REVIEW ARTICLE:Future of Lead Chelation Distribution and Treatment

Lead is the major environmental toxin resulting in the ill health and deleterious effect on almost all organs in the human body in a slow and effective manner. The best treatment for lead poisoning is chelation therapy which is next only to prevention. The authors describe the disruption of homeostasis of the human body by lead in various tissues like blood, bones, liver, kidneys and brain; and the ability of lead to enter the cell using calcium channels and calcium receptors like Ca++ dependant K+ ion channels, transient receptor potential channels, T-tubules, calmodulin receptors, inositol trisphosphate receptors and ryanodine receptors. We report a few novel chelating agents like ionophores, decadentate ligands, picolinate ligands, octadentate ligand, allicin, thiamine, that show good potential for being used in chelation therapy. Future of leadpoisoning is a challenge to all and it needs to be meticulously studies to have an economic and health approach

Teaching Syntactic Functions of words through Differentiated Instruction to College students

Differentiated Instruction is basically an action between which teachers increase studying by going with college students signalizes to instruction and estimation. It means various instructional strategies that address various students' learning needs. The College students come to college with a large variety of background knowledge, language and past schooling experience with the individual difference. The Students are expected to learn the syntactic functions of words. This research paper is to investigate the benefits of introducing differentiated education. It helps to mobilize inservice teachers, enhance their presentation and encourage positive point of view and beliefs among apprentice and tutors in higher education

Effect of Interventional Strategies to Learn Geometry- A comparative study

Mathematics is an excellent tool for developing mental discipline and for encouraging logical thinking and mental rigor. Statistics indicate that the difficulty of teaching and mastering mathematics, and geometry, in particular, has led to widespread test failure. Teachers utilize various instructional strategies to help students to focus their attention, for better comprehension and retention and to monitor and evaluate learning. The present study was done to examine the efficacy of two strategies in comparison with the with conventional (chalk and talk) method of teaching Geometry. The two experimental Intervention Strategies were (a) use of Power Point presentation (hereinafter termed as PPT) and use of Paper Folding. The study was done on one hundred and five (N=105) students of class VI in a rural Government Higher Secondary School, Coimbatore. The students were randomly assigned to three groups viz., two Experimental groups namely the (a)Power Point Group and (b) Paper Folding group (n=35) each and Conventional Group (hereinafter termed as Chalk and Talk Group, n=35) as the control group. Based on a test of Geometry, developed from the curriculum, the data was collected prior and after the Intervention for both the Groups (two Experimental groups and control). The results of descriptive statistics, Paired sample t -test and ANOVA showed that there was no significant improvement in learning Geometry in control Group whereas significant improvement in scores was found in the Paper Folding Intervention Group than the PPT Intervention Group. The comparison between the instructional strategies also showed that Paper Folding as the Instructional Strategy improved the scores in the evaluation test than the PPT and Chalk and Talk Method. The study concludes that Paper folding as an instructional strategy is highly recommended for teaching Geometry for Students of High School

Incremental dimension reduction of tensors with random index

We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure

Machine Learning based Early Stage Identification of Liver Tumor using Ultrasound Images

Liver cancer is one of the most malignant diseases and its diagnosis requires more computational time. It can be minimized by applying a Machine learning algorithm for the diagnosis of cancer. The existing machine learning technique uses only the color-based methods to classify images which are not efficient. So, it is proposed to use texture-based classification for diagnosis. The input image is resized and pre-processed by Gaussian filters. The features are extracted by applying Gray level co-occurrence matrix (GLCM) and Local binary pattern (LBP in the preprocessed image. The Local Binary Pattern (LBP) is an efficient texture operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. The extracted features are classified by multi-support vector machine (Multi SVM) and K-Nearest Neighbor (K-NN) algorithms. The Advantage of combining SVM with KNN is that SVM measures a large number of values whereas KNN accurately measures point values. The results obtained from the proposed techniques achieved high precision, accuracy, sensitivity and specificity than the existing method

Effect of land configuration and methods of establishment on pearl millet (Pennisetum glaucam)

The present study examines the impact of land configuration and establishment methods on the growth and productivity of pearl millet. The experiment was conducted using a split-plot design with three main plot treatments, flatbed planting (M1), ridges and furrows (M2) and raised bed paired row planting (M3) and four subplot treatments: direct sowing (S1), 10- day-old seedlings (DOS) (S2), 15 DOS (dapog) (S3) and 20 DOS (S4). Each treatment combination was replicated three times. The results revealed that among the main plot treatments, ridges and furrows (M2) demonstrated superior performance exhibiting greater plant height, a higher total number of tillers, and increased dry matter production (DMP) at harvest. In subplot treatments, direct sowing (S1) resulted in better growth parameters, including greater plant height, higher DMP at harvest, and improved indices such as Leaf Area Index (LAI), Crop Growth Rate (CGR), Relative Growth Rate (RGR) and Net Assimilation Rate (NAR). In contrast, the 20 DOS in raised bed paired row planting (M3) recorded the shortest time to heading and 50% flowering. Among the treatment combinations, direct sowing in ridges and furrows (M2S1) achieved the highest plant height, maximum DMP at harvest and superior grain and straw yield

Mineral composition of some selected brown seaweeds from Mandapam region of Gulf of Mannar, Tamil Nadu

63-66Mineral content was determined in different brown seaweeds (Sargassum wightii, Padina tetrastromatica, Chnoospora minima, Hormophysa triquetra, Sargassum myriocystum, Sargassum plagiophyllum and Sargassum ilicifolium), collected from Mandapam region (Gulf of Mannar), Southeast coast of India. The ash content of different seaweeds ranged from 15 % to 20.5 %. The ash values were significantly different among the seaweeds (P˂ 0.05). The selected brown seaweeds contained both macro elements (0.77-564.5 mg/100g; Na, K, Ca, Mg) and trace elements (0.1-4.83 mg/100g; Zn, Mn, Fe, Cu). The present study was carried out in some of the underutilized brown seaweeds and it was concluded that the selected species can be used as feed additives in future.</span

New generalized fuzzy metrics and fixed point theorem in fuzzy metric space

In this paper, in fuzzy metric spaces (in the sense of Kramosil and Michalek (Kibernetika 11:336-344, 1957)) we introduce the concept of a generalized fuzzy metric which is the extension of a fuzzy metric. First, inspired by the ideas of Grabiec (Fuzzy Sets Syst. 125:385-389, 1989), we define a new G-contraction of Banach type with respect to this generalized fuzzy metric, which is a generalization of the contraction of Banach type (introduced by M Grabiec). Next, inspired by the ideas of Gregori and Sapena (Fuzzy Sets Syst. 125:245-252, 2002), we define a new GV-contraction of Banach type with respect to this generalized fuzzy metric, which is a generalization of the contraction of Banach type (introduced by V Gregori and A Sapena). Moreover, we provide the condition guaranteeing the existence of a fixed point for these single-valued contractions. Next, we show that the generalized pseudodistance J:X×X→[0,∞) (introduced by Włodarczyk and Plebaniak (Appl. Math. Lett. 24:325-328, 2011)) may generate some generalized fuzzy metric NJ on X. The paper includes also the comparison of our results with those existing in the literature

A Study to assess the effectiveness of structured teaching program on awareness of quality of life among elderly cardiac patients in GKNM Hospital, Coimbatore

STATEMENT OF THE PROBLEM: A Study to Assess the Effectiveness of Structured Teaching Program on the Awareness of Quality Of Life among Elderly Cardiac Patients at G.K.N.M Hospital, Coimbatore. OBJECTIVES: 1. To assess the quality of life of elderly cardiac patients. 2. To assess the effectiveness of structured teaching program. 3. To find the association between the pre- test level of scores and selected demographic variables. Research Design: Pre- Experimental, One Group pre-test post-test design. Settings: Cardiac and Cardio – Thoracic Out-Patient Departments and Master Health Department, GKNM Hospital. Conceptual Framework: The modified Imogene King’s Goal Attainment Model was used. Samples: 40 elderly cardiac patients. Sampling Technique: Non-Probability Convenient Sampling Technique. METHODOLOGY: A self-instructional module was used to collect the data. The pre-test level of awareness on quality of life was assessed using modified WHOQOLBREF scale and a structured teaching for about 30 minutes regarding, exercise, nutrition, sleep, medication safety, alternatives ways to alleviate pain, skin protection, social wellness, cognitive well- being, psychological well- being, emotional health, safety measures and environmental health was given on an individual basis, and the post-test was collected on the next consequent visit by using the same questionnaire. RESULTS: Descriptive and inferential statistics were used to analyze the data and the results showed that there was a significant difference between the pre-test and the post-test level of awareness on quality of life. The overall mean difference was 36.15. the awareness on quality of life was tested by paired ‘t’ test and the results were highly significant at ‘t’ < 0.05. These findings indicated that the Structured Teaching Program was effective in creating awareness on quality of life among elderly cardiac patients. CONCLUSION: The findings of the study revealed that the elderly cardiac patients receiving the structured teaching program had a better awareness on quality of life. Hence this teaching program can be implemented by the nurses in cardiac and cardio-thoracic and master health departments, on a regular basis

Iterative Vessel Segmentation with Stopping Criterion for Fundus Imagery

Vessel segmentation in fundus images plays vital role in diagnosing and treating patients in Ophthalmology. This proposed vessel segmentation algorithm consists of three stages to improve the lower contrast fundus images includes enhancement followed by thresholding and segmentation. Adaptive histogram equalization method is used to enhance the input image. From the enhanced image the major vessel are extracted by thresholding using gray thresh method. The new vessel pixels are identified iteratively using region growing method in which a new stopping criterion is introduced to improve the accuracy. The proposed method outperforms than the existing method of iterative vessel segmentation which achieves 3% greater in accuracy. &nbsp