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Optimization of machining parameters for turning operation of heat-treated Ti-6Al-3Mo-2Nb-2Sn-2Zr-1.5Cr alloy by Taguchi method

TC21 alloy is a high-strength titanium alloy that has been gaining attention in various industries for its excellent combination of strength, toughness, and corrosion resistance. Given that this alloy is hard to cut material, therefore this study aims to optimize the process parameters of Turing this alloy under different conditions (i.e. as-received alloy, and heat-treated alloy). The L9 Taguchi approach-base orthogonal array is used to determine the optimum cutting parameters and the least number of experimental trials required. The achievement of this target, three different cutting

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications

Modeling circular supply chains as an approach for waste management: A systematic review and a conceptual framework

All world countries are suffering from repercussions of the global climate change problems and there is an urgent need to mitigate their negative impacts. Improper waste management methods contribute directly to climate change where common waste treatment methods are basically relying on incineration or landfilling. Nowadays, incorporating the circular economy perspective into the business model demonstrates the ability of creating value from wastes and reducing the residuals by adopting the circular supply chains management (CSCM) as a promising alternative to linear supply chains. Studying

Artificial Intelligence
Healthcare
Circuit Theory and Applications
Software and Communications
Mechanical Design
Innovation, Entrepreneurship and Competitiveness

Commercial Versus Natural Activated Carbon Fabricated Sheets: Applied to Dyes Removal Application

Industrial dyes are considered one of the main causes of increased water pollution of water. Many businesses, such as steel and paper, are located along riverbanks because they require large amounts of water in their manufacturing processes, and their wastes, which contain acids, alkalis, dyes, and other chemicals, are dumped and poured into rivers as effluents. For example, chemical enterprises producing aluminum emit a significant quantity of fluoride into the air and effluents into water bodies. Fertilizer facilities produce a lot of ammonia, whereas steel plants produce cyanide. Many

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Software and Communications
Agriculture and Crops
Mechanical Design
Innovation, Entrepreneurship and Competitiveness

Crystal violet removal using algae-based activated carbon and its composites with bimetallic Fe0-Cu

The textile industry is considered a source of pollution because of the discharge of dye wastewater. The dye wastewater effluent has a significant impact on the aquatic environment. According to the World Bank, textile dyeing, and treatment contribute 17 to 20% of the pollution of water. This paper aims to prepare the bimetallic nano zero-valent iron-copper (Fe0-Cu), algae-activated carbon, and their composites (AC-Fe0-Cu), which are employed as adsorbents. In this paper, Synthetic adsorbents are prepared and examined for the adsorption and removal of soluble cationic crystal violet (CV) dye

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Software and Communications
Mechanical Design
Innovation, Entrepreneurship and Competitiveness

Enhanced removal of crystal violet using rawfava bean peels, its chemically activated carbon compared with commercial activated carbon

Crystal violet is a basic dye that is widely used by various industries, such as textiles and paints. These industries discharge their effluents, contaminated with crystal violet, into water streams, and these effluents have an adverse effect on aquatic organisms, the environment, and human health. Crystal violet is a basic dye that is widely used by various industries, such as textiles and paints. These industries discharge their effluents, contaminated with crystal violet, into water streams, and these effluents have an adverse effect on aquatic organisms, the environment, and human health

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications

Review on Coral Reef Regeneration Methods through Renewable Powered Electrotherapy

The restoration of coral reef population in coastal regions is currently a growing concern. Many attempts have been made to apply new approaches to limit the deterioration of coral reefs, and to accelerate the growth of new reefs to protect coastal areas and ecosystems using available renewable energy sources. This paper highlights the new approaches and their various advantages and limitations in tidal and wave energy. The paper also suggests improvements to some of those systems using the recent developments in soft robotics, especially the use of biomimetic fish as a feasible support

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Mechanical Design

Experimental investigation of methyl-orange removal using eco-friendly cost-effective materials raw fava bean peels and their formulated physical, and chemically activated carbon

The discharge of effluents from dye industries into water streams poses a significant environmental and public health risk. In response, eco-friendly adsorbents derived from agricultural waste, such as Fava Bean Peels (R–FBP), have been investigated as potential materials for the removal of such pollutants. In this study, R–FBP and their corresponding physical and chemically activated carbon (P-RFB-AC and C-FBP-AC) were synthesized using H3PO4 acid and characterized using FT-IR, and SEM analyses. An optimization process was conducted to determine the optimum conditions for achieving high

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Software and Communications

Bio-inspired adsorption sheets from waste material for anionic methyl orange dye removal

Abstract: Nano zero-valent iron (nZVI), bimetallic nano zero-valent iron-copper (Fe0–Cu), and Raw algae (sargassum dentifolium) activated carbon-supported bimetallic nano zero-valent iron-copper (AC-Fe0–Cu) are synthesized and characterized using FT-IR, XRD, and SEM. The maximum removal capacity is demonstrated by bimetallic activated carbon AC-Fe0–Cu, which is estimated at 946.5 mg/g capacity at the condition pH = 7, 30 min contact time under shaking at 120 rpm at ambient temperature, 200 ppm of M.O, and 1 g/l dose of raw algae-Fe0–Cu adsorbent. The elimination capability of the H3PO4

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Software and Communications
Agriculture and Crops
Mechanical Design

Valorization of Agricultural and Marine Waste for Fabrication of Bio-Adsorbent Sheets

Industrial wastewater often contains considerable amounts of toxic pollutants that would endanger public health and the environment. In developing countries, these toxins are often discharged into natural ecosystems without pretreatment as it requires costly treatment processes, which causes long-term harmful socioeconomic impacts. Employing wastewater treatment plants using physical, biological, and chemical methods to clean the wastewater is considered by many nations the answer to the environmental crises. The treated water could be used for targeting the irrigation systems in its majority

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Software and Communications
Agriculture and Crops

COVID-19 Diagnosis from CT-images Using Transfer Learning

In symptomatic patients, a positive COVID-19 test is critical for securing life-saving services such as ICU care and ventilator support; it may cause septic shock, septic pneumonia, respiratory failure, heart difficulties, liver issues, and even death. CAD systems help people in rural places and doctors in the early detection of COVID-19. A diagnostic and severity detection technique utilizing transfer learning and a backpropagation neural network has been developed with the aid of a computer for this purpose. This study aims to compare and analyze multiple deep learning-enhanced strategies

Healthcare