Evaluation of the application of ERTS-1 data to the regional land use planning process. [Northeast Wisconsin

NASA Technical Reports Server (NTRS)

Clapp, J. L. (Principal Investigator); Green, T., III; Hanson, G. F.; Kiefer, R. W.; Niemann, B. J., Jr.

1974-01-01

The author has identified the following significant results. Employing simple and economical extraction methods, ERTS can provide valuable data to the planners at the state or regional level with a frequency never before possible. Interactive computer methods of working directly with ERTS digital information show much promise for providing land use information at a more specific level, since the data format production rate of ERTS justifies improved methods of analysis.

A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

PubMed

Gao, Yingbin; Kong, Xiangyu; Zhang, Huihui; Hou, Li'an

2017-05-01

Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is proposed for searching the optimum solution of a linear neural network. This information criterion exhibits a unique global minimum attained if and only if the state matrix is composed of the desired MCs of an autocorrelation matrix of an input signal. By using gradient ascent method and recursive least square (RLS) method, two algorithms are developed for multiple MCs extraction. The global convergences of the proposed algorithms are also analyzed by the Lyapunov method. The proposed algorithms can extract the multiple MCs in parallel and has advantage in dealing with high dimension matrices. Since the weighted matrix does not require an accurate value, it facilitates the system design of the proposed algorithms for practical applications. The speed and computation advantages of the proposed algorithms are verified through simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

GDRMS: a system for automatic extraction of the disease-centre relation

NASA Astrophysics Data System (ADS)

Yang, Ronggen; Zhang, Yue; Gong, Lejun

2012-01-01

With the rapidly increasing of biomedical literature, the deluge of new articles is leading to information overload. Extracting the available knowledge from the huge amount of biomedical literature has become a major challenge. GDRMS is developed as a tool that extracts the relationship between disease and gene, gene and gene from biomedical literatures using text mining technology. It is a ruled-based system which also provides disease-centre network visualization, constructs the disease-gene database, and represents a gene engine for understanding the function of the gene. The main focus of GDRMS is to provide a valuable opportunity to explore the relationship between disease and gene for the research community about etiology of disease.

Extracting Inter-business Relationship from World Wide Web

NASA Astrophysics Data System (ADS)

Jin, Yingzi; Matsuo, Yutaka; Ishizuka, Mitsuru

Social relation plays an important role in a real community. Interaction patterns reveal relations among actors (such as persons, groups, companies), which can be merged into valuable information as a network structure. In this paper, we propose a new approach to extract inter-business relationship from the Web. Extraction of relation between a pair of companies is realized by using a search engine and text processing. Since names of companies co-appear coincidentaly on the Web, we propose an advanced algorithm which is characterized by addition of keywords (or we call relation words) to a query. The relation words are obtained from either an annotated corpus or the Web. We show some examples and comprehensive evaluations on our approach.

A Hybrid Human-Computer Approach to the Extraction of Scientific Facts from the Literature.

PubMed

Tchoua, Roselyne B; Chard, Kyle; Audus, Debra; Qin, Jian; de Pablo, Juan; Foster, Ian

2016-01-01

A wealth of valuable data is locked within the millions of research articles published each year. Reading and extracting pertinent information from those articles has become an unmanageable task for scientists. This problem hinders scientific progress by making it hard to build on results buried in literature. Moreover, these data are loosely structured, encoded in manuscripts of various formats, embedded in different content types, and are, in general, not machine accessible. We present a hybrid human-computer solution for semi-automatically extracting scientific facts from literature. This solution combines an automated discovery, download, and extraction phase with a semi-expert crowd assembled from students to extract specific scientific facts. To evaluate our approach we apply it to a challenging molecular engineering scenario, extraction of a polymer property: the Flory-Huggins interaction parameter. We demonstrate useful contributions to a comprehensive database of polymer properties.

On-line object feature extraction for multispectral scene representation

NASA Technical Reports Server (NTRS)

Ghassemian, Hassan; Landgrebe, David

1988-01-01

A new on-line unsupervised object-feature extraction method is presented that reduces the complexity and costs associated with the analysis of the multispectral image data and data transmission, storage, archival and distribution. The ambiguity in the object detection process can be reduced if the spatial dependencies, which exist among the adjacent pixels, are intelligently incorporated into the decision making process. The unity relation was defined that must exist among the pixels of an object. Automatic Multispectral Image Compaction Algorithm (AMICA) uses the within object pixel-feature gradient vector as a valuable contextual information to construct the object's features, which preserve the class separability information within the data. For on-line object extraction the path-hypothesis and the basic mathematical tools for its realization are introduced in terms of a specific similarity measure and adjacency relation. AMICA is applied to several sets of real image data, and the performance and reliability of features is evaluated.

Extraction of microseismic waveforms characteristics prior to rock burst using Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Li, Xuelong; Li, Zhonghui; Wang, Enyuan; Feng, Junjun; Chen, Liang; Li, Nan; Kong, Xiangguo

2016-09-01

This study provides a new research idea concerning rock burst prediction. The characteristics of microseismic (MS) waveforms prior to and during the rock burst were studied through the Hilbert-Huang transform (HHT). In order to demonstrate the advantage of the MS features extraction based on HHT, the conventional analysis method (Fourier transform) was also used to make a comparison. The results show that HHT is simple and reliable, and could extract in-depth information about the characteristics of MS waveforms. About 10 days prior to the rock burst, the main frequency of MS waveforms transforms from the high-frequency to low-frequency. What's more, the waveforms energy also presents accumulation characteristic. Based on our study results, it can be concluded that the MS signals analysis through HHT could provide valuable information about the coal or rock deformation and fracture.

Quantitative evaluation of translational medicine based on scientometric analysis and information extraction.

PubMed

Zhang, Yin; Diao, Tianxi; Wang, Lei

2014-12-01

Designed to advance the two-way translational process between basic research and clinical practice, translational medicine has become one of the most important areas in biomedicine. The quantitative evaluation of translational medicine is valuable for the decision making of global translational medical research and funding. Using the scientometric analysis and information extraction techniques, this study quantitatively analyzed the scientific articles on translational medicine. The results showed that translational medicine had significant scientific output and impact, specific core field and institute, and outstanding academic status and benefit. While it is not considered in this study, the patent data are another important indicators that should be integrated in the relevant research in the future. © 2014 Wiley Periodicals, Inc.

Automated Information Extraction on Treatment and Prognosis for Non-Small Cell Lung Cancer Radiotherapy Patients: Clinical Study.

PubMed

Zheng, Shuai; Jabbour, Salma K; O'Reilly, Shannon E; Lu, James J; Dong, Lihua; Ding, Lijuan; Xiao, Ying; Yue, Ning; Wang, Fusheng; Zou, Wei

2018-02-01

In outcome studies of oncology patients undergoing radiation, researchers extract valuable information from medical records generated before, during, and after radiotherapy visits, such as survival data, toxicities, and complications. Clinical studies rely heavily on these data to correlate the treatment regimen with the prognosis to develop evidence-based radiation therapy paradigms. These data are available mainly in forms of narrative texts or table formats with heterogeneous vocabularies. Manual extraction of the related information from these data can be time consuming and labor intensive, which is not ideal for large studies. The objective of this study was to adapt the interactive information extraction platform Information and Data Extraction using Adaptive Learning (IDEAL-X) to extract treatment and prognosis data for patients with locally advanced or inoperable non-small cell lung cancer (NSCLC). We transformed patient treatment and prognosis documents into normalized structured forms using the IDEAL-X system for easy data navigation. The adaptive learning and user-customized controlled toxicity vocabularies were applied to extract categorized treatment and prognosis data, so as to generate structured output. In total, we extracted data from 261 treatment and prognosis documents relating to 50 patients, with overall precision and recall more than 93% and 83%, respectively. For toxicity information extractions, which are important to study patient posttreatment side effects and quality of life, the precision and recall achieved 95.7% and 94.5% respectively. The IDEAL-X system is capable of extracting study data regarding NSCLC chemoradiation patients with significant accuracy and effectiveness, and therefore can be used in large-scale radiotherapy clinical data studies. ©Shuai Zheng, Salma K Jabbour, Shannon E O'Reilly, James J Lu, Lihua Dong, Lijuan Ding, Ying Xiao, Ning Yue, Fusheng Wang, Wei Zou. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 01.02.2018.

Extraction of valuable compounds from mangosteen pericarps by hydrothermal assisted sonication

NASA Astrophysics Data System (ADS)

Machmudah, Siti; Lestari, Sarah Duta; Shiddiqi, Qifni Yasa'Ash; Widiyastuti, Winardi, Sugeng; Wahyudiono, Kanda, Hideki; Goto, Motonobu

2015-12-01

Valuable compounds, such as xanthone and phenolic compounds, from mangosteen pericarps was extracted by hydrothermal treatment at temperatures of 120-160 °C and pressures of 5 MPa using batch and semi-batch extractor. This method is a simple and environmentally friendly extraction method requiring no chemicals other than water. Under these conditions, there is possibility for the formation of phenolic compounds from mangosteen pericarps from decomposition of bounds between lignin, cellulose, and hemicellulose via autohydrolysis. In order to increase the amount of extracted valuable compounds, sonication pre-treament was performed prior to the hydrothermal extraction process. 30 min of sonication pre-treatment could increase significantly the amount of xanthone and phenolic compounds mangosteen pericarps extraction. In batch-system, the xanthone recovery approach to 100 % at 160 °C with 30 min sonication pre-treatment for 150 min extraction time. Under semi-batch process, the total phenolic compounds in the extract was 217 mg/g sample at 160 °C with 30 min sonication pre-treatment for 150 min total extraction time. The results revealed that hydrothermal extraction assisted sonication pre-treatment is applicable method for the isolation of polyphenolic compounds from other types of biomass and may lead to an advanced plant biomass components extraction technology.

Extraction of actionable information from crowdsourced disaster data.

PubMed

Kiatpanont, Rungsun; Tanlamai, Uthai; Chongstitvatana, Prabhas

Natural disasters cause enormous damage to countries all over the world. To deal with these common problems, different activities are required for disaster management at each phase of the crisis. There are three groups of activities as follows: (1) make sense of the situation and determine how best to deal with it, (2) deploy the necessary resources, and (3) harmonize as many parties as possible, using the most effective communication channels. Current technological improvements and developments now enable people to act as real-time information sources. As a result, inundation with crowdsourced data poses a real challenge for a disaster manager. The problem is how to extract the valuable information from a gigantic data pool in the shortest possible time so that the information is still useful and actionable. This research proposed an actionable-data-extraction process to deal with the challenge. Twitter was selected as a test case because messages posted on Twitter are publicly available. Hashtag, an easy and very efficient technique, was also used to differentiate information. A quantitative approach to extract useful information from the tweets was supported and verified by interviews with disaster managers from many leading organizations in Thailand to understand their missions. The information classifications extracted from the collected tweets were first performed manually, and then the tweets were used to train a machine learning algorithm to classify future tweets. One particularly useful, significant, and primary section was the request for help category. The support vector machine algorithm was used to validate the results from the extraction process of 13,696 sample tweets, with over 74 percent accuracy. The results confirmed that the machine learning technique could significantly and practically assist with disaster management by dealing with crowdsourced data.

The Identification of Proteoglycans and Glycosaminoglycans in Archaeological Human Bones and Teeth

PubMed Central

Coulson-Thomas, Yvette M.; Coulson-Thomas, Vivien J.; Norton, Andrew L.; Gesteira, Tarsis F.; Cavalheiro, Renan P.; Meneghetti, Maria Cecília Z.; Martins, João R.; Dixon, Ronald A.; Nader, Helena B.

2015-01-01

Bone tissue is mineralized dense connective tissue consisting mainly of a mineral component (hydroxyapatite) and an organic matrix comprised of collagens, non-collagenous proteins and proteoglycans (PGs). Extracellular matrix proteins and PGs bind tightly to hydroxyapatite which would protect these molecules from the destructive effects of temperature and chemical agents after death. DNA and proteins have been successfully extracted from archaeological skeletons from which valuable information has been obtained; however, to date neither PGs nor glycosaminoglycan (GAG) chains have been studied in archaeological skeletons. PGs and GAGs play a major role in bone morphogenesis, homeostasis and degenerative bone disease. The ability to isolate and characterize PG and GAG content from archaeological skeletons would unveil valuable paleontological information. We therefore optimized methods for the extraction of both PGs and GAGs from archaeological human skeletons. PGs and GAGs were successfully extracted from both archaeological human bones and teeth, and characterized by their electrophoretic mobility in agarose gel, degradation by specific enzymes and HPLC. The GAG populations isolated were chondroitin sulfate (CS) and hyaluronic acid (HA). In addition, a CSPG was detected. The localization of CS, HA, three small leucine rich PGs (biglycan, decorin and fibromodulin) and glypican was analyzed in archaeological human bone slices. Staining patterns were different for juvenile and adult bones, whilst adolescent bones had a similar staining pattern to adult bones. The finding that significant quantities of PGs and GAGs persist in archaeological bones and teeth opens novel venues for the field of Paleontology. PMID:26107959

Essential oils (EOs), pressurized liquid extracts (PLE) and carbon dioxide supercritical fluid extracts (SFE-CO2) from Algerian Thymus munbyanus as valuable sources of antioxidants to be used on an industrial level.

PubMed

Bendif, Hamdi; Adouni, Khaoula; Miara, Mohamed Djamel; Baranauskienė, Renata; Kraujalis, Paulius; Venskutonis, Petras Rimantas; Nabavi, Seyed Mohammad; Maggi, Filippo

2018-09-15

The aim of this study was to demonstrate the potential of extracts from Algerian Thymus munbyanus as a valuable source of antioxidants for use on an industrial level. To this end, a study was conducted on the composition and antioxidant activities of essential oils (EOs), pressurized liquid extracts (PLE) and supercritical fluid extracts (SFE-CO 2 ) obtained from Thymus munbyanus subsp. coloratus (TMC) and subsp. munbyanus (TMM). EOs and SFE-CO 2 extracts were analysed by GC-FID and GC×GC-TOFMS revealing significant differences. A successive extraction of the solid SFE-CO 2 residue by PLE extraction with solvents of increasing polarity such as acetone, ethanol and water, was carried out. The extracts were evaluated for total phenolic content by Folin-Ciocalteu assay, while the antioxidant power was assessed by DPPH, FRAP, and ORAC assays. SFE-CO 2 extracts were also analysed for their tocopherol content. The antioxidant activity of PLE extracts was found to be higher than that of SFE-CO 2 extracts, and this increased with solvent polarity (water > ethanol > acetone). Overall, these results support the use of T. munbyanus as a valuable source of substances to be used on an industrial level as preservative agents. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predicate Argument Structure Frames for Modeling Information in Operative Notes

PubMed Central

Wang, Yan; Pakhomov, Serguei; Melton, Genevieve B.

2015-01-01

The rich information about surgical procedures contained in operative notes is a valuable data source for improving the clinical evidence base and clinical research. In this study, we propose a set of Predicate Argument Structure (PAS) frames for surgical action verbs to assist in the creation of an information extraction (IE) system to automatically extract details about the techniques, equipment, and operative steps from operative notes. We created PropBank style PAS frames for the 30 top surgical action verbs based on examination of randomly selected sample sentences from 3,000 Laparoscopic Cholecystectomy notes. To assess completeness of the PAS frames to represent usage of same action verbs, we evaluated the PAS frames created on sample sentences from operative notes of 6 other gastrointestinal surgical procedures. Our results showed that the PAS frames created with one type of surgery can successfully denote the usage of the same verbs in operative notes of broader surgical categories. PMID:23920664

Identification and Progression of Heart Disease Risk Factors in Diabetic Patients from Longitudinal Electronic Health Records.

PubMed

Jonnagaddala, Jitendra; Liaw, Siaw-Teng; Ray, Pradeep; Kumar, Manish; Dai, Hong-Jie; Hsu, Chien-Yeh

2015-01-01

Heart disease is the leading cause of death worldwide. Therefore, assessing the risk of its occurrence is a crucial step in predicting serious cardiac events. Identifying heart disease risk factors and tracking their progression is a preliminary step in heart disease risk assessment. A large number of studies have reported the use of risk factor data collected prospectively. Electronic health record systems are a great resource of the required risk factor data. Unfortunately, most of the valuable information on risk factor data is buried in the form of unstructured clinical notes in electronic health records. In this study, we present an information extraction system to extract related information on heart disease risk factors from unstructured clinical notes using a hybrid approach. The hybrid approach employs both machine learning and rule-based clinical text mining techniques. The developed system achieved an overall microaveraged F-score of 0.8302.

Cancer Imaging Phenomics Software Suite: Application to Brain and Breast Cancer | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The transition of oncologic imaging from its “industrial era” to it is “information era” demands analytical methods that 1) extract information from this data that is clinically and biologically relevant; 2) integrate imaging, clinical, and genomic data via rigorous statistical and computational methodologies in order to derive models valuable for understanding cancer mechanisms, diagnosis, prognostic assessment, response evaluation, and personalized treatment management; 3) are available to the biomedical community for easy use and application, with the aim of understanding, diagnosing, an

Array data extractor (ADE): a LabVIEW program to extract and merge gene array data.

PubMed

Kurtenbach, Stefan; Kurtenbach, Sarah; Zoidl, Georg

2013-12-01

Large data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research. Highly advanced bioinformatics tools have been made available to researchers, but a demand for user-friendly software allowing researchers to quickly extract expression information for multiple genes from multiple studies persists. Here, we present a user-friendly LabVIEW program to automatically extract gene expression data for a list of genes from multiple normalized microarray datasets. Functionality was tested for 288 class A G protein-coupled receptors (GPCRs) and expression data from 12 studies comparing normal and diseased human hearts. Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets. Although existing software allows for complex data analyses, the LabVIEW based program presented here, "Array Data Extractor (ADE)", provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way. Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge.

Extracting the Textual and Temporal Structure of Supercomputing Logs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, S; Singh, I; Chandra, A

2009-05-26

Supercomputers are prone to frequent faults that adversely affect their performance, reliability and functionality. System logs collected on these systems are a valuable resource of information about their operational status and health. However, their massive size, complexity, and lack of standard format makes it difficult to automatically extract information that can be used to improve system management. In this work we propose a novel method to succinctly represent the contents of supercomputing logs, by using textual clustering to automatically find the syntactic structures of log messages. This information is used to automatically classify messages into semantic groups via an onlinemore » clustering algorithm. Further, we describe a methodology for using the temporal proximity between groups of log messages to identify correlated events in the system. We apply our proposed methods to two large, publicly available supercomputing logs and show that our technique features nearly perfect accuracy for online log-classification and extracts meaningful structural and temporal message patterns that can be used to improve the accuracy of other log analysis techniques.« less

Scene text recognition in mobile applications by character descriptor and structure configuration.

PubMed

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

Urban-field land use in southern New England: A first look

NASA Technical Reports Server (NTRS)

Simpson, R. B. (Principal Investigator)

1972-01-01

There are no author-identified significant results in this report. First look evaluation of ERTS-1 multiband imagery for urban-field land use applications revealed a great deal of potentially valuable information. The amount of land use detail which can be extracted confidently from ERTS imagery is encouraging, and the objectives of the proposed project are considered feasible providing timely cloud-free coverage is available.

Natural Language Processing in Radiology: A Systematic Review.

PubMed

Pons, Ewoud; Braun, Loes M M; Hunink, M G Myriam; Kors, Jan A

2016-05-01

Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are stored for communication and documentation of diagnostic imaging, harnessing their potential requires efficient and automated information extraction: they exist mainly as free-text clinical narrative, from which it is a major challenge to obtain structured data. Natural language processing (NLP) provides techniques that aid the conversion of text into a structured representation, and thus enables computers to derive meaning from human (ie, natural language) input. Used on radiology reports, NLP techniques enable automatic identification and extraction of information. By exploring the various purposes for their use, this review examines how radiology benefits from NLP. A systematic literature search identified 67 relevant publications describing NLP methods that support practical applications in radiology. This review takes a close look at the individual studies in terms of tasks (ie, the extracted information), the NLP methodology and tools used, and their application purpose and performance results. Additionally, limitations, future challenges, and requirements for advancing NLP in radiology will be discussed. (©) RSNA, 2016 Online supplemental material is available for this article.

Volume and Value of Big Healthcare Data.

PubMed

Dinov, Ivo D

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions.

Volume and Value of Big Healthcare Data

PubMed Central

Dinov, Ivo D.

2016-01-01

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions. PMID:26998309

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

TextHunter – A User Friendly Tool for Extracting Generic Concepts from Free Text in Clinical Research

PubMed Central

Jackson MSc, Richard G.; Ball, Michael; Patel, Rashmi; Hayes, Richard D.; Dobson, Richard J.B.; Stewart, Robert

2014-01-01

Observational research using data from electronic health records (EHR) is a rapidly growing area, which promises both increased sample size and data richness - therefore unprecedented study power. However, in many medical domains, large amounts of potentially valuable data are contained within the free text clinical narrative. Manually reviewing free text to obtain desired information is an inefficient use of researcher time and skill. Previous work has demonstrated the feasibility of applying Natural Language Processing (NLP) to extract information. However, in real world research environments, the demand for NLP skills outweighs supply, creating a bottleneck in the secondary exploitation of the EHR. To address this, we present TextHunter, a tool for the creation of training data, construction of concept extraction machine learning models and their application to documents. Using confidence thresholds to ensure high precision (>90%), we achieved recall measurements as high as 99% in real world use cases. PMID:25954379

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Time-dependent analysis of dosage delivery information for patient-controlled analgesia services.

PubMed

Kuo, I-Ting; Chang, Kuang-Yi; Juan, De-Fong; Hsu, Steen J; Chan, Chia-Tai; Tsou, Mei-Yung

2018-01-01

Pain relief always plays the essential part of perioperative care and an important role of medical quality improvement. Patient-controlled analgesia (PCA) is a method that allows a patient to self-administer small boluses of analgesic to relieve the subjective pain. PCA logs from the infusion pump consisted of a lot of text messages which record all events during the therapies. The dosage information can be extracted from PCA logs to provide easily understanding features. The analysis of dosage information with time has great help to figure out the variance of a patient's pain relief condition. To explore the trend of pain relief requirement, we developed a PCA dosage information generator (PCA DIG) to extract meaningful messages from PCA logs during the first 48 hours of therapies. PCA dosage information including consumption, delivery, infusion rate, and the ratio between demand and delivery is presented with corresponding values in 4 successive time frames. Time-dependent statistical analysis demonstrated the trends of analgesia requirements decreased gradually along with time. These findings are compatible with clinical observations and further provide valuable information about the strategy to customize postoperative pain management.

Indirect tissue electrophoresis: a new method for analyzing solid tissue protein.

PubMed

Smith, A C

1988-01-01

1. The eye lens core (nucleus) has been a valuable source of molecular biologic information. 2. In these studies, lens nuclei are usually homogenized so that any protein information related to anatomical subdivisions, or layers, of the nucleus is lost. 3. The present report is of a new method, indirect tissue electrophoresis (ITE), which, when applied to fish lens nuclei, permitted (a) automatic correlation of protein information with anatomic layer, (b) production of large, clear electrophoretic patterns even from small tissue samples and (c) detection of more proteins than in liquid extracts of homogenized tissues. 4. ITE seems potentially applicable to a variety of solid tissues.

Current technologies and new insights for the recovery of high valuable compounds from fruits by-products.

PubMed

Ferrentino, Giovanna; Asaduzzaman, Md; Scampicchio, Matteo Mario

2018-02-11

The recovery of high valuable compounds from food waste is becoming a tighten issue in food processing. The large amount of non-edible residues produced by food industries causes pollution, difficulties in the management, and economic loss. The waste produced during the transformation of fruits includes a huge amount of materials such as peels, seeds, and bagasse, whose disposal usually represents a problem. Research over the past 20 years revealed that many food wastes could serve as a source of potentially valuable bioactive compounds, such as antioxidants and vitamins with increasing scientific interest thanks to their beneficial effects on human health. The challenge for the recovery of these compounds is to find the most appropriate and environment friendly extraction technique able to achieve the maximum extraction yield without compromising the stability of the extracted products. Based on this scenario, the aim of the current review is twofold. The first is to give a brief overview of the most important bioactive compounds occurring in fruit wastes. The second is to describe the pro and cons of the most up-to-dated innovative and environment friendly extraction technologies that can be an alternative to the classical solvent extraction procedures for the recovery of valuable compounds from fruit processing. Furthermore, a final section will take into account published findings on the combination of some of these technologies to increase the extracts yields of bioactives.

A SOAP Web Service for accessing MODIS land product subsets

DOE Office of Scientific and Technical Information (OSTI.GOV)

SanthanaVannan, Suresh K; Cook, Robert B; Pan, Jerry Yun

2011-01-01

Remote sensing data from satellites have provided valuable information on the state of the earth for several decades. Since March 2000, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board NASA s Terra and Aqua satellites have been providing estimates of several land parameters useful in understanding earth system processes at global, continental, and regional scales. However, the HDF-EOS file format, specialized software needed to process the HDF-EOS files, data volume, and the high spatial and temporal resolution of MODIS data make it difficult for users wanting to extract small but valuable amounts of information from the MODIS record. Tomore » overcome this usability issue, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemical Dynamics at Oak Ridge National Laboratory (ORNL) developed a Web service that provides subsets of MODIS land products using Simple Object Access Protocol (SOAP). The ORNL DAAC MODIS subsetting Web service is a unique way of serving satellite data that exploits a fairly established and popular Internet protocol to allow users access to massive amounts of remote sensing data. The Web service provides MODIS land product subsets up to 201 x 201 km in a non-proprietary comma delimited text file format. Users can programmatically query the Web service to extract MODIS land parameters for real time data integration into models, decision support tools or connect to workflow software. Information regarding the MODIS SOAP subsetting Web service is available on the World Wide Web (WWW) at http://daac.ornl.gov/modiswebservice.« less

Mining biomedical images towards valuable information retrieval in biomedical and life sciences

PubMed Central

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. PMID:27538578

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

Smart Health - Potential and Pathways: A Survey

NASA Astrophysics Data System (ADS)

Arulananthan, C.; Hanifa, Sabibullah Mohamed

2017-08-01

Healthcare is an imperative key field of research, where individuals or groups can be engaged in the self-tracking of any kind of biological, physical, behavioral, or environmental information. In a massive health care data, the valuable information is hidden. The quantity of the available unstructured data has been expanding on an exponential scale. The newly developing Disruptive Technologies can handle many challenges that face data analysis and ability to extract valuable information via data analytics. Connected Wellness in Healthcare would retrieve patient’s physiological, pathological and behavioral parameters through sensors to perform inner workings of human body analysis. Disruptive technologies can take us from a reactive illness-driven to a proactive wellness-driven system in health care. It is need to be strive and create a smart health system towards wellness-driven instead of being illness-driven, today’s biggest problem in health care. Wellness-driven-analytics application help to promote healthiest living environment called “Smart Health”, deliver empower based quality of living. The contributions of this survey reveals and opens (touches uncovered areas) the possible doors in the line of research on smart health and its computing technologies.

Project X: competitive intelligence data mining and analysis

NASA Astrophysics Data System (ADS)

Gilmore, John F.; Pagels, Michael A.; Palk, Justin

2001-03-01

Competitive Intelligence (CI) is a systematic and ethical program for gathering and analyzing information about your competitors' activities and general business trends to further your own company's goals. CI allows companies to gather extensive information on their competitors and to analyze what the competition is doing in order to maintain or gain a competitive edge. In commercial business this potentially translates into millions of dollars in annual savings or losses. The Internet provides an overwhelming portal of information for CI analysis. The problem is how a company can automate the translation of voluminous information into valuable and actionable knowledge. This paper describes Project X, an agent-based data mining system specifically developed for extracting and analyzing competitive information from the Internet. Project X gathers CI information from a variety of sources including online newspapers, corporate websites, industry sector reporting sites, speech archiving sites, video news casts, stock news sites, weather sites, and rumor sites. It uses individual industry specific (e.g., pharmaceutical, financial, aerospace, etc.) commercial sector ontologies to form the knowledge filtering and discovery structures/content required to filter and identify valuable competitive knowledge. Project X is described in detail and an example competitive intelligence case is shown demonstrating the system's performance and utility for business intelligence.

A Sustainable and Selective Roasting and Water-Leaching Process to Simultaneously Extract Valuable Metals from Low-Grade Ni-Cu Matte

NASA Astrophysics Data System (ADS)

Cui, Fuhui; Mu, Wenning; Wang, Shuai; Xin, Haixia; Xu, Qian; Zhai, Yuchun

2018-03-01

Due to stringent environmental requirements and the complex occurrence of valuable metals, traditional pyrometallurgical methods are unsuitable for treating low-grade nickel-copper matte. A clean and sustainable two-stage sulfating roasting and water-leaching process was used to simultaneously extract valuable metals from low-grade nickel-copper matte. Ammonium and sodium sulfate were used as sulfating agents. The first roasting temperature, mass ratio of ammonium sulfate to matte, roasting time, dosage of sodium sulfate, second roasting temperature and leaching temperature were studied. Under optimal conditions, 98.89% of Ni, 97.48% of Cu and 95.82% of Co, but only 1.34% of Fe, were extracted. X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to reveal the sulfating mechanism during the roasting process.

Array data extractor (ADE): a LabVIEW program to extract and merge gene array data

PubMed Central

2013-01-01

Background Large data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research. Highly advanced bioinformatics tools have been made available to researchers, but a demand for user-friendly software allowing researchers to quickly extract expression information for multiple genes from multiple studies persists. Findings Here, we present a user-friendly LabVIEW program to automatically extract gene expression data for a list of genes from multiple normalized microarray datasets. Functionality was tested for 288 class A G protein-coupled receptors (GPCRs) and expression data from 12 studies comparing normal and diseased human hearts. Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets. Conclusions Although existing software allows for complex data analyses, the LabVIEW based program presented here, “Array Data Extractor (ADE)”, provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way. Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge. PMID:24289243

Asymptotic Cramer-Rao bounds for Morlet wavelet filter bank transforms of FM signals

NASA Astrophysics Data System (ADS)

Scheper, Richard

2002-03-01

Wavelet filter banks are potentially useful tools for analyzing and extracting information from frequency modulated (FM) signals in noise. Chief among the advantages of such filter banks is the tendency of wavelet transforms to concentrate signal energy while simultaneously dispersing noise energy over the time-frequency plane, thus raising the effective signal to noise ratio of filtered signals. Over the past decade, much effort has gone into devising new algorithms to extract the relevant information from transformed signals while identifying and discarding the transformed noise. Therefore, estimates of the ultimate performance bounds on such algorithms would serve as valuable benchmarks in the process of choosing optimal algorithms for given signal classes. Discussed here is the specific case of FM signals analyzed by Morlet wavelet filter banks. By making use of the stationary phase approximation of the Morlet transform, and assuming that the measured signals are well resolved digitally, the asymptotic form of the Fisher Information Matrix is derived. From this, Cramer-Rao bounds are analytically derived for simple cases.

Pharmacokinetic Tumor Heterogeneity as a Prognostic Biomarker for Classifying Breast Cancer Recurrence Risk.

PubMed

Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; McDonald, Elizabeth S; Rosen, Mark; Mies, Carolyn; Feldman, Michael; Kontos, Despina

2015-06-01

Heterogeneity in cancer can affect response to therapy and patient prognosis. Histologic measures have classically been used to measure heterogeneity, although a reliable noninvasive measurement is needed both to establish baseline risk of recurrence and monitor response to treatment. Here, we propose using spatiotemporal wavelet kinetic features from dynamic contrast-enhanced magnetic resonance imaging to quantify intratumor heterogeneity in breast cancer. Tumor pixels are first partitioned into homogeneous subregions using pharmacokinetic measures. Heterogeneity wavelet kinetic (HetWave) features are then extracted from these partitions to obtain spatiotemporal patterns of the wavelet coefficients and the contrast agent uptake. The HetWave features are evaluated in terms of their prognostic value using a logistic regression classifier with genetic algorithm wrapper-based feature selection to classify breast cancer recurrence risk as determined by a validated gene expression assay. Receiver operating characteristic analysis and area under the curve (AUC) are computed to assess classifier performance using leave-one-out cross validation. The HetWave features outperform other commonly used features (AUC = 0.88 HetWave versus 0.70 standard features). The combination of HetWave and standard features further increases classifier performance (AUCs 0.94). The rate of the spatial frequency pattern over the pharmacokinetic partitions can provide valuable prognostic information. HetWave could be a powerful feature extraction approach for characterizing tumor heterogeneity, providing valuable prognostic information.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

PubMed

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. © The Author(s) 2016. Published by Oxford University Press.

Querying and Extracting Timeline Information from Road Traffic Sensor Data

PubMed Central

Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

2016-01-01

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset. PMID:27563900

Photosynthetic Performance of the Imidazolinone Resistant Sunflower Exposed to Single and Combined Treatment by the Herbicide Imazamox and an Amino Acid Extract

PubMed Central

Balabanova, Dobrinka A.; Paunov, Momchil; Goltsev, Vasillij; Cuypers, Ann; Vangronsveld, Jaco; Vassilev, Andon

2016-01-01

The herbicide imazamox may provoke temporary yellowing and growth retardation in IMI-R sunflower hybrids, more often under stressful environmental conditions. Although, photosynthetic processes are not the primary sites of imazamox action, they might be influenced; therefore, more information about the photosynthetic performance of the herbicide-treated plants could be valuable for a further improvement of the Clearfield technology. Plant biostimulants have been shown to ameliorate damages caused by different stress factors on plants, but very limited information exists about their effects on herbicide-stressed plants. In order to characterize photosynthetic performance of imazamox-treated sunflower IMI-R plants, we carried out experiments including both single and combined treatments by imazamox and a plant biostimulants containing amino acid extract. We found that imazamox application in a rate of 132 μg per plant (equivalent of 40 g active ingredient ha−1) induced negative effects on both light-light dependent photosynthetic redox reactions and leaf gas exchange processes, which was much less pronounced after the combined application of imazamox and amino acid extract. PMID:27826304

Extracting Databases from Dark Data with DeepDive.

PubMed

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data : the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data - scientific papers, Web classified ads, customer service notes, and so on - were instead in a relational database, it would give analysts a massive and valuable new set of "big data." DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference.

Teratogenic and toxic effects of Lingzhi or Reishi medicinal mushroom, Ganoderma lucidum (W.Curt.:Fr.) P. Karst. (higher Basidiomycetes), on zebrafish embryo as model.

PubMed

Dulay, Rich Milton R; Kalaw, Sofronio P; Reyes, Renato G; Alfonso, Noel F; Eguchi, Fumio

2012-01-01

This paper highlights the teratogenic and toxic effects of Ganoderma lucidum (Lingzhi or Reishi mushroom) extract on zebrafish embryos. Hatchability, malformations, and lethality rate of zebrafish embryos were assessed to provide valuable information regarding the potential teratogenic activity of G. lucidum. Hatching was completed 48 h post treatment application (hpta) at 1% or lower concentrations of extract and embryo water. The hatching rate of embryos treated with 5% or higher concentrations was significantly lower (p> 0.05) than the control. Tail malformation was the most marked morphological abnormality in embryos at 72 hpta, which was obviously caused by 1% extract (55.56% tail malformation) and was observed in all embryos exposed to 5% of extract. Growth retardation was evident in embryos exposed to 5%, 10%, and 20%. However, lethal effect of extract of G. lucidum was dependent on dose and time of exposure. Mortality rates of embryos treated with 5% (44.44%) or higher concentrations of the extract was significantly higher (p > 0.05) than that of the control embryos at 72 hpta. These results suggest that G. lucidum extract has lethal and sub-lethal effects on zebrafish embryos.

Biologic Propensities and Phytochemical Profile of Vangueria madagascariensis J. F. Gmelin (Rubiaceae): An Underutilized Native Medicinal Food Plant from Africa

PubMed Central

Ramalingum, Nelvana; Mahomoodally, M. Fawzi

2014-01-01

Vangueria madagascariensis (VM), consumed for its sweet-sour fruits, is used as a biomedicine for the management of diabetes and bacterial infections in Africa. The study aims to assess the potential of VM on α-amylase, α-glucosidase, glucose movement, and antimicrobial activity. The antioxidant properties were determined by measuring the FRAP, iron chelating activity, and abilities to scavenge DPPH, HOCl, ∙OH, and NO radicals. Leaf decoction, leaf methanol, and unripe fruit methanol extracts were observed to significantly inhibit α-amylase. Active extracts against α-glucosidase were unripe fruit methanol, unripe fruit decoction, leaf decoction, and ripe fruit methanol, which were significantly lower than acarbose. Kinetic studies revealed a mixed noncompetitive type of inhibition. Leaf methanolic extract was active against S. aureus and E. coli. Total phenolic content showed a strong significant positive correlation (r = 0.88) with FRAP. Methanolic leaf extract showed a more efficient NO scavenging potential and was significantly lower than ascorbic acid. Concerning ∙OH-mediated DNA degradation, only the methanol extracts of leaf, unripe fruit, and ripe fruit had IC50 values which were significantly lower than α-tocopherol. Given the dearth of information on the biologic propensities of VM, this study has established valuable primary information which has opened new perspectives for further pharmacological research. PMID:24812627

Usability-driven pruning of large ontologies: the case of SNOMED CT.

PubMed

López-García, Pablo; Boeker, Martin; Illarramendi, Arantza; Schulz, Stefan

2012-06-01

To study ontology modularization techniques when applied to SNOMED CT in a scenario in which no previous corpus of information exists and to examine if frequency-based filtering using MEDLINE can reduce subset size without discarding relevant concepts. Subsets were first extracted using four graph-traversal heuristics and one logic-based technique, and were subsequently filtered with frequency information from MEDLINE. Twenty manually coded discharge summaries from cardiology patients were used as signatures and test sets. The coverage, size, and precision of extracted subsets were measured. Graph-traversal heuristics provided high coverage (71-96% of terms in the test sets of discharge summaries) at the expense of subset size (17-51% of the size of SNOMED CT). Pre-computed subsets and logic-based techniques extracted small subsets (1%), but coverage was limited (24-55%). Filtering reduced the size of large subsets to 10% while still providing 80% coverage. Extracting subsets to annotate discharge summaries is challenging when no previous corpus exists. Ontology modularization provides valuable techniques, but the resulting modules grow as signatures spread across subhierarchies, yielding a very low precision. Graph-traversal strategies and frequency data from an authoritative source can prune large biomedical ontologies and produce useful subsets that still exhibit acceptable coverage. However, a clinical corpus closer to the specific use case is preferred when available.

Data Processing and Text Mining Technologies on Electronic Medical Records: A Review

PubMed Central

Sun, Wencheng; Li, Yangyang; Liu, Fang; Fang, Shengqun; Wang, Guoyan

2018-01-01

Currently, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed, and treatment results. EMR has been recognized as a valuable resource for large-scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy, and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation, and data reduction. For semistructured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (named-entity recognition) and RE (relation extraction). This paper focuses on the process of EMR processing and emphatically analyzes the key techniques. In addition, we make an in-depth study on the applications developed based on text mining together with the open challenges and research issues for future work. PMID:29849998

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov

PubMed Central

Xu, Jun; Lee, Hee-Jin; Zeng, Jia; Wu, Yonghui; Zhang, Yaoyun; Huang, Liang-Chin; Johnson, Amber; Holla, Vijaykumar; Bailey, Ann M; Cohen, Trevor; Meric-Bernstam, Funda; Bernstam, Elmer V

2016-01-01

Objective: Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. Methods: We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. Results and Discussion: The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy. PMID:27013523

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov.

PubMed

Xu, Jun; Lee, Hee-Jin; Zeng, Jia; Wu, Yonghui; Zhang, Yaoyun; Huang, Liang-Chin; Johnson, Amber; Holla, Vijaykumar; Bailey, Ann M; Cohen, Trevor; Meric-Bernstam, Funda; Bernstam, Elmer V; Xu, Hua

2016-07-01

Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Steroid hormones in environmental matrices: extraction method comparison.

PubMed

Andaluri, Gangadhar; Suri, Rominder P S; Graham, Kendon

2017-11-09

The U.S. Environmental Protection Agency (EPA) has developed methods for the analysis of steroid hormones in water, soil, sediment, and municipal biosolids by HRGC/HRMS (EPA Method 1698). Following the guidelines provided in US-EPA Method 1698, the extraction methods were validated with reagent water and applied to municipal wastewater, surface water, and municipal biosolids using GC/MS/MS for the analysis of nine most commonly detected steroid hormones. This is the first reported comparison of the separatory funnel extraction (SFE), continuous liquid-liquid extraction (CLLE), and Soxhlet extraction methods developed by the U.S. EPA. Furthermore, a solid phase extraction (SPE) method was also developed in-house for the extraction of steroid hormones from aquatic environmental samples. This study provides valuable information regarding the robustness of the different extraction methods. Statistical analysis of the data showed that SPE-based methods provided better recovery efficiencies and lower variability of the steroid hormones followed by SFE. The analytical methods developed in-house for extraction of biosolids showed a wide recovery range; however, the variability was low (≤ 7% RSD). Soxhlet extraction and CLLE are lengthy procedures and have been shown to provide highly variably recovery efficiencies. The results of this study are guidance for better sample preparation strategies in analytical methods for steroid hormone analysis, and SPE adds to the choice in environmental sample analysis.

Polycapillary lenses for soft x-ray transmission in ITER: Model, comparison with experiments, and potential application

NASA Astrophysics Data System (ADS)

Mazon, D.; Liegeard, C.; Jardin, A.; Barnsley, R.; Walsh, M.; O'Mullane, M.; Sirinelli, A.; Dorchies, F.

2016-11-01

Measuring Soft X-Ray (SXR) radiation [0.1 keV; 15 keV] in tokamaks is a standard way of extracting valuable information on the particle transport and magnetohydrodynamic activity. Generally, the analysis is performed with detectors positioned close to the plasma for a direct line of sight. A burning plasma, like the ITER deuterium-tritium phase, is too harsh an environment to permit the use of such detectors in close vicinity of the machine. We have thus investigated in this article the possibility of using polycapillary lenses in ITER to transport the SXR information several meters away from the plasma in the complex port-plug geometry.

Polycapillary lenses for soft x-ray transmission in ITER: Model, comparison with experiments, and potential application.

PubMed

Mazon, D; Liegeard, C; Jardin, A; Barnsley, R; Walsh, M; O'Mullane, M; Sirinelli, A; Dorchies, F

2016-11-01

Measuring Soft X-Ray (SXR) radiation [0.1 keV; 15 keV] in tokamaks is a standard way of extracting valuable information on the particle transport and magnetohydrodynamic activity. Generally, the analysis is performed with detectors positioned close to the plasma for a direct line of sight. A burning plasma, like the ITER deuterium-tritium phase, is too harsh an environment to permit the use of such detectors in close vicinity of the machine. We have thus investigated in this article the possibility of using polycapillary lenses in ITER to transport the SXR information several meters away from the plasma in the complex port-plug geometry.

Extracting Databases from Dark Data with DeepDive

PubMed Central

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data: the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data — scientific papers, Web classified ads, customer service notes, and so on — were instead in a relational database, it would give analysts a massive and valuable new set of “big data.” DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference. PMID:28316365

Informatics in radiology: automated Web-based graphical dashboard for radiology operational business intelligence.

PubMed

Nagy, Paul G; Warnock, Max J; Daly, Mark; Toland, Christopher; Meenan, Christopher D; Mezrich, Reuben S

2009-11-01

Radiology departments today are faced with many challenges to improve operational efficiency, performance, and quality. Many organizations rely on antiquated, paper-based methods to review their historical performance and understand their operations. With increased workloads, geographically dispersed image acquisition and reading sites, and rapidly changing technologies, this approach is increasingly untenable. A Web-based dashboard was constructed to automate the extraction, processing, and display of indicators and thereby provide useful and current data for twice-monthly departmental operational meetings. The feasibility of extracting specific metrics from clinical information systems was evaluated as part of a longer-term effort to build a radiology business intelligence architecture. Operational data were extracted from clinical information systems and stored in a centralized data warehouse. Higher-level analytics were performed on the centralized data, a process that generated indicators in a dynamic Web-based graphical environment that proved valuable in discussion and root cause analysis. Results aggregated over a 24-month period since implementation suggest that this operational business intelligence reporting system has provided significant data for driving more effective management decisions to improve productivity, performance, and quality of service in the department.

Ginkgo biloba Extract for Patients with Early Diabetic Nephropathy: A Systematic Review

PubMed Central

Zhang, Lei; Mao, Wei; Guo, Xinfeng; Wu, Yifan; Li, Chuang; Lu, Zhaoyu; Su, Guobin; Li, Xiaoyan; Liu, Zhuangzhu; Guo, Rong; Jie, Xina; Wen, Zehuai; Liu, Xusheng

2013-01-01

Objectives. To evaluate the effectiveness and safety of a Ginkgo biloba extract for patients with early diabetic nephropathy. Methods. Randomised controlled trials (RCTs) conducted on adults with early diabetic nephropathy which used Gingko biloba extract were included. The major databases were searched, and manufacturers of Gingko biloba products were contacted for information on any published or unpublished studies. Two authors independently extracted the data from the included studies. Data analysis was conducted using Review Manager 5.0 software. Results. Sixteen RCTs were included. Ginkgo biloba extract decreased the urinary albumin excretion rate (UAER), fasting blood glucose (FBG), serum creatinine (SCR), and blood urea nitrogen (BUN). The extract also improved hemorheology. The methodological quality in the included studies was low. The explicit generation of the allocation sequence was described in only 6 trials. None of the included trials were confirmed to use blinding. Three studies had observed adverse events. One study using angiotensin-converting enzyme inhibitor (ACEi) reported mild cough in both groups. No serious adverse effects were reported. Conclusions. Gingko biloba extract is a valuable drug which has prospect in treating early diabetic nephropathy, especially with high UAER baseline level. The safety for early diabetic nephropathy is uncertain. Long-term, double-blinded RCTs with large sample sizes are still needed to provide stronger evidence. PMID:23533513

Integrating GPCR-specific information with full text articles

PubMed Central

2011-01-01

Background With the continued growth in the volume both of experimental G protein-coupled receptor (GPCR) data and of the related peer-reviewed literature, the ability of GPCR researchers to keep up-to-date is becoming increasingly curtailed. Results We present work that integrates the biological data and annotations in the GPCR information system (GPCRDB) with next-generation methods for intelligently exploring, visualising and interacting with the scientific articles used to disseminate them. This solution automatically retrieves relevant information from GPCRDB and displays it both within and as an adjunct to an article. Conclusions This approach allows researchers to extract more knowledge more swiftly from literature. Importantly, it allows reinterpretation of data in articles published before GPCR structure data became widely available, thereby rescuing these valuable data from long-dormant sources. PMID:21910883

Urban Boundary Extraction and Urban Sprawl Measurement Using High-Resolution Remote Sensing Images: a Case Study of China's Provincial

NASA Astrophysics Data System (ADS)

Wang, H.; Ning, X.; Zhang, H.; Liu, Y.; Yu, F.

2018-04-01

Urban boundary is an important indicator for urban sprawl analysis. However, methods of urban boundary extraction were inconsistent, and construction land or urban impervious surfaces was usually used to represent urban areas with coarse-resolution images, resulting in lower precision and incomparable urban boundary products. To solve above problems, a semi-automatic method of urban boundary extraction was proposed by using high-resolution image and geographic information data. Urban landscape and form characteristics, geographical knowledge were combined to generate a series of standardized rules for urban boundary extraction. Urban boundaries of China's 31 provincial capitals in year 2000, 2005, 2010 and 2015 were extracted with above-mentioned method. Compared with other two open urban boundary products, accuracy of urban boundary in this study was the highest. Urban boundary, together with other thematic data, were integrated to measure and analyse urban sprawl. Results showed that China's provincial capitals had undergone a rapid urbanization from year 2000 to 2015, with the area change from 6520 square kilometres to 12398 square kilometres. Urban area of provincial capital had a remarkable region difference and a high degree of concentration. Urban land became more intensive in general. Urban sprawl rate showed inharmonious with population growth rate. About sixty percent of the new urban areas came from cultivated land. The paper provided a consistent method of urban boundary extraction and urban sprawl measurement using high-resolution remote sensing images. The result of urban sprawl of China's provincial capital provided valuable urbanization information for government and public.

Recovery and identification of bacterial DNA from illicit drugs.

PubMed

Cho, Kaymann T; Richardson, Michelle M; Kirkbride, K Paul; McNevin, Dennis; Nelson, Michelle; Pianca, Dennis; Roffey, Paul; Gahan, Michelle E

2014-02-01

Bacterial infections, including Bacillus anthracis (anthrax), are a common risk associated with illicit drug use, particularly among injecting drug users. There is, therefore, an urgent need to survey illicit drugs used for injection for the presence of bacteria and provide valuable information to health and forensic authorities. The objectives of this study were to develop a method for the extraction of bacterial DNA from illicit drugs and conduct a metagenomic survey of heroin and methamphetamine seized in the Australian Capital Territory during 2002-2011 for the presence of pathogens. Trends or patterns in drug contamination and their health implications for injecting drug users were also investigated. Methods based on the ChargeSwitch(®)gDNA mini kit (Invitrogen), QIAamp DNA extraction mini kit (QIAGEN) with and without bead-beating, and an organic phenol/chloroform extraction with ethanol precipitation were assessed for the recovery efficiency of both free and cellular bacterial DNA. Bacteria were identified using polymerase chain reaction and electrospray ionization-mass spectrometry (PCR/ESI-MS). An isopropanol pre-wash to remove traces of the drug and diluents, followed by a modified ChargeSwitch(®) method, was found to efficiently lyse cells and extract free and cellular DNA from Gram-positive and Gram-negative bacteria in heroin and methamphetamine which could then be identified by PCR/ESI-MS. Analysis of 12 heroin samples revealed the presence of DNA from species of Comamonas, Weissella, Bacillus, Streptococcus and Arthrobacter. No organisms were detected in the nine methamphetamine samples analysed. This study develops a method to extract and identify Gram-positive and Gram-negative bacteria from illicit drugs and demonstrates the presence of a range of bacterial pathogens in seized drug samples. These results will prove valuable for future work investigating trends or patterns in drug contamination and their health implications for injecting drug users as well as enabling forensic links between seizures to be examined. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Antimicrobial potential of macro and microalgae against pathogenic and spoilage microorganisms in food.

PubMed

Pina-Pérez, M C; Rivas, A; Martínez, A; Rodrigo, D

2017-11-15

Algae are a valuable and never-failing source of bioactive compounds. The increasing efforts to use ingredients that are as natural as possible in the formulation of innovative products has given rise to the introduction of macro and microalgae in food industry. To date, scarce information has been published about algae ingredients as antimicrobials in food. The antimicrobial potential of algae is highly dependent on: (i) type, brown algae being the most effective against foodborne bacteria; (ii) the solvent used in the extraction of bioactive compounds, ethanolic and methanolic extracts being highly effective against Gram-positive and Gram-negative bacteria; and (iii) the concentration of the extract. The present paper reviews the main antimicrobial potential of algal species and their bioactive compounds in reference and real food matrices. The validation of the algae antimicrobial potential in real food matrices is still a research niche, being meat and bakery products the most studied substrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic optical detection and classification of marine animals around MHK converters using machine vision

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brunton, Steven

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robustmore » principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.« less

Usability-driven pruning of large ontologies: the case of SNOMED CT

PubMed Central

Boeker, Martin; Illarramendi, Arantza; Schulz, Stefan

2012-01-01

Objectives To study ontology modularization techniques when applied to SNOMED CT in a scenario in which no previous corpus of information exists and to examine if frequency-based filtering using MEDLINE can reduce subset size without discarding relevant concepts. Materials and Methods Subsets were first extracted using four graph-traversal heuristics and one logic-based technique, and were subsequently filtered with frequency information from MEDLINE. Twenty manually coded discharge summaries from cardiology patients were used as signatures and test sets. The coverage, size, and precision of extracted subsets were measured. Results Graph-traversal heuristics provided high coverage (71–96% of terms in the test sets of discharge summaries) at the expense of subset size (17–51% of the size of SNOMED CT). Pre-computed subsets and logic-based techniques extracted small subsets (1%), but coverage was limited (24–55%). Filtering reduced the size of large subsets to 10% while still providing 80% coverage. Discussion Extracting subsets to annotate discharge summaries is challenging when no previous corpus exists. Ontology modularization provides valuable techniques, but the resulting modules grow as signatures spread across subhierarchies, yielding a very low precision. Conclusion Graph-traversal strategies and frequency data from an authoritative source can prune large biomedical ontologies and produce useful subsets that still exhibit acceptable coverage. However, a clinical corpus closer to the specific use case is preferred when available. PMID:22268217

NPCARE: database of natural products and fractional extracts for cancer regulation.

PubMed

Choi, Hwanho; Cho, Sun Young; Pak, Ho Jeong; Kim, Youngsoo; Choi, Jung-Yun; Lee, Yoon Jae; Gong, Byung Hee; Kang, Yeon Seok; Han, Taehoon; Choi, Geunbae; Cho, Yeeun; Lee, Soomin; Ryoo, Dekwoo; Park, Hwangseo

2017-01-01

Natural products have increasingly attracted much attention as a valuable resource for the development of anticancer medicines due to the structural novelty and good bioavailability. This necessitates a comprehensive database for the natural products and the fractional extracts whose anticancer activities have been verified. NPCARE (http://silver.sejong.ac.kr/npcare) is a publicly accessible online database of natural products and fractional extracts for cancer regulation. At NPCARE, one can explore 6578 natural compounds and 2566 fractional extracts isolated from 1952 distinct biological species including plants, marine organisms, fungi, and bacteria whose anticancer activities were validated with 1107 cell lines for 34 cancer types. Each entry in NPCARE is annotated with the cancer type, genus and species names of the biological resource, the cell line used for demonstrating the anticancer activity, PubChem ID, and a wealth of information about the target gene or protein. Besides the augmentation of plant entries up to 743 genus and 197 families, NPCARE is further enriched with the natural products and the fractional extracts of diverse non-traditional biological resources. NPCARE is anticipated to serve as a dominant gateway for the discovery of new anticancer medicines due to the inclusion of a large number of the fractional extracts as well as the natural compounds isolated from a variety of biological resources.

a New Multi-Spectral Threshold Normalized Difference Water Index Mst-Ndwi Water Extraction Method - a Case Study in Yanhe Watershed

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhao, H.; Hao, H.; Wang, C.

2018-05-01

Accurate remote sensing water extraction is one of the primary tasks of watershed ecological environment study. Since the Yanhe water system has typical characteristics of a small water volume and narrow river channel, which leads to the difficulty for conventional water extraction methods such as Normalized Difference Water Index (NDWI). A new Multi-Spectral Threshold segmentation of the NDWI (MST-NDWI) water extraction method is proposed to achieve the accurate water extraction in Yanhe watershed. In the MST-NDWI method, the spectral characteristics of water bodies and typical backgrounds on the Landsat/TM images have been evaluated in Yanhe watershed. The multi-spectral thresholds (TM1, TM4, TM5) based on maximum-likelihood have been utilized before NDWI water extraction to realize segmentation for a division of built-up lands and small linear rivers. With the proposed method, a water map is extracted from the Landsat/TM images in 2010 in China. An accuracy assessment is conducted to compare the proposed method with the conventional water indexes such as NDWI, Modified NDWI (MNDWI), Enhanced Water Index (EWI), and Automated Water Extraction Index (AWEI). The result shows that the MST-NDWI method generates better water extraction accuracy in Yanhe watershed and can effectively diminish the confusing background objects compared to the conventional water indexes. The MST-NDWI method integrates NDWI and Multi-Spectral Threshold segmentation algorithms, with richer valuable information and remarkable results in accurate water extraction in Yanhe watershed.

Polycapillary lenses for soft x-ray transmission in ITER: Model, comparison with experiments, and potential application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazon, D., E-mail: Didier.Mazon@cea.fr; Jardin, A.; Liegeard, C.

2016-11-15

Measuring Soft X-Ray (SXR) radiation [0.1 keV; 15 keV] in tokamaks is a standard way of extracting valuable information on the particle transport and magnetohydrodynamic activity. Generally, the analysis is performed with detectors positioned close to the plasma for a direct line of sight. A burning plasma, like the ITER deuterium-tritium phase, is too harsh an environment to permit the use of such detectors in close vicinity of the machine. We have thus investigated in this article the possibility of using polycapillary lenses in ITER to transport the SXR information several meters away from the plasma in the complex port-plugmore » geometry.« less

Big data in fashion industry

NASA Astrophysics Data System (ADS)

Jain, S.; Bruniaux, J.; Zeng, X.; Bruniaux, P.

2017-10-01

Significant work has been done in the field of big data in last decade. The concept of big data includes analysing voluminous data to extract valuable information. In the fashion world, big data is increasingly playing a part in trend forecasting, analysing consumer behaviour, preference and emotions. The purpose of this paper is to introduce the term fashion data and why it can be considered as big data. It also gives a broad classification of the types of fashion data and briefly defines them. Also, the methodology and working of a system that will use this data is briefly described.

Interferometric atmospheric refractive-index environmental monitor

NASA Astrophysics Data System (ADS)

Ludman, Jacques E.; Ludman, Jacques J.; Callahan, Heidi; Robinson, John; Davis, Seth; Caulfield, H. John; Watt, David; Sampson, John L.; Hunt, Arlon

1995-06-01

Long, open-path, outdoor interferometric measurement of the index of refraction as a function of wavelength (spectral refractivity) requires a number of innovations. These include active compensation for vibration and turbulence. The use of electronic compensation produces an electronic signal that is ideal for extracting data. This allows the appropriate interpretation of those data and the systematic and fast scanning of the spectrum by the use of bandwidths that are intermediate between lasers (narrow bandwidth) and white light (broad bandwidth). An Environmental Interferometer that incorporates these features should be extremely valuable in both pollutant detection and pollutant identification. Spectral refractivity measurements complement the information available

Ancient Mitochondrial DNA Analyses of Ascaris Eggs Discovered in Coprolites from Joseon Tomb

PubMed Central

Oh, Chang Seok; Seo, Min; Hong, Jong Ha; Chai, Jong-Yil; Oh, Seung Whan; Park, Jun Bum; Shin, Dong Hoon

2015-01-01

Analysis of ancient DNA (aDNA) extracted from Ascaris is very important for understanding the phylogenetic lineage of the parasite species. When aDNAs obtained from a Joseon tomb (SN2-19-1) coprolite in which Ascaris eggs were identified were amplified with primers for cytochrome b (cyt b) and 18S small subunit ribosomal RNA (18S rRNA) gene, the outcome exhibited Ascaris specific amplicon bands. By cloning, sequencing, and analysis of the amplified DNA, we obtained information valuable for comprehending genetic lineage of Ascaris prevalent among pre-modern Joseon peoples. PMID:25925186

Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

PubMed Central

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-01-01

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. PMID:25225874

Mobile-cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors.

PubMed

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-09-15

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

[The influence of stinging nettle (Urtica dioica L.) extracts on the activity of catalase in THP1 monocytes/macrophages].

PubMed

Wolska, Jolanta; Janda, Katarzyna; Szkyrpan, Sylwia; Gutowska, Izabela

2015-01-01

Stinging nettle (Urtica dioicd L.) is one of the most valuable plants used in phytotherapy. The herbal raw material is a herb (Urticae herba), leaves (Urticae folium), roots (Urticae radix) and seeds (Urticae semina). This plant is a good source of vitamins, minerals, fibre, protein and biologically active compounds with antioxidant properties. The literature provides limited information about the chemical composition and properties of the seed heads. No papers are available on the effect of extracts of this plant on catalase activity in human cells. The aim of this study was to investigate the impact of stinging nettle (Urtica dioica L.) extracts on the antioxidant activity of catalase in THP1 macrophages. Two types of extracts: water and alcohol, at two different concentrations, were used in experiments. Nettle was collected in September and October in 2012 in the area of Szczecin. The collected plant material was frozen and lyophilized. After those procedures water and alcohol extracts of nettle were prepared and then added to THP1 cells. The antioxidant activity of catalase was established with the spectrophotometric method. The study showed that both extracts (water and alcohol) significantly increased the antioxidant activity of catalase in THP1 cells. The increase in catalase was directly proportional to the concentration of the added alcohol extract.

A flexible data-driven comorbidity feature extraction framework.

PubMed

Sideris, Costas; Pourhomayoun, Mohammad; Kalantarian, Haik; Sarrafzadeh, Majid

2016-06-01

Disease and symptom diagnostic codes are a valuable resource for classifying and predicting patient outcomes. In this paper, we propose a novel methodology for utilizing disease diagnostic information in a predictive machine learning framework. Our methodology relies on a novel, clustering-based feature extraction framework using disease diagnostic information. To reduce the data dimensionality, we identify disease clusters using co-occurrence statistics. We optimize the number of generated clusters in the training set and then utilize these clusters as features to predict patient severity of condition and patient readmission risk. We build our clustering and feature extraction algorithm using the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP) which contains 7 million hospital discharge records and ICD-9-CM codes. The proposed framework is tested on Ronald Reagan UCLA Medical Center Electronic Health Records (EHR) from 3041 Congestive Heart Failure (CHF) patients and the UCI 130-US diabetes dataset that includes admissions from 69,980 diabetic patients. We compare our cluster-based feature set with the commonly used comorbidity frameworks including Charlson's index, Elixhauser's comorbidities and their variations. The proposed approach was shown to have significant gains between 10.7-22.1% in predictive accuracy for CHF severity of condition prediction and 4.65-5.75% in diabetes readmission prediction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recovery of Palm Oil and Valuable Material from Oil Palm Empty Fruit Bunch by Sub-critical Water.

PubMed

Ahmad Kurnin, Nor Azrin; Shah Ismail, Mohd Halim; Yoshida, Hiroyuki; Izhar, Shamsul

2016-01-01

Oil palm empty fruit bunch (EFB) is one of the solid wastes produced in huge volume by palm oil mill. Whilst it still contains valuable oil, approximately 22.6 million tons is generated annually and treated as solid waste. In this work, sub-critical water (sub-cw) was used to extract oil, sugar and tar from spikelet of EFB. The spikelet was treated with sub-cw between 180-280°C and a reaction time of 2 and 5 minutes. The highest yield of oil was 0.075 g-oil/g-dry EFB, obtained at 240°C and reaction time of 5 minutes. Astonishingly, oil that was extracted through this method was 84.5% of that obtained through Soxhlet method using hexane. Yield of oil extracted was strongly affected by the reaction temperature and time. Higher reaction temperature induces the dielectric constant of water towards the non-polar properties of solvent; thus increases the oil extraction capability. Meanwhile, the highest yield of sugar was 0.20 g-sugar/g-dry EFB obtained at 220°C. At this temperature, the ion product of water is high enough to enable maximum sub-critical water hydrolysis reaction. This study showed that oil and other valuable material can be recovered using water at sub-critical condition, and most attractive without the use of harmful organic solvent.

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method can achieve better performance than such previous methods as entropy and Gibbs error based methods and a conventional committee-based method. We also show that the incorporation of named entity recognition into the active learning for event extraction and the unknown word handling further improve the active learning method. In addition, the adaptation of the active learning method into named entity recognition tasks also improves the document selection for manual annotation of named entities.

A graph-based approach to detect spatiotemporal dynamics in satellite image time series

NASA Astrophysics Data System (ADS)

Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

2017-08-01

Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

Using Airborne Remote Sensing to Increase Situational Awareness in Civil Protection and Humanitarian Relief - the Importance of User Involvement

NASA Astrophysics Data System (ADS)

Römer, H.; Kiefl, R.; Henkel, F.; Wenxi, C.; Nippold, R.; Kurz, F.; Kippnich, U.

2016-06-01

Enhancing situational awareness in real-time (RT) civil protection and emergency response scenarios requires the development of comprehensive monitoring concepts combining classical remote sensing disciplines with geospatial information science. In the VABENE++ project of the German Aerospace Center (DLR) monitoring tools are being developed by which innovative data acquisition approaches are combined with information extraction as well as the generation and dissemination of information products to a specific user. DLR's 3K and 4k camera system which allow for a RT acquisition and pre-processing of high resolution aerial imagery are applied in two application examples conducted with end users: a civil protection exercise with humanitarian relief organisations and a large open-air music festival in cooperation with a festival organising company. This study discusses how airborne remote sensing can significantly contribute to both, situational assessment and awareness, focussing on the downstream processes required for extracting information from imagery and for visualising and disseminating imagery in combination with other geospatial information. Valuable user feedback and impetus for further developments has been obtained from both applications, referring to innovations in thematic image analysis (supporting festival site management) and product dissemination (editable web services). Thus, this study emphasises the important role of user involvement in application-related research, i.e. by aligning it closer to user's requirements.

Introduction to metabolic genetic engineering for the production of valuable secondary metabolites in in vivo and in vitro plant systems.

PubMed

Benedito, Vagner A; Modolo, Luzia V

2014-01-01

Plants are capable of producing a myriad of chemical compounds. While these compounds serve specific functions in the plant, many have surprising effects on the human body, often with positive action against diseases. These compounds are often difficult to synthesize ex vivo and require the coordinated and compartmentalized action of enzymes in living organisms. However, the amounts produced in whole plants are often small and restricted to single tissues of the plant or even cellular organelles, making their extraction an expensive process. Since most natural products used in therapeutics are specialized, secondary plant metabolites, we provide here an overview of the classification of the main classes of these compounds, with its biochemical pathways and how this information can be used to create efficient in and ex planta production pipelines to generate highly valuable compounds. Metabolic genetic engineering is introduced in light of physiological and genetic methods to enhance production of high-value plant secondary metabolites.

Fractionation of Pb and Cu in the fine fraction (<10 mm) of waste excavated from a municipal landfill.

PubMed

Kaczala, Fabio; Orupõld, Kaja; Augustsson, Anna; Burlakovs, Juris; Hogland, Marika; Bhatnagar, Amit; Hogland, William

2017-11-01

The fractionation of metals in the fine fraction (<10 mm) of excavated waste from an Estonian landfill was carried out to evaluate the metal (Pb and Cu) contents and their potential towards not only mobility but also possibilities of recovery/extraction. The fractionation followed the BCR (Community Bureau of Reference) sequential extraction, and the exchangeable (F1), reducible (F2), oxidizable (F3) and residual fractions were determined. The results showed that Pb was highly associated with the reducible (F2) and oxidizable (F3) fractions, suggesting the potential mobility of this metal mainly when in contact with oxygen, despite the low association with the exchangeable fraction (F1). Cu has also shown the potential for mobility when in contact with oxygen, since high associations with the oxidizable fraction (F3) were observed. On the other hand, the mobility of metals in excavated waste can be seen as beneficial considering the circular economy and recovery of such valuables back into the economy. To conclude, not only the total concentration of metals but also a better understanding of fractionation and in which form metals are bound is very important to bring information on how to manage the fine fraction from excavated waste both in terms of environmental impacts and also recovery of such valuables in the economy.

Versatile and efficient pore network extraction method using marker-based watershed segmentation

NASA Astrophysics Data System (ADS)

Gostick, Jeff T.

2017-08-01

Obtaining structural information from tomographic images of porous materials is a critical component of porous media research. Extracting pore networks is particularly valuable since it enables pore network modeling simulations which can be useful for a host of tasks from predicting transport properties to simulating performance of entire devices. This work reports an efficient algorithm for extracting networks using only standard image analysis techniques. The algorithm was applied to several standard porous materials ranging from sandstone to fibrous mats, and in all cases agreed very well with established or known values for pore and throat sizes, capillary pressure curves, and permeability. In the case of sandstone, the present algorithm was compared to the network obtained using the current state-of-the-art algorithm, and very good agreement was achieved. Most importantly, the network extracted from an image of fibrous media correctly predicted the anisotropic permeability tensor, demonstrating the critical ability to detect key structural features. The highly efficient algorithm allows extraction on fairly large images of 5003 voxels in just over 200 s. The ability for one algorithm to match materials as varied as sandstone with 20% porosity and fibrous media with 75% porosity is a significant advancement. The source code for this algorithm is provided.

Analytical 3D views and virtual globes — scientific results in a familiar spatial context

NASA Astrophysics Data System (ADS)

Tiede, Dirk; Lang, Stefan

In this paper we introduce analytical three-dimensional (3D) views as a means for effective and comprehensible information delivery, using virtual globes and the third dimension as an additional information carrier. Four case studies are presented, in which information extraction results from very high spatial resolution (VHSR) satellite images were conditioned and aggregated or disaggregated to regular spatial units. The case studies were embedded in the context of: (1) urban life quality assessment (Salzburg/Austria); (2) post-disaster assessment (Harare/Zimbabwe); (3) emergency response (Lukole/Tanzania); and (4) contingency planning (faked crisis scenario/Germany). The results are made available in different virtual globe environments, using the implemented contextual data (such as satellite imagery, aerial photographs, and auxiliary geodata) as valuable additional context information. Both day-to-day users and high-level decision makers are addressees of this tailored information product. The degree of abstraction required for understanding a complex analytical content is balanced with the ease and appeal by which the context is conveyed.

Standardized data sharing in a paediatric oncology research network--a proof-of-concept study.

PubMed

Hochedlinger, Nina; Nitzlnader, Michael; Falgenhauer, Markus; Welte, Stefan; Hayn, Dieter; Koumakis, Lefteris; Potamias, George; Tsiknakis, Manolis; Saraceno, Davide; Rinaldi, Eugenia; Ladenstein, Ruth; Schreier, Günter

2015-01-01

Data that has been collected in the course of clinical trials are potentially valuable for additional scientific research questions in so called secondary use scenarios. This is of particular importance in rare disease areas like paediatric oncology. If data from several research projects need to be connected, so called Core Datasets can be used to define which information needs to be extracted from every involved source system. In this work, the utility of the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) as a format for Core Datasets was evaluated and a web tool was developed which received Source ODM XML files and--via Extensible Stylesheet Language Transformation (XSLT)--generated standardized Core Dataset ODM XML files. Using this tool, data from different source systems were extracted and pooled for joined analysis in a proof-of-concept study, facilitating both, basic syntactic and semantic interoperability.

Comprehensive transcriptome analysis and flavonoid profiling of Ginkgo leaves reveals flavonoid content alterations in day-night cycles.

PubMed

Ni, Jun; Dong, Lixiang; Jiang, Zhifang; Yang, Xiuli; Chen, Ziying; Wu, Yuhuan; Xu, Maojun

2018-01-01

Ginkgo leaves are raw materials for flavonoid extraction. Thus, the timing of their harvest is important to optimize the extraction efficiency, which benefits the pharmaceutical industry. In this research, we compared the transcriptomes of Ginkgo leaves harvested at midday and midnight. The differentially expressed genes with the highest probabilities in each step of flavonoid biosynthesis were down-regulated at midnight. Furthermore, real-time PCR corroborated the transcriptome results, indicating the decrease in flavonoid biosynthesis at midnight. The flavonoid profiles of Ginkgo leaves harvested at midday and midnight were compared, and the total flavonoid content decreased at midnight. A detailed analysis of individual flavonoids showed that most of their contents were decreased by various degrees. Our results indicated that circadian rhythms affected the flavonoid contents in Ginkgo leaves, which provides valuable information for optimizing their harvesting times to benefit the pharmaceutical industry.

Telefetalcare: a first prototype of a wearable fetal electrocardiograph.

PubMed

Fanelli, A; Signorini, M G; Ferrario, M; Perego, P; Piccini, L; Andreoni, G; Magenes, G

2011-01-01

Fetal heart rate monitoring is fundamental to infer information about fetal health state during pregnancy. The cardiotocography (CTG) is the most common antepartum monitoring technique. Abdominal ECG recording represents the most valuable alternative to cardiotocography, as it allows passive, non invasive and long term fetal monitoring. Unluckily fetal ECG has low SNR and needs to be extracted from abdominal recordings using ad hoc algorithms. This work describes a prototype of a wearable fetal ECG electrocardiograph. The system has flat band frequency response between 1-60 Hz and guarantees good signal quality. It was tested on pregnant women between the 30(th) and 34(th) gestational week. Several electrodes configurations were tested, in order to identify the best solution. Implementation of a simple algorithm for FECG extraction permitted the reliable detection of maternal and fetal QRS complexes. The system will allow continuative and deep screening of fetal heart rate, introducing the possibility of home fetal monitoring.

A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos

PubMed Central

Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

2016-01-01

Objective Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today’s keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users’ information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. Materials and Methods The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively. Results The authors produced a prototype implementation of the proposed system, which is publicly accessible at https://patentq.njit.edu/oer. To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Conclusion Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable information, as well as intuitively and conveniently preview essential content of a single or a collection of videos. PMID:26335986

Association Rule Analysis for Tour Route Recommendation and Application to Wctsnop

NASA Astrophysics Data System (ADS)

Fang, H.; Chen, C.; Lin, J.; Liu, X.; Fang, D.

2017-09-01

The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality.

How PNNL Extracts Rare Earth Elements from Geothermal Brine

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2016-07-12

By looking at a problem at a nanoscale level, PNNL researchers are developing an economic way to extract valuable rare earth elements from geothermal fluids. This novel approach may help meet the high demand for rare earth elements that are used in many clean energy technologies.

Geothermal resources and energy complex use in Russia

NASA Astrophysics Data System (ADS)

Svalova, V.

2009-04-01

Geothermal energy use is the perspective way to clean sustainable development of the world. Russia has rich high and low temperature geothermal resources and makes good steps in their use. In Russia the geothermal resources are used predominantly for heat supply both heating of several cities and settlements on Northern Caucasus and Kamchatka with a total number of the population 500000. Besides in some regions of country the deep heat is used for greenhouses of common area 465000 m2. Most active the hydrothermal resources are used in Krasnodar territory, Dagestan and on Kamchatka. The approximately half of extracted resources is applied for heat supply of habitation and industrial puttings, third - to a heating of greenhouses, and about 13 % - for industrial processes. Besides the thermal waters are used approximately on 150 health resorts and 40 factories on bottling mineral water. The most perspective direction of usage of low temperature geothermal resources is the use of heat pumps. This way is optimal for many regions of Russia - in its European part, on Ural and others. The electricity is generated by some geothermal power plants (GeoPP) only in the Kamchatka Peninsula and Kuril Islands. At present three stations work in Kamchatka: Pauzhetka GeoPP (11MW e installed capacity) and two Severo-Mutnovka GeoPP ( 12 and 50 MWe). Moreover, another GeoPP of 100 MVe is now under preparation in the same place. Two small GeoPP are in operation in Kuril's Kunashir Isl, and Iturup Isl, with installed capacity of 2,б MWe and 6 MWe respectively. There are two possible uses of geothermal resources depending on structure and properties of thermal waters: heat/power and mineral extraction. The heat/power direction is preferable for low mineralized waters when valuable components in industrial concentration are absent, and the general mineralization does not interfere with normal operation of system. When high potential geothermal waters are characterized by the high mineralization and propensity for scaling, the extraction of mineral components should be considered. The mineral-extraction direction is basic for geothermal waters, containing valuable components in industrial quantities. Thus, the ability to extract minerals is dependent upon the use and maturity of recovery technologies. For such waters the heat is an added product, which use can raise efficiency of basic mineral production processes and even to save fuel. The process of extraction of valuable components should be dominant in such systems. The most significant deposits of thermal waters represent the brines containing from 35 up to 400 and more g/l of salts. They are mineral raw materials for many chemical elements. Many brines can become deposits of valuable chemical elements: cesium, boron, strontium, tantalum, magnesium, calcium, tungsten, etc. Basically it is possible to recover iodine, bromine, boron, chloride salts of ammonium, potassium, sodium, calcium and magnesium from natural solutions using inexpensive technological solutions. Extraction of other chemical elements is complicated due to high cost of technology. There is a perspective method of ion-exchange pitches for selective extraction of certain components from natural waters. In a basis of the method there is the principle of selective sorption of ions of useful elements or their complexes in solutions with special compounds. Works of some scientific institutes in Russia strive to create the procedures of chemical processing of hydrothermal minerals to expand the spheres of its economic application. Many laboratory and natural tests on extraction of valuable components from thermal waters confirm the necessity and an opportunity of complex use of this nonconventional raw material. It is planned to recover I, Br, KCl, CaCl, NaCl from brines in Yaroslavl area. New methods of mineral and valuable elements extraction from industrial solutions are developed on the basis of biosorbent use.

Evaluation of the suitability of Skylab data for the purpose of petroleum exploration

NASA Technical Reports Server (NTRS)

Collins, R. J. (Principal Investigator); Petzel, G.; Everett, J. R.

1975-01-01

The author has identified the following significant results. Comparisons of the various photographic bands of Skylab imagery indicate that, overall, standard color (particularly S190B) is the most valuable for geological purposes. Detailed examination of all bands indicates that as with ERTS imagery each band contains useful information that is unique to it. The results of geological interpretations based on ERTS and Skylab imagery are strikingly similar. It appears that more information can be extracted from a single Skylab overpass than a single ERTS overpass, but that with repeated passes the lower resolution ERTS imagery may yield information comparable to that contained in S190B imagery. Comparison of Skylab photography to high altitude aircraft photography suggests that there are distinct advantages to using Skylab imagery for regional geologic interpretations. This is primarily because of the synoptic view provided by the space acquired imagery allows and encourages integration of regional geologic features.

Efficient isolation method for high-quality genomic DNA from cicada exuviae.

PubMed

Nguyen, Hoa Quynh; Kim, Ye Inn; Borzée, Amaël; Jang, Yikweon

2017-10-01

In recent years, animal ethics issues have led researchers to explore nondestructive methods to access materials for genetic studies. Cicada exuviae are among those materials because they are cast skins that individuals left after molt and are easily collected. In this study, we aim to identify the most efficient extraction method to obtain high quantity and quality of DNA from cicada exuviae. We compared relative DNA yield and purity of six extraction protocols, including both manual protocols and available commercial kits, extracting from four different exoskeleton parts. Furthermore, amplification and sequencing of genomic DNA were evaluated in terms of availability of sequencing sequence at the expected genomic size. Both the choice of protocol and exuvia part significantly affected DNA yield and purity. Only samples that were extracted using the PowerSoil DNA Isolation kit generated gel bands of expected size as well as successful sequencing results. The failed attempts to extract DNA using other protocols could be partially explained by a low DNA yield from cicada exuviae and partly by contamination with humic acids that exist in the soil where cicada nymphs reside before emergence, as shown by spectroscopic measurements. Genomic DNA extracted from cicada exuviae could provide valuable information for species identification, allowing the investigation of genetic diversity across consecutive broods, or spatiotemporal variation among various populations. Consequently, we hope to provide a simple method to acquire pure genomic DNA applicable for multiple research purposes.

Predicting nucleic acid binding interfaces from structural models of proteins

PubMed Central

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2011-01-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767

Critical fluid extraction of Juniperus virginiana L. and bioactivity of extracts against subterranean termites and wood-rot fungi.

Treesearch

F. J. Eller; Carol A. Clausen; Frederick Green; S.L. Taylor

2010-01-01

Eastern red cedar (Juniperus virginiana L.) is an abundant renewable resource and represents a vast potential source of valuable natural products that may serve as natural biocides. Both the wood and needles from J. virginiana were extracted using liquid carbon dioxide (L-CO2) as well as ethanol (EtOH) and the yields determined.Woodblocks were...

Potential for green microalgae to produce hydrogen, pharmaceuticals and other high value products in a combined process.

PubMed

Skjånes, Kari; Rebours, Céline; Lindblad, Peter

2013-06-01

Green microalgae for several decades have been produced for commercial exploitation, with applications ranging from health food for human consumption, aquaculture and animal feed, to coloring agents, cosmetics and others. Several products from green algae which are used today consist of secondary metabolites that can be extracted from the algal biomass. The best known examples are the carotenoids astaxanthin and β-carotene, which are used as coloring agents and for health-promoting purposes. Many species of green algae are able to produce valuable metabolites for different uses; examples are antioxidants, several different carotenoids, polyunsaturated fatty acids, vitamins, anticancer and antiviral drugs. In many cases, these substances are secondary metabolites that are produced when the algae are exposed to stress conditions linked to nutrient deprivation, light intensity, temperature, salinity and pH. In other cases, the metabolites have been detected in algae grown under optimal conditions, and little is known about optimization of the production of each product, or the effects of stress conditions on their production. Some green algae have shown the ability to produce significant amounts of hydrogen gas during sulfur deprivation, a process which is currently studied extensively worldwide. At the moment, the majority of research in this field has focused on the model organism, Chlamydomonas reinhardtii, but other species of green algae also have this ability. Currently there is little information available regarding the possibility for producing hydrogen and other valuable metabolites in the same process. This study aims to explore which stress conditions are known to induce the production of different valuable products in comparison to stress reactions leading to hydrogen production. Wild type species of green microalgae with known ability to produce high amounts of certain valuable metabolites are listed and linked to species with ability to produce hydrogen during general anaerobic conditions, and during sulfur deprivation. Species used today for commercial purposes are also described. This information is analyzed in order to form a basis for selection of wild type species for a future multi-step process, where hydrogen production from solar energy is combined with the production of valuable metabolites and other commercial uses of the algal biomass.

Potential for green microalgae to produce hydrogen, pharmaceuticals and other high value products in a combined process

PubMed Central

2013-01-01

Green microalgae for several decades have been produced for commercial exploitation, with applications ranging from health food for human consumption, aquaculture and animal feed, to coloring agents, cosmetics and others. Several products from green algae which are used today consist of secondary metabolites that can be extracted from the algal biomass. The best known examples are the carotenoids astaxanthin and β-carotene, which are used as coloring agents and for health-promoting purposes. Many species of green algae are able to produce valuable metabolites for different uses; examples are antioxidants, several different carotenoids, polyunsaturated fatty acids, vitamins, anticancer and antiviral drugs. In many cases, these substances are secondary metabolites that are produced when the algae are exposed to stress conditions linked to nutrient deprivation, light intensity, temperature, salinity and pH. In other cases, the metabolites have been detected in algae grown under optimal conditions, and little is known about optimization of the production of each product, or the effects of stress conditions on their production. Some green algae have shown the ability to produce significant amounts of hydrogen gas during sulfur deprivation, a process which is currently studied extensively worldwide. At the moment, the majority of research in this field has focused on the model organism, Chlamydomonas reinhardtii, but other species of green algae also have this ability. Currently there is little information available regarding the possibility for producing hydrogen and other valuable metabolites in the same process. This study aims to explore which stress conditions are known to induce the production of different valuable products in comparison to stress reactions leading to hydrogen production. Wild type species of green microalgae with known ability to produce high amounts of certain valuable metabolites are listed and linked to species with ability to produce hydrogen during general anaerobic conditions, and during sulfur deprivation. Species used today for commercial purposes are also described. This information is analyzed in order to form a basis for selection of wild type species for a future multi-step process, where hydrogen production from solar energy is combined with the production of valuable metabolites and other commercial uses of the algal biomass. PMID:22765907

Surface characterization of cottonseed meal products by SEM, SEM-EDS, XRD and XPS analysis

USDA-ARS?s Scientific Manuscript database

The utilization of cottonseed meal as a valuable industrial feedstock needs to be exploited. We have recently produced water-washed cottonseed meal, total cottonseed protein, sequentially extracted water- and alkali-soluble proteins, and two residues after the total and sequential protein extraction...

Eastern red cedar: critical fluid extraction and bioactivity of extracts

USDA-ARS?s Scientific Manuscript database

Eastern red cedar is an abundant natural resource in the United States. It is valuable for its lumber and cedarwood oil derived from the wood. Cedarwood is generally obtained by steam distillation; however, this process has several disadvantages, including relatively low yields and altered oil chara...

Patient walk detection in hospital room using Microsoft Kinect V2.

PubMed

Liang Liu; Mehrotra, Sanjay

2016-08-01

This paper describes a system using Kinect sensor to detect patient walk automatically in a hospital room setting. The system is especially essential for the case when the patient is alone and the nursing staff is absent. The patient activities are represented by the features extracted from Kinect V2 skeletons. The analysis to the recognized walk could help us to better understand the health situation of the patient and the possible hospital acquired infection (HAI), and provide valuable information to healthcare givers for making a corresponding treatment decision and alteration. The Kinect V2 depth sensor provides the ground truth.

Medicinal plants with promising antileishmanial activity in Iran: a systematic review and meta-analysis.

PubMed

Soosaraei, Masoud; Fakhar, Mahdi; Hosseini Teshnizi, Saeed; Ziaei Hezarjaribi, Hajar; Banimostafavi, Elham Sadat

2017-09-01

Leishmaniasis is a major public health problem worldwide. The aim of the present study was to investigate medicinal plants with anti- Leishmania activity which used in Iran. Data were systematically gathered from five English databases including Ebsco, Science Direct, PubMed, Google Scholar and Scopus, four Persian databases including Magiran, Iran doc, Iran medex and the Scientific Information Database (SID) from 1999 to April 2015. Information obtained included plant family, extraction method, concentrations of extracts, animal models and parasite strains. A total of 68 articles including 188 experiments (140 in vitro and 48 in vivo) between 1999 and 2015, met our eligibility criteria. Thoroughly, 98 types of plants were examined against three genera of Leishmania spp. For the heterogeneity study conducted, it was showed that there was a great deal of variation among studies. Based on random effect, meta-analysis pooled mean of IC50 was obtained 456.64 (95% CI: 396.15, 517.12). The most Iranian plants used as anti-leishmanial activity were Artemisia species , Allium sativum , Achilleamille folium , Peganum harmala and Thymus vulgaris . The present systematic and meta-analysis review provide valuable information about natural products with anti- Leishmania activity, which would be examined in the future experimental and clinical trials and herbal combination therapy.

Monitoring ground subsidence in Shanghai maglev area using two kinds of SAR data

NASA Astrophysics Data System (ADS)

Wu, Jicang; Zhang, Lina; Chen, Jie; Li, Tao

2012-11-01

Shanghai maglev is a very fast traffic tool, so it is very strict with the stability of the roadbed. However, the ground subsidence is a problem in Shanghai because of the poor geological condition and human-induced factors. So it is necessary to monitor ground subsidence in the area along the Shanghai maglev precisely and frequently. Traditionally, a precise levelling method is used to survey along the track. It is expensive and time consuming, and can only get the ground subsidence information on sparse benchmarks. Recently, the small baseline differential SAR technique plays a valuable part in monitoring ground subsidence, which can extract ground subsidence information with high spatial resolution in a wide area. In this paper, L-band ALOS PALSAR data and C-band Envisat ASAR data are used to extract ground subsidence information using the SBAS method in the Shanghai maglev area. The results show that the general pattern of ground subsidence from InSAR processing of two differential bands of SAR images is similar. Both results show that there is no significant ground subsidence on the maglev line. Near the railway line, there are a few places with subsidence rates at about -20 mm/y or even more, such as Chuansha town, the junction of the maglev and Waihuan road.

Identification of research hypotheses and new knowledge from scientific literature.

PubMed

Shardlow, Matthew; Batista-Navarro, Riza; Thompson, Paul; Nawaz, Raheel; McNaught, John; Ananiadou, Sophia

2018-06-25

Text mining (TM) methods have been used extensively to extract relations and events from the literature. In addition, TM techniques have been used to extract various types or dimensions of interpretative information, known as Meta-Knowledge (MK), from the context of relations and events, e.g. negation, speculation, certainty and knowledge type. However, most existing methods have focussed on the extraction of individual dimensions of MK, without investigating how they can be combined to obtain even richer contextual information. In this paper, we describe a novel, supervised method to extract new MK dimensions that encode Research Hypotheses (an author's intended knowledge gain) and New Knowledge (an author's findings). The method incorporates various features, including a combination of simple MK dimensions. We identify previously explored dimensions and then use a random forest to combine these with linguistic features into a classification model. To facilitate evaluation of the model, we have enriched two existing corpora annotated with relations and events, i.e., a subset of the GENIA-MK corpus and the EU-ADR corpus, by adding attributes to encode whether each relation or event corresponds to Research Hypothesis or New Knowledge. In the GENIA-MK corpus, these new attributes complement simpler MK dimensions that had previously been annotated. We show that our approach is able to assign different types of MK dimensions to relations and events with a high degree of accuracy. Firstly, our method is able to improve upon the previously reported state of the art performance for an existing dimension, i.e., Knowledge Type. Secondly, we also demonstrate high F1-score in predicting the new dimensions of Research Hypothesis (GENIA: 0.914, EU-ADR 0.802) and New Knowledge (GENIA: 0.829, EU-ADR 0.836). We have presented a novel approach for predicting New Knowledge and Research Hypothesis, which combines simple MK dimensions to achieve high F1-scores. The extraction of such information is valuable for a number of practical TM applications.

Assessment of Homomorphic Analysis for Human Activity Recognition from Acceleration Signals.

PubMed

Vanrell, Sebastian Rodrigo; Milone, Diego Humberto; Rufiner, Hugo Leonardo

2017-07-03

Unobtrusive activity monitoring can provide valuable information for medical and sports applications. In recent years, human activity recognition has moved to wearable sensors to deal with unconstrained scenarios. Accelerometers are the preferred sensors due to their simplicity and availability. Previous studies have examined several \\azul{classic} techniques for extracting features from acceleration signals, including time-domain, time-frequency, frequency-domain, and other heuristic features. Spectral and temporal features are the preferred ones and they are generally computed from acceleration components, leaving the acceleration magnitude potential unexplored. In this study, based on homomorphic analysis, a new type of feature extraction stage is proposed in order to exploit discriminative activity information present in acceleration signals. Homomorphic analysis can isolate the information about whole body dynamics and translate it into a compact representation, called cepstral coefficients. Experiments have explored several configurations of the proposed features, including size of representation, signals to be used, and fusion with other features. Cepstral features computed from acceleration magnitude obtained one of the highest recognition rates. In addition, a beneficial contribution was found when time-domain and moving pace information was included in the feature vector. Overall, the proposed system achieved a recognition rate of 91.21% on the publicly available SCUT-NAA dataset. To the best of our knowledge, this is the highest recognition rate on this dataset.

Cancer patients on Twitter: a novel patient community on social media.

PubMed

Sugawara, Yuya; Narimatsu, Hiroto; Hozawa, Atsushi; Shao, Li; Otani, Katsumi; Fukao, Akira

2012-12-27

Patients increasingly turn to the Internet for information on medical conditions, including clinical news and treatment options. In recent years, an online patient community has arisen alongside the rapidly expanding world of social media, or "Web 2.0." Twitter provides real-time dissemination of news, information, personal accounts and other details via a highly interactive form of social media, and has become an important online tool for patients. This medium is now considered to play an important role in the modern social community of online, "wired" cancer patients. Fifty-one highly influential "power accounts" belonging to cancer patients were extracted from a dataset of 731 Twitter accounts with cancer terminology in their profiles. In accordance with previously established methodology, "power accounts" were defined as those Twitter accounts with 500 or more followers. We extracted data on the cancer patient (female) with the most followers to study the specific relationships that existed between the user and her followers, and found that the majority of the examined tweets focused on greetings, treatment discussions, and other instances of psychological support. These findings went against our hypothesis that cancer patients' tweets would be centered on the dissemination of medical information and similar "newsy" details. At present, there exists a rapidly evolving network of cancer patients engaged in information exchange via Twitter. This network is valuable in the sharing of psychological support among the cancer community.

Tuberculosis diagnosis support analysis for precarious health information systems.

PubMed

Orjuela-Cañón, Alvaro David; Camargo Mendoza, Jorge Eliécer; Awad García, Carlos Enrique; Vergara Vela, Erika Paola

2018-04-01

Pulmonary tuberculosis is a world emergency for the World Health Organization. Techniques and new diagnosis tools are important to battle this bacterial infection. There have been many advances in all those fields, but in developing countries such as Colombia, where the resources and infrastructure are limited, new fast and less expensive strategies are increasingly needed. Artificial neural networks are computational intelligence techniques that can be used in this kind of problems and offer additional support in the tuberculosis diagnosis process, providing a tool to medical staff to make decisions about management of subjects under suspicious of tuberculosis. A database extracted from 105 subjects with precarious information of people under suspect of pulmonary tuberculosis was used in this study. Data extracted from sex, age, diabetes, homeless, AIDS status and a variable with clinical knowledge from the medical personnel were used. Models based on artificial neural networks were used, exploring supervised learning to detect the disease. Unsupervised learning was used to create three risk groups based on available information. Obtained results are comparable with traditional techniques for detection of tuberculosis, showing advantages such as fast and low implementation costs. Sensitivity of 97% and specificity of 71% where achieved. Used techniques allowed to obtain valuable information that can be useful for physicians who treat the disease in decision making processes, especially under limited infrastructure and data. Copyright © 2018 Elsevier B.V. All rights reserved.

Simultaneous Extraction of Lithium and Hydrogen From Seawater

DTIC Science & Technology

2010-10-26

etc.) References 1. U. Bardi , Extracting minerals from seawater: An energy analysis, Sustainability, 2, 980 (2010). 2. K-S. Chung, J -C. Lee, W...Michele Anderson, ONR Code: 332, michele.anderson1@navy.mil Project Objective: The ultimate goal of the proposed research is to demonstrate a ...novel electrolytic process for extracting Li from seawater, which contains a number of valuable metals (Table1). 1 The technical objectives of this

Informing child welfare policy and practice: using knowledge discovery and data mining technology via a dynamic Web site.

PubMed

Duncan, Dean F; Kum, Hye-Chung; Weigensberg, Elizabeth Caplick; Flair, Kimberly A; Stewart, C Joy

2008-11-01

Proper management and implementation of an effective child welfare agency requires the constant use of information about the experiences and outcomes of children involved in the system, emphasizing the need for comprehensive, timely, and accurate data. In the past 20 years, there have been many advances in technology that can maximize the potential of administrative data to promote better evaluation and management in the field of child welfare. Specifically, this article discusses the use of knowledge discovery and data mining (KDD), which makes it possible to create longitudinal data files from administrative data sources, extract valuable knowledge, and make the information available via a user-friendly public Web site. This article demonstrates a successful project in North Carolina where knowledge discovery and data mining technology was used to develop a comprehensive set of child welfare outcomes available through a public Web site to facilitate information sharing of child welfare data to improve policy and practice.

Biological Properties of Fucoxanthin in Oil Recovered from Two Brown Seaweeds Using Supercritical CO2 Extraction

PubMed Central

Periaswamy Sivagnanam, Saravana; Yin, Shipeng; Choi, Jae Hyung; Park, Yong Beom; Woo, Hee Chul; Chun, Byung Soo

2015-01-01

The bioactive materials in brown seaweeds hold great interest for developing new drugs and healthy foods. The oil content in brown seaweeds (Saccharina japonica and Sargassum horneri) was extracted by using environmentally friendly supercritical CO2 (SC-CO2) with ethanol as a co-solvent in a semi-batch flow extraction process and compared the results with a conventional extraction process using hexane, ethanol, and acetone mixed with methanol (1:1, v/v). The SC-CO2 method was used at a temperature of 45 °C and pressure of 250 bar. The flow rate of CO2 (27 g/min) was constant for the entire extraction period of 2 h. The obtained oil from the brown seaweeds was analyzed to determine their valuable compounds such as fatty acids, phenolic compounds, fucoxanthin and biological properties including antioxidant, antimicrobial, and antihypertension effects. The amounts of fucoxanthin extracted from the SC-CO2 oils of S. japonica and S. horneri were 0.41 ± 0.05 and 0.77 ± 0.07 mg/g, respectively. High antihypertensive activity was detected when using mixed acetone and methanol, whereas the phenolic content and antioxidant property were higher in the oil extracted by SC-CO2. The acetone–methanol mix extracts exhibited better antimicrobial activities than those obtained by other means. Thus, the SC-CO2 extraction process appears to be a good method for obtaining valuable compounds from both brown seaweeds, and showed stronger biological activity than that obtained by the conventional extraction process. PMID:26035021

Biological Properties of Fucoxanthin in Oil Recovered from Two Brown Seaweeds Using Supercritical CO2 Extraction.

PubMed

Sivagnanam, Saravana Periaswamy; Yin, Shipeng; Choi, Jae Hyung; Park, Yong Beom; Woo, Hee Chul; Chun, Byung Soo

2015-05-29

The bioactive materials in brown seaweeds hold great interest for developing new drugs and healthy foods. The oil content in brown seaweeds (Saccharina japonica and Sargassum horneri) was extracted by using environmentally friendly supercritical CO2 (SC-CO2) with ethanol as a co-solvent in a semi-batch flow extraction process and compared the results with a conventional extraction process using hexane, ethanol, and acetone mixed with methanol (1:1, v/v). The SC-CO2 method was used at a temperature of 45 °C and pressure of 250 bar. The flow rate of CO2 (27 g/min) was constant for the entire extraction period of 2 h. The obtained oil from the brown seaweeds was analyzed to determine their valuable compounds such as fatty acids, phenolic compounds, fucoxanthin and biological properties including antioxidant, antimicrobial, and antihypertension effects. The amounts of fucoxanthin extracted from the SC-CO2 oils of S. japonica and S. horneri were 0.41 ± 0.05 and 0.77 ± 0.07 mg/g, respectively. High antihypertensive activity was detected when using mixed acetone and methanol, whereas the phenolic content and antioxidant property were higher in the oil extracted by SC-CO2. The acetone-methanol mix extracts exhibited better antimicrobial activities than those obtained by other means. Thus, the SC-CO2 extraction process appears to be a good method for obtaining valuable compounds from both brown seaweeds, and showed stronger biological activity than that obtained by the conventional extraction process.

Field test for repellency of cedarwood oil and cedrol to little fire ants

USDA-ARS?s Scientific Manuscript database

Eastern red cedars (ERC) (Juniperus virginiana L.) are an abundant renewable resource and represent a vast potential source of valuable natural products that may serve as natural biocides. The aromatic wood can be extracted to obtain cedarwood oil (CWO) and critical carbon dioxide (CO2) extraction o...

Characteristics of extraction and functionality of protein from tomato pomace produced with different industrial processing methods

USDA-ARS?s Scientific Manuscript database

The seeds from tomato pomace, a by-product of tomato processing, contains valuable but underutilized protein with unique functional properties. The objectives of this research were to study the impact of industrial hot and cold break tomato processing on protein extraction from defatted tomato seeds...

Real-time bilinear rotation decoupling in absorptive mode J-spectroscopy: Detecting low-intensity metabolite peak close to high-intensity metabolite peak with convenience.

PubMed

Verma, Ajay; Baishya, Bikash

2016-05-01

"Pure shift" NMR spectra display singlet peak per chemical site. Thus, high resolution is offered at the cost of valuable J-coupling information. In the present work, real-time BIRD (BIlinear Rotation Decoupling) is applied to the absorptive-mode 2D J-spectroscopy to provide pure shift spectrum in the direct dimension and J-coupling information in the indirect dimension. Quite often in metabolomics, proton NMR spectra from complex bio-fluids display tremendous signal overlap. Although conventional J-spectroscopy in principle overcomes this problem by separating the multiplet information from chemical shift information, however, only magnitude mode of the experiment is practical, sacrificing much of the potential high resolution that could be achieved. Few J-spectroscopy methods have been reported so far that produce high-resolution pure shift spectrum along with J-coupling information for crowded spectral regions. In the present work, high-quality J-resolved spectrum from important metabolomic mixture such as tissue extract from rat cortex is demonstrated. Many low-intensity metabolite peaks which are obscured by the broad dispersive tails from high-intensity metabolite peaks in regular magnitude mode J-spectrum can be clearly identified in real-time BIRD J-resolved spectrum. The general practice of removing such spectral overlap is tedious and time-consuming as it involves repeated sample preparation to change the pH of the tissue extract sample and subsequent spectra recording. Copyright © 2016 Elsevier Inc. All rights reserved.

Chlorophyll Fluorescence Analysis of Cyanobacterial Photosynthesis and Acclimation

PubMed Central

Campbell, Douglas; Hurry, Vaughan; Clarke, Adrian K.; Gustafsson, Petter; Öquist, Gunnar

1998-01-01

Cyanobacteria are ecologically important photosynthetic prokaryotes that also serve as popular model organisms for studies of photosynthesis and gene regulation. Both molecular and ecological studies of cyanobacteria benefit from real-time information on photosynthesis and acclimation. Monitoring in vivo chlorophyll fluorescence can provide noninvasive measures of photosynthetic physiology in a wide range of cyanobacteria and cyanolichens and requires only small samples. Cyanobacterial fluorescence patterns are distinct from those of plants, because of key structural and functional properties of cyanobacteria. These include significant fluorescence emission from the light-harvesting phycobiliproteins; large and rapid changes in fluorescence yield (state transitions) which depend on metabolic and environmental conditions; and flexible, overlapping respiratory and photosynthetic electron transport chains. The fluorescence parameters FV/FM, FV′/FM′,qp,qN, NPQ, and φPS II were originally developed to extract information from the fluorescence signals of higher plants. In this review, we consider how the special properties of cyanobacteria can be accommodated and used to extract biologically useful information from cyanobacterial in vivo chlorophyll fluorescence signals. We describe how the pattern of fluorescence yield versus light intensity can be used to predict the acclimated light level for a cyanobacterial population, giving information valuable for both laboratory and field studies of acclimation processes. The size of the change in fluorescence yield during dark-to-light transitions can provide information on respiration and the iron status of the cyanobacteria. Finally, fluorescence parameters can be used to estimate the electron transport rate at the acclimated growth light intensity. PMID:9729605

Real-time bilinear rotation decoupling in absorptive mode J-spectroscopy: Detecting low-intensity metabolite peak close to high-intensity metabolite peak with convenience

NASA Astrophysics Data System (ADS)

Verma, Ajay; Baishya, Bikash

2016-05-01

;Pure shift; NMR spectra display singlet peak per chemical site. Thus, high resolution is offered at the cost of valuable J-coupling information. In the present work, real-time BIRD (BIlinear Rotation Decoupling) is applied to the absorptive-mode 2D J-spectroscopy to provide pure shift spectrum in the direct dimension and J-coupling information in the indirect dimension. Quite often in metabolomics, proton NMR spectra from complex bio-fluids display tremendous signal overlap. Although conventional J-spectroscopy in principle overcomes this problem by separating the multiplet information from chemical shift information, however, only magnitude mode of the experiment is practical, sacrificing much of the potential high resolution that could be achieved. Few J-spectroscopy methods have been reported so far that produce high-resolution pure shift spectrum along with J-coupling information for crowded spectral regions. In the present work, high-quality J-resolved spectrum from important metabolomic mixture such as tissue extract from rat cortex is demonstrated. Many low-intensity metabolite peaks which are obscured by the broad dispersive tails from high-intensity metabolite peaks in regular magnitude mode J-spectrum can be clearly identified in real-time BIRD J-resolved spectrum. The general practice of removing such spectral overlap is tedious and time-consuming as it involves repeated sample preparation to change the pH of the tissue extract sample and subsequent spectra recording.

Multi-Excitonic Quantum Dot Molecules

NASA Astrophysics Data System (ADS)

Scheibner, M.; Stinaff, E. A.; Doty, M. F.; Ware, M. E.; Bracker, A. S.; Gammon, D.; Ponomarev, I. V.; Reinecke, T. L.; Korenev, V. L.

2006-03-01

With the ability to create coupled pairs of quantum dots, the next step towards the realization of semiconductor based quantum information processing devices can be taken. However, so far little knowledge has been gained on these artificial molecules. Our photoluminescence experiments on single InAs/GaAs quantum dot molecules provide the systematics of coupled quantum dots by delineating the spectroscopic features of several key charge configurations in such quantum systems, including X, X^+,X^2+, XX, XX^+ (with X being the neutral exciton). We extract general rules which determine the formation of molecular states of coupled quantum dots. These include the fact that quantum dot molecules provide the possibility to realize various spin configurations and to switch the electron hole exchange interaction on and off by shifting charges inside the molecule. This knowledge will be valuable in developing implementations for quantum information processing.

Automatically identifying health- and clinical-related content in wikipedia.

PubMed

Liu, Feifan; Moosavinasab, Soheil; Agarwal, Shashank; Bennett, Andrew S; Yu, Hong

2013-01-01

Physicians are increasingly using the Internet for finding medical information related to patient care. Wikipedia is a valuable online medical resource to be integrated into existing clinical question answering (QA) systems. On the other hand, Wikipedia contains a full spectrum of world's knowledge and therefore comprises a large partition of non-health-related content, which makes disambiguation more challenging and consequently leads to large overhead for existing systems to effectively filter irrelevant information. To overcome this, we have developed both unsupervised and supervised approaches to identify health-related articles as well as clinically relevant articles. Furthermore, we explored novel features by extracting health related hierarchy from the Wikipedia category network, from which a variety of features were derived and evaluated. Our experiments show promising results and also demonstrate that employing the category hierarchy can effectively improve the system performance.

Experiences in extraction of contact parameters from process-evaluation test-structures

NASA Technical Reports Server (NTRS)

Lieneweg, Udo

1988-01-01

Six-terminal-contact test structures are introduced for characterizing ohmic contacts between a metal and a heavily doped semiconductor layer. Specifically, the six-terminal test structure supplies the additional information needed in order to calculate the transmission length and eventual corrections to the characteristic resistance per unit width due to finite contact length. The essential feature of this test structure is a square contact with four taps in the lower (semiconductor) layer. Every other one of these taps is used for current injection ('front'). From the voltage drop at the opposite tap and the side taps, the 'end' resistance and the 'side' resistances are calculated. The test structures are shown to give valuable information complementary to the common front resistance measurements. The interfacial resistivity is obtained directly after proper correction for flange effects.

Secure VM for Monitoring Industrial Process Controllers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Dipankar; Ali, Mohammad Hassan; Abercrombie, Robert K

2011-01-01

In this paper, we examine the biological immune system as an autonomic system for self-protection, which has evolved over millions of years probably through extensive redesigning, testing, tuning and optimization process. The powerful information processing capabilities of the immune system, such as feature extraction, pattern recognition, learning, memory, and its distributive nature provide rich metaphors for its artificial counterpart. Our study focuses on building an autonomic defense system, using some immunological metaphors for information gathering, analyzing, decision making and launching threat and attack responses. In order to detection Stuxnet like malware, we propose to include a secure VM (or dedicatedmore » host) to the SCADA Network to monitor behavior and all software updates. This on-going research effort is not to mimic the nature but to explore and learn valuable lessons useful for self-adaptive cyber defense systems.« less

Device for Extracting Flavors and Fragrances

NASA Technical Reports Server (NTRS)

Chang, F. R.

1986-01-01

Machine for making coffee and tea in weightless environment may prove even more valuable on Earth as general extraction apparatus. Zero-gravity beverage maker uses piston instead of gravity to move hot water and beverage from one chamber to other and dispense beverage. Machine functions like conventional coffeemaker during part of operating cycle and includes additional features that enable operation not only in zero gravity but also extraction under pressure in presence or absence of gravity.

Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging.

PubMed

Falahati, Farshad; Westman, Eric; Simmons, Andrew

2014-01-01

Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in medical imaging and medical image analysis have provided a means to generate and extract valuable neuroimaging information. Automatic classification techniques provide tools to analyze this information and observe inherent disease-related patterns in the data. In particular, these classifiers have been used to discriminate AD patients from healthy control subjects and to predict conversion from mild cognitive impairment to AD. In this paper, recent studies are reviewed that have used machine learning and multivariate analysis in the field of AD research. The main focus is on studies that used structural magnetic resonance imaging (MRI), but studies that included positron emission tomography and cerebrospinal fluid biomarkers in addition to MRI are also considered. A wide variety of materials and methods has been employed in different studies, resulting in a range of different outcomes. Influential factors such as classifiers, feature extraction algorithms, feature selection methods, validation approaches, and cohort properties are reviewed, as well as key MRI-based and multi-modal based studies. Current and future trends are discussed.

NeuroElectro: a window to the world's neuron electrophysiology data

PubMed Central

Tripathy, Shreejoy J.; Savitskaya, Judith; Burton, Shawn D.; Urban, Nathaniel N.; Gerkin, Richard C.

2014-01-01

The behavior of neural circuits is determined largely by the electrophysiological properties of the neurons they contain. Understanding the relationships of these properties requires the ability to first identify and catalog each property. However, information about such properties is largely locked away in decades of closed-access journal articles with heterogeneous conventions for reporting results, making it difficult to utilize the underlying data. We solve this problem through the NeuroElectro project: a Python library, RESTful API, and web application (at http://neuroelectro.org) for the extraction, visualization, and summarization of published data on neurons' electrophysiological properties. Information is organized both by neuron type (using neuron definitions provided by NeuroLex) and by electrophysiological property (using a newly developed ontology). We describe the techniques and challenges associated with the automated extraction of tabular electrophysiological data and methodological metadata from journal articles. We further discuss strategies for how to best combine, normalize and organize data across these heterogeneous sources. NeuroElectro is a valuable resource for experimental physiologists attempting to supplement their own data, for computational modelers looking to constrain their model parameters, and for theoreticians searching for undiscovered relationships among neurons and their properties. PMID:24808858

Improved Proteomic Analysis Following Trichloroacetic Acid Extraction of Bacillus anthracis Spore Proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaiser, Brooke LD; Wunschel, David S.; Sydor, Michael A.

2015-08-07

Proteomic analysis of bacterial samples provides valuable information about cellular responses and functions under different environmental pressures. Proteomic analysis is dependent upon efficient extraction of proteins from bacterial samples without introducing bias toward extraction of particular protein classes. While no single method can recover 100% of the bacterial proteins, selected protocols can improve overall protein isolation, peptide recovery, or enrich for certain classes of proteins. The method presented here is technically simple and does not require specialized equipment such as a mechanical disrupter. Our data reveal that for particularly challenging samples, such as B. anthracis Sterne spores, trichloroacetic acid extractionmore » improved the number of proteins identified within a sample compared to bead beating (714 vs 660, respectively). Further, TCA extraction enriched for 103 known spore specific proteins whereas bead beating resulted in 49 unique proteins. Analysis of C. botulinum samples grown to 5 days, composed of vegetative biomass and spores, showed a similar trend with improved protein yields and identification using our method compared to bead beating. Interestingly, easily lysed samples, such as B. anthracis vegetative cells, were equally as effectively processed via TCA and bead beating, but TCA extraction remains the easiest and most cost effective option. As with all assays, supplemental methods such as implementation of an alternative preparation method may provide additional insight to the protein biology of the bacteria being studied.« less

Miscanthus x giganteus bark organosolv fractionation: fate of lipophilic components and formation of valuable phenolic byproducts.

PubMed

Villaverde, Juan José; De Vega, Alberto; Ligero, Pablo; Freire, Carmen S R; Neto, Carlos Pascoal; Silvestre, Armando J D

2010-07-28

The behavior of Miscanthus x giganteus bark lipophilic extractives during three acid organosolv pulping processes (Acetosolv, formic acid fractionation, and Milox) was investigated. It was demonstrated that nearly 90% of the lipophilic extractives were removed from pulps by either dissolution in the organosolv liquors (fatty acids and alcohols) or extensive degradation (sterols). The organosolv liquors were found to be rich in vanillin, syringaldehyde, and ferulic, vanillic, and p-coumaric acids. The Acetosolv fractionation process was found to be the most efficient in the removal of lipophilic components from pulps, and it was also the process that generated higher amounts of valuable monomeric phenolic compounds that could be exploited within the biorefinery context.

A Cleaner Process for Selective Recovery of Valuable Metals from Electronic Waste of Complex Mixtures of End-of-Life Electronic Products.

PubMed

Sun, Zhi; Xiao, Y; Sietsma, J; Agterhuis, H; Yang, Y

2015-07-07

In recent years, recovery of metals from electronic waste within the European Union has become increasingly important due to potential supply risk of strategic raw material and environmental concerns. Electronic waste, especially a mixture of end-of-life electronic products from a variety of sources, is of inherently high complexity in composition, phase, and physiochemical properties. In this research, a closed-loop hydrometallurgical process was developed to recover valuable metals, i.e., copper and precious metals, from an industrially processed information and communication technology waste. A two-stage leaching design of this process was adopted in order to selectively extract copper and enrich precious metals. It was found that the recovery efficiency and extraction selectivity of copper both reached more than 95% by using ammonia-based leaching solutions. A new electrodeposition process has been proven feasible with 90% current efficiency during copper recovery, and the copper purity can reach 99.8 wt %. The residue from the first-stage leaching was screened into coarse and fine fractions. The coarse fraction was returned to be releached for further copper recovery. The fine fraction was treated in the second-stage leaching using sulfuric acid to further concentrate precious metals, which could achieve a 100% increase in their concentrations in the residue with negligible loss into the leaching solution. By a combination of different leaching steps and proper physical separation of light materials, this process can achieve closed-loop recycling of the waste with significant efficiency.

Thrombus segmentation by texture dynamics from microscopic image sequences

NASA Astrophysics Data System (ADS)

Brieu, Nicolas; Serbanovic-Canic, Jovana; Cvejic, Ana; Stemple, Derek; Ouwehand, Willem; Navab, Nassir; Groher, Martin

2010-03-01

The genetic factors of thrombosis are commonly explored by microscopically imaging the coagulation of blood cells induced by injuring a vessel of mice or of zebrafish mutants. The latter species is particularly interesting since skin transparency permits to non-invasively acquire microscopic images of the scene with a CCD camera and to estimate the parameters characterizing the thrombus development. These parameters are currently determined by manual outlining, which is both error prone and extremely time consuming. Even though a technique for automatic thrombus extraction would be highly valuable for gene analysts, little work can be found, which is mainly due to very low image contrast and spurious structures. In this work, we propose to semi-automatically segment the thrombus over time from microscopic image sequences of wild-type zebrafish larvae. To compensate the lack of valuable spatial information, our main idea consists of exploiting the temporal information by modeling the variations of the pixel intensities over successive temporal windows with a linear Markov-based dynamic texture formalization. We then derive an image from the estimated model parameters, which represents the probability of a pixel to belong to the thrombus. We employ this probability image to accurately estimate the thrombus position via an active contour segmentation incorporating also prior and spatial information of the underlying intensity images. The performance of our approach is tested on three microscopic image sequences. We show that the thrombus is accurately tracked over time in each sequence if the respective parameters controlling prior influence and contour stiffness are correctly chosen.

Prognostic value of tissue-type plasminogen activator (tPA) and its complex with the type-1 inhibitor (PAI-1) in breast cancer

PubMed Central

Witte, J H de; Sweep, C G J; Klijn, J G M; Grebenschikov, N; Peters, H A; Look, M P; Tienoven, ThH van; Heuvel, J J T M; Vries, J Bolt-De; Benraad, ThJ; Foekens, J A

1999-01-01

The prognostic value of tissue-type plasminogen activator (tPA) measured in samples derived from 865 patients with primary breast cancer using a recently developed enzyme-linked immunosorbent assay (ELISA) was evaluated. Since the assay could easily be adapted to the assessment of the complex of tPA with its type-1 inhibitor (PAI-1), it was investigated whether the tPA:PAI-1 complex also provides prognostic information. To this end, cytosolic extracts and corresponding detergent extracts of 100 000 g pellets obtained after ultracentrifugation when preparing the cytosolic fractions for routine steroid hormone receptor determination were assayed. Statistically significant correlations were found between the cytosolic levels and those determined in the pellet extracts (Spearman correlation coefficient rs = 0.75, P < 0.001 for tPA and r = 0.50, P < 0.001 for tPA:PAI-1 complex). In both Cox univariate and multivariate analysis elevated levels of (total) tPA determined in the pellet extracts, but not in cytosols, were associated with prolonged relapse-free (RFS) and overall survival (OS). In contrast, high levels of the tPA:PAI-1 complex measured in cytosols, but not in the pellet extracts, were associated with a poor RFS and OS. The prognostic information provided by the cytosolic tPA:PAI-1 complex was comparable to that provided by cytosolic (total) PAI-1. Furthermore, the estimated levels of free, uncomplexed tPA and PAI-1, in cytosols and in pellet extracts, were related to patient prognosis in a similar way as the (total) levels of tPA and PAI-1 respectively. Determination of specific forms of components of the plasminogen activation system, i.e. tPA:PAI-1 complex and free, uncomplexed tPA and/or PAI-1, may be considered a useful adjunct to the analyses of the separate components (tPA and/or PAI-1) and provide valuable additional prognostic information with respect to survival of breast cancer patients. © 1999 Cancer Research Campaign PMID:10390010

Ultra-high performance liquid chromatography coupled to mass spectrometry applied to the identification of valuable phenolic compounds from Eucalyptus wood.

PubMed

Santos, Sónia A O; Vilela, Carla; Freire, Carmen S R; Neto, Carlos Pascoal; Silvestre, Armando J D

2013-11-01

Ultra-high performance liquid chromatography (UHPLC) was applied for the first time in the analysis of wood extracts. The potential of this technique coupled to ion trap mass spectrometry in the rapid and effective detection and identification of bioactive components in complex vegetal samples was demonstrated. Several dozens of compounds were detected in less than 30min of analysis time, corresponding to more than 3-fold reduction in time, when compared to conventional HPLC analysis of similar extracts. The phenolic chemical composition of Eucalyptus grandis, Eucalyptus urograndis (E. grandis×E. urophylla) and Eucalyptus maidenii wood extracts was assessed for the first time, with the identification of 51 phenolic compounds in the three wood extracts. Twenty of these compounds are reported for the first time as Eucalyptus genus components. Ellagic acid and ellagic acid-pentoside are the major components in all extracts, followed by gallic and quinic acids in E. grandis and E. urograndis and ellagic acid-pentoside isomer, isorhamnetin-hexoside and gallic acid in E. maidenii. The antioxidant scavenging activity of the extracts was evaluated, with E. grandis wood extract showing the lowest IC50 value. Moreover, the antioxidant activity of these extracts was higher than that of the commercial antioxidant BHT and of those of the corresponding bark extracts. These results, together with the phenolic content values, open good perspectives for the exploitation of these renewable resources as a source of valuable phenolic compounds. Copyright © 2013 Elsevier B.V. All rights reserved.

Identification of the traditional Tibetan medicine "Shaji" and their different extracts through tri-step infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Yue; Li, Jingyi; Fan, Gang; Sun, Suqin; Zhang, Yuxin; Zhang, Yi; Tu, Ya

2016-11-01

Hippophae rhamnoides subsp. sinensis Rousi, Hippophae gyantsensis (Rousi) Y. S. Lian, Hippophae neurocarpa S. W. Liu & T. N. He and Hippophae tibetana Schlechtendal are typically used under one name "Shaji", to treat cardiovascular diseases and lung disorders in Tibetan medicine (TM). A complete set of infrared (IR) macro-fingerprints of these four Hippophae species should be characterized and compared simply, accurately, and in detail for identification. In the present study, tri-step IR spectroscopy, which included Fourier transform IR (FT-IR) spectroscopy, second derivative IR (SD-IR) spectroscopy and two-dimensional correlation IR (2D-IR) spectroscopy, was employed to discriminate the four Hippophae species and their corresponding extracts using different solvents. The relevant spectra exhibited the holistic chemical compositions and variations. Flavonoids, fatty acids and sugars were found to be the main chemical components. Characteristic peak positions, intensities and shapes derived from FT-IR, SD-IR and 2D-IR spectra provided valuable information for sample discrimination. Principal component analysis (PCA) of spectral differences was performed to illustrate the objective identification. Results showed that the species and their extracts can be clearly distinguished. Thus, a quick, precise and effective tri-step IR spectroscopy combined with PCA can be applied to identify and discriminate medicinal materials and their extracts in TM research.

Predicting nucleic acid binding interfaces from structural models of proteins.

PubMed

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Metabolic fate of cardiac glycosides and flavonoids upon fermentation of aqueous sea squill (Drimia maritima L.) extracts.

PubMed

Knittel, Diana N; Stintzing, Florian C; Kammerer, Dietmar R

2015-06-10

Sea squill (Drimia maritima L.) extracts have been used for centuries for the medical treatment of heart diseases. A procedure for the preparation of Drimia extracts applied for such purposes comprising a fermentation step is described in the German Homoeopathic Pharmacopoeia (GHP). However, little is known about the secondary metabolite profile of such extracts and the fate of these components upon processing and storage. Thus, in the present study sea squill extracts were monitored during fermentation and storage by HPLC-DAD-MS(n) and GC-MS to characterise and quantitate individual cardiac glycosides and phenolic compounds. For this purpose, a previously established HPLC method for the separation and quantitation of pharmacologically relevant cardiac glycosides (bufadienolides) was validated. Within 12 months of storage, total bufadienolide contents decreased by about 50%, which was attributed to microbial and plant enzyme activities. The metabolisation and degradation rates of individual bufadienolide glycosides significantly differed, which was attributed to differing structures of the aglycones. Further degradation of bufadienolide aglycones was also observed. Besides reactions well known from human metabolism studies, dehydration of individual compounds was monitored. Quantitatively predominating flavonoids were also metabolised throughout the fermentation process. The present study provides valuable information about the profile and stability of individual cardiac glycosides and phenolic compounds in fermented Drimia extracts prepared for medical applications, and expands the knowledge of cardiac glycoside conversion upon microbial fermentation. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of Antioxidant Properties, Phenolic Compounds, Anthelmintic, and Cytotoxic Activities of Various Extracts Isolated from Nepeta cadmea: An Endemic Plant for Turkey.

PubMed

Kaska, Arzu; Deniz, Nahide; Çiçek, Mehmet; Mammadov, Ramazan

2018-05-10

Nepeta cadmea Boiss. is a species endemic to Turkey that belongs to the Nepeta genus. Several species of this genus are used in folk medicine. This study was designed to investigate the phenolic compounds, antioxidant, anthelmintic, and cytotoxic activities of various extracts (ethanol, methanol, acetone, and water) of N. cadmea. The antioxidant activities of these extracts were analyzed using scavenging methods (DPPH, ABTS, and H 2 O 2 scavenging activity), the β-carotene/linoleic acid test system, the phosphomolybdenum method, and metal chelating activity. Among the 4 different extracts of N. cadmea that were evaluated, the water extract showed the highest amount of radical scavenging (DPPH, 25.54 μg/mL and ABTS, 14.51 μg/mL) and antioxidant activities (β-carotene, 86.91%). In the metal chelating and H 2 O 2 scavenging activities, the acetone extract was statistically different from the other extracts. For the phosphomolybdenum method, the antioxidant capacity of the extracts was in the range of 8.15 to 80.40 μg/mg. The phenolic content of the ethanol extract was examined using HPLC and determined some phenolics: epicatechin, chlorogenic, and caffeic acids. With regard to the anthelmintic properties, dose-dependent activity was observed in each of the extracts of N. cadmea. All the extracts exhibited high cytotoxic activities. The results will provide additional information for further studies on the biological activities of N. cadmea, while also helping us to understand the importance of this species. Furthermore, based on the results obtained, N. cadmea may be considered as a potentially useful supplement for the human diet, as well as a natural antioxidant for medicinal applications. The plants of the Nepeta genus have been extensively used as traditional herbal medicines. Nepeta cadmea Boiss., one of the species belonging to the Nepeta genus, is a species endemic to Turkey. In our study, we demonstrated the antioxidant capacities, total phenolic, flavonoid, tannin content, anthelmintic, and cytotoxic activities of various extracts of Nepeta cadmea. The present study could well supply valuable data for future investigations and further information on the potential use of this endemic plant for humans, in both dietary and pharmacological applications. © 2018 Institute of Food Technologists®.

Supercritical CO2 Extraction of Rice Bran Oil -the Technology, Manufacture, and Applications.

PubMed

Sookwong, Phumon; Mahatheeranont, Sugunya

2017-06-01

Rice bran is a good source of nutrients that have large amounts of phytochemicals and antioxidants. Conventional rice bran oil production requires many processes that may deteriorate and degrade these valuable substances. Supercritical CO 2 extraction is a green alternative method for producing rice bran oil. This work reviews production of rice bran oil by supercritical carbon dioxide (SC-CO 2 ) extraction. In addition, the usefulness and advantages of SC-CO 2 extracted rice bran oil for edible oil and health purpose is also described.

Pediatric Brain Extraction Using Learning-based Meta-algorithm

PubMed Central

Shi, Feng; Wang, Li; Dai, Yakang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2012-01-01

Magnetic resonance imaging of pediatric brain provides valuable information for early brain development studies. Automated brain extraction is challenging due to the small brain size and dynamic change of tissue contrast in the developing brains. In this paper, we propose a novel Learning Algorithm for Brain Extraction and Labeling (LABEL) specially for the pediatric MR brain images. The idea is to perform multiple complementary brain extractions on a given testing image by using a meta-algorithm, including BET and BSE, where the parameters of each run of the meta-algorithm are effectively learned from the training data. Also, the representative subjects are selected as exemplars and used to guide brain extraction of new subjects in different age groups. We further develop a level-set based fusion method to combine multiple brain extractions together with a closed smooth surface for obtaining the final extraction. The proposed method has been extensively evaluated in subjects of three representative age groups, such as neonate (less than 2 months), infant (1–2 years), and child (5–18 years). Experimental results show that, with 45 subjects for training (15 neonates, 15 infant, and 15 children), the proposed method can produce more accurate brain extraction results on 246 testing subjects (75 neonates, 126 infants, and 45 children), i.e., at average Jaccard Index of 0.953, compared to those by BET (0.918), BSE (0.902), ROBEX (0.901), GCUT (0.856), and other fusion methods such as Majority Voting (0.919) and STAPLE (0.941). Along with the largely-improved computational efficiency, the proposed method demonstrates its ability of automated brain extraction for pediatric MR images in a large age range. PMID:22634859

A Review of Botany and Pharmacological Effect and Chemical Composition of Echinophora Species Growing in Iran.

PubMed

Hosseini, Zohreh; Lorigooini, Zahra; Rafieian-Kopaei, Mahmoud; Shirmardi, Hamzeh Ali; Solati, Kamal

2017-01-01

This review was conducted to investigate the botany, phytochemistry, and pharmacological properties of Echinophora species. The information of this review was obtained by searching for keywords Apiaceae , Echinophora , pharmacological effects, and traditional and modern medicine in scientific articles and books published in search engines Scopus, Google Scholar, Science Direct, PubMed, and Web of Science. The traditional uses of Echinophora and the existence of valuable phytochemicals in the plant have led to isolation and drug discovery of natural medicines such as antibiotic, analgesics, and anticancer drugs, and the beneficial effects of these plants can widely be used in healthcare. Echinophora species are medicinal and aromatic plants that are belong to Apiaceae family. This genus have four species in Iran. The botany, geographical distribution, traditional and pharmacological effects of Echinophora genus were described. Also, the major chemical constituents of the essential oil and extract of different species of Echinophora that have been reported. Overall, the existence of valuable phytochemicals purpose Echinophora species as novel candidate to isolation and drug discovery of natural medicines such as antibiotic, analgesics, and anticancer drugs.

Lipid Composition of Oil Extracted from Wasted Norway Lobster (Nephrops norvegicus) Heads and Comparison with Oil Extracted from Antarctic Krill (Euphasia superba).

PubMed

Albalat, Amaya; Nadler, Lauren E; Foo, Nicholas; Dick, James R; Watts, Andrew J R; Philp, Heather; Neil, Douglas M; Monroig, Oscar

2016-12-01

In the UK, the Norway lobster ( Nephrops norvegicus ) supports its most important shellfish fishery. Nephrops are sold either whole, or as "tails-only" for the scampi trade. In the "tailing" process, the "head" (cephalothorax) is discarded as waste. A smaller crustacean species, the Antarctic krill Euphasia superba , represents an economically valuable industry, as its extractable oil is sold as a human dietary supplement. The aim of this study was to determine the amount and composition of the oil contained in discarded Nephrops heads and to compare its composition to the oil extracted from krill. Differences due to Geographical variation and seasonal patterns in the amount and composition of lipid were also noted. Results indicated that Nephrops head waste samples collected from more southern locations in Scotland (Clyde Sea area) contained higher levels of oil when compared to samples collected from northern locations in Iceland. Moreover, seasonal differences within the Clyde Sea area in Scotland were also observed, with oil extracted from Nephrops head waste peaking at around 11.5% during the summer months when larger and more mature females were caught by trawl. At this time of the year, the valuable fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) accounted for around 23% of the total fatty acid content in oil extracted from Nephrops head waste. A seasonal effect on EPA content was found, with higher levels obtained in the summer, while no trend was found in DHA percentages. Finally, oil from Nephrops head waste contained a higher proportion of EPA and DHA than krill oil but these fatty acids were more abundantly linked to the neutral lipids rather to than polar lipids. The characterization of lipid that could be extracted from Nephrops head waste should be seen as a first step for the commercial use of a valuable resource currently wasted. This approach is extremely relevant given the current limited supply of EPA and DHA and changes in the Common Fisheries Policy.

Lipid Composition of Oil Extracted from Wasted Norway Lobster (Nephrops norvegicus) Heads and Comparison with Oil Extracted from Antarctic Krill (Euphasia superba)

PubMed Central

Albalat, Amaya; Nadler, Lauren E.; Foo, Nicholas; Dick, James R.; Watts, Andrew J. R.; Philp, Heather; Neil, Douglas M.; Monroig, Oscar

2016-01-01

In the UK, the Norway lobster (Nephrops norvegicus) supports its most important shellfish fishery. Nephrops are sold either whole, or as “tails-only” for the scampi trade. In the “tailing” process, the “head” (cephalothorax) is discarded as waste. A smaller crustacean species, the Antarctic krill Euphasia superba, represents an economically valuable industry, as its extractable oil is sold as a human dietary supplement. The aim of this study was to determine the amount and composition of the oil contained in discarded Nephrops heads and to compare its composition to the oil extracted from krill. Differences due to Geographical variation and seasonal patterns in the amount and composition of lipid were also noted. Results indicated that Nephrops head waste samples collected from more southern locations in Scotland (Clyde Sea area) contained higher levels of oil when compared to samples collected from northern locations in Iceland. Moreover, seasonal differences within the Clyde Sea area in Scotland were also observed, with oil extracted from Nephrops head waste peaking at around 11.5% during the summer months when larger and more mature females were caught by trawl. At this time of the year, the valuable fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) accounted for around 23% of the total fatty acid content in oil extracted from Nephrops head waste. A seasonal effect on EPA content was found, with higher levels obtained in the summer, while no trend was found in DHA percentages. Finally, oil from Nephrops head waste contained a higher proportion of EPA and DHA than krill oil but these fatty acids were more abundantly linked to the neutral lipids rather to than polar lipids. The characterization of lipid that could be extracted from Nephrops head waste should be seen as a first step for the commercial use of a valuable resource currently wasted. This approach is extremely relevant given the current limited supply of EPA and DHA and changes in the Common Fisheries Policy. PMID:27916863

Bioleaching mechanism of Zn, Pb, In, Ag, Cd and As from Pb/Zn smelting slag by autotrophic bacteria.

PubMed

Wang, Jia; Huang, Qifei; Li, Ting; Xin, Baoping; Chen, Shi; Guo, Xingming; Liu, Changhao; Li, Yuping

2015-08-15

A few studies have focused on release of valuable/toxic metals from Pb/Zn smelting slag by heterotrophic bioleaching using expensive yeast extract as an energy source. The high leaching cost greatly limits the practical potential of the method. In this work, autotrophic bioleaching using cheap sulfur or/and pyrite as energy matter was firstly applied to tackle the smelting slag and the bioleaching mechanisms were explained. The results indicated autotrophic bioleaching can solubilize valuable/toxic metals from slag, yielding maximum extraction efficiencies of 90% for Zn, 86% for Cd and 71% for In, although the extraction efficiencies of Pb, As and Ag were poor. The bioleaching performance of Zn, Cd and Pb was independent of leaching system, and leaching mechanism was acid dissolution. A maximum efficiency of 25% for As was achieved by acid dissolution in sulfursulfur oxidizing bacteria (S-SOB), but the formation of FeAsO4 reduced extraction efficiency in mixed energy source - mixed culture (MS-MC). Combined works of acid dissolution and Fe(3+) oxidation in MS-MC was responsible for the highest extraction efficiency of 71% for In. Ag was present in the slag as refractory AgPb4(AsO4)3 and AgFe2S3, so extraction did not occur. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiplexed, quantitative, and targeted metabolite profiling by LC-MS/MRM.

PubMed

Wei, Ru; Li, Guodong; Seymour, Albert B

2014-01-01

Targeted metabolomics, which focuses on a subset of known metabolites representative of biologically relevant metabolic pathways, is a valuable tool to discover biomarkers and link disease phenotypes to underlying mechanisms or therapeutic modes of action. A key advantage of targeted metabolomics, compared to discovery metabolomics, is its immediate readiness for extracting biological information derived from known metabolites and quantitative measurements. However, simultaneously analyzing hundreds of endogenous metabolites presents a challenge due to their diverse chemical structures and properties. Here we report a method which combines different chromatographic separation conditions, optimal ionization polarities, and the most sensitive triple-quadrupole MS-based data acquisition mode, multiple reaction monitoring (MRM), to quantitatively profile 205 endogenous metabolites in 10 min.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-06-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Study into the identification of irradiation ground paprika

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beczner, J.; Farkas, J.; Kiss, I.

From international colloquium: the identification of irradiated foodstuffs; Karlsruhe, Germany (24 Oct 1973). Several methods for the demonstration of irradiation in ground paprika were tested. In carbonyl compounds extracted by steam distillation unambiguous changes, which might have served as a basis for detecting irradiation, were not observed. Derivatography did not prove suitable either. On the basis of the size of ESR signal, the control sample and the irradiated one could be distinguished 2 to 3 weeks after irradiation. After a longer storage period, the size of the signal is irrelevant. Further study of the shape of the ESR signals maymore » yield valuable information in experiments on the demonstration of irradiation. (GE)« less

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-04-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

A Novel Higher Order Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Xu, Shuxiang

2010-05-01

In this paper a new Higher Order Neural Network (HONN) model is introduced and applied in several data mining tasks. Data Mining extracts hidden patterns and valuable information from large databases. A hyperbolic tangent function is used as the neuron activation function for the new HONN model. Experiments are conducted to demonstrate the advantages and disadvantages of the new HONN model, when compared with several conventional Artificial Neural Network (ANN) models: Feedforward ANN with the sigmoid activation function; Feedforward ANN with the hyperbolic tangent activation function; and Radial Basis Function (RBF) ANN with the Gaussian activation function. The experimental results seem to suggest that the new HONN holds higher generalization capability as well as abilities in handling missing data.

A new linoleiyl arabinopyranoside from the bark of Bauhinia racemosa Lam and a new flavonoidal glycoside from the leaves of Cordia dichotoma Linn.

PubMed

Rahman, Md Azizur; Akhtar, Juber

2016-10-01

Phytochemical investigation is very valuable for the ethnomedicinally important plants Bauhinia racemosa Lam (BR) and Cordia dichotoma Linn (CD) used for the cure of variety of ailments. This study was thus designed for phytochemical investigation of BR bark and CD leaves. Phytoconstituents were isolated from the methanolic extracts of the plants by column chromatography using silica gel as stationary phase. The structures had been established on the basis of their physicochemical and spectral data, i.e. IR, (1)H NMR, (13)C NMR and MS. Elution of the columns with different solvents furnished six compounds (1-6) from the methanolic extract of BR bark and three compounds (7-9) from the methanolic extract of CD leaves which were structurally elucidated. The present phytochemical investigation reported several new compounds useful in increasing the existing knowledge of phytoconstituents from BR bark and CD leaves which is very valuable, as these drugs are used in the Indian traditional systems of medicine.

Deep cleaning of a metallurgical zinc leaching residue and recovery of valuable metals

NASA Astrophysics Data System (ADS)

Xing, Peng; Ma, Bao-zhong; Zeng, Peng; Wang, Cheng-yan; Wang, Ling; Zhang, Yong-lu; Chen, Yong-qiang; Wang, Shuo; Wang, Qiu-yin

2017-11-01

Huge quantities of zinc leaching residues (ZLRs) generated from zinc production are dumped continuously around the world and pose a potential environmental threat because of their considerable amounts of entrained heavy metals (mainly lead). Most ZLRs have not been properly treated and the valuable metals in them have not yet been effectively recovered. Herein, the deep cleaning of a ZLR and recovery of valuable metals via a hydrometallurgical route were investigated. The cleaning process consists of two essential stages: acid leaching followed by calcium chloride leaching. The optimum conditions for extracting zinc, copper, and indium by acid leaching were a sulfuric acid concentration of 200 g·L-1, a liquid/solid ratio of 4:1 (mL/g), a leaching time of 2 h, and a temperature of 90°C. For lead and silver extractions, the optimum conditions were a calcium chloride concentration of 400 g·L-1, a pH value of 1.0, a leaching time of 1 h, and a temperature of 30°C. After calcium chloride leaching, silver and lead were extracted out and the lead was finally recovered as electrolytic lead by electrowinning. The anglesite phase, which poses the greatest potential environmental hazard, was removed from the ZLR after deep cleaning, thus reducing the cost of environmental management of ZLRs. The treatment of chlorine and spent electrolyte generated in the process was discussed.

Influence of biochar on heavy metals and microbial community during composting of river sediment with agricultural wastes.

PubMed

Chen, Yaoning; Liu, Yao; Li, Yuanping; Wu, Yanxin; Chen, Yanrong; Zeng, Guangming; Zhang, Jiachao; Li, Hui

2017-11-01

Studies were performed to evaluate influence of biochar addition on physico-chemical process, heavy metals transformation and bacterial community diversity during composting of sediment with agricultural wastes. Simultaneously, the relationships between those parameters including heavy metals and bacterial community compositions were evaluated by redundancy analysis (RDA). The results show that the extraction efficiency of DTPA extractable heavy metals decreased in both piles, and reduced more in pile with biochar addition about 0.1-2.96%. Biochar addition dramatically influenced the bacterial community structure during the composting process. Moreover, the bacterial community composition was significantly correlated with C/N ratio, water soluble carbon (WSC), and organic matter (OM) (P<0.05) in pile with biochar addition; while significantly correlated with temperature, WSC, and C/N ratio in pile which was free of biochar. This study would provide some valuable information for improving the composting for disposal of river sediment with heavy metals contamination. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology (RSM)*

PubMed Central

Zhang, Yun-jian; Li, Qiang; Zhang, Yu-xiu; Wang, Dan; Xing, Jian-min

2012-01-01

Succinic acid is considered as an important platform chemical. Succinic acid fermentation with Actinobacillus succinogenes strain BE-1 was optimized by central composite design (CCD) using a response surface methodology (RSM). The optimized production of succinic acid was predicted and the interactive effects between glucose, yeast extract, and magnesium carbonate were investigated. As a result, a model for predicting the concentration of succinic acid production was developed. The accuracy of the model was confirmed by the analysis of variance (ANOVA), and the validity was further proved by verification experiments showing that percentage errors between actual and predicted values varied from 3.02% to 6.38%. In addition, it was observed that the interactive effect between yeast extract and magnesium carbonate was statistically significant. In conclusion, RSM is an effective and useful method for optimizing the medium components and investigating the interactive effects, and can provide valuable information for succinic acid scale-up fermentation using A. succinogenes strain BE-1. PMID:22302423

The characteristics of dissolved organic matter (DOM) in storm sewer sediments and the binding interaction with Cu(II) in four typical regions in Beijing, China.

PubMed

Zhang, Ziyang; Li, Kun; Zhang, Xiaoran; Li, Haiyan

2017-07-01

In this work, dissolved organic matter (DOM) was extracted from storm sewer sediments collected in four typical regions (residential, campus, traffic and business regions) in Beijing, China. The basic characteristics of DOM were analyzed by UV-visible spectroscopy (UV-Vis), excitation-emission matrix Fluorescence Spectroscopy and Fourier Transform Infrared Spectroscopy. Furthermore, the complexation between DOM and Cu(II) were investigated. The results showed that there were large amount of aromatic structure in the DOM extracted from storm sewer sediments. The microbial activities had also made a contribution to the DOM in storm sewer sediments. The composition of DOM influenced the complexing capacity of Cu(II) greatly, which may be attributed to the protein-like and humic-like substances in storm sewer sediments. This study demonstrated valuable information on the structure present in the DOM of storm sewer sediments and provided new insight for exploring the relationship between DOM and co-existing heavy metals in storm sewer sediments.

Rapid identification and simultaneous analysis of multiple constituents from Rheum tanguticum Maxim. ex Balf. by UPLC/Q-TOF-MS.

PubMed

Gao, Liang-Liang; Guo, Tao; Xu, Xu-Dong; Yang, Jun-Shan

2017-07-01

Rhubarb contains biologically active compounds such as anthraquinones, anthrones, stilbenes and tannins. A rapid and efficient UPLC/Q-TOF-MS/MS method was developed and applied towards identifying the constituents of Rheum tanguticum Maxim. ex Balf. for the first time. Chemical constituents were separated and investigated by UPLC/Q-TOF-MS/MS in the negative ion mode. The ESI-MS 2 fragmentation pathways of four types of compounds were interpreted, providing a very useful guidance for the characterisation of different types of compounds. Based on the exact mass information, fragmentation characteristic and LC retention time of 7 reference standards, 30 constituents were tentatively identified from the methanol extract of R. tanguticum. Among them, seven compounds were described for the first time from R. tanguticum and two from the genus Rheum were described for the first time. The analytical tool used here is valuable for the rapid separation and identification of multiple and minor constituents in methanol extracts of R. tanguticum.

Method of analysis and quality-assurance practices by the U. S. Geological Survey Organic Geochemistry Research Group; determination of four selected mosquito insecticides and a synergist in water using liquid-liquid extraction and gas chrom

USGS Publications Warehouse

Zimmerman, L.R.; Strahan, A.P.; Thurman, E.M.

2001-01-01

A method of analysis and quality-assurance practices were developed for the determination of four mosquito insecticides (malathion, metho-prene, phenothrin, and resmethrin) and one synergist (piperonyl butoxide) in water. The analytical method uses liquid-liquid extraction (LLE) and gas chromatography/mass spectrometry (GC/MS). Good precision and accuracy were demonstrated in reagent water, urban surface water, and ground water. The mean accuracies as percentages of the true compound concentrations from water samples spiked at 10 and 50 nanograms per liter ranged from 68 to 171 percent, with standard deviations in concentrations of 27 nanograms per liter or less. The method detection limit for all compounds was 5.9 nanograms per liter or less for 247-milliliter samples. This method is valuable for acquiring information about the fate and transport of these mosquito insecticides and one synergist in water.

DNA extraction and amplification from contemporary Polynesian bark-cloth.

PubMed

Moncada, Ximena; Payacán, Claudia; Arriaza, Francisco; Lobos, Sergio; Seelenfreund, Daniela; Seelenfreund, Andrea

2013-01-01

Paper mulberry has been used for thousands of years in Asia and Oceania for making paper and bark-cloth, respectively. Museums around the world hold valuable collections of Polynesian bark-cloth. Genetic analysis of the plant fibers from which the textiles were made may answer a number of questions of interest related to provenance, authenticity or species used in the manufacture of these textiles. Recovery of nucleic acids from paper mulberry bark-cloth has not been reported before. We describe a simple method for the extraction of PCR-amplifiable DNA from small samples of contemporary Polynesian bark-cloth (tapa) using two types of nuclear markers. We report the amplification of about 300 bp sequences of the ITS1 region and of a microsatellite marker. Sufficient DNA was retrieved from all bark-cloth samples to permit successful PCR amplification. This method shows a means of obtaining useful genetic information from modern bark-cloth samples and opens perspectives for the analyses of small fragments derived from ethnographic materials.

DNA Extraction and Amplification from Contemporary Polynesian Bark-Cloth

PubMed Central

Moncada, Ximena; Payacán, Claudia; Arriaza, Francisco; Lobos, Sergio; Seelenfreund, Daniela; Seelenfreund, Andrea

2013-01-01

Background Paper mulberry has been used for thousands of years in Asia and Oceania for making paper and bark-cloth, respectively. Museums around the world hold valuable collections of Polynesian bark-cloth. Genetic analysis of the plant fibers from which the textiles were made may answer a number of questions of interest related to provenance, authenticity or species used in the manufacture of these textiles. Recovery of nucleic acids from paper mulberry bark-cloth has not been reported before. Methodology We describe a simple method for the extraction of PCR-amplifiable DNA from small samples of contemporary Polynesian bark-cloth (tapa) using two types of nuclear markers. We report the amplification of about 300 bp sequences of the ITS1 region and of a microsatellite marker. Conclusions Sufficient DNA was retrieved from all bark-cloth samples to permit successful PCR amplification. This method shows a means of obtaining useful genetic information from modern bark-cloth samples and opens perspectives for the analyses of small fragments derived from ethnographic materials. PMID:23437166

Development of a GIService based on spatial data mining for location choice of convenience stores in Taipei City

NASA Astrophysics Data System (ADS)

Jung, Chinte; Sun, Chih-Hong

2006-10-01

Motivated by the increasing accessibility of technology, more and more spatial data are being made digitally available. How to extract the valuable knowledge from these large (spatial) databases is becoming increasingly important to businesses, as well. It is essential to be able to analyze and utilize these large datasets, convert them into useful knowledge, and transmit them through GIS-enabled instruments and the Internet, conveying the key information to business decision-makers effectively and benefiting business entities. In this research, we combine the techniques of GIS, spatial decision support system (SDSS), spatial data mining (SDM), and ArcGIS Server to achieve the following goals: (1) integrate databases from spatial and non-spatial datasets about the locations of businesses in Taipei, Taiwan; (2) use the association rules, one of the SDM methods, to extract the knowledge from the integrated databases; and (3) develop a Web-based SDSS GIService as a location-selection tool for business by the product of ArcGIS Server.

Bioactive Phytochemicals from Wild Arbutus unedo L. Berries from Different Locations in Portugal: Quantification of Lipophilic Components

PubMed Central

Fonseca, Daniela F. S.; Salvador, Ângelo C.; Santos, Sónia A. O.; Vilela, Carla; Freire, Carmen S. R.; Silvestre, Armando J. D.; Rocha, Sílvia M.

2015-01-01

The lipophilic composition of wild Arbutus unedo L. berries, collected from six locations in Penacova (center of Portugal), as well as some general chemical parameters, namely total soluble solids, pH, titratable acidity, total phenolic content and antioxidant activity was studied in detail to better understand its potential as a source of bioactive compounds. The chemical composition of the lipophilic extracts, focused on the fatty acids, triterpenoids, sterols, long chain aliphatic alcohols and tocopherols, was investigated by gas chromatography–mass spectrometry (GC–MS) analysis of the dichloromethane extracts. The lipophilic extractives of the ripe A. unedo berries ranged from 0.72% to 1.66% (w/w of dry weight), and consisted mainly of triterpenoids, fatty acids and sterols. Minor amounts of long chain aliphatic alcohols and tocopherols were also identified. Forty-one compounds were identified and among these, ursolic acid, lupeol, α-amyrin, linoleic and α-linolenic acids, and β-sitosterol were highlighted as the major components. To the best of our knowledge the current research study provides the most detailed phytochemical repository for the lipophilic composition of A. unedo, and offers valuable information for future valuation and exploitation of these berries. PMID:26110390

Mutual information-based LPI optimisation for radar network

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun

2015-07-01

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

Investigation of BOLD fMRI Resonance Frequency Shifts and Quantitative Susceptibility Changes at 7 T

PubMed Central

Bianciardi, Marta; van Gelderen, Peter; Duyn, Jeff H.

2013-01-01

Although blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) experiments of brain activity generally rely on the magnitude of the signal, they also provide frequency information that can be derived from the phase of the signal. However, because of confounding effects of instrumental and physiological origin, BOLD related frequency information is difficult to extract and therefore rarely used. Here, we explored the use of high field (7 T) and dedicated signal processing methods to extract frequency information and use it to quantify and interpret blood oxygenation and blood volume changes. We found that optimized preprocessing improves detection of task-evoked and spontaneous changes in phase signals and resonance frequency shifts over large areas of the cortex with sensitivity comparable to that of magnitude signals. Moreover, our results suggest the feasibility of mapping BOLD quantitative susceptibility changes in at least part of the activated area and its largest draining veins. Comparison with magnitude data suggests that the observed susceptibility changes originate from neuronal activity through induced blood volume and oxygenation changes in pial and intracortical veins. Further, from frequency shifts and susceptibility values, we estimated that, relative to baseline, the fractional oxygen saturation in large vessels increased by 0.02–0.05 during stimulation, which is consistent to previously published estimates. Together, these findings demonstrate that valuable information can be derived from fMRI imaging of BOLD frequency shifts and quantitative susceptibility changes. PMID:23897623

Solvent extraction of Cu, Mo, V, and U from leach solutions of copper ore and flotation tailings.

PubMed

Smolinski, Tomasz; Wawszczak, Danuta; Deptula, Andrzej; Lada, Wieslawa; Olczak, Tadeusz; Rogowski, Marcin; Pyszynska, Marta; Chmielewski, Andrzej Grzegorz

2017-01-01

Flotation tailings from copper production are deposits of copper and other valuable metals, such as Mo, V and U. New hydrometallurgical technologies are more economical and open up new possibilities for metal recovery. This work presents results of the study on the extraction of copper by mixed extractant consisting p -toluidine dissolved in toluene. The possibility of simultaneous liquid-liquid extraction of molybdenum and vanadium was examined. D2EHPA solutions was used as extractant, and recovery of individual elements compared for the representative samples of ore and copper flotation tailings. Radiometric methods were applied for process optimization.

A simple and rapid electrophoretic method to characterize simple phenols, lignans, complex phenols, phenolic acids, and flavonoids in extra-virgin olive oil.

PubMed

Carrasco-Pancorbo, Alegria; Gómez-Caravaca, Ana Maria; Cerretani, Lorenzo; Bendini, Alessandra; Segura-Carretero, Antonio; Fernández-Gutiérrez, Alberto

2006-09-01

We have devised a simple and rapid capillary electrophoretic method which provides the analyst with a useful tool for the characterization of the polyphenolic fraction of extra-virgin olive oil. This method that uses a capillary with 50 microm id and a total length of 47 cm (40 cm to the detector) with a detection window of 100 x 200 microm, and a buffer solution containing 45 mM of sodium tetraborate pH 9.3 offers valuable information about all the families of compounds present in the polar fraction of the olive oil. The detection was carried out by UV absorption at 200, 240, 280, and 330 nm in order to facilitate the identification of the compounds. Concretely, the method permits the identification of simple phenols, lignans, complex phenols (isomeric forms of secoiridoids), phenolic acids, and flavonoids in the SPE-Diol extracts from extra-virgin olive oil in a short time (less than 10 min) and provides a satisfactory resolution. Peak identification was done by comparing both migration time and spectral data obtained from olive oil samples and standards (commercial or isolated (by HPLC-MS) standards), with spiked methanol-water extracts of olive oil with HPLC-collected compounds and commercially available standards at several concentration levels, studying the information of the electropherograms obtained at several wavelengths and also using the information previously reported.

Fusion of Remote Sensing Methods, UAV Photogrammetry and LiDAR Scanning products for monitoring fluvial dynamics

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip

2015-04-01

Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.

Analysis of different image-based biofeedback models for improving cycling performances

NASA Astrophysics Data System (ADS)

Bibbo, D.; Conforto, S.; Bernabucci, I.; Carli, M.; Schmid, M.; D'Alessio, T.

2012-03-01

Sport practice can take advantage from the quantitative assessment of task execution, which is strictly connected to the implementation of optimized training procedures. To this aim, it is interesting to explore the effectiveness of biofeedback training techniques. This implies a complete chain for information extraction containing instrumented devices, processing algorithms and graphical user interfaces (GUIs) to extract valuable information (i.e. kinematics, dynamics, and electrophysiology) to be presented in real-time to the athlete. In cycling, performance indexes displayed in a simple and perceivable way can help the cyclist optimize the pedaling. To this purpose, in this study four different GUIs have been designed and used in order to understand if and how a graphical biofeedback can influence the cycling performance. In particular, information related to the mechanical efficiency of pedaling is represented in each of the designed interfaces and then displayed to the user. This index is real-time calculated on the basis of the force signals exerted on the pedals during cycling. Instrumented pedals for bikes, already designed and implemented in our laboratory, have been used to measure those force components. A group of subjects underwent an experimental protocol and pedaled with (the interfaces have been used in a randomized order) and without graphical biofeedback. Preliminary results show how the effective perception of the biofeedback influences the motor performance.

Lobster processing by-products as valuable bioresource of marine functional ingredients, nutraceuticals, and pharmaceuticals.

PubMed

Nguyen, Trung T; Barber, Andrew R; Corbin, Kendall; Zhang, Wei

2017-01-01

The worldwide annual production of lobster was 165,367 tons valued over $3.32 billion in 2004, but this figure rose up to 304,000 tons in 2012. Over half the volume of the worldwide lobster production has been processed to meet the rising global demand in diversified lobster products. Lobster processing generates a large amount of by-products (heads, shells, livers, and eggs) which account for 50-70% of the starting material. Continued production of these lobster processing by-products (LPBs) without corresponding process development for efficient utilization has led to disposal issues associated with costs and pollutions. This review presents the promising opportunities to maximize the utilization of LPBs by economic recovery of their valuable components to produce high value-added products. More than 50,000 tons of LPBs are globally generated, which costs lobster processing companies upward of about $7.5 million/year for disposal. This not only presents financial and environmental burdens to the lobster processors but also wastes a valuable bioresource. LPBs are rich in a range of high-value compounds such as proteins, chitin, lipids, minerals, and pigments. Extracts recovered from LPBs have been demonstrated to possess several functionalities and bioactivities, which are useful for numerous applications in water treatment, agriculture, food, nutraceutical, pharmaceutical products, and biomedicine. Although LPBs have been studied for recovery of valuable components, utilization of these materials for the large-scale production is still very limited. Extraction of lobster components using microwave, ultrasonic, and supercritical fluid extraction were found to be promising techniques that could be used for large-scale production. LPBs are rich in high-value compounds that are currently being underutilized. These compounds can be extracted for being used as functional ingredients, nutraceuticals, and pharmaceuticals in a wide range of commercial applications. The efficient utilization of LPBs would not only generate significant economic benefits but also reduce the problems of waste management associated with the lobster industry. This comprehensive review highlights the availability of the global LPBs, the key components in LPBs and their current applications, the limitations to the extraction techniques used, and the suggested emerging techniques which may be promising on an industrial scale for the maximized utilization of LPBs. Graphical abstractLobster processing by-product as bioresource of several functional and bioactive compounds used in various value-added products.

Advanced eddy current test signal analysis for steam generator tube defect classification and characterization

NASA Astrophysics Data System (ADS)

McClanahan, James Patrick

Eddy Current Testing (ECT) is a Non-Destructive Examination (NDE) technique that is widely used in power generating plants (both nuclear and fossil) to test the integrity of heat exchanger (HX) and steam generator (SG) tubing. Specifically for this research, laboratory-generated, flawed tubing data were examined. The purpose of this dissertation is to develop and implement an automated method for the classification and an advanced characterization of defects in HX and SG tubing. These two improvements enhanced the robustness of characterization as compared to traditional bobbin-coil ECT data analysis methods. A more robust classification and characterization of the tube flaw in-situ (while the SG is on-line but not when the plant is operating), should provide valuable information to the power industry. The following are the conclusions reached from this research. A feature extraction program acquiring relevant information from both the mixed, absolute and differential data was successfully implemented. The CWT was utilized to extract more information from the mixed, complex differential data. Image Processing techniques used to extract the information contained in the generated CWT, classified the data with a high success rate. The data were accurately classified, utilizing the compressed feature vector and using a Bayes classification system. An estimation of the upper bound for the probability of error, using the Bhattacharyya distance, was successfully applied to the Bayesian classification. The classified data were separated according to flaw-type (classification) to enhance characterization. The characterization routine used dedicated, flaw-type specific ANNs that made the characterization of the tube flaw more robust. The inclusion of outliers may help complete the feature space so that classification accuracy is increased. Given that the eddy current test signals appear very similar, there may not be sufficient information to make an extremely accurate (>95%) classification or an advanced characterization using this system. It is necessary to have a larger database fore more accurate system learning.

Extraction and identification of flavonoids from parsley extracts by HPLC analysis

NASA Astrophysics Data System (ADS)

Stan, M.; Soran, M. L.; Varodi, C.; Lung, I.

2012-02-01

Flavonoids are phenolic compounds isolated from a wide variety of plants, and are valuable for their multiple properties, including antioxidant and antimicrobial activities. In the present work, parsley (Petroselinum crispum L.) extracts were obtained by three different extraction techniques: maceration, ultrasonic-assisted and microwave-assisted solvent extractions. The extractions were performed with ethanol-water mixtures in various ratios. From these extracts, flavonoids like the flavones apigenin and luteolin, and the flavonols quercetin and kaempferol were identified using an HPLC Shimadzu apparatus equipped with PDA and MS detectors. The separation method involved a gradient step. The mobile phase consisted of two solvents: acetonitrile and distilled water with 0.1% formic acid. The separation was performed on a RP-C18 column.

Life-Cycle environmental impact assessment of mineral industries

NASA Astrophysics Data System (ADS)

Hisan Farjana, Shahjadi; Huda, Nazmul; Parvez Mahmud, M. A.

2018-05-01

Mining is the extraction and processing of valuable ferro and non-ferro metals and minerals to be further used in manufacturing industries. Valuable metals and minerals are extracted from the geological deposits and ores deep in the surface through complex manufacturing technologies. The extraction and processing of mining industries involve particle emission to air or water, toxicity to the environment, contamination of water resources, ozone layer depletion and most importantly decay of human health. Despite all these negative impacts towards sustainability, mining industries are working throughout the world to facilitate the employment sector, economy and technological growth. The five most important miners in the world are South Africa, Russia, Australia, Ukraine, Guinea. The mining industries contributes to their GDP significantly. However, the most important issue is making the mining world sustainable thus reducing the emissions. To address the environmental impacts caused by the mining sectors, this paper is going to analyse the environmental impacts caused by the 5 major minerals extraction processes, which are bauxite, ilmenite, iron ore, rutile and uranium by using the life-cycle impact assessment technologies. The analysis is done here using SimaPro software version 8.4 using ReCipe, CML and Australian indicator method.

Laser pulse bidirectional reflectance from CALIPSO mission

NASA Astrophysics Data System (ADS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Vaughan, Mark; Liu, Zhaoyan; Rodier, Sharon; Hunt, William; Powell, Kathy; Lucker, Patricia; Trepte, Charles

2018-06-01

This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. To better analyze the surface returns, the CALIOP receiver impulse response and the downlinked samples' distribution at 30 m vertical resolution are discussed. The saturated laser pulse magnitudes from snow and ice surfaces are recovered based on information extracted from the tail end of the surface signal. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud-covered regions and MODIS BRDF-albedo model parameters. In addition to the surface bidirectional reflectance, the column top-of-atmosphere bidirectional reflectances are calculated from the CALIOP lidar background data and compared with the bidirectional reflectances derived from WFC radiance measurements. The retrieved CALIOP surface bidirectional reflectance and column top-of-atmosphere bidirectional reflectance results provide unique information to complement existing MODIS standard data products and are expected to have valuable applications for modelers.

Estimation of road profile variability from measured vehicle responses

NASA Astrophysics Data System (ADS)

Fauriat, W.; Mattrand, C.; Gayton, N.; Beakou, A.; Cembrzynski, T.

2016-05-01

When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets.

Advanced Video Analysis Needs for Human Performance Evaluation

NASA Technical Reports Server (NTRS)

Campbell, Paul D.

1994-01-01

Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

Next-Generation Pathology.

PubMed

Caie, Peter D; Harrison, David J

2016-01-01

The field of pathology is rapidly transforming from a semiquantitative and empirical science toward a big data discipline. Large data sets from across multiple omics fields may now be extracted from a patient's tissue sample. Tissue is, however, complex, heterogeneous, and prone to artifact. A reductionist view of tissue and disease progression, which does not take this complexity into account, may lead to single biomarkers failing in clinical trials. The integration of standardized multi-omics big data and the retention of valuable information on spatial heterogeneity are imperative to model complex disease mechanisms. Mathematical modeling through systems pathology approaches is the ideal medium to distill the significant information from these large, multi-parametric, and hierarchical data sets. Systems pathology may also predict the dynamical response of disease progression or response to therapy regimens from a static tissue sample. Next-generation pathology will incorporate big data with systems medicine in order to personalize clinical practice for both prognostic and predictive patient care.

Logarithmic profile mapping multi-scale Retinex for restoration of low illumination images

NASA Astrophysics Data System (ADS)

Shi, Haiyan; Kwok, Ngaiming; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Lin, Ching-Feng; Wong, Chin Yeow

2018-04-01

Images are valuable information sources for many scientific and engineering applications. However, images captured in poor illumination conditions would have a large portion of dark regions that could heavily degrade the image quality. In order to improve the quality of such images, a restoration algorithm is developed here that transforms the low input brightness to a higher value using a modified Multi-Scale Retinex approach. The algorithm is further improved by a entropy based weighting with the input and the processed results to refine the necessary amplification at regions of low brightness. Moreover, fine details in the image are preserved by applying the Retinex principles to extract and then re-insert object edges to obtain an enhanced image. Results from experiments using low and normal illumination images have shown satisfactory performances with regard to the improvement in information contents and the mitigation of viewing artifacts.

A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos.

PubMed

Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

2016-04-01

Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit.edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable information, as well as intuitively and conveniently preview essential content of a single or a collection of videos. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas.

PubMed

Cumbo, Fabio; Fiscon, Giulia; Ceri, Stefano; Masseroli, Marco; Weitschek, Emanuel

2017-01-03

Data extraction and integration methods are becoming essential to effectively access and take advantage of the huge amounts of heterogeneous genomics and clinical data increasingly available. In this work, we focus on The Cancer Genome Atlas, a comprehensive archive of tumoral data containing the results of high-throughout experiments, mainly Next Generation Sequencing, for more than 30 cancer types. We propose TCGA2BED a software tool to search and retrieve TCGA data, and convert them in the structured BED format for their seamless use and integration. Additionally, it supports the conversion in CSV, GTF, JSON, and XML standard formats. Furthermore, TCGA2BED extends TCGA data with information extracted from other genomic databases (i.e., NCBI Entrez Gene, HGNC, UCSC, and miRBase). We also provide and maintain an automatically updated data repository with publicly available Copy Number Variation, DNA-methylation, DNA-seq, miRNA-seq, and RNA-seq (V1,V2) experimental data of TCGA converted into the BED format, and their associated clinical and biospecimen meta data in attribute-value text format. The availability of the valuable TCGA data in BED format reduces the time spent in taking advantage of them: it is possible to efficiently and effectively deal with huge amounts of cancer genomic data integratively, and to search, retrieve and extend them with additional information. The BED format facilitates the investigators allowing several knowledge discovery analyses on all tumor types in TCGA with the final aim of understanding pathological mechanisms and aiding cancer treatments.

The value of necropsy reports for animal health surveillance.

PubMed

Küker, Susanne; Faverjon, Celine; Furrer, Lenz; Berezowski, John; Posthaus, Horst; Rinaldi, Fabio; Vial, Flavie

2018-06-18

Animal health data recorded in free text, such as in necropsy reports, can have valuable information for national surveillance systems. However, these data are rarely utilized because the text format requires labor-intensive classification of records before they can be analyzed with using statistical or other software. In a previous study, we designed a text-mining tool to extract data from text in necropsy reports. In the current study, we used the tool to extract data from the reports from pig and cattle necropsies performed between 2000 and 2011 at the Institute of Animal Pathology (ITPA), University of Bern, Switzerland. We evaluated data quality in terms of credibility, completeness and representativeness of the Swiss pig and cattle populations. Data was easily extracted from necropsy reports. Data quality in terms of completeness and validity varied a lot depending on the type of data reported. Diseases of the gastrointestinal system were reported most frequently (54.6% of pig submissions and 40.8% of cattle submissions). Diseases affecting serous membranes were reported in 16.0% of necropsied pigs and 27.6% of cattle. Respiratory diseases were reported in 18.3% of pigs and 21.6% of cattle submissions. This study suggests that extracting data from necropsy reports can provide information of value for animal health surveillance. This data has potential value for monitoring endemic disease syndromes in different age and production groups, or for early detection of emerging or re-emerging diseases. The study identified data entry and other errors that could be corrected to improve the quality and validity of the data. Submissions to veterinary diagnostic laboratories have selection biases and these should be considered when designing surveillance systems that include necropsy reports.

Preliminary Study of Information Extraction of LANDSAT TM Data for a Suburban/regional Test Site

NASA Technical Reports Server (NTRS)

Toll, D. L.

1985-01-01

A substantial amount of spectral information is available from TM (as compared to MSS) data for a 14.25 square km area between Beltsville and Laurel, Maryland. Large buildings and street patterns were resolved in the TM imagery. While there was added information content in TM data for discriminating surburban/regional land cover, characteristics of MSS can improve land cover discrimination over TM when conventional classification procedures are used on digital data. The improved qualitization of TM is likely valuable in situations where there are spectral similarities between classes. The spatial resolution in TM decreased land cover discrimination as a result of increased within class variability. For many general digital evaluations, inclusion of four bands representing the four spectral regions can provide much useful land cover discrimination. Inclusion of TM 6 indicates an improvement in spectral class discrimination. Of primary spectral importance is the discrimination between water, vegetative surfaces, and impervious surfaces due to differences in thermal properties. Results from the principle component transformed data clearly indicates additional information content in TM over MSS.

Serial analysis of gene expression (SAGE) in normal human trabecular meshwork.

PubMed

Liu, Yutao; Munro, Drew; Layfield, David; Dellinger, Andrew; Walter, Jeffrey; Peterson, Katherine; Rickman, Catherine Bowes; Allingham, R Rand; Hauser, Michael A

2011-04-08

To identify the genes expressed in normal human trabecular meshwork tissue, a tissue critical to the pathogenesis of glaucoma. Total RNA was extracted from human trabecular meshwork (HTM) harvested from 3 different donors. Extracted RNA was used to synthesize individual SAGE (serial analysis of gene expression) libraries using the I-SAGE Long kit from Invitrogen. Libraries were analyzed using SAGE 2000 software to extract the 17 base pair sequence tags. The extracted sequence tags were mapped to the genome using SAGE Genie map. A total of 298,834 SAGE tags were identified from all HTM libraries (96,842, 88,126, and 113,866 tags, respectively). Collectively, there were 107,325 unique tags. There were 10,329 unique tags with a minimum of 2 counts from a single library. These tags were mapped to known unique Unigene clusters. Approximately 29% of the tags (orphan tags) did not map to a known Unigene cluster. Thirteen percent of the tags mapped to at least 2 Unigene clusters. Sequence tags from many glaucoma-related genes, including myocilin, optineurin, and WD repeat domain 36, were identified. This is the first time SAGE analysis has been used to characterize the gene expression profile in normal HTM. SAGE analysis provides an unbiased sampling of gene expression of the target tissue. These data will provide new and valuable information to improve understanding of the biology of human aqueous outflow.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

PubMed

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

BioCreative Workshops for DOE Genome Sciences: Text Mining for Metagenomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Cathy H.; Hirschman, Lynette

The objective of this project was to host BioCreative workshops to define and develop text mining tasks to meet the needs of the Genome Sciences community, focusing on metadata information extraction in metagenomics. Following the successful introduction of metagenomics at the BioCreative IV workshop, members of the metagenomics community and BioCreative communities continued discussion to identify candidate topics for a BioCreative metagenomics track for BioCreative V. Of particular interest was the capture of environmental and isolation source information from text. The outcome was to form a “community of interest” around work on the interactive EXTRACT system, which supported interactive taggingmore » of environmental and species data. This experiment is included in the BioCreative V virtual issue of Database. In addition, there was broad participation by members of the metagenomics community in the panels held at BioCreative V, leading to valuable exchanges between the text mining developers and members of the metagenomics research community. These exchanges are reflected in a number of the overview and perspective pieces also being captured in the BioCreative V virtual issue. Overall, this conversation has exposed the metagenomics researchers to the possibilities of text mining, and educated the text mining developers to the specific needs of the metagenomics community.« less

Changes in resistant starch from two banana cultivars during postharvest storage.

PubMed

Wang, Juan; Tang, Xue Juan; Chen, Ping Sheng; Huang, Hui Hua

2014-08-01

Banana resistant starch samples were extracted and isolated from two banana cultivars (Musa AAA group, Cavendish subgroup and Musa ABB group, Pisang Awak subgroup) at seven ripening stages during postharvest storage. The structures of the resistant starch samples were analysed by light microscopy, polarising microscopy, scanning electron microscopy, X-ray diffraction, and infrared spectroscopy. Physicochemical properties (e.g., water-holding capacity, solubility, swelling power, transparency, starch-iodine absorption spectrum, and Brabender microviscoamylograph profile) were determined. The results revealed significant differences in microstructure and physicochemical characteristics among the banana resistant starch samples during different ripening stages. The results of this study provide valuable information for the potential applications of banana resistant starches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of earth resources technology satellite data to urban and regional planning: Test site, County of Los Angeles

NASA Technical Reports Server (NTRS)

Raje, S.; Mcknight, J.; Willoughby, G.; Economy, R. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The County of Los Angeles photointerpreted ERTS film products to define problems of interest, coordinated ground truth over the complex test site including interfaces with secondary users as well as participated in on-line analyses of the GE multispectral information extraction systems. Interactive machine analyses were carried out, developing techniques and procedures as well as evaluating the outputs for community and regional planning. Extensive aircraft underflight coverage was provided that was valuable both in inputs preparation and outputs evaluation of the machine-aided analyses. One of the nonstandard ERTS images led to the discovery of a major new fault lineament on the northern slope of the Santa Monica Mountains.

Synthesis of silver nanoparticle and its application.

PubMed

Pandian, A Muthu Kumara; Karthikeyan, C; Rajasimman, M; Dinesh, M G

2015-11-01

In this work, silver nanoparticles have been synthesized by wet chemical technique, green synthesis and microbial methods. Silver nitrate (10(-3)M) was used with aqueous extract to produce silver nanoparticles. From the results it was observed that the yield of nanoparticles was high in green synthesis. The size of the silver nanoparticles was determined from Scanning Electron Microscope analysis (SEM). Fourier Transform Infrared spectroscopy (FTIR) was carried out to determine the presence of biomolecules in them. Its cytotoxic effect was studied in cancerous cell line and normal cell line. MTT assay was done to test its optimal concentration and efficacy which gives valuable information for the use of silver nanoparticles for future cancer therapy. Copyright © 2015 Elsevier Inc. All rights reserved.

Aqueous Extract Composition of Spent Ginger (Zingiber officinale var. Amarum) from Essential Oil Distillation

NASA Astrophysics Data System (ADS)

Manuhara, G. J.; Mentari, G. P.; Khasanah, L. U.; Utami, R.

2018-03-01

Ginger (Zingiber officinale var Amarum) is widely used as raw material for essential oil production in Indonesia and contain high functional compounds. After producing essential oil, distillation leave less valuable spent ginger. This research was conducted to determine the bioactive compounds remained in aqueous extract of the spent ginger. The extracts were produced at various combination of temperature (55, 75, 95°C) and duration (15, 30, 45 minutes). The extract composition was observed using Gas Chromatography - Mass Spectrometry analysis. The temperature and time of maceration extraction affected the content of compounds in spent ginger aqueous extracts. The extracts contained four largest components of α-curcumene, α-zingiberene, β-sesquiphellandrene and β-bisabolene. The aqueous extracts from spent ginger contained the compounds which may contribute to distinctive flavor of ginger and also bioactive function.

Construction of a database for published phase II/III drug intervention clinical trials for the period 2009-2014 comprising 2,326 records, 90 disease categories, and 939 drug entities.

PubMed

Jeong, Sohyun; Han, Nayoung; Choi, Boyoon; Sohn, Minji; Song, Yun-Kyoung; Chung, Myeon-Woo; Na, Han-Sung; Ji, Eunhee; Kim, Hyunah; Rhew, Ki Yon; Kim, Therasa; Kim, In-Wha; Oh, Jung Mi

2016-06-01

To construct a database of published clinical drug trials suitable for use 1) as a research tool in accessing clinical trial information and 2) in evidence-based decision-making by regulatory professionals, clinical research investigators, and medical practitioners. Comprehensive information obtained from a search of design elements and results of clinical trials in peer reviewed journals using PubMed (http://www.ncbi.nlm.ih.gov/pubmed). The methodology to develop a structured database was devised by a panel composed of experts in medical, pharmaceutical, information technology, and members of Ministry of Food and Drug Safety (MFDS) using a step by step approach. A double-sided system consisting of user mode and manager mode served as the framework for the database; elements of interest from each trial were entered via secure manager mode enabling the input information to be accessed in a user-friendly manner (user mode). Information regarding methodology used and results of drug treatment were extracted as detail elements of each data set and then inputted into the web-based database system. Comprehensive information comprising 2,326 clinical trial records, 90 disease states, and 939 drugs entities and concerning study objectives, background, methods used, results, and conclusion could be extracted from published information on phase II/III drug intervention clinical trials appearing in SCI journals within the last 10 years. The extracted data was successfully assembled into a clinical drug trial database with easy access suitable for use as a research tool. The clinically most important therapeutic categories, i.e., cancer, cardiovascular, respiratory, neurological, metabolic, urogenital, gastrointestinal, psychological, and infectious diseases were covered by the database. Names of test and control drugs, details on primary and secondary outcomes and indexed keywords could also be retrieved and built into the database. The construction used in the database enables the user to sort and download targeted information as a Microsoft Excel spreadsheet. Because of the comprehensive and standardized nature of the clinical drug trial database and its ease of access it should serve as valuable information repository and research tool for accessing clinical trial information and making evidence-based decisions by regulatory professionals, clinical research investigators, and medical practitioners.

A survey of social media data analysis for physical activity surveillance.

PubMed

Liu, Sam; Young, Sean D

2018-07-01

Social media data can provide valuable information regarding people's behaviors and health outcomes. Previous studies have shown that social media data can be extracted to monitor and predict infectious disease outbreaks. These same approaches can be applied to other fields including physical activity research and forensic science. Social media data have the potential to provide real-time monitoring and prediction of physical activity level in a given region. This tool can be valuable to public health organizations as it can overcome the time lag in the reporting of physical activity epidemiology data faced by traditional research methods (e.g. surveys, observational studies). As a result, this tool could help public health organizations better mobilize and target physical activity interventions. The first part of this paper aims to describe current approaches (e.g. topic modeling, sentiment analysis and social network analysis) that could be used to analyze social media data to provide real-time monitoring of physical activity level. The second aim of this paper was to discuss ways to apply social media analysis to other fields such as forensic sciences and provide recommendations to further social media research. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Physical characteristics related to bra fit.

PubMed

Chen, Chin-Man; LaBat, Karen; Bye, Elizabeth

2010-04-01

Producing well-fitting garments has been a challenge for retailers and manufacturers since mass production began. Poorly fitted bras can cause discomfort or pain and result in lost sales for retailers. Because body contours are important factors affecting bra fit, this study analyses the relationship of physical characteristics to bra-fit problems. This study has used 3-D body-scanning technology to extract upper body angles from a sample of 103 college women; these data were used to categorise physical characteristics into shoulder slope, bust prominence, back curvature and acromion placement. Relationships between these physical categories and bra-fit problems were then analysed. Results show that significant main effects and two-way interactions of the physical categories exist in the fit problems of poor bra support and bra-motion restriction. The findings are valuable in helping the apparel industry create better-fitting bras. STATEMENT OF RELEVANCE: Poorly fitted bras can cause discomfort or pain and result in lost sales for retailers. The findings regarding body-shape classification provide researchers with a statistics method to quantify physical characteristics and the findings regarding the relationship analysis between physical characteristics and bra fit offer bra companies valuable information about bra-fit perceptions attributable to women with figure variations.

Extract from the Zooxanthellate Jellyfish Cotylorhiza tuberculata Modulates Gap Junction Intercellular Communication in Human Cell Cultures

PubMed Central

Leone, Antonella; Lecci, Raffaella Marina; Durante, Miriana; Piraino, Stefano

2013-01-01

On a global scale, jellyfish populations in coastal marine ecosystems exhibit increasing trends of abundance. High-density outbreaks may directly or indirectly affect human economical and recreational activities, as well as public health. As the interest in biology of marine jellyfish grows, a number of jellyfish metabolites with healthy potential, such as anticancer or antioxidant activities, is increasingly reported. In this study, the Mediterranean “fried egg jellyfish” Cotylorhiza tuberculata (Macri, 1778) has been targeted in the search forputative valuable bioactive compounds. A medusa extract was obtained, fractionated, characterized by HPLC, GC-MS and SDS-PAGE and assayed for its biological activity on breast cancer cells (MCF-7) and human epidermal keratinocytes (HEKa). The composition of the jellyfish extract included photosynthetic pigments, valuable ω-3 and ω-6 fatty acids, and polypeptides derived either from jellyfish tissues and their algal symbionts. Extract fractions showed antioxidant activity and the ability to affect cell viability and intercellular communication mediated by gap junctions (GJIC) differentially in MCF-7and HEKa cells. A significantly higher cytotoxicity and GJIC enhancement in MCF-7 compared to HEKa cells was recorded. A putative action mechanism for the anticancer bioactivity through the modulation of GJIC has been hypothesized and its nutraceutical and pharmaceutical potential was discussed. PMID:23697954

Extract from the zooxanthellate jellyfish Cotylorhiza tuberculata modulates gap junction intercellular communication in human cell cultures.

PubMed

Leone, Antonella; Lecci, Raffaella Marina; Durante, Miriana; Piraino, Stefano

2013-05-22

On a global scale, jellyfish populations in coastal marine ecosystems exhibit increasing trends of abundance. High-density outbreaks may directly or indirectly affect human economical and recreational activities, as well as public health. As the interest in biology of marine jellyfish grows, a number of jellyfish metabolites with healthy potential, such as anticancer or antioxidant activities, is increasingly reported. In this study, the Mediterranean "fried egg jellyfish" Cotylorhiza tuberculata (Macri, 1778) has been targeted in the search forputative valuable bioactive compounds. A medusa extract was obtained, fractionated, characterized by HPLC, GC-MS and SDS-PAGE and assayed for its biological activity on breast cancer cells (MCF-7) and human epidermal keratinocytes (HEKa). The composition of the jellyfish extract included photosynthetic pigments, valuable ω-3 and ω-6 fatty acids, and polypeptides derived either from jellyfish tissues and their algal symbionts. Extract fractions showed antioxidant activity and the ability to affect cell viability and intercellular communication mediated by gap junctions (GJIC) differentially in MCF-7 and HEKa cells. A significantly higher cytotoxicity and GJIC enhancement in MCF-7 compared to HEKa cells was recorded. A putative action mechanism for the anticancer bioactivity through the modulation of GJIC has been hypothesized and its nutraceutical and pharmaceutical potential was discussed.

What Clinical Information Is Valuable to Doctors Using Mobile Electronic Medical Records and When?

PubMed

Kim, Junetae; Lee, Yura; Lim, Sanghee; Kim, Jeong Hoon; Lee, Byungtae; Lee, Jae-Ho

2017-10-18

There has been a lack of understanding on what types of specific clinical information are most valuable for doctors to access through mobile-based electronic medical records (m-EMRs) and when they access such information. Furthermore, it has not been clearly discussed why the value of such information is high. The goal of this study was to investigate the types of clinical information that are most valuable to doctors to access through an m-EMR and when such information is accessed. Since 2010, an m-EMR has been used in a tertiary hospital in Seoul, South Korea. The usage logs of the m-EMR by doctors were gathered from March to December 2015. Descriptive analyses were conducted to explore the overall usage patterns of the m-EMR. To assess the value of the clinical information provided, the usage patterns of both the m-EMR and a hospital information system (HIS) were compared on an hourly basis. The peak usage times of the m-EMR were defined as continuous intervals having normalized usage values that are greater than 0.5. The usage logs were processed as an indicator representing specific clinical information using factor analysis. Random intercept logistic regression was used to explore the type of clinical information that is frequently accessed during the peak usage times. A total of 524,929 usage logs from 653 doctors (229 professors, 161 fellows, and 263 residents; mean age: 37.55 years; males: 415 [63.6%]) were analyzed. The highest average number of m-EMR usage logs (897) was by medical residents, whereas the lowest (292) was by surgical residents. The usage amount for three menus, namely inpatient list (47,096), lab results (38,508), and investigation list (25,336), accounted for 60.1% of the peak time usage. The HIS was used most frequently during regular hours (9:00 AM to 5:00 PM). The peak usage time of the m-EMR was early in the morning (6:00 AM to 10:00 AM), and the use of the m-EMR from early evening (5:00 PM) to midnight was higher than during regular business hours. Four factors representing the types of clinical information were extracted through factor analysis. Factors related to patient investigation status and patient conditions were associated with the peak usage times of the m-EMR (P<.01). Access to information regarding patient investigation status and patient conditions is crucial for decision making during morning activities, including ward rounds. The m-EMRs allow doctors to maintain the continuity of their clinical information regardless of the time and location constraints. Thus, m-EMRs will best evolve in a manner that enhances the accessibility of clinical information helpful to the decision-making process under such constraints. ©Junetae Kim, Yura Lee, Sanghee Lim, Jeong Hoon Kim, Byungtae Lee, Jae-Ho Lee. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.10.2017.

What Clinical Information Is Valuable to Doctors Using Mobile Electronic Medical Records and When?

PubMed Central

Lim, Sanghee; Kim, Jeong Hoon; Lee, Byungtae

2017-01-01

Background There has been a lack of understanding on what types of specific clinical information are most valuable for doctors to access through mobile-based electronic medical records (m-EMRs) and when they access such information. Furthermore, it has not been clearly discussed why the value of such information is high. Objective The goal of this study was to investigate the types of clinical information that are most valuable to doctors to access through an m-EMR and when such information is accessed. Methods Since 2010, an m-EMR has been used in a tertiary hospital in Seoul, South Korea. The usage logs of the m-EMR by doctors were gathered from March to December 2015. Descriptive analyses were conducted to explore the overall usage patterns of the m-EMR. To assess the value of the clinical information provided, the usage patterns of both the m-EMR and a hospital information system (HIS) were compared on an hourly basis. The peak usage times of the m-EMR were defined as continuous intervals having normalized usage values that are greater than 0.5. The usage logs were processed as an indicator representing specific clinical information using factor analysis. Random intercept logistic regression was used to explore the type of clinical information that is frequently accessed during the peak usage times. Results A total of 524,929 usage logs from 653 doctors (229 professors, 161 fellows, and 263 residents; mean age: 37.55 years; males: 415 [63.6%]) were analyzed. The highest average number of m-EMR usage logs (897) was by medical residents, whereas the lowest (292) was by surgical residents. The usage amount for three menus, namely inpatient list (47,096), lab results (38,508), and investigation list (25,336), accounted for 60.1% of the peak time usage. The HIS was used most frequently during regular hours (9:00 AM to 5:00 PM). The peak usage time of the m-EMR was early in the morning (6:00 AM to 10:00 AM), and the use of the m-EMR from early evening (5:00 PM) to midnight was higher than during regular business hours. Four factors representing the types of clinical information were extracted through factor analysis. Factors related to patient investigation status and patient conditions were associated with the peak usage times of the m-EMR (P<.01). Conclusions Access to information regarding patient investigation status and patient conditions is crucial for decision making during morning activities, including ward rounds. The m-EMRs allow doctors to maintain the continuity of their clinical information regardless of the time and location constraints. Thus, m-EMRs will best evolve in a manner that enhances the accessibility of clinical information helpful to the decision-making process under such constraints. PMID:29046269

Functional source separation and hand cortical representation for a brain–computer interface feature extraction

PubMed Central

Tecchio, Franca; Porcaro, Camillo; Barbati, Giulia; Zappasodi, Filippo

2007-01-01

A brain–computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI features – spatial and time-frequency properties – are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients. PMID:17331989

Method for in situ heating of hydrocarbonaceous formations

DOEpatents

Little, William E.; McLendon, Thomas R.

1987-01-01

A method for extracting valuable constituents from underground hydrocarbonaceous deposits such as heavy crude tar sands and oil shale is disclosed. Initially, a stratum containing a rich deposit is hydraulically fractured to form a horizontally extending fracture plane. A conducting liquid and proppant is then injected into the fracture plane to form a conducting plane. Electrical excitations are then introduced into the stratum adjacent the conducting plate to retort the rich stratum along the conducting plane. The valuable constituents from the stratum adjacent the conducting plate are then recovered. Subsequently, the remainder of the deposit is also combustion retorted to further recover valuable constituents from the deposit. Various R.F. heating systems are also disclosed for use in the present invention.

Phytochemical Screening: Antioxidant and Antibacterial Properties of Potamogeton Species in Order to Obtain Valuable Feed Additives.

PubMed

Lupoae, Paul; Cristea, Victor; Borda, Daniela; Lupoae, Mariana; Gurau, Gabriela; Dinica, Rodica Mihaela

2015-01-01

The alcoholic extracts from three submerged perennial plants Potamogeton crispus L., P. pusillus L. and P. pectinatus L. were analyzed by gas chromatography-mass spectrometry coupled with solid phase microextraction (SPME-GC/MS) and by High Performance Liquid Chromatography (HPLC) and their volatile fingerprint and polyphenols composition was mutually compared. Twenty-nine chemical compounds were detected and identified in ethanolic and methanolic extracts; the highest abundance (over 5%) in descending order, was detected for 9,9-dimethyl-8,10- dioxapentacyclo (5,3,0(2,5) 0(3,5,)0 (3,6) decane (21.65%), phenol 2,6 bis (1,1 dimethyletyl) 4-1-methylpropil (20.8%), pentadecanoic acid (14.3%), 2-(5-chloro-2-Methoxyphenyl) pyrrole (8.66%), propanedioic (malonic) acid 2-(4-methylphenyl) sulfonyl ethylidene (5.77%), 2 hydroxy-3 tert butyl-5-isopropyl-6 methyl phenyl ketone (5.76%). The highest total polyphenols and flavonoids content was found in the methanolic extract of P. crispus (112.5±0.5 mg tannic acid/g dry extract; 64.2±1.2 mg quercitin/g dry extract). Antioxidant activities (2,2-difenil-1-picrilhidrazil, hydrogen peroxide and reducing power assays) of obtained extracts are comparable with the standard compounds, butylated hydroxytoluene, rutin and ascorbic acid. Antibacterial efficiency of methanolic extracts was notably demonstrated against Gram negative (Escherichia coli, Enterobacter hormaechei) and Gram positive bacteria (Enterococcus casseliflavus). The data reported for the first time for Romanian Potamogeton species, provides extensive support for the chemical investigations of these plants of the aquatic anthropogene ecosystems in order to obtain valuable bioadditives for animal feed and/or pharmaceutical/food industry.

Modeling of the Kinetics of Supercritical Fluid Extraction of Lipids from Microalgae with Emphasis on Extract Desorption

PubMed Central

Sovová, Helena; Nobre, Beatriz P.; Palavra, António

2016-01-01

Microalgae contain valuable biologically active lipophilic substances such as omega-3 fatty acids and carotenoids. In contrast to the recovery of vegetable oils from seeds, where the extraction with supercritical CO2 is used as a mild and selective method, economically viable application of this method on similarly soluble oils from microalgae requires, in most cases, much higher pressure. This paper presents and verifies hypothesis that this difference is caused by high adsorption capacity of microalgae. Under the pressures usually applied in supercritical fluid extraction from plants, microalgae bind a large fraction of the extracted oil, while under extremely high CO2 pressures their adsorption capacity diminishes and the extraction rate depends on oil solubility in supercritical CO2. A mathematical model for the extraction from microalgae was derived and applied to literature data on the extraction kinetics in order to determine model parameters. PMID:28773546

Comparison of three sequential extraction procedures for arsenic fractionation in highly polluted sites.

PubMed

Wan, Xiang; Dong, Haochen; Feng, Liu; Lin, Zhijia; Luo, Qiuchen

2017-07-01

Three sequential extraction procedures (SEPs) including Tessier, Rauret, and Shiowatana SEPs, were compared for arsenic fractionation using highly polluted soils. In the definition context of exchangeable, reducible, oxidizable and residual fractions, with similar arsenic recovery and reproducibility, Tessier and Rauret SEPs were comparable to each other, whereas Shiowatana SEP showed higher extraction efficiency in all the first three arsenic fractions, although it might overestimate the reducible arsenic. Pot experiment indicated three SEPs all could provide an estimation of the most bioavailable arsenic fraction, and the application of Shiowatana SEP should be preferred. Accordingly, a case study with Shiowatana SEP for a site near a realgar mine area is conducted. The results show that although arsenic in this area presents predominantly in the stable fractions, the sum of most bioavailable fractions was accounted around 11% of total arsenic, and moreover, about another 10% of the total arsenic, the fourth fraction in Shiowatana SEP is likely to be transferred into bioavailable species under suitable conditions, such as strong acid impact, revealing a real major risk source being formed. The study indicated that Shiowatana should be more suitable for arsenic fractionation to provide valuable information in the framework of risk assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improvement of a headspace solid phase microextraction-gas chromatography/mass spectrometry method for the analysis of wheat bread volatile compounds.

PubMed

Raffo, Antonio; Carcea, Marina; Castagna, Claudia; Magrì, Andrea

2015-08-07

An improved method based on headspace solid phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was proposed for the semi-quantitative determination of wheat bread volatile compounds isolated from both whole slice and crust samples. A DVB/CAR/PDMS fibre was used to extract volatiles from the headspace of a bread powdered sample dispersed in a sodium chloride (20%) aqueous solution and kept for 60min at 50°C under controlled stirring. Thirty-nine out of all the extracted volatiles were fully identified, whereas for 95 other volatiles a tentative identification was proposed, to give a complete as possible profile of wheat bread volatile compounds. The use of an array of ten structurally and physicochemically similar internal standards allowed to markedly improve method precision with respect to previous HS-SPME/GC-MS methods for bread volatiles. Good linearity of the method was verified for a selection of volatiles from several chemical groups by calibration with matrix-matched extraction solutions. This simple, rapid, precise and sensitive method could represent a valuable tool to obtain semi-quantitative information when investigating the influence of technological factors on volatiles formation in wheat bread and other bakery products. Copyright © 2015 Elsevier B.V. All rights reserved.

Hybrid Signal Processing Technique to Improve the Defect Estimation in Ultrasonic Non-Destructive Testing of Composite Structures

PubMed Central

Raisutis, Renaldas; Samaitis, Vykintas

2017-01-01

This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert–Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert–Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals. PMID:29232845

Current and New Insights in the Sustainable and Green Recovery of Nutritionally Valuable Compounds from Stevia rebaudiana Bertoni.

PubMed

Koubaa, Mohamed; Roselló-Soto, Elena; Šic Žlabur, Jana; Režek Jambrak, Anet; Brnčić, Mladen; Grimi, Nabil; Boussetta, Nadia; Barba, Francisco J

2015-08-12

The South American plant Stevia rebaudiana Bertoni is a great source of noncaloric sweeteners (steviol glycosides), mainly concentrated in its leaves, but also has important antioxidant compounds (vitamin C, polyphenols, chlorophylls, and carotenoids) and other important macro- and micronutrients such as folic acid and all of the essential amino acids except tryptophan. Traditionally, conventional methods have been used to recover nutritionally valuable compounds from plant food matrices. However, nowadays, the need for obtaining greener, sustainable, and viable processes has led both food industries and food scientists to develop new processes in full correspondence with the green extraction concept. This review focuses on some of the most promising nonconventional and emerging technologies, which may constitute a potential alternative to conventional methods or even could be combined to obtain a synergistic effect, thus reducing extraction time as well as solvent consumption and avoiding the use of toxic solvents.

Isolation of friedelin from black condensate of cork.

PubMed

Pires, Ricardo A; Aroso, Ivo; Silva, Susana P; Mano, João F; Reis, Rui L

2011-11-01

Black condensates (BC) are wastes of the insulation corkboard industry that contain several valuable chemicals, including friedelin, a terpene exhibiting biological activity. Herein, we report a straightforward procedure to extract friedelin from BC. Using this procedure, we were able to extract friedelin with yields between 0.4% and 2.9% and to further purify it obtaining purities from 77.0% to 99.3% (HPLC). The initial BC (2 batches), extracted raw product and purified friedelin were analyzed using FTIR. The extraction yields and purities were found to be directly related to the intensity of the carbonyl vibration at 1713 cm(-1) in the FTIR spectrum of the used BC batch. Therefore, these spectra can be used to screen and select BC batches suitable for friedelin extraction.

Green ultrasound-assisted extraction of anthocyanin and phenolic compounds from purple sweet potato using response surface methodology

NASA Astrophysics Data System (ADS)

Zhu, Zhenzhou; Guan, Qingyan; Guo, Ying; He, Jingren; Liu, Gang; Li, Shuyi; Barba, Francisco J.; Jaffrin, Michel Y.

2016-01-01

Response surface methodology was used to optimize experimental conditions for ultrasound-assisted extraction of valuable components (anthocyanins and phenolics) from purple sweet potatoes using water as a solvent. The Box-Behnken design was used for optimizing extraction responses of anthocyanin extraction yield, phenolic extraction yield, and specific energy consumption. Conditions to obtain maximal anthocyanin extraction yield, maximal phenolic extraction yield, and minimal specific energy consumption were different; an overall desirability function was used to search for overall optimal conditions: extraction temperature of 68ºC, ultrasonic treatment time of 52 min, and a liquid/solid ratio of 20. The optimized anthocyanin extraction yield, phenolic extraction yield, and specific energy consumption were 4.91 mg 100 g-1 fresh weight, 3.24 mg g-1 fresh weight, and 2.07 kWh g-1, respectively, with a desirability of 0.99. This study indicates that ultrasound-assisted extraction should contribute to a green process for valorization of purple sweet potatoes.

Machine Learning and Data Mining Methods in Diabetes Research.

PubMed

Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

2017-01-01

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

Data mining and medical world: breast cancers' diagnosis, treatment, prognosis and challenges.

PubMed

Oskouei, Rozita Jamili; Kor, Nasroallah Moradi; Maleki, Saeid Abbasi

2017-01-01

The amount of data in electronic and real world is constantly on the rise. Therefore, extracting useful knowledge from the total available data is very important and time consuming task. Data mining has various techniques for extracting valuable information or knowledge from data. These techniques are applicable for all data that are collected inall fields of science. Several research investigations are published about applications of data mining in various fields of sciences such as defense, banking, insurances, education, telecommunications, medicine and etc. This investigation attempts to provide a comprehensive survey about applications of data mining techniques in breast cancer diagnosis, treatment & prognosis till now. Further, the main challenges in these area is presented in this investigation. Since several research studies currently are going on in this issues, therefore, it is necessary to have a complete survey about all researches which are completed up to now, along with the results of those studies and important challenges which are currently exist in this area for helping young researchers and presenting to them the main problems that are still exist in this area.

Pilot-scale resin adsorption as a means to recover and fractionate apple polyphenols.

PubMed

Kammerer, Dietmar R; Carle, Reinhold; Stanley, Roger A; Saleh, Zaid S

2010-06-09

The purification and fractionation of phenolic compounds from crude plant extracts using a food-grade acrylic adsorbent were studied at pilot-plant scale. A diluted apple juice concentrate served as a model phenolic solution for column adsorption and desorption trials. Phenolic concentrations were evaluated photometrically using the Folin-Ciocalteu assay and by HPLC-DAD. Recovery rates were significantly affected by increasing phenolic concentrations of the feed solutions applied to the column. In contrast, the flow rate during column loading hardly influenced adsorption efficiency, whereas the temperature and pH value were shown to be crucial parameters determining both total phenolic recovery rates and the adsorption behavior of individual polyphenols. As expected, the eluent composition had the greatest impact on the desorption characteristics of both total and individual phenolic compounds. HPLC analyses revealed significantly different elution profiles of individual polyphenols depending on lipophilicity. This technique allows fractionation of crude plant phenolic extracts, thus providing the opportunity to design the functional properties of the resulting phenolic fractions selectively, and the present study delivers valuable information with regard to the adjustment of individual process parameters.

Measurements of the Total Reaction Cross Sections for 6,8He and 8,9Li Nuclei with Energies of (25-45)A Mev on natAl, natTa and natPb

NASA Astrophysics Data System (ADS)

Erdemchimeg, B.; Artukh, A. G.; Klygin, S. A.; Kononenko, G. A.; Kyslukha, D. A.; Sereda, Yu. M.; Vorontzov, A. N.; Lukyanov, S. M.; Penionzhkevich, Yu. E.; Davaa, S.; Khuukhenkhuu, G.; Borcea, C.; Rotaru, F.; Stanoiu, M.; Martina, L.; Saillant, F.; Raine, B.

2015-06-01

The total nuclear reaction cross sections (σR) measurements have long been of interest since they tell us about the radii and transparency of these nuclei and give clues to understanding of their structure. For studies of unstable nuclei, in particular the physical properties of halo nuclei and the neutron skin thickness, it is valuable to know not only the root-mean-square radii (rms) but it is important to know the details of nucleusnucleus potentials. Our goal was to study total reaction cross sections (σR) by a direct measurement technique (the so-called beam attenuation or transmission method) which allows to extract model independent information. The interaction radii for 6He, 8,9Li were extracted, which are in agreement with the previous measurement at the similar energies (about a few tens of AMeV) Our results show a tendency of increasing radii as function of mass of the secondary targets.

Data mining and medical world: breast cancers’ diagnosis, treatment, prognosis and challenges

PubMed Central

Oskouei, Rozita Jamili; Kor, Nasroallah Moradi; Maleki, Saeid Abbasi

2017-01-01

The amount of data in electronic and real world is constantly on the rise. Therefore, extracting useful knowledge from the total available data is very important and time consuming task. Data mining has various techniques for extracting valuable information or knowledge from data. These techniques are applicable for all data that are collected inall fields of science. Several research investigations are published about applications of data mining in various fields of sciences such as defense, banking, insurances, education, telecommunications, medicine and etc. This investigation attempts to provide a comprehensive survey about applications of data mining techniques in breast cancer diagnosis, treatment & prognosis till now. Further, the main challenges in these area is presented in this investigation. Since several research studies currently are going on in this issues, therefore, it is necessary to have a complete survey about all researches which are completed up to now, along with the results of those studies and important challenges which are currently exist in this area for helping young researchers and presenting to them the main problems that are still exist in this area. PMID:28401016

Recognizing stationary and locomotion activities using combinational of spectral analysis with statistical descriptors features

NASA Astrophysics Data System (ADS)

Zainudin, M. N. Shah; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

2017-10-01

Prior knowledge in pervasive computing recently garnered a lot of attention due to its high demand in various application domains. Human activity recognition (HAR) considered as the applications that are widely explored by the expertise that provides valuable information to the human. Accelerometer sensor-based approach is utilized as devices to undergo the research in HAR since their small in size and this sensor already build-in in the various type of smartphones. However, the existence of high inter-class similarities among the class tends to degrade the recognition performance. Hence, this work presents the method for activity recognition using our proposed features from combinational of spectral analysis with statistical descriptors that able to tackle the issue of differentiating stationary and locomotion activities. The noise signal is filtered using Fourier Transform before it will be extracted using two different groups of features, spectral frequency analysis, and statistical descriptors. Extracted signal later will be classified using random forest ensemble classifier models. The recognition results show the good accuracy performance for stationary and locomotion activities based on USC HAD datasets.

Literacy and Informational Interviews

ERIC Educational Resources Information Center

Decarie, Christina

2010-01-01

Informational interviews are valuable tools for improving writing, editing, and interviewing skills, and they are also extremely valuable in improving the soft skills that are valued by employers, such as confidence, adaptability, the ability to set and keep deadlines, the ability to manage risk, and so on. These soft skills, this article argues,…

Methods of analysis by the U.S. Geological Survey Organic Geochemistry Research Group : determination of selected herbicides and their degradation products in water using solid-phase extraction and gas chromatography/mass spectrometry

USGS Publications Warehouse

Kish, J.L.; Thurman, E.M.; Scribner, E.A.; Zimmerman, L.R.

2000-01-01

A method for the extraction and analysis of eight herbicides and five degradation products using solid-phase extraction from natural water samples followed by gas chromatography/mass spectrometry is presented in this report. This method was developed for dimethenamid; flufenacet; fluometuron and its degradation products, demethylfluometuron (DMFM), 3-(trifluromethyl)phenylurea (TFMPU), 3-(trifluromethyl)-aniline (TFMA); molinate; norflurazon and its degradation product, demethylnorflurazon; pendamethalin; the degradation product of prometryn, deisopropylprometryn; propanil; and trifluralin. The eight herbicides are used primarily in the southern United States where cotton, rice, and soybeans are produced. The exceptions are dimethenamid and flufenacet, which are used on corn in the Midwest. Water samples received by the U.S. Geological Survey's Organic Geochemistry Research Group in Lawrence, Kansas, are filtered to remove suspended particulate matter and then passed through disposable solid-phase extraction columns containing octadecyl-bonded porous silica (C-18) to extract the compounds. The herbicides and their degradation products are removed from the column by ethyl acetate elution. The eluate is evaporated under nitrogen, and components then are separated, identified, and quantified by injecting an aliquot of the concentrated extract into a high-resolution, fused-silica capillary column of a gas chromatograph/mass spectrometer under selected-ion mode. Method detection limits ranged from 0.02 to 0.05 ?g/L for all compounds with the exception of TFMPU, which has a method detection limit of 0.32 ?g/L. The mean absolute recovery is 107 percent. This method for the determination of herbicides and their degradation products is valuable for acquiring information about water quality and compound fate and transport in water.

Ensembles of adaptive spatial filters increase BCI performance: an online evaluation

NASA Astrophysics Data System (ADS)

Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin

2016-08-01

Objective: In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain-computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Approach: Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. Main results: The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. Significance: CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI inefficiency to one-fourth in comparison to previous non-adaptive paradigms.

Ensembles of adaptive spatial filters increase BCI performance: an online evaluation.

PubMed

Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin

2016-08-01

In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain-computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI inefficiency to one-fourth in comparison to previous non-adaptive paradigms.

New technology of extracting the amount of rare earth metals from the red mud

NASA Astrophysics Data System (ADS)

Martoyan, G. A.; Karamyan, G. G.; Vardan, G. A.

2016-01-01

The paper outlined the environmental and economic problems associated with red mud - the waste generated in processing of bauxite ore for aluminum production. The chemical analysis of red mud has identified a number of useful elements including rare earth metals. The electromembrane technology of red mud processing with extraction of valuable elements is described. A possible scheme of separation of these metals through electrolysis is also given.

Technologies for Extracting Valuable Metals and Compounds from Geothermal Fluids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harrison, Stephen

2014-04-30

Executive Summary Simbol Materials studied various methods of extracting valuable minerals from geothermal brines in the Imperial Valley of California, focusing on the extraction of lithium, manganese, zinc and potassium. New methods were explored for managing the potential impact of silica fouling on mineral extraction equipment, and for converting silica management by-products into commercial products.` Studies at the laboratory and bench scale focused on manganese, zinc and potassium extraction and the conversion of silica management by-products into valuable commercial products. The processes for extracting lithium and producing lithium carbonate and lithium hydroxide products were developed at the laboratory scale andmore » scaled up to pilot-scale. Several sorbents designed to extract lithium as lithium chloride from geothermal brine were developed at the laboratory scale and subsequently scaled-up for testing in the lithium extraction pilot plant. Lithium The results of the lithium studies generated the confidence for Simbol to scale its process to commercial operation. The key steps of the process were demonstrated during its development at pilot scale: 1. Silica management. 2. Lithium extraction. 3. Purification. 4. Concentration. 5. Conversion into lithium hydroxide and lithium carbonate products. Results show that greater than 95% of the lithium can be extracted from geothermal brine as lithium chloride, and that the chemical yield in converting lithium chloride to lithium hydroxide and lithium carbonate products is greater than 90%. The product purity produced from the process is consistent with battery grade lithium carbonate and lithium hydroxide. Manganese and zinc Processes for the extraction of zinc and manganese from geothermal brine were developed. It was shown that they could be converted into zinc metal and electrolytic manganese dioxide after purification. These processes were evaluated for their economic potential, and at the present time Simbol Materials is evaluating other products with greater commercial value. Potassium Silicotitanates, zeolites and other sorbents were evaluated as potential reagents for the extraction of potassium from geothermal brines and production of potassium chloride (potash). It was found that zeolites were effective at removing potassium but the capacity of the zeolites and the form that the potassium is in does not have economic potential. Iron-silica by-product The conversion of iron-silica by-product produced during silica management operations into more valuable materials was studied at the laboratory scale. Results indicate that it is technically feasible to convert the iron-silica by-product into ferric chloride and ferric sulfate solutions which are precursors to a ferric phosphate product. However, additional work to purify the solutions is required to determine the commercial viability of this process. Conclusion Simbol Materials is in the process of designing its first commercial plant based on the technology developed to the pilot scale during this project. The investment in the commercial plant is hundreds of millions of dollars, and construction of the commercial plant will generate hundreds of jobs. Plant construction will be completed in 2016 and the first lithium products will be shipped in 2017. The plant will have a lithium carbonate equivalent production capacity of 15,000 tonnes per year. The gross revenues from the project are expected to be approximately $ 80 to 100 million annually. During this development program Simbol grew from a company of about 10 people to over 60 people today. Simbol is expected to employ more than 100 people once the plant is constructed. Simbol Materials’ business is scalable in the Imperial Valley region because there are eleven geothermal power plants already in operation, which allows Simbol to expand its business from one plant to multiple plants. Additionally, the scope of the resource is vast in terms of potential products such as lithium, manganese and zinc and potentially potassium.« less

Inhibitory effect of fruit extracts on the formation of heterocyclic amines.

PubMed

Cheng, Ka-Wing; Wu, Qingli; Zheng, Zong Ping; Peng, Xiaofang; Simon, James E; Chen, Feng; Wang, Mingfu

2007-12-12

Natural extracts have attracted considerable attention for development into effective inhibitors against the formation of genotoxic heterocyclic amines (HAs) in processed foods. In this study, four fruit extracts (apple, elderberry, grape seed, and pineapple) were evaluated for their effects on HA formation in fried beef patties. Apple and grape seed extracts were found to be the most effective in both the degree of inhibition in the formation of individual HAs (2-amino-3,8-dimethylimidazo [4,5-f]quinoxaline (MeIQx), 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (4,8-DiMeIQx), and 2-amino-1-methyl-6-henylimidazo [4,5-b]pyridine (PhIP)) and in the reduction of total HA content (approximately 70% relative to the control). Activity-guided analysis of apple extract using model systems (PhIP- and MeIQx-producing models) showed that the proanthocyanidins, phloridzin and chlorogenic acid were responsible for reducing the amount of HAs formed. Proanthocyanidins were identified as the dominant inhibitors because they were strongly active against HA formation in both the PhIP and MeIQx model systems. For phloridzin, the inhibitory effect was observed only on the formation of PhIP. In contrast, chlorogenic acid, although effective against the formation of MeIQx, significantly enhanced the formation of PhIP. This is the first report showing the inhibitory activities of apple phenolics on the formation of heterocyclic amines. The findings provide valuable information for the development of effective strategies to minimize HA content of cooked meats and to identify several new natural products that may have new applications in the food industry.

Thermodynamic Insight into the Solvation and Complexation Behavior of U(VI) in Ionic Liquid: Binding of CMPO with U(VI) Studied by Optical Spectroscopy and Calorimetry.

PubMed

Wu, Qi; Sun, Taoxiang; Meng, Xianghai; Chen, Jing; Xu, Chao

2017-03-06

The complexation of U(VI) with octylphenyl-N,N-diisobutylcarbamoylmethylphosphine oxide (CMPO, denoted as L) in ionic liquid (IL) C 4 mimNTf 2 was investigated by UV-vis absorption spectrophotometry and isothermal titration calorimetry. Spectro-photometric titration suggests that three successive complexes, UO 2 L j 2+ (j = 1-3), formed both in "dry" (water content < 250 ppm) and "wet" (water content ≈ 12 500 ppm) ionic liquid. However, the thermodynamic parameters are distinctly different in the two ILs. In dry IL, the complexation strength between CMPO and U(VI) is much stronger, with stability constants of the respective complexes more than 1 order of magnitude higher than that in wet IL. Energetically, the complexation of U(VI) with CMPO in dry IL is mainly driven by negative enthalpies. In contrast, the complexation in wet IL is overwhelmingly driven by highly positive entropies as a result of the release of a large amount of water molecules from the solvation sphere of U(VI). Moreover, comparisons between the fitted absorption spectra of complexes in wet IL and that of extractive samples from solvent extraction have identified the speciation involved in the extraction of U(VI) by CMPO in ionic liquid. The results from this study not only offer a thermodynamic insight into the complexation behavior of U(VI) with CMPO in IL but also provide valuable information for understanding the extraction behavior in the corresponding solvent extraction system.

Learning about individuals' health from aggregate data.

PubMed

Colbaugh, Rich; Glass, Kristin

2017-07-01

There is growing awareness that user-generated social media content contains valuable health-related information and is more convenient to collect than typical health data. For example, Twitter has been employed to predict aggregate-level outcomes, such as regional rates of diabetes and child poverty, and to identify individual cases of depression and food poisoning. Models which make aggregate-level inferences can be induced from aggregate data, and consequently are straightforward to build. In contrast, learning models that produce individual-level (IL) predictions, which are more informative, usually requires a large number of difficult-to-acquire labeled IL examples. This paper presents a new machine learning method which achieves the best of both worlds, enabling IL models to be learned from aggregate labels. The algorithm makes predictions by combining unsupervised feature extraction, aggregate-based modeling, and optimal integration of aggregate-level and IL information. Two case studies illustrate how to learn health-relevant IL prediction models using only aggregate labels, and show that these models perform as well as state-of-the-art models trained on hundreds or thousands of labeled individuals.

Improving mental task classification by adding high frequency band information.

PubMed

Zhang, Li; He, Wei; He, Chuanhong; Wang, Ping

2010-02-01

Features extracted from delta, theta, alpha, beta and gamma bands spanning low frequency range are commonly used to classify scalp-recorded electroencephalogram (EEG) for designing brain-computer interface (BCI) and higher frequencies are often neglected as noise. In this paper, we implemented an experimental validation to demonstrate that high frequency components could provide helpful information for improving the performance of the mental task based BCI. Electromyography (EMG) and electrooculography (EOG) artifacts were removed by using blind source separation (BSS) techniques. Frequency band powers and asymmetry ratios from the high frequency band (40-100 Hz) together with those from the lower frequency bands were used to represent EEG features. Finally, Fisher discriminant analysis (FDA) combining with Mahalanobis distance were used as the classifier. In this study, four types of classifications were performed using EEG signals recorded from four subjects during five mental tasks. We obtained significantly higher classification accuracy by adding the high frequency band features compared to using the low frequency bands alone, which demonstrated that the information in high frequency components from scalp-recorded EEG is valuable for the mental task based BCI.

An evaluation of the suitability of ERTS data for the purposes of petroleum exploration. [Anadarko Basin of Texas and Oklahoma

NASA Technical Reports Server (NTRS)

Collins, R. J.; Mccown, F. P.; Stonis, L. P.; Petzel, G.; Everett, J. R.

1974-01-01

This experiment was designed to determine the types and amounts of information valuable to petroleum exploration extractable from ERTS data and the cost of obtaining the information using traditional or conventional means. It was desired that an evaluation of this new petroleum exploration tool be made in a geologically well known area in order to assess its usefulness in an unknown area. The Anadarko Basin lies in western Oklahoma and the panhandle of Texas. It was chosen as a test site because there is a great deal of published information available on the surface and subsurface geology of the area, and there are many known structures that act as traps for hydrocarbons. This basin is similar to several other large epicontinental sedimentary basins. It was found that ERTS imagery is an excellent tool for reconnaissance exploration of large sedimentary basins or new exploration provinces. For the first time, small and medium size oil companies can rapidly and effectively analyze exploration provinces as a whole.

Big Data of the Cosmic Web

NASA Astrophysics Data System (ADS)

Kitaura, Francisco-Shu

2016-10-01

One of the main goals in cosmology is to understand how the Universe evolves, how it forms structures, why it expands, and what is the nature of dark matter and dark energy. Next decade large and expensive observational projects will bring information on the structure and the distribution of many millions of galaxies at different redshifts enabling us to make great progress in answering these questions. However, these data require a very special and complex set of analysis tools to extract the maximum valuable information. Statistical inference techniques are being developed, bridging the gaps between theory, simulations, and observations. In particular, we discuss the efforts to address the question: What is the underlying nonlinear matter distribution and dynamics at any cosmic time corresponding to a set of observed galaxies in redshift space? An accurate reconstruction of the initial conditions encodes the full phase-space information at any later cosmic time (given a particular structure formation model and a set of cosmological parameters). We present advances to solve this problem in a self-consistent way with Big Data techniques of the Cosmic Web.

Site Selection for the First Sustainable Mars Base

NASA Astrophysics Data System (ADS)

Barker, D. C.; James, G.; Chamitoff, G.; Clifford, S.

2015-10-01

Water is the most valuable resource needed for human habitability and its location and ease of extraction should be the main constraint for defining a sustainable and growing human settlement on Mars followed by exploration and scientific objectives.

Recontextualizing Military Structures along the Stanegate and Hadrian's Wall Utilizing Aerial Photography and GIS Mapping

NASA Astrophysics Data System (ADS)

Sieteski, Sara

This dissertation examines the region along the Stanegate frontier, just below Hadrian's Wall, on both a macroscopic and microscopic level, to analyze how landscape affected placement of forts, camps, and other military structures. It aims to explore known archaeological structures as well as expose new areas of interest, not yet discovered through traditional survey methods. It asks the question of whether temporary structures helped lead to the development of permanent structures, as part of the overall limes defensive strategy. While a lack of archaeological dating on many of these structures often provides the greatest challenge, the aim is to determine what additional information can be deduced about how landscape affected this region and to set an agenda of future survey work, designed to improve our understanding of it. In addition, this approach aims to improve understanding of the function of these installations and their relationship to the Wall and each other. Aerial photography and the construction of a geographic information system (GIS) can prove a valuable tool in surveying the region, to extract data from forts, camps, and recently discovered land depressions. Measurements can be taken to determine if there is a similar building pattern which might reflect contemporaneous construction periods. Distances between structures can be taken to determine the significance of their spacing and arrangement. In addition, data sets containing information on bedrock, ancient woodlands, ecology, and hydrology can provide valuable insight on the topography of each site. This work is meant to serve as a foundational piece for future scholars to build upon to continue to expand our understanding of the region, as computational methods become more sophisticated and data access becomes more readily available across the globe.

The Prostate, Lung, Colorectal and Ovarian Cancer (PLCO) Screening Trial Pathology Tissue Resource.

PubMed

Zhu, Claire S; Huang, Wen-Yi; Pinsky, Paul F; Berg, Christine D; Sherman, Mark; Yu, Kelly J; Carrick, Danielle M; Black, Amanda; Hoover, Robert; Lenz, Petra; Williams, Craig; Hawkins, Laura; Chaloux, Matthew; Yurgalevitch, Susan; Mathew, Sunitha; Miller, Amy; Olivo, Vanessa; Khan, Asia; Pretzel, Shannon M; Multerer, Deborah; Beckmann, Patricia; Broski, Karen G; Freedman, Neal D

2016-12-01

Pathology tissue specimens with associated epidemiologic and clinical data are valuable for cancer research. The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial undertook a large-scale effort to create a public resource of pathology tissues from PLCO participants who developed a cancer during the trial. Formalin-fixed paraffin-embedded tissue blocks were obtained from pathology laboratories on a loan basis for central processing of tissue microarrays, with additional free-standing tissue cores collected for nucleic acid extraction. Pathology tissue specimens were obtained for prostate cancer (n = 1,052), lung cancer (n = 434), colorectal cancer (n = 675) and adenoma (n = 658), ovarian cancer and borderline tumors (n = 212), breast cancer (n = 870), and bladder cancer (n = 204). The process of creating this resource was complex, involving multidisciplinary teams with expertise in pathology, epidemiology, information technology, project management, and specialized laboratories. Creating the PLCO tissue resource required a multistep process, including obtaining medical records and contacting pathology departments where pathology materials were stored after obtaining necessary patient consent and authorization. The potential to link tissue biomarkers to prospectively collected epidemiologic information, screening and clinical data, and matched blood or buccal samples offers valuable opportunities to study etiologic heterogeneity, mechanisms of carcinogenesis, and biomarkers for early detection and prognosis. The methods and protocols developed for this effort, and the detailed description of this resource provided here, will be useful for those seeking to use PLCO pathology tissue specimens for their research and may also inform future tissue collection efforts in other settings. Cancer Epidemiol Biomarkers Prev; 25(12); 1635-42. ©2016 AACR. ©2016 American Association for Cancer Research.

Antioxidant Activities and Caffeic Acid Content in New Zealand Asparagus (Asparagus officinalis) Roots Extracts

PubMed Central

Zhang, Hongxia; Al-Juhaimi, Fahad Y.; Bekhit, Alaa El-Din Ahmed

2018-01-01

Asparagus officinalis are perennial plants that require re-planting every 10–20 years. The roots are traditionally mulched in the soil or treated as waste. The A. officinalis roots (AR) contain valuable bioactive compounds that may have some health benefiting properties. The aim of this study was to investigate the total polyphenol and flavonoid contents (TPC and TFC, respectively) and antioxidant (2,2-diphenyl-1-picrylhydrazyl (DPPH), Oxygen Radical Absorbance Capacity (ORAC) and Ferric Reducing/Antioxidant Power (FRAP) assays) activities of New Zealand AR extract. The antioxidant activity decreased with a longer extraction time. PMID:29617287

An automated processing chains for surface temperature monitoring on Earth's most active volcanoes by optical data from multiple satellites

NASA Astrophysics Data System (ADS)

Silvestri, Malvina; Musacchio, Massimo; Fabrizia Buongiorno, Maria

2017-04-01

The Geohazards Exploitation Platform, or GEP is one of six Thematic Exploitation Platforms developed by ESA to serve data user communities. As a new element of the ground segment delivering satellite results to users, these cloud-based platforms provide an online environment to access information, processing tools, computing resources for community collaboration. The aim is to enable the easy extraction of valuable knowledge from vast quantities of satellite-sensed data now being produced by Europe's Copernicus programme and other Earth observation satellites. In this context, the estimation of surface temperature on active volcanoes around the world is considered. E2E processing chains have been developed for different satellite data (ASTER, Landsat8 and Sentinel 3 missions) using thermal infrared (TIR) channels by applying specific algorithms. These chains have been implemented on the GEP platform enabling the use of EO missions and the generation of added value product such as surface temperature map, from not skilled users. This solution will enhance the use of satellite data and improve the dissemination of the results saving valuable time (no manual browsing, downloading or processing is needed) and producing time series data that can be speedily extracted from a single co-registered pixel, to highlight gradual trends within a narrow area. Moreover, thanks to the high-resolution optical imagery of Sentinel 2 (MSI), the detection of lava maps during an eruption can be automatically obtained. The proposed lava detection method is based on a contextual algorithm applied to Sentinel-2 NIR (band 8 - 0.8 micron) and SWIR (band 12 - 2.25 micron) data. Examples derived by last eruptions on active volcanoes are showed.

World data centre for microorganisms: an information infrastructure to explore and utilize preserved microbial strains worldwide

PubMed Central

Wu, Linhuan; Sun, Qinglan; Desmeth, Philippe; Sugawara, Hideaki; Xu, Zhenghong; McCluskey, Kevin; Smith, David; Alexander, Vasilenko; Lima, Nelson; Ohkuma, Moriya; Robert, Vincent; Zhou, Yuguang; Li, Jianhui; Fan, Guomei; Ingsriswang, Supawadee; Ozerskaya, Svetlana; Ma, Juncai

2017-01-01

The World Data Centre for Microorganisms (WDCM) was established 50 years ago as the data center of the World Federation for Culture Collections (WFCC)—Microbial Resource Center (MIRCEN). WDCM aims to provide integrated information services using big data technology for microbial resource centers and microbiologists all over the world. Here, we provide an overview of WDCM including all of its integrated services. Culture Collections Information Worldwide (CCINFO) provides metadata information on 708 culture collections from 72 countries and regions. Global Catalogue of Microorganism (GCM) gathers strain catalogue information and provides a data retrieval, analysis, and visualization system of microbial resources. Currently, GCM includes >368 000 strains from 103 culture collections in 43 countries and regions. Analyzer of Bioresource Citation (ABC) is a data mining tool extracting strain related publications, patents, nucleotide sequences and genome information from public data sources to form a knowledge base. Reference Strain Catalogue (RSC) maintains a database of strains listed in International Standards Organization (ISO) and other international or regional standards. RSC allocates a unique identifier to strains recommended for use in diagnosis and quality control, and hence serves as a valuable cross-platform reference. WDCM provides free access to all these services at www.wdcm.org. PMID:28053166

MDANSE: An Interactive Analysis Environment for Molecular Dynamics Simulations.

PubMed

Goret, G; Aoun, B; Pellegrini, E

2017-01-23

The MDANSE software-Molecular Dynamics Analysis of Neutron Scattering Experiments-is presented. It is an interactive application for postprocessing molecular dynamics (MD) simulations. Given the widespread use of MD simulations in material and biomolecular sciences to get a better insight for experimental techniques such as thermal neutron scattering (TNS), the development of MDANSE has focused on providing a user-friendly, interactive, graphical user interface for analyzing many trajectories in the same session and running several analyses simultaneously independently of the interface. This first version of MDANSE already proposes a broad range of analyses, and the application has been designed to facilitate the introduction of new analyses in the framework. All this makes MDANSE a valuable tool for extracting useful information from trajectories resulting from a wide range of MD codes.

Kinetic modeling in PET imaging of hypoxia

PubMed Central

Li, Fan; Joergensen, Jesper T; Hansen, Anders E; Kjaer, Andreas

2014-01-01

Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia. PMID:25250200

The electromagnetic multipole moments of the charged open-flavor {Z}_{\\bar{c}q} states

NASA Astrophysics Data System (ADS)

Azizi, K.; Özdem, U.

2018-05-01

The electromagnetic multipole moments of the open-flavor {Z}\\bar{cq} states are investigated by assuming a diquark–antidiquark picture for their internal structure and quantum numbers {J}{PC}={1}+- for their spin-parity. In particular, their magnetic and quadrupole moments are extracted in the framework of light-cone QCD sum rule by the help of the photon distribution amplitudes. The electromagnetic multipole moments of the open-flavor {Z}\\bar{cq} states are important dynamical observables, which encode valuable information on their underlying structure. The results obtained for the magnetic moments of different structures are considerably large and can be measured in future experiments. We obtain very small values for the quadrupole moments of {Z}\\bar{cq} states indicating a nonspherical charge distribution.

Sentiment topic mining based on comment tags

NASA Astrophysics Data System (ADS)

Zhang, Daohai; Liu, Xue; Li, Juan; Fan, Mingyue

2018-03-01

With the development of e-commerce, various comments based on tags are generated, how to extract valuable information from these comment tags has become an important content of business management decisions. This study takes HUAWEI mobile phone tags as an example using the sentiment analysis and topic LDA mining method. The first step is data preprocessing and classification of comment tag topic mining. And then make the sentiment classification for comment tags. Finally, mine the comments again and analyze the emotional theme distribution under different sentiment classification. The results show that HUAWEI mobile phone has a good user experience in terms of fluency, cost performance, appearance, etc. Meanwhile, it should pay more attention to independent research and development, product design and development. In addition, battery and speed performance should be enhanced.

Cerebellar Abiotrophy Across Domestic Species.

PubMed

Scott, Erica Yuki; Woolard, Kevin Douglas; Finno, Carrie J; Murray, James D

2018-06-01

Cerebellar abiotrophy (CA) is a neurodegenerative disorder affecting the cerebellum and occurs in multiple species. Although CA is well researched in humans and mice, domestic species such as the dog, cat, sheep, cow, and horse receive little recognition. This may be due to few studies addressing the mechanism of CA in these species. However, valuable information can still be extracted from these cases. A review of the clinicohistologic phenotype of CA in these species and determining the various etiologies of CA may aid in determining conserved and required pathways necessary for proper cerebellar development and function. This review outlines research approaches of studies of CA in domestic species, compared to the approaches used in mice, with the objective of comparing CA in domestic species while identifying areas for further research efforts.

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

PubMed

Bulbul, Gonca; Chaves, Gepoliano; Olivier, Joseph; Ozel, Rifat Emrah; Pourmand, Nader

2018-06-06

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology.

On-line monitoring of fluid bed granulation by photometric imaging.

PubMed

Soppela, Ira; Antikainen, Osmo; Sandler, Niklas; Yliruusi, Jouko

2014-11-01

This paper introduces and discusses a photometric surface imaging approach for on-line monitoring of fluid bed granulation. Five granule batches consisting of paracetamol and varying amounts of lactose and microcrystalline cellulose were manufactured with an instrumented fluid bed granulator. Photometric images and NIR spectra were continuously captured on-line and particle size information was extracted from them. Also key process parameters were recorded. The images provided direct real-time information on the growth, attrition and packing behaviour of the batches. Moreover, decreasing image brightness in the drying phase was found to indicate granule drying. The changes observed in the image data were also linked to the moisture and temperature profiles of the processes. Combined with complementary process analytical tools, photometric imaging opens up possibilities for improved real-time evaluation fluid bed granulation. Furthermore, images can give valuable insight into the behaviour of excipients or formulations during product development. Copyright © 2014 Elsevier B.V. All rights reserved.

Application of ERTS images and image processing to regional geologic problems and geologic mapping in northern Arizona

NASA Technical Reports Server (NTRS)

Goetz, A. F. H. (Principal Investigator); Billingsley, F. C.; Gillespie, A. R.; Abrams, M. J.; Squires, R. L.; Shoemaker, E. M.; Lucchitta, I.; Elston, D. P.

1975-01-01

The author has identified the following significant results. Computer image processing was shown to be both valuable and necessary in the extraction of the proper subset of the 200 million bits of information in an ERTS image to be applied to a specific problem. Spectral reflectivity information obtained from the four MSS bands can be correlated with in situ spectral reflectance measurements after path radiance effects have been removed and a proper normalization has been made. A detailed map of the major fault systems in a 90,000 sq km area in northern Arizona was compiled from high altitude photographs and pre-existing published and unpublished map data. With the use of ERTS images, three major fault systems, the Sinyala, Bright Angel, and Mesa Butte, were identified and their full extent measured. A byproduct of the regional studies was the identification of possible sources of shallow ground water, a scarce commodity in these regions.

A microseismic workflow for managing induced seismicity risk as CO 2 storage projects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matzel, E.; Morency, C.; Pyle, M.

2015-10-27

It is well established that fluid injection has the potential to induce earthquakes—from microseismicity to large, damaging events—by altering state-of-stress conditions in the subsurface. While induced seismicity has not been a major operational issue for carbon storage projects to date, a seismicity hazard exists and must be carefully addressed. Two essential components of effective seismic risk management are (1) sensitive microseismic monitoring and (2) robust data interpretation tools. This report describes a novel workflow, based on advanced processing algorithms applied to microseismic data, to help improve management of seismic risk. This workflow has three main goals: (1) to improve themore » resolution and reliability of passive seismic monitoring, (2) to extract additional, valuable information from continuous waveform data that is often ignored in standard processing, and (3) to minimize the turn-around time between data collection, interpretation, and decision-making. These three objectives can allow for a better-informed and rapid response to changing subsurface conditions.« less

Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer.

PubMed

Hoogendoorn, Mark; Szolovits, Peter; Moons, Leon M G; Numans, Mattijs E

2016-05-01

Machine learning techniques can be used to extract predictive models for diseases from electronic medical records (EMRs). However, the nature of EMRs makes it difficult to apply off-the-shelf machine learning techniques while still exploiting the rich content of the EMRs. In this paper, we explore the usage of a range of natural language processing (NLP) techniques to extract valuable predictors from uncoded consultation notes and study whether they can help to improve predictive performance. We study a number of existing techniques for the extraction of predictors from the consultation notes, namely a bag of words based approach and topic modeling. In addition, we develop a dedicated technique to match the uncoded consultation notes with a medical ontology. We apply these techniques as an extension to an existing pipeline to extract predictors from EMRs. We evaluate them in the context of predictive modeling for colorectal cancer (CRC), a disease known to be difficult to diagnose before performing an endoscopy. Our results show that we are able to extract useful information from the consultation notes. The predictive performance of the ontology-based extraction method moves significantly beyond the benchmark of age and gender alone (area under the receiver operating characteristic curve (AUC) of 0.870 versus 0.831). We also observe more accurate predictive models by adding features derived from processing the consultation notes compared to solely using coded data (AUC of 0.896 versus 0.882) although the difference is not significant. The extracted features from the notes are shown be equally predictive (i.e. there is no significant difference in performance) compared to the coded data of the consultations. It is possible to extract useful predictors from uncoded consultation notes that improve predictive performance. Techniques linking text to concepts in medical ontologies to derive these predictors are shown to perform best for predicting CRC in our EMR dataset. Copyright © 2016 Elsevier B.V. All rights reserved.

Accurate quantification of 5 German cockroach (GCr) allergens in complex extracts using multiple reaction monitoring mass spectrometry (MRM MS).

PubMed

Mindaye, S T; Spiric, J; David, N A; Rabin, R L; Slater, J E

2017-12-01

German cockroach (GCr) allergen extracts are complex and heterogeneous products, and methods to better assess their potency and composition are needed for adequate studies of their safety and efficacy. The objective of this study was to develop an assay based on liquid chromatography and multiple reaction monitoring mass spectrometry (LC-MRM MS) for rapid, accurate, and reproducible quantification of 5 allergens (Bla g 1, Bla g 2, Bla g 3, Bla g 4, and Bla g 5) in crude GCr allergen extracts. We first established a comprehensive peptide library of allergens from various commercial extracts as well as recombinant allergens. Peptide mapping was performed using high-resolution MS, and the peptide library was then used to identify prototypic and quantotypic peptides to proceed with MRM method development. Assay development included a systematic optimization of digestion conditions (buffer, digestion time, and trypsin concentration), chromatographic separation, and MS parameters. Robustness and suitability were assessed following ICH (Q2 [R1]) guidelines. The method is precise (RSD < 10%), linear over a wide range (r > 0.99, 0.01-1384 fmol/μL), and sensitive (LLOD and LLOQ <1 fmol/μL). Having established the parameters for LC-MRM MS, we quantified allergens from various commercial GCr extracts and showed considerable variability that may impact clinical efficacy. Our data demonstrate that the LC-MRM MS method is valuable for absolute quantification of allergens in GCr extracts and likely has broader applicability to other complex allergen extracts. Definitive quantification provides a new standard for labelling of allergen extracts, which will inform patient care, enable personalized therapy, and enhance the efficacy of immunotherapy for environmental and food allergies. © 2017 The Authors. Clinical & Experimental Allergy published by John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Method for detecting damage in carbon-fibre reinforced plastic-steel structures based on eddy current pulsed thermography

NASA Astrophysics Data System (ADS)

Li, Xuan; Liu, Zhiping; Jiang, Xiaoli; Lodewijks, Gabrol

2018-01-01

Eddy current pulsed thermography (ECPT) is well established for non-destructive testing of electrical conductive materials, featuring the advantages of contactless, intuitive detecting and efficient heating. The concept of divergence characterization of the damage rate of carbon fibre-reinforced plastic (CFRP)-steel structures can be extended to ECPT thermal pattern characterization. It was found in this study that the use of ECPT technology on CFRP-steel structures generated a sizeable amount of valuable information for comprehensive material diagnostics. The relationship between divergence and transient thermal patterns can be identified and analysed by deploying mathematical models to analyse the information about fibre texture-like orientations, gaps and undulations in these multi-layered materials. The developed algorithm enabled the removal of information about fibre texture and the extraction of damage features. The model of the CFRP-glue-steel structures with damage was established using COMSOL Multiphysics® software, and quantitative non-destructive damage evaluation from the ECPT image areas was derived. The results of this proposed method illustrate that damaged areas are highly affected by available information about fibre texture. This proposed work can be applied for detection of impact induced damage and quantitative evaluation of CFRP structures.

Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations.

PubMed

Hoogendoorn, Mark; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

2017-09-01

Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients, we are able to show that we can predict therapy outcome with an area under the curve of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants, it is hard to generalize the results, but they do show great potential in this type of information.

Oral History and American Advertising: How the "Pepsi Generation" Came Alive.

ERIC Educational Resources Information Center

Dreyfus, Carol; Connors, Thomas

1985-01-01

Described is a project in which the Archives Center of the National Museum of American History and the George Meany Memorial Archives analyzed a collection of advertising materials of the Pepsi-Cola USA company and conducted interviews to gather historically valuable information concerning the company. Valuable social history information was…

A PC-aided optical foetal heart rate detection system.

PubMed

Oweis, Rami J; As'ad, Hala; Aldarawsheh, Amany; Al-Khdeirat, Rawan; Lwissy, Kaldoun

2014-01-01

Safe monitoring of foetal heart rate is a valuable tool for the healthy evolution and wellbeing of both foetus and mother. This paper presents a non-invasive optical technique that allows for foetal heart rate detection using a photovoltaic infrared (IR) detector placed on the mother's abdomen. The system presented here consists of a photoplethysmography (PPG) circuit, abdomen circuit and a personal computer equipped with MATLAB. A near IR beam having a wavelength of 880 nm is transmitted through the mother's abdomen and foetal tissue. The received abdominal signal that conveys information pertaining to the mother and foetal heart rate is sensed by a low noise photodetector. The PC receives the signal through the National Instrumentation Data Acquisition Card (NIDAQ). After synchronous detection of the abdominal and finger PPG signals, the designed MATLAB-based software saves, analyses and extracts information related to the foetal heart rate. Extraction is carried out using recursive least squares adaptive filtration. Measurements on eight pregnant women with gestational periods ranging from 35-39 weeks were performed using the proposed system and CTG. Results show a correlation coefficient of 0.978 and a correlation confidence interval between 88-99.6%. The t test results in a p value of 0.034, which is less than 0.05. Low power, low cost, high signal-to-noise ratio, reduction of ambient light effect and ease of use are the main characteristics of the proposed system.

Geoparsing text for characterizing urban operational environments through machine learning techniques

NASA Astrophysics Data System (ADS)

Garfinkle, Noah W.; Selig, Lucas; Perkins, Timothy K.; Calfas, George W.

2017-05-01

Increasing worldwide internet connectivity and access to sources of print and open social media has increased near realtime availability of textual information. Capabilities to structure and integrate textual data streams can contribute to more meaningful representations of operational environment factors (i.e., Political, Military, Economic, Social, Infrastructure, Information, Physical Environment, and Time [PMESII-PT]) and tactical civil considerations (i.e., Areas, Structures, Capabilities, Organizations, People and Events [ASCOPE]). However, relying upon human analysts to encode this information as it arrives quickly proves intractable. While human analysts possess an ability to comprehend context in unstructured text far beyond that of computers, automated geoparsing (the extraction of locations from unstructured text) can empower analysts to automate sifting through datasets for areas of interest. This research evaluates existing approaches to geoprocessing as well as initiating the research and development of locally-improved methods of tagging parts of text as possible locations, resolving possible locations into coordinates, and interfacing such results with human analysts. The objective of this ongoing research is to develop a more contextually-complete picture of an area of interest (AOI) including human-geographic context for events. In particular, our research is working to make improvements to geoparsing (i.e., the extraction of spatial context from documents), which requires development, integration, and validation of named-entity recognition (NER) tools, gazetteers, and entity-attribution. This paper provides an overview of NER models and methodologies as applied to geoparsing, explores several challenges encountered, presents preliminary results from the creation of a flexible geoparsing research pipeline, and introduces ongoing and future work with the intention of contributing to the efficient geocoding of information containing valuable insights into human activities in space.

Revisiting Frazier's subdeltas: enhancing datasets with dimensionality, better to understand geologic systems

USGS Publications Warehouse

Flocks, James

2006-01-01

Scientific knowledge from the past century is commonly represented by two-dimensional figures and graphs, as presented in manuscripts and maps. Using today's computer technology, this information can be extracted and projected into three- and four-dimensional perspectives. Computer models can be applied to datasets to provide additional insight into complex spatial and temporal systems. This process can be demonstrated by applying digitizing and modeling techniques to valuable information within widely used publications. The seminal paper by D. Frazier, published in 1967, identified 16 separate delta lobes formed by the Mississippi River during the past 6,000 yrs. The paper includes stratigraphic descriptions through geologic cross-sections, and provides distribution and chronologies of the delta lobes. The data from Frazier's publication are extensively referenced in the literature. Additional information can be extracted from the data through computer modeling. Digitizing and geo-rectifying Frazier's geologic cross-sections produce a three-dimensional perspective of the delta lobes. Adding the chronological data included in the report provides the fourth-dimension of the delta cycles, which can be visualized through computer-generated animation. Supplemental information can be added to the model, such as post-abandonment subsidence of the delta-lobe surface. Analyzing the regional, net surface-elevation balance between delta progradations and land subsidence is computationally intensive. By visualizing this process during the past 4,500 yrs through multi-dimensional animation, the importance of sediment compaction in influencing both the shape and direction of subsequent delta progradations becomes apparent. Visualization enhances a classic dataset, and can be further refined using additional data, as well as provide a guide for identifying future areas of study.

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Automated identification and geometrical features extraction of individual trees from Mobile Laser Scanning data in Budapest

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Székely, Balázs; Folly-Ritvay, Zoltán; Skobrák, Ferenc; Koenig, Kristina; Höfle, Bernhard

2016-04-01

Mobile Laser Scanning (MLS) is an evolving operational measurement technique for urban environment providing large amounts of high resolution information about trees, street features, pole-like objects on the street sides or near to motorways. In this study we investigate a robust segmentation method to extract the individual trees automatically in order to build an object-based tree database system. We focused on the large urban parks in Budapest (Margitsziget and Városliget; KARESZ project) which contained large diversity of different kind of tree species. The MLS data contained high density point cloud data with 1-8 cm mean absolute accuracy 80-100 meter distance from streets. The robust segmentation method contained following steps: The ground points are determined first. As a second step cylinders are fitted in vertical slice 1-1.5 meter relative height above ground, which is used to determine the potential location of each single trees trunk and cylinder-like object. Finally, residual values are calculated as deviation of each point from a vertically expanded fitted cylinder; these residual values are used to separate cylinder-like object from individual trees. After successful parameterization, the model parameters and the corresponding residual values of the fitted object are extracted and imported into the tree database. Additionally, geometric features are calculated for each segmented individual tree like crown base, crown width, crown length, diameter of trunk, volume of the individual trees. In case of incompletely scanned trees, the extraction of geometric features is based on fitted circles. The result of the study is a tree database containing detailed information about urban trees, which can be a valuable dataset for ecologist, city planners, planting and mapping purposes. Furthermore, the established database will be the initial point for classification trees into single species. MLS data used in this project had been measured in the framework of KARESZ project for whole Budapest. BSz contributed as an Alexander von Humboldt Research Fellow.

Modelling the effects of cerebral microvasculature morphology on oxygen transport.

PubMed

Park, Chang Sub; Payne, Stephen J

2016-01-01

The cerebral microvasculature plays a vital role in adequately supplying blood to the brain. Determining the health of the cerebral microvasculature is important during pathological conditions, such as stroke and dementia. Recent studies have shown the complex relationship between cerebral metabolic rate and transit time distribution, the transit times of all the possible pathways available dependent on network topology. In this paper, we extend a recently developed technique to solve for residue function, the amount of tracer left in the vasculature at any time, and transit time distribution in an existing model of the cerebral microvasculature to calculate cerebral metabolism. We present the mathematical theory needed to solve for oxygen concentration followed by results of the simulations. It is found that oxygen extraction fraction, the fraction of oxygen removed from the blood in the capillary network by the tissue, and cerebral metabolic rate are dependent on both mean and heterogeneity of the transit time distribution. For changes in cerebral blood flow, a positive correlation can be observed between mean transit time and oxygen extraction fraction, and a negative correlation between mean transit time and metabolic rate of oxygen. A negative correlation can also be observed between transit time heterogeneity and the metabolic rate of oxygen for a constant cerebral blood flow. A sensitivity analysis on the mean and heterogeneity of the transit time distribution was able to quantify their respective contributions to oxygen extraction fraction and metabolic rate of oxygen. Mean transit time has a greater contribution than the heterogeneity for oxygen extraction fraction. This is found to be opposite for metabolic rate of oxygen. These results provide information on the role of the cerebral microvasculature and its effects on flow and metabolism. They thus open up the possibility of obtaining additional valuable clinical information for diagnosing and treating cerebrovascular diseases. Copyright © 2015. Published by Elsevier Ltd.

Green procedure with a green solvent for fats and oils' determination. Microwave-integrated Soxhlet using limonene followed by microwave Clevenger distillation.

PubMed

Virot, Matthieu; Tomao, Valérie; Ginies, Christian; Visinoni, Franco; Chemat, Farid

2008-07-04

Here is described a green and original alternative procedure for fats and oils' determination in oleaginous seeds. Extractions were carried out using a by-product of the citrus industry as extraction solvent, namely d-limonene, instead of hazardous petroleum solvents such as n-hexane. The described method is achieved in two steps using microwave energy: at first, extractions are attained using microwave-integrated Soxhlet, followed by the elimination of the solvent from the medium using a microwave Clevenger distillation in the second step. Oils extracted from olive seeds were compared with both conventional Soxhlet and microwave-integrated Soxhlet extraction procedures performed with n-hexane in terms of qualitative and quantitative determination. No significant difference was obtained between each extract allowing us to conclude that the proposed method is effective and valuable.

A statistical framework for multiparameter analysis at the single-cell level.

PubMed

Torres-García, Wandaliz; Ashili, Shashanka; Kelbauskas, Laimonas; Johnson, Roger H; Zhang, Weiwen; Runger, George C; Meldrum, Deirdre R

2012-03-01

Phenotypic characterization of individual cells provides crucial insights into intercellular heterogeneity and enables access to information that is unavailable from ensemble averaged, bulk cell analyses. Single-cell studies have attracted significant interest in recent years and spurred the development of a variety of commercially available and research-grade technologies. To quantify cell-to-cell variability of cell populations, we have developed an experimental platform for real-time measurements of oxygen consumption (OC) kinetics at the single-cell level. Unique challenges inherent to these single-cell measurements arise, and no existing data analysis methodology is available to address them. Here we present a data processing and analysis method that addresses challenges encountered with this unique type of data in order to extract biologically relevant information. We applied the method to analyze OC profiles obtained with single cells of two different cell lines derived from metaplastic and dysplastic human Barrett's esophageal epithelium. In terms of method development, three main challenges were considered for this heterogeneous dynamic system: (i) high levels of noise, (ii) the lack of a priori knowledge of single-cell dynamics, and (iii) the role of intercellular variability within and across cell types. Several strategies and solutions to address each of these three challenges are presented. The features such as slopes, intercepts, breakpoint or change-point were extracted for every OC profile and compared across individual cells and cell types. The results demonstrated that the extracted features facilitated exposition of subtle differences between individual cells and their responses to cell-cell interactions. With minor modifications, this method can be used to process and analyze data from other acquisition and experimental modalities at the single-cell level, providing a valuable statistical framework for single-cell analysis.

Extraction, integration and analysis of alternative splicing and protein structure distributed information

PubMed Central

D'Antonio, Matteo; Masseroli, Marco

2009-01-01

Background Alternative splicing has been demonstrated to affect most of human genes; different isoforms from the same gene encode for proteins which differ for a limited number of residues, thus yielding similar structures. This suggests possible correlations between alternative splicing and protein structure. In order to support the investigation of such relationships, we have developed the Alternative Splicing and Protein Structure Scrutinizer (PASS), a Web application to automatically extract, integrate and analyze human alternative splicing and protein structure data sparsely available in the Alternative Splicing Database, Ensembl databank and Protein Data Bank. Primary data from these databases have been integrated and analyzed using the Protein Identifier Cross-Reference, BLAST, CLUSTALW and FeatureMap3D software tools. Results A database has been developed to store the considered primary data and the results from their analysis; a system of Perl scripts has been implemented to automatically create and update the database and analyze the integrated data; a Web interface has been implemented to make the analyses easily accessible; a database has been created to manage user accesses to the PASS Web application and store user's data and searches. Conclusion PASS automatically integrates data from the Alternative Splicing Database with protein structure data from the Protein Data Bank. Additionally, it comprehensively analyzes the integrated data with publicly available well-known bioinformatics tools in order to generate structural information of isoform pairs. Further analysis of such valuable information might reveal interesting relationships between alternative splicing and protein structure differences, which may be significantly associated with different functions. PMID:19828075

Measurement of participant experience and satisfaction of exercise programs for low back pain: a structured literature review.

PubMed

Slade, Susan C; Keating, Jennifer L

2010-10-01

The objective of this review was to identify measuring instruments that might be suitable for assessment of satisfaction and experience of exercise programs designed to help people with persistent, recurrent low back pain. The review was designed as a structured literature review adapted from the Cochrane Collaboration Systematic Review and the Quality of Reporting of Meta-analyses and Preferred Reporting Items for Systematic Reviews and Meta-analyses Guidelines. A priori inclusion and exclusion criteria were established and electronic databases were searched without limits until February 2009. Data extraction guidelines were developed to extract the same information from each included article. Thematic analysis, conducted by two independent reviewers, was applied to identify emergent codes and themes from the questionnaires. The relevant questions were then evaluated for applicability to the back pain population. Ten potentially useful instruments were described in the 11 included articles. The following domains of experience were common to the included instruments: care-provider qualities, support staff, governance, access, and facilities. The answers to questions based on these themes may give valuable insights into the experience of exercise programs in general and for low back pain. Important information that would inform researchers and clinicians regarding the components of successful exercise programs may be gained from the development of an instrument that assesses experience of exercise program participation. Research into the experience of people who have participated in exercise programs may be a key to understanding their motivation, engagement, compliance or noncompliance and success or failure. Wiley Periodicals, Inc.

Barrier Island Shorelines Extracted from Landsat Imagery

USGS Publications Warehouse

Guy, Kristy K.

2015-10-13

The shoreline is a common variable used as a metric for coastal erosion or change (Himmelstoss and others, 2010). Although shorelines are often extracted from topographic data (for example, ground-based surveys and light detection and ranging [lidar]), image-based shorelines, corrected for their inherent uncertainties (Moore and others, 2006), have provided much of our understanding of long-term shoreline change because they pre-date routine lidar elevation survey methods. Image-based shorelines continue to be valuable because of their higher temporal resolution compared to costly airborne lidar surveys. A method for extracting sandy shorelines from 30-meter (m) resolution Landsat imagery is presented here.

Phytochemical analysis of Gymnema sylvestre and evaluation of its antimicrobial activity.

PubMed

Chodisetti, Bhuvaneswari; Rao, Kiranmayee; Giri, Archana

2013-01-01

Gymnema sylvestre (CS 149), known to be a rich source of saponins and other valuable phytochemicals, has been analysed for antimicrobial activity. The chloroform extracts of aerial and root parts of G. sylvestre exhibited higher antimicrobial activity as compared to diethyl ether and acetone. The root extracts of chloroform have shown competitive minimum inhibitory concentration and minimum bactericidal concentration values in the range of 0.04-1.28 mg mL(-1) and 0.08-2.56 mg/mL, respectively, towards the pathogens. The GC-MS analysis of chloroform extracts has shown the presence of compounds like eicosane, oleic acid, stigmasterol and vitamin E.

Antimicrobial Activities of Silver Nanoparticles Synthesized by Using Water Extract of Arnicae anthodium.

PubMed

Dobrucka, Renata; Długaszewska, Jolanta

2015-06-01

Green synthesis of nanoparticles has gained significant importance in recent years and has become the one of the most preferred methods. Also, green synthesis of nanoparticles is valuable branch of nanotechnology. Plant extracts are eco-friendly and can be an economic option for synthesis of nanoparticles. This study presents method the synthesis of silver nanoparticles using water extract of Arnicae anthodium. Formation of silver nanoparticles was confirmed by UV-visble spectroscopy, Fourier transform infrared spectroscopy and total reflection X-ray fluorescence analysis. The morphology of the synthesized silver nanoparticles was verified by SEM-EDS. The obtained silver nanoparticles were used to study their antimicrobial activity.

A process to preserve valuable compounds and acquire essential oils from pomelo flavedo using a microwave irradiation treatment.

PubMed

Liu, Zaizhi; Zu, Yuangang; Yang, Lei

2017-06-01

A microwave pretreatment method was developed to preserve pectin, naringin, and limonin contents in pomelo flavedo to allow for longer storage times and subsequent extraction of pomelo essential oil. In terms of the essential oil, microwave pretreatment performed better than hydrodistillation with respect to extraction efficiency (1.88±0.06% in 24min versus 1.91±0.08% in 240min), oxygenation fraction (48.59±1.32% versus 29.63±1.02%), energy consumption (0.15kWh versus 1.54kWh), and environmental impact (123.20g CO 2 versus 1232g CO 2 ). Microwave-pretreated samples retained higher amounts of pectin, naringin, and limonin compared with non-pretreated samples. No obvious change in the degree of pectin esterification was observed. This study shows that the proposed process is a promising methodology for both preserving valuable compounds in pomelo flavedo during storage and acquiring essential oils. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Foundation for Understanding Knowledge Sharing: Organizational Culture, Informal Workplace Learning, Performance Support, and Knowledge Management

ERIC Educational Resources Information Center

Caruso, Shirley J.

2017-01-01

This paper serves as an exploration into some of the ways in which organizations can promote, capture, share, and manage the valuable knowledge of their employees. The problem is that employees typically do not share valuable information, skills, or expertise with other employees or with the entire organization. The author uses research as well as…

Inspection of a Medieval Wood Sculpture Using Computer Tomography

NASA Astrophysics Data System (ADS)

Kapitany, K.; Somogyi, A.; Barsi, A.

2016-06-01

Computer tomography (CT) is an excellent technique for obtaining accurate 3D information about the human body. It allows to visualize the organs, bones and blood vessels, furthermore it enables to diagnose anomalies and diseases. Its spatial reconstruction capability supports other interesting applications, such as inspecting different, even valuable objects like ancient sculptures. Current paper presents a methodology of evaluating CT and video imagery through the example of investigating a wood Madonna with infant Jesus sculpture from the 14th century. The developed techniques extract the outer boundary of the statue, which has been triangulated to derive the surface model. The interior of the sculpture has also been revealed: the iron bolts and rivets as well as the woodworm holes can be mapped. By merging the interior and outer data (geometry and texture) interesting visualizations (perspective views, sections etc.) have been created.

Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

PubMed Central

Song, Min

2016-01-01

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

Application of SIR-B data for groundwater exploration in the Arabian shield and sand-drift monitoring in the AN Nafud and Al Jafurah fringe areas, Kingdom of Saudi Arabia

NASA Technical Reports Server (NTRS)

Berlin, G. L.; Tarabzouni, M. A.; Munshi, Z. M. N.; Chavez, P. S., Jr.

1984-01-01

The primary objectives of the investigation are to determine fully the utility of Shuttle Imaging Radar-B (SIR-B) images for providing valuable surface indicators for ground-water prospecting in the Arabian shield and to identify and assess defining characteristics of sand sheets, sand streaks, and sand dunes in the fringe areas of An Nafud and Al Jafurah. Specific objectives include the determination of the incremental contribution of incidence angle to the total information that can be extracted from SIR-B standard and digitally-enhanced images in the AL Jafurah fringe area; the determination of the incremental contribution of digitally-registered multisensor images; and the development of a groundwater exploration plan for the Ha'il test area in the Arabian Shield.

Research on aviation unsafe incidents classification with improved TF-IDF algorithm

NASA Astrophysics Data System (ADS)

Wang, Yanhua; Zhang, Zhiyuan; Huo, Weigang

2016-05-01

The text content of Aviation Safety Confidential Reports contains a large number of valuable information. Term frequency-inverse document frequency algorithm is commonly used in text analysis, but it does not take into account the sequential relationship of the words in the text and its role in semantic expression. According to the seven category labels of civil aviation unsafe incidents, aiming at solving the problems of TF-IDF algorithm, this paper improved TF-IDF algorithm based on co-occurrence network; established feature words extraction and words sequential relations for classified incidents. Aviation domain lexicon was used to improve the accuracy rate of classification. Feature words network model was designed for multi-documents unsafe incidents classification, and it was used in the experiment. Finally, the classification accuracy of improved algorithm was verified by the experiments.

Natural scene logo recognition by joint boosting feature selection in salient regions

NASA Astrophysics Data System (ADS)

Fan, Wei; Sun, Jun; Naoi, Satoshi; Minagawa, Akihiro; Hotta, Yoshinobu

2011-01-01

Logos are considered valuable intellectual properties and a key component of the goodwill of a business. In this paper, we propose a natural scene logo recognition method which is segmentation-free and capable of processing images extremely rapidly and achieving high recognition rates. The classifiers for each logo are trained jointly, rather than independently. In this way, common features can be shared across multiple classes for better generalization. To deal with large range of aspect ratio of different logos, a set of salient regions of interest (ROI) are extracted to describe each class. We ensure the selected ROIs to be both individually informative and two-by-two weakly dependant by a Class Conditional Entropy Maximization criteria. Experimental results on a large logo database demonstrate the effectiveness and efficiency of our proposed method.

Detection of Practice Pattern Trends through Natural Language Processing of Clinical Narratives and Biomedical Literature

PubMed Central

Chen, Elizabeth S.; Stetson, Peter D.; Lussier, Yves A.; Markatou, Marianthi; Hripcsak, George; Friedman, Carol

2007-01-01

Clinical knowledge, best evidence, and practice patterns evolve over time. The ability to track these changes and study practice trends may be valuable for performance measurement and quality improvement efforts. The goal of this study was to assess the feasibility and validity of methods to generate and compare trends in biomedical literature and clinical narrative. We focused on the challenge of detecting trends in medication usage over time for two diseases: HIV/AIDS and asthma. Information about disease-specific medications in published randomized control trials and discharge summaries at New York-Presbyterian Hospital over a ten-year period were extracted using Natural Language Processing. This paper reports on the ability of our semi-automated process to discover disease-drug practice pattern trends and interpretation of findings across the biomedical and clinical text sources. PMID:18693810

Rating Quantitative and Mapping of Sliding of the Quarry of Ouenza, Algeria

NASA Astrophysics Data System (ADS)

Mohamed, Boudiaf; Rachid, Chaib

The exploitation of iron ore deposit of Ouenza runs into serious difficulties related to landslides. Among the most important events of sliding, we have those of the site "Zerga" including lands located above the ore body "north" of Zerga. The overall area of the landslide is 40,000 m2. Instabilities of land are also manifested in other mine workings, thereby destroying the natural and economic resources. Thus, issues of prevention are needed to secure the career staff and preserve the resources and assets. Our goal is to determine the stability parameters of the quarry to allow the extraction of ore in good working conditions. This allows us to have a topographic map that puts us in the problem and gives us valuable information to guide us in our work to eliminate the slip

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harman-Ware, Anne E.; Sykes, Robert; Peter, Gary F.

Terpenoids, naturally occurring compounds derived from isoprene units present in pine oleoresin, are a valuable source of chemicals used in solvents, fragrances, flavors, and have shown potential use as a biofuel. This paper describes a method to extract and analyze the terpenoids present in loblolly pine saplings and pine lighter wood. Various extraction solvents were tested over different times and temperatures. Samples were analyzed by pyrolysis-molecular beam mass spectrometry before and after extractions to monitor the extraction efficiency. The pyrolysis studies indicated that the optimal extraction method used a 1:1 hexane/acetone solvent system at 22°C for 1 h. Extracts frommore » the hexane/acetone experiments were analyzed using a low thermal mass modular accelerated column heater for fast-GC/FID analysis. The most abundant terpenoids from the pine samples were quantified, using standard curves, and included the monoterpenes, α- and β-pinene, camphene, and δ-carene. Sesquiterpenes analyzed included caryophyllene, humulene, and α-bisabolene. In conclusion, diterpenoid resin acids were quantified in derivatized extractions, including pimaric, isopimaric, levopimaric, palustric, dehydroabietic, abietic, and neoabietic acids.« less

Antioxidant effects of gastrointestinal digested purple carrot extract on the human cells of colonic mucosa.

PubMed

Olejnik, Anna; Rychlik, Joanna; Kidoń, Marcin; Czapski, Janusz; Kowalska, Katarzyna; Juzwa, Wojciech; Olkowicz, Mariola; Dembczyński, Radosław; Moyer, Mary Pat

2016-01-01

Purple carrot (PC) is a potential dietary constituent, which represents a valuable source of antioxidants and can modulate the reactive oxygen species (ROS) level in the gastrointestinal tract. Antioxidant capacity of a PC extract subjected to digestion process simulated in the artificial alimentary tract, including the stomach, small intestine and colon, was analyzed in normal human cells of colon mucosa. Results indicated that the extract obtained upon passage through the gastrointestinal tract, which could come into contact with the colonic cells in situ, was less potent than the extract, which was not subjected to digestion process. Digested PC extract exhibited intracellular ROS-inhibitory capacity, with 1mg/mL showing the ROS clearance of 18.4%. A 20.7% reduction in oxidative DNA damage due to colon mucosa cells' treatment with digested PC extract was observed. These findings indicate that PC extract is capable of colonic cells' protection against the adverse effects of oxidative stress. Copyright © 2015 Elsevier Ltd. All rights reserved.

Precious Metals Recovery from Electroplating Wastewater: A Review

NASA Astrophysics Data System (ADS)

Azmi, A. A.; Jai, J.; Zamanhuri, N. A.; Yahya, A.

2018-05-01

Metal bearing electroplating wastewater posts great health and environmental concerns, but could also provide opportunities for precious and valuable metal recovery, which can make the treatment process more cost-effective and sustainable. Current conventional electroplating wastewater treatment and metal recovery methods include chemical precipitation, coagulation and flocculation, ion exchange, membrane filtration, adsorption, electrochemical treatment and photocatalysis. However, these physico-chemical methods have several disadvantages such as high initial capital cost, high operational cost due to expensive chemical reagents and electricity supply, generation of metal complexes sludge which requires further treatment, ineffective in diluted and/or concentrated wastewater, low precious metal selectivity, and slow recovery process. On the other hand, metal bio-reduction assisted by bioactive phytochemical compounds extracted from plants and plant parts is a new found technology explored by several researchers in recent years aiming to recover precious and valuable metals from secondary sources mainly industrial wastewater by utilizing low-cost and eco-friendly biomaterials as reagents. Extract of plants contains polyphenolic compounds which have great antioxidant properties and reducing capacities, able to reduce metal ions into zerovalent metal atoms and stabilize the metal particles formed. This green bio-recovery method has a value added in their end products since the metals are recovered in nano-sized particles which are more valuable and have high commercial demand in other fields ranging from electrochemistry to medicine.

Automatic age and gender classification using supervised appearance model

NASA Astrophysics Data System (ADS)

Bukar, Ali Maina; Ugail, Hassan; Connah, David

2016-11-01

Age and gender classification are two important problems that recently gained popularity in the research community, due to their wide range of applications. Research has shown that both age and gender information are encoded in the face shape and texture, hence the active appearance model (AAM), a statistical model that captures shape and texture variations, has been one of the most widely used feature extraction techniques for the aforementioned problems. However, AAM suffers from some drawbacks, especially when used for classification. This is primarily because principal component analysis (PCA), which is at the core of the model, works in an unsupervised manner, i.e., PCA dimensionality reduction does not take into account how the predictor variables relate to the response (class labels). Rather, it explores only the underlying structure of the predictor variables, thus, it is no surprise if PCA discards valuable parts of the data that represent discriminatory features. Toward this end, we propose a supervised appearance model (sAM) that improves on AAM by replacing PCA with partial least-squares regression. This feature extraction technique is then used for the problems of age and gender classification. Our experiments show that sAM has better predictive power than the conventional AAM.

Preliminary Estimation of Deoxynivalenol Excretion through a 24 h Pilot Study

PubMed Central

Rodríguez-Carrasco, Yelko; Mañes, Jordi; Berrada, Houda; Font, Guillermina

2015-01-01

A duplicate diet study was designed to explore the occurrence of 15 Fusarium mycotoxins in the 24 h-diet consumed by one volunteer as well as the levels of mycotoxins in his 24 h-collected urine. The employed methodology involved solvent extraction at high ionic strength followed by dispersive solid phase extraction and gas chromatography determination coupled to mass spectrometry in tandem. Satisfactory results in method performance were achieved. The method’s accuracy was in a range of 68%–108%, with intra-day relative standard deviation and inter-day relative standard deviation lower than 12% and 15%, respectively. The limits of quantitation ranged from 0.1 to 8 µg/Kg. The matrix effect was evaluated and matrix-matched calibrations were used for quantitation. Only deoxynivalenol (DON) was quantified in both food and urine samples. A total DON daily intake amounted to 49.2 ± 5.6 µg whereas DON daily excretion of 35.2 ± 4.3 µg was determined. DON daily intake represented 68.3% of the established DON provisional maximum tolerable daily intake (PMTDI). Valuable preliminary information was obtained as regards DON excretion and needs to be confirmed in large-scale monitoring studies. PMID:25723325

Contour matching for a fish recognition and migration-monitoring system

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Schoenberger, Robert B.; Shiozawa, Dennis; Xu, Xiaoqian; Zhan, Pengcheng

2004-12-01

Fish migration is being monitored year round to provide valuable information for the study of behavioral responses of fish to environmental variations. However, currently all monitoring is done by human observers. An automatic fish recognition and migration monitoring system is more efficient and can provide more accurate data. Such a system includes automatic fish image acquisition, contour extraction, fish categorization, and data storage. Shape is a very important characteristic and shape analysis and shape matching are studied for fish recognition. Previous work focused on finding critical landmark points on fish shape using curvature function analysis. Fish recognition based on landmark points has shown satisfying results. However, the main difficulty of this approach is that landmark points sometimes cannot be located very accurately. Whole shape matching is used for fish recognition in this paper. Several shape descriptors, such as Fourier descriptors, polygon approximation and line segments, are tested. A power cepstrum technique has been developed in order to improve the categorization speed using contours represented in tangent space with normalized length. Design and integration including image acquisition, contour extraction and fish categorization are discussed in this paper. Fish categorization results based on shape analysis and shape matching are also included.

Classification of Amazonian rosewood essential oil by Raman spectroscopy and PLS-DA with reliability estimation.

PubMed

Almeida, Mariana R; Fidelis, Carlos H V; Barata, Lauro E S; Poppi, Ronei J

2013-12-15

The Amazon tree Aniba rosaeodora Ducke (rosewood) provides an essential oil valuable for the perfume industry, but after decades of predatory extraction it is at risk of extinction. The extraction of the essential oil from wood implies the cutting of the tree, and then the study of oil extracted from the leaves is important as a sustainable alternative. The goal of this study was to test the applicability of Raman spectroscopy and Partial Least Square Discriminant Analysis (PLS-DA) as means to classify the essential oil extracted from different parties (wood, leaves and branches) of the Brazilian tree A. rosaeodora. For the development of classification models, the Raman spectra were split into two sets: training and test. The value of the limit that separates the classes was calculated based on the distribution of samples of training. This value was calculated in a manner that the classes are divided with a lower probability of incorrect classification for future estimates. The best model presented sensitivity and specificity of 100%, predictive accuracy and efficiency of 100%. These results give an overall vision of the behavior of the model, but do not give information about individual samples; in this case, the confidence interval for each sample of classification was also calculated using the resampling bootstrap technique. The methodology developed have the potential to be an alternative for standard procedures used for oil analysis and it can be employed as screening method, since it is fast, non-destructive and robust. © 2013 Elsevier B.V. All rights reserved.

Leaching characteristics of rare metal elements and chlorine in fly ash from ash melting plants for metal recovery.

PubMed

Jung, Chang-Hwan; Osako, Masahiro

2009-05-01

In terms of resource recovery and environmental impact, melting furnace fly ash (MFA) is attracting much attention in Japan due to its high metal content. The study aims to obtain fundamental information on using a water extraction method not only to concentrate valuable rare metals but also to remove undesirable substances such as chlorine for their recovery from MFA. The composition and leaching characteristics of MFA was investigated. The results revealed that the metal content in MFA is nearly equal to raw ore quality. The content of Ag, In, Pd, Pb, and Zn is, in fact, higher than the content of raw ore. As for leaching behavior, Ag, Bi, In, Ga, Ge, Sb, Sn, and Te showed the lowest release at a neutral pH range. Pd was leached constantly regardless of pH, but its concentration was quite low. On the other hand, most of the Tl was easily leached, revealing that water extraction is not appropriate for Tl recovery from MFA. Major elements Cl, Ca, Na, and K, occupying about 70% of MFA, were mostly leached regardless of pH. Base metal elements Cu, Pb, and Zn showed minimum solubility at a neutral pH. The leaching ratio of target rare metal elements and base metal elements suggests that the optimal pH for water extraction is 8-10, at which the leaching concentration is minimized. The water extraction process removed most of the Cl, Ca, Na, and K, and the concentration of rare metals and base metals increased by four or five times.

Green auctions and reduction of information rents in payments for environmental services: an experimental investigation in Sunan County, northwestern China.

PubMed

Deng, Xiaohong; Xu, Zhongmin

2015-01-01

Reducing information rents is an important task for government agencies wishing to purchase maximal environmental services with limited budgets. This paper reports on several green auction options for reducing information rents and improving the performance of the "Grain for Green" Payments for environmental services (PES) program implemented in northwestern China. In r experimental auctions and investigations, door-to-door interviews were conducted and bidding envelopes and survey questionnaires were used to determine the offers and the foregone profits of the participants. Three scenarios are analyzed in this paper: a uniform price auction, a discriminatory price auction, and an opportunity-cost system. The results show that compared to the uniform price auction system, the other auction systems can increase the cost-effectiveness of conservation contracting. Competitive bidding can reveal true opportunity costs and can reduce information rents extracted from the government by farmers using private information. The demographics and average bids of these auction types were also analyzed. "Perfect information" in the opportunity-cost offer system has the best performance but is very hard to implement in reality. The results of this research show that the auction is a valuable tool for purchasing conservation contracts in northwestern China, but that in the future, the performance of these auctions should be studied with relaxed model assumptions.

A new generation of tools for search, recovery and quality evaluation of World Wide Web medical resources.

PubMed

Aguillo, I

2000-01-01

Although the Internet is already a valuable information resource in medicine, there are important challenges to be faced before physicians and general users will have extensive access to this information. As a result of a research effort to compile a health-related Internet directory, new tools and strategies have been developed to solve key problems derived from the explosive growth of medical information on the Net and the great concern over the quality of such critical information. The current Internet search engines lack some important capabilities. We suggest using second generation tools (client-side based) able to deal with large quantities of data and to increase the usability of the records recovered. We tested the capabilities of these programs to solve health-related information problems, recognising six groups according to the kind of topics addressed: Z39.50 clients, downloaders, multisearchers, tracing agents, indexers and mappers. The evaluation of the quality of health information available on the Internet could require a large amount of human effort. A possible solution may be to use quantitative indicators based on the hypertext visibility of the Web sites. The cybermetric measures are valid for quality evaluation if they are derived from indirect peer review by experts with Web pages citing the site. The hypertext links acting as citations need to be extracted from a controlled sample of quality super-sites.

Fractal Folding and Medium Viscoelasticity Contribute Jointly to Chromosome Dynamics

NASA Astrophysics Data System (ADS)

Polovnikov, K. E.; Gherardi, M.; Cosentino-Lagomarsino, M.; Tamm, M. V.

2018-02-01

Chromosomes are key players of cell physiology, their dynamics provides valuable information about its physical organization. In both prokaryotes and eukaryotes, the short-time motion of chromosomal loci has been described with a Rouse model in a simple or viscoelastic medium. However, little emphasis has been put on the influence of the folded organization of chromosomes on the local dynamics. Clearly, stress propagation, and thus dynamics, must be affected by such organization, but a theory allowing us to extract such information from data, e.g., on two-point correlations, is lacking. Here, we describe a theoretical framework able to answer this general polymer dynamics question. We provide a scaling analysis of the stress-propagation time between two loci at a given arclength distance along the chromosomal coordinate. The results suggest a precise way to assess folding information from the dynamical coupling of chromosome segments. Additionally, we realize this framework in a specific model of a polymer whose long-range interactions are designed to make it fold in a fractal way and immersed in a medium characterized by subdiffusive fractional Langevin motion with a tunable scaling exponent. This allows us to derive explicit analytical expressions for the correlation functions.

An evaluation of the suitability of ERTS data for the purposes of petroleum exploration. [Anadarko Basin in Oklahoma and Texas

NASA Technical Reports Server (NTRS)

Everett, J. R.; Petzel, G.

1974-01-01

This investigation was undertaken to determine the types and amounts of information valuable to petroleum exploration that are extractable from ERTS data and to determine the cost of obtaining the information from ERTS relative to costs using traditional or conventional means. In particular, it was desirable to evaluate this new petroleum exploration tool in a geologically well-known area in order to assess its potential usefulness in an unknown area. In light of the current energy situation, it is felt that such an evaluation is important in order to best utilize technical efforts with customary exploration tools, by rapidly focusing attention on the most promising areas in order to reduce the time required to go through the exploration cycle and to maximize cost savings. The Anadarko Basin lies in western Oklahoma and the panhandle of Texas (Figure 1). It was chosen as a test site because there is a great deal of published information available on the surface and subsurface geology of the area, there are many known structures that act as traps for hydrocarbons, and it is similar to several other large epicontinental sedimentary basins.

Validation of a Microscale Extraction and High Throughput UHPLC-QTOF-MS Analysis Method for Huperzine A in Huperzia

PubMed Central

Cuthbertson, Daniel; Piljac-Žegarac, Jasenka; Lange, Bernd Markus

2011-01-01

Herein we report on an improved method for the microscale extraction of huperzine A (HupA), an acetylcholinesterase-inhibiting alkaloid, from as little as 3 mg of tissue homogenate from the clubmoss Huperzia squarrosa (G. Forst.) Trevis with 99.95 % recovery. We also validated a novel UHPLC-QTOF-MS method for the high-throughput analysis of H. squarrosa extracts in only 6 min, which, in combination with the very low limit of detection (20 pg on column) and the wide linear range for quantification (20 to 10,000 pg on column), allow for a highly efficient screening of extracts containing varying amounts of HupA. Utilization of this methodology has the potential to conserve valuable plant resources. PMID:22275140

A two-step approach for copper and nickel extracting and recovering by emulsion liquid membrane.

PubMed

Bi, Qiang; Xue, Juanqin; Guo, Yingjuan; Li, Guoping; Cui, Haibin

2016-11-01

The recycling of copper and nickel from metallurgical wastewater using emulsion liquid membrane (ELM) was studied. P507 (2-ethylhexyl phosphonic acid-2-ethylhexyl ester) and TBP (tributyl phosphate) were used as carriers for the extraction of copper and nickel by ELMs, respectively. The influence of four emulsion composition variables, namely, the internal phase volume fraction (ϕ), surfactant concentration (Wsurf), internal phase stripping acid concentration (Cio) and the carrier concentration (Cc), and the process variable treat ratio on the extraction efficiencies of copper or nickel were studied. Under the optimum conditions, 98% copper and nickel were recycled by using ELM. The results indicated that ELM extraction is a promising industrial application technology to retrieve valuable metals in low concentration metallurgical wastewater.

Antioxidant potential of hydro-methanolic extract of Prasium majus L: an in vitro study.

PubMed

Chaouche, T M; Haddouchi, F; Ksouri, R; Medini, F; El-Haci, I A; Boucherit, Z; Sekkal, F Z; Atik-Bekara, F

2013-11-01

Phytochemicals are extensively found at different levels in many medicinal plants. To investigate the phenolic compound content and in vitro antioxidant activity of hydro-methanolic extract from Prasium majus L. (Lamiaceae). The present investigation comprises, estimation of total polyphenol, flavonoid, tannin, in vitro antioxidant assays such as total antioxidant capacity, DPPH, ABTS, beta-carotene and ferric reducing power. P. majus exhibited 64.25 mg GAE g(-1) extract of polyphenol phenol content and better scavenging activity of DPPH (IC50 = 7.95 microg mL(-1)), ABTS*+ (IC50 = 373.78 microg mL(-1)) and beta-carotene (IC50 = 122.56 microg mL(-1)). Our results clearly demonstrated that hydro-methanolic extract P. majus has antioxidant capacity. Therefore is a valuable source of natural antioxidants.

Bioactive compounds of sea cucumbers and their therapeutic effects

NASA Astrophysics Data System (ADS)

Shi, Shujuan; Feng, Wenjing; Hu, Song; Liang, Shixiu; An, Nina; Mao, Yongjun

2016-05-01

Sea cucumbers belong to the Class Holothuroidea of marine invertebrates. They are commercially valuable and prized as a food and folk medicine in Asia. Nutritionally, sea cucumbers have an impressive profile of valuable nutrients such as vitamins, minerals and amino acids. A number of unique biological and pharmacological activities/properties, including anticancer, anticoagulant/antithrombotic, antimicrobial, antioxidant, antihyperlipidemic, antihyperglycemic, anti-inflammatory, antihypertension and radioprotective, have been ascribed to various compounds isolated from sea cucumbers. The therapeutic properties and medicinal benefits of sea cucumbers can be linked to the presence of a wide array of bioactives, especially triterpene glycosides, acid mucopolysaccharide, sphingoid bases, glycolipids, fucosylated chondroitin sulfate, polysaccharides, phospholipids, cerebrosides, phosphatidylcholines, and other extracts and hydrolysates. This review highlights the valuable bioactive components as well as the multiple therapeutic properties of sea cucumbers with a view to exploring their potential uses as functional foods and a natural source of new multifunctional drugs.

Simultaneous determination of nine saponins from Panax notoginseng using HPLC and pressurized liquid extraction.

PubMed

Wan, J B; Lai, C M; Li, S P; Lee, M Y; Kong, L Y; Wang, Y T

2006-04-11

A HPLC and pressurized liquid extraction (PLE) method was developed for simultaneous determination of nine saponins, including notoginsenoside R1, ginsenoside Rg1, Re, Rf, Rb1, Rc, Rb2, Rb3 and Rd in Panax notoginseng. The analysis was performed on C18 column with water-acetonitrile gradient elution and the investigated saponins were authenticated by comparing retention time and mass spectra with their reference compounds. Several methods including PLE, ultrasonication, soxhlet extraction and immersion were used for sample preparation and their extraction efficiency was compared. The results showed that PLE has the highest extraction efficiency and repeatability, which would be valuable on standardization of sample preparation for quality control of Chinese medicines. The developed HPLC and PLE is an effective approach for simultaneously quantitative determination of sapoinins in P. notoginseng, which could be used for quality control of P. notoginseng and its preparations.

A novel method of genomic DNA extraction for Cactaceae1

PubMed Central

Fehlberg, Shannon D.; Allen, Jessica M.; Church, Kathleen

2013-01-01

• Premise of the study: Genetic studies of Cactaceae can at times be impeded by difficult sampling logistics and/or high mucilage content in tissues. Simplifying sampling and DNA isolation through the use of cactus spines has not previously been investigated. • Methods and Results: Several protocols for extracting DNA from spines were tested and modified to maximize yield, amplification, and sequencing. Sampling of and extraction from spines resulted in a simplified protocol overall and complete avoidance of mucilage as compared to typical tissue extractions. Sequences from one nuclear and three plastid regions were obtained across eight genera and 20 species of cacti using DNA extracted from spines. • Conclusions: Genomic DNA useful for amplification and sequencing can be obtained from cactus spines. The protocols described here are valuable for any cactus species, but are particularly useful for investigators interested in sampling living collections, extensive field sampling, and/or conservation genetic studies. PMID:25202521

Vaccinium corymbosum L. (blueberry) extracts exhibit protective action against cadmium toxicity in Saccharomyces cerevisiae cells.

PubMed

Oprea, Eliza; Ruta, Lavinia L; Nicolau, Ioana; Popa, Claudia V; Neagoe, Aurora D; Farcasanu, Ileana C

2014-01-01

Blueberries (Vaccinium corymbosum L.) are a rich source of antioxidants and their consumption is believed to contribute to food-related protection against oxidative stress. In the present study, the chemoprotective action of blueberry extracts against cadmium toxicity was investigated using a cadmium-hypersensitive strain of Saccharomyces cerevisiae. Four varieties of blueberries were used in the study, and it was found that the extracts with high content of total anthocyanidins exhibited significant protective effect against the toxicity of cadmium and H2O2. Both the blueberry extracts and pure cyanidin exhibited protective effects against cadmium in a dose-dependent manner, but without significantly interfering with the cadmium accumulation by the yeast cells. The results imply that the blueberry extracts might be a potentially valuable food supplement for individuals exposed to high cadmium. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ethnomedicinal and phytochemical review of Pakistani medicinal plants used as antibacterial agents against Escherichia coli

PubMed Central

2014-01-01

Medicinal plants have always been part of human culture and have the potential to cure different diseases caused by microorganisms. In Pakistan, biologists are mainly focusing on plants’ antimicrobial activities against Escherichia coli due to its increasing resistance to antibiotics. In total, extracts from 34 ethnomedicinally valuable Pakistani plants were reported for in-vitro anti-E. coli activities. Mostly methanolic extracts of medicinal plants were used in different studies, which have shown comparatively higher inhibitory activities against E. coli than n-hexane and aqueous extracts. It has been found that increasing concentration (mg/ml) of methanolic extract can significantly increase (p < 0.01) anti-E. coli activities. Not all medicinal plants are extracted in solvents others than above, which should also be tested against E. coli. Moreover, medicinal plant species must be fully explored phytochemically, which may lead to the development of new drugs. PMID:25135359

The Australian Pharmaceutical Benefits Scheme data collection: a practical guide for researchers.

PubMed

Mellish, Leigh; Karanges, Emily A; Litchfield, Melisa J; Schaffer, Andrea L; Blanch, Bianca; Daniels, Benjamin J; Segrave, Alicia; Pearson, Sallie-Anne

2015-11-02

The Pharmaceutical Benefits Scheme (PBS) is Australia's national drug subsidy program. This paper provides a practical guide to researchers using PBS data to examine prescribed medicine use. Excerpts of the PBS data collection are available in a variety of formats. We describe the core components of four publicly available extracts (the Australian Statistics on Medicines, PBS statistics online, section 85 extract, under co-payment extract). We also detail common analytical challenges and key issues regarding the interpretation of utilisation using the PBS collection and its various extracts. Research using routinely collected data is increasing internationally. PBS data are a valuable resource for Australian pharmacoepidemiological and pharmaceutical policy research. A detailed knowledge of the PBS, the nuances of data capture, and the extracts available for research purposes are necessary to ensure robust methodology, interpretation, and translation of study findings into policy and practice.

Transcriptional profiling of resistant and susceptible buffalograsses in response to Blissus occiduus (Hemiptera: Blissidae) feeding

USDA-ARS?s Scientific Manuscript database

Understanding plant resistance mechanisms at a molecular level would provide valuable insights into the biological pathways impacted by insect feeding, and help explain specific plant tolerance mechanisms. As a first step in this process, we conducted next generation sequencing using RNA extracted f...

Extracting Valuable Data from Classroom Trading Pits

ERIC Educational Resources Information Center

Bergstrom, Theodore C.; Kwok, Eugene

2005-01-01

How well does competitive theory explain the outcome in experimental markets? The authors examined the results of a large number of classroom trading experiments that used a pit-trading design found in Experiments with Economic Principles, an introductory economics textbook by Bergstrom and Miller. They compared experimental outcomes with…

Current update in methodologies for extraction and analysis of isoflvones and proteins

USDA-ARS?s Scientific Manuscript database

Soy foods are traditional culinary staples for a significant proportion of the Asian population. In the past several decades, soy and its food products have become popular globally because of their valuable health benefits. There are many recent reports on bioactive components, largely isoflavones t...

An Automated Approach to Extracting River Bank Locations from Aerial Imagery Using Image Texture

DTIC Science & Technology

2013-01-01

Atchafalaya River, LA. Map Data: Google, United States Department of Agriculture Farm Ser- vice Agency, Europa Technologies AUTOMATED RIVER BANK...traverse morphologically smooth landscapes including rivers in sand or ice . Within these limitations, we hold that this technique rep- resents a valuable

Membrane-filtered olive mill wastewater: Quality assessment of the dried phenolic-rich fraction

USDA-ARS?s Scientific Manuscript database

A current trend in olive mill wastewater (OMWW) management is to not only decrease environmental pollution but also extract and utilize valuable by-products. Therefore, the objectives of this study were to explore different techniques for drying a phenolic-rich membrane filtration fraction of OMWW a...

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

PubMed

Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

2014-07-01

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. © 2013 Wiley Periodicals, Inc.

Tyre-road grip coefficient assessment - Part II: online estimation using instrumented vehicle, extended Kalman filter, and neural network

NASA Astrophysics Data System (ADS)

Luque, Pablo; Mántaras, Daniel A.; Fidalgo, Eloy; Álvarez, Javier; Riva, Paolo; Girón, Pablo; Compadre, Diego; Ferran, Jordi

2013-12-01

The main objective of this work is to determine the limit of safe driving conditions by identifying the maximal friction coefficient in a real vehicle. The study will focus on finding a method to determine this limit before reaching the skid, which is valuable information in the context of traffic safety. Since it is not possible to measure the friction coefficient directly, it will be estimated using the appropriate tools in order to get the most accurate information. A real vehicle is instrumented to collect information of general kinematics and steering tie-rod forces. A real-time algorithm is developed to estimate forces and aligning torque in the tyres using an extended Kalman filter and neural networks techniques. The methodology is based on determining the aligning torque; this variable allows evaluation of the behaviour of the tyre. It transmits interesting information from the tyre-road contact and can be used to predict the maximal tyre grip and safety margin. The maximal grip coefficient is estimated according to a knowledge base, extracted from computer simulation of a high detailed three-dimensional model, using Adams® software. The proposed methodology is validated and applied to real driving conditions, in which maximal grip and safety margin are properly estimated.

Towards an Age-Phenome Knowledge-base

PubMed Central

2011-01-01

Background Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages. Results Here we present the Age-Phenome Knowledge-base (APK), in which knowledge about age-related phenotypic patterns and events can be modeled and stored for retrieval. The APK contains evidence connecting specific ages or age groups with phenotypes, such as disease and clinical traits. Using a simple text mining tool developed for this purpose, we extracted instances of age-phenotype associations from journal abstracts related to non-insulin-dependent Diabetes Mellitus. In addition, links between age and phenotype were extracted from clinical data obtained from the NHANES III survey. The knowledge stored in the APK is made available for the relevant research community in the form of 'Age-Cards', each card holds the collection of all the information stored in the APK about a particular age. These Age-Cards are presented in a wiki, allowing community review, amendment and contribution of additional information. In addition to the wiki interaction, complex searches can also be conducted which require the user to have some knowledge of database query construction. Conclusions The combination of a knowledge model based repository with community participation in the evolution and refinement of the knowledge-base makes the APK a useful and valuable environment for collecting and curating existing knowledge of the connections between age and phenotypes. PMID:21651792

Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer’s disease

PubMed Central

Gray, Katherine R.; Wolz, Robin; Heckemann, Rolf A.; Aljabar, Paul; Hammers, Alexander; Rueckert, Daniel

2012-01-01

Imaging biomarkers for Alzheimer’s disease are desirable for improved diagnosis and monitoring, as well as drug discovery. Automated image-based classification of individual patients could provide valuable diagnostic support for clinicians, when considered alongside cognitive assessment scores. We investigate the value of combining cross-sectional and longitudinal multi-region FDG-PET information for classification, using clinical and imaging data from the Alzheimer’s Disease Neuroimaging Initiative. Whole-brain segmentations into 83 anatomically defined regions were automatically generated for baseline and 12-month FDG-PET images. Regional signal intensities were extracted at each timepoint, as well as changes in signal intensity over the follow-up period. Features were provided to a support vector machine classifier. By combining 12-month signal intensities and changes over 12 months, we achieve significantly increased classification performance compared with using any of the three feature sets independently. Based on this combined feature set, we report classification accuracies of 88% between patients with Alzheimer’s disease and elderly healthy controls, and 65% between patients with stable mild cognitive impairment and those who subsequently progressed to Alzheimer’s disease. We demonstrate that information extracted from serial FDG-PET through regional analysis can be used to achieve state-of-the-art classification of diagnostic groups in a realistic multi-centre setting. This finding may be usefully applied in the diagnosis of Alzheimer’s disease, predicting disease course in individuals with mild cognitive impairment, and in the selection of participants for clinical trials. PMID:22236449

Determination of terpenoid content in pine by organic solvent extraction and fast-GC analysis

DOE PAGES

Harman-Ware, Anne E.; Sykes, Robert; Peter, Gary F.; ...

2016-01-25

Terpenoids, naturally occurring compounds derived from isoprene units present in pine oleoresin, are a valuable source of chemicals used in solvents, fragrances, flavors, and have shown potential use as a biofuel. This paper describes a method to extract and analyze the terpenoids present in loblolly pine saplings and pine lighter wood. Various extraction solvents were tested over different times and temperatures. Samples were analyzed by pyrolysis-molecular beam mass spectrometry before and after extractions to monitor the extraction efficiency. The pyrolysis studies indicated that the optimal extraction method used a 1:1 hexane/acetone solvent system at 22°C for 1 h. Extracts frommore » the hexane/acetone experiments were analyzed using a low thermal mass modular accelerated column heater for fast-GC/FID analysis. The most abundant terpenoids from the pine samples were quantified, using standard curves, and included the monoterpenes, α- and β-pinene, camphene, and δ-carene. Sesquiterpenes analyzed included caryophyllene, humulene, and α-bisabolene. In conclusion, diterpenoid resin acids were quantified in derivatized extractions, including pimaric, isopimaric, levopimaric, palustric, dehydroabietic, abietic, and neoabietic acids.« less

Microwave-assisted extraction of lipid from fish waste

NASA Astrophysics Data System (ADS)

Rahimi, M. A.; Omar, R.; Ethaib, S.; Siti Mazlina, M. K.; Awang Biak, D. R.; Nor Aisyah, R.

2017-06-01

Processing fish waste for extraction of value added products such as protein, lipid, gelatin, amino acids, collagen and oil has become one of the most intriguing researches due to its valuable properties. In this study the extraction of lipid from sardine fish waste was carried out using microwave-assisted extraction (MAE) and compared with Soxhlets and Hara and Radin methods. A mixture of two organic solvents isopropanol/hexane and distilled water were used for MAE and Hara and Radin methods. Meanwhile, Soxhlet method utilized only hexane as solvent. The results show that the higher yield of lipid 80.5 mg/g was achieved using distilled water in MAE method at 10 min extraction time. Soxhlet extraction method only produced 46.6 mg/g of lipid after 4 hours of extraction time. Lowest yield of lipid was found at 15.8 mg/g using Hara and Radin method. Based on aforementioned results, it can be concluded MAE method is superior compared to the Soxhlet and Hara and Radin methods which make it an attractive route to extract lipid from fish waste.

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Dermatological Feasibility of Multimodal Facial Color Imaging Modality for Cross-Evaluation of Facial Actinic Keratosis

PubMed Central

Bae, Youngwoo; Son, Taeyoon; Nelson, J. Stuart; Kim, Jae-Hong; Choi, Eung Ho; Jung, Byungjo

2010-01-01

Background/Purpose Digital color image analysis is currently considered as a routine procedure in dermatology. In our previous study, a multimodal facial color imaging modality (MFCIM), which provides a conventional, parallel- and cross-polarization, and fluorescent color image, was introduced for objective evaluation of various facial skin lesions. This study introduces a commercial version of MFCIM, DermaVision-PRO, for routine clinical use in dermatology and demonstrates its dermatological feasibility for cross-evaluation of skin lesions. Methods/Results Sample images of subjects with actinic keratosis or non-melanoma skin cancers were obtained at four different imaging modes. Various image analysis methods were applied to cross-evaluate the skin lesion and, finally, extract valuable diagnostic information. DermaVision-PRO is potentially a useful tool as an objective macroscopic imaging modality for quick prescreening and cross-evaluation of facial skin lesions. Conclusion DermaVision-PRO may be utilized as a useful tool for cross-evaluation of widely distributed facial skin lesions and an efficient database management of patient information. PMID:20923462

DOE Office of Scientific and Technical Information (OSTI.GOV)

Denton, J. S.; Goldstein, S. J.; Paviet, P.

Studies of uranium-series (U-series) disequilibria within and around ore deposits provide valuable information on the extent and timing of actinide mobility, via mineral-fluid interaction, over a range of spatial and temporal scales. Such information is useful in studies of analogs of high-level nuclear-waste repositories, as well as for mining and mineral extraction sites, locations of previous nuclear weapons testing, and legacy nuclear waste contamination. In this study we present isotope dilution mass spectrometry U-series measurements for fracture-fill materials (hematite, goethite, kaolinite, calcite, dolomite and quartz) from one such analog; the Nopal I uranium ore deposit situated at Peña Blanca inmore » the Chihuahua region of northern Mexico. The ore deposit is located in fractured, unsaturated volcanic tuff and fracture-fill materials from surface fractures as well as fractures in a vertical drill core have been analyzed. High uranium concentrations in the fracture-fill materials (between 12 and 7700 ppm) indicate uranium mobility and transport from the deposit. Furthermore, uranium concentrations generally decrease with horizontal distance away from the deposit but in this deposit there is no trend with depth below the surface.« less

The potential of satellite data to study individual wildfire events

NASA Astrophysics Data System (ADS)

Benali, Akli; López-Saldana, Gerardo; Russo, Ana; Sá, Ana C. L.; Pinto, Renata M. S.; Nikos, Koutsias; Owen, Price; Pereira, Jose M. C.

2014-05-01

Large wildfires have important social, economic and environmental impacts. In order to minimize their impacts, understand their main drivers and study their dynamics, different approaches have been used. The reconstruction of individual wildfire events is usually done by collection of field data, interviews and by implementing fire spread simulations. All these methods have clear limitations in terms of spatial and temporal coverage, accuracy, subjectivity of the collected information and lack of objective independent validation information. In this sense, remote sensing is a promising tool with the potential to provide relevant information for stakeholders and the research community, by complementing or filling gaps in existing information and providing independent accurate quantitative information. In this work we show the potential of satellite data to provide relevant information regarding the dynamics of individual large wildfire events, filling an important gap in wildfire research. We show how MODIS active-fire data, acquired up to four times per day, and satellite-derived burnt perimeters can be combined to extract relevant information wildfire events by describing the methods involved and presenting results for four regions of the world: Portugal, Greece, SE Australia and California. The information that can be retrieved encompasses the start and end date of a wildfire event and its ignition area. We perform an evaluation of the information retrieved by comparing the satellite-derived parameters with national databases, highlighting the strengths and weaknesses of both and showing how the former can complement the latter leading to more complete and accurate datasets. We also show how the spatio-temporal distribution of wildfire spread dynamics can be reconstructed using satellite-derived active-fires and how relevant descriptors can be extracted. Applying graph theory to satellite active-fire data, we define the major fire spread paths that yield information about the major spatial corridors through which fires spread, and their relative importance in the full fire event. These major fire paths are then used to extract relevant descriptors, such as the distribution of fire spread direction, rate of spread and fire intensity (i.e. energy emitted). The reconstruction of the fire spread is shown for some case studies for Portugal and is also compared with fire progressions obtained by air-borne sensors for SE Australia. The approach shows solid results, providing a valuable tool for the reconstruction of individual fire events, understand their complex spread patterns and their main drivers of fire propagation. The major fire pathsand the spatio-temporal distribution of active fires are being currently combined with fire spread simulations within the scope oftheFIRE-MODSATproject, to provideuseful information to support and improve fire suppression strategies.

Towards a high yield recovery of polyphenols from olive mill wastewater on activated carbon coated with milk proteins: Experimental design and antioxidant activity.

PubMed

Yangui, Asma; Abderrabba, Manef

2018-10-01

Activated carbon coated with milk proteins was used for the removal and recovery of phenolic compounds from actual olive mill wastewater (OMW). The extraction of polyphenols using the new adsorbent based on natural coating agent has significant potential compared with traditional extraction methods, as it significantly increases the extraction yield (80%) and overall efficiencies of the process for total phenols (75.4%) and hydroxytyrosol (90.6%) which is the most valuable compound. Complete discussions on the adsorption isotherms, kinetic and thermodynamic were performed and the optimum adsorption variables were investigated using the response surface methodology and the central composite experimental design. The extracted polyphenols exhibited a high antioxidant activity and a fast scavenging effect on DPPH free radical. The strategy devised in this work for polyphenol extraction using modified activated carbon with biological coating agent is of simple design, very effective and ensure the recovery of highly antioxidant extract. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ultrasonic-Assisted Extraction of Raspberry Seed Oil and Evaluation of Its Physicochemical Properties, Fatty Acid Compositions and Antioxidant Activities

PubMed Central

Huang, Qun; Wang, Jinli; Lin, Qiyang; Liu, Mingxin; Lee, Won Young; Song, Hongbo

2016-01-01

Ultrasonic-assisted extraction was employed for highly efficient separation of aroma oil from raspberry seeds. A central composite design with two variables and five levels was employed and effects of process variables of sonication time and extraction temperature on oil recovery and quality were investigated. Optimal conditions predicted by response surface methodology were sonication time of 37 min and extraction temperature of 54°C. Specifically, ultrasonic-assisted extraction (UAE) was able to provide a higher content of beneficial unsaturated fatty acids, whereas conventional Soxhlet extraction (SE) resulted in a higher amount of saturated fatty acids. Moreover, raspberry seed oil contained abundant amounts of edible linoleic acid and linolenic acid, which suggest raspberry seeds could be valuable edible sources of natural γ-linolenic acid products. In comparison with SE, UAE exerted higher free radical scavenging capacities. In addition, UAE significantly blocked H2O2-induced intracellular reactive oxygen species (ROS) generation. PMID:27120053

Separation of Active Compounds from Food by-Product (Cocoa Shell) Using Subcritical Water Extraction.

PubMed

Jokić, Stela; Gagić, Tanja; Knez, Željko; Šubarić, Drago; Škerget, Mojca

2018-06-11

Large amounts of residues are produced in the food industries. The waste shells from cocoa processing are usually burnt for fuel or used as a mulch in gardens to add nutrients to soil and to suppress weeds. The objectives of this work were: (a) to separate valuable compounds from cocoa shell by applying sustainable green separation process—subcritical water extraction (SWE); (b) identification and quantification of active compounds, sugars and sugar degradation products in obtained extracts using HPLC; (c) characterization of the antioxidant activity of extracts; (d) optimization of separation process using response surface methodology (RSM). Depending on applied extraction conditions, different concentration of theobromine, caffeine, theophylline, epicatechin, catechin, chlorogenic acid and gallic acid were determined in the extracts obtained by subcritical water. Furthermore, mannose, glucose, xylose, arabinose, rhamnose and fucose were detected as well as their important degradation products such as 5-hydroxymethylfurfural (5-HMF), furfural, levulinic acid, lactic acid and formic acid.

Tenebrio molitor Extracts Modulate the Response to Environmental Stressors and Extend Lifespan in Caenorhabditis elegans.

PubMed

Won, Seong-Min; Cha, Hye-Uk; Yi, Sun Shin; Kim, Sung-Jo; Park, Sang-Kyu

2016-09-08

Tenebrio molitor are large insects and their larvae are consumed as food in many countries. The nutritional composition of T. molitor has been studied and contains high amounts of proteins, unsaturated fatty acids, and valuable minerals. However, the bioactivity of T. molitor has not been fully understood. We examined the effects of T. molitor extracts on resistance to oxidative stress and organism's lifespan using Caenorhabditis elegans as a model system. The response to heat shock and ultraviolet (UV) irradiation was monitored in vivo. The extracts from T. molitor showed significant effects on resistance to oxidative stress and UV irradiation and extend both mean and maximum lifespan of C. elegans. The number of progeny produced significantly increased in animals supplemented with T. molitor extracts. In addition, the expression of hsp-16.2 and sod-3 was markedly upregulated by supplementation with T. molitor extracts. These findings suggest that T. molitor extracts can increase response to stressors and extend lifespan by the induction of longevity assurance genes in C. elegans.

Highly efficient extraction of anthocyanins from grape skin using deep eutectic solvents as green and tunable media.

PubMed

Jeong, Kyung Min; Zhao, Jing; Jin, Yan; Heo, Seong Rok; Han, Se Young; Yoo, Da Eun; Lee, Jeongmi

2015-12-01

Deep eutectic solvents (DESs) were investigated as tunable, environmentally benign, yet superior extraction media to enhance the extraction of anthocyanins from grape skin, which is usually discarded as waste. Ten DESs containing choline chloride as hydrogen bond acceptor combined with different hydrogen bond donors were screened for high extraction efficiencies based on the anthocyanin extraction yields. As a result, citric acid, D-(+)-maltose, and fructose were selected as the effective DES components, and the newly designed DES, CM-6 that is composed of citric acid and D-(+)-maltose at 4:1 molar ratio, exhibited significantly higher levels of anthocyanin extraction yields than conventional extraction solvents such as 80% aqueous methanol. The final extraction method was established based on the ultrasound-assisted extraction under conditions optimized using response surface methodology. Its extraction yields were double or even higher than those of conventional methods that are time-consuming and use volatile organic solvents. Our method is truly a green method for anthocyanin extraction with great extraction efficiency using a minimal amount of time and solvent. Moreover, this study suggested that grape skin, the by-products of grape juice processing, could serve as a valuable source for safe, natural colorants or antioxidants by use of the eco-friendly extraction solvent, CM-6.

High performance curcumin subcritical water extraction from turmeric (Curcuma longa L.).

PubMed

Valizadeh Kiamahalleh, Mohammad; Najafpour-Darzi, Ghasem; Rahimnejad, Mostafa; Moghadamnia, Ali Akbar; Valizadeh Kiamahalleh, Meisam

2016-06-01

Curcumin is a hydrophobic polyphenolic compound derived from turmeric rhizome, which consists about 2-5% of the total rhizome content and is a more valuable component of turmeric. For reducing the drawbacks of conventional extraction (using organic solvents) of curcumin, the water as a clean solvent was used for extracting curcumin. Subcritical water extraction (SWE) experimental setup was fabricated in a laboratory scale and the influences of some parameters (e.g. extraction temperature, particle size, retention time and pressure) on the yield of extraction were investigated. Optimum extraction conditions such as SWE pressure of 10bar, extractive temperature of 140°C, particle size of 0.71mm and retention time of 14min were defined. The maximum amount of curcumin extracted at the optimum condition was 3.8wt%. The yield of curcumin extraction was more than 76wt% with regards to the maximum possible curcumin content of turmeric, as known to be 5%. The scanning electron microscope (SEM) images from the outer surface of turmeric, before and after extraction, clearly demonstrated the effect of each parameter; changes in porosity and hardness of turmeric that is directly related to the amount of extracted curcumin in process optimization of the extraction parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification.

PubMed

Chen, Xiaobo; Zhang, Han; Zhang, Lichi; Shen, Celina; Lee, Seong-Whan; Shen, Dinggang

2017-10-01

Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for diagnosing various neurodegenerative diseases, including Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Current studies mainly construct the FC networks between grey matter (GM) regions of the brain based on temporal co-variations of the blood oxygenation level-dependent (BOLD) signals, which reflects the synchronized neural activities. However, it was rarely investigated whether the FC detected within the white matter (WM) could provide useful information for diagnosis. Motivated by the recently proposed functional correlation tensors (FCT) computed from RS-fMRI and used to characterize the structured pattern of local FC in the WM, we propose in this article a novel MCI classification method based on the information conveyed by both the FC between the GM regions and that within the WM regions. Specifically, in the WM, the tensor-based metrics (e.g., fractional anisotropy [FA], similar to the metric calculated based on diffusion tensor imaging [DTI]) are first calculated based on the FCT and then summarized along each of the major WM fiber tracts connecting each pair of the brain GM regions. This could capture the functional information in the WM, in a similar network structure as the FC network constructed for the GM, based only on the same RS-fMRI data. Moreover, a sliding window approach is further used to partition the voxel-wise BOLD signal into multiple short overlapping segments. Then, both the FC and FCT between each pair of the brain regions can be calculated based on the BOLD signal segments in the GM and WM, respectively. In such a way, our method can generate dynamic FC and dynamic FCT to better capture functional information in both GM and WM and further integrate them together by using our developed feature extraction, selection, and ensemble learning algorithms. The experimental results verify that the dynamic FCT can provide valuable functional information in the WM; by combining it with the dynamic FC in the GM, the diagnosis accuracy for MCI subjects can be significantly improved even using RS-fMRI data alone. Hum Brain Mapp 38:5019-5034, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

ICDTag: A Prototype for a Web-Based System for Organizing Physician-Written Blog Posts Using a Hybrid Taxonomy-Folksonomy Approach

PubMed Central

2013-01-01

Background Medical blogs have emerged as new media, extending to a wider range of medical audiences, including health professionals and patients to share health-related information. However, extraction of quality health-related information from medical blogs is challenging primarily because these blogs lack systematic methods to organize their posts. Medical blogs can be categorized according to their author into (1) physician-written blogs, (2) nurse-written blogs, and (3) patient-written blogs. This study focuses on how to organize physician-written blog posts that discuss disease-related issues and how to extract quality information from these posts. Objective The goal of this study was to create and implement a prototype for a Web-based system, called ICDTag, based on a hybrid taxonomy–folksonomy approach that follows a combination of a taxonomy classification schemes and user-generated tags to organize physician-written blog posts and extract information from these posts. Methods First, the design specifications for the Web-based system were identified. This system included two modules: (1) a blogging module that was implemented as one or more blogs, and (2) an aggregator module that aggregated posts from different blogs into an aggregator website. We then developed a prototype for this system in which the blogging module included two blogs, the cardiology blog and the gastroenterology blog. To analyze the usage patterns of the prototype, we conducted an experiment with data provided by cardiologists and gastroenterologists. Next, we conducted two evaluation types: (1) an evaluation of the ICDTag blog, in which the browsing functionalities of the blogging module were evaluated from the end-user’s perspective using an online questionnaire, and (2) an evaluation of information quality, in which the quality of the content on the aggregator website was assessed from the perspective of medical experts using an emailed questionnaire. Results Participants of this experiment included 23 cardiologists and 24 gastroenterologists. Positive evaluations on the main functions and the organization of information on the ICDTag blogs were given by 18 of the participants via an online questionnaire. These results supported our hypothesis that the use of a taxonomy-folksonomy structure has significant potential to improve the organization of information in physician-written blogs. The quality of the content on the aggregator website was assessed by 3 cardiology experts and 3 gastroenterology experts via an email questionnaire. The results of this questionnaire demonstrated that the experts considered the aggregated tags and categories semantically related to the posts’ content. Conclusions This study demonstrated that applying the hybrid taxonomy–folksonomy approach to physician-written blogs that discuss disease-related issues has valuable potential to make these blogs a more organized and systematic medium and supports the extraction of quality information from their posts. Thus, it is worthwhile to develop more mature systems that make use of the hybrid approach to organize posts in physician-written blogs. PMID:23470419

ICDTag: a prototype for a web-based system for organizing physician-written blog posts using a hybrid taxonomy-folksonomy approach.

PubMed

Batch, Yamen; Yusof, Maryati Mohd; Noah, Shahrul Azman

2013-02-27

Medical blogs have emerged as new media, extending to a wider range of medical audiences, including health professionals and patients to share health-related information. However, extraction of quality health-related information from medical blogs is challenging primarily because these blogs lack systematic methods to organize their posts. Medical blogs can be categorized according to their author into (1) physician-written blogs, (2) nurse-written blogs, and (3) patient-written blogs. This study focuses on how to organize physician-written blog posts that discuss disease-related issues and how to extract quality information from these posts. The goal of this study was to create and implement a prototype for a Web-based system, called ICDTag, based on a hybrid taxonomy-folksonomy approach that follows a combination of a taxonomy classification schemes and user-generated tags to organize physician-written blog posts and extract information from these posts. First, the design specifications for the Web-based system were identified. This system included two modules: (1) a blogging module that was implemented as one or more blogs, and (2) an aggregator module that aggregated posts from different blogs into an aggregator website. We then developed a prototype for this system in which the blogging module included two blogs, the cardiology blog and the gastroenterology blog. To analyze the usage patterns of the prototype, we conducted an experiment with data provided by cardiologists and gastroenterologists. Next, we conducted two evaluation types: (1) an evaluation of the ICDTag blog, in which the browsing functionalities of the blogging module were evaluated from the end-user's perspective using an online questionnaire, and (2) an evaluation of information quality, in which the quality of the content on the aggregator website was assessed from the perspective of medical experts using an emailed questionnaire. Participants of this experiment included 23 cardiologists and 24 gastroenterologists. Positive evaluations on the main functions and the organization of information on the ICDTag blogs were given by 18 of the participants via an online questionnaire. These results supported our hypothesis that the use of a taxonomy-folksonomy structure has significant potential to improve the organization of information in physician-written blogs. The quality of the content on the aggregator website was assessed by 3 cardiology experts and 3 gastroenterology experts via an email questionnaire. The results of this questionnaire demonstrated that the experts considered the aggregated tags and categories semantically related to the posts' content. This study demonstrated that applying the hybrid taxonomy-folksonomy approach to physician-written blogs that discuss disease-related issues has valuable potential to make these blogs a more organized and systematic medium and supports the extraction of quality information from their posts. Thus, it is worthwhile to develop more mature systems that make use of the hybrid approach to organize posts in physician-written blogs.

Bioactive Natural Products Prioritization Using Massive Multi-informational Molecular Networks.

PubMed

Olivon, Florent; Allard, Pierre-Marie; Koval, Alexey; Righi, Davide; Genta-Jouve, Gregory; Neyts, Johan; Apel, Cécile; Pannecouque, Christophe; Nothias, Louis-Félix; Cachet, Xavier; Marcourt, Laurence; Roussi, Fanny; Katanaev, Vladimir L; Touboul, David; Wolfender, Jean-Luc; Litaudon, Marc

2017-10-20

Natural products represent an inexhaustible source of novel therapeutic agents. Their complex and constrained three-dimensional structures endow these molecules with exceptional biological properties, thereby giving them a major role in drug discovery programs. However, the search for new bioactive metabolites is hampered by the chemical complexity of the biological matrices in which they are found. The purification of single constituents from such matrices requires such a significant amount of work that it should be ideally performed only on molecules of high potential value (i.e., chemical novelty and biological activity). Recent bioinformatics approaches based on mass spectrometry metabolite profiling methods are beginning to address the complex task of compound identification within complex mixtures. However, in parallel to these developments, methods providing information on the bioactivity potential of natural products prior to their isolation are still lacking and are of key interest to target the isolation of valuable natural products only. In the present investigation, we propose an integrated analysis strategy for bioactive natural products prioritization. Our approach uses massive molecular networks embedding various informational layers (bioactivity and taxonomical data) to highlight potentially bioactive scaffolds within the chemical diversity of crude extracts collections. We exemplify this workflow by targeting the isolation of predicted active and nonactive metabolites from two botanical sources (Bocquillonia nervosa and Neoguillauminia cleopatra) against two biological targets (Wnt signaling pathway and chikungunya virus replication). Eventually, the detection and isolation processes of a daphnane diterpene orthoester and four 12-deoxyphorbols inhibiting the Wnt signaling pathway and exhibiting potent antiviral activities against the CHIKV virus are detailed. Combined with efficient metabolite annotation tools, this bioactive natural products prioritization pipeline proves to be efficient. Implementation of this approach in drug discovery programs based on natural extract screening should speed up and rationalize the isolation of bioactive natural products.

Spent yeast as natural source of functional food additives

PubMed

Rakowska, Rita; Sadowska, Anna; Dybkowska, Ewa; Świderski, Franciszek

Spent yeasts are by-products arising from beer and wine production which over many years have been chiefly used as feed additives for livestock. They contain many valuable and bioactive substances which has thereby generated much interest in their exploitation. Up till now, the main products obtained from beer-brewing yeasts are β-glucans and yeast extracts. Other like foodstuffs include dried brewer’s yeast, where this is dried and the bitterness removed to be fit for human consumption as well as mannan-oligosaccharides hitherto used in the feed industry. β-glucans constitute the building blocks of yeast cell walls and can thus be used in human nutrition as dietary supplements or serving as food additives in functional foods. β-glucans products obtained via post-fermentation of beer also exhibit a high and multi-faceted biological activity where they improve the blood’s lipid profile, enhance immunological status and have both prebiotic and anti-oxidant properties. Yeast extracts are currently being used more and more to enhance flavour in foodstuffs, particularly for meat and its products. Depending on how autolysis is carried out, it is possible to design extracts of various meat flavours characteristic of specific meats. Many different flavour profiles can be created which may be additionally increased in combination with vegetable extracts. Within the food market, yeast extracts can appear in various guises such as liquids, pastes or powders. They all contain significant amounts of glutamic acid, 5’-GMP and 5’-IMP nucleotides together with various amino acids and peptides that act synergistically for enhancing the flavour of foodstuff products. Recent studies have demonstrated additional benefits of yeast extracts as valuable sources of amino acids and peptides which can be used in functional foods and dietary supplements. These products possess GRAS status (Generally Recognised As Safe) which thereby also adds further as to why they should be used as natural food additives that are functional.

Phytochemical Composition and Antioxidant Activities of Dianthus Thunbergii Hooper and Hypoxis Argentea Harv Ex Baker: Plants Used for the Management of Diabetes Mellitus in Eastern Cape, South Africa.

PubMed

Akinrinde, Akinleye Stephen; Afolayan, Anthony Jide; Bradley, Graeme

2018-01-01

Inhabitants of the Eastern Cape Province of South Africa use the roots of Dianthus thunbergii and corms of Hypoxis argentea to treat diabetes mellitus and other ailments. The objective of this study was to analyze the phytochemical composition and antioxidant activities of the aqueous and ethanol extracts of the roots and corms of two plants. Total phenolics, flavonoids, flavonols, proanthocyanidins, tannins, and alkaloids were determined by standard methods. The scavenging activities of the extracts against 1,1 diphenyl-2-picrylhydrazyl (DPPH), 2'-azino-bis (3-ethylbenthiazoline-6-sulfonic acid (ABTS), nitric oxide (NO), hydrogen peroxide (H 2 O 2 ), and their ferric-reducing antioxidant potentials (FRAPs) were measured. The ethanol extract of H. argentea had the highest content of phenolics (66.71 ± 2.71 mg gallic acid equivalent/g) and tannins (1.18 ± 0.07 mg TAE/g), while the ethanol extract of D. thunbergii gave higher contents of flavonoids and proanthocyanidins (62.21 ± 1.75 mg Qe/g and 432.62 ± 2.43 mg Ca/g, respectively). Flavonols were the most predominant in the aqueous extract of H. argentea (25.51 ± 1.92 mg Qe/g). We observed a concentration-dependent response in the ABTS- and H 2 O 2 -scavenging activities and FRAP values of the extracts and standards (Vitamin C, butylated hydroxytoluene, and rutin). The ethanol extracts of both plants generally demonstrated better antioxidant activities against H 2 O 2 , NO, and ABTS while also possessing better reducing power than the aqueous extracts. The aqueous extract of D. thunbergii , however, showed the best DPPH scavenging activity. The higher content of phytochemicals and antioxidant capacity obtained for the ethanol extracts of D. thunbergii and H. argentea may prove to be valuable information in selecting suitable extraction solvents for the medicinal applications of both plants. Ethanol extracts of Hypoxis argentea had the highest levels of phenolics and tanninsEthanol extracts of Dianthus thunbergii had the highest levels of flavonoids and proanthocyanidinsEthanol extracts of both plants possess better antioxidant activityagainst hydrogen peroxide, nitric oxide, and ABTS as well as higher reducingpower than the aqueous extractsAqueous extract of Dianthus thunbergii had the highest free radical scavenging activity as measured with DPPH. Abbreviations used: ABTS: 2'-azino-bis (3-ethylbenthiazoline-6-sulfonic acid); BHT: Butylated hydroxytoluene; DPPH: 1,1 diphenyl-2-picrylhydrazyl; DTA: Dianthus thunbergii aqueous extract (16.6%); DTE: Dianthus thunbergii ethanol extract (2.4%); Fe 3+ -TPTZ: Ferric tripyridyltriazine; FRAP: Ferric-reducing antioxidant potentials; GAE: Gallic acid equivalent; HAA: Hypoxis argentea aqueous extract (3.2%); HAE: Hypoxis argentea ethanol extract (1.8%); Qe: Quercetin equivalence; ROS: Reactive oxygen species; TBA: Thiobarbituric acid;TCA: Trichloroacetic acid.

Social media as an information source for rapid flood inundation mapping

NASA Astrophysics Data System (ADS)

Fohringer, J.; Dransch, D.; Kreibich, H.; Schröter, K.

2015-12-01

During and shortly after a disaster, data about the hazard and its consequences are scarce and not readily available. Information provided by eyewitnesses via social media is a valuable information source, which should be explored in a~more effective way. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in the case of floods. The novelty of this approach is the utilization of quantitative data that are derived from photos from eyewitnesses extracted from social media posts and their integration with established data. Due to the rapid availability of these posts compared to traditional data sources such as remote sensing data, areas affected by a flood, for example, can be determined quickly. The challenge is to filter the large number of posts to a manageable amount of potentially useful inundation-related information, as well as to interpret and integrate the posts into mapping procedures in a timely manner. To support rapid inundation mapping we propose a methodology and develop "PostDistiller", a tool to filter geolocated posts from social media services which include links to photos. This spatial distributed contextualized in situ information is further explored manually. In an application case study during the June 2013 flood in central Europe we evaluate the utilization of this approach to infer spatial flood patterns and inundation depths in the city of Dresden.

Social media as an information source for rapid flood inundation mapping

NASA Astrophysics Data System (ADS)

Fohringer, J.; Dransch, D.; Kreibich, H.; Schröter, K.

2015-07-01

During and shortly after a disaster data about the hazard and its consequences are scarce and not readily available. Information provided by eye-witnesses via social media are a valuable information source, which should be explored in a more effective way. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in case of floods. The novelty of this approach is the utilization of quantitative data that are derived from photos from eye-witnesses extracted from social media posts and its integration with established data. Due to the rapid availability of these posts compared to traditional data sources such as remote sensing data, for example areas affected by a flood can be determined quickly. The challenge is to filter the large number of posts to a manageable amount of potentially useful inundation-related information as well as their timely interpretation and integration in mapping procedures. To support rapid inundation mapping we propose a methodology and develop a tool to filter geo-located posts from social media services which include links to photos. This spatial distributed contextualized in-situ information is further explored manually. In an application case study during the June 2013 flood in central Europe we evaluate the utilization of this approach to infer spatial flood patterns and inundation depths in the city of Dresden.

Green Auctions and Reduction of Information Rents in Payments for Environmental Services: An Experimental Investigation in Sunan County, Northwestern China

PubMed Central

Deng, Xiaohong; Xu, Zhongmin

2015-01-01

Reducing information rents is an important task for government agencies wishing to purchase maximal environmental services with limited budgets. This paper reports on several green auction options for reducing information rents and improving the performance of the “Grain for Green” Payments for environmental services (PES) program implemented in northwestern China. In r experimental auctions and investigations, door-to-door interviews were conducted and bidding envelopes and survey questionnaires were used to determine the offers and the foregone profits of the participants. Three scenarios are analyzed in this paper: a uniform price auction, a discriminatory price auction, and an opportunity-cost system. The results show that compared to the uniform price auction system, the other auction systems can increase the cost-effectiveness of conservation contracting. Competitive bidding can reveal true opportunity costs and can reduce information rents extracted from the government by farmers using private information. The demographics and average bids of these auction types were also analyzed. “Perfect information” in the opportunity-cost offer system has the best performance but is very hard to implement in reality. The results of this research show that the auction is a valuable tool for purchasing conservation contracts in northwestern China, but that in the future, the performance of these auctions should be studied with relaxed model assumptions. PMID:25793263

Field trial of the enhanced data authentication system (EDAS)

DOE PAGES

Thomas, Maikael A.; Hymel, Ross W.; Baldwin, George; ...

2016-11-01

The Enhanced Data Authentication System (EDAS) is means to securely branch information from an existing measurement system or data stream to a secondary observer. In an international nuclear safeguards context, the EDAS connects to operator instrumentation, and provides a cryptographically secure copy of the information for a safeguards inspectorate. However, this novel capability could be a valuable complement to inspector-owned safeguards instrumentation, offering context that is valuable for anomaly resolution and contingency.

Selectively Distracted: Divided Attention and Memory for Important Information.

PubMed

Middlebrooks, Catherine D; Kerr, Tyson; Castel, Alan D

2017-08-01

Distractions and multitasking are generally detrimental to learning and memory. Nevertheless, people often study while listening to music, sitting in noisy coffee shops, or intermittently checking their e-mail. The current experiments examined how distractions and divided attention influence one's ability to selectively remember valuable information. Participants studied lists of words that ranged in value from 1 to 10 points while completing a digit-detection task, while listening to music, or without distractions. Though participants recalled fewer words following digit detection than in the other conditions, there were no significant differences between conditions in terms of selectively remembering the most valuable words. Similar results were obtained across a variety of divided-attention tasks that stressed attention and working memory to different degrees, which suggests that people may compensate for divided-attention costs by selectively attending to the most valuable items and that factors that worsen memory do not necessarily impair the ability to selectively remember important information.

Emotion Analysis of Telephone Complaints from Customer Based on Affective Computing.

PubMed

Gong, Shuangping; Dai, Yonghui; Ji, Jun; Wang, Jinzhao; Sun, Hai

2015-01-01

Customer complaint has been the important feedback for modern enterprises to improve their product and service quality as well as the customer's loyalty. As one of the commonly used manners in customer complaint, telephone communication carries rich emotional information of speeches, which provides valuable resources for perceiving the customer's satisfaction and studying the complaint handling skills. This paper studies the characteristics of telephone complaint speeches and proposes an analysis method based on affective computing technology, which can recognize the dynamic changes of customer emotions from the conversations between the service staff and the customer. The recognition process includes speaker recognition, emotional feature parameter extraction, and dynamic emotion recognition. Experimental results show that this method is effective and can reach high recognition rates of happy and angry states. It has been successfully applied to the operation quality and service administration in telecom and Internet service company.

Extracting lunar dust parameters from image charge signals produced by the Lunar Dust Experiment

NASA Astrophysics Data System (ADS)

Stanley, J.; Kempf, S.; Horanyi, M.; Szalay, J.

2015-12-01

The Lunar Dust Experiment (LDEX) onboard the Lunar Atmosphere and Dust Environment Explorer (LADEE) is an impact ionization dust detector used to characterize the lunar dust exosphere generated by the impacts of large interplanetary particles and meteor streams (Horanyi et al., 2015). In addition to the mass and speed of these lofted particles, LDEX is sensitive to their charge. The resulting signatures of impact events therefore provide valuable information about not only the ambient plasma environment, but also the speed vectors of these dust grains. Here, impact events produced from LDEX's calibration at the Dust Accelerator Laboratory are analyzed using an image charge model derived from the electrostatic simulation program, Coulomb. We show that parameters such as dust grain speed, size, charge, and position of entry into LDEX can be recovered and applied to data collected during LADEE's seven-month mission.

Optimal GHZ Paradox for Three Qubits

NASA Astrophysics Data System (ADS)

Ren, Changliang; Su, Hong-Yi; Xu, Zhen-Peng; Wu, Chunfeng; Chen, Jing-Ling

2015-08-01

Quatum nonlocality as a valuable resource is of vital importance in quantum information processing. The characterization of the resource has been extensively investigated mainly for pure states, while relatively less is know for mixed states. Here we prove the existence of the optimal GHZ paradox by using a novel and simple method to extract an optimal state that can saturate the tradeoff relation between quantum nonlocality and the state purity. In this paradox, the logical inequality which is formulated by the GHZ-typed event probabilities can be violated maximally by the optimal state for any fixed amount of purity (or mixedness). Moreover, the optimal state can be described as a standard GHZ state suffering flipped color noise. The maximal amount of noise that the optimal state can resist is 50%. We suggest our result to be a step toward deeper understanding of the role played by the AVN proof of quantum nonlocality as a useful physical resource.

Opportunities for collaborative phenotyping for disease resistance traits in a large beef cattle resource population.

PubMed

Thallman, R M; Kuehn, L A; Allan, M F; Bennett, G L; Koohmaraie, M

2008-01-01

The Germplasm Evaluation (GPE) Project at the US Meat Animal Research Center (USMARC) is planned to produce about 3,000 calves per year in support of the following objectives: identification and validation of genetic polymorphisms related to economically relevant traits (ERT), estimation of breed and heterosis effects among 16 breeds for ERT, and estimation of genetic correlations among ERT and physiological indicator traits (PIT). Opportunities exist for collaboration in the development and collection of PIT phenotypes for disease resistance. Other areas of potential collaboration include detailed diagnosis (identification of disease causing organisms, etc.) of treated animals, collaborative development of epidemiological statistical models that would extract more information from the records of diagnoses and treatments, or pharmacogenetics. Concentrating a variety of different phenotypes and research approaches on the same population makes each component much more valuable than it would be individually.

Integrated bioleaching of copper metal from waste printed circuit board-a comprehensive review of approaches and challenges.

PubMed

Awasthi, Abhishek Kumar; Zeng, Xianlai; Li, Jinhui

2016-11-01

Waste electrical and electronic equipment (e-waste) is the most rapidly growing waste stream in the world, and the majority of the residues are openly disposed of in developing countries. Waste printed circuit boards (WPCBs) make up the major portion of e-waste, and their informal recycling can cause environmental pollution and health risks. Furthermore, the conventional disposal and recycling techniques-mechanical treatments used to recover valuable metals, including copper-are not sustainable in the long term. Chemical leaching is rapid and efficient but causes secondary pollution. Bioleaching is a promising approach, eco-friendly and economically feasible, but it is slower process. This review considers the recycling potential of microbes and suggests an integrated bioleaching approach for Cu extraction and recovery from WPCBs. The proposed recycling system should be more effective, efficient and both technically and economically feasible.

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning

PubMed Central

Lagier, Samuel; Begnaud, Frédéric; Rodriguez, Ivan; Carleton, Alan

2015-01-01

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. Here we show that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) are dynamically reformatted in the network at the timescale of a single breath, giving rise to separated patterns of activity in ensemble of output neurons (mitral/tufted cells; M/T). Strikingly, the extent of pattern separation in M/T assemblies predicts behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimuli distinction, a process that is sculpted by synaptic inhibition. PMID:26301325

An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media.

PubMed

Wyllie, Jessica; Lucas, Benjamin; Carlson, Jamie; Kitchens, Brent; Kozary, Ben; Zaki, Mohamed

2016-01-01

Using a small-scale descriptive network analysis approach, this study highlights the importance of stakeholder networks for identifying valuable stakeholders and the management of existing stakeholders in the context of mental health not-for-profit services. We extract network data from the social media brand pages of three health service organizations from the U.S., U.K., and Australia, to visually map networks of 579 social media brand pages (represented by nodes), connected by 5,600 edges. This network data is analyzed using a collection of popular graph analysis techniques to assess the differences in the way each of the service organizations manage stakeholder networks. We also compare node meta-information against basic topology measures to emphasize the importance of effectively managing relationships with stakeholders who have large external audiences. Implications and future research directions are also discussed.

Spurious Additional Warming Reconstructed From Borehole Temperatures Corrected for the Effect of the Last Glacial Cycle

NASA Astrophysics Data System (ADS)

Šafanda, Jan

2018-03-01

Reconstructions of past ground surface temperature changes from temperature logs conducted in several hundred meter deep boreholes have proved to be a valuable independent source of information on climate variations over the last millennium. The reconstruction techniques have been evolving for more than two decades to extract optimally the climate signal of the last millennium contained in the temperature logs of different length performed in sites with different histories of the Last Glacial Cycle. This paper analyzes the method of the Last Glacial Cycle thermal effect removal from such borehole temperature profiles used by Beltrami et al. (2017, https://doi.org/10.1002/2016GL071317) in reconstructing the last 500 year history. I show that the reported results of additional warming in this period reconstructed from the corrected borehole data for North America are an artifact generated by the correction.

Transfer Learning for Improved Audio-Based Human Activity Recognition.

PubMed

Ntalampiras, Stavros; Potamitis, Ilyas

2018-06-25

Human activities are accompanied by characteristic sound events, the processing of which might provide valuable information for automated human activity recognition. This paper presents a novel approach addressing the case where one or more human activities are associated with limited audio data, resulting in a potentially highly imbalanced dataset. Data augmentation is based on transfer learning; more specifically, the proposed method: (a) identifies the classes which are statistically close to the ones associated with limited data; (b) learns a multiple input, multiple output transformation; and (c) transforms the data of the closest classes so that it can be used for modeling the ones associated with limited data. Furthermore, the proposed framework includes a feature set extracted out of signal representations of diverse domains, i.e., temporal, spectral, and wavelet. Extensive experiments demonstrate the relevance of the proposed data augmentation approach under a variety of generative recognition schemes.

ParaBTM: A Parallel Processing Framework for Biomedical Text Mining on Supercomputers.

PubMed

Xing, Yuting; Wu, Chengkun; Yang, Xi; Wang, Wei; Zhu, En; Yin, Jianping

2018-04-27

A prevailing way of extracting valuable information from biomedical literature is to apply text mining methods on unstructured texts. However, the massive amount of literature that needs to be analyzed poses a big data challenge to the processing efficiency of text mining. In this paper, we address this challenge by introducing parallel processing on a supercomputer. We developed paraBTM, a runnable framework that enables parallel text mining on the Tianhe-2 supercomputer. It employs a low-cost yet effective load balancing strategy to maximize the efficiency of parallel processing. We evaluated the performance of paraBTM on several datasets, utilizing three types of named entity recognition tasks as demonstration. Results show that, in most cases, the processing efficiency can be greatly improved with parallel processing, and the proposed load balancing strategy is simple and effective. In addition, our framework can be readily applied to other tasks of biomedical text mining besides NER.

The intermediate wavelength magnetic anomaly field of the north Pacific and possible source distributions

NASA Technical Reports Server (NTRS)

Labrecque, J. L.; Cande, S. C.; Jarrard, R. D. (Principal Investigator)

1983-01-01

A technique that eliminates external field sources and the effects of strike aliasing was used to extract from marine survey data the intermediate wavelength magnetic anomaly field for (B) in the North Pacific. A strong correlation exists between this field and the MAGSAT field although a directional sensitivity in the MAGSAT field can be detected. The intermediate wavelength field is correlated to tectonic features. Island arcs appear as positive anomalies of induced origin likely due to variations in crustal thickness. Seamount chains and oceanic plateaus also are manifested by strong anomalies. The primary contribution to many of these anomalies appears to be due to a remanent magnetization. The source parameters for the remainder of these features are presently unidentified ambiguous. Results indicate that the sea surface field is a valuable source of information for secular variation analysis and the resolution of intermediate wavelength source parameters.

VR for Mars Pathfinder

NASA Technical Reports Server (NTRS)

Blackmon, Theodore

1998-01-01

Virtual reality (VR) technology has played an integral role for Mars Pathfinder mission, operations Using an automated machine vision algorithm, the 3d topography of the Martian surface was rapidly recovered fro -a the stereo images captured. by the Tender camera to produce photo-realistic 3d models, An advanced, interface was developed for visualization and interaction with. the virtual environment of the Pathfinder landing site for mission scientists at the Space Flight Operations Facility of the Jet Propulsion Laboratory. The VR aspect of the display allowed mission scientists to navigate on Mars in Bud while remaining here on Earth, thus improving their spatial awareness of the rock field that surrounds the lenders Measurements of positions, distances and angles could be easily extracted from the topographic models, providing valuable information for science analysis and mission. planning. Moreover, the VR map of Mars has also been used to assist with the archiving and planning of activities for the Sojourner rover.

Joint inversions of two VTEM surveys using quasi-3D TDEM and 3D magnetic inversion algorithms

NASA Astrophysics Data System (ADS)

Kaminski, Vlad; Di Massa, Domenico; Viezzoli, Andrea

2016-05-01

In the current paper, we present results of a joint quasi-three-dimensional (quasi-3D) inversion of two versatile time domain electromagnetic (VTEM) datasets, as well as a joint 3D inversion of associated aeromagnetic datasets, from two surveys flown six years apart from one another (2007 and 2013) over a volcanogenic massive sulphide gold (VMS-Au) prospect in northern Ontario, Canada. The time domain electromagnetic (TDEM) data were inverted jointly using the spatially constrained inversion (SCI) approach. In order to increase the coherency in the model space, a calibration parameter was added. This was followed by a joint inversion of the total magnetic intensity (TMI) data extracted from the two surveys. The results of the inversions have been studied and matched with the known geology, adding some new valuable information to the ongoing mineral exploration initiative.

Nutraceuticals, A New Challenge for Medicinal Chemistry.

PubMed

Sut, Stefania; Baldan, Valeria; Faggian, Marta; Peron, Gregorio; Dall Acqua, Stefano

2016-01-01

"Nutraceuticals" are food-derived products largely used for their presumed healthpromoting or disease-preventing effects. In the recent years, many efforts have been aimed at assessing nutraceutical efficacy and safety, but these factors are difficult to address because of the complex chemical compositions and multiple mode of actions. Thus, the study of nutraceutical ingredients poses several challenges for the medicinal chemistry field, some of which are related to extraction and chemical characterization, some to in vitro and in vivo bioactivity evaluation, and some to the bioavailability and interaction of these natural mixtures with organs and microbiota. Furthermore, because of their nature as medicinal and food products, these nutraceuticals can also be considered as a valuable source of new "lead compounds", creating the opportunity to discover new classes of therapeutic agents. This review provides information on these themes, showing the new challenges that comprehensive medicinal chemistry research is called to answer in the field of nutraceuticals.

Management of Breast Milk Oversupply in Traditional Persian Medicine.

PubMed

Kabiri, Marya; Kamalinejad, Mohammad; Sohrabvand, Farnaz; Bioos, Soodabeh; Babaeian, Mohammad

2017-10-01

Comprehensive explanation about milk oversupply is not available in the current literature because few studies have been done on this topic. In traditional Persian medicine, milk oversupply and its management have been described. The aim of this study was to investigate milk oversupply from the perspective of medieval Persian practitioners. In this study, some main medical resources of traditional Persian medicine such as Al-Havi and the Canon of Medicine were studied to extract valuable information about milk oversupply. Etiology of milk overproduction according to traditional Persian medicine is based on humors theory and cannot be easily compared with current medical concepts. Diet modifications and natural remedies have been applied for managing this condition but the majority of traditional Persian medicine interventions for reducing milk oversupply have not been scientifically investigated in modern medicine. The knowledge of milk oversupply in traditional Persian medicine may be helpful to conduct further related studies.

Analysis and implementation of a World Health Organization health report: methodological concepts and strategies.

PubMed

von Groote, Per Maximilian; Giustini, Alessandro; Bickenbach, Jerome Edmond

2014-01-01

A long-standing scientific discourse on the use of health research evidence to inform policy has come to produce multiple implementation theories, frameworks, models, and strategies. It is from this extensive body of research that the authors extract and present essential components of an implementation process in the health domain, gaining valuable guidance on how to successfully meet the challenges of implementation. Furthermore, this article describes how implementation content can be analyzed and reorganized, with a special focus on implementation at different policy, systems and services, and individual levels using existing frameworks and tools. In doing so, the authors aim to contribute to the establishment and testing of an implementation framework for reports such as the World Health Organization World Report on Disability, the World Health Organization International Perspectives on Spinal Cord Injury, and other health policy reports or technical health guidelines.

Usage of FTIR-ATR as Non-Destructive Analysis of Selected Toxic Dyes

NASA Astrophysics Data System (ADS)

Bartošová, Alica; Blinová, Lenka; Sirotiak, Maroš; Michalíková, Anna

2017-06-01

The degradation of the environment which is due to the discharge of polluting wastewater from industrial sources poses a real problem in several countries. Textile industries use large volumes of water in their operations, discharging thus large volume of wastewater into the environment, most of which is untreated. The wastewater contains a variety of chemicals from various stages of process operations, including desizing, scouring, bleaching and dyeing. The main purpose of this paper is to introduce Infrared Spectrometry with Fourier transformation as a non-destructive method for study, identifation and rapid determination of selected representatives of cationic (Methylene Blue), azo (Congo Red, Eriochrome Black T) and nitroso (Naphthol Green B) dyes. In conjunction with the ATR technique, FTIR offers a reliable detection method of dyes without extraction by other dangerous substances. Spectral interpretation of dye spectra revealed valuable information about the identification and characterization of each group of dyes.

Study of the dopamine effect into cell solutions by impedance analysis

NASA Astrophysics Data System (ADS)

Paivana, G.; Apostolou, T.; Kaltsas, G.; Kintzios, S.

2017-11-01

Electrochemical Impedance Spectroscopy (EIS) has become a technique that is frequently used for biological assays. Impedance is defined as a complex - valued generalization of resistance and varies depending on its use per application field. In health sciences, bioimpedance is widely used as non-invasive and low cost alternative in many medical areas that provides valuable information about health status. This work focuses on assessing the effects of a bioactive substance applied to immobilized cells. Dopamine was used as a stimulant in order to implement impedance analysis with a specific type of cells. Dopamine constitutes one of the most important catecholamine neurotransmitters in both the mammalian central and peripheral nervous systems. The main purpose is to extract calibration curves at different frequencies with known dopamine concentrations in order to describe the behavior of cells applied to dopamine using an impedance measurement device. For comparison purposes, non-immobilized cells were tested for the same dopamine concentrations.

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning.

PubMed

Gschwend, Olivier; Abraham, Nixon M; Lagier, Samuel; Begnaud, Frédéric; Rodriguez, Ivan; Carleton, Alan

2015-10-01

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features, thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. We found that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) were dynamically reformatted in the network on the timescale of a single breath, giving rise to separated patterns of activity in an ensemble of output neurons, mitral/tufted (M/T) cells. Notably, the extent of pattern separation in M/T assemblies predicted behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimulus distinction, a process that is sculpted by synaptic inhibition.

Emotion Analysis of Telephone Complaints from Customer Based on Affective Computing

PubMed Central

Gong, Shuangping; Ji, Jun; Wang, Jinzhao; Sun, Hai

2015-01-01

Customer complaint has been the important feedback for modern enterprises to improve their product and service quality as well as the customer's loyalty. As one of the commonly used manners in customer complaint, telephone communication carries rich emotional information of speeches, which provides valuable resources for perceiving the customer's satisfaction and studying the complaint handling skills. This paper studies the characteristics of telephone complaint speeches and proposes an analysis method based on affective computing technology, which can recognize the dynamic changes of customer emotions from the conversations between the service staff and the customer. The recognition process includes speaker recognition, emotional feature parameter extraction, and dynamic emotion recognition. Experimental results show that this method is effective and can reach high recognition rates of happy and angry states. It has been successfully applied to the operation quality and service administration in telecom and Internet service company. PMID:26633967

NMR-based metabolomic analysis of spatial variation in soft corals.

PubMed

He, Qing; Sun, Ruiqi; Liu, Huijuan; Geng, Zhufeng; Chen, Dawei; Li, Yinping; Han, Jiao; Lin, Wenhan; Du, Shushan; Deng, Zhiwei

2014-03-28

Soft corals are common marine organisms that inhabit tropical and subtropical oceans. They are shown to be rich source of secondary metabolites with biological activities. In this work, soft corals from two geographical locations were investigated using ¹H-NMR spectroscopy coupled with multivariate statistical analysis at the metabolic level. A partial least-squares discriminant analysis showed clear separation among extracts of soft corals grown in Sanya Bay and Weizhou Island. The specific markers that contributed to discrimination between soft corals in two origins belonged to terpenes, sterols and N-containing compounds. The satisfied precision of classification obtained indicates this approach using combined ¹H-NMR and chemometrics is effective to discriminate soft corals collected in different geographical locations. The results revealed that metabolites of soft corals evidently depended on living environmental condition, which would provide valuable information for further relevant coastal marine environment evaluation.

Modeling and numerical simulations of growth and morphologies of three dimensional aggregated silver films

NASA Astrophysics Data System (ADS)

Davis, L. J.; Boggess, M.; Kodpuak, E.; Deutsch, M.

2012-11-01

We report on a model for the deposition of three dimensional, aggregated nanocrystalline silver films, and an efficient numerical simulation method developed for visualizing such structures. We compare our results to a model system comprising chemically deposited silver films with morphologies ranging from dilute, uniform distributions of nanoparticles to highly porous aggregated networks. Disordered silver films grown in solution on silica substrates are characterized using digital image analysis of high resolution scanning electron micrographs. While the latter technique provides little volume information, plane-projected (two dimensional) island structure and surface coverage may be reliably determined. Three parameters governing film growth are evaluated using these data and used as inputs for the deposition model, greatly reducing computing requirements while still providing direct access to the complete (bulk) structure of the films throughout the growth process. We also show how valuable three dimensional characteristics of the deposited materials can be extracted using the simulated structures.

Management of Breast Milk Oversupply in Traditional Persian Medicine

PubMed Central

Kabiri, Marya; Kamalinejad, Mohammad; Sohrabvand, Farnaz; Bioos, Soodabeh

2017-01-01

Comprehensive explanation about milk oversupply is not available in the current literature because few studies have been done on this topic. In traditional Persian medicine, milk oversupply and its management have been described. The aim of this study was to investigate milk oversupply from the perspective of medieval Persian practitioners. In this study, some main medical resources of traditional Persian medicine such as Al-Havi and the Canon of Medicine were studied to extract valuable information about milk oversupply. Etiology of milk overproduction according to traditional Persian medicine is based on humors theory and cannot be easily compared with current medical concepts. Diet modifications and natural remedies have been applied for managing this condition but the majority of traditional Persian medicine interventions for reducing milk oversupply have not been scientifically investigated in modern medicine. The knowledge of milk oversupply in traditional Persian medicine may be helpful to conduct further related studies. PMID:28817945

An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media

PubMed Central

Carlson, Jamie; Kitchens, Brent; Kozary, Ben; Zaki, Mohamed

2016-01-01

Using a small-scale descriptive network analysis approach, this study highlights the importance of stakeholder networks for identifying valuable stakeholders and the management of existing stakeholders in the context of mental health not-for-profit services. We extract network data from the social media brand pages of three health service organizations from the U.S., U.K., and Australia, to visually map networks of 579 social media brand pages (represented by nodes), connected by 5,600 edges. This network data is analyzed using a collection of popular graph analysis techniques to assess the differences in the way each of the service organizations manage stakeholder networks. We also compare node meta-information against basic topology measures to emphasize the importance of effectively managing relationships with stakeholders who have large external audiences. Implications and future research directions are also discussed. PMID:27711236

Literature review on production process to obtain extra virgin olive oil enriched in bioactive compounds. Potential use of byproducts as alternative sources of polyphenols.

PubMed

Frankel, Edwin; Bakhouche, Abdelhakim; Lozano-Sánchez, Jesús; Segura-Carretero, Antonio; Fernández-Gutiérrez, Alberto

2013-06-05

This review describes the olive oil production process to obtain extra virgin olive oil (EVOO) enriched in polyphenol and byproducts generated as sources of antioxidants. EVOO is obtained exclusively by mechanical and physical processes including collecting, washing, and crushing of olives, malaxation of olive paste, centrifugation, storage, and filtration. The effect of each step is discussed to minimize losses of polyphenols from large quantities of wastes. Phenolic compounds including phenolic acids, alcohols, secoiridoids, lignans, and flavonoids are characterized in olive oil mill wastewater, olive pomace, storage byproducts, and filter cake. Different industrial pilot plant processes are developed to recover phenolic compounds from olive oil byproducts with antioxidant and bioactive properties. The technological information compiled in this review will help olive oil producers to improve EVOO quality and establish new processes to obtain valuable extracts enriched in polyphenols from byproducts with food ingredient applications.

GEM at 10: a decade's experience with the Guideline Elements Model.

PubMed

Hajizadeh, Negin; Kashyap, Nitu; Michel, George; Shiffman, Richard N

2011-01-01

The Guideline Elements Model (GEM) was developed in 2000 to organize the information contained in clinical practice guidelines using XML and to represent guideline content in a form that can be understood by human readers and processed by computers. In this work, we systematically reviewed the literature to better understand how GEM was being used, potential barriers to its use, and suggestions for improvement. Fifty external and twelve internally produced publications were identified and analyzed. GEM was used most commonly for modeling and ontology creation. Other investigators applied GEM for knowledge extraction and data mining, for clinical decision support for guideline generation. The GEM Cutter software-used to markup guidelines for translation into XML- has been downloaded 563 times since 2000. Although many investigators found GEM to be valuable, others critiqued its failure to clarify guideline semantics, difficulties in markup, and the fact that GEM files are not usually executable.

Towards Better Understanding QBism.

PubMed

Khrennikov, Andrei

2018-01-01

Recently I posted a paper entitled "External observer reflections on QBism". As any external observer, I was not able to reflect all features of QBism properly. The comments I received from one of QBism's creators, C. A. Fuchs, were very valuable to me in better understanding the views of QBists. Some of QBism's features are very delicate and extracting them from articles of QBists is not a simple task. Therefore, I hope that the second portion of my reflections on QBism (or, strictly speaking, my reflections on Fuchs reflections on my earlier reflections) might be interesting and useful for other experts in quantum foundations and quantum information theory (especially, taking into account my previous aggressively anti-QBism position). In the present paper I correct some of my earlier posted critical comments on QBism. At the same time, other critical comments gained new validation through my recent deeper understanding of QBists views on a number of problems.

Development of Solvent Extraction Approach to Recycle Enriched Molybdenum Material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tkac, Peter; Brown, M. Alex; Sen, Sujat

2016-06-01

Argonne National Laboratory, in cooperation with Oak Ridge National Laboratory and NorthStar Medical Technologies, LLC, is developing a recycling process for a solution containing valuable Mo-100 or Mo-98 enriched material. Previously, Argonne had developed a recycle process using a precipitation technique. However, this process is labor intensive and can lead to production of large volumes of highly corrosive waste. This report discusses an alternative process to recover enriched Mo in the form of ammonium heptamolybdate by using solvent extraction. Small-scale experiments determined the optimal conditions for effective extraction of high Mo concentrations. Methods were developed for removal of ammonium chloridemore » from the molybdenum product of the solvent extraction process. In large-scale experiments, very good purification from potassium and other elements was observed with very high recovery yields (~98%).« less

On the space monitoring of the Sassi and Murgia Park (Matera UNESCO site) using LANDSAT time series

NASA Astrophysics Data System (ADS)

Lanorte, Antonio; Nole, Gabriele; Manzi, Teresa; Lasaponara, Rosa

2015-04-01

This paper is focused on the preliminary results obtained in the framework of the Great relevance project " Smart management of cultural heritage sites in Italy and Argentina: Earth Observation and pilot projects funded by the Ministero degli Affari Esteri e della Cooperazione Internazionale --MAE, 17/04/2014, Prot. nr. 0090692, 2014-2016. A temporal series (1999-2011) of the LANDSAT TM data was used to carried out investigation in the Murgia Park enclosed in the Matera UNESCO site . The PCA was adopted to enhance regions of localized change in multi-temporal data sets (Lasaponara 2006). Both naturally vegetated areas (forest, shrub-land, herbaceous cover) and agricultural lands have been investigated in order to extract the most prominent natural and/or man induced alterations affecting soil and vegetation cover. Results from PCA were compared with independent data sets and field survey to evaluate the reliability of the obtained maps of the ongoing land degradation phenomenon. Such analyses can provide valuable information for an operational monitoring of the status of vegetation which is an indicator of the degree of stress namely any disturbance that adversely influences plants in response to natural hazards and/or anthropogenic activities. Our findings suggest that the Landsat TM time series can provide valuable information for environmental management policies involving biodiversity preservation and rational exploitation of natural and agricultural resources. Acknowledgement This research was performed within the framework of the Great relevance project " Smart management of cultural heritage sites in Italy and Argentina: Earth Observation and pilot projects funded by the Ministero degli Affari Esteri e della Cooperazione Internazionale --MAE, 17/04/2014, Prot. nr. 0090692, 2014-2016

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data. PMID:16438716

Genome sequencing of the extinct Eurasian wild aurochs illuminates the phylogeography and evolution of cattle

USDA-ARS?s Scientific Manuscript database

Interrogation of modern and ancient bovine genome sequences provides a valuable model to study the evolution of cattle. Here, we analyse the first complete wild aurochs (Bos primigenius) genome sequence using DNA extracted from a ~ 6,750 year-old humerus bone retrieved from a cave site in Derbyshire...

Isothermal microwave and microwave-convection drying of olive pomace

USDA-ARS?s Scientific Manuscript database

Olive pomace is the residue produced when olives are pressed for oil. Valuable polyphenolic compounds can be extracted from olive pomace, but this material is more than 60% water (wet basis) and thus costly to transport and process in its original, wet form. The objective of this study was thus to ...

Investigating the Relationship between Dialogue Structure and Tutoring Effectiveness: A Hidden Markov Modeling Approach

ERIC Educational Resources Information Center

Boyer, Kristy Elizabeth; Phillips, Robert; Ingram, Amy; Ha, Eun Young; Wallis, Michael; Vouk, Mladen; Lester, James

2011-01-01

Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems research. Human-human tutoring offers a valuable model for identifying effective tutorial strategies, but extracting them is a challenge because of the richness of human dialogue. This article addresses that challenge through a machine learning…

Data, Data Everywhere--Not a Report in Sight!

ERIC Educational Resources Information Center

Norman, Wendy

2003-01-01

Presents six steps of data warehouse development that result in valuable, long-term reporting solutions, discussing how to choose the right reporting vehicle. The six steps are: defining one's needs; mapping the source for each element; extracting the data; cleaning and verifying the data; moving the data into a relational database; and developing…

Automatically extracting the significant aspects evaluated in game reviews

NASA Astrophysics Data System (ADS)

Fong, Chiok Hoong; Ng, Yen Kaow

2017-04-01

Understanding the criteria (or "aspects") that reviewers use to evaluate games is important to game developers and publishers, since this will give them important input on how to improve their products. Techniques for the extraction of such aspects have been studied by others, albeit not specific to the gaming industry. In this paper we demonstrate an aspect extraction and analysis system specific to computer games. The system extracts game review texts from a list of known websites and automatically extracts candidate aspects from the review text using techniques from natural language processing and sentiment analysis. It then ranks the candidate aspects using the HITS algorithm. To evaluate the correctness of the extracted aspects, we used the system to calculate an overall score for each game by aggregating its highly-rated aspects, weighted by the importance of the respective aspects. The aggregated scores resulted in a ranking of games, which we compared to a known ranking from a popular website - the rankings showed overall consistency, which suggests that the system has extracted valuable aspects from the reviews. Using the extracted aspect, our system also facilitates the analysis of a game, by evaluating how review articles have rated its performance in these extracted aspects.

Quantification of hair cortisol concentration in common marmosets (Callithrix jacchus) and tufted capuchins (Cebus apella).

PubMed

Phillips, Kimberley A; Tukan, Alyson N; Rigodanzo, Anna D; Reusch, Ryan T; Brasky, Kathleen M; Meyer, Jerrold S

2018-06-04

Quantifying cortisol concentration in hair is a non-invasive biomarker of long-term hypothalamic-pituitary-adrenal (HPA) activation, and thus can provide important information on laboratory animal health. Marmosets (Callithrix jacchus) and capuchins (Cebus apella) are New World primates increasingly used in biomedical and neuroscience research, yet published hair cortisol concentrations for these species are limited. Review of the existing published hair cortisol values from marmosets reveals highly discrepant values and the use of variable techniques for hair collection, processing, and cortisol extraction. In this investigation we utilized a well-established, standardized protocol to extract and quantify cortisol from marmoset (n = 12) and capuchin (n = 4) hair. Shaved hair samples were collected from the upper thigh during scheduled exams and analyzed via methanol extraction and enzyme immunoassay. In marmosets, hair cortisol concentration ranged from 2,710 to 6,267 pg/mg and averaged 4,070 ± 304 pg/mg. In capuchins, hair cortisol concentration ranged from 621 to 2,089 pg/mg and averaged 1,092 ± 338 pg/mg. Hair cortisol concentration was significantly different between marmosets and capuchins, with marmosets having higher concentrations than capuchins. The incorporation of hair cortisol analysis into research protocols provides a non-invasive measure of HPA axis activity over time, which offers insight into animal health. Utilization of standard protocols across laboratories is essential to obtaining valid measurements and allowing for valuable future cross-species comparisons. © 2018 Wiley Periodicals, Inc.

Revealing small-scale diffracting discontinuities by an optimization inversion algorithm

NASA Astrophysics Data System (ADS)

Yu, Caixia; Zhao, Jingtao; Wang, Yanfei

2017-02-01

Small-scale diffracting geologic discontinuities play a significant role in studying carbonate reservoirs. The seismic responses of them are coded in diffracted/scattered waves. However, compared with reflections, the energy of these valuable diffractions is generally one or even two orders of magnitude weaker. This means that the information of diffractions is strongly masked by reflections in the seismic images. Detecting the small-scale cavities and tiny faults from the deep carbonate reservoirs, mainly over 6 km, poses an even bigger challenge to seismic diffractions, as the signals of seismic surveyed data are weak and have a low signal-to-noise ratio (SNR). After analyzing the mechanism of the Kirchhoff migration method, the residual of prestack diffractions located in the neighborhood of the first Fresnel aperture is found to remain in the image space. Therefore, a strategy for extracting diffractions in the image space is proposed and a regularized L 2-norm model with a smooth constraint to the local slopes is suggested for predicting reflections. According to the focusing conditions of residual diffractions in the image space, two approaches are provided for extracting diffractions. Diffraction extraction can be directly accomplished by subtracting the predicted reflections from seismic imaging data if the residual diffractions are focused. Otherwise, a diffraction velocity analysis will be performed for refocusing residual diffractions. Two synthetic examples and one field application demonstrate the feasibility and efficiency of the two proposed methods in detecting the small-scale geologic scatterers, tiny faults and cavities.

Multi-Response Extraction Optimization Based on Anti-Oxidative Activity and Quality Evaluation by Main Indicator Ingredients Coupled with Chemometric Analysis on Thymus quinquecostatus Celak.

PubMed

Chang, Yan-Li; Shen, Meng; Ren, Xue-Yang; He, Ting; Wang, Le; Fan, Shu-Sheng; Wang, Xiu-Huan; Li, Xiao; Wang, Xiao-Ping; Chen, Xiao-Yi; Sui, Hong; She, Gai-Mei

2018-04-19

Thymus quinquecostatus Celak is a species of thyme in China and it used as condiment and herbal medicine for a long time. To set up the quality evaluation of T. quinquecostatus , the response surface methodology (RSM) based on its 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity was introduced to optimize the extraction condition, and the main indicator components were found through an UPLC-LTQ-Orbitrap MS n method. The ethanol concentration, solid-liquid ratio, and extraction time on optimum conditions were 42.32%, 1:17.51, and 1.8 h, respectively. 35 components having 12 phenolic acids and 23 flavonoids were unambiguously or tentatively identified both positive and negative modes to employ for the comprehensive analysis in the optimum anti-oxidative part. A simple, reliable, and sensitive HPLC method was performed for the multi-component quantitative analysis of T. quinquecostatus using six characteristic and principal phenolic acids and flavonoids as reference compounds. Furthermore, the chemometrics methods (principal components analysis (PCA) and hierarchical clustering analysis (HCA)) appraised the growing areas and harvest time of this herb closely relative to the quality-controlled. This study provided full-scale qualitative and quantitative information for the quality evaluation of T. quinquecostatus , which would be a valuable reference for further study and development of this herb and related laid the foundation of further study on its pharmacological efficacy.

Simultaneous extraction, identification and quantification of phenolic compounds in Eclipta prostrata using microwave-assisted extraction combined with HPLC-DAD-ESI-MS/MS.

PubMed

Fang, Xinsheng; Wang, Jianhua; Hao, Jifu; Li, Xueke; Guo, Ning

2015-12-01

A simple and rapid method was developed using microwave-assisted extraction (MAE) combined with HPLC-DAD-ESI-MS/MS for the simultaneous extraction, identification, and quantification of phenolic compounds in Eclipta prostrata, a common herb and vegetable in China. The optimized parameters of MAE were: employing 50% ethanol as solvent, microwave power 400 W, temperature 70 °C, ratio of liquid/solid 30 mL/g and extraction time 2 min. Compared to conventional extraction methods, the optimized MAE can avoid the degradation of the phenolic compounds and simultaneously obtained the highest yields of all components faster with less consumption of solvent and energy. Six phenolic acids, six flavonoid glycosides and one coumarin were firstly identified. The phenolic compounds were quantified by HPLC-DAD with good linearity, precision, and accuracy. The extract obtained by MAE showed significant antioxidant activity. The proposed method provides a valuable and green analytical methodology for the investigation of phenolic components in natural plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Antimicrobial and Antibiofilm Activities of Citrus Water-Extracts Obtained by Microwave-Assisted and Conventional Methods.

PubMed

Caputo, Leonardo; Quintieri, Laura; Cavalluzzi, Maria Maddalena; Lentini, Giovanni; Habtemariam, Solomon

2018-06-17

Citrus pomace is a huge agro-food industrial waste mostly composed of peels and traditionally used as compost or animal feed. Owing to its high content of compounds beneficial to humans (e.g., flavonoids, phenol-like acids, and terpenoids), citrus waste is increasingly used to produce valuable supplements, fragrance, or antimicrobials. However, such processes require sustainable and efficient extraction strategies by solvent-free techniques for environmentally-friendly good practices. In this work, we evaluated the antimicrobial and antibiofilm activity of water extracts of three citrus peels (orange, lemon, and citron) against ten different sanitary relevant bacteria. Both conventional extraction methods using hot water (HWE) and microwave-assisted extraction (MAE) were used. Even though no extract fully inhibited the growth of the target bacteria, these latter (mostly pseudomonads) showed a significant reduction in biofilm biomass. The most active extracts were obtained from orange and lemon peel by using MAE at 100 °C for 8 min. These results showed that citrus peel water infusions by MAE may reduce biofilm formation possibly enhancing the susceptibility of sanitary-related bacteria to disinfection procedures.

Comparison in antioxidant and antitumor activities of pine polyphenols and its seven biotransformation extracts by fungi

PubMed Central

Li, Hui

2017-01-01

Microbial transformation can strengthen the antioxidant and antitumor activities of polyphenols. Polyphenols contents, antioxidant and antitumor activities of pine polyphenols and its biotransformation extracts by Aspergillus niger, Aspergillus oryzae, Aspergillus carbonarius, Aspergillus candidus, Trichodermas viride, Mucor wutungkiao and Rhizopus sp were studied. Significant differences were noted in antioxidant and antitumor activities. The highest antioxidant activities in Trolox equivalent antioxidant capacity (TEAC), DPPH radical scavenging activity, superoxide anion radical scavenging activity, hydroxyl radical scavenging activity, reducing power assay and antitumor activity against LoVo cells were biotransformation extract of Aspergillus carbonarius (BAC), biotransformation extract of Mucor wutungkiao (BMW), biotransformation extract of Aspergillus carbonarius (BAC), biotransformation extract of Aspergillus niger (BAN), biotransformation extract of Aspergillus oryzae (BAO) and BMW, respectively. Correlation analysis found that antioxidant and antitumor activities were associated with polyphenols contents and types of free radicals and tumors. A. carbonarius can make polyphenol oxidation, hydroxylation and methylation, and form new polyphenols. In conclusion, A. carbonarius, A. niger and M. wutungkiao are valuable microorganisms used for polyphenols biotransformation and enhance the antioxidant and antitumor activities of polyphenols. PMID:28560092

HISTORICAL ANALYSIS, A VALUABLE TOOL IN COMMUNITY-BASED ENVIRONMENTAL PROTECTION

EPA Science Inventory

A historical analysis of the ecological consequences of development can be a valuable tool in community-based environmental protection. These studies can engage the public in environmental issues and lead to informed decision making. Historical studies provide an understanding of...

An exploratory study of air emissions associated with shale gas development and production in the Barnett Shale.

PubMed

Rich, Alisa; Grover, James P; Sattler, Melanie L

2014-01-01

Information regarding air emissions from shale gas extraction and production is critically important given production is occurring in highly urbanized areas across the United States. Objectives of this exploratory study were to collect ambient air samples in residential areas within 61 m (200 feet) of shale gas extraction/production and determine whether a "fingerprint" of chemicals can be associated with shale gas activity. Statistical analyses correlating fingerprint chemicals with methane, equipment, and processes of extraction/production were performed. Ambient air sampling in residential areas of shale gas extraction and production was conducted at six counties in the Dallas/Fort Worth (DFW) Metroplex from 2008 to 2010. The 39 locations tested were identified by clients that requested monitoring. Seven sites were sampled on 2 days (typically months later in another season), and two sites were sampled on 3 days, resulting in 50 sets of monitoring data. Twenty-four-hour passive samples were collected using summa canisters. Gas chromatography/mass spectrometer analysis was used to identify organic compounds present. Methane was present in concentrations above laboratory detection limits in 49 out of 50 sampling data sets. Most of the areas investigated had atmospheric methane concentrations considerably higher than reported urban background concentrations (1.8-2.0 ppm(v)). Other chemical constituents were found to be correlated with presence of methane. A principal components analysis (PCA) identified multivariate patterns of concentrations that potentially constitute signatures of emissions from different phases of operation at natural gas sites. The first factor identified through the PCA proved most informative. Extreme negative values were strongly and statistically associated with the presence of compressors at sample sites. The seven chemicals strongly associated with this factor (o-xylene, ethylbenzene, 1,2,4-trimethylbenzene, m- and p-xylene, 1,3,5-trimethylbenzene, toluene, and benzene) thus constitute a potential fingerprint of emissions associated with compression. Information regarding air emissions from shale gas development and production is critically important given production is now occurring in highly urbanized areas across the United States. Methane, the primary shale gas constituent, contributes substantially to climate change; other natural gas constituents are known to have adverse health effects. This study goes beyond previous Barnett Shale field studies by encompassing a wider variety of production equipment (wells, tanks, compressors, and separators) and a wider geographical region. The principal components analysis, unique to this study, provides valuable information regarding the ability to anticipate associated shale gas chemical constituents.

Antioxidant, antimicrobial, toxicity and analgesic properties of ethanol extract of Solena amplexicaulis root.

PubMed

Kabir, Md Golam; Rahman, Md Monsor; Ahmed, Nazim Uddin; Fakruddin, Md; Islam, Saiful; Mazumdar, Reaz Mohammad

2014-08-19

This study was subjected to investigate different pharmacological properties of ethanol extract of Solena amplexicaulis root. The extract contains flavonoid, alkaloid, saponin and steroid compounds. The extract exhibited excellent antioxidant activity in DPPH radical scavenging activity. The extract also showed potent activity in brine shrimp lethality bioassay. The LC50 value was found to 44.677 μg/ml. The extract showed better anti-bacterial activity against gram-negative bacteria. In antifungal assay, the maximum 79.31% of anti-mycotic activity was observed against Aspergillus ochraceus while minimum 44.2% against Rhizopus oryzae. MIC value ranged between 1500-3000 μg/ml. The extract was found moderately toxic with a 24-hr LD50 value of 81.47 mg/kg in Swiss albino mice. The degree of inhibition by the ethanolic extract of the root was found less than that of standard analgesic drug diclofenac sodium. The extract also showed moderate anti-inflammatory and antinociceptive activity and anti-diabetic property. Reducing power of the extract was comparable with standard ascorbic acid. Moderate in vitro thrombolytic activity, lipid peroxidation inhibition property, metal chelating ability and stress-protective activity was also observed. Ethanol extract of Solena amplexicaulis root can be valuable for treatment of different diseases.

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Informational and decisional empowerment in online health support communities: initial psychometric validation of the Cyber Info-Decisional Empowerment Scale (CIDES) and preliminary data from administration of the scale.

PubMed

Seçkin, Gül

2011-12-01

This article presents initial psychometric validation of an instrument developed to measure cyber informational and decisional empowerment. The article provides preliminary insights into the extent to which cyber patients view the digital environment of peer-based information and support as a resource for informed and empowered participation in self health care management. Data come from cancer patients (N = 350) who participated in the Study of Virtual Health Networks for Cancer Patients of the 21st Century. Data were first analyzed using exploratory factor analysis with principle component extraction and Varimax rotation. Age-based split-sample analysis (≥ 51 and ≤ 50) was performed on a subsample, which consisted of only women (N = 255), in order to cross-validate psychometric data obtained from the full sample. A confirmatory factor analysis was conducted using AMOS 19.0. to further validate the scale. The composite scale is unidimensional with excellent internal consistency reliability. The highest average scores were obtained for informational empowerment items. The lowest average was for the item that measured empowerment to seek second opinion from additional health care professionals. The ability of this composite measure to provide information about the extent to which computer-connected patients view digital peer support as an empowerment tool makes it a valuable addition to the literature in health informatics, supportive cancer care, and health quality of life research.

Data of 10 SSR markers for genomes of homo sapiens and monkeys.

PubMed

Reddy, K K V V V S; Raju, S Viswanadha; Someswara Rao, Chinta

2017-06-01

In this data, we present 10 Simple Sequence Repeat(SSR) markers TAGA, TCAT, GAAT, AGAT, AGAA, GATA, TATC, CTTT, TCTG and TCTA which are extracted from the genomes of homo sapiens and monkeys using string matching mechanism [1]. All loci showed 4 Base Pair(bp) in allele size, indicating that there are some polymorphisms between individuals correlating to the number of SSR repeats that maybe useful for the detection of similarity among the genotypes. Collectively, these data show that the SSR extraction is a valuable method to illustrate genetic variation of genomes.

Assessment of ecotoxicity and total volatile organic compound (TVOC) emissions from food and children's toy products.

PubMed

Szczepańska, Natalia; Marć, Mariusz; Kudłak, Błażej; Simeonov, Vasil; Tsakovski, Stefan; Namieśnik, Jacek

2018-09-30

The development of new methods for identifying a broad spectrum of analytes, as well as highly selective tools to provide the most accurate information regarding the processes and relationships in the world, has been an area of interest for researchers for many years. The information obtained with these tools provides valuable data to complement existing knowledge but, above all, to identify and determine previously unknown hazards. Recently, attention has been paid to the migration of xenobiotics from the surfaces of various everyday objects and the resulting impacts on human health. Since children are among those most vulnerable to health consequences, one of the main subjects of interest is the migration of low-molecular-weight compounds from toys and products intended for children. This migration has become a stimulus for research aimed at determining the degree of release of compounds from popular commercially available chocolate/toy sets. One of main objectives of this research was to determine the impact of time on the ecotoxicity (with Vibrio fischeri bioluminescent bacteria) of extracts of products intended for children and to assess the correlation with total volatile organic compound emissions using basic chemometric methods. The studies on endocrine potential (with XenoScreen YES/YAS) of the extracts and showed that compounds released from the studied objects (including packaging foils, plastic capsules storing toys, most of toys studied and all chocolate samples) exhibit mostly androgenic antagonistic behavior while using artificial saliva as extraction medium increased the impact observed. The impact of time in most cases was positive one and increased with prolonging extraction time. The small-scale stationary environmental test chambers - μ-CTE™ 250 system was employed to perform the studies aimed at determining the profile of total volatile organic compounds (TVOCs) emissions. Due to this it was possible to state that objects from which the greatest amounts of contaminants are released are plastic containers (with emission rate falling down from 3273 to 2280 ng/g of material at 6 h of conditioning in elevated temperature). Copyright © 2018 Elsevier Inc. All rights reserved.

Anti-Photoaging Effect of Jeju Putgyul (Unripe Citrus) Extracts on Human Dermal Fibroblasts and Ultraviolet B-induced Hairless Mouse Skin.

PubMed

Choi, Seung-Hyun; Choi, Sun-Il; Jung, Tae-Dong; Cho, Bong-Yeon; Lee, Jin-Ha; Kim, Seung-Hyung; Yoon, Seon-A; Ham, Young-Min; Yoon, Weon-Jong; Cho, Ju-Hyun; Lee, Ok-Hawn

2017-09-25

Ultraviolet (UV) radiation stimulates the expression of matrix metalloproteinases (MMPs) and inflammatory cytokines. These signaling pathways participate in the degradation of the extracellular matrix and induce inflammatory responses that lead to photoaging. This study evaluated the antioxidant activity and the effect on MMPs and procollagen of putgyul extract in vitro. The anti-photoaging activity of putgyul extracts was estimated in vivo using hairless mice (HR-1). The putgyul extracts reduced MMP-1 production and increased the content of procollagen type I carboxy-terminal peptide in human dermal fibroblasts. Ultravilot-B (UVB)-induced expression of inflammatory cytokines and MMPs was detected in mice, and putgyul extracts suppressed the expression. These results suggest that putgyul extract inhibits photoaging by inhibiting the expression of MMPs that degrade collagen and inhibiting cytokines that induce inflammatory responses. The mouse model also demonstrated that oral administration of putgyul extracts decreased wrinkle depth, epidermal thickness, collagen degradation, and trans-epidermal water loss, and increased β-glucosidase activity on UVB exposed skin. Putgyul extract protects against UVB-induced damage of skin and could be valuable in the prevention of photoaging.

Anti-Photoaging Effect of Jeju Putgyul (Unripe Citrus) Extracts on Human Dermal Fibroblasts and Ultraviolet B-induced Hairless Mouse Skin

PubMed Central

Choi, Seung-Hyun; Choi, Sun-Il; Jung, Tae-Dong; Cho, Bong-Yeon; Lee, Jin-Ha; Kim, Seung-Hyung; Yoon, Seon-A; Ham, Young-Min; Yoon, Weon-Jong; Cho, Ju-Hyun; Lee, Ok-Hawn

2017-01-01

Ultraviolet (UV) radiation stimulates the expression of matrix metalloproteinases (MMPs) and inflammatory cytokines. These signaling pathways participate in the degradation of the extracellular matrix and induce inflammatory responses that lead to photoaging. This study evaluated the antioxidant activity and the effect on MMPs and procollagen of putgyul extract in vitro. The anti-photoaging activity of putgyul extracts was estimated in vivo using hairless mice (HR-1). The putgyul extracts reduced MMP-1 production and increased the content of procollagen type I carboxy-terminal peptide in human dermal fibroblasts. Ultravilot-B (UVB)-induced expression of inflammatory cytokines and MMPs was detected in mice, and putgyul extracts suppressed the expression. These results suggest that putgyul extract inhibits photoaging by inhibiting the expression of MMPs that degrade collagen and inhibiting cytokines that induce inflammatory responses. The mouse model also demonstrated that oral administration of putgyul extracts decreased wrinkle depth, epidermal thickness, collagen degradation, and trans-epidermal water loss, and increased β-glucosidase activity on UVB exposed skin. Putgyul extract protects against UVB-induced damage of skin and could be valuable in the prevention of photoaging. PMID:28946661

Bioleaching of zinc and manganese from spent Zn-Mn batteries and mechanism exploration.

PubMed

Xin, Baoping; Jiang, Wenfeng; Aslam, Hina; Zhang, Kai; Liu, Changhao; Wang, Renqing; Wang, Yutao

2012-02-01

In this work, bioleaching was used to extract valuable Zn and Mn from spent Zn-Mn batteries. The results showed that 96% of Zn extraction was achieved within 24h regardless of energy source types and bioleaching bacteria species. However, initial pH had a remarkable influence on Zn release, extraction dose sharply decreased from 2200 to 500mg/l when the initial pH value increased from 1.5 to 3.0 or higher. In contrast to Zn, all the tested factors evidently affected Mn extraction; the maximum released dose of 3020mg/l was obtained under the optimum conditions. The acidic dissolution by biogenic H(2)SO(4) by the non-contact mechanism was responsible for Zn extraction, while Mn extraction was owed to both contact/biological and non-contact mechanisms. The combined action of acidic dissolution of soluble Mn(2+) by biogenic H(2)SO(4) and reductive dissolution of insoluble Mn(4+) by Fe(2+) resulted in 60% of Mn extraction, while contact of microbial cells with the spent battery material and incubation for more than 7days was required to achieve the maximum extraction of Mn. Copyright © 2011 Elsevier Ltd. All rights reserved.

Proton chemical shift tensors determined by 3D ultrafast MAS double-quantum NMR spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Rongchun; Mroue, Kamal H.; Ramamoorthy, Ayyalusamy

2015-10-01

Proton NMR spectroscopy in the solid state has recently attracted much attention owing to the significant enhancement in spectral resolution afforded by the remarkable advances in ultrafast magic angle spinning (MAS) capabilities. In particular, proton chemical shift anisotropy (CSA) has become an important tool for obtaining specific insights into inter/intra-molecular hydrogen bonding. However, even at the highest currently feasible spinning frequencies (110-120 kHz), 1H MAS NMR spectra of rigid solids still suffer from poor resolution and severe peak overlap caused by the strong 1H-1H homonuclear dipolar couplings and narrow 1H chemical shift (CS) ranges, which render it difficult to determine the CSA of specific proton sites in the standard CSA/single-quantum (SQ) chemical shift correlation experiment. Herein, we propose a three-dimensional (3D) 1H double-quantum (DQ) chemical shift/CSA/SQ chemical shift correlation experiment to extract the CS tensors of proton sites whose signals are not well resolved along the single-quantum chemical shift dimension. As extracted from the 3D spectrum, the F1/F3 (DQ/SQ) projection provides valuable information about 1H-1H proximities, which might also reveal the hydrogen-bonding connectivities. In addition, the F2/F3 (CSA/SQ) correlation spectrum, which is similar to the regular 2D CSA/SQ correlation experiment, yields chemical shift anisotropic line shapes at different isotropic chemical shifts. More importantly, since the F2/F1 (CSA/DQ) spectrum correlates the CSA with the DQ signal induced by two neighboring proton sites, the CSA spectrum sliced at a specific DQ chemical shift position contains the CSA information of two neighboring spins indicated by the DQ chemical shift. If these two spins have different CS tensors, both tensors can be extracted by numerical fitting. We believe that this robust and elegant single-channel proton-based 3D experiment provides useful atomistic-level structural and dynamical information for a variety of solid systems that possess high proton density.

Proton chemical shift tensors determined by 3D ultrafast MAS double-quantum NMR spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Rongchun; Mroue, Kamal H.; Ramamoorthy, Ayyalusamy, E-mail: ramamoor@umich.edu

2015-10-14

Proton NMR spectroscopy in the solid state has recently attracted much attention owing to the significant enhancement in spectral resolution afforded by the remarkable advances in ultrafast magic angle spinning (MAS) capabilities. In particular, proton chemical shift anisotropy (CSA) has become an important tool for obtaining specific insights into inter/intra-molecular hydrogen bonding. However, even at the highest currently feasible spinning frequencies (110–120 kHz), {sup 1}H MAS NMR spectra of rigid solids still suffer from poor resolution and severe peak overlap caused by the strong {sup 1}H–{sup 1}H homonuclear dipolar couplings and narrow {sup 1}H chemical shift (CS) ranges, which rendermore » it difficult to determine the CSA of specific proton sites in the standard CSA/single-quantum (SQ) chemical shift correlation experiment. Herein, we propose a three-dimensional (3D) {sup 1}H double-quantum (DQ) chemical shift/CSA/SQ chemical shift correlation experiment to extract the CS tensors of proton sites whose signals are not well resolved along the single-quantum chemical shift dimension. As extracted from the 3D spectrum, the F1/F3 (DQ/SQ) projection provides valuable information about {sup 1}H–{sup 1}H proximities, which might also reveal the hydrogen-bonding connectivities. In addition, the F2/F3 (CSA/SQ) correlation spectrum, which is similar to the regular 2D CSA/SQ correlation experiment, yields chemical shift anisotropic line shapes at different isotropic chemical shifts. More importantly, since the F2/F1 (CSA/DQ) spectrum correlates the CSA with the DQ signal induced by two neighboring proton sites, the CSA spectrum sliced at a specific DQ chemical shift position contains the CSA information of two neighboring spins indicated by the DQ chemical shift. If these two spins have different CS tensors, both tensors can be extracted by numerical fitting. We believe that this robust and elegant single-channel proton-based 3D experiment provides useful atomistic-level structural and dynamical information for a variety of solid systems that possess high proton density.« less

Modified sequential extraction for biochar and petroleum coke: Metal release potential and its environmental implications.

PubMed

von Gunten, Konstantin; Alam, Md Samrat; Hubmann, Magdalena; Ok, Yong Sik; Konhauser, Kurt O; Alessi, Daniel S

2017-07-01

A modified Community Bureau of Reference (CBR) sequential extraction method was tested to assess the composition of untreated pyrogenic carbon (biochar) and oil sands petroleum coke. Wood biochar samples were found to contain lower concentrations of metals, but had higher fractions of easily mobilized alkaline earth and transition metals. Sewage sludge biochar was determined to be less recalcitrant and had higher total metal concentrations, with most of the metals found in the more resilient extraction fractions (oxidizable, residual). Petroleum coke was the most stable material, with a similar metal distribution pattern as the sewage sludge biochar. The applied sequential extraction method represents a suitable technique to recover metals from these materials, and is a valuable tool in understanding the metal retaining and leaching capability of various biochar types and carbonaceous petroleum coke samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Crocus sativus Petals: Waste or Valuable Resource? The Answer of High-Resolution and High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance.

PubMed

Righi, Valeria; Parenti, Francesca; Tugnoli, Vitaliano; Schenetti, Luisa; Mucci, Adele

2015-09-30

Intact Crocus sativus petals were studied for the first time by high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy, revealing the presence of kinsenoside (2) and goodyeroside A (3), together with 3-hydroxy-γ-butyrolactone (4). These findings were confirmed by HR-NMR analysis of the ethanol extract of fresh petals and showed that, even though carried out rapidly, partial hydrolysis of glucopyranosyloxybutanolides occurs during extraction. On the other hand, kaempferol 3-O-sophoroside (1), which is "NMR-silent" in intact petals, is present in extracts. These results suggest to evaluate the utilization of saffron petals for phytopharmaceutical and nutraceutical purposes to exploit a waste product of massive production of commercial saffron and point to the application of HR-MAS NMR for monitoring bioactive compounds directly on intact petals, avoiding the extraction procedure and the consequent hydrolysis reaction.

Standardization of immunotherapy adverse events in patient information leaflets and development of an interface terminology for outpatients' monitoring.

PubMed

Zini, E M; Lanzola, G; Quaglini, S; Cornet, R

2018-01-01

Immunotherapy is effective for treating cancer, but it is also associated with a wide spectrum of adverse events. In order to detect them early, the patients need to be monitored at home, between the therapy administrations, e.g., by asking them to report outcomes, usually including symptoms and quality of life measures. For the collected data to be reusable, the symptoms need to be in a standardized form. The aim of this study is to explore the standardization of the information contained in the patient information leaflets (PILs) of immunotherapy drugs, by creating an interface terminology of immunotherapy-related adverse events, which should support a consistent collection of symptoms from the patients. PILs contain a significant amount of information in free text, but they mix patient-reportable and clinically assessable events. We extracted a list of patient-reportable adverse events, mapped them to reference terminologies and compared the mapping results to choose the best-performing reference terminology. The PILs standardization led to the extraction of 151 symptoms and 424 terms, including both preferred terms and synonyms in English and Italian. Among the reference terminologies we considered, SNOMED CT allowed us to map all concepts and became, hence, the main reference terminology for the resulting interface terminology. A preliminary validation on the PIL of a new immunotherapy drug showed that our interface terminology already contained all the mentioned symptoms. PILs provide a valuable source for determining adverse events. The resulting interface terminology includes Italian and English terms for patient-reportable adverse events for five immunotherapy drugs representative of their category. Further work will be undertaken to evaluate the usability of the interface terminology and the patients' experience and satisfaction with the proposed terms, made available for example through an app, as well as its effectiveness on data quality and quality of care. Copyright © 2017 Elsevier Inc. All rights reserved.

Extraction of manganese by alkyl monocarboxylic acid in a mixed extractant from a leaching solution of spent lithium-ion battery ternary cathodic material

NASA Astrophysics Data System (ADS)

Joo, Sung-Ho; Shin, Dongju; Oh, ChangHyun; Wang, Jei-Pil; Shin, Shun Myung

2016-02-01

We investigate the separation of manganese by an antagonistic effect from a leaching solution of ternary cathodic material of spent lithium-ion batteries that contain 11,400 mg L-1 Co, 11,700 mg L-1 Mn, 12,200 mg L-1 Ni, and 5300 mg L-1 Li using a mixture of alkyl monocarboxylic acid and di-(2-ethylhexyl)phosphoric acid extractants. pH isotherm, distribution coefficient, separation factor, McCabe-Thiele diagram, selective scrubbing, and countercurrent extraction tests are carried out to prove an antagonistic effect and to recover manganese using alkyl monocarboxylic in the mixed extractant. Slope analysis is used to determine the extraction mechanism between a mixture of extractants and valuable metals. An increasing concentration of alkyl monocarboxylic acid in the mixture of extractants results in a decrease in distribution coefficient of cobalt and manganese, however, the separation factor value (β(Mn/Co)) increases at pH 4.5. This is caused by slope analysis where alkyl monocarboxylic acid disrupts the extraction mechanism between di-(2-ethylhexyl)phosphoric acid and cobalt. Finally, continuous countercurrent extraction in a mini-plant test demonstrate the feasibility of manganese recovery from cobalt, nickel, and lithium.

Assessing the Value of Post-processed State-of-the-art Long-term Weather Forecast Ensembles within An Integrated Agronomic Modelling Framework

NASA Astrophysics Data System (ADS)

LI, Y.; Castelletti, A.; Giuliani, M.

2014-12-01

Over recent years, long-term climate forecast from global circulation models (GCMs) has been demonstrated to show increasing skills over the climatology, thanks to the advances in the modelling of coupled ocean-atmosphere dynamics. Improved information from long-term forecast is supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping time) and for more effectively coping with the adverse impacts of climate variability. Yet, evaluating how valuable this information can be is not straightforward and farmers' response must be taken into consideration. Indeed, while long-range forecast are traditionally evaluated in terms of accuracy by comparison of hindcast and observed values, in the context of agricultural systems, potentially useful forecast information should alter the stakeholders' expectation, modify their decisions and ultimately have an impact on their annual benefit. Therefore, it is more desirable to assess the value of those long-term forecasts via decision-making models so as to extract direct indication of probable decision outcomes from farmers, i.e. from an end-to-end perspective. In this work, we evaluate the operational value of thirteen state-of-the-art long-range forecast ensembles against climatology forecast and subjective prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of farmers' behavior. Collected ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and distributed crop simulation model. The agronomic model is first simulated using the forecast information (ex-ante), followed by a second run with actual climate (ex-post). Multi-year simulations are performed to account for climate variability and the value of the different climate forecast is evaluated against the perfect foresight scenario based on the expected crop productivity as well as the land-use decisions. Our results show that not all the products generate beneficial effects to farmers and that the forecast errors might be amplified by the farmers decisions.

The fibres and polyphenols in sea buckthorn (Hippophaë rhamnoides) extraction residues delay postprandial lipemia.

PubMed

Linderborg, Kaisa M; Lehtonen, Henna-Maria; Järvinen, Riikka; Viitanen, Matti; Kallio, Heikki

2012-06-01

The triacylglycerol (TAG) response to fatty meals containing dried and crushed berries or berry extraction residues was studied in a postprandial cross-over study with healthy normal-weight male volunteers. The berry material included sea buckthorn berries, sea buckthorn CO₂ extraction residue (CO₂-sea buckthorn) and sea buckthorn or black currant CO₂ and ethanol extraction residue (CO₂-EtOH-sea buckthorn, CO₂-EtOH-black currant). Extraction residues were used in order to advance the potential use of valuable side stream components containing polyphenols and fibre as human food. Compared to the berry-depleted control, all berry meals delayed lipemia, whereas there were no differences in the total area under the TAG response curve. The lipemic delay largely derived from the fibre rather than from the polyphenols. Even so, the effect of polyphenols may be complementary since sea buckthorn and CO₂-sea buckthorn showed significant differences in relation to control in a wider range of TAG areas than polyphenol-depleted CO₂-EtOH-sea buckthorn.

IR and Raman studies of oil and seedcake extracts from natural and genetically modified flax seeds

NASA Astrophysics Data System (ADS)

Żuk, M.; Dymińska, L.; Kulma, A.; Boba, A.; Prescha, A.; Szopa, J.; Mączka, M.; Zając, A.; Szołtysek, K.; Hanuza, J.

2011-03-01

Flax plant of the third generation (F3) overexpressing key genes of flavonoid pathway cultivated in field in 2008 season was used as the plant material throughout this study. The biochemical properties of seed, oil and seedcake extracts from natural and transgenic flax plants were compared. Overproduction of flavonoids (kaempferol), phenolic acids (coumaric, ferulic/synapic) and lignan-secoisolariciresinol diglucoside (SDG) in oil and extracts from transgenic seeds has been revealed providing a valuable source of these compounds for biotechnological application. The changes in fatty acids composition and increase in their stability against oxidation along three plant generations were also detected. The analysis of oil and seedcake extracts was performed using Raman and IR spectroscopy. The wavenumbers and integral intensities of Raman and IR bands were used to identify the components of phenylpropanoid pathway in oil and seedcake extracts from control and transgenic flax seeds. The spectroscopic data were compared to those obtained from biochemical analysis.

Applications of artificial intelligence systems in the analysis of epidemiological data.

PubMed

Flouris, Andreas D; Duffy, Jack

2006-01-01

A brief review of the germane literature suggests that the use of artificial intelligence (AI) statistical algorithms in epidemiology has been limited. We discuss the advantages and disadvantages of using AI systems in large-scale sets of epidemiological data to extract inherent, formerly unidentified, and potentially valuable patterns that human-driven deductive models may miss.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

Characterisation of metals in the electronic waste of complex mixtures of end-of-life ICT products for development of cleaner recovery technology.

PubMed

Sun, Z H I; Xiao, Y; Sietsma, J; Agterhuis, H; Visser, G; Yang, Y

2015-01-01

Recycling of valuable metals from electronic waste, especially complex mixtures of end-of-life information and communication technology (ICT) products, is of great difficulty due to their complexity and heterogeneity. One of the important reasons is the lack of comprehensive characterisation on such materials, i.e. accurate compositions, physical/chemical properties. In the present research, we focus on developing methodologies for the characterisation of metals in an industrially processed ICT waste. The morphology, particle size distribution, compositional distribution, occurrence, liberation as well as the thermo-chemical properties of the ICT waste were investigated with various characterisation techniques, including X-ray Fluorescence Spectrometry (XRF), differential scanning calorimetry (DSC) and scanning electron microscopy (SEM) with energy dispersed spectroscopy (EDS). Due to the high heterogeneity of the material, special sample preparation procedures were introduced to minimise the discrepancies during compositional analyses. As a result, a clearer overview of the ICT waste has been reached. This research provides better understanding of the extractability of each metal and improves the awareness of potential obstacles for extraction. It will lead to smarter decisions during further development of a clean and effective recovery process. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tensor-based tracking of the aorta in phase-contrast MR images

NASA Astrophysics Data System (ADS)

Azad, Yoo-Jin; Malsam, Anton; Ley, Sebastian; Rengier, Fabian; Dillmann, Rüdiger; Unterhinninghofen, Roland

2014-03-01

The velocity-encoded magnetic resonance imaging (PC-MRI) is a valuable technique to measure the blood flow velocity in terms of time-resolved 3D vector fields. For diagnosis, presurgical planning and therapy control monitoring the patient's hemodynamic situation is crucial. Hence, an accurate and robust segmentation of the diseased vessel is the basis for further methods like the computation of the blood pressure. In the literature, there exist some approaches to transfer the methods of processing DT-MR images to PC-MR data, but the potential of this approach is not fully exploited yet. In this paper, we present a method to extract the centerline of the aorta in PC-MR images by applying methods from the DT-MRI. On account of this, in the first step the velocity vector fields are converted into tensor fields. In the next step tensor-based features are derived and by applying a modified tensorline algorithm the tracking of the vessel course is accomplished. The method only uses features derived from the tensor imaging without the use of additional morphology information. For evaluation purposes we applied our method to 4 volunteer as well as 26 clinical patient datasets with good results. In 29 of 30 cases our algorithm accomplished to extract the vessel centerline.

Extracting Spatiotemporal Objects from Raster Data to Represent Physical Features and Analyze Related Processes

NASA Astrophysics Data System (ADS)

Zollweg, J. A.

2017-10-01

Numerous ground-based, airborne, and orbiting platforms provide remotely-sensed data of remarkable spatial resolution at short time intervals. However, this spatiotemporal data is most valuable if it can be processed into information, thereby creating meaning. We live in a world of objects: cars, buildings, farms, etc. On a stormy day, we don't see millions of cubes of atmosphere; we see a thunderstorm `object'. Temporally, we don't see the properties of those individual cubes changing, we see the thunderstorm as a whole evolving and moving. There is a need to represent the bulky, raw spatiotemporal data from remote sensors as a small number of relevant spatiotemporal objects, thereby matching the human brain's perception of the world. This presentation reveals an efficient algorithm and system to extract the objects/features from raster-formatted remotely-sensed data. The system makes use of the Python object-oriented programming language, SciPy/NumPy for matrix manipulation and scientific computation, and export/import to the GeoJSON standard geographic object data format. The example presented will show how thunderstorms can be identified and characterized in a spatiotemporal continuum using a Python program to process raster data from NOAA's High-Resolution Rapid Refresh v2 (HRRRv2) data stream.

Metabolite profiling of ginsenosides in rat plasma, urine and feces by LC-MS/MS and its application to a pharmacokinetic study after oral administration of Panax ginseng extract.

PubMed

Dong, Wei-Wei; Han, Xiong-Zhe; Zhao, Jinhua; Zhong, Fei-Liang; Ma, Rui; Wu, Songquan; Li, Donghao; Quan, Lin-Hu; Jiang, Jun

2018-03-01

Panax ginseng is widely consumed as a functional food in the form of tea, powder, capsules, among others, and possesses a range of pharmacological activities including adaptogenic, immune-modulatory, anti-tumor, anti-aging and anti-inflammatory effects. The aim of this study was to identify and quantify the major ginsenosides and their metabolites in rat plasma, urine and feces after administration of P. ginseng extract using LC-MS/MS. We collected rat plasma samples at 0.5, 1, 2, 4, 8, 12, 24 and 48 h, and the amounts of urine and fecal samples accumulated in 24 h. Fourteen major ginsenosides and their metabolites were observed in fecal samples at high levels; however, low levels of 11 ginsenosides were detected in urine samples. The pharmacokinetics of the major ginsenosides and their metabolites was investigated in plasma. The results indicated that the maximum plasma concentration, time to maximum concentration and area under the curve of compound K were significantly greater than those of other ginsenosides. This study thus provides valuable information for drug development and clinical application of P. ginseng. Copyright © 2017 John Wiley & Sons, Ltd.

Development of a simple and sensitive method for the characterization of odorous waste gas emissions by means of solid-phase microextraction (SPME) and GC-MS/olfactometry.

PubMed

Kleeberg, K K; Liu, Y; Jans, M; Schlegelmilch, M; Streese, J; Stegmann, R

2005-01-01

A solid-phase microextraction (SPME) method has been developed for the extraction of odorous compounds from waste gas. The enriched compounds were characterized by gas chromatography-mass spectrometry (GC-MS) and gas chromatography followed by simultaneous flame ionization detection and olfactometry (GC-FID/O). Five different SPME fiber coatings were tested, and the carboxen/polydimethylsiloxane (CAR/PDMS) fiber showed the highest ability to extract odorous compounds from the waste gas. Furthermore, parameters such as exposure time, desorption temperature, and desorption time have been optimized. The SPME method was successfully used to characterize an odorous waste gas from a fat refinery prior to and after waste gas treatment in order to describe the treatment efficiency of the used laboratory scale plant which consisted of a bioscrubber/biofilter combination and an activated carbon adsorber. The developed method is a valuable approach to provide detailed information of waste gas composition and complements existing methods for the determination of odors. However, caution should be exercised if CAR/PDMS fibers are used for the quantification of odorous compounds in multi-component matrices like waste gas emissions since the relative affinity of each analyte was shown to differ according to the total amount of analytes present in the sample.

Seeing is believing: on the use of image databases for visually exploring plant organelle dynamics.

PubMed

Mano, Shoji; Miwa, Tomoki; Nishikawa, Shuh-ichi; Mimura, Tetsuro; Nishimura, Mikio

2009-12-01

Organelle dynamics vary dramatically depending on cell type, developmental stage and environmental stimuli, so that various parameters, such as size, number and behavior, are required for the description of the dynamics of each organelle. Imaging techniques are superior to other techniques for describing organelle dynamics because these parameters are visually exhibited. Therefore, as the results can be seen immediately, investigators can more easily grasp organelle dynamics. At present, imaging techniques are emerging as fundamental tools in plant organelle research, and the development of new methodologies to visualize organelles and the improvement of analytical tools and equipment have allowed the large-scale generation of image and movie data. Accordingly, image databases that accumulate information on organelle dynamics are an increasingly indispensable part of modern plant organelle research. In addition, image databases are potentially rich data sources for computational analyses, as image and movie data reposited in the databases contain valuable and significant information, such as size, number, length and velocity. Computational analytical tools support image-based data mining, such as segmentation, quantification and statistical analyses, to extract biologically meaningful information from each database and combine them to construct models. In this review, we outline the image databases that are dedicated to plant organelle research and present their potential as resources for image-based computational analyses.

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

USGS Publications Warehouse

Wallace, C.S.A.; Marsh, S.E.

2005-01-01

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

76 FR 7121 - Privacy Act of 1974; Proposed Implementation

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-09

... identity of confidential sources and the nature of the information supplied by informants as well as... the information. Confidential sources and informers might refuse to provide valuable information... nature of the information they supplied. Loss of access to such sources would seriously impair the...

a Web-Based Platform for Visualizing Spatiotemporal Dynamics of Big Taxi Data

NASA Astrophysics Data System (ADS)

Xiong, H.; Chen, L.; Gui, Z.

2017-09-01

With more and more vehicles equipped with Global Positioning System (GPS), access to large-scale taxi trajectory data has become increasingly easy. Taxis are valuable sensors and information associated with taxi trajectory can provide unprecedented insight into many aspects of city life. But analysing these data presents many challenges. Visualization of taxi data is an efficient way to represent its distributions and structures and reveal hidden patterns in the data. However, Most of the existing visualization systems have some shortcomings. On the one hand, the passenger loading status and speed information cannot be expressed. On the other hand, mono-visualization form limits the information presentation. In view of these problems, this paper designs and implements a visualization system in which we use colour and shape to indicate passenger loading status and speed information and integrate various forms of taxi visualization. The main work as follows: 1. Pre-processing and storing the taxi data into MongoDB database. 2. Visualization of hotspots for taxi pickup points. Through DBSCAN clustering algorithm, we cluster the extracted taxi passenger's pickup locations to produce passenger hotspots. 3. Visualizing the dynamic of taxi moving trajectory using interactive animation. We use a thinning algorithm to reduce the amount of data and design a preloading strategyto load the data smoothly. Colour and shape are used to visualize the taxi trajectory data.

Sequential Super-Resolution Imaging of Bacterial Regulatory Proteins: The Nucleoid and the Cell Membrane in Single, Fixed E. coli Cells.

PubMed

Spahn, Christoph; Glaesmann, Mathilda; Gao, Yunfeng; Foo, Yong Hwee; Lampe, Marko; Kenney, Linda J; Heilemann, Mike

2017-01-01

Despite their small size and the lack of compartmentalization, bacteria exhibit a striking degree of cellular organization, both in time and space. During the last decade, a group of new microscopy techniques emerged, termed super-resolution microscopy or nanoscopy, which facilitate visualizing the organization of proteins in bacteria at the nanoscale. Single-molecule localization microscopy (SMLM) is especially well suited to reveal a wide range of new information regarding protein organization, interaction, and dynamics in single bacterial cells. Recent developments in click chemistry facilitate the visualization of bacterial chromatin with a resolution of ~20 nm, providing valuable information about the ultrastructure of bacterial nucleoids, especially at short generation times. In this chapter, we describe a simple-to-realize protocol that allows determining precise structural information of bacterial nucleoids in fixed cells, using direct stochastic optical reconstruction microscopy (dSTORM). In combination with quantitative photoactivated localization microscopy (PALM), the spatial relationship of proteins with the bacterial chromosome can be studied. The position of a protein of interest with respect to the nucleoids and the cell cylinder can be visualized by super-resolving the membrane using point accumulation for imaging in nanoscale topography (PAINT). The combination of the different SMLM techniques in a sequential workflow maximizes the information that can be extracted from single cells, while maintaining optimal imaging conditions for each technique.

LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise.

PubMed

Mantini, Dante; Petrucci, Francesca; Pieragostino, Damiana; Del Boccio, Piero; Di Nicola, Marta; Di Ilio, Carmine; Federici, Giorgio; Sacchetta, Paolo; Comani, Silvia; Urbani, Andrea

2007-03-26

Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances. LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples. The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.

Measuring the intangibles: a metrics for the economic complexity of countries and products.

PubMed

Cristelli, Matthieu; Gabrielli, Andrea; Tacchella, Andrea; Caldarelli, Guido; Pietronero, Luciano

2013-01-01

We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation.

Analysis on Time-Lag Effect of Research and Development Investment in the Pharmaceutical Industry in Korea

PubMed Central

Lee, Munjae; Choi, Mankyu

2015-01-01

Objectives The aim of this study is to analyze the influence of the research and development (R&D) investment of pharmaceutical companies on enterprise value. Methods The period of the empirical analysis is from 2000 to 2012, considering the period after the influence of the financial crisis. Financial statements and comments in general and internal transactions were extracted from TS-2000 of the Korea Listed Company Association, and data related to stock price were extracted from KISVALUE-III of National Information and Credit Evaluation Information Service Co., Ltd. STATA 12.0 was used as the statistical package for panel analysis. Results In the pharmaceutical firms, the influence of the R&D intensity with regard to Tobin's q was found to be positive. However, only the R&D expenditure intensities of previous years 2 and 5 (t–2 and t–5, respectively) were statistically significant (p < 0.1), whereas those of previous years 1, 3, and 4 years (t–1, t–3, and t–4, respectively) were not statistically significant. Conclusion R&D investment not only affects the enterprise value but is also evaluated as an investment activity that raises the long-term enterprise value. The research findings will serve as valuable data to understand the enterprise value of the Korea pharmaceutical industry and to strengthen reform measures. Not only should new drug development be made, but also investment and support should be provided according to the specific factors suitable to improve the competitiveness of each company, such as generic, incrementally modified drugs, and biosimilar products. PMID:26473091

Analysis on Time-Lag Effect of Research and Development Investment in the Pharmaceutical Industry in Korea.

PubMed

Lee, Munjae; Choi, Mankyu

2015-08-01

The aim of this study is to analyze the influence of the research and development (R&D) investment of pharmaceutical companies on enterprise value. The period of the empirical analysis is from 2000 to 2012, considering the period after the influence of the financial crisis. Financial statements and comments in general and internal transactions were extracted from TS-2000 of the Korea Listed Company Association, and data related to stock price were extracted from KISVALUE-III of National Information and Credit Evaluation Information Service Co., Ltd. STATA 12.0 was used as the statistical package for panel analysis. In the pharmaceutical firms, the influence of the R&D intensity with regard to Tobin's q was found to be positive. However, only the R&D expenditure intensities of previous years 2 and 5 (t-2 and t-5, respectively) were statistically significant (p < 0.1), whereas those of previous years 1, 3, and 4 years (t-1, t-3, and t-4, respectively) were not statistically significant. R&D investment not only affects the enterprise value but is also evaluated as an investment activity that raises the long-term enterprise value. The research findings will serve as valuable data to understand the enterprise value of the Korea pharmaceutical industry and to strengthen reform measures. Not only should new drug development be made, but also investment and support should be provided according to the specific factors suitable to improve the competitiveness of each company, such as generic, incrementally modified drugs, and biosimilar products.

Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products

PubMed Central

Cristelli, Matthieu; Gabrielli, Andrea; Tacchella, Andrea; Caldarelli, Guido; Pietronero, Luciano

2013-01-01

We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation. PMID:23940633

454-pyrosequencing: A tool for discovery and biomarker development

USDA-ARS?s Scientific Manuscript database

The Roche GS-FLX (454) sequencer has made possible what was thought impossible just a few years ago: sequence >1 million high-quality nucleotide reads (mean 400 bp) in less than 12 h. This technology provides valuable species-specific sequence information, and is a valuable tool to discover and und...

In vitro antileishmanial activity of Mexican medicinal plants.

PubMed

Delgado-Altamirano, Ronna; Monzote, Lianet; Piñón-Tápanes, Abel; Vibrans, Heike; Rivero-Cruz, J Fausto; Ibarra-Alvarado, César; Rojas-Molina, Alejandra

2017-09-01

To evaluate the anti-leishmanial activity and cytotoxicity of aqueous and organic extracts of ten plants used in Mexican traditional medicine as anti-parasitics. For the organic extracts, plant material was macerated in dichloromethane (CH 2 Cl 2 ) and dichloromethane/methanol (CH 2 Cl 2 /MeOH) (1:1) during two weeks; the aqueous extracts were prepared by infusion. The extracts were tested against promastigotes and intracellular amastigotes of Leishmania amazonensis . The cytotoxicity was assayed in parallel on peritoneal macrophages of BALB/c mice. Four of the thirty extracts tested were active and selective against L. amazonensis promastigotes: Schinus molle (CH 2 Cl 2 and CH 2 Cl 2 /MeOH), Lantana camara (CH 2 Cl 2 ) and Prosopis laevigata (aqueous). These extracts had a median inhibitory concentration (IC 50 ) against intracellular amastigotes under 50 μg/mL and a selectivity index (SI) higher than 5, which indicates that they constitute valuable candidates to obtain secondary metabolites with leishmanicidal activity. The results derived from this study indicate that L. camara, P. laevigata, and S. molle might provide interesting new leads for the development of antileishmanial drugs.

Antifungal activity of medicinal plant extracts; preliminary screening studies.

PubMed

Webster, Duncan; Taschereau, Pierre; Belland, René J; Sand, Crystal; Rennie, Robert P

2008-01-04

In the setting of HIV and organ transplantation, opportunistic fungal infections have become a common cause of morbidity and mortality. Thus antifungal therapy is playing a greater role in health care. Traditional plants are a valuable source of novel antifungals. To assess in vitro antifungal activity of aqueous plant extracts. The minimum inhibitory concentrations were determined for each extract in the setting of human pathogenic fungal isolates. Plants were harvested and identification verified. Aqueous extracts were obtained and antifungal susceptibilities determined using serial dilutional extracts with a standardized microdilution broth methodology. Twenty-three fungal isolates were cultured and exposed to the plant extracts. Five known antifungals were used as positive controls. Results were read at 48 and 72 h. Of the 14 plants analyzed, Fragaria virginiana Duchesne, Epilobium angustifolium L. and Potentilla simplex Michx. demonstrated strong antifungal potential overall. Fragaria virginiana had some degree of activity against all of the fungal pathogens. Alnus viridis DC., Betula alleghaniensis Britt. and Solidago gigantea Ait. also demonstrated a significant degree of activity against many of the yeast isolates. Fragaria virginiana, Epilobium angustifolium and Potentilla simplex demonstrate promising antifungal potential.

[Application of regular expression in extracting key information from Chinese medicine literatures about re-evaluation of post-marketing surveillance].

PubMed

Wang, Zhifei; Xie, Yanming; Wang, Yongyan

2011-10-01

Computerizing extracting information from Chinese medicine literature seems more convenient than hand searching, which could simplify searching process and improve the accuracy. However, many computerized auto-extracting methods are increasingly used, regular expression is so special that could be efficient for extracting useful information in research. This article focused on regular expression applying in extracting information from Chinese medicine literature. Two practical examples were reported in this article about regular expression to extract "case number (non-terminology)" and "efficacy rate (subgroups for related information identification)", which explored how to extract information in Chinese medicine literature by means of some special research method.

Effect of censoring trace-level water-quality data on trend-detection capability

USGS Publications Warehouse

Gilliom, R.J.; Hirsch, R.M.; Gilroy, E.J.

1984-01-01

Monte Carlo experiments were used to evaluate whether trace-level water-quality data that are routinely censored (not reported) contain valuable information for trend detection. Measurements are commonly censored if they fall below a level associated with some minimum acceptable level of reliability (detection limit). Trace-level organic data were simulated with best- and worst-case estimates of measurement uncertainty, various concentrations and degrees of linear trend, and different censoring rules. The resulting classes of data were subjected to a nonparametric statistical test for trend. For all classes of data evaluated, trends were most effectively detected in uncensored data as compared to censored data even when the data censored were highly unreliable. Thus, censoring data at any concentration level may eliminate valuable information. Whether or not valuable information for trend analysis is, in fact, eliminated by censoring of actual rather than simulated data depends on whether the analytical process is in statistical control and bias is predictable for a particular type of chemical analyses.

Phytochemical Composition and Antioxidant Activities of Dianthus Thunbergii Hooper and Hypoxis Argentea Harv Ex Baker: Plants Used for the Management of Diabetes Mellitus in Eastern Cape, South Africa

PubMed Central

Akinrinde, Akinleye Stephen; Afolayan, Anthony Jide; Bradley, Graeme

2018-01-01

Background: Inhabitants of the Eastern Cape Province of South Africa use the roots of Dianthus thunbergii and corms of Hypoxis argentea to treat diabetes mellitus and other ailments. Objective: The objective of this study was to analyze the phytochemical composition and antioxidant activities of the aqueous and ethanol extracts of the roots and corms of two plants. Materials and Methods: Total phenolics, flavonoids, flavonols, proanthocyanidins, tannins, and alkaloids were determined by standard methods. The scavenging activities of the extracts against 1,1 diphenyl-2-picrylhydrazyl (DPPH), 2'-azino-bis (3-ethylbenthiazoline-6-sulfonic acid (ABTS), nitric oxide (NO), hydrogen peroxide (H2O2), and their ferric-reducing antioxidant potentials (FRAPs) were measured. Results: The ethanol extract of H. argentea had the highest content of phenolics (66.71 ± 2.71 mg gallic acid equivalent/g) and tannins (1.18 ± 0.07 mg TAE/g), while the ethanol extract of D. thunbergii gave higher contents of flavonoids and proanthocyanidins (62.21 ± 1.75 mg Qe/g and 432.62 ± 2.43 mg Ca/g, respectively). Flavonols were the most predominant in the aqueous extract of H. argentea (25.51 ± 1.92 mg Qe/g). We observed a concentration-dependent response in the ABTS- and H2O2-scavenging activities and FRAP values of the extracts and standards (Vitamin C, butylated hydroxytoluene, and rutin). The ethanol extracts of both plants generally demonstrated better antioxidant activities against H2O2, NO, and ABTS while also possessing better reducing power than the aqueous extracts. The aqueous extract of D. thunbergii, however, showed the best DPPH scavenging activity. Conclusion: The higher content of phytochemicals and antioxidant capacity obtained for the ethanol extracts of D. thunbergii and H. argentea may prove to be valuable information in selecting suitable extraction solvents for the medicinal applications of both plants. SUMMARY Ethanol extracts of Hypoxis argentea had the highest levels of phenolics and tanninsEthanol extracts of Dianthus thunbergii had the highest levels of flavonoids and proanthocyanidinsEthanol extracts of both plants possess better antioxidant activityagainst hydrogen peroxide, nitric oxide, and ABTS as well as higher reducingpower than the aqueous extractsAqueous extract of Dianthus thunbergii had the highest free radical scavenging activity as measured with DPPH. Abbreviations used: ABTS: 2'-azino-bis (3-ethylbenthiazoline-6-sulfonic acid); BHT: Butylated hydroxytoluene; DPPH: 1,1 diphenyl-2-picrylhydrazyl; DTA: Dianthus thunbergii aqueous extract (16.6%); DTE: Dianthus thunbergii ethanol extract (2.4%); Fe3+-TPTZ: Ferric tripyridyltriazine; FRAP: Ferric-reducing antioxidant potentials; GAE: Gallic acid equivalent; HAA: Hypoxis argentea aqueous extract (3.2%); HAE: Hypoxis argentea ethanol extract (1.8%); Qe: Quercetin equivalence; ROS: Reactive oxygen species; TBA: Thiobarbituric acid;TCA: Trichloroacetic acid. PMID:29720831

Anti-inflammatory and antioxidative effects of Camellia oleifera Abel components.

PubMed

Xiao, Xiaomei; He, Liangmei; Chen, Yayun; Wu, Longhuo; Wang, Lin; Liu, Zhiping

2017-11-01

Camellia oleifera Abel is a member of Camellia, and its seeds are used to extract Camellia oil, which is generally used as cooking oil in the south of China. Camellia oil consists of unsaturated fatty acids, tea polyphenol, squalene, saponin, carrot element and vitamins, etc. The seed remains after oil extraction of C. oleifera Abel are by-products of oil production, named as Camellia oil cake. Its extracts contain bioactive compounds including sasanquasaponin, flavonoid and tannin. Major components from Camellia oil and its cake have been shown to have anti-inflammatory, antioxidative, antimicrobial and antitumor activities. In this review, we will summarize the latest advance in the studies on anti-inflammatory or antioxidative effects of C. oleifera products, thus providing valuable reference for the future research and development of C. oleifera Abel.

Combining polar organic chemical integrative samplers (POCIS) with toxicity testing to evaluate pesticide mixture effects on natural phototrophic biofilms.

PubMed

Pesce, Stéphane; Morin, Soizic; Lissalde, Sophie; Montuelle, Bernard; Mazzella, Nicolas

2011-03-01

Polar organic chemical integrative samplers (POCIS) are valuable tools in passive sampling methods for monitoring polar organic pesticides in freshwaters. Pesticides extracted from the environment using such methods can be used to toxicity tests. This study evaluated the acute effects of POCIS extracts on natural phototrophic biofilm communities. Our results demonstrate an effect of POCIS pesticide mixtures on chlorophyll a fluorescence, photosynthetic efficiency and community structure. Nevertheless, the range of biofilm responses differs according to origin of the biofilms tested, revealing spatial variations in the sensitivity of natural communities in the studied stream. Combining passive sampler extracts with community-level toxicity tests offers promising perspectives for ecological risk assessment. Copyright © 2010 Elsevier Ltd. All rights reserved.

Extraction and characterization of beta-D-glucan from oat for industrial utilization.

PubMed

Ahmad, Asif; Anjum, Faqir Muhammad; Zahoor, Tahir; Nawaz, Haq; Ahmed, Zaheer

2010-04-01

Oat beta-D-glucan is a valuable functional ingredient having numerous industrial, nutritional and health benefits. Its extraction needs careful attention as extraction process may affect the physiochemical and functional properties of extracted beta-D-glucan. The present study aimed at analyzing the effect of extraction of beta-D-glucan gum pellets from oat cultivar followed by detailed chemical and functional analysis. Enzymatic extraction process resulted in highest yield and recovery. Chemical analysis revealed protein as a dominating impurity. The water binding capacity of the beta-D-glucan ranged between 3.14 and 4.52 g g(-1) of sample. beta-D-Glucan exhibited ideal foaming stability when appropriate extraction technique was used. The viscosity of beta-D-glucan gum ranged between 35.6 and 56.16 cp. The color analysis showed L* value of beta-D-glucan gum pellet ranged between 72.18 and 83.54. Phosphorus, potassium and calcium appeared as major minerals in beta-D-glucan gum whereas iron, manganese and copper appeared as minor minerals. FTIR spectroscopy also confirms the presence of beta-D-glucan, protein and other components in extracted beta-D-glucan gum pellets. Overall, extracted beta-D-glucan showed a good potential for industrial usage. Copyright 2010 Elsevier B.V. All rights reserved.

Challenges in Managing Information Extraction

ERIC Educational Resources Information Center

Shen, Warren H.

2009-01-01

This dissertation studies information extraction (IE), the problem of extracting structured information from unstructured data. Example IE tasks include extracting person names from news articles, product information from e-commerce Web pages, street addresses from emails, and names of emerging music bands from blogs. IE is all increasingly…

Antioxidant, genotoxic and antigenotoxic activities of daphne gnidium leaf extracts

PubMed Central

2012-01-01

Background Plants play a significant role in maintaining human health and improving the quality of human life. They serve humans well as valuable components of food, as well as in cosmetics, dyes, and medicines. In fact, many plant extracts prepared from plants have been shown to exert biological activity in vitro and in vivo. The present study explored antioxidant and antigenotoxic effects of Daphne gnidium leaf extracts. Methods The genotoxic potential of petroleum ether, chloroform, ethyl acetate, methanol and total oligomer flavonoid (TOF) enriched extracts from leaves of Daphne gnidium, was assessed using Escherichia coli PQ37. Likewise, the antigenotoxicity of the same extracts was tested using the “SOS chromotest test”. Antioxidant activities were studied using non enzymatic and enzymatic method: NBT/Riboflavine and xantine oxidase. Results None of the different extracts produced a genotoxic effect, except TOF extract at the lowest tested dose. Our results showed that D. gnidium leaf extracts possess an antigenotoxic effect against the nitrofurantoin a mutagen of reference. Ethyl acetate and TOF extracts were the most effective in inhibiting xanthine oxidase activity. While, methanol extract was the most potent superoxide scavenger when tested with the NBT/Riboflavine assay. Conclusions The present study has demonstrated that D. gnidium leaf extract possess antioxidant and antigenotoxic effects. These activities could be ascribed to compounds like polyphenols and flavonoid. Further studies are required to isolate the active molecules. PMID:22974481

Massive parallel 3D PIC simulation of negative ion extraction

NASA Astrophysics Data System (ADS)

Revel, Adrien; Mochalskyy, Serhiy; Montellano, Ivar Mauricio; Wünderlich, Dirk; Fantz, Ursel; Minea, Tiberiu

2017-09-01

The 3D PIC-MCC code ONIX is dedicated to modeling Negative hydrogen/deuterium Ion (NI) extraction and co-extraction of electrons from radio-frequency driven, low pressure plasma sources. It provides valuable insight on the complex phenomena involved in the extraction process. In previous calculations, a mesh size larger than the Debye length was used, implying numerical electron heating. Important steps have been achieved in terms of computation performance and parallelization efficiency allowing successful massive parallel calculations (4096 cores), imperative to resolve the Debye length. In addition, the numerical algorithms have been improved in terms of grid treatment, i.e., the electric field near the complex geometry boundaries (plasma grid) is calculated more accurately. The revised model preserves the full 3D treatment, but can take advantage of a highly refined mesh. ONIX was used to investigate the role of the mesh size, the re-injection scheme for lost particles (extracted or wall absorbed), and the electron thermalization process on the calculated extracted current and plasma characteristics. It is demonstrated that all numerical schemes give the same NI current distribution for extracted ions. Concerning the electrons, the pair-injection technique is found well-adapted to simulate the sheath in front of the plasma grid.

Determination of ethyl glucuronide in hair: a rapid sample pretreatment involving simultaneous milling and extraction.

PubMed

Mönch, Bettina; Becker, Roland; Nehls, Irene

2014-01-01

A combination of simultaneous milling and extraction known as micropulverized extraction was developed for the quantification of the alcohol marker ethyl glucuronide (EtG) in hair samples using a homogeneous reference material and a mixer mill. Best extraction results from 50 mg of hair were obtained with 2-mL plastic tubes containing two steel balls (∅ = 5 mm), 0.5 mL of water and with an oscillating frequency of 30 s(-1) over a period of 30 min. EtG was quantified employing a validated GC-MS procedure involving derivatization with pentafluoropropionic acid anhydride. This micropulverization procedure was compared with dry milling followed by separate aqueous extraction and with aqueous extraction after manual cutting to millimeter-size snippets. Micropulverization yielded 28.0 ± 1.70 pg/mg and was seen to be superior to manually cutting (23.0 ± 0.83 pg/mg) and equivalent to dry grinding (27.7 ± 1.71 pg/mg) with regard to completeness of EtG extraction. The option to process up to 20 samples simultaneously makes micropulverization especially valuable for the high throughput of urgent samples.

Identification of the NADPH Oxidase 4 Inhibiting Principle of Lycopus europaeus.

PubMed

Revoltella, Silvia; Baraldo, Giorgia; Waltenberger, Birgit; Schwaiger, Stefan; Kofler, Philipp; Moesslacher, Julia; Huber-Seidel, Astrid; Pagitz, Konrad; Kohl, Roland; Jansen-Duerr, Pidder; Stuppner, Hermann

2018-03-14

NADPH oxidase 4 (Nox4) has recently been implicated as driving force in cellular senescence. Thus, there is growing interest to develop Nox4 inhibitors, which might be valuable agents for cosmeceutical applications. Alpine plants represent a valuable source for the identification of novel bioactive natural products with anti-ageing effects, especially substances that protect plants against UV radiation, which is also known to contribute to the ageing of human skin. Therefore, the aim of this study was to identify novel Nox4 inhibitors from alpine plants. Within an initial screening of extracts of alpine plants on their ability to inhibit Nox4 activity in HEK cells, the methanolic extract of the subaerial parts of Lycopus europaeus showed a strong inhibition of Nox4 (81% chemiluminescence quenching) and a simultaneously high cell viability (91% vitality). Rosmarinic acid was isolated and identified as the major compound in this bioactive extract. It showed a dose dependent inhibitory activity on Nox4 with an IC 50 of 1 µM. Moreover, it also showed a significant inhibitory activity on Nox2 in the low micromolar range, whereas no inhibition of Nox5 was detected. Further investigations confirmed that the observed effects of rosmarinic acid on Nox2 and Nox4 are real inhibitory activities, and not due to ROS scavenging effects. Therefore, L. europaeus , which we demonstrated to be a good source of rosmarinic acid, has great potential for usage in cosmeceutical products with anti-ageing activity.

Investigation of Acidithiobacillus ferrooxidans in pure and mixed-species culture for bioleaching of Theisen sludge from former copper smelting.

PubMed

Klink, C; Eisen, S; Daus, B; Heim, J; Schlömann, M; Schopf, S

2016-06-01

The aim of this study was to investigate the potential of bioleaching for the treatment of an environmentally hazardous waste, a blast-furnace flue dust designated Theisen sludge. Bioleaching of Theisen sludge was investigated at acidic conditions with Acidithiobacillus ferrooxidans in pure and mixed-species culture with Acidiphilium. In shaking-flask experiments, bioleaching parameters (pH, redox potential, zinc extraction from ZnS, ferrous- and ferric-iron concentration) were controlled regularly. The analysis of the dissolved metals showed that 70% zinc and 45% copper were extracted. Investigations regarding the arsenic and antimony species were performed. When iron ions were lacking, animonate (Sb(V)) and total arsenic concentration were highest in solution. The bioleaching approach was scaled up in stirred-tank bioreactors resulting in higher leaching efficiency of valuable trace elements. Concentrations of dissolved antimony were approx. 23 times, and of cobalt, germanium, and rhenium three times higher in comparison to shaking-flask experiments, when considering the difference in solid load of Theisen sludge. The extraction of base and trace metals from Theisen sludge, despite of its high content of heavy metals and organic compounds, was feasible with iron-oxidizing acidophilic bacteria. In stirred-tank bioreactors, the mixed-species culture performed better. To the best of our knowledge, this study is the first providing an appropriate biological technology for the treatment of Theisen sludge to win valuable elements. © 2016 The Society for Applied Microbiology.

Exploring the Microbiome of Callinectes sapidus (Maryland Blue Crab)

PubMed Central

Reed, Elizabeth; Ottesen, Andrea

2018-01-01

ABSTRACT The Maryland blue crab (Callinectes sapidus) is a treasured food, especially in areas surrounding the Chesapeake Bay. It has huge economic impact on commerce, and thus, understanding the bacterial, fungal, and viral constituents of its microbiome provides valuable information to safely manage aquaculture, handling, and cooking of this valuable commodity. PMID:29853506

a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information

NASA Astrophysics Data System (ADS)

Lian, Shizhong; Chen, Jiangping; Luo, Minghai

2016-06-01

Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.

Tools and Services for Working with Multiple Land Remote Sensing Data Products

NASA Astrophysics Data System (ADS)

Krehbiel, C.; Friesz, A.; Harriman, L.; Quenzer, R.; Impecoven, K.; Maiersperger, T.

2016-12-01

The availability of increasingly large and diverse satellite remote sensing datasets provides both an opportunity and a challenge across broad Earth science research communities. On one hand, the extensive assortment of available data offer unprecedented opportunities to improve our understanding of Earth science and enable data use across a multitude of science disciplines. On the other hand, increasingly complex formats, data structures, and metadata can be an obstacle to data use for the broad user community that is interested in incorporating remote sensing Earth science data into their research. NASA's Land Processes Distributed Active Archive Center (LP DAAC) provides easy to use Python notebook tutorials for services such as accessing land remote sensing data from the LP DAAC Data Pool and interpreting data quality information from MODIS. We use examples to demonstrate the capabilities of the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), such as spatially and spectrally subsetting data, decoding valuable quality information, and exploring initial analysis results within the user interface. We also show data recipes for R and Python scripts that help users process ASTER L1T and ASTER Global Emissivity Datasets.

Data Resources for the Computer-Guided Discovery of Bioactive Natural Products.

PubMed

Chen, Ya; de Bruyn Kops, Christina; Kirchmair, Johannes

2017-09-25

Natural products from plants, animals, marine life, fungi, bacteria, and other organisms are an important resource for modern drug discovery. Their biological relevance and structural diversity make natural products good starting points for drug design. Natural product-based drug discovery can benefit greatly from computational approaches, which are a valuable precursor or supplementary method to in vitro testing. We present an overview of 25 virtual and 31 physical natural product libraries that are useful for applications in cheminformatics, in particular virtual screening. The overview includes detailed information about each library, the extent of its structural information, and the overlap between different sources of natural products. In terms of chemical structures, there is a large overlap between freely available and commercial virtual natural product libraries. Of particular interest for drug discovery is that at least ten percent of known natural products are readily purchasable and many more natural products and derivatives are available through on-demand sourcing, extraction and synthesis services. Many of the readily purchasable natural products are of small size and hence of relevance to fragment-based drug discovery. There are also an increasing number of macrocyclic natural products and derivatives becoming available for screening.

Comparative Variable Temperature Studies of Polyamide II with a Benchtop Fourier Transform and a Miniature Handheld Near-Infrared Spectrometer Using 2D-COS and PCMW-2D Analysis.

PubMed

Unger, Miriam; Pfeifer, Frank; Siesler, Heinz W

2016-07-01

The main objective of this communication is to compare the performance of a miniaturized handheld near-infrared (NIR) spectrometer with a benchtop Fourier transform near-infrared (FT-NIR) spectrometer. Generally, NIR spectroscopy is an extremely powerful analytical tool to study hydrogen-bonding changes of amide functionalities in solid and liquid materials and therefore variable temperature NIR measurements of polyamide II (PAII) have been selected as a case study. The information content of the measurement data has been further enhanced by exploiting the potential of two-dimensional correlation spectroscopy (2D-COS) and the perturbation correlation moving window two-dimensional (PCMW2D) evaluation technique. The data provide valuable insights not only into the changes of the hydrogen-bonding structure and the recrystallization of the hydrocarbon segments of the investigated PAII but also in their sequential order. Furthermore, it has been demonstrated that the 2D-COS and PCMW2D results derived from the spectra measured with the miniaturized NIR instrument are equivalent to the information extracted from the data obtained with the high-performance FT-NIR instrument. © The Author(s) 2016.

Deconstructing thermodynamic parameters of a coupled system from site-specific observables.

PubMed

Chowdhury, Sandipan; Chanda, Baron

2010-11-02

Cooperative interactions mediate information transfer between structural domains of a protein molecule and are major determinants of protein function and modulation. The prevalent theories to understand the thermodynamic origins of cooperativity have been developed to reproduce the complex behavior of a global thermodynamic observable such as ligand binding or enzyme activity. However, in most cases the measurement of a single global observable cannot uniquely define all the terms that fully describe the energetics of the system. Here we establish a theoretical groundwork for analyzing protein thermodynamics using site-specific information. Our treatment involves extracting a site-specific parameter (defined as χ value) associated with a structural unit. We demonstrate that, under limiting conditions, the χ value is related to the direct interaction terms associated with the structural unit under observation and its intrinsic activation energy. We also introduce a site-specific interaction energy term (χ(diff)) that is a function of the direct interaction energy of that site with every other site in the system. When combined with site-directed mutagenesis and other molecular level perturbations, analyses of χ values of site-specific observables may provide valuable insights into protein thermodynamics and structure.

Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data

NASA Astrophysics Data System (ADS)

Kumar, C.; Shetty, A.; Raval, S.; Champatiray, P. K.; Sharma, R.

2014-11-01

This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.

Pitfalls and Limitations in the Interpretation of Geophysical Images for Hydrologic Properties and Processes

NASA Astrophysics Data System (ADS)

Day-Lewis, F. D.

2014-12-01

Geophysical imaging (e.g., electrical, radar, seismic) can provide valuable information for the characterization of hydrologic properties and monitoring of hydrologic processes, as evidenced in the rapid growth of literature on the subject. Geophysical imaging has been used for monitoring tracer migration and infiltration, mapping zones of focused groundwater/surface-water exchange, and verifying emplacement of amendments for bioremediation. Despite the enormous potential for extraction of hydrologic information from geophysical images, there also is potential for misinterpretation and over-interpretation. These concerns are particularly relevant when geophysical results are used within quantitative frameworks, e.g., conversion to hydrologic properties through petrophysical relations, geostatistical estimation and simulation conditioned to geophysical inversions, and joint inversion. We review pitfalls to interpretation associated with limited image resolution, spatially variable image resolution, incorrect data weighting, errors in the timing of measurements, temporal smearing resulting from changes during data acquisition, support-volume/scale effects, and incorrect assumptions or approximations involved in modeling geophysical or other jointly inverted data. A series of numerical and field-based examples illustrate these potential problems. Our goal in this talk is to raise awareness of common pitfalls and present strategies for recognizing and avoiding them.

Identification of resinous materials on 16th and 17th century reverse-glass objects by gas chromatography/mass spectrometry

NASA Astrophysics Data System (ADS)

Baumer, Ursula; Dietemann, Patrick; Koller, Johann

2009-07-01

Objects of hinterglasmalerei, reverse-glass paintings, are painted on the back side of glass panels. Obviously, the paint layers are applied in reverse order, starting with the uppermost layer. The finished hinterglas painting is viewed through the glass, thus revealing an impressive gloss and depth of colour. The binding media of two precious objects of hinterglasmalerei from the 16th and 17th century have been identified as almost exclusively resinous. Identification was performed by a special optimised analysis procedure, which is discussed in this paper: solvent extracts are analysed by gas chromatography/mass spectrometry, both with and without derivatisation or hydrolysis. In an additional step, oxalic acid is added to the methanol extracts prior to injection. This attenuates the peaks of the non-acidic compounds, whereas the acids elute with good resolution. The non-acidic compounds are emphasised after injection of the underivatised extracts. This approach minimises compositional changes caused by the sample preparation and derivatisation steps. Chromatograms of aged samples with a very complex composition are simplified, which allows a more reliable and straightforward identification of significant markers for various materials. The binding media of the hinterglas objects were thus shown to consist of mixtures of different natural resins, larch turpentine, heat-treated Pinaceae resin or mastic. Typical compounds of dragon's blood, a natural red resin, were also detectable in red glazes by the applied analysis routine. Identification of the binding media provides valuable information that can be used in the development of an adequate conservation treatment.

A structural SVM approach for reference parsing.

PubMed

Zhang, Xiaoli; Zou, Jie; Le, Daniel X; Thoma, George R

2011-06-09

Automated extraction of bibliographic data, such as article titles, author names, abstracts, and references is essential to the affordable creation of large citation databases. References, typically appearing at the end of journal articles, can also provide valuable information for extracting other bibliographic data. Therefore, parsing individual reference to extract author, title, journal, year, etc. is sometimes a necessary preprocessing step in building citation-indexing systems. The regular structure in references enables us to consider reference parsing a sequence learning problem and to study structural Support Vector Machine (structural SVM), a newly developed structured learning algorithm on parsing references. In this study, we implemented structural SVM and used two types of contextual features to compare structural SVM with conventional SVM. Both methods achieve above 98% token classification accuracy and above 95% overall chunk-level accuracy for reference parsing. We also compared SVM and structural SVM to Conditional Random Field (CRF). The experimental results show that structural SVM and CRF achieve similar accuracies at token- and chunk-levels. When only basic observation features are used for each token, structural SVM achieves higher performance compared to SVM since it utilizes the contextual label features. However, when the contextual observation features from neighboring tokens are combined, SVM performance improves greatly, and is close to that of structural SVM after adding the second order contextual observation features. The comparison of these two methods with CRF using the same set of binary features show that both structural SVM and CRF perform better than SVM, indicating their stronger sequence learning ability in reference parsing.

Empirical Mode Decomposition and k-Nearest Embedding Vectors for Timely Analyses of Antibiotic Resistance Trends

PubMed Central

Teodoro, Douglas; Lovis, Christian

2013-01-01

Background Antibiotic resistance is a major worldwide public health concern. In clinical settings, timely antibiotic resistance information is key for care providers as it allows appropriate targeted treatment or improved empirical treatment when the specific results of the patient are not yet available. Objective To improve antibiotic resistance trend analysis algorithms by building a novel, fully data-driven forecasting method from the combination of trend extraction and machine learning models for enhanced biosurveillance systems. Methods We investigate a robust model for extraction and forecasting of antibiotic resistance trends using a decade of microbiology data. Our method consists of breaking down the resistance time series into independent oscillatory components via the empirical mode decomposition technique. The resulting waveforms describing intrinsic resistance trends serve as the input for the forecasting algorithm. The algorithm applies the delay coordinate embedding theorem together with the k-nearest neighbor framework to project mappings from past events into the future dimension and estimate the resistance levels. Results The algorithms that decompose the resistance time series and filter out high frequency components showed statistically significant performance improvements in comparison with a benchmark random walk model. We present further qualitative use-cases of antibiotic resistance trend extraction, where empirical mode decomposition was applied to highlight the specificities of the resistance trends. Conclusion The decomposition of the raw signal was found not only to yield valuable insight into the resistance evolution, but also to produce novel models of resistance forecasters with boosted prediction performance, which could be utilized as a complementary method in the analysis of antibiotic resistance trends. PMID:23637796

Pharmacognostic studies of the leaves and stem of Careya arborea Roxb.

PubMed Central

Gupta, Prakash Chandra; Sharma, Nisha; Rao, Ch V

2012-01-01

Objective To study detailed pharmacognostic profile of leaves and stem of Careya arborea (C. arborea) Roxb. (Lecthyidaceae), an important medicinal plant in the Indian system of medicine. Methods Leaf and stem samples of C. arborea were studied by macroscopical, microscopical, physicochemical, phytochemical, fluorescence analysis of powder of the plant and other methods for standardization recommended by WHO. Results Macroscopically, the leaves are simple, broadly obovate in shape, acuminate apex with crenate, dentate margin, petioles (0.1–1.8 cm) long. Microscopically, the leaf showed the presence of median large size vascular bundle covered with fibrous bundle sheath, arrangement of xylem in cup shape and presence of cortical vascular bundle, patches of sclerenchyma, phloem fibers in groups and brown pigment containing cells in stem are some of the diagnostic features noted from anatomical study. Powder microscopy of leaf revealed the presence of parenchyma cells, xylem with pitted vessels and epidermis with anisocytic stomata. The investigations also included leaf surface data; quantitative leaf microscopy and fluorescence analysis. Physiochemical parameters such as loss on drying, swelling index, extractive values and ash values were also determined and results showed that total ash of the stem bark was about two times higher than leaf and water soluble extractive value of leaf and stem bark was two times higher than alcohol soluble extractive value. Preliminary phytochemical screening showed the presence of triterpenoids, saponins, tannins and flavonoids. Conclusions The results of the study can serve as a valuable source of information and provide suitable standards for identification of this plant material in future investigations and applications. PMID:23569939

Extracting atmospheric turbulence and aerosol characteristics from passive imagery

NASA Astrophysics Data System (ADS)

Reinhardt, Colin N.; Wayne, D.; McBryde, K.; Cauble, G.

2013-09-01

Obtaining accurate, precise and timely information about the local atmospheric turbulence and extinction conditions and aerosol/particulate content remains a difficult problem with incomplete solutions. It has important applications in areas such as optical and IR free-space communications, imaging systems performance, and the propagation of directed energy. The capability to utilize passive imaging data to extract parameters characterizing atmospheric turbulence and aerosol/particulate conditions would represent a valuable addition to the current piecemeal toolset for atmospheric sensing. Our research investigates an application of fundamental results from optical turbulence theory and aerosol extinction theory combined with recent advances in image-quality-metrics (IQM) and image-quality-assessment (IQA) methods. We have developed an algorithm which extracts important parameters used for characterizing atmospheric turbulence and extinction along the propagation channel, such as the refractive-index structure parameter C2n , the Fried atmospheric coherence width r0 , and the atmospheric extinction coefficient βext , from passive image data. We will analyze the algorithm performance using simulations based on modeling with turbulence modulation transfer functions. An experimental field campaign was organized and data were collected from passive imaging through turbulence of Siemens star resolution targets over several short littoral paths in Point Loma, San Diego, under conditions various turbulence intensities. We present initial results of the algorithm's effectiveness using this field data and compare against measurements taken concurrently with other standard atmospheric characterization equipment. We also discuss some of the challenges encountered with the algorithm, tasks currently in progress, and approaches planned for improving the performance in the near future.

Influence of nuclei segmentation on breast cancer malignancy classification

NASA Astrophysics Data System (ADS)

Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

2009-02-01

Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

MOEX: Solvent extraction approach for recycling enriched 98Mo/ 100Mo material

DOE PAGES

Tkac, Peter; Brown, M. Alex; Momen, Abdul; ...

2017-03-20

Several promising pathways exist for the production of 99Mo/ 99mTc using enriched 98Mo or 100Mo. Use of Mo targets require a major change in current generator technology, and the necessity for an efficient recycle pathway to recover valuable enriched Mo material. High recovery yields, purity, suitable chemical form and particle size are required. Results on the development of the MOEX– molybdenum solvent extraction – approach to recycle enriched Mo material are presented. Furthermore, the advantages of the MOEX process are very high decontamination factors from potassium and other elements, high throughput, easy scalability, automation, and minimal waste generation.

A modal parameter extraction procedure applicable to linear time-invariant dynamic systems

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Craig, R. R., Jr.

1985-01-01

Modal analysis has emerged as a valuable tool in many phases of the engineering design process. Complex vibration and acoustic problems in new designs can often be remedied through use of the method. Moreover, the technique has been used to enhance the conceptual understanding of structures by serving to verify analytical models. A new modal parameter estimation procedure is presented. The technique is applicable to linear, time-invariant systems and accommodates multiple input excitations. In order to provide a background for the derivation of the method, some modal parameter extraction procedures currently in use are described. Key features implemented in the new technique are elaborated upon.

MOEX: Solvent extraction approach for recycling enriched 98Mo/ 100Mo material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tkac, Peter; Brown, M. Alex; Momen, Abdul

Several promising pathways exist for the production of 99Mo/ 99mTc using enriched 98Mo or 100Mo. Use of Mo targets require a major change in current generator technology, and the necessity for an efficient recycle pathway to recover valuable enriched Mo material. High recovery yields, purity, suitable chemical form and particle size are required. Results on the development of the MOEX– molybdenum solvent extraction – approach to recycle enriched Mo material are presented. Furthermore, the advantages of the MOEX process are very high decontamination factors from potassium and other elements, high throughput, easy scalability, automation, and minimal waste generation.

Information extraction system

DOEpatents

Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

2014-05-13

An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

Microwave-assisted extraction of herbacetin diglucoside from flax (Linum usitatissimum L.) seed cakes and its quantification using an RP-HPLC-UV system.

PubMed

Fliniaux, Ophélie; Corbin, Cyrielle; Ramsay, Aina; Renouard, Sullivan; Beejmohun, Vickram; Doussot, Joël; Falguières, Annie; Ferroud, Clotilde; Lamblin, Frédéric; Lainé, Eric; Roscher, Albrecht; Grand, Eric; Mesnard, François; Hano, Christophe

2014-03-10

Flax (Linum usitatissimum L.) seeds are widely used for oil extraction and the cold-pressed flaxseed (or linseed) cakes obtained during this process constitute a valuable by-product. The flavonol herbacetin diglucoside (HDG) has been previously reported as a constituent of the flaxseed lignan macromolecule linked through ester bonds to the linker molecule hydroxymethylglutaric acid. In this context, the development and validation of a new approach using microwave-assisted extraction (MAE) of HDG from flaxseed cakes followed by quantification with a reverse-phase HPLC system with UV detection was purposed. The experimental parameters affecting the HDG extraction yield, such as microwave power, extraction time and sodium hydroxide concentration, from the lignan macromolecule were optimized. A maximum HDG concentration of 5.76 mg/g DW in flaxseed cakes was measured following an irradiation time of 6 min, for a microwave power of 150 W using a direct extraction in 0.1 M NaOH in 70% (v/v) aqueous methanol. The optimized method was proven to be rapid and reliable in terms of precision, repeatability, stability and accuracy for the extraction of HDG. Comparison with a conventional extraction method demonstrated that MAE is more effective and less time-consuming.

The comparison of anti-oxidative kinetics in vitro of the fluid extract from maidenhair tree, motherwort and hawthorn.

PubMed

Bernatoniene, Jurga; Kucinskaite, Agne; Masteikova, Ruta; Kalveniene, Zenona; Kasparaviciene, Giedre; Savickas, Arunas

2009-01-01

The aim of the study was to perform a quantitative analysis of fluid extracts of maidenhair tree (Ginkgo biloba L.), motherwort (Leonurus cardiaca L.) and hawthorn (Crataegus monogyna Jacq.), to evaluate their antioxidant activity and to compare their ability to inactivate free radicals. The antioxidant activity was measured using the DPPH*and the ABTS*+ radical scavenging reaction systems. The study showed that the manifestation of the radical scavenging capacity in the DPPH* reaction system was in the following order: the fluid extract of hawthorn (70.37 +/- 0.80%) > the fluid extract of maidenhair tree (82.63 +/- 0.23%) > the fluid extract of motherwort (84.89 +/- 0.18%), while in the ABTS*+ reaction system, the manifestation of the radical scavenging capacity was in the following order: the fluid extract of hawthorn (87.09 +/- 0.55%) > the fluid extract of motherwort (88.28 +/- 1.06%) > the fluid extract of maidenhair tree (88.39 +/- 0.72%). The results showed that in the DPPH* reaction system, fluid extract of motherwort manifested higher antioxidant activity, compared to the fluid extracts of maidenhair tree and hawthorn. By contrast, in the ABTS*+ reaction system, higher antioxidant activity was found in the fluid extract of maidenhair tree, compared to the fluid extracts of motherwort and hawthorn. This would suggest that preparations manufactured from these herbal raw materials could be used as effective preventive means and valuable additional remedies in the treatment of diseases caused by oxidative stress.

Complex investigation of extraction techniques applied for cyclitols and sugars isolation from different species of Solidago genus.

PubMed

Ratiu, Ileana-Andreea; Al-Suod, Hossam; Ligor, Magdalena; Ligor, Tomasz; Railean-Plugaru, Viorica; Buszewski, Bogusław

2018-03-15

Cyclitols are phytochemicals naturally occurring in plant material, which attracted an increasing interest due to multiple medicinal attributes, among which the most important are the antidiabetic, antioxidant, and anticancer properties. Due to their valuable properties, sugars are used in the food industry as sweeteners, preservatives, texture modifiers, fermentation substrates, and flavoring and coloring agents. In this study, we report for the first time the quantitative analysis of sugars and cyclitols isolated from Solidago virgaurea L., which was used for the selection of the optimal solvent and extraction technique that can provide the best possible yield. Moreover, the quantities of sugars and cyclitols extracted from two other species, Solidago canadensis and Solidago gigantea, were investigated using the best extraction method and the most appropriate solvent. Comparative analysis of natural plant extracts obtained using five different techniques-maceration, Soxhlet extraction, pressurized liquid extraction, ultrasound-assisted extraction, and supercritical fluid extraction-was performed in order to decide the most suitable, efficient, and economically convenient extraction method. Three different solvents were used. Analysis of samples has been performed by solid-phase extraction for purification and pre-concentration, followed by derivation and GC-MS analysis. Highest efficiency for the total amount of obtained compounds has been reached by PLE, when water was used as a solvent. d-pinitol amount was almost similar for every solvent and for all the extraction techniques involved. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The impact of real-time and predictive traffic information on travelers' behavior on the I-4 corridor. Final report.

DOT National Transportation Integrated Search

2003-07-01

Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transport...

Preliminary Study of Bioinformatics Patents and Their Classifications Registered in the KIPRIS Database.

PubMed

Park, Hyun-Seok

2012-12-01

Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.

Identification and characterisation of water and alkali soluble oligosaccharides from hazelnut skin (Corylus avellana L.).

PubMed

Montella, Rosa; Coïsson, Jean Daniel; Travaglia, Fabiano; Locatelli, Monica; Bordiga, Matteo; Meyrand, Mickael; Barile, Daniela; Arlorio, Marco

2013-10-15

Hazelnut skins are a good example of agricultural by-product with the potential to become a valuable source of functional ingredients. In this work, the fibre from hazelnut skins was extracted by using water and alkali solution and characterised by a suite of analytical tools (MALDI-FTICR, nano LC-Chip-Q-ToF and gas chromatography). Over thirty complex free oligosaccharides, composed mainly of galacturonic acid and N-acetylgalactosamine, were characterised for the first time in the present study. Their concentration ranged between 16 and 34mg per g of extract. The oligosaccharides isolated from this agricultural by-product are mainly hexose oligosaccharides (potentially galacto-oligosaccharides,) and xyloglucans. The identified composition could justify the bioactive activity of the extracts, namely prebiotic activity, previously demonstrated. Copyright © 2013 Elsevier Ltd. All rights reserved.

Selective extraction of halogenated compounds from data measured by comprehensive multidimensional gas chromatography/high resolution time-of-flight mass spectrometry for non-target analysis of environmental and biological samples.

PubMed

Hashimoto, Shunji; Zushi, Yasuyuki; Fushimi, Akihiro; Takazawa, Yoshikatsu; Tanabe, Kiyoshi; Shibata, Yasuyuki

2013-03-22

We developed a method that selectively extracts a subset from comprehensive 2D gas chromatography (GC×GC) and high-resolution time-of-flight mass spectrometry (HRTOFMS) data to detect and identify trace levels of organohalogens. The data were obtained by measuring several environmental and biological samples, namely fly ash, soil, sediment, the atmosphere, and human urine. For global analysis, some samples were measured without purification. By using our novel software, the mass spectra of organochlorines or organobromines were then extracted into a data subset under high mass accuracy conditions that were approximately equivalent to a mass resolution of 6000 for some samples. Mass defect filtering as pre-screening for the data extraction was very effective in removing the mass spectra of hydrocarbons. Those results showed that data obtained with HRTOFMS are valuable for global analysis of organohalogens, and probably of other compounds if specific data extraction methods can be devised. Copyright © 2013 Elsevier B.V. All rights reserved.

Preparation of Formalin-fixed Paraffin-embedded Tissue Cores for both RNA and DNA Extraction.

PubMed

Patel, Palak G; Selvarajah, Shamini; Boursalie, Suzanne; How, Nathan E; Ejdelman, Joshua; Guerard, Karl-Philippe; Bartlett, John M; Lapointe, Jacques; Park, Paul C; Okello, John B A; Berman, David M

2016-08-21

Formalin-fixed paraffin embedded tissue (FFPET) represents a valuable, well-annotated substrate for molecular investigations. The utility of FFPET in molecular analysis is complicated both by heterogeneous tissue composition and low yields when extracting nucleic acids. A literature search revealed a paucity of protocols addressing these issues, and none that showed a validated method for simultaneous extraction of RNA and DNA from regions of interest in FFPET. This method addresses both issues. Tissue specificity was achieved by mapping cancer areas of interest on microscope slides and transferring annotations onto FFPET blocks. Tissue cores were harvested from areas of interest using 0.6 mm microarray punches. Nucleic acid extraction was performed using a commercial FFPET extraction system, with modifications to homogenization, deparaffinization, and Proteinase K digestion steps to improve tissue digestion and increase nucleic acid yields. The modified protocol yields sufficient quantity and quality of nucleic acids for use in a number of downstream analyses, including a multi-analyte gene expression platform, as well as reverse transcriptase coupled real time PCR analysis of mRNA expression, and methylation-specific PCR (MSP) analysis of DNA methylation.

Anticancer and antioxidant activity of bread enriched with broccoli sprouts.

PubMed

Gawlik-Dziki, Urszula; Świeca, Michał; Dziki, Dariusz; Sęczyk, Łukasz; Złotek, Urszula; Różyło, Renata; Kaszuba, Kinga; Ryszawy, Damian; Czyż, Jarosław

2014-01-01

This study is focused on antioxidant and anticancer capacity of bread enriched with broccoli sprouts (BS) in the light of their potential bioaccessibility and bioavailability. Generally, bread supplementation elevated antioxidant potential of product (both nonenzymatic and enzymatic antioxidant capacities); however, the increase was not correlated with the percent of BS. A replacement up to 2% of BS gives satisfactory overall consumers acceptability and desirable elevation of antioxidant potential. High activity was especially found for extracts obtained after simulated digestion, which allows assuming their protective effect for upper gastrointestinal tract; thus, the anticancer activity against human stomach cancer cells (AGS) was evaluated. A prominent cytostatic response paralleled by the inhibition of AGS motility in the presence of potentially mastication-extractable phytochemicals indicates that phenolic compounds of BS retain their biological activity in bread. Importantly, the efficient phenolics concentration was about 12 μM for buffer extract, 13 μM for extracts after digestion in vitro, and 7 μM for extract after absorption in vitro. Our data confirm chemopreventive potential of bread enriched with BS and indicate that BS comprise valuable food supplement for stomach cancer chemoprevention.

Changes in Drosophila melanogaster Sleep-Wake Behavior Due to Lotus (Nelumbo nucifera) Seed and Hwang Jeong (Polygonatum sibiricum) Extracts

PubMed Central

Jo, Kyungae; Jeon, SangDuk; Ahn, Chang-Won; Han, Sung Hee; Suh, Hyung Joo

2017-01-01

We evaluated the sleep enhancement activity of the medicinal herbs valerian (Valeriana officinalis), jujube (Ziziphus jujube), lotus seed (Nelumbo nucifera), Gastrodia elata, Polygonatum sibiricum, and baekbokryung (Poria cocos), which can relieve insomnia in a Drosophila model. Locomotor activity was measured in the Drosophila model to evaluate the sleep activity of Korean medicinal herbs traditionally used as sleep aids. The group treated with lotus seed extract showed less nocturnal activity. Treatment with 10 or 20 mg/mL of P. sibiricum significantly reduced nocturnal activity compared to the control group (P<0.05). The activity and sleep bouts of fruit flies were significantly decreased by a high-dose treatment (10 mg/mL) of lotus or P. sibiricum extracts at night. Caffeine-treated Drosophila showed increased nocturnal activity and decreased total sleep time (P<0.05). Flies receiving the 10 mg-doses of lotus seed or P. sibiricum extract showed significantly different nocturnal locomotor activity and total sleep time compared to caffeine-treated Drosophila. Lotus seed and P. sibiricum extracts are attractive and valuable sleep-potentiating nutraceuticals. PMID:29333381

Development of Mushroom-Based Cosmeceutical Formulations with Anti-Inflammatory, Anti-Tyrosinase, Antioxidant, and Antibacterial Properties.

PubMed

Taofiq, Oludemi; Heleno, Sandrina A; Calhelha, Ricardo C; Alves, Maria José; Barros, Lillian; Barreiro, Maria Filomena; González-Paramás, Ana M; Ferreira, Isabel C F R

2016-10-14

The cosmetic industry is in a constant search for natural compounds or extracts with relevant bioactive properties, which became valuable ingredients to design cosmeceutical formulations. Mushrooms have been markedly studied in terms of nutritional value and medicinal properties. However, there is still slow progress in the biotechnological application of mushroom extracts in cosmetic formulations, either as antioxidants, anti-aging, antimicrobial, and anti-inflammatory agents or as hyperpigmentation correctors. In the present work, the cosmeceutical potential of ethanolic extracts prepared from Agaricus bisporus , Pleurotus ostreatus , and Lentinula edodes was analyzed in terms of anti-inflammatory, anti-tyrosinase, antioxidant, and antibacterial activities. The extracts were characterized in terms of phenolic acids and ergosterol composition, and further incorporated in a base cosmetic cream to achieve the same bioactive purposes. From the results obtained, the final cosmeceutical formulations presented 85%-100% of the phenolic acids and ergosterol levels found in the mushroom extracts, suggesting that there was no significant loss of bioactive compounds. The final cosmeceutical formulation also displayed all the ascribed bioactivities and as such, mushrooms can further be exploited as natural cosmeceutical ingredients.

Evaluation of antioxidant potential of Artocarpus heterophyllus L. J33 variety fruit waste from different extraction methods and identification of phenolic constituents by LCMS.

PubMed

Daud, Mohd Nazrul Hisham; Fatanah, Dian Nashiela; Abdullah, Noriham; Ahmad, Rohaya

2017-10-01

Artocarpus heterophyllus J33 (AhJ33) fruit is a popular and valuable jackfruit variety in Malaysia. For export, the pulp has to be separated from the skin which is usually discarded. Hence, the conversion of the fruit waste to food products with economic value needs to be explored utilizing the waste to wealth concept. This paper reports the evaluation of antioxidant potential of AhJ33 fruit waste (rind and rachis) extracts from three different extraction methods (maceration, percolation and Soxhlet). The antioxidant potential was assessed by DPPH radical scavenging, FRAP and β-carotene bleaching assays. The total phenolic and total flavonoid contents were estimated by TPC and the TFC assays. For both rind and rachis, the maceration technique yielded extracts with the strongest antioxidant activities which correlated with the highest TPC and TFC values. TOF LCMS analyses identified two phenolic acids as the major constituents responsible for the antioxidant activity of the active extracts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Information extraction from multi-institutional radiology reports.

PubMed

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

The radiology report is the most important source of clinical imaging information. It documents critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to the referring physicians and records that information for future clinical and research use. Although efforts to structure some radiology report information through predefined templates are beginning to bear fruit, a large portion of radiology report information is entered in free text. The free text format is a major obstacle for rapid extraction and subsequent use of information by clinicians, researchers, and healthcare information systems. This difficulty is due to the ambiguity and subtlety of natural language, complexity of described images, and variations among different radiologists and healthcare organizations. As a result, radiology reports are used only once by the clinician who ordered the study and rarely are used again for research and data mining. In this work, machine learning techniques and a large multi-institutional radiology report repository are used to extract the semantics of the radiology report and overcome the barriers to the re-use of radiology report information in clinical research and other healthcare applications. We describe a machine learning system to annotate radiology reports and extract report contents according to an information model. This information model covers the majority of clinically significant contents in radiology reports and is applicable to a wide variety of radiology study types. Our automated approach uses discriminative sequence classifiers for named-entity recognition to extract and organize clinically significant terms and phrases consistent with the information model. We evaluated our information extraction system on 150 radiology reports from three major healthcare organizations and compared its results to a commonly used non-machine learning information extraction method. We also evaluated the generalizability of our approach across different organizations by training and testing our system on data from different organizations. Our results show the efficacy of our machine learning approach in extracting the information model's elements (10-fold cross-validation average performance: precision: 87%, recall: 84%, F1 score: 85%) and its superiority and generalizability compared to the common non-machine learning approach (p-value<0.05). Our machine learning information extraction approach provides an effective automatic method to annotate and extract clinically significant information from a large collection of free text radiology reports. This information extraction system can help clinicians better understand the radiology reports and prioritize their review process. In addition, the extracted information can be used by researchers to link radiology reports to information from other data sources such as electronic health records and the patient's genome. Extracted information also can facilitate disease surveillance, real-time clinical decision support for the radiologist, and content-based image retrieval. Copyright © 2015 Elsevier B.V. All rights reserved.

Review of Extracting Information From the Social Web for Health Personalization

PubMed Central

Karlsen, Randi; Bonander, Jason

2011-01-01

In recent years the Web has come into its own as a social platform where health consumers are actively creating and consuming Web content. Moreover, as the Web matures, consumers are gaining access to personalized applications adapted to their health needs and interests. The creation of personalized Web applications relies on extracted information about the users and the content to personalize. The Social Web itself provides many sources of information that can be used to extract information for personalization apart from traditional Web forms and questionnaires. This paper provides a review of different approaches for extracting information from the Social Web for health personalization. We reviewed research literature across different fields addressing the disclosure of health information in the Social Web, techniques to extract that information, and examples of personalized health applications. In addition, the paper includes a discussion of technical and socioethical challenges related to the extraction of information for health personalization. PMID:21278049

Proteomic analysis of formalin-fixed paraffin embedded tissue by MALDI imaging mass spectrometry

PubMed Central

Casadonte, Rita; Caprioli, Richard M

2012-01-01

Archived formalin-fixed paraffin-embedded (FFPE) tissue collections represent a valuable informational resource for proteomic studies. Multiple FFPE core biopsies can be assembled in a single block to form tissue microarrays (TMAs). We describe a protocol for analyzing protein in FFPE -TMAs using matrix-assisted laser desorption/ionization (MAL DI) imaging mass spectrometry (IMS). The workflow incorporates an antigen retrieval step following deparaffinization, in situ trypsin digestion, matrix application and then mass spectrometry signal acquisition. The direct analysis of FFPE -TMA tissue using IMS allows direct analysis of multiple tissue samples in a single experiment without extraction and purification of proteins. The advantages of high speed and throughput, easy sample handling and excellent reproducibility make this technology a favorable approach for the proteomic analysis of clinical research cohorts with large sample numbers. For example, TMA analysis of 300 FFPE cores would typically require 6 h of total time through data acquisition, not including data analysis. PMID:22011652

Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System.

PubMed

Chen, Donghua; Zhang, Runtong; Liu, Kecheng; Hou, Lei

2018-06-19

Patient-reported posts in Online Health Communities (OHCs) contain various valuable information that can help establish knowledge-based online support for online patients. However, utilizing these reports to improve online patient services in the absence of appropriate medical and healthcare expert knowledge is difficult. Thus, we propose a comprehensive knowledge discovery method that is based on the Unified Medical Language System for the analysis of narrative posts in OHCs. First, we propose a domain-knowledge support framework for OHCs to provide a basis for post analysis. Second, we develop a Knowledge-Involved Topic Modeling (KI-TM) method to extract and expand explicit knowledge within the text. We propose four metrics, namely, explicit knowledge rate, latent knowledge rate, knowledge correlation rate, and perplexity, for the evaluation of the KI-TM method. Our experimental results indicate that our proposed method outperforms existing methods in terms of providing knowledge support. Our method enhances knowledge support for online patients and can help develop intelligent OHCs in the future.

SH2 Domain Histochemistry.

PubMed

Buhs, Sophia; Nollau, Peter

2017-01-01

Among posttranslational modifications, the phosphorylation of tyrosine residues is a key modification in cell signaling. Because of its biological importance, characterization of the cellular state of tyrosine phosphorylation is of great interest. Based on the unique properties of endogenously expressed SH2 domains recognizing tyrosine phosphorylated signaling proteins with high specificity we have developed an alternative approach, coined SH2 profiling, enabling us to decipher complex patterns of tyrosine phosphorylation in various normal and cancerous tissues. So far, SH2 profiling has largely been applied for the analysis of protein extracts with the limitation that information on spatial distribution and intensity of tyrosine phosphorylation within a tissue is lost. Here, we describe a novel SH2 domain based strategy for differential characterization of the state of tyrosine phosphorylation in formaldehyde-fixed and paraffin-embedded tissues. This approach demonstrates that SH2 domains may serve as very valuable tools for the analysis of the differential state of tyrosine phosphorylation in primary tissues fixed and processed under conditions frequently applied by routine pathology laboratories.

SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents

PubMed Central

Heifets, Abraham; Jurisica, Igor

2012-01-01

The patent literature is a rich catalog of biologically relevant chemicals; many public and commercial molecular databases contain the structures disclosed in patent claims. However, patents are an equally rich source of metadata about bioactive molecules, including mechanism of action, disease class, homologous experimental series, structural alternatives, or the synthetic pathways used to produce molecules of interest. Unfortunately, this metadata is discarded when chemical structures are deposited separately in databases. SCRIPDB is a chemical structure database designed to make this metadata accessible. SCRIPDB provides the full original patent text, reactions and relationships described within any individual patent, in addition to the molecular files common to structural databases. We discuss how such information is valuable in medical text mining, chemical image analysis, reaction extraction and in silico pharmaceutical lead optimization. SCRIPDB may be searched by exact chemical structure, substructure or molecular similarity and the results may be restricted to patents describing synthetic routes. SCRIPDB is available at http://dcv.uhnres.utoronto.ca/SCRIPDB. PMID:22067445

Review of Public Tweets Over Turkey Within a Pre-Determined Time

NASA Astrophysics Data System (ADS)

Gulnerman, A. G.; Gengec, N. E.; Karaman, H.

2016-09-01

Spatial data by using public knowledge is the most popular way to gather data in terms of social media within the last decade. Literature defines, public or volunteers are accepted bionic sensors detecting their surroundings and share what they detect in terms of their social media applications or microblogs. Besides being cheapest and fastest and easy way of spatial data acquisition, public or volunteers provides not only spatial data but also attribute data which makes the data more valuable. To understand and interpret those data have some difficulties according to locality. Although some difficulties like difference of languages, society structure and the time period would affect tweets depending on locality, gathering public knowledge or volunteered data contribute many scientific or private researches like Urban, Environmental, and Market side. To extract information, data should be reviewed locally according to main aim of research. In this study, our aim is to draw a perspective for a PhD research about volunteered data in the case of Turkey.

Phase correlation imaging of unlabeled cell dynamics

NASA Astrophysics Data System (ADS)

Ma, Lihong; Rajshekhar, Gannavarpu; Wang, Ru; Bhaduri, Basanta; Sridharan, Shamira; Mir, Mustafa; Chakraborty, Arindam; Iyer, Rajashekar; Prasanth, Supriya; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel

2016-09-01

We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially-resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport. Specifically, we show that PCI can extract quantitatively the diffusion coefficient map associated with live cells, as well as standard Brownian particles. Due to its high sensitivity to mass transport, PCI can be applied to studying the integrity of actin polymerization dynamics. Our results indicate that the cyto-D treatment blocking the actin polymerization has a dominant effect at the large spatial scales, in the region surrounding the cell. We found that PCI can distinguish between senescent and quiescent cells, which is extremely difficult without using specific markers currently. We anticipate that PCI will be used alongside established, fluorescence-based techniques to enable valuable new studies of cell function.

α - synuclein under the magnifying glass. Insights from atomistic and coarse-grain simulations

NASA Astrophysics Data System (ADS)

Ilie, Ioana M.; Nayar, Divya; den Otter, Wouter K.; van der Vegt, Nico F. A.; Briels, Wim J.; University of Twente Collaboration; University of Darmstadt Collaboration

Neurodegenerative diseases are linked to the accumulation of misfolded intrinsically disordered proteins in the brain. Here, we use both all-atom and coarse-grain simulations to explore the intricate dynamics and the aggregation of α-synuclein, the protein implicated in Parkinson's disease. We explore the free energy landscapes of α-synuclein by using Molecular Dynamics simulations and extract information on the structure of the protein as well as on its binding affinities. Next, to study the aggregation, we proceed with representing α-synuclein as a chain of deformable particles that can adapt their geometry, binding affinities and can rearrange into different disordered and ordered structures. We use Brownian Dynamics to simulate the translational and rotational motions of the particles, as well as their interaction properties. The simulations show valuable insight into the internal dynamics of α-synuclein and the formation of ordered and disordered aggregates. In addition, the study is extended to investigate the attachment and folding of a protein to a fiber.

Framework for SEM contour analysis

NASA Astrophysics Data System (ADS)

Schneider, L.; Farys, V.; Serret, E.; Fenouillet-Beranger, C.

2017-03-01

SEM images provide valuable information about patterning capability. Geometrical properties such as Critical Dimension (CD) can be extracted from them and are used to calibrate OPC models, thus making OPC more robust and reliable. However, there is currently a shortage of appropriate metrology tools to inspect complex two-dimensional patterns in the same way as one would work with simple one-dimensional patterns. In this article we present a full framework for the analysis of SEM images. It has been proven to be fast, reliable and robust for every type of structure, and particularly for two-dimensional structures. To achieve this result, several innovative solutions have been developed and will be presented in the following pages. Firstly, we will present a new noise filter which is used to reduce noise on SEM images, followed by an efficient topography identifier, and finally we will describe the use of a topological skeleton as a measurement tool that can extend CD measurements on all kinds of patterns.

Quantifying Multistate Cytoplasmic Molecular Diffusion in Bacterial Cells via Inverse Transform of Confined Displacement Distribution.

PubMed

Chen, Tai-Yen; Jung, Won; Santiago, Ace George; Yang, Feng; Krzemiński, Łukasz; Chen, Peng

2015-11-12

Single-molecule tracking (SMT) of fluorescently tagged cytoplasmic proteins can provide valuable information on the underlying biological processes in living cells via subsequent analysis of the displacement distributions; however, the confinement effect originated from the small size of a bacterial cell skews the protein's displacement distribution and complicates the quantification of the intrinsic diffusive behaviors. Using the inverse transformation method, we convert the skewed displacement distribution (for both 2D and 3D imaging conditions) back to that in free space for systems containing one or multiple (non)interconverting Brownian diffusion states, from which we can reliably extract the number of diffusion states as well as their intrinsic diffusion coefficients and respective fractional populations. We further demonstrate a successful application to experimental SMT data of a transcription factor in living E. coli cells. This work allows a direct quantitative connection between cytoplasmic SMT data with diffusion theory for analyzing molecular diffusive behavior in live bacteria.

Nonlinear circuits for naturalistic visual motion estimation

PubMed Central

Fitzgerald, James E; Clark, Damon A

2015-01-01

Many animals use visual signals to estimate motion. Canonical models suppose that animals estimate motion by cross-correlating pairs of spatiotemporally separated visual signals, but recent experiments indicate that humans and flies perceive motion from higher-order correlations that signify motion in natural environments. Here we show how biologically plausible processing motifs in neural circuits could be tuned to extract this information. We emphasize how known aspects of Drosophila's visual circuitry could embody this tuning and predict fly behavior. We find that segregating motion signals into ON/OFF channels can enhance estimation accuracy by accounting for natural light/dark asymmetries. Furthermore, a diversity of inputs to motion detecting neurons can provide access to more complex higher-order correlations. Collectively, these results illustrate how non-canonical computations improve motion estimation with naturalistic inputs. This argues that the complexity of the fly's motion computations, implemented in its elaborate circuits, represents a valuable feature of its visual motion estimator. DOI: http://dx.doi.org/10.7554/eLife.09123.001 PMID:26499494

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

PubMed Central

Amenabar, Iban; Poly, Simon; Goikoetxea, Monika; Nuansing, Wiwat; Lasch, Peter; Hillenbrand, Rainer

2017-01-01

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm−1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine. PMID:28198384

Tertiary structural propensities reveal fundamental sequence/structure relationships.

PubMed

Zheng, Fan; Zhang, Jian; Grigoryan, Gevorg

2015-05-05

Extracting useful generalizations from the continually growing Protein Data Bank (PDB) is of central importance. We hypothesize that the PDB contains valuable quantitative information on the level of local tertiary structural motifs (TERMs). We show that by breaking a protein structure into its constituent TERMs, and querying the PDB to characterize the natural ensemble matching each, we can estimate the compatibility of the structure with a given amino acid sequence through a metric we term "structure score." Considering submissions from recent Critical Assessment of Structure Prediction (CASP) experiments, we found a strong correlation (R = 0.69) between structure score and model accuracy, with poorly predicted regions readily identifiable. This performance exceeds that of leading atomistic statistical energy functions. Furthermore, TERM-based analysis of two prototypical multi-state proteins rapidly produced structural insights fully consistent with prior extensive experimental studies. We thus find that TERM-based analysis should have considerable utility for protein structural biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantifying Multistate Cytoplasmic Molecular Diffusion in Bacterial Cells via Inverse Transform of Confined Displacement Distribution

PubMed Central

2016-01-01

Single-molecule tracking (SMT) of fluorescently tagged cytoplasmic proteins can provide valuable information on the underlying biological processes in living cells via subsequent analysis of the displacement distributions; however, the confinement effect originated from the small size of a bacterial cell skews the protein’s displacement distribution and complicates the quantification of the intrinsic diffusive behaviors. Using the inverse transformation method, we convert the skewed displacement distribution (for both 2D and 3D imaging conditions) back to that in free space for systems containing one or multiple (non)interconverting Brownian diffusion states, from which we can reliably extract the number of diffusion states as well as their intrinsic diffusion coefficients and respective fractional populations. We further demonstrate a successful application to experimental SMT data of a transcription factor in living E. coli cells. This work allows a direct quantitative connection between cytoplasmic SMT data with diffusion theory for analyzing molecular diffusive behavior in live bacteria. PMID:26491971

Branching pattern in natural drainage network

NASA Astrophysics Data System (ADS)

Hooshyar, M.; Singh, A.; Wang, D.

2017-12-01

The formation and growth of river channels and their network evolution are governed by the erosional and depositional processes operating on the landscape due to movement of water. The branching structure of drainage network is an important feature related to the network topology and contain valuable information about the forming mechanisms of the landscape. We studied the branching patterns in natural drainage networks, extracted from 1 m Digital Elevation Models (DEMs) of 120 catchments with minimal human impacts across the United States. We showed that the junction angles have two distinct modes an the observed modes are physically explained as the optimal angles that result in minimum energy dissipation and are linked to the exponent characterizing slope-area curve. Our findings suggest that the flow regimes, debris-flow dominated or fluvial, have distinct characteristic angles which are functions of the scaling exponent of the slope-area curve. These findings enable us to understand the geomorphological signature of hydrological processes on drainage networks and develop more refined landscape evolution models.

Vibrational biospectroscopy: from plants to animals to humans. A historical perspective

NASA Astrophysics Data System (ADS)

Shaw, R. Anthony; Mantsch, Henry H.

1999-05-01

Today, more than ever, vibrational spectroscopy means different things to different people. From their roots as molecular fingerprinting techniques, both infrared and Raman spectroscopy have evolved to the point where they play roles in a staggering variety of scientific endeavors. This survey focuses upon biological and medical applications. The past 40 years have witnessed enormous advances in our understanding of the building blocks of life, and vibrational spectroscopy has played an important role. That role is reviewed briefly here. In parallel with these efforts, the near-IR community developed powerful 'chemometric' methods to extract a wealth of information from spectra that appeared superficially featureless. As vibrational spectroscopy is finding new niches in the medical and clinical realms, these chemometric methods are proving to be a valuable (but not infallible!) adjunct to conventional spectral interpretation. This survey includes a brief outline of biomedical vibrational spectroscopy and imaging, including several representative examples to illustrate the strengths and pitfalls of a growing reliance upon multivariate quantitation and classification methods.

Employment of Geoscientists in the Private Sector

NASA Astrophysics Data System (ADS)

Russell, J. L.

2001-05-01

In the private sector, major employers of geoscientists engage in diverse activities ranging from resource exploration and extraction, assessment of geologic hazards, and determination of environmental impacts. These firms actively recruit, from the breadth of geoscience disciplines, technically qualified individuals with the ability to make pragmatic decisions in the context of multidisciplinary teams that commonly include non-scientists. Moreover, they expect applicants to communicate effectively verbally and in writing, as well as demonstrate skills and experience in integrating field investigations, conducting laboratory studies, and accomplishing computer modeling. These applicants should be capable of simultaneously working in multiple projects which are rapidly evolving. Successful recruiting and employment requires interactions between the job applicant and potential employer conducted with honesty and integrity. Resumes and associated transmittal letters should be directed to specific employers based on the applicant's review of information on the firm from the Internet and other sources. "Shotgun" or blanket approaches are seldom productive. Participation in pertinent professional societies, internships, and summer employment can provide valuable experiences and opportunities for networking with potential employers.

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

NASA Astrophysics Data System (ADS)

Amenabar, Iban; Poly, Simon; Goikoetxea, Monika; Nuansing, Wiwat; Lasch, Peter; Hillenbrand, Rainer

2017-02-01

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm-1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine.

A real-time algorithm for the harmonic estimation and frequency tracking of dominant components in fusion plasma magnetic diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alves, D.; Coelho, R.; Collaboration: JET-EFDA Contributors

2013-08-15

The real-time tracking of instantaneous quantities such as frequency, amplitude, and phase of components immerse in noisy signals has been a common problem in many scientific and engineering fields such as power systems and delivery, telecommunications, and acoustics for the past decades. In magnetically confined fusion research, extracting this sort of information from magnetic signals can be of valuable assistance in, for instance, feedback control of detrimental magnetohydrodynamic modes and disruption avoidance mechanisms by monitoring instability growth or anticipating mode-locking events. This work is focused on nonlinear Kalman filter based methods for tackling this problem. Similar methods have already provenmore » their merits and have been successfully employed in this scientific domain in applications such as amplitude demodulation for the motional Stark effect diagnostic. In the course of this work, three approaches are described, compared, and discussed using magnetic signals from the Joint European Torus tokamak plasma discharges for benchmarking purposes.« less

A Study on the Assessment of Multi-Factors Affecting Urban Floods Using Satellite Image: A Case Study in Nakdong Basin, S. Korea

NASA Astrophysics Data System (ADS)

Kwak, Youngjoo; Kondoh, Akihiko

2010-05-01

Floods are also related to the changes in social economic conditions and land use. Recently, floods increased due to rapid urbanization and human activity in the lowland. Therefore, integrated management of total basin system is necessary to get the secure society. Typhoon ‘Rusa’ swept through eastern and southern parts of South Korea in the 2002. This pity experience gave us valuable knowledge that could be used to mitigate the future flood hazards. The purpose of this study is to construct the digital maps of the multi-factors related to urban flood concerning geomorphologic characteristics, land cover, and surface wetness. Parameters particularly consider geomorphologic functional unit, geomorphologic parameters derived from DEM (digital elevation model), and land use. The research area is Nakdong River Basin in S. Korea. As a result of preliminary analysis for Pusan area, the vulnerability map and the flood-prone areas can be extracted by applying spatial analysis on GIS (geographic information system).

The Development Of New Space Charge Compensation Methods For Multi-Components Ion Beam Extracted From ECR Ion Source at IMP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, L.; Zhao, H.W.; Cao, Y.

2005-03-15

Two new space charge compensation methods developed in IMP are discussed in this paper. There are negative high voltage electrode method (NHVEM) and electronegative charge gas method (EGM). Some valuable experimental data have been achieved, especially using electronegative gas method in O6+ and O7+ dramatic and stable increasing of ion current was observed.

76 FR 23540 - Proposed Information Collection; Comment Request; Annual Survey of Manufactures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-27

... provides valuable information to private companies, research organizations, and trade associations... DEPARTMENT OF COMMERCE Census Bureau Proposed Information Collection; Comment Request; Annual... information collections, as required by the Paperwork Reduction Act of 1995, Public Law 104-13 (44 U.S.C. 3506...

Study of sulfur bonding on gallium arsenide (100) surfaces using supercritical fluid extraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cabauy, P.; Darici, Y.; Furton, K.G.

1995-12-01

In the last decades Gallium Arsenide (GaAs) has been considered the semiconductor that will replace silicon because of its direct band gap and high electron mobility. Problems with GaAs Fermi level pinning has halted its widespread use in the electronics industry. The formation of oxides on GaAs results in a high density of surface states that effectively pin the surface Fermi level at the midgap. Studies on sulfur passivation have eliminated oxidation and virtually unpinned the Fermi level on the GaAs surface. This has given rise to interest in sulfur-GaAs bonds. In this presentation, we will discuss the types ofmore » sulfur bonds extracted from a sulfur passivated GaAs (100) using Supercritical Fluid (CO2) Extraction (SFE). SFE can be a valuable tool in the study of chemical speciations on semiconductor surfaces. The variables evaluated to effectively study the sulfur species from the GaAs surface include passivation techniques, supercritical fluid temperatures, densities, and extraction times.« less

Deep eutectic solvent-based valorization of spent coffee grounds.

PubMed

Yoo, Da Eun; Jeong, Kyung Min; Han, Se Young; Kim, Eun Mi; Jin, Yan; Lee, Jeongmi

2018-07-30

Spent coffee grounds (SCGs) are viewed as a valuable resource for useful bioactive compounds, such as chlorogenic acids and flavonoids, and we suggest an eco-friendly and efficient valorization method. A series of choline chloride-based deep eutectic solvents (DESs) were tested as green extraction solvents for use with ultrasound-assisted extraction. Extraction efficiency was evaluated based on total phenolic content (TPC), total flavonoid content, total chlorogenic acids, and/or anti-oxidant activity. A binary DES named HC-6, which was composed of 1,6-hexanediol:choline chloride (molar ratio 7:1) was designed to produce the highest efficiency. Experimental conditions were screened and optimized for maximized efficiency using a two-level fractional factorial design and a central composite design, respectively. As a result, the proposed method presented significantly enhanced TPC and anti-oxidant activity. In addition, phenolic compounds could be easily recovered from extracts at high recovery yields (>90%) by adsorption chromatography. Copyright © 2018 Elsevier Ltd. All rights reserved.

Extraction of high added value biological compounds from sardine, sardine-type fish and mackerel canning residues--a review.

PubMed

Ferraro, Vincenza; Carvalho, Ana P; Piccirillo, Clara; Santos, Manuela M; Castro, Paula M L; Pintado, Manuela E

2013-08-01

Different valuable compounds, which can be employed in medicine or in other industries (i.e. food, agrochemical, pharmaceutical) can be recovered from by-products and waste from the fish canning industries. They include lipids, proteins, bio-polymers, minerals, amino acids and enzymes; they can be extracted from wastewaters and/or from solid residues (head, viscera, skin, tails and flesh) generated along the canning process, through the filleting, cooking, salting or smoking stages. In this review, the opportunities for the extraction and the valorisation of bioactive compounds from sardine, sardine-type fish and mackerel canning residues are examined and discussed. These are amongst the most consumed fishes in the Mediterranean area; moreover, canning is one of the most important and common methods of preservation. The large quantities of by-products generated have great potentials for the extraction of biologically desirable high added value compounds. Copyright © 2013 Elsevier B.V. All rights reserved.

Production of astaxanthin rich feed supplement for animals from Phaffia rhodozyma yeast at low cost

NASA Astrophysics Data System (ADS)

Irtiza, Ayesha; Shatunova, Svetlana; Glukhareva, Tatiana; Kovaleva, Elena

2017-09-01

Dietary nutrients such as amino acids, vitamins, minerals and antioxidants can play a significant role in determining meat quality and also the growth rate of poultry or animal. Phaffia rhodozyma was grown on waste from brewery industry to produce astaxanthin rich feed supplements at a very low cost. Phaffia rhodozyma is yeast specie that has ability to produce carotenoids and approximately 80% of its total carotenoid content is astaxanthin, which is highly valuable carotenoid for food, feed and aquaculture industry. This study was carried out to test yeast extract of spent yeast from brewing industry waste (residual yeast) as potential nitrogen source for growth of Phaffia rhodozyma. Cultivation was carried out in liquid media prepared by yeast extracts and other components (glucose and peptone). Carotenoids from the biomass were released into biomass by suspending cells in DMSO for destruction of cells followed by extraction with petroleum ether. The extracted carotenoids were studied by spectrophotometry to identify and quantify astaxanthin and other carotenoids produced.

Chemical characterization and bioactive properties of aqueous and organic extracts of Geranium robertianum L.

PubMed

Graça, V C; Barros, Lillian; Calhelha, Ricardo C; Dias, Maria Inês; Carvalho, Ana Maria; Santos-Buelga, Celestino; Santos, P F; Ferreira, Isabel C F R

2016-09-14

Geranium robertianum L. has been used in folk medicine and herbalism practice for the treatment of various conditions, but the study of its bioactivity has been barely addressed. Although its phytochemical composition has received some attention, contributions to the nutritional composition are practically unknown. Herein, G. robertianum gathered in Trás-os-Montes, Northeastern Portugal, was chemically characterized regarding nutritional parameters, and the antioxidant activity and cytotoxicity against several human tumor cell lines and non-tumor porcine liver primary cells of several aqueous and organic extracts were evaluated. G. robertianum showed to be an equilibrated valuable herb, rich in carbohydrates and proteins, and poor in fat, providing sugars, tocopherols, organic and essential fatty acids. Amongst the extracts, the acetone one showed the highest total phenol and total flavonoid contents, as well as the greatest antioxidant and cytotoxic activities. This extract showed to contain hydrolysable tannins (e.g. geraniin and castalagin/vescalagin), as the main phenolic compounds.

Recovery of Silver and Gold from Copper Anode Slimes

NASA Astrophysics Data System (ADS)

Chen, Ailiang; Peng, Zhiwei; Hwang, Jiann-Yang; Ma, Yutian; Liu, Xuheng; Chen, Xingyu

2015-02-01

Copper anode slimes, produced from copper electrolytic refining, are important industrial by-products containing several valuable metals, particularly silver and gold. This article provides a comprehensive overview of the development of the extraction processes for recovering silver and gold from conventional copper anode slimes. Existing processes, namely pyrometallurgical processes, hydrometallurgical processes, and hybrid processes involving the combination of pyrometallurgical and hydrometallurgical technologies, are discussed based in part on a review of the form and characteristics of silver and gold in copper anode slimes. The recovery of silver and gold in pyrometallurgical processes is influenced in part by the slag and matte/metal chemistry and related characteristics, whereas the extraction of these metals in hydrometallurgical processes depends on the leaching reagents used to break the structure of the silver- and gold-bearing phases, such as selenides. By taking advantage of both pyrometallurgical and hydrometallurgical techniques, high extraction yields of silver and gold can be obtained using such combined approaches that appear promising for efficient extraction of silver and gold from copper anode slimes.

Fast modal extraction in NASTRAN via the FEER computer program. [based on automatic matrix reduction method for lower modes of structures with many degrees of freedom

NASA Technical Reports Server (NTRS)

Newman, M. B.; Pipano, A.

1973-01-01

A new eigensolution routine, FEER (Fast Eigensolution Extraction Routine), used in conjunction with NASTRAN at Israel Aircraft Industries is described. The FEER program is based on an automatic matrix reduction scheme whereby the lower modes of structures with many degrees of freedom can be accurately extracted from a tridiagonal eigenvalue problem whose size is of the same order of magnitude as the number of required modes. The process is effected without arbitrary lumping of masses at selected node points or selection of nodes to be retained in the analysis set. The results of computational efficiency studies are presented, showing major arithmetic operation counts and actual computer run times of FEER as compared to other methods of eigenvalue extraction, including those available in the NASTRAN READ module. It is concluded that the tridiagonal reduction method used in FEER would serve as a valuable addition to NASTRAN for highly increased efficiency in obtaining structural vibration modes.

Sea Cucumbers Metabolites as Potent Anti-Cancer Agents.

PubMed

Janakiram, Naveena B; Mohammed, Altaf; Rao, Chinthalapally V

2015-05-12

Sea cucumbers and their extracts have gained immense popularity and interest among researchers and nutritionists due to their nutritive value, potential health benefits, and use in the treatment of chronic inflammatory diseases. Many areas of the world use sea cucumbers in traditional foods and folk medicine. Though the actual components and their specific functions still remain to be investigated, most sea cucumber extracts are being studied for their anti-inflammatory functions, immunostimulatory properties, and for cancer prevention and treatment. There is large scope for the discovery of additional bioactive, valuable compounds from this natural source. Sea cucumber extracts contain unique components, such as modified triterpene glycosides, sulfated polysaccharides, glycosphingolipids, and esterified phospholipids. Frondanol A5, an isopropyl alcohol/water extract of the enzymatically hydrolyzed epithelia of the edible North Atlantic sea cucumber, Cucumaria frondosa, contains monosulfated triterpenoid glycoside Frondoside A, the disulfated glycoside Frondoside B, the trisulfated glycoside Frondoside C, 12-methyltetradecanoic acid, eicosapentaenoic acid, and fucosylated chondroitin sulfate. We have extensively studied the efficacy of this extract in preventing colon cancer in rodent models. In this review, we discuss the anti-inflammatory, immunostimulatory, and anti-tumor properties of sea cucumber extracts.

Development of green extraction processes for Nannochloropsis gaditana biomass valorization.

PubMed

Sánchez-Camargo, Andrea Del Pilar; Pleite, Natalia; Mendiola, José Antonio; Cifuentes, Alejandro; Herrero, Miguel; Gilbert-López, Bienvenida; Ibáñez, Elena

2018-04-23

In the present work, the valorization of Nannochloropsis gaditana biomass is proposed within the concept of biorefinery. To this aim, high-pressure homogenization (HPH) was used to break down the strong cell wall and supercritical fluid extraction (SFE) with pure CO 2 was applied as a first step to extract valuable compounds (such as non-polar lipids and pigments). Extraction of the remaining residue for the recovery of bioactive compounds was studied by means of an experimental design based on response surface methodology (RSM) employing pressurized liquid extraction (PLE) with green solvents such as water and ethanol. Optimum extract was achieved with pure ethanol at 170°C for 20 min, providing an important antioxidant capacity (0.72 ± 0.03 mmol trolox eq g -1 extract). Complete chemical characterization of the optimum extract was carried out by using different chromatographic methods such as reverse-phase high-performance liquid chromatography with diode array detection (RP-HPLC-DAD), normal-phase HPLC with evaporative light scattering detection (NP-HPLC-ELSD) and gas chromatography coupled to mass spectrometry detection (GC-MS); carotenoids (e.g. violaxanthin), chlorophylls and polar lipids were the main compounds observed while palmitoleic, palmitic, myristic acids and the polyunsaturated eicosapentanoic (EPA) acid were the predominant fatty acids in all PLE extracts. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of Ultrasonic-Assisted Aqueous Two-Phase Extraction of Phloridzin from Malus Micromalus Makino with Ethanol/Ammonia Sulfate System.

PubMed

Zhang, Zhen; Liu, Fang; He, Caian; Yu, Yueli; Wang, Min

2017-12-01

Application of an aqueous two-phase system (ATPS) coupled with ultrasonic technology for the extraction of phloridzin from Malus micromalus Makino was evaluated and optimized by response surface methodology (RSM). The ethanol/ammonium sulfate ATPS was selected for detailed investigation, including the phase diagram, effect of phase composition and extract conditions on the partition of phloridzin, and the recycling of ammonium sulfate. In addition, the evaluation of extraction efficiency and the identification of phloridzin were investigated. The optimal partition coefficient (6.55) and recovery (92.86%) of phloridzin were obtained in a system composed of 35% ethanol (w/w) and 16% (NH 4 ) 2 SO 4 (w/w), 51:1 liquid-to-solid ratio, and extraction temperature of 36 °C. Comparing with the traditional solvent extraction with respective 35% and 80% ethanol, ultrasonic-assisted aqueous two-phase extraction (UAATPE) strategy had significant advantages with lower ethanol consumption, less impurity of sugar and protein, and higher extracting efficiency of phloridzin. Our result indicated that UAATPE was a valuable method for the extraction and preliminary purification of phloridzin from the fruit of Malus micromalus Makino, which has great potential in the deep processing of Malus micromalus Makino industry to increase these fruits' additional value and drive the local economic development. © 2017 Institute of Food Technologists®.

Influence of extraction conditions on antioxidant properties of passion fruit (Passiflora edulis) peel.

PubMed

Wong, Yuh Shan; Sia, Chiaw Mei; Khoo, Hock Eng; Ang, Yee Kwang; Chang, Sui Kiat; Chang, Sui Kiat; Yim, Hip Seng

2014-01-01

As a by-product of tropical fruit juice industry, passion fruit peel is a valuable functional food. It is rich in antioxidants. To determine its potential antioxidant properties of passion fruit peel, this study aimed to evaluate the effect of extraction conditions on total phenolic content and antioxidant activity. The extraction conditions were selected from different percentages of ethanol (0-100%, v/v), extraction times (60-300 min), and extraction temperatures (25-60°C) that based on the optimal percentage of DPPH radical scavenging activity. The selected extraction condition was applied for further determination of total phenolic content (TPC) of the passion fruit peel extract using Folin-Ciocalteu reagent assay, while the antioxidant activities were evaluated using DPPH and ABTS radicals scavenging assays, ferric reducing antioxidant power (FRAP), and β-carotene bleaching (BCB) assay. The best extraction conditions were 40% ethanol, 60 min extraction time, and extraction temperature of 30°C. The chosen extraction conditions have contributed to the high TPC and antioxidant activity of passion fruit peel. The levels of antioxidant activity obtained from the passion fruit peel were also lower compared to BHA and α-tocopherol. Positive correlations were observed between TPC and antioxidant activities as assessed by DPPH, ABTS, FRAP, and BCB assays. As a waste of passion fruit consumption or by-product of fruit juice industry, its peel could be considered as a potential source of natural antioxidant for possible functional food and industrial applications.

Research of information classification and strategy intelligence extract algorithm based on military strategy hall

NASA Astrophysics Data System (ADS)

Chen, Lei; Li, Dehua; Yang, Jie

2007-12-01

Constructing virtual international strategy environment needs many kinds of information, such as economy, politic, military, diploma, culture, science, etc. So it is very important to build an information auto-extract, classification, recombination and analysis management system with high efficiency as the foundation and component of military strategy hall. This paper firstly use improved Boost algorithm to classify obtained initial information, then use a strategy intelligence extract algorithm to extract strategy intelligence from initial information to help strategist to analysis information.

Test Expectancy and Memory for Important Information

PubMed Central

Middlebrooks, Catherine D.; Murayama, Kou; Castel, Alan D.

2016-01-01

Prior research suggests that learners study and remember information differently depending upon the type of test they expect to later receive. The current experiments investigate how testing expectations impact the study of and memory for valuable information. Participants studied lists of words ranging in value from 1–10 points with the goal being to maximize their score on a later memory test. Half of the participants were told to expect a recognition test after each list, while the other half were told to expect a recall test. After several lists of receiving tests congruent with expectations, participants studying for a recognition test instead received an unexpected recall test. In Experiment 1, participants who had studied for a recognition test recalled less of the valuable information than participants anticipating the recall format. These participants continued to attend less to item value on future (expected) recall tests than participants who had only ever experienced recall testing. When the recognition tests were made more demanding in Experiment 2, value-based recall improved relative to Experiment 1: though memory for the valuable information remained superior when participants studied with the expectation of having to recall the information, there were no longer significant differences after accounting for recall testing experience. Thus, recall-based testing encouraged strategic, value-based encoding and enhanced retrieval of important information, while recognition testing in some cases limited value-based study and memory. These results extend prior work concerning the impact of testing expectations on memory, offering further insight into how people study important information. PMID:28095010

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

Foundations of Full Text Electronic Information Delivery Systems. Implications for Information Professionals.

ERIC Educational Resources Information Center

Kibirige, Harry M.

Information has become an increasingly valuable commodity. Access to full-text information, containing text, images, and in some cases, sound, is becoming vital to decision-making for organizations as well as individuals. The book covers the following topics: (1) the information marketplace in a cyberculture; (2) the telecommunications foundation…

Herbivory by the insect diaphorina citri induces greater change in citrus plant volatile profile than does infection by the bacterium, Candidatus Liberibacter asiaticus

PubMed Central

Hijaz, Faraj; El-Shesheny, Ibrahim; Killiny, Nabil

2013-01-01

The volatile organic compound (VOC) profile in plant leaves often changes after biotic and abiotic stresses. Monitoring changes in VOCs in plant leaves could provide valuable information about multitrophic interactions. In the current study, we investigated the effect of Asian citrus psyllid (ACP) infestation, citrus greening pathogen (Candidatus Liberibacter asiaticus [CLas]) infection, and simultaneous attack by ACP and CLas on the VOC content of citrus leaves. Leaf volatiles were extracted using hexane and analyzed with gas chromatography-mass spectrometry (GC-MS). Although ACP is a phloem-sucking insect that causes minimal damage to plant tissues, the relative amount of 21 out of the 27 VOCs increased 2- to 10-fold in ACP-infested plants. The relative amount of d-limonene, β-phelandrene, citronellal, and undecanal were increased 4- to 20- fold in CLas-infected plants. A principle component analysis (PCA) and cluster analysis (CA) showed that VOC patterns of ACP-infested and CLas-infected plants were different from each other and were also different from the controls, while the VOC pattern of double-attacked plants was more like that of the controls than that of ACP-infested or CLas-infected plants. VOC amounts from leaves were compromised when plants were attacked by ACP and CLas. The results of this study showed that a simple direct extraction of citrus leaf volatiles could be successfully used to discriminate between healthy and CLas-infected plants. Information about the effects of insect and pathogen attack on the VOC content profile of plants might contribute to a better understanding of biotic stress. PMID:23857364

Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery

USGS Publications Warehouse

Hatten, James R.

2014-01-01

The Mount Graham red squirrel (Tamiasciurus hudsonicus grahamensis) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.

Herbivory by the insect diaphorina citri induces greater change in citrus plant volatile profile than does infection by the bacterium, Candidatus Liberibacter asiaticus.

PubMed

Hijaz, Faraj; El-Shesheny, Ibrahim; Killiny, Nabil

2013-10-01

The volatile organic compound (VOC) profile in plant leaves often changes after biotic and abiotic stresses. Monitoring changes in VOCs in plant leaves could provide valuable information about multitrophic interactions. In the current study, we investigated the effect of Asian citrus psyllid (ACP) infestation, citrus greening pathogen (Candidatus Liberibacter asiaticus [CLas]) infection, and simultaneous attack by ACP and CLas on the VOC content of citrus leaves. Leaf volatiles were extracted using hexane and analyzed with gas chromatography-mass spectrometry (GC-MS). Although ACP is a phloem-sucking insect that causes minimal damage to plant tissues, the relative amount of 21 out of the 27 VOCs increased 2- to 10-fold in ACP-infested plants. The relative amount of d-limonene, β-phelandrene, citronellal, and undecanal were increased 4- to 20- fold in CLas-infected plants. A principle component analysis (PCA) and cluster analysis (CA) showed that VOC patterns of ACP-infested and CLas-infected plants were different from each other and were also different from the controls, while the VOC pattern of double-attacked plants was more like that of the controls than that of ACP-infested or CLas-infected plants. VOC amounts from leaves were compromised when plants were attacked by ACP and CLas. The results of this study showed that a simple direct extraction of citrus leaf volatiles could be successfully used to discriminate between healthy and CLas-infected plants. Information about the effects of insect and pathogen attack on the VOC content profile of plants might contribute to a better understanding of biotic stress.

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods.

PubMed

Salvatore, Stefania; Bramness, Jørgen Gustav; Reid, Malcolm J; Thomas, Kevin Victor; Harman, Christopher; Røislien, Jo

2015-01-01

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

Construction of an annotated corpus to support biomedical information extraction

PubMed Central

Thompson, Paul; Iqbal, Syed A; McNaught, John; Ananiadou, Sophia

2009-01-01

Background Information Extraction (IE) is a component of text mining that facilitates knowledge discovery by automatically locating instances of interesting biomedical events from huge document collections. As events are usually centred on verbs and nominalised verbs, understanding the syntactic and semantic behaviour of these words is highly important. Corpora annotated with information concerning this behaviour can constitute a valuable resource in the training of IE components and resources. Results We have defined a new scheme for annotating sentence-bound gene regulation events, centred on both verbs and nominalised verbs. For each event instance, all participants (arguments) in the same sentence are identified and assigned a semantic role from a rich set of 13 roles tailored to biomedical research articles, together with a biological concept type linked to the Gene Regulation Ontology. To our knowledge, our scheme is unique within the biomedical field in terms of the range of event arguments identified. Using the scheme, we have created the Gene Regulation Event Corpus (GREC), consisting of 240 MEDLINE abstracts, in which events relating to gene regulation and expression have been annotated by biologists. A novel method of evaluating various different facets of the annotation task showed that average inter-annotator agreement rates fall within the range of 66% - 90%. Conclusion The GREC is a unique resource within the biomedical field, in that it annotates not only core relationships between entities, but also a range of other important details about these relationships, e.g., location, temporal, manner and environmental conditions. As such, it is specifically designed to support bio-specific tool and resource development. It has already been used to acquire semantic frames for inclusion within the BioLexicon (a lexical, terminological resource to aid biomedical text mining). Initial experiments have also shown that the corpus may viably be used to train IE components, such as semantic role labellers. The corpus and annotation guidelines are freely available for academic purposes. PMID:19852798

Analyzing jobs for redesign decisions.

PubMed

Conn, V S; Davis, N K; Occena, L G

1996-01-01

Job analysis, the collection and interpretation of information that describes job behaviors and activities performed by occupants of jobs, can provide nurse administrators with valuable information for redesigning effective and efficient systems of care.

Emotional voices in context: A neurobiological model of multimodal affective information processing

NASA Astrophysics Data System (ADS)

Brück, Carolin; Kreifelts, Benjamin; Wildgruber, Dirk

2011-12-01

Just as eyes are often considered a gateway to the soul, the human voice offers a window through which we gain access to our fellow human beings' minds - their attitudes, intentions and feelings. Whether in talking or singing, crying or laughing, sighing or screaming, the sheer sound of a voice communicates a wealth of information that, in turn, may serve the observant listener as valuable guidepost in social interaction. But how do human beings extract information from the tone of a voice? In an attempt to answer this question, the present article reviews empirical evidence detailing the cerebral processes that underlie our ability to decode emotional information from vocal signals. The review will focus primarily on two prominent classes of vocal emotion cues: laughter and speech prosody (i.e. the tone of voice while speaking). Following a brief introduction, behavioral as well as neuroimaging data will be summarized that allows to outline cerebral mechanisms associated with the decoding of emotional voice cues, as well as the influence of various context variables (e.g. co-occurring facial and verbal emotional signals, attention focus, person-specific parameters such as gender and personality) on the respective processes. Building on the presented evidence, a cerebral network model will be introduced that proposes a differential contribution of various cortical and subcortical brain structures to the processing of emotional voice signals both in isolation and in context of accompanying (facial and verbal) emotional cues.

An application programming interface for extreme precipitation and hazard products

NASA Astrophysics Data System (ADS)

Kirschbaum, D.; Stanley, T.; Cappelaere, P. G.; Reed, J.; Lammers, M.

2016-12-01

Remote sensing data provides situational awareness of extreme events and hazards over large areas in a way that is impossible to achieve with in situ data. However, more valuable than raw data is actionable information based on user needs. This information can take the form of derived products, extraction of a subset of variables in a larger data matrix, or data processing for a specific goal. These products can then stream to the end users, who can use these data to improve local to global decision making. This presentation will outline both the science and methodology of two new data products and tools that can provide relevant climate and hazard data for response and support. The Global Precipitation Measurement (GPM) mission provides near real-time information on rain and snow around the world every thirty minutes. Through a new applications programing interface (API), this data can be freely accessed by consumers to visualize, analyze, and communicate where, when and how much rain is falling worldwide. The second tool is a global landslide model that provides situational awareness of potential landslide activity in near real-time, utilizing several remotely sensed data products. This hazard information is also provided through an API and is being ingested by the emergency response community, international aid organizations, and others around the world. This presentation will highlight lessons learned through the development, implementation, and communication of these products and tools with the goal of enabling better and more effective decision making.

Capturing Accurate and Useful Information on Medication-Related Telenursing Triage Calls.

PubMed

Lake, R; Li, L; Baysari, M; Byrne, M; Robinson, M; Westbrook, J I

2016-01-01

Registered nurses providing telenursing triage and advice services record information on the medication related calls they handle. However the quality and consistency of these data were rarely examined. Our aim was to examine medication related calls made to the healthdirect advice service in November 2014, to assess their basic characteristics and how the data entry format influenced information collected and data consistency. Registered nurses selected the patient question type from a range of categories, and entered the medications involved in a free text field. Medication names were manually extracted from the free text fields. We also compared the selected patient question type with the free text description of the call, in order to gauge data consistency. Results showed that nurses provided patients with advice on medication-related queries in a timely matter (the median call duration of 9 minutes). From 1835 calls, we were able to identify and classify 2156 medications into 384 generic names. However, in 204 cases (11.2% of calls) no medication name was entered. A further 308 (15.0%) of the medication names entered were not identifiable. When we compared the selected patient question with the free text description of calls, we found that these were consistent in 63.27% of cases. Telenursing and triage advice services provide a valuable resource to the public with quick and easily accessible advice. To support nurses provide quality services and record accurate information about the queries, appropriate data entry format and design would be beneficial.

Emotional voices in context: a neurobiological model of multimodal affective information processing.

PubMed

Brück, Carolin; Kreifelts, Benjamin; Wildgruber, Dirk

2011-12-01

Just as eyes are often considered a gateway to the soul, the human voice offers a window through which we gain access to our fellow human beings' minds - their attitudes, intentions and feelings. Whether in talking or singing, crying or laughing, sighing or screaming, the sheer sound of a voice communicates a wealth of information that, in turn, may serve the observant listener as valuable guidepost in social interaction. But how do human beings extract information from the tone of a voice? In an attempt to answer this question, the present article reviews empirical evidence detailing the cerebral processes that underlie our ability to decode emotional information from vocal signals. The review will focus primarily on two prominent classes of vocal emotion cues: laughter and speech prosody (i.e. the tone of voice while speaking). Following a brief introduction, behavioral as well as neuroimaging data will be summarized that allows to outline cerebral mechanisms associated with the decoding of emotional voice cues, as well as the influence of various context variables (e.g. co-occurring facial and verbal emotional signals, attention focus, person-specific parameters such as gender and personality) on the respective processes. Building on the presented evidence, a cerebral network model will be introduced that proposes a differential contribution of various cortical and subcortical brain structures to the processing of emotional voice signals both in isolation and in context of accompanying (facial and verbal) emotional cues. Copyright © 2011 Elsevier B.V. All rights reserved.

Extraction and purification of high added value compounds from by-products of the winemaking chain using alternative/nonconventional processes/technologies.

PubMed

Yammine, Sami; Brianceau, Sylène; Manteau, Sébastien; Turk, Mohammad; Ghidossi, Rémy; Vorobiev, Eugène; Mietton-Peuchot, Martine

2018-05-24

Grape byproducts are today considered as a cheap source of valuable compounds since existent technologies allow the recovery of target compounds and their recycling. The goal of the current article is to explore the different recovery stages used by both conventional and alternative techniques and processes. Alternative pre-treatments techniques reviewed are: ultrasounds, pulsed electric fields and high voltage discharges. In addition, nonconventional solvent extraction under high pressure, specifically, supercritical fluid extraction and subcritical water extraction are discussed. Finally alternative purification technologies, for example membrane processing were also examined. The intent is to describe the mechanisms involved by these alternative technologies and to summarize the work done on the improvement of the extraction process of phenolic compounds from winery by-products. With a focus on the developmental stage of each technology, highlighting the research need and challenges to be overcome for an industrial implementation of these unitary operations in the overall extraction process. A critical comparison of conventional and alternative techniques will be reviewed for ethe pre-treatment of raw material, the diffusion of polyphenols and the purification of these high added value compounds. This review intends to give the reader some key answers (costs, advantages, drawbacks) to help in the choice of alternative technologies for extraction purposes.

Dengue fever treatment with Carica papaya leaves extracts

PubMed Central

Ahmad, Nisar; Fazal, Hina; Ayaz, Muhammad; Abbasi, Bilal Haider; Mohammad, Ijaz; Fazal, Lubna

2011-01-01

The main objective of the current study is to investigate the potential of Carica papaya leaves extracts against Dengue fever in 45 year old patient bitten by carrier mosquitoes. For the treatment of Dengue fever the extract was prepared in water. 25 mL of aqueous extract of C. papaya leaves was administered to patient infected with Dengue fever twice daily i.e. morning and evening for five consecutive days. Before the extract administration the blood samples from patient were analyzed. Platelets count (PLT), White Blood Cells (WBC) and Neutrophils (NEUT) decreased from 176×103/µL, 8.10×103/µL, 84.0% to 55×103/µL, 3.7×103/µL and 46.0%. Subsequently, the blood samples were rechecked after the administration of leaves extract. It was observed that the PLT count increased from 55×103/µL to 168×103/µL, WBC from 3.7×103/µL to 7.7×103/µL and NEUT from 46.0% to 78.3%. From the patient feelings and blood reports it showed that Carica papaya leaves aqueous extract exhibited potential activity against Dengue fever. Furthermore, the different parts of this valuable specie can be further used as a strong natural candidate against viral diseases. PMID:23569787

Comprehensive process for the recovery of value and critical materials from electronic waste

DOE PAGES

Diaz, Luis A.; Lister, Tedd E.; Parkman, Jacob A.; ...

2016-04-08

The development of technologies that contribute to the proper disposal and treatment of electronic waste is not just an environmental need, but an opportunity for the recovery and recycle of valuable metals and critical materials. Value elements in electronic waste include gold, palladium, silver, copper, nickel, and rare earth elements (RE). Here, we present the development of a process that enables efficient recycling of metals from scrap mobile electronics. An electro recycling (ER) process, based on the regeneration of Fe 3+ as a weak oxidizer, is studied for the selective recovery of base metals while leaving precious metals for separatemore » extraction at reduced chemical demand. A separate process recovers rare earth oxides from magnets in electronics. Furthermore, recovery and extraction efficiencies ca. 90 % were obtained for the extraction of base metals from the non-ferromagnetic fraction in the two different solution matrices tested (H 2SO 4, and HCl). The effect of the pre-extraction of base metals in the increase of precious metals extraction efficiency was verified. On the other hand, the extraction of rare earths from the ferromagnetic fraction, performed by means of anaerobic extraction in acid media, was assessed for the selective recovery of rare earths. We developed a comprehensive flow sheet to process electronic waste to value products.« less

ARTSY-J: Convenient and precise measurement of 3JHNHα couplings in medium-size proteins from TROSY-HSQC spectra

NASA Astrophysics Data System (ADS)

Roche, Julien; Ying, Jinfa; Shen, Yang; Torchia, Dennis A.; Bax, Ad

2016-07-01

A new and convenient method, named ARTSY-J, is introduced that permits extraction of the 3JHNHα couplings in proteins from the relative intensities in a pair of 15N-1H TROSY-HSQC spectra. The pulse scheme includes 3JHNHα dephasing of the narrower TROSY 1HN-{15N} doublet component during a delay, integrated into the regular two-dimensional TROSY-HSQC pulse scheme, and compares the obtained intensity with a reference spectrum where 3JHNHα dephasing is suppressed. The effect of passive 1Hα spin flips downscales the apparent 3JHNHα coupling by a uniform factor that depends approximately linearly on both the duration of the 3JHNHα dephasing delay and the 1H-1H cross relaxation rate. Using such a correction factor, which accounts for the effects of both inhomogeneity of the radiofrequency field and 1Hα spin flips, agreement between prior and newly measured values for the small model protein GB3 is better than 0.3 Hz. Measurement for the HIV-1 protease homodimer (22 kDa) yields 3JHNHα values that agree to better than 0.7 Hz with predictions made on the basis of a previously parameterized Karplus equation. Although for Gly residues the two individual 3JHNHα couplings cannot be extracted from a single set of ARTSY-J spectra, the measurement provides valuable ϕ angle information.

Synchrotron x-ray microdiffraction reveals intrinsic structural features of amyloid deposits in situ.

PubMed

Briki, Fatma; Vérine, Jérôme; Doucet, Jean; Bénas, Philippe; Fayard, Barbara; Delpech, Marc; Grateau, Gilles; Riès-Kautt, Madeleine

2011-07-20

Amyloidoses are increasingly recognized as a major public health concern in Western countries. All amyloidoses share common morphological, structural, and tinctorial properties. These consist of staining by specific dyes, a fibrillar aspect in electron microscopy and a typical cross-β folding in x-ray diffraction patterns. Most studies that aim at deciphering the amyloid structure rely on fibers generated in vitro or extracted from tissues using protocols that may modify their intrinsic structure. Therefore, the fine details of the in situ architecture of the deposits remain unknown. Here, we present to our knowledge the first data obtained on ex vivo human renal tissue sections using x-ray microdiffraction. The typical cross-β features from fixed paraffin-embedded samples are similar to those formed in vitro or extracted from tissues. Moreover, the fiber orientation maps obtained across glomerular sections reveal an intrinsic texture that is correlated with the glomerulus morphology. These results are of the highest importance to understanding the formation of amyloid deposits and are thus expected to trigger new incentives for tissue investigation. Moreover, the access to intrinsic structural parameters such as fiber size and orientation using synchrotron x-ray microdiffraction, could provide valuable information concerning in situ mechanisms and deposit formation with potential benefits for diagnostic and therapeutic purposes. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.