Search results for: built up extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3953

Search results for: built up extraction

2243 Polymorphism in Myostatin Gene and Its Association with Growth Traits in Kurdi Sheep of Northern Khorasan

Authors: Masoud Alipanah, Sekineh Akbari, Gholamreza Dashab

Abstract:

Myostatin genes or factor 8 affecting on growth and making differentiation works (GDF8) as a moderator in the development of skeletal muscle inhibitor. If mutations occurs in the coding region of myostatin, alter its inhibitory role and the muscle growth is increased. In this study, blood samples were collected randomly from 60 Kurdish sheep in northern Khorasan and DNA extraction was performed using a modified salt. A fragment 337 bp from exon 3 myostatin gene and-specific primers by using a polymerase chain reaction (PCR) were amplified. In order to detect different forms of an allele at this locus HaeΙΙΙ restriction enzymes and PCR-RFLP analysis were used. Band patterns clarification was performed using agarose gel electrophoresis. The frequency of genotypes mm, Mm, and MM, were respectively detected, 0, 0.15 and 0.85. The allele frequency for alleles m and M, were respectively, 0.07 and 0.93. The statistical analyses indicated that m allele was significantly associated with body weight. The results of this study suggest that the Myostatin gene possibly is a candidate gene that affects growth traits in Kurdish sheep.

Keywords: GDF8 gene, Kurdi Sheep of Northern Khorasan, polymorphism, weight traits

Procedia PDF Downloads 337
2242 Real-Time Recognition of the Terrain Configuration to Improve Driving Stability for Unmanned Robots

Authors: Bongsoo Jeon, Jayoung Kim, Jihong Lee

Abstract:

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor (exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit (IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

Keywords: inertial measurement unit, laser range finder, real-time recognition of the ground shape, proprioceptive sensor

Procedia PDF Downloads 284
2241 Modeling and Simulation of a Hybrid System Solar Panel and Wind Turbine in the Quingeo Heritage Center in Ecuador

Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

Abstract:

In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

Procedia PDF Downloads 263
2240 Characterization of Onion Peels Extracts and Its Utilization in a Deep Fried Snack

Authors: Nabia Siddiqui, Tahira Mohsin Ali, Tanveer Abbas, Abid Hasnain

Abstract:

The present study proposed the use of different onion peel extracts in a South Asian snacks called ‘sew’. The polyphenols extracted from peels were initially analyzed for their antimicrobial potential and bioactive components following three different extraction systems. A relatively higher level of total phenolic content (TP), total flavonoid (TF) and antioxidant activity was observed for EWE (ethanol and water based) extracts followed by EAAE (ethanol and acetic acid) and WE (water extract) sample. Onion extracts showed ability to inhibit gram-positive as well as gram-negative bacteria. The incorporation of onion peel extracts in sew showed a marked increase in bioactive components. Besides bioactivity, sensory attributes, textural characteristics and storage stability of these snacks containing onion peel extract also significantly improved during the shelf study at ambient temperature for up to two months. Thus, these results justify the utilization of these plant polyphenols in fried snacks.

Keywords: onion peels extract, South Asian snacks, antioxidant capacity, bioactivity

Procedia PDF Downloads 236
2239 Flexible Cities: A Multisided Spatial Application of Tracking Livability of Urban Environment

Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

Abstract:

The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

Procedia PDF Downloads 140
2238 A Fuzzy Approach to Liver Tumor Segmentation with Zernike Moments

Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

Procedia PDF Downloads 449
2237 KSVD-SVM Approach for Spontaneous Facial Expression Recognition

Authors: Dawood Al Chanti, Alice Caplier

Abstract:

Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

Procedia PDF Downloads 300
2236 Intrusion Detection System Using Linear Discriminant Analysis

Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

Abstract:

Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

Procedia PDF Downloads 223
2235 Blind Watermarking Using Discrete Wavelet Transform Algorithm with Patchwork

Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

Abstract:

This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

Procedia PDF Downloads 265
2234 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

Procedia PDF Downloads 505
2233 Composite Electrospun Aligned PLGA/Curcumin/Heparin Nanofibrous Membranes for Wound Dressing Application

Authors: Jyh-Ping Chen, Yu-Tin Lai

Abstract:

Wound healing is a complicated process involving overlapping hemostasis, inflammation, proliferation, and maturation phases. Ideal wound dressings can replace native skin functions in full thickness skin wounds through faster healing rate and also by reducing scar formation. Poly(lactic-co-glycolic acid) (PLGA) is an U.S. FDA approved biodegradable polymer to be used as ideal wound dressing material. Several in vitro and in vivo studies have demonstrated the effectiveness of curcumin in decreasing the release of inflammatory cytokines, inhibiting enzymes associated with inflammations, and scavenging free radicals that are the major cause of inflammation during wound healing. Heparin has binding affinities to various growth factors. With the unique and beneficial features offered by those molecules toward the complex process of wound healing, we postulate a composite wound dressing constructed from PLGA, curcumin and heparin would be a good candidate to accelerate scarless wound healing. In this work, we use electrospinning to prepare curcumin-loaded aligned PLGA nanofibrous membranes (PC NFMs). PC NFMs were further subject to oxygen plasma modification and surfaced-grafted with heparin through carbodiimide-mediated covalent bond formation to prepare curcumin-loaded PLGA-g-heparin (PCH) NFMs. The nanofibrous membranes could act as three-dimensional scaffolds to attract fibroblast migration, reduce inflammation, and increase wound-healing related growth factors concentrations at wound sites. From scanning electron microscopy analysis, the nanofibers in each NFM are with diameters ranging from 456 to 479 nm and with alignment angles within  0.5°. The NFMs show high tensile strength and good water absorptivity and provide suitable pore size for nutrients/wastes transport. Exposure of human dermal fibroblasts to the extraction medium of PC or PCH NFM showed significant protective effects against hydrogen peroxide than PLGA NFM. In vitro wound healing assays also showed that the extraction medium of PCH NFM showed significantly better migration ability toward fibroblasts than PC NFM, which is further better than PLGA NFM. The in vivo healing efficiency of the NFMs was further evaluated by a full thickness excisional wound healing diabetic rat model. After 14 days, PCH NFMs exhibits 86% wound closure rate, which is significantly different from other groups (79% for PC and 73% for PLGA NFM). Real-time PCR analysis indicated PC and PCH NFMs down regulated anti-oxidative enzymes like glutathione peroxidase (GPx) and superoxide dismutase (SOD), which are well-known transcription factors involved in cellular inflammatory responses to stimuli. From histology, the wound area treated with PCH NFMs showed more vascular lumen formation from immunohistochemistry of α-smooth muscle actin. The wound site also had more collagen type III (65.8%) expression and less collagen type I (3.5%) expression, indicating scar-less wound healing. From Western blot analysis, the PCH NFM showed good affinity toward growth factors from increased concentration of transforming growth factor-β (TGF-β) and fibroblast growth factor-2 (FGF-2) at the wound site to accelerate wound healing. From the results, we suggest PCH NFM as a promising candidate for wound dressing applications.

Keywords: Curcumin, heparin, nanofibrous membrane, poly(lactic-co-glycolic acid) (PLGA), wound dressing

Procedia PDF Downloads 153
2232 Building an Integrated Relational Database from Swiss Nutrition National Survey and Swiss Health Datasets for Data Mining Purposes

Authors: Ilona Mewes, Helena Jenzer, Farshideh Einsele

Abstract:

Objective: The objective of the study was to integrate two big databases from Swiss nutrition national survey (menuCH) and Swiss health national survey 2012 for data mining purposes. Each database has a demographic base data. An integrated Swiss database is built to later discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption. Design: Swiss nutrition national survey (menuCH) with approx. 2000 respondents from two different surveys, one by Phone and the other by questionnaire along with Swiss health national survey 2012 with 21500 respondents were pre-processed, cleaned and finally integrated to a unique relational database. Results: The result of this study is an integrated relational database from the Swiss nutritional and health databases.

Keywords: health informatics, data mining, nutritional and health databases, nutritional and chronical databases

Procedia PDF Downloads 108
2231 EduEasy: Smart Learning Assistant System

Authors: A. Karunasena, P. Bandara, J. A. T. P. Jayasuriya, P. D. Gallage, J. M. S. D. Jayasundara, L. A. P. Y. P. Nuwanjaya

Abstract:

Usage of smart learning concepts has increased rapidly all over the world recently as better teaching and learning methods. Most educational institutes such as universities are experimenting those concepts with their students. Smart learning concepts are especially useful for students to learn better in large classes. In large classes, the lecture method is the most popular method of teaching. In the lecture method, the lecturer presents the content mostly using lecture slides, and the students make their own notes based on the content presented. However, some students may find difficulties with the above method due to various issues such as speed in delivery. The purpose of this research is to assist students in large classes in the following content. The research proposes a solution with four components, namely note-taker, slide matcher, reference finder, and question presenter, which are helpful for the students to obtain a summarized version of the lecture note, easily navigate to the content and find resources, and revise content using questions.

Keywords: automatic summarization, extractive text summarization, speech recognition library, sentence extraction, automatic web search, automatic question generator, sentence scoring, the term weight

Procedia PDF Downloads 141
2230 Preconcentration and Determination of Cyproheptadine in Biological Samples by Hollow Fiber Liquid Phase Microextraction Coupled with High Performance Liquid Chromatography

Authors: Sh. Najari Moghadam, M. Qomi, F. Raofie, J. Khadiv

Abstract:

In this study, a liquid phase microextraction by hollow fiber (HF-LPME) combined with high performance liquid chromatography-UV detector was applied to preconcentrate and determine trace levels of Cyproheptadine in human urine and plasma samples. Cyproheptadine was extracted from 10 mL alkaline aqueous solution (pH: 9.81) into an organic solvent (n-octnol) which was immobilized in the wall pores of a hollow fiber. Then, it was back-extracted into an acidified aqueous solution (pH: 2.59) located inside the lumen of the hollow fiber. This method is simple, efficient and cost-effective. It is based on pH gradient and differences between two aqueous phases. In order to optimize the HF-LPME, some affecting parameters including the pH of donor and acceptor phases, the type of organic solvent, ionic strength, stirring rate, extraction time and temperature were studied and optimized. Under optimal conditions enrichment factor, limit of detection (LOD) and relative standard deviation (RSD(%), n=3) were up to 112, 15 μg.L−1 and 2.7, respectively.

Keywords: biological samples, cyproheptadine, hollow fiber, liquid phase microextraction

Procedia PDF Downloads 281
2229 Quantifying Product Impacts on Biodiversity: The Product Biodiversity Footprint

Authors: Leveque Benjamin, Rabaud Suzanne, Anest Hugo, Catalan Caroline, Neveux Guillaume

Abstract:

Human products consumption is one of the main drivers of biodiversity loss. However, few pertinent ecological indicators regarding product life cycle impact on species and ecosystems have been built. Life cycle assessment (LCA) methodologies are well under way to conceive standardized methods to assess this impact, by taking already partially into account three of the Millennium Ecosystem Assessment pressures (land use, pollutions, climate change). Coupling LCA and ecological data and methods is an emerging challenge to develop a product biodiversity footprint. This approach was tested on three case studies from food processing, textile, and cosmetic industries. It allowed first to improve the environmental relevance of the Potential Disappeared Fraction of species, end-point indicator typically used in life cycle analysis methods, and second to introduce new indicators on overexploitation and invasive species. This type of footprint is a major step in helping companies to identify their impacts on biodiversity and to propose potential improvements.

Keywords: biodiversity, companies, footprint, life cycle assessment, products

Procedia PDF Downloads 321
2228 Isolation of Antimicrobial Compounds from Marine Sponge Neopetrosia exigua

Authors: Haitham Qaralleh, Syed Z. Idid, Shahbudin Saad, Deny Susanti, Osama Althunibat

Abstract:

This study was carried out to isolate the active antimicrobial compounds from Neopetrosia exigua using bio-guided assay isolation against Staphylococcus aureus. N. exigua was extracted using methanol and subjected to liquid-liquid extraction using solvents with different polarity (n-hexane, carbon tetrachloride, dichloromethane, n-butanol and water). Purification of the active components of n-butanol and dichloromethane fractions was done using Sephadex LH-20 and reverse phase chromatography. Based on the biological guided fractionation results, dichloromethane and n-butanol fractions showed the highest antimicrobial activity. Purification of the active components of n-butanol and dichloromethane fractions yielded three compounds. The structure of the isolated compounds were elucidated and found to be 5-hydroxy-1H-indole-3-carboxylic acid methyl ester, cyclo-1`-demethylcystalgerone and avarol derivative. Avarol was showed potent bactericidal effect against S. aureus. N. exigua appears to be rich source of natural antimicrobial agents. Further studies are needed to investigate the mode of action of these compounds.

Keywords: antimicrobial, avarol, Neopetrosia exigua, Staphylococcus aureus

Procedia PDF Downloads 429
2227 The Effect of Smart-Nano Materials in Thermal Retrofit of Healthcare Envelope Layout in Desert Climate: A Case Study on Semnan

Authors: Foroozan Sadri, Mohammadmehdi Moulaii, Farkhondeh Vahdati

Abstract:

Smart materials can create a great revolution in our built environment, as living systems do. In this research, the optimal structure of healthcare building envelopes is analyzed in terms of thickness according to the utility of the smart-nano materials as nontoxic substances in the region. The research method in this paper is based on library studies and simulation. Grasshopper program is employed to simulate thermal characteristics to achieve the optimum U-value in Semnan desert climate, according to Iranian national standards. The potential of healthcare envelope layouts in thermal properties development (primarily U-value) of these buildings is discussed due to the high thermal loads of healthcare buildings and also toxicity effects of conventional materials. As a result, envelope thicknesses are calculated, and the performance of the nano-PCM and gypsum wallboards are compared. A solution with comparable performance using smart-nano materials instead of conventional materials would determine a decrease in wall thickness.

Keywords: energy saving, exterior envelope, smart-nano materials, thermal performance, U-value

Procedia PDF Downloads 165
2226 Dietary Gluten and the Balance of Gut Microbiota in the Dextran Sulphate Sodium Induced Colitis Model

Authors: Austin Belfiori, Kevin Rinek, Zach Barcroft, Jennifer Berglind

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Diet influences the composition of the gut microbiota and host's health. Disruption of the balance among the microbiota, epithelial cells, and resident immune cells in the intestine is involved in the pathogenesis of inflammatory bowel disease (IBD). To study the role of gut microbiota in intestinal inflammation, the microbiome of control mice (C57BL6) given a gluten-containing standard diet versus C57BL6 mice given the gluten-free (GF) feed (n=10 in each group) was examined. All mice received the 3% DSS for 5 days. Throughout the study, feces were collected and processed for DNA extraction and MiSeq Illumina sequencing of V4 region of bacterial 16S rRNA gene. Alpha and beta diversities and compositional differences at phylum and genus levels were determined in intestinal microbiota. The mice receiving the GF diet showed a significantly increased abundance of Firmicutes and a decrease of Bacteroides and Lactobacillus at phylum level. Therefore, the gluten free diet led to reductions in beneficial gut bacteria populations. These findings indicate a role of wheat gluten in dysbiosis of the intestinal microbiota.

Keywords: gluten, colitis, microbiota, DSS, dextran sulphate sodium

Procedia PDF Downloads 207
2225 Coastal Erosion Control Alternatives with Geosynthetics: Study Case of Ponta Negra Beach, Natal, Brazil

Authors: M. A. Medeiros, A. A. N. Dantas, F. A. N. França, R. F. Amaral

Abstract:

There are several alternatives of coastal erosion control with geosynthetics. As an important stage of any Civil Engineering project, literature review is necessary in order to evaluate these alternatives and to guide the decisions. Ponta Negra beachfront has a very intensive urban pressure. In addition, a very short sand area induces high intensity erosion processes. Different attempts of solving the problem were already built. However, erosion issues are still an important concern since these structures collapsed. Geosynthetics present a great potential to be applied in this area. In order to study coastal erosion control alternatives with the use of geosynthetics, this paper presents a literature review about this subject. Several studies were collected in which beach conditions are similar to those found in Ponta Negra beach. It was possible to evaluate the alternatives that might be used in the area. Further studies include the application of such techniques in pilot areas and the evaluation of the erosion process. Finally, the best alternative for futures studies on Ponta Negra beach is geocontainers of geotextiles.

Keywords: geosynthetics, coastal erosion control, alternatives, Ponta Negra beach

Procedia PDF Downloads 147
2224 Identification and Characterization of Nuclear Envelope Protein Interactions

Authors: Mohammed Hakim Jafferali, Balaje Vijayaraghavan, Ricardo A. Figueroa, Ellinor Crafoord, Veronica J. Larsson, Einar Hallberg, Santhosh Gudise

Abstract:

The nuclear envelope which surrounds the chromatin of eukaryotic cells contains more than a hundred transmembrane proteins. Mutations in some genes encoding nuclear envelope proteins give rise to human diseases including neurological disorders. The function of many nuclear envelope proteins is not well established. This is partly because nuclear envelope proteins and their interactions are difficult to study due to the inherent resistance to extraction of nuclear envelope proteins. We have developed a novel method called MCLIP, to identify interacting partners of nuclear envelope proteins in live cells. Using MCLIP, we found three new binding partners of the inner nuclear membrane protein Samp1: the intermediate filament protein Lamin B1, the LINC complex protein Sun1 and the G-protein Ran. Furthermore, using in vitro studies, we show that Samp1 binds both Emerin and Ran directly. We have also studied the interaction between Samp1 and Ran in detail. The results show that the Samp1 binds stronger to RanGTP than RanGDP. Samp1 is the first transmembrane protein known to bind Ran and it is tempting to speculate that Samp1 may provide local binding sites for RanGTP at membranes.

Keywords: MCLIP, nuclear envelope, ran, Samp1

Procedia PDF Downloads 349
2223 Contrast Enhancement of Color Images with Color Morphing Approach

Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

Abstract:

Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

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2222 The Antimicrobial Activity of the Essential Oil of Salvia officinalis Harvested in Boumerdes

Authors: N. Mezıou-Cheboutı, A. Merabet, N. Behidj, F. Z. Bissaad

Abstract:

The Algeria by its location, offers a rich and diverse vegetation. A large number of aromatic and medicinal plants grow spontaneously. The interest in these plants has continued to grow in recent years. Their particular properties due to the essential oil fraction can be utilized to treat microbial infections. To this end, and in the context of the valuation of the Algerian flora, we became interested in the species of the family Lamiaceae which is one of the most used as a global source of spices and extracts strong families antimicrobial potency. The plant on which we have based our choice is a species of sage "Salvia officinalis" from the Isser localized region within the province of Boumerdes. This work focuses on the study of the antimicrobial activity of essential oil extracted from the leaves of salvia officinalis. The extraction is carried out by HE hydrodistillation and reveals a yield of 1.06℅. The study of the antimicrobial activity of the essential oil by the method of at aromatogramme shown that Gram positive bacteria are most susceptible (Staphylococcus aureus and Bacillus subtilis) with a strong inhibition of growth. The yeast Candida albicans fungus Aspergillus niger and have shown moderately sensitive.

Keywords: Salvia officinalis, steam distillation, essential oil, aromatogram, anti-microbial activity

Procedia PDF Downloads 313
2221 A Greedy Alignment Algorithm Supporting Medication Reconciliation

Authors: David Tresner-Kirsch

Abstract:

Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

Procedia PDF Downloads 280
2220 KCBA, A Method for Feature Extraction of Colonoscopy Images

Authors: Vahid Bayrami Rad

Abstract:

In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

Procedia PDF Downloads 49
2219 Mentorship and Feelings of Identify and Self-Efficacy in Women Returning to the Workforce after an Extended Child-Rearing Leave

Authors: Jacquelyn Irene Eidson

Abstract:

Women who leave the workforce due to motherhood and wish to return are a valuable, untapped resource for organizations. Levinson’s theory of adult development defines life as a sequence of transitions requiring difficult decisions that prompt humans to question their identity and their self-efficacy. The experience of being a working mother and the experience of workplace mentorship have received extensive research attention. Merging the two experiences and focusing on feelings of identity and self-efficacy provides a unique and focused opportunity for learning. Through one-on-one interviews and focus group discussion with working mothers that had previously left the workforce for an extended leave due to child-rearing, a meaningful description of their experiences will be obtained. Data is currently being collected via a collaboration with state banking associations in the United States. Results from the study will enable organizations worldwide to more effectively provide mentorship opportunities built around a culture of understanding while more effectively recruiting, supporting, developing, and retaining this valuable talent pool.

Keywords: identity, mentorship, self-efficacy, working mother

Procedia PDF Downloads 189
2218 Excavations in the Maadi Area Maadi-West the Stone House

Authors: Mohamed Bekheit Gad Khaleil

Abstract:

The Maadi was a civilization .It is considered one of the oldest civilizations in the world and an area of prehistoric times, especially the civilization (Nakada 1&2 ) It contains the oldest stone house in the history. Many excavations have been done in this area. This report was prepared under my supervision and in cooperation with the German institute .The stone building was redocumented, photographed and drawn once again . The stone building has been built carefully. The measurements for this building are (8m x 4m).and the depth of this building is 2m underground and an entrance located at the eastern part of the northern wall and it has three huge pits in the middle of the building seem to have contained wooden posts, most probably to support the roof. The use of the building is unclear. Circular impressions in front of the north wall and in the south-eastern part of the floor indicate that much of it was a storehouse for numerous vessels such as unique feature may have not only served for private domestic purposes. Before starting work in any site, instruction must be followed :- 1-Gather as much information about this place as possible . (Historical background - previous excavations - maps - pictures) 2-Writing, recording, describing and documenting 3- Draw a map of the site showing the place’s division system (trenches) 4- Safe ( Workers & The Place )

Keywords: photographing, excavations, documentation, registration

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2217 Effect of Water Activity, Temperature, and Incubation Time on Growth and Ochratoxin a Production by Aspergillus fresenii and Aspergillus sulphureus on Niger Seeds

Authors: Yung-Chen Hsu, Juan Hernandez, W. T. Evert Ting, Dawit Gizachew

Abstract:

Mycotoxin contamination of foods and feeds poses a high risk for human and animal health. Ochratoxin A (OTA) is a ubiquitous mycotoxin produced by Aspergillus and Penicillium fungi. It exhibits nephrotoxicity, teratogenicity, mutagenicity, and immunotoxicity in both humans and animals. OTA has been detected in foods such as cereals, coffee, grapes, cocoa, wine, and spices. Consumption of food contaminated with OTA has been linked to kidney and liver diseases. Niger (Guizotia abyssinica) is an oil seed that is used for extracting cooking oil in countries like Ethiopia and India. The seed cake (a byproduct from oil extraction) is also used as dairy cattle feed in Ethiopia. It is also exported to North America and Europe to be used mainly as bird feed. To our knowledge, there have been no studies on the growth and production of OTA on niger seeds. In this study, the environment conditions that support OTA production including effects of water activity, temperature, and incubation time on growth and OTA production by A. fresenii and A. sulphureus were investigated.

Keywords: mycotoxin, ochratoxin A, aspergillus, niger seed

Procedia PDF Downloads 363
2216 Generating Insights from Data Using a Hybrid Approach

Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

Abstract:

Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

Procedia PDF Downloads 109
2215 Agricultural Solid Wastes Generation in Nigeria and Their Recycling Potentials into Building Materials

Authors: Usman Aliyu Jalam, Shuaibu Alolo Sumaila, Sa’adiya Iliyasu Muhammed

Abstract:

Modern building industry lays much emphasis on sophisticated materials that have high embodied energy with intrinsic distinctiveness for damaging the environment. But today, advances in solid waste management have resulted in alternative building materials as partial or complete replacement of the conventional materials like cement, aggregate etc particularly for low cost housing. Investigations carried out revealed that an estimated 18.0 million tonnes of agricultural solid wastes are being generated in Nigeria annually. This constitutes a problem not only to the natural environment but also to the built environment more particularly with the way the wastes are being dispose of. The paper has discussed the present status on the generation and utilisation of agricultural solid wastes, their recycling potentials and environmental implications. It further discovered that although considerable quantity of these wastes were found to have the potentials of being recycled as building materials, the availability of the appropriate technology remains a big challenge in the country. Moreover, majority of the wastes type have gained popularity as fuel. As such, the economic and environmental benefits of recycling the wastes and the use of the wastes as fuel need further investigation.

Keywords: agricultural waste, building, environment, materials, Nigeria

Procedia PDF Downloads 394
2214 Intelligent Semi-Active Suspension Control of a Electric Model Vehicle System

Authors: Shiuh-Jer Huang, Yun-Han Yeh

Abstract:

A four-wheel drive electric vehicle was built with hub DC motors and FPGA embedded control structure. A 40 steps manual adjusting motorcycle shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. An intelligent fuzzy logic controller was proposed to real-time search appropriate damping ratio based on vehicle running condition. Then, a robust fuzzy sliding mode controller (FSMC) is employed to regulate the target damping ratio of each wheel axis semi-active suspension system. Finally, different road surface conditions are chosen to evaluate the control performance of this semi-active suspension and compare with that of passive system based on wheel axis acceleration signal.

Keywords: acceleration, FPGA, Fuzzy sliding mode control, semi-active suspension

Procedia PDF Downloads 410