Developing routes to produce cellulose nanocrystals (CNCs) from high-lignin wood residues is essential for expanding sustainable nanocellulose feedstocks. In this work, Meranti (Shorea sp.) sawdust was valorized into CNCs by integrating ammonium persulfate (APS) pretreatment with subsequent sulfuric acid hydrolysis. To establish a severity map and define an operating window, APS pretreatment severity was systematically varied by adjusting APS concentration and the sawdust-to-APS (solid-to-liquid) ratio, and its influence on CNC structural properties was evaluated. APS pretreatment partially disrupted and oxidized the lignocellulosic matrix, enabling acid hydrolysis to liberate crystalline cellulose domains. XRD analysis confirmed th

Arcology is a new vision of urban design for densely populated settlements. It is referred to as the urban formation aimed at achieving the highest level of utilization in the least area of land to reduce human impact on the environment. Moreover, the integration of this formation with the environment will work to reduce energy consumption, and achieve an economy that is characterized by adaptation and self-sufficiency, leading towards sustainable urbanism. The current study deals with this new concept in sustainable urban design, in an attempt to investigate its impact on traditional urban formation and to make a comparison between them. The lack of a clear conception of the term ‘arcology’ and comparing it with the organic compact urb

The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were co

Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

The primary goal of in-situ load testing is to evaluate the safety and performance of a structural system under particular loading conditions. Advancements in building techniques, analytical tools, and monitoring instruments are prompting the evaluation of the appropriate loading value, loading process, and examination criteria. The procedure for testing reinforced concrete (RC) structures on-site, as outlined in the ACI Building Code, involves conducting a 24-h load test and applying specific evaluation criteria. This article detailed a retrofitting project for an RC slab-beams system by utilizing carbon fiber-reinforced polymer (CFRP) sheets to strengthen the structure following a fire incident. The RC structure showed indicators of deter

Activated carbon derived from Ficus Binjamina agro-waste synthesized by pyro carbonic acid microwave method and treated with silicon oxide (SiO2) was used to enhance the adsorption capability of the malachite green (MG) dye. Three factors of concentration of dye, time of mixing, and the amount of activated carbon with four levels were used to investigate their effect on the MG removal efficiency. The results show that 0.4 g/L dosage, 80 mg/L dye concentration, and 40 min adsorption duration were found as an optimum conditions for 99.13% removal efficiency. The results also reveal that Freundlich isotherm and the pseudo-second-order kinetic models were the best models to describe the equilibrium adsorption data.

A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu

As the prices of the fuel and power had fluctuated many times in the last decade and new policies appeared and signed by most of the world countries to eliminate global warming and environmental impact on the earth surface and humanity exciting, an urgent need appeared to develop the renewable energy harnessing technologies on the short-term and long-term and one of these promising technologies are the vertical axis wind turbines, and mostly the combined types. The purpose of the present work is to combine a cavity type Savonius with straight bladed Darrieus to eliminate the poor self-starting ability for Darrieus type and low performance for Savonius type and for this purpose, a three-bladed Darrieus type with symmetric

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m