Synthesis and Characterization of Titanium-Substituted Large Pore SSZ-42 Zeolite

Titanium-substituted large pore SSZ-42 zeolite was synthesized for the first time using the corresponding borosilicate as starting material. Substitution of boron by titanium took place via either high temperature treatment with TiCl₄ vapor or by treatment with Ti(OiPr)₄ in dry toluene at 120°C. Both deboronated and boron-containing samples were found to be suitable for post-synthesis incorporation of titanium in the zeolite framework. The obtained materials were characterized by FTIR, UV-visible and XPS. Titanium-modified SSZ-42 was found to be active for phenol hydroxylation and cyclohexene epoxidation.     

Wind Power Prediction Based on Machine Learning and Deep Learning Models

Wind power is one of the sustainable ways to generate renewable energy. In recent years, some countries have set renewables to meet future energy needs, with the primary goal of reducing emissions and promoting sustainable growth, primarily the use of wind and solar power. To achieve the prediction of wind power generation, several deep and machine learning models are constructed in this article as base models. These regression models are Deep neural network (DNN), k-nearest neighbor (KNN) regressor, long short-term memory (LSTM), averaging model, random forest (RF) regressor, bagging regressor, and gradient boosting (GB) regressor. In addition, data cleaning and data preprocessing were performed to the data. The dataset used in this study includes 4 features and 50530 instances. To accurately predict the wind power values, we propose in this paper a new optimization technique based on stochastic fractal search and particle swarm optimization (SFS-PSO) to optimize the parameters of LSTM network. Five evaluation criteria were utilized to estimate the efficiency of the regression models, namely, mean absolute error (MAE), Nash Sutcliffe Efficiency (NSE), mean square error (MSE), coefficient of determination (R²), root mean squared error (RMSE). The experimental results illustrated that the proposed optimization of LSTM using SFS-PSO model achieved the best results with R² equals 99.99% in predicting the wind power values.     

Detection of malaria infection via latex agglutination assay

A rapid test for malaria diagnosis based on specific agglutination of sensitive polystyrene particles containing carboxylic acid with antigen or antibody molecules in the presence of their corresponding antibody or antigen in human plasma has been achieved. The particle-malaria antigen conjugate (PAgC), particle-monoclonal IgG antibody to Plasmodium falciparum heat shock protein 70 conjugate (PmAbC), and particle-polyclonal IgG antibody to P. falciparum malaria conjugate (PpAbC) were prepared via adsorption process. The higher affinity of the malaria antigen adsorption onto particles was observed compared to that of the antibodies. Immunoagglutination of sensitive latex particles was monitored by measuring the change in turbidity, and the aggregate's formation was clearly observed under optical microscope. The efficacy in malaria diagnosis of the conjugated particles evaluated at an outpatient malaria clinic (Mae Sod, Thailand) indicated a success detection of antibody or antigen. Sensitivity of PAgC, PmAbC, and PpAbC for P. falciparum was 84%, 90%, and 90%, respectively, while specificity for malaria disease was 70% for PAgC and 80% for PmAbC and PpAbC. The rapid agglutination-based latex particles assay developed herein showed a great potential for diagnosis of malaria infection.     

Gold surface functionalization and patterning for specific immobilization of olfactory receptors carried by nanosomes

There is substantial interest in engineering solid supports to achieve functional immobilization of membrane receptors both for investigation of their biological function and for the development of novel biosensors. Three simple and practical strategies for immobilization of a human olfactory receptor carried by nanosomes are presented. The basis of the functionalization of solid gold surfaces is a self-assembled monolayer (SAM) containing biotinyl groups. Biotinyl groups are subsequently used to attach neutravidin and then biotinylated monoclonal antibody directed against the receptor to allow its specific grafting. Surface plasmon resonance technique is implemented for real-time monitoring of step-by-step surface functionalization and, in addition, for testing the functional response of immobilized olfactory receptors. We show that OR1740 is functional when immobilized via a tag attached to its C-terminus, but not via its N-terminus. Finally, we demonstrate that gold surfaces can be patterned by the SAMs tested using microcontact printing. AFM images of immobilized nanosomes onto a patterned surface suggest that small nanosomes flatten and fuse into larger vesicles but do not merge into a continuous layer. The whole study emphasizes the outstanding performances of the BAT/PEGAT SAM, which could be useful for developing on-a-chip sensor formats for membrane receptor investigations and use.     

Experimental investigation of the rheological behavior of algerian crude oils from the quagmires

In this work, the rheological behavior for three types of crude oil coming from different quagmires namely Amassak, Tamendjelt and Tin Fouye of the TFT sector (Tin Fouye Tabankort/South Algeria) has been experimentally investigated. A controlled stress rheometer (AR 2000, TA Instrument) was used throughout this investigation. The experimental measurements in terms of flow and dynamic tests were carried out at different temperatures during the shear rate over the range of 0–700?s^?1 and frequency range of 0.1–10?rad/s. The obtained results show that the viscosity and shear stress of the crude oils decreases about 53.30%, 58.80%, and 59% respectively, when the temperature increased from 10 to 20?°C. The yield stress required to flow of crude oils also decreased to 37.06%, 89.78%, and 77.53% respectively. The dynamic analysis of the crude oils by identifying of the storage modulus (G′) and the loss modulus (G″) has indicated that the rheological properties of crude oils were significantly temperature-dependent.     

Fire tests of steel-to-timber connections with high fire resistance

This paper presents the results of twenty-one fire tests on unprotected steel-to-timber connections with dowel-type fasteners and one or two slotted-in steel plates. The experimental results of this type of connections available in existing studies have been mostly limited to a fire resistance duration of 60 min. The tests performed in this study target a significant increase of fire resistance to reach 90 and 120 min. Two configurations of connections with one and two slotted-in steel plates, i.e., two or four shear planes, were tested. The temperatures were measured at different locations in the wood members and along the steel plates. Two load levels for fire tests were determined on the basis of tests performed at ambient temperature. The experimental results show that the specimens proposed for steel-to-timber connections with dowel-type fasteners are suitable for achieving fire resistance of 90 and 120 min.     

Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute, making the machine learning (ML) solutions more appealing. Patients with cardiac arrhythmias can benefit from competent monitoring to save their lives. Cardiac arrhythmia classification and prediction have greatly improved in recent years. Arrhythmias are a category of conditions in which the heart's electrical activity is abnormally rapid or sluggish. Every year, it is one of the main reasons of mortality for both men and women, worldwide. For the classification of arrhythmias, this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors (KNN) classifier. The proposed method makes advantage of the UCI repository, which has a 279-attribute high-dimensional cardiac arrhythmia dataset. The proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s features. The purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia patients. This method of comprehensive arrhythmia classification outperforms earlier methods presented in the literature. The achieved classification accuracy using the proposed approach is 99.8%.     

Effect of Nickel Nitrate Concentration on the Size of Nickel Oxide Nanoparticles Bio-synthesized by Artemisia herba-alba Aqueous Leaves Extract and Improving Their Antioxidant Activities

Journal of Inorganic and Organometallic Polymers and Materials - This work aims to investigate the effect of nickel nitrate concentration on the size and antioxidant activity of nickel oxide...     

Optimizing the Antibacterial Activity of Iron Oxide Nanoparticles Using Central Composite Design

This work aims to optimize the antibacterial activity of iron oxide nanoparticles (IONPs) against both Gram-positive and Gram-negative bacteria. IONPs were greenly biosynthesized using Moringa oleifera leaves extract, and surface methodology (RSM) based on central composite design (CCD) was employed to investigate the combined effect of various experimental factors on the antibacterial activity of IONPs. The reaction and annealing temperatures besides precursor concentration were set as independent variables, while the antibacterial activity was set as a response to obtain the optimal conditions that maximizes IONPs antibacterial activity. Different characterization techniques such as UV–Vis, FTIR, XRD, SEM, and EDX were employed to study the properties of the biosynthesized nanoparticles. Meanwhile, the antibacterial activity was tested using the disk diffusion method. The characterizations results have confirmed the biosynthesis of Hematite (α-Fe₂O₃) nanoparticles of rhombohedral structure. The generated model has exhibited predicted values very close to the actual proving its validity to analyze and optimize the studied process. The model indicated that all the investigated parameters and their interactions have significantly affected IONPs antibacterial activity. An optimal antibacterial activity was achieved when biosynthesis factors at their lower levels (? 1). Furthermore, the effect of IONPs size on the antibacterial activity was studied and the results shown that the latter is significantly related to the nanoparticles size.

Graphical Abstract