Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Several new derivatives of 1, 2, 4-triazoles linked to phthalimide moiety were synthesized through following multisteps. The first step involved preparation of 2, 2-diphthalimidyl ethanoic acid [2] via reaction of two moles of phthalimide with dichloroacetic acid. Treatment of the resulted imide with ethanol in the second step afforded 2, 2-diphthalimidyl ester [3] which inturn was introduced in reaction with hydrazine hydrate in the third step, producing the corresponding hydrazide derivative [4]. The synthesized hydazide was introduced in different synthetic paths including treatment with carbon disulfide in alkaline solution then with hydrazine hydrate to afford the new 1, 2, 4-triazole [10]. Reaction of compound [10] with different alde

In this study, chalcones were synthesis by condensing 2-acetylpyridine with aromatic aldehyde derivatives in dilute ethanolic potassium hydroxide solution at room temperature according to Claisen-Schmidt condensation. After that, new heterocyclic derivatives such as Oxazine, Thiazine and Pyrazol were synthesis by reaction between chalcones with urea, thiourea and hydrazine hydrate respectively scheme 1. All these compounds wrer characterization by FTIR, 1H-NMR spectroscopy and elemental analysis.

Schiff bases, named after Hugo Schiff, are aldehyde- or ketone-like compounds in which the carbonyl group is replaced by imine or azomethine group. They are widely used for industrial purposes and also have a broad range of applications as antioxidants. An overview of antioxidant applications of Schiff bases and their complexes is discussed in this review. A brief history of the synthesis and reactivity of Schiff bases and their complexes is presented. Factors of antioxidants are illustrated and discussed. Copyright © 2016 John Wiley & Sons, Ltd.

  Secnidazole was linked with ciprofloxacin as mutual prodrugs to get antibiotics with broader spectrum of activity, improved physicochemical properties and given by single dose to improve patient’s compliance. Furthermore, they provide structural modifications to overcome bacterial adaptation. The structures of the synthesized compounds were confirmed using FT-IR, mass spectrometry, elemental microanalysis (CHNO) and some physiochemical properties. This modification was led to an increase in Log P values for Mutual I (Log P 1.114) and Mutual II (Log P 1.97) compared with its values for Secnidazole (Log P -0.373) and ciprofloxacin (Log P -0.832). The solubility of prodrugs had been determined in different media, Mutual II showed 1