajay Kumar

Mansoura Engineering Journal

Present paper aimed to examine the static and dynamic response of a carbon nanotube (CNT) infused multiscale functionally graded (FGM) rectangular plate structure. A third-order shear deformation theory (TSDT) based on Reddy’s formulation with enforcing negligible transverse shear stresses at the outermost surface of the plate, is used. A nine-noded isoparametric element with 13 displacement variables per node is numerically investigated for finite element analysis. Using the Halpin-Tsai and homogeneous equation the elastic behaviour of the final material is obtained. The current result is first checked against a previously published result to validate the present mathematical model. The finite element …

Explainable Multi-Horizon Wind Power Forecasting Via Aquila-Optimized Machine Learning Models, Mostafa A. Abdelnaby, Nahla B. Abdel-Hamid, Eman M. El-Gendy, Mahmoud M. Saafan

Mansoura Engineering Journal

The inherently unpredictable nature of wind energy necessitates the development of sophisticated forecasting models to ensure grid stability and optimal distribution. In this research, we propose a novel and systematic approach to wind power forecasting (WPF) across diverse timescales. This approach leverages the power of various machine learning (ML) models, metaheuristic hyperparameter optimization, and utilizes explainable artificial intelligence (XAI). The developed methodology is based on the Aquila optimizer (AO), capable of automatically adjusting different ML models for four different time periods (30 minutes, 6 hours, 24 hours, and 36 hours) on the data collected from the Gabal El-Zayt wind power …

A Novel Superaug Adaptive Data Augmentation Strategy For Metabolic Syndrome Prediction: The First Egyptian National Cohort Study With Multi-National Comparison, Nihal Elsonny, Ashraf Elsharkawy, Abeer Tawakol, Amira Y. Haikal

Mansoura Engineering Journal

Metabolic Syndrome (MetS) is a multifactorial disorder associated with an increased risk of cardiovascular disease, type 2 diabetes, and obesity-related complications. Early and accurate prediction of MetS remains challenging due to heterogeneous data sources, class imbalance, limited sample sizes in regional studies, and poor generalization across populations.

This study introduces a comprehensive machine learning framework for predicting MetS and its prognostic factors using two heterogeneous datasets: a newly collected Egyptian clinical cohort and the U.S.-based (NHANES) [CDC, 2023] dataset. For each dataset, multiple experimental pipelines are developed, integrating preprocessing, feature selection, data augmentation, hyperparameter tuning, and ensemble modeling. …

Effect Of Two Cut Off Rows On Seepage Underneath Hy-Draulic Structures Using Weak Form Differential Quadra-Ture Element Method: A Theoretical Approach, Esraa Ahmed, El-Masry A. A, Hossam A.A. Abdel Gawad, Ahmed Elhamrawy

Mansoura Engineering Journal

Investigating confined seepage underneath hydraulic structures is crucial to ensure the safety of these structures. The Weak Form Quadrature Element Method (WFQEM) is the basis of this paper, which explores the behavior of confined flow. The seepage flow governing equation is solved numerically to estimate the uplift pressure underneath the hydraulic structures and the exit gradient.The Gauss–Lobatto–Legendre (GLL) type is used as nodal and integration points. Several models were solved to validate the applied numerical method. The obtained results are compared with theoretical and preceding numerical solutions mentioned in the literature. The system of equations generated from applying the WFQEM …

Warm Mix Asphalt: Key Issues, Performance Challenges, And Modeling Advances, Mahmoud Owais, Marwa Awad

Mansoura Engineering Journal

Warm Mix Asphalt (WMA) has emerged as a sustainable alternative to conventional Hot Mix Asphalt by enabling asphalt production and compaction at reduced temperatures, thereby lowering energy consumption, emissions, and worker exposure to heat and fumes. Despite these advantages, the field performance of WMA remains influenced by technology-specific mechanisms, additive–binder compatibility, aggregate characteristics, moisture susceptibility, compaction quality, recycled material content, and climatic conditions. This review provides a critical synthesis of major WMA technologies, including foamed systems, chemical additives, organic waxes, hybrid additives, bio-based modifiers, and WMA mixtures incorporating reclaimed asphalt pavement. Particular attention is given to how these technologies affect …

Reliability-Oriented Spatiotemporal Machine Learning For High-Impact Power Outage Event Prediction, Marwa Gamal

Mansoura Engineering Journal

Power outages have become an increasing concern for modern power systems due to their impact on infrastructure reliability, economic activities, and public safety. The growing frequency of extreme weather events and the rising demand for electricity have made it more difficult to anticipate high-impact outage events. One of the main challenges in this context is the complex interaction between temporal patterns and geographic variations, which traditional methods often fail to capture effectively. This study develops a machine learning framework that combines temporal characteristics with geographic information to improve the prediction of high-impact power outages. Temporal features such as seasonal patterns, …