Biosynthesized ZnO NPs loaded-electrospun PVA/sodium alginate/glycine nanofibers: synthesis, spinning optimization and antimicrobial activity evaluation.

In this work, microalgae-based zinc oxide nanoparticles loaded with electrospun polyvinyl alcohol (PVA)/sodium alginate (SA) nanofibers were fabricated by electro-spinner. PVA/SA fibrous mats were crosslinked by citric acid, which enhanced their thermal stability and swelling behavior. Green-synthesized ZnO NPs were laboratory synthesized and characterized by FTIR, XRD, EDX, SEM, TEM and TGA analyses.

Machine learning boosts wind turbine efficiency with smart failure detection and strategic placement.

The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analysis or by using Supervisory Control and Data Acquisition (SCADA) data of wind turbines, wherein conventional fault pattern identification is a time-consuming, guesswork process. This work proposed an intelligent automated approach to early fault detection through the implementation of the HARO (Huber Adam Regression Optimizer) model, which combines Transformer networks with Lasso Regression and the Adam optimizer.

Enhancing heart disease classification based on greylag goose optimization algorithm and long short-term memory.

Heart disease is a category of various conditions that affect the heart, which includes multiple diseases that influence its structure and operation. Such conditions may consist of coronary artery disease, which is characterized by the narrowing or clotting of the arteries that supply blood to the heart muscle, with the resulting threat of heart attacks. Heart rhythm disorders (arrhythmias), heart valve problems, congenital heart defects present at birth, and heart muscle disorders (cardiomyopathies) are other types of heart disease.

Enhanced human activity recognition in medical emergencies using a hybrid deep CNN and bi-directional LSTM model with wearable sensors.

Human activity recognition (HAR) is one of the most important segments of technology advancement in applications of smart devices, healthcare systems & fitness. HAR uses details from wearable sensors that capture the way human beings move or engage with their surrounding. Several researchers have thus presented different ways of modeling human motion, and some have been as follows: Many researchers have presented different methods of modeling human movements.

Impact of molecular configuration on the photoluminescence and electrical characteristics of poly-pyrrol-thiazol-imine polymers films.

The optical, photoluminescence, and electrical properties of Poly(Z)-PTI and Poly(E)-PTI, two Poly-Pyrrol-Thiazol-Imine polymers with comparable chemical structures but distinct configurations, were examined. Using the dip-casting method, polymer films were deposited on ITO substrates. UV-VIS spectroscopy revealed that both polymers diverged between 500 and 800 nm, showing the impact of molecular arrangement, but showed similar absorption behavior for wavelengths shorter than 500 nm.

AHP VIKOR framework for selecting wind turbine materials with a focus on corrosion and efficiency.

The research objective in the context of the study relates to the major concern of corrosion affecting the wind turbines in operation to find materials with high durability in relation to environmental conditions of operation, strength, and cost. A method is an integration of the Analytical Hierarchy Process (AHP) and VIKOR Multi-Criteria Decision Making (MCDM) techniques that will assess seven different material options on sixteen criteria that comprise corrosion resistance, mechanical properties, cost, and a negative environmental impact. From this result, the AHP method calculated the weights for the indicators and chose potential materials, and finally, the VIKOR method used these materials and compared and ranked them to obtain a compromise solution.

Establishing a productive heterogeneous catalyst based on silver nanoparticles supported on a crosslinked vinyl polymer for the reduction of nitrophenol.

The treatment of toxic nitrophenols in industrial wastewater is urgently needed from environmental, health, and economic points of view. The current study addresses the synthesis of the crosslinked vinyl polymer poly(acrylonitrile--2-acrylamido-2-methylpropane sulfonic acid) (poly(AN--AMPS)) through free radical copolymerization techniques using acrylonitrile (AN) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) monomers with different ratios and potassium persulfate (KPS) as an initiator in an aqueous medium. The prepared copolymer was utilized as a supporting matrix for silver nanoparticles (AgNPs) the chemical reduction of silver nitrate within the copolymer framework.

Enhancing deep learning-based slope stability classification using a novel metaheuristic optimization algorithm for feature selection.

The evaluation of slope stability is of crucial importance in geotechnical engineering and has significant implications for infrastructure safety, natural hazard mitigation, and environmental protection. This study aimed to identify the most influential factors affecting slope stability and evaluate the performance of various machine learning models for classifying slope stability. Through correlation analysis and feature importance evaluation using a random forest regressor, cohesion, unit weight, slope height, and friction angle were identified as the most critical parameters influencing slope stability.

Hybrid attention-based deep neural networks for short-term wind power forecasting using meteorological data in desert regions.

This study introduces an optimized hybrid deep learning approach that leverages meteorological data to improve short-term wind energy forecasting in desert regions. Over a year, various machine learning and deep learning models have been tested across different wind speed categories, with multiple performance metrics used for evaluation. Hyperparameter optimization for the LSTM and Conv-Dual Attention Long Short-Term Memory (Conv-DA-LSTM) architectures was performed.

Integrating machine and deep learning technologies in green buildings for enhanced energy efficiency and environmental sustainability.

A green building (GB) is a design idea that integrates environmentally conscious technology and sustainable procedures throughout the building's life cycle. However, because different green requirements and performances are integrated into the building design, the GB design procedure typically takes longer than conventional structures. Machine learning (ML) and other advanced artificial intelligence (AI), such as DL techniques, are frequently utilized to assist designers in completing their work more quickly and precisely.

Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption.

Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended.

Synergistic antimicrobial action of nanocellulose, nanoselenium, and nanocomposite against pathogenic microorganisms.

Recently, there has been a surge in curiosity regarding the application of biopolymer-derived nanomaterials, primarily attributable to their extensive array of potential applications. In this study, nanocellulose was extracted from algae, biomolecule substances synthesized selenium nanoparticles, and a simple nanocomposite of nanocellulose and nanoselenium was elaborated using nanocellulose as a reducing agent under hydrothermal conditions. These nanocomposite materials have markedly improved properties at low concentrations.

Synthesis, characterization of poly L(+) lactic acid and its application in sustained release of isosorbide dinitrate.

Poly L(+) lactic acid (PLLA) has become crucial in the biomedical industry for various uses. The direct polycondensation method was used to prepare Poly L(+) Lactic Acid (PLLA). Different catalysts, including metal oxides and metal halides, were used to test the polymerization technique.

Electrospun network based on polyacrylonitrile-polyphenyl/titanium oxide nanofibers for high-performance supercapacitor device.

Nanofibers and mat-like polyacrylonitrile-polyphenyl/titanium oxide (PAN-Pph./TiO) with proper electrochemical properties were fabricated via a single-step electrospinning technique for supercapacitor application. Scanning electron microscopy (SEM), scanning transmission electron microscopy (STEM), thermogravimetry (TGA), fourier transform infrared (FTIR), X-ray diffraction (XRD) and energy dispersive X-ray (EDX) were conducted to characterize the morphological and chemical composition of all fabricated nanofibers.

Biobran-loaded core/shell nanofibrous scaffold: a promising wound dressing candidate.

This research examined the effectiveness of Biobran as a bioactive substance that could potentially improve wound healing. It also looked at how Biobran affects the properties of a nanofibrous scaffold made through coaxial electrospinning. This is the first study exploring the use of Biobran in this context and its interaction with nanofibrous scaffolds.

Bioproduction and optimization of newly characterized melanin pigment from Streptomyces djakartensis NSS-3 with its anticancer, antimicrobial, and radioprotective properties.

Background: Melanin is a natural pigment that is considered a promising biomaterial for numerous biotechnological applications across several industries. Melanin has biomedical applications as antimicrobial, anticancer, and antioxidant properties. Additionally, in the pharmaceutical and cosmetic industries, it is used in drug delivery and as a radioprotective agent.

An improved deep reinforcement learning routing technique for collision-free VANET.

Vehicular Adhoc Networks (VANETs) is an emerging field that employs a wireless local area network (WLAN) characterized by an ad-hoc topology. Vehicular Ad Hoc Networks (VANETs) comprise diverse entities that are integrated to establish effective communication among themselves and with other associated services. Vehicular Ad Hoc Networks (VANETs) commonly encounter a range of obstacles, such as routing complexities and excessive control overhead.

Wearable Electrospun Piezoelectric Mats Based on a PVDF Nanofiber-ZnO@ZnS Core-Shell Nanoparticles Composite for Power Generation.

This work adopted a strategy to use new functional high-performance piezoelectric materials for sustainable energy production in wearable self-powered electrical devices. An innovative modification in electrospinning was used to produce highly aligned nanofibers. In the nanogenerator, the flexible membrane constituents were tunefully combined.

Microwave-assisted of new derivatives of polyimine conjugated polymer based on Schiff base: synthesis, characterization, and photo-physical properties as a photoluminescent materials.

The condensation of pyrrole-2,5-dicarbaldehyde (1) with 5-(2-amino-4-phenylthiazol-5-yl)-4-phenylthiazol-2-amine (2) and/or 5-(4-Amino-phenyl)-4-phenylthiazol-2-amine (3) gave new poly(Z)-N-((5-(iminomethyl)-1H-pyrrol-2-yl)methylene)-5-(2-((E)-(5-(iminomethyl)-I-pyrrol-2-yl)methyleneamino)-4-phenylthiazol-5-yl)-4-phenylthiaol-2-amine (P1) and/or poly(E)-N-((5-(iminomethyl)-1H-pyrrol-2-yl)methylene)-5-(4-((E)-(5-(iminomethyl)-1H-pyrrol-2-yl)methyleneamino)phenyl)-4-phenylthiaol-2-amine (P2) as a novel conjugated polymer by microwave irradiation and traditional heating.. It is evident that the microwave irradiation technique quickly raised the molecular weight of polyimines.

Synthesis, electrospinning, and molecular docking of poly(methyl methacrylate) Schiff bases and their applications as polymeric antimicrobial agents and for dye removal.

The antibacterial activity of a variety of modified poly(methyl methacrylate) Schiff bases against common microbial infections and removal of methylene blue (MB) dye were screened. The Schiff bases were synthesized from the reaction of the modified (PMMA) with vanillin (PMMA) and cinnamaldehyde (PMMA). By using Fourier transformer infrared (FT-IR), X-ray diffraction analysis (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM), the structures of the nanofibers of the synthesized Schiff bases were confirmed.

Synthesis, Characterization, and Anticancer Potency of Branched Poly (p-Hydroxy Styrene) Schiff-Bases.

A significant issue in cancer biology is finding anticancer therapies that effectively kill cancer cells. Through the use of several aldehydes, Schiff bases based on branched poly (p-hydroxy styrene) are created. The branched polymer is first chloroacetylated, then aminated with 1,4-phenylenediamine, and finally, aldehydes are reacted with the aminated polymer to produce the Schiff base compounds.

Biosynthesis of cellulose from Ulva lactuca, manufacture of nanocellulose and its application as antimicrobial polymer.

Green nanotechnology has recently been recognized as a more proper and safer tool for medical applications thanks to its natural reductions with low toxicity and avoidance of injurious chemicals. The macroalgal biomass was used for nanocellulose biosynthesis. Algae are abundant in the environment and have a high content of cellulose.

Electrospun cellulose acetate/activated carbon composite modified by EDTA (rC/AC-EDTA) for efficient methylene blue dye removal.

The present study fabricated regenerated cellulose nanofiber incorporated with activated carbon and functionalized rC/AC3.7 with EDTA reagent for methylene blue (MB) dye removal. The rC/AC3.