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Augmented Green Hydrogen Production at Binary Nickel/Cobalt Oxide Nanostructured Catalyst
No full textDeveloping robust, inexpensive, and efficient electrocatalysts for hydrogen evolution via water splitting is crucial for the improvement of green hydrogen production technology. Herein, a standard three-electrode system is useful to assess the activity of single and mixed NiOx and CoOx electrocatalysts, assembled onto a glassy carbon (GC) electrode via the electrodeposition technique, toward the hydrogen evolution reaction (HER) in an alkaline medium of 0.5 M NaOH. The net results of several electrochemical experiments (linear sweep voltammetry (LSV), current transients (i–t curves), Nyquist and Tafel plots) confirm the superiority of the NiOx/CoOx/GC (binary modified catalyst at which CoOx and NiOx are introduced to the GC surface, respectively) in terms of achieving a higher activity (61.49 mA cm−2 at − 2 V) and stability (ca. 6.8 mA cm−2 after 8 h of continuous electrolysis), a lower charge transfer resistance (Rct, 21 Ω), and a lower Tafel slope (34 mV/decade) indicating the improved charge transfer mobility and accordingly the fastest kinetics toward HER
Balto: comedic representation of medical professionals in TV drama
No full textMedical professionals have been portrayed as hard-working and serious individuals in most Egyptian dramas. Recent Egyptian TV series have portrayed medical service providers, highlighting different aspects of their personalities. The present paper adopts an approach that combines the studies of humor and language to investigate the comedic representation of medical professionals in contemporary Egyptian television TV drama, with special reference to a recent TV series called Balto (2023). Within the framework of humor theories of incongruity and superiority, this paper aims to analyze elements of the comedic portrayal of health professionals in the selected TV series, Balto, to investigate how humor is employed to both humanize the long-idealized depiction of doctors as well as critique societal perceptions of representatives of the medical sector in Egypt. The paper particularly focuses on analyzing how the protagonist and other medical professionals practice their work, exercise managerial power, and operate/function with their peers and patients within a small remote health unit
Integrated decision support system for optimizing time and cost trade offs in linear repetitive construction projects
No full texttime and cost performance. Traditional scheduling techniques often struggle to effectively address these complexities. This paper aims to enhance project optimization by introducing a metaheuristicbased Time-Cost Trade-off (TCT) framework specifically designed for repetitive project environments. Unlike previous studies that focus solely on single-algorithm applications, this research evaluates two metaheuristic optimization strategies—Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)—within a consistent problem setting. The framework employs both algorithms, which are independently assessed for their effectiveness in tackling the Linear Repetitive Project Time-Cost Trade-off (LRPTCT) problem. The methodology utilizes task decomposition alongside the Line of Balance (LOB) scheduling technique, facilitating a more detailed and adaptable planning process. Each sub-task is systematically evaluated to identify the optimal construction method based on cost-time trade-offs, with scheduling constraints integrated into the fitness functions of both GA and PSO. Results from an in-depth case study reveal significant improvements in project efficiency. Specifically, GA achieved approximately a 3.25% reduction in direct costs, a 20% reduction in indirect costs, and a 7% reduction in total construction costs. In comparison, PSO demonstrated slightly superior cost performance, with a 4% reduction in direct costs and comparable reductions in indirect costs, along with a 20% decrease in total project duration. These findings highlight practical gains in resource utilization and scheduling efficiency. This study presents a structured, comparative analysis of GA and PSO within the LOB-based TCT framework, providing a replicable methodology for optimizing schedules in linear repetitive projects. By bridging the gap between traditional scheduling techniques and advanced optimization algorithms, this research contributes valuable insights for enhancing operational efficiency and informed decision-making in construction project management
Transforming facility management with BIM, IoT, and Digital Twin: a data-driven approach to air quality monitoring
No full textPoor indoor air quality in healthcare facilities can significantly impact patient recovery, increase the risk of airborne disease transmission, and compromise staff well-being. Conventional monitoring methods typically rely on manual or static measurements, lacking the real-time responsiveness required for proactive facility management. This study proposes an integrated Building Information Modeling (BIM), Internet of Things (IoT), and Digital Twin (DT) framework to enable continuous air quality monitoring and data-driven decision-making. A case study was conducted in an Egyptian healthcare facility, where IoT sensors captured critical parameters, including airflow (CFM), pressure (Pa), CO₂ levels (ppm), and temperature (°C). These data were transmitted to ThingSpeak, a cloud-based analytics platform, and dynamically integrated into a BIM model using Dynamo scripts in Autodesk Revit. This integration enabled real-time, color-coded visualization of environmental conditions, supporting rapid, data-driven responses to changing air quality. A pilot study with a BIM expert validated the framework, highlighting challenges such as internet dependency, data security risks, interoperability limitations, and the limited availability of as-is BIM models. Despite these constraints, the system demonstrated its effectiveness in real-time monitoring and proactive facility management, providing a scalable, data-driven approach for improving operational efficiency and indoor air quality in healthcare environments
Prototyping Various MPPT Techniques Used in Wind Energy Conversion Systems for Response Time Monitoring
No full textThis paper focuses on prototyping various maximum power point tracking (MPPT) techniques used in wind energy conversion systems (WECS) for response time monitoring. MPPT plays a crucial role in optimizing the power extraction from wind turbines by dynamically adjusting their operating conditions to track the maximum power point. The response time of an MPPT algorithm determines how quickly it can adapt to changes in wind conditions and maximize power output. In this study, we implement and compare multiple MPPT techniques on an emulated WECS. Several commonly used MPPT techniques, such as perturb and observe (P&O), incremental conductance (IncCond), and tip speed ratio (TSR), are implemented and evaluated based on their response time. The response time metrics include settling time, overshoot, and steady-state error. The experimental setup allows for real-time data acquisition and analysis of the different MPPT techniques\u27 performance under dynamic wind profiles. The acquired data is analyzed to assess each algorithm\u27s response time and impact on the system\u27s power output and stability. The results obtained from the prototyping experiments provide valuable insights into the effectiveness of different MPPT techniques in terms of their response time characteristics. Additionally, the results concluded the applicability of indirect methods for implementation using low processing capability Arduino chip rather than the direct one. Only 6.3 ms was needed by TSR to adopt the dynamic variation in wind speed, while 16.27 ms was observed in IncCond
Exploring the Printability and Marine Degradation of Biodegradable, Starch-Based Polymers in Additive Manufacturing
No full textPolymer waste is an increasingly growing problem nowadays with millions of tons being deposited in nature each year, effecting flora and fauna in different environments. In order to address this topic, one aspect in current research is the replacement of traditional, petrochemical polymers with bio-based and biodegradable alternatives. Within this work the possibility of 3D printing functional parts with a biodegradable, starch-based polymer is presented with a focus on the printing behavior as well as the biodegradability, in particular in marine environments where polymer waste is accumulated. For this purpose, two promising biodegradable polymer alternatives, namely Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and Solanyl, a starch-based biopolymer, were investigated. A design of experiment FFF study was carried out using a pellet-printing technique with varying the printing parameters in order to determine the most suitable process for each material. Biodegradation in saltwater was assessed by measuring the oxygen consumption using the biochemical oxygen demand (BOD) method. Results show that Solanyl was easier to handle in the printing process and delivered a higher part quality, while also exhibiting a higher degradation rate in the saltwater immersion tests
Experimental Study for Improving Oil Recovery Using Organic Alkaline and Nano-Silica for An Egyptian Oil Field
No full textThe oil and gas industry continually seeks innovative methods to enhance hydrocarbon recovery due to the declining productivity of conventional techniques. Current recovery methods, such as water flooding and chemical flooding, often face limitations like high interfacial tension, unfavorable wettability, and reduced mobility of oil, especially under harsh reservoir conditions of high salinity. To address these challenges, this study explores the implementation of nanotechnology in enhanced oil recovery (EOR), focusing on the distinct and unique properties of nanoparticles. Nanoparticles, particularly SiO2, were chosen for their ability to significantly decrease interfacial tension, alter wettability, and improve oil mobility. SiO2 nanoparticles exhibit high surface area-to-volume ratio, stability under reservoir conditions, and effectiveness in high salinity environments, making them superior to other nanoparticles in this context. This study discusses the modeling and optimization of different flooding scenarios using organic alkaline, ethylenediamine, and SiO2 nanoparticles under harsh reservoir conditions. Organic alkaline was selected to overcome issues related to inorganic alkaline, such as calcium and magnesium ion precipitation and polymer viscosity reduction. The physical properties of the displacing fluids and crude oil were measured, and flooding runs were tested on a linear sand pack unit using various slug concentrations. Wettability alterations were also observed with different concentrations. Design Expert software was utilized to generate and determine the optimum concentrations. The results demonstrated that the highest oil recovery was achieved with 0.7 wt.% ethylenediamine and 0.02475 wt.% Nano silica. These findings suggest that incorporating SiO2 nanoparticles in EOR can significantly enhance oil recovery efficiency under challenging reservoir conditions, offering a promising advancement over traditional methods
CMS RPC L1 Trigger clustering at CMSSW
No full textThe Compact Muon Solenoid detector at the Large Hadron Collider is a multipurpose experiment designed for studying proton–proton and heavy-ion collisions. It features a 3.8 T Solenoid magnet, a Silicon tracker, Electromagnetic and Hadronic Calorimeters, and the Muon system. For the High Luminosity LHC, CMS will undergo Phase-2 upgrades to handle higher collision rates, with PileUp increasing from 50 to 140/200 interactions per bunch crossing, collision energy reaching 14 TeV, and peak luminosity rising to 5−7.5×1034 cm−2s−1. These upgrades aim to enable even more precise Standard Model measurements, improvements in the Higgs sector, and searches for Beyond Standard Model physics. This document describes the main features of the Endcap Muon Track Finder ++ algorithm, developed in the CMS Software; it is the Level 1 Trigger algorithm upgrade being developed for Phase-2 of the currently used Endcap Track Finder. The efficiency of the algorithm was computed on simulations generated with and without RPC and iRPC ((i)RPC) information, using a pre-trained model
Adaptation: Strengthening Resilience Through National Adaptation Plans
No full textWith the aim to bring into effect and localize the Sharm El-Sheikh Adaptation Agenda (SAA) and the Global Goal on Adaptation (GGA), this policy research paper looks at three interrelated adaptation axes: increasing finance and capacity, investing in people, and building urban resilience. This study identifies institutional, financial, and governance mechanisms that can provide equitable and effective climate adaptation through comparative case studies of Egypt and Kenya, two African countries with different but complementary adaptation pathways. With a focus on two primary themes— localizing the SAA and operationalizing the GGA—it evaluates adaptation finance flows, community-based health and education systems, and urban infrastructure planning. Particular focus is placed on subnational governance, youth-led innovation, and inclusive financing frameworks that prioritize vulnerable populations like women, Indigenous communities, and smallholder farmers. Lessons learned offer scalable, context-specific models for other developing countries preparing comprehensive adaptation frameworks for COP30 and beyond