Modeling the rate of corrosion of carbon steel using activated diethanolamine solutions for CO2 absorption

A mechanistic model is developed to investigate the influence of an activator on the corrosion rate of carbon steel in the absorption processes of carbon dioxide (CO₂). Piperazine (PZ) is used as the activator in diethanolamine (DEA) aqueous solutions. The developed model for corrosion takes into consideration the effect of fluid flow, transfer of charge and diffusion of oxidizing agents and operating parameters like temperature, activator concentration, CO₂ loading and pH. The study consists of two major models: Vapor-liquid Equilibrium (VLE) model and electrochemical corrosion model. The electrolyte-NRTL equilibrium model was used for determination of concentration of chemical species in the bulk solution. The results of speciation were subsequently used for producing polarization curves and predicting the rate of corrosion occurring at the surface of metal. An increase in concentration of activator, increases the rate of corrosion of carbon steel in mixtures of activated DEA.     

Optimized Intelligent Auto-Regressive Neural Network Model (ARNN) for Prediction of Non-Linear Exogenous Signals

Wireless Personal Communications - The paper presents a prediction of non-linear exogenous signal by optimized intelligent auto-regressive neural network model (ARNN). A signal comprises of two...     

Micro‐morphological,environmental and phytochemical investigation of herbal medicines by using LM and SEM: A quality control tool

The use of quality control tool for authentication of Jadwar (Delphinium denudatum Wall. ex Hook.f. & Thomson), a folk herbal drug used for the treatment of different ailments, was studied. People face problems of adulteration for this drug at global, regional, national and local levels. Two different plant species are commercially marketed in the Indo‐Pak Subcontinent under the same trade name of Jadwar. One is D. denudatum Wall. ex Hook.f. & Thomson and the other is Aconitum heterophyllum Wall. ex Royle. To focus on this problem, a marketable available drug sample of Jadwar was authenticated by using basic microscopy tools (LM) and advanced chemo‐taxonomic markers. Authentication, quality and standardization of this drug was achieved using morphology, organoleptography, UV and IR analyses, scanning electron microscopy of pollen and anatomical investigations. The techniques used for authentication marked the clear difference between the studied plants. Microscopic studies, chemotaxonomic investigation and other techniques used in this project provided the basis for the authentication of this species.     

Analysis of Titanium-Coated Glass and Imidex (PI) Laser Bonded Samples

Based on previous results of bond strength, scanning electron microscopy(SEM)/energy dispersive spectroscopy (EDS) and x-ray photoelectron spectroscopy (for thin film thickness in the range of 50 to 200 nm range), it is expected for a moderate film thickness of titanium (over 50 nm) for the system of sputtered Ti-coated glass/polymer two factors play important roles in getting strong bond between Ti/Polyimide interface: (i) mechanical interlocking property and (ii) chemical bond formation such as Ti-C, Ti-O between Ti and imidex (PI) film. In this study, a systematic investigation has been conducted to understand the effects of thin films on bond quality and on failure mechanism of the interface between 400 nm sputtered Ti-coated glass/imidex (PI) system. This article basically studies if for this higher film thickness the failure pattern and bond strength are consistent with the previous data. From previous studies (for thin film thickness of 50 to 200 nm) the conclusion extracted is thin film with thickness of less than 50 nm exhibited low bond strength when compared to film thickness over 50 nm and from the results obtained in this study it is concluded that the bond reliability and failure modes of sputtered Ti film on glass are consistent even for a film thickness as high as 400 nm and three types of failure modes are found : (i) cohesive failure mode, (ii) Ti/glass interface failure mode, and (iii) glass failure mode. The roughness value for this coating thickness is 17 nm.     

Elemental analyses and determination of lead content in kohl (stone) by laser-induced breakdown spectroscopy

Elemental analyses of kohl (stone) samples collected from three different parts of the world were performed using laser-induced breakdown spectroscopy (LIBS). The analyses indicated that lead (Pb), copper (Cu), silver (Ag), iron (Fe), calcium (Ca), aluminum (Al), silicon (Si), and sodium (Na) were present in all the kohl samples. In addition to these elements, the sample from Madina, Kingdom of Saudi Arabia (KSA), contained the elements tin (Sn), zirconium (Zr), and antimony (Sb). The sample from Mount Toor, Egypt, also contained Sn. Also, quantitative analysis for lead was carried out by the standard addition method using the LIBS technique. The result showed the presence of 14.12 ± 0.28% by weight of Pb in the sample from Madina, which compares well with the measurement done using atomic absorption spectroscopy (AAS) (13.31 ± 0.46%). The standard addition method used three calibration curves drawn for three emission lines of the LIBS spectra of Pb. The limits of detection (LoD) for these calibration curves varied from 0.27% to 1.16% by weight. The lead contents of the samples from Mount Toor and the local market of Bangladesh were also measured by the AAS technique, and the results were 14.61 ± 0.48% and 8.98 ± 0.35% by weight, respectively. The reason for determining only the lead content in kohl, which may be used as an eye cosmetic, is the adverse effect that lead has on health.     

Pollen morphological investigations of family Cactaceae and its taxonomic implication by light microscopy and scanning electron microscopy

The family Cactaceae is the diversified group of angiosperm plants whose pollen statistics has been used for taxonomic identification. In this article, we present the pollen morphology of eight species belong to seven taxonomically complex genera of Cactaceae including Astrophytum, Cylindropuntia, Echinocereus, Echinopsis, Mammillaria, Opuntia, and Thelocactus using light and scanning electron microscopy. The pollen grains were acetolyzed, measured, described, and electron photomicrographs were taken. Cactaceae can be characterized by presenting different palynomorphological features including pollen type, sculpturing, polar and equatorial diameter, aperture orientation, exine thickness, P/E ratio, and echini features. Four types of pollen shapes, that is, prolate spheroidal (three species), subprolate (two species), prolate (two species), and oblate spheroidal in Echinocereus reichenbachii were observed. The polar and equatorial diameter observed maximum in O. ficus indica 116.95 and 112.27 μm while minimum in M. compressa 38.42 and 21.05 μm. Pollen of two types, tricolpate in members of subfamily Cactioideae and pantoporate in the Opuntioideae were examined. The fertility percentage has been observed maximum in Opuntia macrocentra (83.84%) and minimum in Opuntia ficus‐indica (57.89%). Exine sculpturing showing great variations such as granulate, reticulate, granulate perforate and micro‐echinate foveolate ornamentation was examined only in Echinopsis eyriesii. A key to species, based on pollen micromorphological attributes, has been constructed for correct identification of complex cactus species.     

The Plastome Sequences of Triticum sphaerococcum (ABD) and Triticum turgidum subsp. durum (AB) Exhibit Evolutionary Changes,Structural Characterization,Comparative Analysis,Phylogenomics and Time Divergence

The mechanism and course of Triticum plastome evolution is currently unknown; thus, it remains unclear how Triticum plastomes evolved during recent polyploidization. Here, we report the complete plastomes of two polyploid wheat species, Triticum sphaerococcum (AABBDD) and Triticum turgidum subsp. durum (AABB), and compare them with 19 available and complete Triticum plastomes to create the first map of genomic structural variation. Both T. sphaerococcum and T. turgidum subsp. durum plastomes were found to have a quadripartite structure, with plastome lengths of 134,531 bp and 134,015 bp, respectively. Furthermore, diploid (AA), tetraploid (AB, AG) and hexaploid (ABD, AGA^m) Triticum species plastomes displayed a conserved gene content and commonly harbored an identical set of annotated unique genes. Overall, there was a positive correlation between the number of repeats and plastome size. In all plastomes, the number of tandem repeats was higher than the number of palindromic and forward repeats. We constructed a Triticum phylogeny based on the complete plastomes and 42 shared genes from 71 plastomes. We estimated the divergence of Hordeum vulgare from wheat around 11.04–11.9 million years ago (mya) using a well-resolved plastome tree. Similarly, Sitopsis species diverged 2.8–2.9 mya before Triticum urartu (AA) and Triticum monococcum (AA). Aegilops speltoides was shown to be the maternal donor of polyploid wheat genomes and diverged ~0.2–0.9 mya. The phylogeny and divergence time estimates presented here can act as a reference framework for future studies of Triticum evolution.     

Characterization of Failed Surface of Ti and Imidex (PI) Film for Different Inter-layer Thicknesses of Ti Film

For miniaturized biomedical devices, laser joining of dissimilar materials offers excellent potential to make precise joints. An important system for consideration is titanium (Ti) coated glass joined with biocompatible imidex polyimide (PI). Metallic Ti with various thicknesses was deposited on top of pyrex 7740 borosilicate glass by using DC-magnetron sputtering deposition method. Effect of bond strength between Ti coated glass and imidex polyimide (PI), due to thickness variation of sputtered Ti coating was studied. Three different Ti inter-layer thicknesses were considered, 50, 200, and 400?nm. Tests results indicated that the thinner film produced lower shear strength and higher thickness produced higher shear strength. It has been observed that thicker film (200 and 400?nm) enhanced considerably the bond strength with enhancing the film roughness as well. Higher roughness resulted in more contact area at the interface, results higher number of chemical bonds and increased mechanical interlocking; which in turn increase the laser joint strength. For stronger bond with higher thickness, mixed mode failure was observed which included cohesive failure of polymer, interface failure of Ti/glass and failure on the glass itself. On the other hand, for weak bond with thinner film, mostly interface failure was observed for this system of Ti coated glass/imidex. For thicker film, chemical bond of Ti-C and Ti-O were observed. The role of both surface characteristics and chemical bonding for laser joints were investigated by using advanced techniques such as X-ray photoelectron spectroscopy, scanning electron microscopy, and energy dispersive spectroscopy.     

Improved Bat Algorithm with Deep Learning-Based Biomedical ECG Signal Classification Model

With new developments experienced in Internet of Things (IoT), wearable, and sensing technology, the value of healthcare services has enhanced. This evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based healthcare. Bio-medical Electrocardiogram (ECG) signals are generally utilized in examination and diagnosis of Cardiovascular Diseases (CVDs) since it is quick and non-invasive in nature. Due to increasing number of patients in recent years, the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from patients. In such scenario computer-assisted automated diagnostic tools are important for classification of ECG signals. The current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECG Signal Classification (IBADL-BECGC) approach. To accomplish this, the proposed IBADL-BECGC model initially pre-processes the input signals. Besides, IBADL-BECGC model applies NasNet model to derive the features from test ECG signals. In addition, Improved Bat Algorithm (IBA) is employed to optimally fine-tune the hyperparameters related to NasNet approach. Finally, Extreme Learning Machine (ELM) classification algorithm is executed to perform ECG classification method. The presented IBADL-BECGC model was experimentally validated utilizing benchmark dataset. The comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.     

Genetic-Frog-Leaping Algorithm for Text Document Clustering

In recent years, the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web. As a result, the use of techniques for extracting useful information from large collections of data, and particularly documents, has become more necessary and challenging. Text clustering is such a technique; it consists in dividing a set of text documents into clusters (groups), so that documents within the same cluster are closely related, whereas documents in different clusters are as different as possible. Clustering depends on measuring the content (i.e., words) of a document in terms of relevance. Nevertheless, as documents usually contain a large number of words, some of them may be irrelevant to the topic under consideration or redundant. This can confuse and complicate the clustering process and make it less accurate. Accordingly, feature selection methods have been employed to reduce data dimensionality by selecting the most relevant features. In this study, we developed a text document clustering optimization model using a novel genetic frog-leaping algorithm that efficiently clusters text documents based on selected features. The proposed approach is based on two metaheuristic algorithms: a genetic algorithm (GA) and a shuffled frog-leaping algorithm (SFLA). The GA performs feature selection, and the SFLA performs clustering. To evaluate its effectiveness, the proposed approach was tested on a well-known text document dataset: the “20Newsgroup” dataset from the University of California Irvine Machine Learning Repository. Overall, after multiple experiments were compared and analyzed, it was demonstrated that using the proposed algorithm on the 20Newsgroup dataset greatly facilitated text document clustering, compared with classical K-means clustering. Nevertheless, this improvement requires longer computational time.