Hydrophobic silica aerogels were successfully preparation by an ambient pressure drying method from sodium silicate (Na2SiO3) with different pH values (5, 6, 7, 8, 9 and 10). In this study, acidic HCl (1M), a basic NH4OH (1M) were selected as a catalyst to perform the surface modification in a TMCS (trimethylchlorosilane) solution. The surface chemical modification of the aerogels was assured by the Fourier transform infrared (FTIR) spectroscopic studies. Other physical properties, such as pore volume and pore size and specific surface area were determined by Brunauer-Emmett- Teller (BET) method. The effect of pH values on the bulk density of aerogel. The sol–gel parameter pH value in the sol, have marked effects on the physical proper

Sol-gel derived CuCo-oxide coatings as solar selective surfaces, synthesized onto aluminium substrates at various annealing temperatures, are analysed by correlating their structural, chemical bonding states, and surface morphological topographies. As the annealing progressed, all the coatings displayed a Cu0.56Co2.44O4 (ICSD 78-2175) phase with preferential orientation along (400) reflection plane. Rietveld refinement of X-ray diffraction (XRD) data indicate that residual stress and microstrains developed around the coating surfaces are reduced resulting in mechanically stable thin films. Enhancement of the crystallite size and preferred orientation of the surface were confirmed via XRD, field emission scanning electron microscopy (FESEM),

This study designed to prepare ultrafine apixaban (APX) o/w nanoemulsion (NE) based gel with droplet size below 50 nm as a good method for transdermal APX delivery without using permeation enhancer, alternatively, the formulation components itself act as permeation enhancer. APX, a potent oral anticoagulant drug that selectively and directly inhibit coagulation factor Xa, was selected as a good candidate for transdermal delivery as it displays poor water solubility (0.028 mg/mL) and low bioavailability (50%). APX-NE gel was prepared using triacetin, triton-x-100 and carbitol as oil phase, surfactant and cosurfactant respectively, while Carbopol 940 used as a gelling agent. Ex vivo permeation of APX-NE gel through human stratum c

Gel polymer electrolytes (GPEs) have attracted considerable attention for rechargeable battery applications because of their high ionic conductivity, mechanical flexibility, and enhanced safety. In the present work, copper-ion-conducting PVA/HPMC gel polymer electrolytes were successfully prepared by the solution casting method using a 50:50 PVA/HPMC blend. Different CuSO₄ concentrations (10, 20, and 30 wt%) were incorporated into the polymer matrix, followed by the addition of 3 mL PANI/[BMIM][BF₄] polyionic liquid. The prepared electrolytes were characterized using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and electrochemical impedance spectroscopy (EIS). SEM analysi

The present study revealed a low-cost process for utilizing desert sand for preparing nanosilica by sol-gel technique. This work required sodium hydroxide, concentrated hydrochloric acid, distillate water as raw materials, and Iraqi sand. Nanosilica sample was characterized by X-Ray Diffraction (XRD), scanning electron microscopy analysis (SEM), atomic force microscope(AFM), surface area (BET) method, and fourier transform infrared (FTIR). The XRD result of produced sample is referred to as amorphous silica, and it has a broad peak at 2Θ= 22° – 22.5 º. SEM showed spherical, agglomerated silica particles with a diameter range of 26.57–28.93 nm. In addition, the average particle size was 76.35nm, with a dimension range of 40-11

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

This study represents an optical biosensor for early skin cancer detection using cysteine-cupped CdSe/CdS Quantum Dots (QDs). The study optimizes QD synthesis, surface, optical functionalization, and bioconjugation to enhance specificity and sensitivity for early skin cancer cell detection. The research provides insights into QD interactions with skin cancer biomarkers, demonstrating high-contrast, precise cellular imaging. Cysteine-capped CdSe/CdS absorption spectra reveal characteristic peaks for undamaged DNA, while spectral shifts indicate structural changes in skin-cancer-damaged DNA. Additionally, fluorescence spectra show sharp peaks for undamaged DNA and notable shifts and intensity variations when interacting with skin cancer. This

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over