Intercomparison of deep learning models in predicting streamflow patterns: insight from CMIP6.

This research was carried out to predict daily streamflow for the Swat River Basin, Pakistan through four deep learning (DL) models: Feed Forward Artificial Neural Networks (FFANN), Seasonal Artificial Neural Networks (SANN), Time Lag Artificial Neural Networks (TLANN) and Long Short-Term Memory (LSTM) under two Shared Socioeconomic Pathways (SSPs) 585 and 245. Taylor Diagram, Random Forest, and Gradient Boosting techniques were used to select the best combination of General Circulation Models (GCMs) for Multi-Model Ensemble (MME) computation. MME was computed via the Random Forest technique for Maximum Temperature (T), Minimum Temperature (T), and precipitation for the aforementioned three techniques.

Study of Kinetics and the Working Mechanism of Silica-Coated Amino-Functionalized CoFeO Ferrite Nanoparticles to Treat Wastewater for Heavy Metals.

This study used a simple coprecipitation method to produce pristine, silica-coated, and amino-functionalized CoFeO nanoadsorbents. Amino-functionalization was done to increase the active surface area and metal ion removal efficiency. Both pristine and functionalized adsorbents were employed to recover Pb(II), Zn(II), and Cu(II) ions from wastewater.

Dielectric Barrier Discharge Plasma Processing and Sr-Doped ZnO/CNT Photocatalyst Decoration of Cotton Fabrics for Self-Cleaning Application.

Nonthermal plasma processing is a chemical-free and environmentally friendly technique to enhance the self-cleaning activity of nanoparticle-coated cotton fabrics. In this research, Sr-doped ZnO/carbon nanotube (CNT) photocatalysts, namely, SZC, SZC, and SZC with different Sr doping concentrations, were synthesized using the sol-gel method and coated on plasma-functionalized fabric to perform the self-cleaning tests. The fabrics were treated with dielectric barrier discharge plasma in an open environment for 3 min to achieve a stable coating of nanoparticles.

Statistically Analyzed Heavy Metal Removal Efficiency of Silica-Coated CuMgFeO Magnetic Adsorbent for Wastewater Treatment.

Even low concentrations of pollutants in water, particularly heavy metals, can significantly affect the ecosystem and human health. Adsorption has been determined to be one of the most effective techniques of removing pollution from wastewater among the various strategies. To remove heavy metals such as Zn and Pb, we prepared a silica-coated CuMgFeO magnetic adsorbent using sol-gel method and tested it for wastewater treatment.

Dual S-Scheme Heterojunction CdS/TiO/g-CN Photocatalyst for Hydrogen Production and Dye Degradation Applications.

This study investigated a ternary CdS/TiO/g-CN heterojunction for degrading synthetic dyes and hydrogen production from aqueous media through visible light-initiated photocatalytic reactions. CdS, TiO, and g-CN were combined in different mass ratios through a simple hydrothermal method to create CdS/TiO/g-CN composite photocatalysts. The prepared heterojunction catalysts were investigated by using FTIR, XRD, EDX, SEM, and UV-visible spectroscopy analysis for their crystal structures, functional groups, elemental composition, microtopography, and optical properties.

Production of combustible fuels and carbon nanotubes from plastic wastes using an in-situ catalytic microwave pyrolysis process.

This study performed in-situ microwave pyrolysis of plastic waste into hydrogen, liquid fuel and carbon nanotubes in the presence of Zeolite Socony Mobil ZSM-5 catalyst. In the presented microwave pyrolysis of plastics, activated carbon was used as a heat susceptor. The microwave power of 1 kW was employed to decompose high-density polyethylene (HDPE) and polypropylene (PP) wastes at moderate temperatures of 400-450 °C.

Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images.

The teeth are the most challenging material to work with in the human body. Existing methods for detecting teeth problems are characterised by low efficiency, the complexity of the experiential operation, and a higher level of user intervention. Older oral disease detection approaches were manual, time-consuming, and required a dentist to examine and evaluate the disease.

IoT Framework for a Decision-Making System of Obesity and Overweight Extrapolation among Children, Youths, and Adults.

Approximately 30% of the global population is suffering from obesity and being overweight, which is approximately 2.1 billion people worldwide. The ratio is expected to surpass 40% by 2030 if the current balance continues to grow.

A Turf-Based Feature Selection Technique for Predicting Factors Affecting Human Health during Pandemic.

Worldwide, COVID-19 is a highly contagious epidemic that has affected various fields. Using Artificial Intelligence (AI) and particular feature selection approaches, this study evaluates the aspects affecting the health of students throughout the COVID-19 lockdown time. The research presented in this paper plays a vital role in indicating the factor affecting the health of students during the lockdown in the COVID-19 pandemic.

Analysis of Statistically Predicted Rate Constants for Pyrolysis of High-Density Plastic Using R Software.

The surge in plastic waste production has forced researchers to work on practically feasible recovery processes. Pyrolysis is a promising and intriguing option for the recycling of plastic waste. Developing a model that simulates the pyrolysis of high-density polyethylene (HDPE) as the most common polymer is important in determining the impact of operational parameters on system behavior.

Physical Activity Monitoring and Classification Using Machine Learning Techniques.

Physical activity plays an important role in controlling obesity and maintaining healthy living. It becomes increasingly important during a pandemic due to restrictions on outdoor activities. Tracking physical activities using miniature wearable sensors and state-of-the-art machine learning techniques can encourage healthy living and control obesity.

Construction of 0D/2D Schottky Heterojunctions of ZnO and TiC Nanosheets with the Enriched Transfer of Interfacial Charges for Photocatalytic Hydrogen Evolution.

The development of cost-effective co-catalysts of high photocatalytic activity and recyclability is still a challenge in the energy transformation domain. In this study, 0D/2D Schottky heterojunctions, consisting of 0D ZnO and 2D TiC, were successfully synthesized by the electrostatic self-assembling of ZnO nanoparticles on TiC nanosheets. In constructing these heterojunctions, TiC nanosheets acted as a co-catalyst for enhancing the transfer of excitons and their separation to support the photocatalytic response of ZnO.

Evaluation of Ultrasonically ZnO Loading Effect on Photocatalytic Self-Cleaning, UV Protection and Antibacterial Activity of Plasma/Citric Acid-Activated Cotton Fabric.

Zinc oxide (ZnO) nanoparticles were loaded over non-thermal plasma (P1) and citric acid (P2)-functionalized cotton fabrics using a room temperature sonification process. The cotton samples were pretreated with dielectric barrier discharge (DBD) plasma and citric acid to introduce some reactive moieties on the fabric to enhance the adhesion power of ZnO nanoparticles with an average particle size of 41 nm. The nanoparticles were dispersed homogeneously on the surface of the P1 sample, which enhanced the antibacterial, UV protection and photocatalytic self-cleaning characteristics of ZnO-loaded fabric.

Kinetics and Adsorption Isotherms of Amine-Functionalized Magnesium Ferrite Produced Using Sol-Gel Method for Treatment of Heavy Metals in Wastewater.

This study is focused on the kinetics and adsorption isotherms of amine-functionalized magnesium ferrite (MgFeO) for treating the heavy metals in wastewater. A sol-gel route was adopted to produce MgFeO nanoparticles. The surfaces of the MgFeO nanoparticles were functionalized using primary amine (ethanolamine).

Non-Thermal Plasma Reduction of Ag Ions into Silver Nanoparticles in Open Atmosphere under Statistically Optimized Conditions for Biological and Photocatalytic Applications.

An environmentally friendly non-thermal DC plasma reduction route was adopted to reduce Ag+ ions at the plasma−liquid interface into silver nanoparticles (AgNPs) under statistically optimized conditions for biological and photocatalytic applications. The efficiency and reactivity of AgNPs were improved by statistically optimizing the reaction parameters with a Box−Behnken Design (BBD). The size of the AgNPs was chosen as a statistical response parameter, while the concentration of the stabilizer, the concentration of the silver salt, and the plasma reaction time were chosen as independent factors.

Investigating the Impact of Cu Doping on the Morphological, Structural, Optical, and Electrical Properties of CoFeO Nanoparticles for Use in Electrical Devices.

This study investigated the production of Cu-doped CoFeO nanoparticles (CFO NPs) using a facile sol-gel technique. The impact of Cu doping on the lattice parameters, morphology, optical properties, and electrical properties of CFO NPs was investigated for applications in electrical devices. The XRD analysis revealed the formation of spinel-phased crystalline structures of the specimens with no impurity phases.

Si/SiO/AlO Supported Growth of CNT Forest for the Production of La/ZnO/CNT Photocatalyst for Hydrogen Production.

The use of ZnO as a photocatalyst with a reduced recombination rate of charge carriers and maximum visible light harvesting remains a challenge for researchers. Herein, we designed and synthesized a unique La/ZnO/CNTs heterojunction system via a sol-gel method to evaluate its photocatalytic performance for hydrogen evolution. A ferrocene powder catalyst was tested for the production of CNT forests over Si/SiO/AlO substrate.

Microstructure and Mechanical Properties of Modified 316L Stainless Steel Alloy for Biomedical Applications Using Powder Metallurgy.

AISI 316L stainless steel (SS) is one of the extensively used biomaterials to produce implants and medical devices. It provides a low-cost solution with ample mechanical properties, corrosion resistance, and biocompatibility compared to its counterpart materials. However, the implants made of this material are subjected to a short life span in human physiological conditions leading to the leaching of metal ions, thus limiting its use as a biomaterial.

Response Surface Methodology and Artificial Neural Network Modelling of Membrane Rotating Biological Contactors for Wastewater Treatment.

Membrane fouling is a major hindrance to widespread wastewater treatment applications. This study optimizes operating parameters in membrane rotating biological contactors (MRBC) for maximized membrane fouling through Response Surface Methodology (RSM) and an Artificial Neural Network (ANN). MRBC is an integrated system, embracing membrane filtration and conventional rotating biological contactor in one individual bioreactor.

Experimental and Numerical Investigation of Effect of Static and Fatigue Loading on Behavior of Different Double Strap Adhesive Joint Configurations in Fiber Metal Laminates.

Double strap lap adhesive joints between metal (AA 6061-T6) and composite (carbon/epoxy) laminates were fabricated and characterized based on strength. Hand layup methods were used to fabricate double strap match lap joints and double strap mismatch lap joints. These joints were compared for their strength under static and fatigue loadings.

Gold Nanorods for Doxorubicin Delivery: Numerical Analysis of Electric Field Enhancement, Optical Properties and Drug Loading/Releasing Efficiency.

The optical properties and electric field enhancement of gold nanorods for different cases were investigated in this study. The numerical analysis was carried out to understand the functionality and working of gold nanorods, while the experimental portion of the work was focused on the efficiency of gold nanorods for targeted drug delivery. COMSOL Multiphysics was used for numerical analysis.

Machine Learning and Internet of Things Enabled Monitoring of Post-Surgery Patients: A Pilot Study.

Artificial Intelligence (AI) and Internet of Things (IoT) offer immense potential to transform conventional healthcare systems. The IoT and AI enabled smart systems can play a key role in driving the future of smart healthcare. Remote monitoring of critical and non-critical patients is one such field which can leverage the benefits of IoT and machine learning techniques.

Analyzing Distributed Vibrating Sensing Technologies in Optical Meshes.

Hundreds of kilometers of optical fibers are installed for optical meshes (OMs) to transmit data over long distances. The visualization of these deployed optical fibers is a highlighted issue because the conventional procedure can only measure the optical losses. Thus, this paper presents distributed vibration sensing (DVS) estimation mechanisms to visualize the optical fiber behavior installed for OMs which is not possible by conventional measurements.

Synthesis and Characterization of Manganese-Modified Black TiO Nanoparticles and Their Performance Evaluation for the Photodegradation of Phenolic Compounds from Wastewater.

The release of phenolic-contaminated treated palm oil mill effluent (TPOME) poses a severe threat to human and environmental health. In this work, manganese-modified black TiO (Mn-B-TiO) was produced for the photodegradation of high concentrations of total phenolic compounds from TPOME. A modified glycerol-assisted technique was used to synthesize visible-light-sensitive black TiO nanoparticles (NPs), which were then calcined at 300 °C for 60 min for conversion to anatase crystalline phase.