Optimization of design and operating parameters in a pilot scale Jameson cell for slime coal cleaning

The Jameson flotation cell has been commonly used to treat a variety of ores (lead, zinc, copper etc.), coal and industrial minerals at commercial scale since 1989. It is especially known to be highly efficient at fine and ultrafine coal recovery. However, although the Jameson cell has quite a simple structure, it may be largely inefficient if the design and operating parameters chosen are not appropriate. In this study, the design and operating parameters of a pilot scale Jameson cell were optimized to obtain a desired metallurgical performance in the slime coal flotation. The optimized design parameters are the nozzle type, the height of the nozzle above the pulp level, the downcomer diameter and the immersion depth of the downcomer. Among the operating parameters optimized are the collector dosage, the frother dosage, the percentage of solids and the froth height. In the optimum conditions, a clean coal with an ash content of 14.90% was obtained from the sample slime having 45.30% ash with a combustible recovery of 74.20%. In addition, a new type nozzle was developed for the Jameson cell, which led to an increase of about 9% in the combustible recovery value.     

Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear

Malaria is a serious worldwide disease, caused by a bite of a female Anopheles mosquito. The parasite transferred into complex life round in which it is grown and reproduces into the human body. The detection and recognition of Plasmodium species are possible and efficient through a process called staining (Giemsa). The staining process slightly colorizes the red blood cells (RBCs) but highlights Plasmodium parasites, white blood cells and artifacts. Giemsa stains nuclei, chromatin in blue tone and RBCs in pink color. It has been reported in numerous studies that manual microscopy is not a trustworthy screening technique when performed by nonexperts. Malaria parasites host in RBCs when it enters the bloodstream. This paper presents segmentation of Plasmodium parasite from the thin blood smear points on region growing and dynamic convolution based filtering algorithm. After segmentation, malaria parasite classified into four Plasmodium species: Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, and Plasmodium malaria. The random forest and K‐nearest neighbor are used for classification base on local binary pattern and hue saturation value features. The sensitivity for malaria parasitemia (MP) is 96.75% on training and testing of the proposed approach while specificity is 94.59%. Beside these, the comparisons of the two features are added to the proposed work for classification having sensitivity is 83.60% while having specificity is 94.90% through random forest classifier based on local binary pattern feature.     

Monte Carlo study of ion-induced secondary electron emission from SiO2

Here we describe a recently developed direct Monte Carlo program to study kinetic electron emission from SiO₂ target. The program includes excitation of the target electrons (by projectile ions, recoiling target atoms and fast primary electrons), subsequent transport and escape of these electrons from the target surface. The program can be used to calculate the electron yields, distribution of electron excitation points in the target and other physical parameters of the emitted electrons. In order to demonstrate the capabilities of this program, we report a study on the kinetic electron emission from SiO₂ induced by fast (1-10 keV) rare gas ions. The calculated kinetic electron yield for various ion energies and masses is in good agreement with the predictions of most frequently applied theoretical model. In addition, the effects of projectile energy, mass and impact angle on the depth distribution of electron excitation points and average escape depth of the outgoing electrons were investigated. It is important to mention that the existing experimental techniques are not capable to measure these parameters.     

Micromorphology,pharmacognosy, and bio‐elemental analysis of an important medicinal herb: Verbascum thapsus L.

The present study was conducted on characterization of morpho‐anatomical, phytochemical, and bio‐elemental analysis of root, stem, and leaf of Verbascum thapsus. Morphologically Verbascum is a biennial plant that flowers for a month and a half in mid‐ to late summer. Various organoleptic features of root, leaf, and stem were recorded. Anatomically the T. S of the root, stem, and leaf showed a typical dicot histological differentiation. Leaf possessed anomocytic stomata, crescent shape vascular bundles, and covered with long and stellate type trichomes while, stem contained collateral type of vascular bundles and a well‐developed pith to store phytochemicals responsible for various pharmacological activities. The powder drug study through scanning electron microscopy revealed the presence of various types of tissues. Branched, tree like and stellate trichomes in root and leaf help in absorption and reduce loss of water. These anatomical features are responsible for the survival of the plant as biennial. Four macro elements (Na, K, Ca, and Mg) and seven microelements (Cr, Cu, Fe, Mn, Ni, Zn, and Cd) and their concentrations in ppm were also studied using Atomic Absorption Spectroscopy. Phytochemical screening of methanolic extract showed existence of various secondary metabolites, while mucilage and anthraquinones was not detected. The present study helps to understand the taxonomic identification of the plant based on morpho‐anatomical features and throws the attention of the researchers to carry out the work for developing its various formulations, which can ultimately be beneficial for the human beings as well as animals.     

Systematics study through scanning electron microscopy; a tool for the authentication of herbal drug Mentha suaveolens Ehrh

In all over the world, herbal drugs are usually adulterated with similar species or varieties due to incorrect identification. Most of herbal products devoid purity and quality, therefore an attempt was carried out to identify plant species and authenticate its herbal drug products from Mentha suaveolens. Microscopy tools provide an excellent platform to identify plants at species level. In this study, microscopic and pharmacokinetic parameters of M. suaveolens were observed. Plant species were collected from high diverse areas of Northern Pakistan. Macro and micro‐morphology including palynology and anatomical features were analyzed to study M. suaveolens. Species characteristics were studied, while implementing microscopic techniques for the delimitation and identification of the species. Traditionally Mentha species are used to cure several diseases that is, digestive disorders, respiratory disorders. Micromorphology (stem, leaves, flowers structure, length etc.), palynology (shape, size of pollen etc.), and anatomical characters (types of stomata, epidermal cell shape, and trichomes) were studied. Micromorphology and anatomical characters were of great interest and significance to discuss the taxonomy of the species. Taxonomic characters were studied to characterize and authenticate the species. The aim of the present study is to observe in detail the taxonomic identification of the species in term of morphology, palynology, and foliar epidermal anatomy for the correct identification along with their medicinal uses in the area.     

Lipid‐derived monomer and corresponding bio‐based nanocomposites

Fatty acid based monomer and corresponding hybrid polymer layered silicate nanocomposites have successfully been prepared by using in situ polymerizations. The hybrid materials were prepared by adding different ratios of nanoclay during free radical homopolymerization of 2‐(acryloyloxy)ethyl stearate (AOES) monomer and copolymerization of AOES with styrene. AOES monomer was synthesized by treating stearic acid with 2‐hydroxyethyl acrylate. The formation of AOES monomer, homopolymer and copolymer was confirmed by ¹H NMR spectroscopic analysis. Further analysis and characterization of the nanocomposites were carried out by XRD, transmission electron microscopy, AFM and attenuated total reflectance Fourier transform infrared spectroscopy. TGA of the polymer nanocomposites was also carried out to evaluate their thermal stability, while flammability tests were conducted to investigate the effect of layered silicate on flame retardancy. Nanofiller addition into the polymer matrix substantially improved the thermal properties and fire retardancy of the composites. © 2016 Society of Chemical Industry     

A human-assisted knowledge extraction method for machining operations

This paper deals with a human-assisted knowledge extraction method to extract “if…then…” rules from a small set of machining data. The presented method utilizes both probabilistic reasoning and fuzzy logical reasoning to benefit from the machining data and from the judgment and preference of a machinist. Using the extracted rules, one can determine the values of operational parameters (feed, cutting velocity, etc.) to ensure the desired machining performance (keep surface roughness within the stipulated range (e.g., moderate)). Applying the presented method in a real-life machining knowledge extraction situation and comparing it with the inductive learning based knowledge extraction method (i.e., ID3), the usefulness of the method is demonstrated. As the concept of manufacturing automation is shifting toward “how to support humans by computers”, the presented method provides some valuable hints to the developers of futuristic computer integrated manufacturing systems.     

Predicting Addiction Severity Index (ASI) interviewer severity ratings for a computer-administered ASI.

The Addiction Severity Index (ASI) is a reliable and valid measure of problem severity among addicted patients. Concerns have been raised about the reliability of the Interviewer Severity Rating (ISR), a summary score for each of 7 domains. As part of an effort to build a computer-administered ASI, regression equations were developed to predict the ISR. Repeated resampling of a large dataset, consisting of 1,124 ASIs conducted by trained interviewers, permitted derivation of stable regression equations predicting the ISR for each ASI domain from patients' answers to preselected interview items. The resulting 7 Predicted Severity Ratings (PSRs) were tested on 8, standardized vignettes, with "gold standard," expert-generated ISRs. Reliabilities compared well with those of intensively trained interviewers. The PSRs could provide an alternative to potentially unreliable interviewer ratings, enhancing the ASI's role in treatment planning and treatment matching and make possible a computer-administered version of the ASI. (PsycINFO Database Record (c) 2010 APA, all rights reserved)