Three Sisters Dam modifications and performance

Energy Technology Data Exchange (ETDEWEB)

Courage, L.J.R. [Monenco AGRA Inc., Calgary, AB (Canada)

1995-12-31

Recent modifications and maintenance carried out at the Three Sisters Dam, in the Alberta Rockies south of the town of Canmore, were described. A detailed account was given of the dam`s geological setting, its abnormally high leakage through the foundation and its sinkhole activity. Results of studies aimed at finding the cause of leakage and sinkhole occurrences were reviewed. Modifications made to the dam since 1951 were detailed, as were modifications to handle probable maximum flood levels. Three approaches for estimating failure probabilities after identification of failure modes were described. The overall conclusion was that based on constant leakage, no settlement in the dam, penstocks, or the powerhouse since construction, the Three Sisters Dam was stable. 1 ref.

George and the big bang

CERN Document Server

Hawking, Lucy; Parsons, Gary

2012-01-01

George has problems. He has twin baby sisters at home who demand his parents’ attention. His beloved pig Freddy has been exiled to a farm, where he’s miserable. And worst of all, his best friend, Annie, has made a new friend whom she seems to like more than George. So George jumps at the chance to help Eric with his plans to run a big experiment in Switzerland that seeks to explore the earliest moment of the universe. But there is a conspiracy afoot, and a group of evildoers is planning to sabotage the experiment. Can George repair his friendship with Annie and piece together the clues before Eric’s experiment is destroyed forever? This engaging adventure features essays by Professor Stephen Hawking and other eminent physicists about the origins of the universe and ends with a twenty-page graphic novel that explains how the Big Bang happened—in reverse!

‘Big Books’ as Mother Tongue-Based Instructional Materials in Bicol for Grade One Pupils

Directory of Open Access Journals (Sweden)

Magdalena M. Ocbian,

2015-11-01

Full Text Available Language experts claim that it is easier for pupils to learn when the mother tongue is used in the teaching learning process including the learning of a second language. This study determined the reading comprehension level of Grade I pupils in Bulusan Central School for school year 2013-2014 as input in developing big books written in the vernacular that can be used as reading materials for Grade 1 pupils. Results of the evaluation revealed that they belong to the frustration and instructional levels in the literal skill; mostly are frustration readers along interpretative and evaluative skills; but are independent readers along applied skills; hence, they have low level of reading comprehension. Based on the result of the study, three big books as MTB-MLE instructional materials in Bicol were produced to develop or enhance Grade 1 pupils’ reading comprehension. Teaching guides were likewise developed.

The Big Data Tools Impact on Development of Simulation-Concerned Academic Disciplines

Directory of Open Access Journals (Sweden)

A. A. Sukhobokov

2015-01-01

Full Text Available The article gives a definition of Big Data on the basis of 5V (Volume, Variety, Velocity, Veracity, Value as well as shows examples of tasks that require using Big Data tools in a diversity of areas, namely: health, education, financial services, industry, agriculture, logistics, retail, information technology, telecommunications and others. An overview of Big Data tools is delivered, including open source products, IBM Bluemix and SAP HANA platforms. Examples of architecture of corporate data processing and management systems using Big Data tools are shown for big Internet companies and for enterprises in traditional industries. Within the overview, a classification of Big Data tools is proposed that fills gaps of previously developed similar classifications. The new classification contains 19 classes and allows embracing several hundreds of existing and emerging products.The uprise and use of Big Data tools, in addition to solving practical problems, affects the development of scientific disciplines concerning the simulation of technical, natural or socioeconomic systems and the solution of practical problems based on developed models. New schools arise in these disciplines. These new schools decide peculiar to each discipline tasks, but for systems with a much bigger number of internal elements and connections between them. Characteristics of the problems to be solved under new schools, not always meet the criteria for Big Data. It is suggested to identify the Big Data as a part of the theory of sorting and searching algorithms. In other disciplines the new schools are called by analogy with Big Data: Big Calculation in numerical methods, Big Simulation in imitational modeling, Big Management in the management of socio-economic systems, Big Optimal Control in the optimal control theory. The paper shows examples of tasks and methods to be developed within new schools. The educed tendency is not limited to the considered disciplines: there are

Flexibility in faculty work-life policies at medical schools in the Big Ten conference.

Science.gov (United States)

Welch, Julie L; Wiehe, Sarah E; Palmer-Smith, Victoria; Dankoski, Mary E

2011-05-01

Women lag behind men in several key academic indicators, such as advancement, retention, and securing leadership positions. Although reasons for these disparities are multifactorial, policies that do not support work-life integration contribute to the problem. The objective of this descriptive study was to compare the faculty work-life policies among medical schools in the Big Ten conference. Each institution's website was accessed in order to assess its work-life policies in the following areas: maternity leave, paternity leave, adoption leave, extension of probationary period, part-time appointments, part-time benefits (specifically health insurance), child care options, and lactation policy. Institutions were sent requests to validate the online data and supply additional information if needed. Each institution received an overall score and subscale scores for family leave policies and part-time issues. Data were verified by the human resources office at 8 of the 10 schools. Work-life policies varied among Big Ten schools, with total scores between 9.25 and 13.5 (possible score: 0-21; higher scores indicate greater flexibility). Subscores were not consistently high or low within schools. Comparing the flexibility of faculty work-life policies in relation to other schools will help raise awareness of these issues and promote more progressive policies among less progressive schools. Ultimately, flexible policies will lead to greater equity and institutional cultures that are conducive to recruiting, retaining, and advancing diverse faculty.

Teenage pregnancy: the impact of maternal adolescent childbearing and older sister's teenage pregnancy on a younger sister.

Science.gov (United States)

Wall-Wieler, Elizabeth; Roos, Leslie L; Nickel, Nathan C

2016-05-25

Risk factors for teenage pregnancy are linked to many factors, including a family history of teenage pregnancy. This research examines whether a mother's teenage childbearing or an older sister's teenage pregnancy more strongly predicts teenage pregnancy. This study used linkable administrative databases housed at the Manitoba Centre for Health Policy (MCHP). The original cohort consisted of 17,115 women born in Manitoba between April 1, 1979 and March 31, 1994, who stayed in the province until at least their 20(th) birthday, had at least one older sister, and had no missing values on key variables. Propensity score matching (1:2) was used to create balanced cohorts for two conditional logistic regression models; one examining the impact of an older sister's teenage pregnancy and the other analyzing the effect of the mother's teenage childbearing. The adjusted odds of becoming pregnant between ages 14 and 19 for teens with at least one older sister having a teenage pregnancy were 3.38 (99 % CI 2.77-4.13) times higher than for women whose older sister(s) did not have a teenage pregnancy. Teenage daughters of mothers who had their first child before age 20 had 1.57 (99 % CI 1.30-1.89) times higher odds of pregnancy than those whose mothers had their first child after age 19. Educational achievement was adjusted for in a sub-population examining the odds of pregnancy between ages 16 and 19. After this adjustment, the odds of teenage pregnancy for teens with at least one older sister who had a teenage pregnancy were reduced to 2.48 (99 % CI 2.01-3.06) and the odds of pregnancy for teen daughters of teenage mothers were reduced to 1.39 (99 % CI 1.15-1.68). Although both were significant, the relationship between an older sister's teenage pregnancy and a younger sister's teenage pregnancy is much stronger than that between a mother's teenage childbearing and a younger daughter's teenage pregnancy. This study contributes to understanding of the broader topic "who is

Consumerism and the Sister Carrie's American Dream%Consumerism and the Sister Carrie''s American Dream

Institute of Scientific and Technical Information of China (English)

卢亚丽

2017-01-01

From the aspect of consumerism to this text analyze Sister Carrie's"American dream"destruction. The author wholly and deeply analyzes the embodiment of consumerism in Dreiser's Sister Carrie and Dreiser's outlook and values under the effect of consumerism. To prove that the reason for destruction of Carrie's American dream is consumerism.

Geographic variance of cardiovascular risk factors among community women: the national Sister to Sister campaign.

Science.gov (United States)

Jarvie, Jennifer L; Johnson, Caitlin E; Wang, Yun; Wan, Yun; Aslam, Farhan; Athanasopoulos, Leonidas V; Pollin, Irene; Foody, JoAnne M

2011-01-01

There are substantial variations in cardiovascular disease (CVD) risk and outcomes among women. We sought to determine geographic variation in risk factor prevalence in a contemporary sample of U.S. women. Using 2008-2009 Sister to Sister (STS) free heart screening data from 17 U.S. cities, we compared rates of obesity (body mass index [BMI] ≥30 kg/m(2)), hypertension (HTN ≥140/90 mm Hg), low high-density lipoprotein cholesterol (HDL-C cities had higher rates of hyperglycemia and low HDL-C. In a large, community-based sample of women nationwide, this comprehensive analysis shows remarkable geographic variation in risk factors, which provides opportunities to improve and reduce a woman's CVD risk. Further investigation is required to understand the reasons behind such variation, which will provide insight toward tailoring preventive interventions to narrow gaps in CVD risk reduction in women.

Somatomedin C deficiency in Asian sisters.

OpenAIRE

McGraw, M E; Price, D A; Hill, D J

1986-01-01

Two sisters of Asian origin showed typical clinical and biochemical features of primary somatomedin C (SM-C) deficiency (Laron dwarfism). Abnormalities of SM-C binding proteins were observed, one sister lacking the high molecular weight (150 Kd) protein.

Eruptive history of South Sister, Oregon Cascades

Science.gov (United States)

Fierstein, J.; Hildreth, W.; Calvert, A.T.

2011-01-01

South Sister is southernmost and highest of the Three Sisters, three geologically dissimilar stratovolcanoes that together form a spectacular 20km reach along the Cascade crest in Oregon. North Sister is a monotonously mafic edifice as old as middle Pleistocene, Middle Sister a basalt-andesite-dacite cone built between 48 and 14ka, and South Sister is a basalt-free edifice that alternated rhyolitic and intermediate modes from 50ka to 2ka (largely contemporaneous with Middle Sister). Detailed mapping, 330 chemical analyses, and 42 radioisotopic ages show that the oldest exposed South Sister lavas were initially rhyolitic ~50ka. By ~37ka, rhyolitic lava flows and domes (72-74% SiO2) began alternating with radially emplaced dacite (63-68% SiO2) and andesite (59-63% SiO2) lava flows. Construction of a broad cone of silicic andesite-dacite (61-64% SiO2) culminated ~30ka in a dominantly explosive sequence that began with crater-forming andesitic eruptions that left fragmental deposits at least 200m thick. This was followed at ~27ka by growth of a steeply dipping summit cone of agglutinate-dominated andesite (56-60.5% SiO2) and formation of a summit crater ~800m wide. This crater was soon filled and overtopped by a thick dacite lava flow and then by >150m of dacitic pyroclastic ejecta. Small-volume dacite lavas (63-67% SiO2) locally cap the pyroclastic pile. A final sheet of mafic agglutinate (54-56% SiO2) - the most mafic product of South Sister - erupted from and drapes the small (300-m-wide) present-day summit crater, ending a summit-building sequence that lasted until ~22ka. A 20kyr-long-hiatus was broken by rhyolite eruptions that produced (1) the Rock Mesa coulee, tephra, and satellite domelets (73.5% SiO2) and (2) the Devils Chain of ~20 domes and short coulees (72.3-72.8% SiO2) from N-S vent alignments on South Sister's flanks. The compositional reversal from mafic summit agglutinate to recent rhyolites epitomizes the frequently changing compositional modes of the

GNE Myopathy in Turkish Sisters with a Novel Homozygous Mutation

Science.gov (United States)

Diniz, Gulden; Secil, Yaprak; Ceylaner, Serdar; Tokucoglu, Figen; Türe, Sabiha; Celebisoy, Mehmet; İncesu, Tülay Kurt; Akhan, Galip

2016-01-01

Background. Hereditary inclusion body myopathy is caused by biallelic defects in the GNE gene located on chromosome 9p13. It generally affects adults older than 20 years of age. Methods and Results. In this study, we present two Turkish sisters with progressive myopathy and describe a novel mutation in the GNE gene. Both sisters had slightly higher levels of creatine kinase (CK) and muscle weakness. The older sister presented at 38 years of age with an inability to climb steps, weakness, and a steppage gait. Her younger sister was 36 years old and had similar symptoms. The first symptoms of the disorder were seen when the sisters were 30 and 34 years old, respectively. The muscle biopsy showed primary myopathic features and presence of rimmed vacuoles. DNA analysis demonstrated the presence of previously unknown homozygous mutations [c.2152 G>A (p.A718T)] in the GNE genes. Conclusion. Based on our literature survey, we believe that ours is the first confirmed case of primary GNE myopathy with a novel missense mutation in Turkey. These patients illustrate that the muscle biopsy is still an important method for the differential diagnosis of vacuolar myopathies in that the detection of inclusions is required for the definitive diagnosis. PMID:27298745

"Innovation on big data for healthy living" | Summer School | 27 June - 6 July 2016

CERN Multimedia

2016-01-01

IBD4Health explores advanced topics related to big data computing and analytics for health and wellbeing, with a focus on innovation and entrepreneurial awareness.     Innovation on big data for healthy living A bioHC Summer School 27 June - 6 July 2016  European Scientific Institute, Archamps, Haute-Savoie Through an interactive case study on obesity, participants will be invited to discover diverse data sources and on-going efforts to develop new tools for large-scale data processing, thus providing a path for in-depth analysis of different causal and contributory factors as a means to supporting the development of optimized interventions and public health approaches to tackle obesity. Participants will also be introduced to Creative Thinking and applied Design Thinking with the opportunity to present (pitch) their ideas in front of a panel of business experts. School faculty include academic and industrial experts from France, the Netherlands, Slovenia, Spain, Sweden and Swit...

Negative Effects of School-Average Achievement on Academic Self-Concept: A Comparison of the Big-Fish-Little-Pond Effect across Australian States and Territories

Science.gov (United States)

Marsh, Herbert W.

2004-01-01

Attending academically selective schools is intended to have positive effects, but a growing body of theoretical and empirical research demonstrates that the effects are negative for academic self-concept. The big-fish-little-pond effect (BFLPE), based on social comparison theory, posits that equally able students will have lower academic…

Big bang models in string theory

Energy Technology Data Exchange (ETDEWEB)

Craps, Ben [Theoretische Natuurkunde, Vrije Universiteit Brussel and The International Solvay Institutes Pleinlaan 2, B-1050 Brussels (Belgium)

2006-11-07

These proceedings are based on lectures delivered at the 'RTN Winter School on Strings, Supergravity and Gauge Theories', CERN, 16-20 January 2006. The school was mainly aimed at PhD students and young postdocs. The lectures start with a brief introduction to spacetime singularities and the string theory resolution of certain static singularities. Then they discuss attempts to resolve cosmological singularities in string theory, mainly focusing on two specific examples: the Milne orbifold and the matrix big bang.

Developing skills in clinical leadership for ward sisters.

Science.gov (United States)

Fenton, Katherine; Phillips, Natasha

The Francis report has called for a strengthening of the ward sister's role. It recommends that sisters should operate in a supervisory capacity and should not be office bound. Effective ward leadership has been recognised as being vital to high-quality patient care and experience, resource management and interprofessional working. However, there is evidence that ward sisters are ill equipped to lead effectively and lack confidence in their ability to do so. University College London Hospitals Foundation Trust has recognised that the job has become almost impossible in increasingly large and complex organisations. Ward sisters spend less than 40% of their time on clinical leadership and the trust is undertaking a number of initiatives to support them in this role.

The Big Fish Down Under: Examining Moderators of the "Big-Fish-Little-Pond" Effect for Australia's High Achievers

Science.gov (United States)

Seaton, Marjorie; Marsh, Herbert W.; Yeung, Alexander Seeshing; Craven, Rhonda

2011-01-01

Big-fish-little-pond effect (BFLPE) research has demonstrated that academic self-concept is negatively affected by attending high-ability schools. This article examines data from large, representative samples of 15-year-olds from each Australian state, based on the three Program for International Student Assessment (PISA) databases that focus on…

Consumerism and the Sister Carrie's American Dream

Institute of Scientific and Technical Information of China (English)

卢亚丽

2017-01-01

From the aspect of consumerism to this text analyze Sister Carrie's"American dream"destruction. The author wholly and deeply analyzes the embodiment of consumerism in Dreiser's Sister Carrie and Dreiser's outlook and values under the effect of consumerism. To prove that the reason for destruction of Carrie's American dream is consumerism.

'For Good, God, and the Empire': French Franciscan Sisters in Ethiopia 1896-1937

Science.gov (United States)

Guidi, Pierre

2018-01-01

In 1897, four French Franciscan sisters arrived in Ethiopia, having been summoned there by the Capuchin missionaries. In 1925, they ran an orphanage, a dispensary, a leper colony and 10 schools with 350 girl students. The students were freed slaves, orphans and upper-class Ethiopian and European girls. After providing a brief background to the…

Big Data Based Analysis Framework for Product Manufacturing and Maintenance Process

OpenAIRE

Zhang , Yingfeng; Ren , Shan

2015-01-01

Part 8: Cloud-Based Manufacturing; International audience; With the widely use of smart sensor devices in the product lifecycle management (PLM), it creates amount of real-time and muti-source lifecycle big data. These data allow decision makers to make better-informed PLM decisions. In this article, an overview framework of big data based analysis for product lifecycle (BDA-PL) was presented to provide a new paradigm by extending the techniques of Internet of Things (IoT) and big data analys...

On Designing a Generic Framework for Cloud-based Big Data Analytics

OpenAIRE

Khan, Samiya; Alam, Mansaf

2017-01-01

Big data analytics has gathered immense research attention lately because of its ability to harness useful information from heaps of data. Cloud computing has been adjudged as one of the best infrastructural solutions for implementation of big data analytics. This research paper proposes a five-layer model for cloud-based big data analytics that uses dew computing and edge computing concepts. Besides this, the paper also presents an approach for creation of custom big data stack by selecting ...

The big two personality traits and adolescents' complete mental health: The mediation role of perceived school stress.

Science.gov (United States)

Tian, Lili; Jiang, Siyi; Huebner, E Scott

2018-05-24

Based on Greenspoon and Saklofske's (2001) dual-factor model of mental health, we defined adolescents' mental health as comprised of two distinguishable factors: positive and negative mental health. We tested the direct relations between the Eysenck's (1967) Big Two personality traits (Extraversion and Neuroticism) and positive and negative mental health, and explored the mediation effects of perceived school stress in accounting for the relations. Direct and indirect relations were estimated by using structural equation modeling with data from 1,009 Chinese adolescents in a 3-wave study. Results indicated that (a) adolescents' levels of neuroticism showed a positive relation to negative mental health and a negative relation to positive mental health, whereas levels of extraversion showed a negative relation to negative mental health and a positive relation to positive mental health; and (b) adolescents' perceived school stress (PSS) mediated the relation between neuroticism and mental health but not the relation between extraversion and mental health. The findings suggest that school professionals should consider adolescents' personality traits and school-based stress when planning and delivering mental health services. The findings of the relations between extraversion and PSS are also discussed in light of the face culture in China. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Small Area Model-Based Estimators Using Big Data Sources

Directory of Open Access Journals (Sweden)

Marchetti Stefano

2015-06-01

Full Text Available The timely, accurate monitoring of social indicators, such as poverty or inequality, on a finegrained spatial and temporal scale is a crucial tool for understanding social phenomena and policymaking, but poses a great challenge to official statistics. This article argues that an interdisciplinary approach, combining the body of statistical research in small area estimation with the body of research in social data mining based on Big Data, can provide novel means to tackle this problem successfully. Big Data derived from the digital crumbs that humans leave behind in their daily activities are in fact providing ever more accurate proxies of social life. Social data mining from these data, coupled with advanced model-based techniques for fine-grained estimates, have the potential to provide a novel microscope through which to view and understand social complexity. This article suggests three ways to use Big Data together with small area estimation techniques, and shows how Big Data has the potential to mirror aspects of well-being and other socioeconomic phenomena.

Separase Is Required for Homolog and Sister Disjunction during Drosophila melanogaster Male Meiosis, but Not for Biorientation of Sister Centromeres.

Science.gov (United States)

Blattner, Ariane C; Chaurasia, Soumya; McKee, Bruce D; Lehner, Christian F

2016-04-01

Spatially controlled release of sister chromatid cohesion during progression through the meiotic divisions is of paramount importance for error-free chromosome segregation during meiosis. Cohesion is mediated by the cohesin protein complex and cleavage of one of its subunits by the endoprotease separase removes cohesin first from chromosome arms during exit from meiosis I and later from the pericentromeric region during exit from meiosis II. At the onset of the meiotic divisions, cohesin has also been proposed to be present within the centromeric region for the unification of sister centromeres into a single functional entity, allowing bipolar orientation of paired homologs within the meiosis I spindle. Separase-mediated removal of centromeric cohesin during exit from meiosis I might explain sister centromere individualization which is essential for subsequent biorientation of sister centromeres during meiosis II. To characterize a potential involvement of separase in sister centromere individualization before meiosis II, we have studied meiosis in Drosophila melanogaster males where homologs are not paired in the canonical manner. Meiosis does not include meiotic recombination and synaptonemal complex formation in these males. Instead, an alternative homolog conjunction system keeps homologous chromosomes in pairs. Using independent strategies for spermatocyte-specific depletion of separase complex subunits in combination with time-lapse imaging, we demonstrate that separase is required for the inactivation of this alternative conjunction at anaphase I onset. Mutations that abolish alternative homolog conjunction therefore result in random segregation of univalents during meiosis I also after separase depletion. Interestingly, these univalents become bioriented during meiosis II, suggesting that sister centromere individualization before meiosis II does not require separase.

Mechanics of Sister Chromatids studied with a Polymer Model

Directory of Open Access Journals (Sweden)

Yang eZhang

2013-10-01

Full Text Available Sister chromatid cohesion denotes the phenomenon that sister chromatids are initially attached to each other in mitosis to guarantee the error-free distribution into the daughter cells. Cohesion is mediated by binding proteins and only resolved after mitotic chromosome condensation is completed. However, the amount of attachement points required to maintain sister chromatid cohesion while still allowing proper chromosome condensation is not known yet. Additionally the impact of cohesion on the mechanical properties of chromosomes also poses an interesting problem. In this work we study the conformational and mechanical properties of sister chromatids by means of computer simulations. We model both protein-mediated cohesion between sister chromatids and chromosome condensation with a dynamic binding mechanisms. We show in a phase diagram that only specific link concentrations lead to connected and fully condensed chromatids that do not intermingle with each other nor separate due to entropic forces. Furthermore we show that dynamic bonding between chromatids decrease the Young's modulus compared to non-bonded chromatids.

Uncoupling of Sister Replisomes during Eukaryotic DNA Replication

NARCIS (Netherlands)

Yardimci, Hasan; Loveland, Anna B.; Habuchi, Satoshi; van Oijen, Antoine M.; Walter, Johannes C.

2010-01-01

The duplication of eukaryotic genomes involves the replication of DNA from multiple origins of replication. In S phase, two sister replisomes assemble at each active origin, and they replicate DNA in opposite directions. Little is known about the functional relationship between sister replisomes.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

Science.gov (United States)

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

little sister: An Afro-Temporal Solo-Play.

Science.gov (United States)

De Berry, Misty

2017-07-03

little sister: An Afro-Temporal Solo-Play is at once a memory-scape and a mytho-biography set to poetry, movement, and mixed media. A performance poem spanning from the Antebellum South to present-moment Chicago, it tells the story of a nomadic spirit named little-she who shape-shifts through the memories and imaginings of her sister, the narrator. Through the characters little-she and the narrator, the solo-performance explores embodied ways to rupture and relieve the impact of macro forms of violence in the micro realm of the everyday. To this end, little sister witnesses and disrupts the legacy of violence in the lives of queer Black women through a trans-temporal navigation of everyday encounters within familial, small groups and intimate partner spaces.

Sister chromatid segregation in meiosis II

Science.gov (United States)

Wassmann, Katja

2013-01-01

Meiotic divisions (meiosis I and II) are specialized cell divisions to generate haploid gametes. The first meiotic division with the separation of chromosomes is named reductional division. The second division, which takes place immediately after meiosis I without intervening S-phase, is equational, with the separation of sister chromatids, similar to mitosis. This meiotic segregation pattern requires the two-step removal of the cohesin complex holding sister chromatids together: cohesin is removed from chromosome arms that have been subjected to homologous recombination in meiosis I and from the centromere region in meiosis II. Cohesin in the centromere region is protected from removal in meiosis I, but this protection has to be removed—deprotected”—for sister chromatid segregation in meiosis II. Whereas the mechanisms of cohesin protection are quite well understood, the mechanisms of deprotection have been largely unknown until recently. In this review I summarize our current knowledge on cohesin deprotection. PMID:23574717

Big data based fraud risk management at Alibaba

OpenAIRE

Chen, Jidong; Tao, Ye; Wang, Haoran; Chen, Tao

2015-01-01

With development of mobile internet and finance, fraud risk comes in all shapes and sizes. This paper is to introduce the Fraud Risk Management at Alibaba under big data. Alibaba has built a fraud risk monitoring and management system based on real-time big data processing and intelligent risk models. It captures fraud signals directly from huge amount data of user behaviors and network, analyzes them in real-time using machine learning, and accurately predicts the bad users and transactions....

Understanding the role of social capital in adolescents' Big Five personality effects on school-to-work transitions

NARCIS (Netherlands)

Baay, Pieter E.; Van Aken, Marcel A G; De Ridder, Denise T D; Van der Lippe, Tanja

2014-01-01

The school-to-work transition constitutes a central developmental task for adolescents. The role of Big Five personality traits in this has received some scientific attention, but prior research has been inconsistent and paid little attention to mechanisms through which personality traits influence

Big data based fraud risk management at Alibaba

Directory of Open Access Journals (Sweden)

Jidong Chen

2015-12-01

Full Text Available With development of mobile internet and finance, fraud risk comes in all shapes and sizes. This paper is to introduce the Fraud Risk Management at Alibaba under big data. Alibaba has built a fraud risk monitoring and management system based on real-time big data processing and intelligent risk models. It captures fraud signals directly from huge amount data of user behaviors and network, analyzes them in real-time using machine learning, and accurately predicts the bad users and transactions. To extend the fraud risk prevention ability to external customers, Alibaba also built up a big data based fraud prevention product called AntBuckler. AntBuckler aims to identify and prevent all flavors of malicious behaviors with flexibility and intelligence for online merchants and banks. By combining large amount data of Alibaba and customers', AntBuckler uses the RAIN score engine to quantify risk levels of users or transactions for fraud prevention. It also has a user-friendly visualization UI with risk scores, top reasons and fraud connections.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

Science.gov (United States)

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

The Lehman Sisters Hypothesis

NARCIS (Netherlands)

I.P. van Staveren (Irene)

2014-01-01

markdownabstract__Abstract__ This article explores the Lehman Sisters Hypothesis. It reviews empirical literature about gender differences in behavioral, experimental, and neuro-economics as well as in other fields of behavioral research. It discusses gender differences along three dimensions of

Big Data Comes to School

Directory of Open Access Journals (Sweden)

Bill Cope

2016-03-01

Full Text Available The prospect of “big data” at once evokes optimistic views of an information-rich future and concerns about surveillance that adversely impacts our personal and private lives. This overview article explores the implications of big data in education, focusing by way of example on data generated by student writing. We have chosen writing because it presents particular complexities, highlighting the range of processes for collecting and interpreting evidence of learning in the era of computer-mediated instruction and assessment as well as the challenges. Writing is significant not only because it is central to the core subject area of literacy; it is also an ideal medium for the representation of deep disciplinary knowledge across a number of subject areas. After defining what big data entails in education, we map emerging sources of evidence of learning that separately and together have the potential to generate unprecedented amounts of data: machine assessments, structured data embedded in learning, and unstructured data collected incidental to learning activity. Our case is that these emerging sources of evidence of learning have significant implications for the traditional relationships between assessment and instruction. Moreover, for educational researchers, these data are in some senses quite different from traditional evidentiary sources, and this raises a number of methodological questions. The final part of the article discusses implications for practice in an emerging field of education data science, including publication of data, data standards, and research ethics.

A genetic algorithm-based job scheduling model for big data analytics.

Science.gov (United States)

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

Victoria Stodden: Scholarly Communication in the Era of Big Data and Big Computation

OpenAIRE

Stodden, Victoria

2015-01-01

Victoria Stodden gave the keynote address for Open Access Week 2015. "Scholarly communication in the era of big data and big computation" was sponsored by the University Libraries, Computational Modeling and Data Analytics, the Department of Computer Science, the Department of Statistics, the Laboratory for Interdisciplinary Statistical Analysis (LISA), and the Virginia Bioinformatics Institute. Victoria Stodden is an associate professor in the Graduate School of Library and Information Scien...

[Analysis of genomic copy number variations in two sisters with primary amenorrhea and hyperandrogenism].

Science.gov (United States)

Zhang, Yanliang; Xu, Qiuyue; Cai, Xuemei; Li, Yixun; Song, Guibo; Wang, Juan; Zhang, Rongchen; Dai, Yong; Duan, Yong

2015-12-01

To analyze genomic copy number variations (CNVs) in two sisters with primary amenorrhea and hyperandrogenism. G-banding was performed for karyotype analysis. The whole genome of the two sisters were scanned and analyzed by array-based comparative genomic hybridization (array-CGH). The results were confirmed with real-time quantitative PCR (RT-qPCR). No abnormality was found by conventional G-banded chromosome analysis. Array-CGH has identified 11 identical CNVs from the sisters which, however, overlapped with CNVs reported by the Database of Genomic Variants (http://projects.tcag.ca/variation/). Therefore, they are likely to be benign. In addition, a -8.44 Mb 9p11.1-p13.1 duplication (38,561,587-47,002,387 bp, hg18) and a -80.9 kb 4q13.2 deletion (70,183,990-70,264,889 bp, hg18) were also detected in the elder and younger sister, respectively. The relationship between such CNVs and primary amenorrhea and hyperandrogenism was however uncertain. RT-qPCR results were in accordance with array-CGH. Two CNVs were detected in two sisters by array-CGH, for which further studies are needed to clarify their correlation with primary amenorrhea and hyperandrogenism.

Understanding the role of social capital in adolescents' Big Five personality effects on school-to-work transitions.

Science.gov (United States)

Baay, Pieter E; van Aken, Marcel A G; de Ridder, Denise T D; van der Lippe, Tanja

2014-07-01

The school-to-work transition constitutes a central developmental task for adolescents. The role of Big Five personality traits in this has received some scientific attention, but prior research has been inconsistent and paid little attention to mechanisms through which personality traits influence job-search outcomes. The current study proposed that the joint effects of Big Five personality traits and social capital (i.e., available resources through social relations) would shed more light on adolescents' job-search outcomes. Analyses on 685 Dutch vocational training graduates showed that extraversion and emotional stability were related to better job-search outcomes after graduation. Some relations between Big Five personality traits and job-search outcomes were explained by social capital, but no relations were dependent on social capital. Social capital had a direct relation with the number of job offers. Contrary to popular belief, this study shows that Big Five personality traits and social capital relate to job-search outcomes largely independently. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

"Sister to the tailor"

DEFF Research Database (Denmark)

Simonton, Deborah

2017-01-01

Milliners, and their sisters, mantuamakers, modistes and marchandes de mode, were skilled artisans, businesswomen and tradeswomen. During the eighteenth century, they commandeered the high-class sewing that set fashion and created stars of their most famous, like Rose Bertrand, milliner to Marie...

How Big Is Too Big?

Science.gov (United States)

Cibes, Margaret; Greenwood, James

2016-01-01

Media Clips appears in every issue of Mathematics Teacher, offering readers contemporary, authentic applications of quantitative reasoning based on print or electronic media. This issue features "How Big is Too Big?" (Margaret Cibes and James Greenwood) in which students are asked to analyze the data and tables provided and answer a…

Longitudinal multilevel models of the big-fish-little-pond effect on academic self-concept: counterbalancing contrast and reflected-glory effects in Hong Kong schools.

Science.gov (United States)

Marsh, H W; Kong, C K; Hau, K T

2000-02-01

Longitudinal multilevel path models (7,997 students, 44 high schools, 4 years) evaluated effects of school-average achievement and perceived school status on academic self-concept in Hong Kong, which has a collectivist culture with a highly achievement-segregated high school system. Consistent with a priori predictions based on the big-fish-little-pond effect (BFLPE), higher school-average achievements led to lower academic self-concepts (contrast effect), whereas higher perceived school status had a counterbalancing positive effect on self-concept (reflected-glory, assimilation effect). The negative BFLPE is the net effect of counterbalancing influences, stronger negative contrast effects, and weaker positive assimilation effects so that controlling perceived school status led to purer--and even more negative--contrast effects. Attending a school where school-average achievement is high simultaneously resulted in a more demanding basis of comparison for one's own accomplishments (the stronger negative contrast effect) and a source of pride (the weaker positive assimilation effect).

Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

Science.gov (United States)

Zeng, Tao; Zhang, Wanwei; Yu, Xiangtian; Liu, Xiaoping; Li, Meiyi; Chen, Luonan

2016-07-01

Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically 'small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as 'large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression

[Two Dutch sisters in analysis with Freud].

Science.gov (United States)

Stroeken, Harry

2010-01-01

The author provides persuasive or at least plausible data for the identity of two patients recorded by Freud in his working season of 1910/11. They were two sisters, living in The Hague/Leiden, who came from a rich banker's family, the van der Lindens. Whereas the treatment does not seem to have led to any decisive improvement for the older of the two, it may have encouraged the younger sister to seek divorce.

Big Sib Students' Perceptions of the Educational Environment at the School of Medical Sciences, Universiti Sains Malaysia, using Dundee Ready Educational Environment Measure (DREEM) Inventory.

Science.gov (United States)

Arzuman, Hafiza; Yusoff, Muhamad Saiful Bahri; Chit, Som Phong

2010-07-01

A cross-sectional descriptive study was conducted among Big Sib students to explore their perceptions of the educational environment at the School of Medical Sciences, Universiti Sains Malaysia (USM) and its weak areas using the Dundee Ready Educational Environment Measure (DREEM) inventory. The DREEM inventory is a validated global instrument for measuring educational environments in undergraduate medical and health professional education. The English version of the DREEM inventory was administered to all Year 2 Big Sib students (n = 67) at a regular Big Sib session. The purpose of the study as well as confidentiality and ethical issues were explained to the students before the questionnaire was administered. The response rate was 62.7% (42 out of 67 students). The overall DREEM score was 117.9/200 (SD 14.6). The DREEM indicated that the Big Sib students' perception of educational environment of the medical school was more positive than negative. Nevertheless, the study also revealed some problem areas within the educational environment. This pilot study revealed that Big Sib students perceived a positive learning environment at the School of Medical Sciences, USM. It also identified some low-scored areas that require further exploration to pinpoint the exact problems. The relatively small study population selected from a particular group of students was the major limitation of the study. This small sample size also means that the study findings cannot be generalised.

Birth weight and fetal growth in infants born to female hairdressers and their sisters.

Science.gov (United States)

Axmon, A; Rylander, L

2009-03-01

To investigate birth weight and fetal growth in female hairdressers, while controlling for intergenerational effects and effects related to childhood exposures. A cohort of women who had attended vocational schools for hairdressers were compared to their sisters with respect to birth weight and fetal growth (measured as small for gestational age (SGA) or large for gestational age (LGA), respectively) in their infants. In total, 6223 infants born to 3137 hairdressers and 8388 infants born to 3952 hairdressers' sisters were studied. Among the infants born to the hairdressers' sisters, the distribution of birth weights were wider than that among the infants born to the hairdressers. This was also reflected in that hairdresser cohort affiliation tended to be protective against both SGA (odds ratio 0.80; 95% confidence interval 0.49 to 1.31) and LGA (0.77; 0.54 to 1.09). For LGA, this effect was even more pronounced among women who had actually worked as hairdressers during at least one pregnancy (0.60; 0.39 to 0.92). The infants born to these women also had a significantly lower mean birth weight (3387 g vs 3419 g; p = 0.033). The results from the present study suggest that infants born to hairdressers have a decreased risk of being LGA. This is most likely not caused by a shift in birth weight distribution or abnormal glucose metabolism.

Sister kinetochores are mechanically fused during meiosis I in yeast.

Science.gov (United States)

Sarangapani, Krishna K; Duro, Eris; Deng, Yi; Alves, Flavia de Lima; Ye, Qiaozhen; Opoku, Kwaku N; Ceto, Steven; Rappsilber, Juri; Corbett, Kevin D; Biggins, Sue; Marston, Adèle L; Asbury, Charles L

2014-10-10

Production of healthy gametes requires a reductional meiosis I division in which replicated sister chromatids comigrate, rather than separate as in mitosis or meiosis II. Fusion of sister kinetochores during meiosis I may underlie sister chromatid comigration in diverse organisms, but direct evidence for such fusion has been lacking. We used laser trapping and quantitative fluorescence microscopy to study native kinetochore particles isolated from yeast. Meiosis I kinetochores formed stronger attachments and carried more microtubule-binding elements than kinetochores isolated from cells in mitosis or meiosis II. The meiosis I-specific monopolin complex was both necessary and sufficient to drive these modifications. Thus, kinetochore fusion directs sister chromatid comigration, a conserved feature of meiosis that is fundamental to Mendelian inheritance. Copyright © 2014, American Association for the Advancement of Science.

Sister Mary Emil Penet, I.H.M.: Founder of the Sister Formation Conference

Science.gov (United States)

Glisky, Joan

2006-01-01

Mary Emil Penet, I.H.M., (1916-2001) used her talents and charisma to shape the first national organization of American women religious, the Sister Formation Conference (SFC; 1954-1964), facilitating the integrated intellectual, spiritual, psychological, and professional development of vowed women religious. In the decade preceding Vatican II, her…

Relationships of Big Five personality traits and nonverbal intelligence at high school age

Directory of Open Access Journals (Sweden)

Voronina Irina

2016-01-01

Full Text Available The article presents the results of study on the relationship of personality traits and intelligence in Russian high school students. The study focused on Big Five personality traits - Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness - and the structure of their relationships with nonverbal intelligence, as measured by the test “Standard Progressive Matrices”. Significant correlations were only found between nonverbal intelligence and Openness (r = 0.26, p < 0.05. The results are interpreted in the context of investment theory, which assumes that personality traits can promote the formation of individual differences in intelligence.

Big Dreams

Science.gov (United States)

Benson, Michael T.

2015-01-01

The Keen Johnson Building is symbolic of Eastern Kentucky University's historic role as a School of Opportunity. It is a place that has inspired generations of students, many from disadvantaged backgrounds, to dream big dreams. The construction of the Keen Johnson Building was inspired by a desire to create a student union facility that would not…

A Grey Theory Based Approach to Big Data Risk Management Using FMEA

Directory of Open Access Journals (Sweden)

Maisa Mendonça Silva

2016-01-01

Full Text Available Big data is the term used to denote enormous sets of data that differ from other classic databases in four main ways: (huge volume, (high velocity, (much greater variety, and (big value. In general, data are stored in a distributed fashion and on computing nodes as a result of which big data may be more susceptible to attacks by hackers. This paper presents a risk model for big data, which comprises Failure Mode and Effects Analysis (FMEA and Grey Theory, more precisely grey relational analysis. This approach has several advantages: it provides a structured approach in order to incorporate the impact of big data risk factors; it facilitates the assessment of risk by breaking down the overall risk to big data; and finally its efficient evaluation criteria can help enterprises reduce the risks associated with big data. In order to illustrate the applicability of our proposal in practice, a numerical example, with realistic data based on expert knowledge, was developed. The numerical example analyzes four dimensions, that is, managing identification and access, registering the device and application, managing the infrastructure, and data governance, and 20 failure modes concerning the vulnerabilities of big data. The results show that the most important aspect of risk to big data relates to data governance.

Product design pattern based on big data-driven scenario

OpenAIRE

Conggang Yu; Lusha Zhu

2016-01-01

This article discusses about new product design patterns in the big data era, gives designer a new rational thinking way, and is a new way to understand the design of the product. Based on the key criteria of the product design process, category, element, and product are used to input the data, which comprises concrete data and abstract data as an enlargement of the criteria of product design process for the establishment of a big data-driven product design pattern’s model. Moreover, an exper...

The Big Fish-Little Pond Effect on Affective Factors Based on PISA 2012 Mathematics Achievement

Directory of Open Access Journals (Sweden)

Dilara BAKAN KALAYCIOĞLU

2017-03-01

Full Text Available In this study, the 2012 PISA Turkey student questionnaire data is considered to determine the big fish-little pond effect. The mathematics self-efficacy, self-concept and anxiety affective factors are examined to explain the relation of each of them with the school type, gender, socioeconomic status, student’s mathematics achievement and school’s mathematics achievement covariates. A total number of 771 students from 88 high schools are in the sample. Factor analyses’ results support the construct validity of the Student Questionnaire’s mathematics self-efficacy, anxiety and self-concept items. Data set is analyzed with Multiple Indicator Multiple Cause Model and the patterns of association with covariates and affective factors were tested simultaneously. According to the results, Anatolian high school students have a higher mathematics self-efficacy and lower mathematics anxiety than do the general high school students. However, when the student mathematics achievement and school mathematics achievement variables were inserted to the model, school type was not associated with mathematics self-efficacy. Moreover, Anatolian high school student’s mathematics anxiety was higher than that of the general high school students. Student’s mathematics achievement was the most significant predictor of the mathematics self-efficacy, anxiety and self-concept factors. Finally, school’s mathematics achievement was a significant predictor of only mathematics self-concept. The identification of increase in school’s mathematics achievement yields a decrease in the student’s mathematics self-concept may be considered as the most important result of this study. These results provide evidence about the Anatolian high schools’ students experience big fish-little pond effect.

GrandBase: generating actionable knowledge from Big Data

Directory of Open Access Journals (Sweden)

Xiu Susie Fang

2017-08-01

Full Text Available Purpose – This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB, called GrandBase. Design/methodology/approach – In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase. In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed. Findings – Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed. Originality/value – To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem. Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

Splitting the chromosome: cutting the ties that bind sister chromatids.

Science.gov (United States)

Nasmyth, K; Peters, J M; Uhlmann, F

2001-01-01

In eukaryotic cells, replicated DNA molecules remain physically connected from their synthesis in S phase until they are separated during anaphase. This phenomenon, called sister chromatid cohesion, is essential for the temporal separation of DNA replication and mitosis and for the equal separation of the duplicated genome. Recent work has identified a number of chromosomal proteins required for cohesion. In this review we discuss how these proteins may connect sister chromatids and how they are removed from chromosomes to allow sister chromatid separation at the onset of anaphase.

Reconstitution of Nucleosomes with Differentially Isotope-labeled Sister Histones.

Science.gov (United States)

Liokatis, Stamatios

2017-03-26

Asymmetrically modified nucleosomes contain the two copies of a histone (sister histones) decorated with distinct sets of Post-translational Modifications (PTMs). They are newly identified species with unknown means of establishment and functional implications. Current analytical methods are inadequate to detect the copy-specific occurrence of PTMs on the nucleosomal sister histones. This protocol presents a biochemical method for the in vitro reconstitution of nucleosomes containing differentially isotope-labeled sister histones. The generated complex can be also asymmetrically modified, after including a premodified histone pool during refolding of histone subcomplexes. These asymmetric nucleosome preparations can be readily reacted with histone-modifying enzymes to study modification cross-talk mechanisms imposed by the asymmetrically pre-incorporated PTM using nuclear magnetic resonance (NMR) spectroscopy. Particularly, the modification reactions in real-time can be mapped independently on the two sister histones by performing different types of NMR correlation experiments, tailored for the respective isotope type. This methodology provides the means to study crosstalk mechanisms that contribute to the formation and propagation of asymmetric PTM patterns on nucleosomal complexes.

Ukrainian and European Baroque in the Context of “Sister Arts” Idea

Directory of Open Access Journals (Sweden)

Olga Shikirinskaya

2015-08-01

Full Text Available The article deals with the “Sister Arts” tradition as the interrelationship of various art forms (poetry, fiction, painting, theatre, music etc. relative to the Baroque period. “Sister Arts” criticism, based on E.G. Lessing essay “Laocoön…” uses the inter-art analogies to appreciate the importance of literature in the Arts, as well as to comprehend aspects of the modern approach to the synthesis of the arts. The article presents the aesthetic concept of Baroque art and its realization in architecture, sculpture, decorative and applied arts, music and literature on the background of the European and Ukrainian cultural tradition.

Towards cloud based big data analytics for smart future cities

OpenAIRE

Khan, Zaheer; Anjum, Ashiq; Soomro, Kamran; Tahir, Muhammad

2015-01-01

A large amount of land-use, environment, socio-economic, energy and transport data is generated in cities. An integrated perspective of managing and analysing such big data can answer a number of science, policy, planning, governance and business questions and support decision making in enabling a smarter environment. This paper presents a theoretical and experimental perspective on the smart cities focused big data management and analysis by proposing a cloud-based analytics service. A proto...

The SIKS/BiGGrid Big Data Tutorial

NARCIS (Netherlands)

Hiemstra, Djoerd; Lammerts, Evert; de Vries, A.P.

2011-01-01

The School for Information and Knowledge Systems SIKS and the Dutch e-science grid BiG Grid organized a new two-day tutorial on Big Data at the University of Twente on 30 November and 1 December 2011, just preceding the Dutch-Belgian Database Day. The tutorial is on top of some exciting new

Could Blobs Fuel Storage-Based Convergence between HPC and Big Data?

Energy Technology Data Exchange (ETDEWEB)

Matri, Pierre; Alforov, Yevhen; Brandon, Alvaro; Kuhn, Michael; Carns, Philip; Ludwig, Thomas

2017-09-05

The increasingly growing data sets processed on HPC platforms raise major challenges for the underlying storage layer. A promising alternative to POSIX-IO- compliant file systems are simpler blobs (binary large objects), or object storage systems. Such systems offer lower overhead and better performance at the cost of largely unused features such as file hierarchies or permissions. Similarly, blobs are increasingly considered for replacing distributed file systems for big data analytics or as a base for storage abstractions such as key-value stores or time-series databases. This growing interest in such object storage on HPC and big data platforms raises the question: Are blobs the right level of abstraction to enable storage-based convergence between HPC and Big Data? In this paper we study the impact of blob-based storage for real-world applications on HPC and cloud environments. The results show that blobbased storage convergence is possible, leading to a significant performance improvement on both platforms

Big Data in der Cloud

DEFF Research Database (Denmark)

Leimbach, Timo; Bachlechner, Daniel

2014-01-01

Technology assessment of big data, in particular cloud based big data services, for the Office for Technology Assessment at the German federal parliament (Bundestag)......Technology assessment of big data, in particular cloud based big data services, for the Office for Technology Assessment at the German federal parliament (Bundestag)...

Epigenetic differences between sister chromatids?

NARCIS (Netherlands)

Lansdorp, Peter M.; Falconer, Ester; Tao, Jiang; Brind'Amour, Julie; Naumann, Ulrike; Kanz, L; Fibbe, WE; Lengerke, C; Dick, JE

2012-01-01

Semi-conservative replication ensures that the DNA sequence of sister chromatids is identical except for replication errors and variation in the length of telomere repeats resulting from replicative losses and variable end processing. What happens with the various epigenetic marks during DNA

Performance Isolation in Cloud-Based Big Data Architectures

NARCIS (Netherlands)

Tekinerdogan, B.; Oral, Alp

2017-01-01

Cloud-based big data systems usually have many different tenants that require access to the server's functionality. In a nonisolated cloud system, the different tenants can freely use the resources of the server. Hereby, disruptive tenants who exceed their limits can easily cause degradation of

Big Surveys, Big Data Centres

Science.gov (United States)

Schade, D.

2016-06-01

Well-designed astronomical surveys are powerful and have consistently been keystones of scientific progress. The Byurakan Surveys using a Schmidt telescope with an objective prism produced a list of about 3000 UV-excess Markarian galaxies but these objects have stimulated an enormous amount of further study and appear in over 16,000 publications. The CFHT Legacy Surveys used a wide-field imager to cover thousands of square degrees and those surveys are mentioned in over 1100 publications since 2002. Both ground and space-based astronomy have been increasing their investments in survey work. Survey instrumentation strives toward fair samples and large sky coverage and therefore strives to produce massive datasets. Thus we are faced with the "big data" problem in astronomy. Survey datasets require specialized approaches to data management. Big data places additional challenging requirements for data management. If the term "big data" is defined as data collections that are too large to move then there are profound implications for the infrastructure that supports big data science. The current model of data centres is obsolete. In the era of big data the central problem is how to create architectures that effectively manage the relationship between data collections, networks, processing capabilities, and software, given the science requirements of the projects that need to be executed. A stand alone data silo cannot support big data science. I'll describe the current efforts of the Canadian community to deal with this situation and our successes and failures. I'll talk about how we are planning in the next decade to try to create a workable and adaptable solution to support big data science.

Sister Mary Theresa Brentano, OSB's Innovative Use of Magnetic Audio Tapes: An Overlooked Story in the History of Educational Technology.

Science.gov (United States)

Herndon, Linda

This paper tells the story of Sister Mary Theresa Brentano, O.S.B's (1902-1987) innovative use of magnetic audiotapes to provide instruction for students in grades K-12. From 1952 to approximately 1968, Brentano implemented, refined, and tested her tape teaching methods with special emphasis on individualizing instruction in the elementary school.…

The effect of phonics-enhanced Big Book reading on the language and literacy skills of 6-year-old pupils of different reading ability attending lower SES schools

Science.gov (United States)

Tse, Laura; Nicholson, Tom

2014-01-01

The purpose of this study was to improve the literacy achievement of lower socioeconomic status (SES) children by combining explicit phonics with Big Book reading. Big Book reading is a component of the text-centered (or book reading) approach used in New Zealand schools. It involves the teacher in reading an enlarged book to children and demonstrating how to use semantic, syntactic, and grapho-phonic cues to learn to read. There has been little research, however, to find out whether the effectiveness of Big Book reading is enhanced by adding explicit phonics. In this study, a group of 96 second graders from three lower SES primary schools in New Zealand were taught in 24 small groups of four, tracked into three different reading ability levels. All pupils were randomly assigned to one of four treatment conditions: a control group who received math instruction, Big Book reading enhanced with phonics (BB/EP), Big Book reading on its own, and Phonics on its own. The results showed that the BB/EP group made significantly better progress than the Big Book and Phonics groups in word reading, reading comprehension, spelling, and phonemic awareness. In reading accuracy, the BB/EP and Big Book groups scored similarly. In basic decoding skills the BB/EP and Phonics groups scored similarly. The combined instruction, compared with Big Book reading and phonics, appeared to have no comparative disadvantages and considerable advantages. The present findings could be a model for New Zealand and other countries in their efforts to increase the literacy achievement of disadvantaged pupils. PMID:25431560

Dam safety at Seven Sisters Generating Station

International Nuclear Information System (INIS)

Carson, R. W.; Gupta, R. C.

1996-01-01

A safety surveillance program for all hydraulic structures in Manitoba was first implemented in 1979, and updated in 1988. This contribution describes the current status of the program, and the nature of the issues that the program was designed to address. The Seven Sisters Station's dam on the Winnipeg River, about 90 km northeast of the City of Winnipeg, was used as an example. Extensive reviews of flood risks and downstream inundation potential at Seven Sisters' revealed a number of deficiencies; these findings will be incorporated into a corporate plan of overall remediation. Updating the program will also include efforts to ensure adherence to national dam safety guidelines. 5 figs

Identifying The Purchasing Power Parity of Indonesia Rupiah (IDR) based on BIG MAC Index

OpenAIRE

Tongam Sihol Nababan

2016-01-01

The aim of this study is to identify : (1) profile of exchange rate and purchasing power parity of IDR against US $ based on Big Mac Index compared to the exchange rate of other countries, and (2) the position of the Big Mac Affordability of Indonesia compared to other ASEAN countries. The results showed that based on Big Mac index during the period April 1998 up to January 2015, IDR exchange rate tends to be undervalued against the USA dollar. The cause of the currency tends to be in a posi...

Geologic map of Three Sisters volcanic cluster, Cascade Range, Oregon

Science.gov (United States)

Hildreth, Wes; Fierstein, Judy; Calvert, Andrew T.

2012-01-01

The cluster of glaciated stratovolcanoes called the Three Sisters—South Sister, Middle Sister, and North Sister—forms a spectacular 20-km-long reach along the crest of the Cascade Range in Oregon. The three eponymous stratocones, though contiguous and conventionally lumped sororally, could hardly display less family resemblance. North Sister (10,085 ft), a monotonously mafic edifice at least as old as 120 ka, is a glacially ravaged stratocone that consists of hundreds of thin rubbly lava flows and intercalated falls that dip radially and steeply; remnants of two thick lava flows cap its summit. Middle Sister (10,047 ft), an andesite-basalt-dacite cone built between 48 and 14 ka, is capped by a thick stack of radially dipping, dark-gray, thin mafic lava flows; asymmetrically glaciated, its nearly intact west flank contrasts sharply with its steep east face. Snow and ice-filled South Sister is a bimodal rhyolitic-intermediate edifice that was constructed between 50 ka and 2 ka; its crater (rim at 10,358 ft) was created between 30 and 22 ka, during the most recent of several explosive summit eruptions; the thin oxidized agglutinate that mantles its current crater rim protects a 150-m-thick pyroclastic sequence that helped fill a much larger crater. For each of the three, the eruptive volume is likely to have been in the range of 15 to 25 km³, but such estimates are fairly uncertain, owing to glacial erosion. The map area consists exclusively of Quaternary volcanic rocks and derivative surficial deposits. Although most of the area has been modified by glaciation, the volcanoes are young enough that the landforms remain largely constructional. Furthermore, twelve of the 145 eruptive units on the map are postglacial, younger than the deglaciation that was underway by about 17 ka. The most recent eruptions were of rhyolite near South Sister, about 2,000 years ago, and of mafic magma near McKenzie Pass, about 1,500 years ago. As observed by trailblazing volcanologist

Identifying The Purchasing Power Parity of Indonesia Rupiah (IDR based on BIG MAC Index

Directory of Open Access Journals (Sweden)

Tongam Sihol Nababan

2016-12-01

Full Text Available The aim of this study is to identify : (1 profile of exchange rate and purchasing power parity of IDR against US $ based on Big Mac Index compared to the exchange rate of other countries, and (2 the position of the Big Mac Affordability of  Indonesia compared to other ASEAN countries. The results showed that based on Big Mac index during the period April 1998 up to January 2015, IDR exchange rate tends to be undervalued against the USA dollar. The cause of the currency tends to be in a position of undervalued due to the components of non-tradable have not been included in Big Mac index. The index of Big Mac Affordability indicates that there is a great disparity of income between Singapore and five other ASEAN countries. The purchasing power of the real income of the people in Singapore is nearly five times the real income of the people in Indonesia.

Big Data Knowledge in Global Health Education.

Science.gov (United States)

Olayinka, Olaniyi; Kekeh, Michele; Sheth-Chandra, Manasi; Akpinar-Elci, Muge

The ability to synthesize and analyze massive amounts of data is critical to the success of organizations, including those that involve global health. As countries become highly interconnected, increasing the risk for pandemics and outbreaks, the demand for big data is likely to increase. This requires a global health workforce that is trained in the effective use of big data. To assess implementation of big data training in global health, we conducted a pilot survey of members of the Consortium of Universities of Global Health. More than half the respondents did not have a big data training program at their institution. Additionally, the majority agreed that big data training programs will improve global health deliverables, among other favorable outcomes. Given the observed gap and benefits, global health educators may consider investing in big data training for students seeking a career in global health. Copyright © 2017 Icahn School of Medicine at Mount Sinai. Published by Elsevier Inc. All rights reserved.

Ontology-Based Big Dimension Modeling in Data Warehouse Schema Design

DEFF Research Database (Denmark)

Iftikhar, Nadeem

2013-01-01

During data warehouse schema design, designers often encounter how to model big dimensions that typically contain a large number of attributes and records. To investigate effective approaches for modeling big dimensions is necessary in order to achieve better query performance, with respect...... partitioning, vertical partitioning and their hybrid. We formalize the design methods and propose an algorithm that describes the modeling process from an OWL ontology to a data warehouse schema. In addition, this paper also presents an effective ontology-based tool to automate the modeling process. The tool...... can automatically generate the data warehouse schema from the ontology of describing the terms and business semantics for the big dimension. In case of any change in the requirements, we only need to modify the ontology, and re-generate the schema using the tool. This paper also evaluates the proposed...

20 CFR 725.225 - Determination of dependency; parent, brother, or sister.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Determination of dependency; parent, brother, or sister. 725.225 Section 725.225 Employees' Benefits EMPLOYMENT STANDARDS ADMINISTRATION... Benefits) § 725.225 Determination of dependency; parent, brother, or sister. An individual who is the miner...

Metabolic syndrome, hypertension, and hyperlipidemia in mothers, fathers, sisters, and brothers of women with polycystic ovary syndrome: a systematic review and meta-analysis.

Science.gov (United States)

Yilmaz, Bulent; Vellanki, Priyathama; Ata, Baris; Yildiz, Bulent Okan

2018-02-01

To provide an evidence-based assessment of metabolic syndrome, hypertension, and hyperlipidemia in first-degree relatives of women with polycystic ovary syndrome (PCOS). Systematic review and meta-analysis. Not applicable. Mothers, fathers, sisters, and brothers of women with and without PCOS. An electronic-based search with the use of PubMed from 1960 to June 2015 and cross-checked references of relevant articles. Metabolic syndrome, hypertension and dyslipidemia, and surrogate markers, including systolic blood pressure (BP), diastolic BP, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. Fourteen of 3,346 studies were included in the meta-analysis. Prevalence of the following was significantly increased in relatives of women with PCOS: metabolic syndrome (risk ratio [RR] 1.78 [95% confidence interval 1.37, 2.30] in mothers, 1.43 [1.12, 1.81] in fathers, and 1.50 [1.12, 2.00] in sisters), hypertension (RR 1.93 [1.58, 2.35] in fathers, 2.92 [1.92, 4.45] in sisters), and dyslipidemia (RR 3.86 [2.54, 5.85] in brothers and 1.29 [1.11, 1.50] in fathers). Moreover, systolic BP (mothers, sisters, and brothers), total cholesterol (mothers and sisters), low-density lipoprotein cholesterol (sisters), and triglycerides (mothers and sisters) were significantly higher in first-degree relatives of PCOS probands than in controls. Our results show evidence of clustering for metabolic syndrome, hypertension, and dyslipidemia in mothers, fathers, sisters, and brothers of women with PCOS. PROSPERO 2016 CRD42016048557. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

The Role of Gender in Youth Mentoring Relationship Formation and Duration

Science.gov (United States)

Rhodes, Jean; Lowe, Sarah R.; Litchfield, Leon; Walsh-Samp, Kathy

2008-01-01

The role of gender in shaping the course and quality of adult-youth mentoring relationships was examined. The study drew on data from a large, random assignment evaluation of Big Brothers Big Sisters of America (BBSA) programs [Grossman, J. B., & Tierney, J. P. (1998). Does mentoring work? An impact study of the Big Brothers Big Sisters program.…

Big Data Science Cafés: High School Students Experiencing Real Research with Scientists

Science.gov (United States)

Walker, C. E.; Pompea, S. M.

2017-12-01

The Education and Public Outreach group at the National Optical Astronomy Observatory has designed an outside-of-school education program to excite the interest of talented youth in future projects like the Large Synoptic Survey Telescope (LSST) and the NOAO (archival) Data Lab - their data approaches and key science projects. Originally funded by the LSST Corporation, the program cultivates talented youth to enter STEM disciplines and serves as a model to disseminate to the 40+ institutions involved in LSST. One Saturday a month during the academic year, high school students have the opportunity to interact with expert astronomers who work with large astronomical data sets in their scientific work. Students learn about killer asteroids, the birth and death of stars, colliding galaxies, the structure of the universe, gravitational waves, dark energy, dark matter, and more. The format for the Saturday science cafés has been a short presentation, discussion (plus food), computer lab activity and more discussion. They last about 2.5 hours and have been planned by a group of interested local high school students, an undergraduate student coordinator, the presenting astronomers, the program director and an evaluator. High school youth leaders help ensure an enjoyable and successful program for fellow students. They help their fellow students with the activities and help evaluate how well the science café went. Their remarks shape the next science café and improve the program. The experience offers youth leaders ownership of the program, opportunities to take on responsibilities and learn leadership and communication skills, as well as foster their continued interests in STEM. The prototype Big Data Science Academy was implemented successfully in the Spring 2017 and engaged almost 40 teens from greater Tucson in the fundamentals of astronomy concepts and research. As with any first implementation there were bumps. However, staff, scientists, and student leaders all

Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction

Directory of Open Access Journals (Sweden)

Hua-pu Lu

2015-01-01

Full Text Available With the rapid development of urban informatization, the era of big data is coming. To satisfy the demand of traffic congestion early warning, this paper studies the method of real-time traffic flow state identification and prediction based on big data-driven theory. Traffic big data holds several characteristics, such as temporal correlation, spatial correlation, historical correlation, and multistate. Traffic flow state quantification, the basis of traffic flow state identification, is achieved by a SAGA-FCM (simulated annealing genetic algorithm based fuzzy c-means based traffic clustering model. Considering simple calculation and predictive accuracy, a bilevel optimization model for regional traffic flow correlation analysis is established to predict traffic flow parameters based on temporal-spatial-historical correlation. A two-stage model for correction coefficients optimization is put forward to simplify the bilevel optimization model. The first stage model is built to calculate the number of temporal-spatial-historical correlation variables. The second stage model is present to calculate basic model formulation of regional traffic flow correlation. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods.

Breaking Sound Barriers: New Perspectives on Effective Big Band Development and Rehearsal

Science.gov (United States)

Greig, Jeremy; Lowe, Geoffrey

2014-01-01

Jazz big band is a common extra-curricular musical activity in Western Australian secondary schools. Jazz big band offers important fundamentals that can help expand a student's musical understanding. However, the teaching of conventions associated with big band jazz has often been haphazard and can be daunting and frightening, especially for…

[Florence Nightingale and charity sisters: revisiting the history].

Science.gov (United States)

Padilha, Maria Itayra Coelho de Souza; Mancia, Joel Rolim

2005-01-01

This study presents an historical analysis on the links between the nursing practice and the influence received from various religious orders/associations along the times, especially from Saint Vincent Paul's charity sisters. The professional nursing which was pioneered by Florence Nightingale in the XlXth century, was directly influenced by the teachings of love and fraternity. In addition, other contributions from the religious orders/associations were the concepts of altruism, valorization of an adequate environment for the care of patients, and the division of work in nursing. The study shows the influence of Charity Sisters on Florence Nightingale.

Clouston′s Disease in Three Sisters

Directory of Open Access Journals (Sweden)

Jayakar Thomas

1988-01-01

Full Text Available In a family of four children, all females, three sisters presented with Clouston′s disease or hidrotic ectodermal dysplasia. The case is reported for the rarity of presentation in a single generation with no history of other family members affected.

Friel and his "sisters"

Directory of Open Access Journals (Sweden)

Nicholas Grene

2010-11-01

Full Text Available This essay, occasioned by a revival of Brian Friel's version of Chekhov's Three Sisters at the Abbey Theatre in 2008, considers the circumstances surrounding its first production by the Field Day Theatre Company in 1981, and the motivation behind the decision to translate Chekhov's text into a specifically Irish dialect of English. It also analyses how Friel's plays since that date, notably the award-winning Dancing at Lughnasa (1990, have changed our perspective on the play.

Small Big Data Congress 2017

NARCIS (Netherlands)

Doorn, J.

2017-01-01

TNO, in collaboration with the Big Data Value Center, presents the fourth Small Big Data Congress! Our congress aims at providing an overview of practical and innovative applications based on big data. Do you want to know what is happening in applied research with big data? And what can already be

GRAMMAR RULE BASED INFORMATION RETRIEVAL MODEL FOR BIG DATA

Directory of Open Access Journals (Sweden)

T. Nadana Ravishankar

2015-07-01

Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.

"Air Toxics under the Big Sky": Examining the Effectiveness of Authentic Scientific Research on High School Students' Science Skills and Interest

Science.gov (United States)

Ward, Tony J.; Delaloye, Naomi; Adams, Earle Raymond; Ware, Desirae; Vanek, Diana; Knuth, Randy; Hester, Carolyn Laurie; Marra, Nancy Noel; Holian, Andrij

2016-01-01

"Air Toxics Under the Big Sky" is an environmental science outreach/education program that incorporates the Next Generation Science Standards (NGSS) 8 Practices with the goal of promoting knowledge and understanding of authentic scientific research in high school classrooms through air quality research. This research explored: (1)…

Changes in Siblings Over Time After the Death of a Brother or Sister From Cancer.

Science.gov (United States)

Akard, Terrah Foster; Skeens, Micah A; Fortney, Christine A; Dietrich, Mary S; Gilmer, Mary Jo; Vannatta, Kathryn; Barrera, Maru; Davies, Betty; Wray, Sarah; Gerhardt, Cynthia A

2018-02-27

Limited research has examined the impact of a child's death from cancer on siblings. Even less is known about how these siblings change over time. This study compared changes in siblings 1 (T1) and 2 (T2) years after the death of a brother or sister from cancer based on bereaved parent and sibling interviews. Participants across 3 institutions represented 27 families and included bereaved mothers (n = 21), fathers (n = 15), and siblings (n = 26) ranging from 8 to 17 years old. Participants completed semistructured interviews. Content analysis identified emerging themes and included frequency counts of participant responses. McNemar tests examined differences in the frequency of responses between T1 and T2 data. Participants reported similar types of changes in bereaved siblings at both time points, including changes in sibling relationships, life perspectives, their personal lives, and school performance. A new theme of "openness" emerged at T2. Frequencies of responses differed according to mother, father, or sibling informant. Overall, participants less frequently reported changes at T2 versus T1. Compared with findings in the first year, participants reported greater sibling maturity at follow-up. Overall changes in bereaved siblings continued over 2 years with less frequency over time, with the exception of increases in maturity and openness. Providers can educate parents regarding the impact of death of a brother or sister over time. Nurses can foster open communication in surviving grieving siblings and parents as potential protective factors in families going through their grief.

A Proposed Concentration Curriculum Design for Big Data Analytics for Information Systems Students

Science.gov (United States)

Molluzzo, John C.; Lawler, James P.

2015-01-01

Big Data is becoming a critical component of the Information Systems curriculum. Educators are enhancing gradually the concentration curriculum for Big Data in schools of computer science and information systems. This paper proposes a creative curriculum design for Big Data Analytics for a program at a major metropolitan university. The design…

Supporting diagnosis and treatment in medical care based on Big Data processing.

Science.gov (United States)

Lupşe, Oana-Sorina; Crişan-Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Bernard, Elena

2014-01-01

With information and data in all domains growing every day, it is difficult to manage and extract useful knowledge for specific situations. This paper presents an integrated system architecture to support the activity in the Ob-Gin departments with further developments in using new technology to manage Big Data processing - using Google BigQuery - in the medical domain. The data collected and processed with Google BigQuery results from different sources: two Obstetrics & Gynaecology Departments, the TreatSuggest application - an application for suggesting treatments, and a home foetal surveillance system. Data is uploaded in Google BigQuery from Bega Hospital Timişoara, Romania. The analysed data is useful for the medical staff, researchers and statisticians from public health domain. The current work describes the technological architecture and its processing possibilities that in the future will be proved based on quality criteria to lead to a better decision process in diagnosis and public health.

Frequent and efficient use of the sister chromatid for DNA double-strand break repair during budding yeast meiosis.

Directory of Open Access Journals (Sweden)

Tamara Goldfarb

2010-10-01

Full Text Available Recombination between homologous chromosomes of different parental origin (homologs is necessary for their accurate segregation during meiosis. It has been suggested that meiotic inter-homolog recombination is promoted by a barrier to inter-sister-chromatid recombination, imposed by meiosis-specific components of the chromosome axis. Consistent with this, measures of Holliday junction-containing recombination intermediates (joint molecules [JMs] show a strong bias towards inter-homolog and against inter-sister JMs. However, recombination between sister chromatids also has an important role in meiosis. The genomes of diploid organisms in natural populations are highly polymorphic for insertions and deletions, and meiotic double-strand breaks (DSBs that form within such polymorphic regions must be repaired by inter-sister recombination. Efforts to study inter-sister recombination during meiosis, in particular to determine recombination frequencies and mechanisms, have been constrained by the inability to monitor the products of inter-sister recombination. We present here molecular-level studies of inter-sister recombination during budding yeast meiosis. We examined events initiated by DSBs in regions that lack corresponding sequences on the homolog, and show that these DSBs are efficiently repaired by inter-sister recombination. This occurs with the same timing as inter-homolog recombination, but with reduced (2- to 3-fold yields of JMs. Loss of the meiotic-chromosome-axis-associated kinase Mek1 accelerates inter-sister DSB repair and markedly increases inter-sister JM frequencies. Furthermore, inter-sister JMs formed in mek1Δ mutants are preferentially lost, while inter-homolog JMs are maintained. These findings indicate that inter-sister recombination occurs frequently during budding yeast meiosis, with the possibility that up to one-third of all recombination events occur between sister chromatids. We suggest that a Mek1-dependent reduction in

Microsoft big data solutions

CERN Document Server

Jorgensen, Adam; Welch, John; Clark, Dan; Price, Christopher; Mitchell, Brian

2014-01-01

Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all,

Big data analytics turning big data into big money

CERN Document Server

Ohlhorst, Frank J

2012-01-01

Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportuni

Extensive range overlap between heliconiine sister species: evidence for sympatric speciation in butterflies?

Science.gov (United States)

Rosser, Neil; Kozak, Krzysztof M; Phillimore, Albert B; Mallet, James

2015-06-30

Sympatric speciation is today generally viewed as plausible, and some well-supported examples exist, but its relative contribution to biodiversity remains to be established. We here quantify geographic overlap of sister species of heliconiine butterflies, and use age-range correlations and spatial simulations of the geography of speciation to infer the frequency of sympatric speciation. We also test whether shifts in mimetic wing colour pattern, host plant use and climate niche play a role in speciation, and whether such shifts are associated with sympatry. Approximately a third of all heliconiine sister species pairs exhibit near complete range overlap, and analyses of the observed patterns of range overlap suggest that sympatric speciation contributes 32%-95% of speciation events. Müllerian mimicry colour patterns and host plant choice are highly labile traits that seem to be associated with speciation, but we find no association between shifts in these traits and range overlap. In contrast, climatic niches of sister species are more conserved. Unlike birds and mammals, sister species of heliconiines are often sympatric and our inferences using the most recent comparative methods suggest that sympatric speciation is common. However, if sister species spread rapidly into sympatry (e.g. due to their similar climatic niches), then assumptions underlying our methods would be violated. Furthermore, although we find some evidence for the role of ecology in speciation, ecological shifts did not show the associations with range overlap expected under sympatric speciation. We delimit species of heliconiines in three different ways, based on "strict and " "relaxed" biological species concepts (BSC), as well as on a surrogate for the widely-used "diagnostic" version of the phylogenetic species concept (PSC). We show that one reason why more sympatric speciation is inferred in heliconiines than in birds may be due to a different culture of species delimitation in the two

Summary big data

CERN Document Server

2014-01-01

This work offers a summary of Cukier the book: "Big Data: A Revolution That Will Transform How we Live, Work, and Think" by Viktor Mayer-Schonberg and Kenneth. Summary of the ideas in Viktor Mayer-Schonberg's and Kenneth Cukier's book: " Big Data " explains that big data is where we use huge quantities of data to make better predictions based on the fact we identify patters in the data rather than trying to understand the underlying causes in more detail. This summary highlights that big data will be a source of new economic value and innovation in the future. Moreover, it shows that it will

Exploring the transition from\\ud staff nurse to\\ud ward sister/manager –\\ud An exploratory case study

OpenAIRE

Enterkin, Judith

2016-01-01

Background\\ud The ward sister/manager figure has traditionally been considered the ward based\\ud clinical leader. This role has evolved over time in response to professional and\\ud political demands; despite or because of this, reports of role ambiguity exist and\\ud the ward sister/manager position has become increasingly difficult to recruit to,\\ud with nurses arguably looking to roles perceived to have greater influence and\\ud status, but less onerous managerial responsibility. Understandin...

Product design pattern based on big data-driven scenario

Directory of Open Access Journals (Sweden)

Conggang Yu

2016-07-01

Full Text Available This article discusses about new product design patterns in the big data era, gives designer a new rational thinking way, and is a new way to understand the design of the product. Based on the key criteria of the product design process, category, element, and product are used to input the data, which comprises concrete data and abstract data as an enlargement of the criteria of product design process for the establishment of a big data-driven product design pattern’s model. Moreover, an experiment and a product design case are conducted to verify the feasibility of the new pattern. Ultimately, we will conclude that the data-driven product design has two patterns: one is the concrete data supporting the product design, namely “product–data–product” pattern, and the second is based on the value of the abstract data for product design, namely “data–product–data” pattern. Through the data, users are involving themselves in the design development process. Data and product form a huge network, and data plays a role of connection or node. So the essence of the design is to find a new connection based on element, and to find a new node based on category.

Colchicine promotes a change in chromosome structure without loss of sister chromatid cohesion in prometaphase I-arrested bivalents.

Science.gov (United States)

Rodríguez, E M; Parra, M T; Rufas, J S; Suja, J A

2001-12-01

In somatic cells colchicine promotes the arrest of cell division at prometaphase, and chromosomes show a sequential loss of sister chromatid arm and centromere cohesion. In this study we used colchicine to analyse possible changes in chromosome structure and sister chromatid cohesion in prometaphase I-arrested bivalents of the katydid Pycnogaster cucullata. After silver staining we observed that in colchicine-arrested prometaphase I bivalents, and in contrast to what was found in control bivalents, sister kinetochores appeared individualised and sister chromatid axes were completely separated all along their length. However, this change in chromosome structure occurred without loss of sister chromatid arm cohesion. We also employed the MPM-2 monoclonal antibody against mitotic phosphoproteins on control and colchicine-treated spermatocytes. In control metaphase I bivalents this antibody labelled the tightly associated sister kinetochores and the interchromatid domain. By contrast, in colchicine-treated prometaphase I bivalents individualised sister kinetochores appeared labelled, but the interchromatid domain did not show labelling. These results support the notion that MPM-2 phosphoproteins, probably DNA topoisomerase IIalpha, located in the interchromatid domain act as "chromosomal staples" associating sister chromatid axes in metaphase I bivalents. The disappearance of these chromosomal staples would induce a change in chromosome structure, as reflected by the separation of sister kinetochores and sister axes, but without a concomitant loss of sister chromatid cohesion.

Big Opportunities and Big Concerns of Big Data in Education

Science.gov (United States)

Wang, Yinying

2016-01-01

Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the…

Benchmarking Big Data Systems and the BigData Top100 List.

Science.gov (United States)

Baru, Chaitanya; Bhandarkar, Milind; Nambiar, Raghunath; Poess, Meikel; Rabl, Tilmann

2013-03-01

"Big data" has become a major force of innovation across enterprises of all sizes. New platforms with increasingly more features for managing big datasets are being announced almost on a weekly basis. Yet, there is currently a lack of any means of comparability among such platforms. While the performance of traditional database systems is well understood and measured by long-established institutions such as the Transaction Processing Performance Council (TCP), there is neither a clear definition of the performance of big data systems nor a generally agreed upon metric for comparing these systems. In this article, we describe a community-based effort for defining a big data benchmark. Over the past year, a Big Data Benchmarking Community has become established in order to fill this void. The effort focuses on defining an end-to-end application-layer benchmark for measuring the performance of big data applications, with the ability to easily adapt the benchmark specification to evolving challenges in the big data space. This article describes the efforts that have been undertaken thus far toward the definition of a BigData Top100 List. While highlighting the major technical as well as organizational challenges, through this article, we also solicit community input into this process.

Think big: learning contexts, algorithms and data science

Directory of Open Access Journals (Sweden)

Baldassarre Michele

2016-12-01

Full Text Available Due to the increasing growth in available data in recent years, all areas of research and the managements of institutions and organisations, specifically schools and universities, feel the need to give meaning to this availability of data. This article, after a brief reference to the definition of big data, intends to focus attention and reflection on their type to proceed to an extension of their characterisation. One of the hubs to make feasible the use of Big Data in operational contexts is to give a theoretical basis to which to refer. The Data, Information, Knowledge and Wisdom (DIKW model correlates these four aspects, concluding in Data Science, which in many ways could revolutionise the established pattern of scientific investigation. The Learning Analytics applications on online learning platforms can be tools for evaluating the quality of teaching. And that is where some problems arise. It becomes necessary to handle with care the available data. Finally, a criterion for deciding whether it makes sense to think of an analysis based on Big Data can be to think about the interpretability and relevance in relation to both institutional and personal processes.

Conociendo Big Data

Directory of Open Access Journals (Sweden)

Juan José Camargo-Vega

2014-12-01

Full Text Available Teniendo en cuenta la importancia que ha adquirido el término Big Data, la presente investigación buscó estudiar y analizar de manera exhaustiva el estado del arte del Big Data; además, y como segundo objetivo, analizó las características, las herramientas, las tecnologías, los modelos y los estándares relacionados con Big Data, y por último buscó identificar las características más relevantes en la gestión de Big Data, para que con ello se pueda conocer todo lo concerniente al tema central de la investigación.La metodología utilizada incluyó revisar el estado del arte de Big Data y enseñar su situación actual; conocer las tecnologías de Big Data; presentar algunas de las bases de datos NoSQL, que son las que permiten procesar datos con formatos no estructurados, y mostrar los modelos de datos y las tecnologías de análisis de ellos, para terminar con algunos beneficios de Big Data.El diseño metodológico usado para la investigación fue no experimental, pues no se manipulan variables, y de tipo exploratorio, debido a que con esta investigación se empieza a conocer el ambiente del Big Data.

Big Data and Big Science

OpenAIRE

Di Meglio, Alberto

2014-01-01

Brief introduction to the challenges of big data in scientific research based on the work done by the HEP community at CERN and how the CERN openlab promotes collaboration among research institutes and industrial IT companies. Presented at the FutureGov 2014 conference in Singapore.

A Big Video Manifesto

DEFF Research Database (Denmark)

Mcilvenny, Paul Bruce; Davidsen, Jacob

2017-01-01

and beautiful visualisations. However, we also need to ask what the tools of big data can do both for the Humanities and for more interpretative approaches and methods. Thus, we prefer to explore how the power of computation, new sensor technologies and massive storage can also help with video-based qualitative......For the last few years, we have witnessed a hype about the potential results and insights that quantitative big data can bring to the social sciences. The wonder of big data has moved into education, traffic planning, and disease control with a promise of making things better with big numbers...

Effect of chloramphenicol on sister chromatid exchange in bovine fibroblasts.

Science.gov (United States)

Arruga, M V; Catalan, J; Moreno, C

1992-03-01

The genotoxic potential of different chloramphenicol concentrations (5, 20, 40 and 60 micrograms ml-1) was investigated in bovine fibroblast primary lines by sister chromatid exchange assay. Chloramphenicol acted for long enough to ensure similar effects to persistent storage in the kidney. In this experiment 10 micrograms ml-1 of 5-bromodeoxyuridine was added for 60 hours for all doses of chloramphenicol and to the control. When the tissue culture cells were exposed to increasing doses, increased numbers of sister chromatid exchanges developed. Differences were significantly different to the control.

Food Yields and Nutrient Analyses of the Three Sisters: A Haudenosaunee Cropping System

Directory of Open Access Journals (Sweden)

Jane Mt.Pleasant

2016-11-01

Full Text Available Scholars have studied The Three Sisters, a traditional cropping system of the Haudenosaunee (Iroquois, from multiple perspectives. However, there is no research examining food yields, defined as the quantities of energy and protein produced per unit land area, from the cropping system within Iroquoia. This article compares food yields and other nutrient contributions from the Three Sisters, comprised of interplanted maize, bean and pumpkin, with monocultures of these same crops. The Three Sisters yields more energy (12.25 x 106 kcal/ha and more protein (349 kg/ha than any of the crop monocultures or mixtures of monocultures planted to the same area. The Three Sisters supplies 13.42 people/ha/yr. with energy and 15.86 people/ha/yr. with protein. Nutrient contents of the crops are further enhanced by nixtamalization, a traditional processing technique where maize is cooked in a high alkaline solution. This process increases calcium, protein quality, and niacin in maize.

Intelligent Control of Micro Grid: A Big Data-Based Control Center

Science.gov (United States)

Liu, Lu; Wang, Yanping; Liu, Li; Wang, Zhiseng

2018-01-01

In this paper, a structure of micro grid system with big data-based control center is introduced. Energy data from distributed generation, storage and load are analized through the control center, and from the results new trends will be predicted and applied as a feedback to optimize the control. Therefore, each step proceeded in micro grid can be adjusted and orgnized in a form of comprehensive management. A framework of real-time data collection, data processing and data analysis will be proposed by employing big data technology. Consequently, a integrated distributed generation and a optimized energy storage and transmission process can be implemented in the micro grid system.

High prevalence of metabolic syndrome in young Hispanic women: findings from the national Sister to Sister campaign.

Science.gov (United States)

Rodriguez, Fátima; Naderi, Sahar; Wang, Yun; Johnson, Caitlin E; Foody, JoAnne M

2013-04-01

Hispanics are the fastest growing segment of the U.S. population and have a higher prevalence of cardiometabolic risk factors as compared with non-Hispanic whites. Further data suggests that Hispanics have undiagnosed complications of metabolic syndrome, namely diabetes mellitus, at an earlier age. We sought to better understand the epidemiology of metabolic syndrome in Hispanic women using data from a large, community-based health screening program. Using data from the Sister to Sister: The Women's Heart Health Foundation community health fairs from 2008 to 2009 held in 17 U.S. cities, we sought to characterize how cardiometabolic risk profiles vary across age for women by race and ethnicity. Metabolic syndrome was defined using the updated National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) guidelines, which included three or more of the following: Waist circumference ≥35 inches, triglycerides ≥150 mg/dL, high-density lipoprotein (HDL) <50 mg/dL, systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg, or a fasting glucose ≥100 mg/dL. A total of 6843 community women were included in the analyses. Metabolic syndrome had a prevalence of 35%. The risk-adjusted odds ratio for metabolic syndrome in Hispanic women versus white women was 1.7 (95% confidence interval, 1.4, 2.0). Dyslipidemia was the strongest predictor of metabolic syndrome among Hispanic women. This disparity appeared most pronounced for younger women. Additional predictors of metabolic syndrome included black race, increasing age, and smoking. In a large, nationally representative sample of women, we found that metabolic syndrome was highly prevalent among young Hispanic women. Efforts specifically targeted to identifying these high-risk women are necessary to prevent the cardiovascular morbidity and mortality associated with metabolic syndrome.

Assessing Big Data

DEFF Research Database (Denmark)

Leimbach, Timo; Bachlechner, Daniel

2015-01-01

In recent years, big data has been one of the most controversially discussed technologies in terms of its possible positive and negative impact. Therefore, the need for technology assessments is obvious. This paper first provides, based on the results of a technology assessment study, an overview...... of the potential and challenges associated with big data and then describes the problems experienced during the study as well as methods found helpful to address them. The paper concludes with reflections on how the insights from the technology assessment study may have an impact on the future governance of big...... data....

Three Sisters Mountain Village development transformation of old coal mine properties into modern day use

International Nuclear Information System (INIS)

Fox, B.

2006-01-01

This paper discussed the development of the Three Sisters Mountain Village, located close to Canmore, Alberta. The paper provided the history and background of the mining and development of the site. It discussed underground mining methodology and planned housing and industrial development. The village included plans for 10,000 residential homes, 2 golf courses, a wellness centre, a school, commercial buildings and wildlife corridors. Environmental concerns were also addressed, as Canmore contains a series of natural wildlife corridors, which act as migration and travelling routes for elk and deer as well as cougars, grizzly bears, and other animals. These routes are essential for the survival of the different herds and animal species. The development progress strategy was discussed. The Three Sisters Mountain Village Development commissioned Golder Associates Ltd. to study and address the environmental concerns of the stakeholders regarding the migrating routes of wildlife. Mining works mitigation, including mapping of the constraint zones, knowledge of subsidence issues and the effects of subsidence on structural stress and the ability to analysis field data to predict potential problems was also presented along with a methodology for mitigation and choice of backfill material to be used to fill the mine workings. The advantages of using concrete paste backfill were also identified

Three Sisters Mountain Village development transformation of old coal mine properties into modern day use

Energy Technology Data Exchange (ETDEWEB)

Fox, B. [Golder Paste Technology Ltd., Sudbury, ON (Canada)

2006-07-01

This paper discussed the development of the Three Sisters Mountain Village, located close to Canmore, Alberta. The paper provided the history and background of the mining and development of the site. It discussed underground mining methodology and planned housing and industrial development. The village included plans for 10,000 residential homes, 2 golf courses, a wellness centre, a school, commercial buildings and wildlife corridors. Environmental concerns were also addressed, as Canmore contains a series of natural wildlife corridors, which act as migration and travelling routes for elk and deer as well as cougars, grizzly bears, and other animals. These routes are essential for the survival of the different herds and animal species. The development progress strategy was discussed. The Three Sisters Mountain Village Development commissioned Golder Associates Ltd. to study and address the environmental concerns of the stakeholders regarding the migrating routes of wildlife. Mining works mitigation, including mapping of the constraint zones, knowledge of subsidence issues and the effects of subsidence on structural stress and the ability to analysis field data to predict potential problems was also presented along with a methodology for mitigation and choice of backfill material to be used to fill the mine workings. The advantages of using concrete paste backfill were also identified.

Analysis of Computer Network Information Based on "Big Data"

Science.gov (United States)

Li, Tianli

2017-11-01

With the development of the current era, computer network and large data gradually become part of the people's life, people use the computer to provide convenience for their own life, but at the same time there are many network information problems has to pay attention. This paper analyzes the information security of computer network based on "big data" analysis, and puts forward some solutions.

Three Sisters Dam: Investigations and monitoring

International Nuclear Information System (INIS)

Slopek, R.J.; Courage, L.J.R.; Keys, R.A.

1990-01-01

The geotechnical investigations, monitoring and interpretation of data associated with the evaluation of the Three Sisters Dam, which has been suffering from excessive seepage and is in need of enhancement, are outlined. The Three Sisters Dam is located in the continental ranges of the Rocky Mountains in Alberta, impounding the Spray Reservoir, and is founded on 60 m of interbedded sand, gravel, silt and clay layers. The computer code PC-SEEP was used to evaluate seepage. Details are provided of drilling, ground-penetrating radar surveys, seismic surveys, penstock inspection, sinkhole activity, piezometer monitoring, silt wells, settlement monuments, and tailrace monitoring. The intensive investigations of the foundations showed that they consist of a complex formation of interfingered stratified layers and leases of talus and glaciofluvial deposits. Due to the depth and nature of these materials drill hole penetration was limited to the use of the Becker hammer. This equipment successfully delineated the major soil horizons of the foundation. The continued information attained from inspection, drilling, testing, radar surveys, seismic work, monitoring of piezometers, leakage, silt wells and settlement monuments indicated that there are no large voids within the foundation of the dam. 2 refs., 12 figs

Psyche’s Sisters: Ambivalence of Sisterhood in Twentieth-century Irish Women’s Short Stories

Directory of Open Access Journals (Sweden)

Ann Wan-lih Chang

2013-03-01

Full Text Available This paper examines and evaluates representations of problematic sisterly relationships in twentieth-century Irish women’s stories which display an emphasis on ambivalence and sibling rivalry.  The paper is based primarily on the literary output of Mary Lavin, Clare Boylan, Moy McCrory, Éilís Ní Dhuibhne, Jan Kennedy, Mary Morrissy and Claire Keegan.  The paper seeks, by reference both to feminist studies and Irish women’s short stories, to demonstrate the consequences and causes of a divided sisterhood which itself may be traced back to a suppression of expression of female solidarity embedded in western culture and manifested in western literary heritage.  Typically, such stories depict a conflict sourced in the need to develop self-identity and framed within the constraints imposed by separate social roles.  This kind of conflict results potentially in rivalry, antagonism, ambivalence, and the domination of one sibling by another.  Daughters/sisters are often depicted in these stories both as competing with each other for limited resources and also as seeking a sense of personal identity through mutual polarisation.  There are also stories into which are woven undertones of domination disguised as sisterly closeness, for which the actual motivation seems to be a repressed aspiration for intimacy.

A study and analysis of recommendation systems for location-based social network (LBSN with big data

Directory of Open Access Journals (Sweden)

Murale Narayanan

2016-03-01

Full Text Available Recommender systems play an important role in our day-to-day life. A recommender system automatically suggests an item to a user that he/she might be interested in. Small-scale datasets are used to provide recommendations based on location, but in real time, the volume of data is large. We have selected Foursquare dataset to study the need for big data in recommendation systems for location-based social network (LBSN. A few quality parameters like parallel processing and multimodal interface have been selected to study the need for big data in recommender systems. This paper provides a study and analysis of quality parameters of recommendation systems for LBSN with big data.

IMPLEMENTASI SISTER PROVINCE PROVINSI JAWA TENGAH DENGAN NEGARA BAGIAN QUEENSLAND AUSTRALIA DI BIDANG PERTANIAN

Directory of Open Access Journals (Sweden)

Reni Windiani

2016-02-01

Full Text Available Globalization on national context has insisted the central government to work together and share duties and rights with the local government in order to achieve the national interest.  In Indonesia, UU 32/2004 about local government provide the chance for them to become more active in foreign policy, such as doing the cooperation in sister province/sister city program. The Central Java Province had done many sister province/sister city program with some partners aboard, such as Fujian province (China, Chungchoeng buk-do province (South Korea and the Queensland province (Australia.  The cooperation cover many sectors such as agriculture, city and village development, transportation and tourism, industry, trade and infestation, education, science and technology, and other sectors that will be confer in advance. From all of the cooperation that have been done between Central Java Province and Queensland, the author, is interested to have research on farming, because central government has had many cows imported from Australia.  This research is become important because central java province is one of the major of national fresh meat distributors. This research is using a qualitative method, with descriptive type of research.  This research has three research questions: How effective is the Sister Province program in Central Java with the Queensland in farm sector? What is the obstacle that holds the Sister Province program in Central Java with the Queensland in farm sector? How is the prospect of Sister Province program in Central Java with the Queensland in farm sector? This result of this research is to prove that the implementation of Sister Province program in Central Java with the Queensland in farm sectors is not effective.  Some of the implementation variables of this program have not been fulfilled. Communication, financial resources and bureaucracy structure are some of the variables that have weakness on this program.  Act of

Analyses of Digman's child-personality data: derivation of Big-Five factor scores from each of six samples.

Science.gov (United States)

Goldberg, L R

2001-10-01

One of the world's richest collections of teacher descriptions of elementary-school children was obtained by John M. Digman from 1959 to 1967 in schools on two Hawaiian islands. In six phases of data collection, 88 teachers described 2,572 of their students, using one of five different sets of personality variables. The present report provides findings from new analyses of these important data, which have never before been analyzed in a comprehensive manner. When factors developed from carefully selected markers of the Big-Five factor structure were compared to those based on the total set of variables in each sample, the congruence between both types of factors was quite high. Attempts to extend the structure to 6 and 7 factors revealed no other broad factors beyond the Big Five in any of the 6 samples. These robust findings provide significant new evidence for the structure of teacher-based assessments of child personality attributes.

Constraining volcanic inflation at Three Sisters Volcanic Field in Oregon, USA, through microgravity and deformation modeling

Science.gov (United States)

Zurek, Jeffrey; William-Jones, Glyn; Johnson, Dan; Eggers, Al

2012-10-01

Microgravity data were collected between 2002 and 2009 at the Three Sisters Volcanic Complex, Oregon, to investigate the causes of an ongoing deformation event west of South Sister volcano. Three different conceptual models have been proposed as the causal mechanism for the deformation event: (1) hydraulic uplift due to continual injection of magma at depth, (2) pressurization of hydrothermal systems and (3) viscoelastic response to an initial pressurization at depth. The gravitational effect of continual magma injection was modeled to be 20 to 33 μGal at the center of the deformation field with volumes based on previous deformation studies. The gravity time series, however, did not detect a mass increase suggesting that a viscoelactic response of the crust is the most likely cause for the deformation from 2002 to 2009. The crust, deeper than 3 km, in the Three Sisters region was modeled as a Maxwell viscoelastic material and the results suggest a dynamic viscosity between 1018 to 5 × 1019 Pa s. This low crustal viscosity suggests that magma emplacement or stall depth is controlled by density and not the brittle ductile transition zone. Furthermore, these crustal properties and the observed geochemical composition gaps at Three Sisters can be best explained by different melt sources and limited magma mixing rather than fractional crystallization. More generally, low intrusion rates, low crustal viscosity, and multiple melt sources could also explain the whole rock compositional gaps observed at other arc volcanoes.

Vocational interests assessed at the end of high school predict life outcomes assessed 10 years later over and above IQ and Big Five personality traits.

Science.gov (United States)

Stoll, Gundula; Rieger, Sven; Lüdtke, Oliver; Nagengast, Benjamin; Trautwein, Ulrich; Roberts, Brent W

2017-07-01

Vocational interests are important aspects of personality that reflect individual differences in motives, goals, and personal strivings. It is therefore plausible that these characteristics have an impact on individuals' lives not only in terms of vocational outcomes, but also beyond the vocational domain. Yet the effects of vocational interests on various life outcomes have rarely been investigated. Using Holland's RIASEC taxonomy (Holland, 1997), which groups vocational interests into 6 broad domains, the present study examined whether vocational interests are significant predictors of life outcomes that show incremental validity over and above the Big Five personality traits. For this purpose, a cohort of German high school students (N = 3,023) was tracked over a period of 10 years after graduating from school. Linear and logistic regression analyses were used to examine the predictive validity of RIASEC interests and Big Five personality traits. Nine outcomes from the domains of work, relationships, and health were investigated. The results indicate that vocational interests are important predictors of life outcomes that show incremental validity over the Big Five personality traits. Vocational interests were significant predictors of 7 of the 9 investigated outcomes: full-time employment, gross income, unemployment, being married, having children, never having had a relationship, and perceived health status. For work and relationship outcomes, vocational interests were even stronger predictors than the Big Five personality traits. For health-related outcomes, the results favored the personality traits. Effects were similar across gender for all outcomes-except 2 relationship outcomes. Possible explanations for these effects are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

IVF for premature ovarian failure: first reported births using oocytes donated from a twin sister.

LENUS (Irish Health Repository)

Sills, Eric Scott

2010-01-01

BACKGROUND: Premature ovarian failure (POF) remains a clinically challenging entity because in vitro fertilisation (IVF) with donor oocytes is currently the only treatment known to be effective. METHODS: A 33 year-old nulligravid patient with a normal karyotype was diagnosed with POF; she had a history of failed fertility treatments and had an elevated serum FSH (42 mIU\\/ml). Oocytes donated by her dizygotic twin sister were used for IVF. The donor had already completed a successful pregnancy herself and subsequently produced a total of 10 oocytes after a combined FSH\\/LH superovulation regime. These eggs were fertilised with sperm from the recipient\\'s husband via intracytoplasmic injection and two fresh embryos were transferred to the recipient on day three. RESULTS: A healthy twin pregnancy resulted from IVF; two boys were delivered by caesarean section at 39 weeks\\' gestation. Additionally, four embryos were cryopreserved for the recipient\\'s future use. The sister-donor achieved another natural pregnancy six months after oocyte retrieval, resulting in a healthy singleton delivery. CONCLUSION: POF is believed to affect approximately 1% of reproductive age females, and POF patients with a sister who can be an oocyte donor for IVF are rare. Most such IVF patients will conceive from treatment using oocytes from an anonymous oocyte donor. This is the first report of births following sister-donor oocyte IVF in Ireland. Indeed, while sister-donor IVF has been successfully undertaken by IVF units elsewhere, this is the only known case where oocyte donation involved twin sisters. As with all types of donor gamete therapy, pre-treatment counselling is important in the circumstance of sister oocyte donation.

The Structural Consequences of Big Data-Driven Education.

Science.gov (United States)

Zeide, Elana

2017-06-01

Educators and commenters who evaluate big data-driven learning environments focus on specific questions: whether automated education platforms improve learning outcomes, invade student privacy, and promote equality. This article puts aside separate unresolved-and perhaps unresolvable-issues regarding the concrete effects of specific technologies. It instead examines how big data-driven tools alter the structure of schools' pedagogical decision-making, and, in doing so, change fundamental aspects of America's education enterprise. Technological mediation and data-driven decision-making have a particularly significant impact in learning environments because the education process primarily consists of dynamic information exchange. In this overview, I highlight three significant structural shifts that accompany school reliance on data-driven instructional platforms that perform core school functions: teaching, assessment, and credentialing. First, virtual learning environments create information technology infrastructures featuring constant data collection, continuous algorithmic assessment, and possibly infinite record retention. This undermines the traditional intellectual privacy and safety of classrooms. Second, these systems displace pedagogical decision-making from educators serving public interests to private, often for-profit, technology providers. They constrain teachers' academic autonomy, obscure student evaluation, and reduce parents' and students' ability to participate or challenge education decision-making. Third, big data-driven tools define what "counts" as education by mapping the concepts, creating the content, determining the metrics, and setting desired learning outcomes of instruction. These shifts cede important decision-making to private entities without public scrutiny or pedagogical examination. In contrast to the public and heated debates that accompany textbook choices, schools often adopt education technologies ad hoc. Given education

Catholic nursing sisters and brothers and racial justice in mid-20th-century America.

Science.gov (United States)

Wall, Barbra Mann

2009-01-01

This historical article considers nursing's work for social justice in the 1960s civil rights movement through the lens of religious sisters and brothers who advocated for racial equality. The article examines Catholic nurses' work with African Americans in the mid-20th century that took place amid the prevailing social conditions of poverty and racial disempowerment, conditions that were linked to serious health consequences. Historical methodology is used within the framework of "bearing witness," a term often used in relation to the civil rights movement and one the sisters themselves employed. Two situations involving nurses in the mid-20th century are examined: the civil rights movement in Selma, Alabama, and the actions for racial justice in Chicago, Illinois. The thoughts and actions of Catholic sister and brother nurses in the mid-20th century are chronicled, including those few sister nurses who stepped outside their ordinary roles in an attempt to change an unjust system entirely.

Making big sense from big data in toxicology by read-across.

Science.gov (United States)

Hartung, Thomas

2016-01-01

Modern information technologies have made big data available in safety sciences, i.e., extremely large data sets that may be analyzed only computationally to reveal patterns, trends and associations. This happens by (1) compilation of large sets of existing data, e.g., as a result of the European REACH regulation, (2) the use of omics technologies and (3) systematic robotized testing in a high-throughput manner. All three approaches and some other high-content technologies leave us with big data--the challenge is now to make big sense of these data. Read-across, i.e., the local similarity-based intrapolation of properties, is gaining momentum with increasing data availability and consensus on how to process and report it. It is predominantly applied to in vivo test data as a gap-filling approach, but can similarly complement other incomplete datasets. Big data are first of all repositories for finding similar substances and ensure that the available data is fully exploited. High-content and high-throughput approaches similarly require focusing on clusters, in this case formed by underlying mechanisms such as pathways of toxicity. The closely connected properties, i.e., structural and biological similarity, create the confidence needed for predictions of toxic properties. Here, a new web-based tool under development called REACH-across, which aims to support and automate structure-based read-across, is presented among others.

Living with a brother or sister with epilepsy: siblings' experiences.

Science.gov (United States)

Hames, Annette; Appleton, Richard

2009-12-01

There is conflicting evidence about the impact of disability upon siblings, and very little research on the siblings of children with epilepsy. There is some evidence that siblings who have less accurate information exhibit more distress. The aim of this study was to assess siblings' response to having a brother or sister with epilepsy and to begin to develop information for them. Parents of children attending paediatric neurology outpatient departments were invited to participate in a pilot study. Parents who consented to take part were asked if they had previously received information for siblings. Parents and siblings participated in a semi-structured interview and siblings were also invited to submit a personal account of living with a brother or sister who had epilepsy. Twenty-five families with a child with epilepsy aged 2.5-15 years initially agreed to take part. None of the families stated that they had ever seen or received any information specifically for siblings. Fourteen siblings from the 25 families, aged 8-25 years, provided a personal account of what it was like living with a brother or sister with epilepsy. Siblings' accounts included both negative and positive feelings, and specifically feelings of care and love for their sibling. This initial study suggests that siblings of children with epilepsy have many positive but also early negative feelings. The results are limited by the size of the study, the fact that most siblings were older sisters, and the mean time since diagnosis was 6 years. Finally, it is hoped that the personal accounts collected in this study will be published for the benefit of other siblings of children with epilepsy.

Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis

Directory of Open Access Journals (Sweden)

Alexandra Amado

2018-01-01

Full Text Available Given the research interest on Big Data in Marketing, we present a research literature analysis based on a text mining semi-automated approach with the goal of identifying the main trends in this domain. In particular, the analysis focuses on relevant terms and topics related with five dimensions: Big Data, Marketing, Geographic location of authors’ affiliation (countries and continents, Products, and Sectors. A total of 1560 articles published from 2010 to 2015 were scrutinized. The findings revealed that research is bipartite between technological and research domains, with Big Data publications not clearly aligning cutting edge techniques toward Marketing benefits. Also, few inter-continental co-authored publications were found. Moreover, findings show that research in Big Data applications to Marketing is still in an embryonic stage, thus making it essential to develop more direct efforts toward business for Big Data to thrive in the Marketing arena.

The Big-Fish-Little-Pond Effect on Academic Self-Concept.

Science.gov (United States)

Marsh, Herbert W.

Marsh and Parker (1984) described the big-fish-little-pond effect (BFLPE) whereby equally able students have lower academic self-concepts in high-ability schools than in low-ability schools. The present investigation, a reanalysis of the Youth in Transition data, supported the generality of the earlier findings and demonstrated new theoretical…

Spinal involvement in Camptodactyly Arthropathy Coxa-vara Pericarditis (CACP) syndrome in two Yemeni sisters

NARCIS (Netherlands)

Emad, Yasser; Ragab, Yasser; Ibrahim, Osama; Khalifa, Maher; Dawood, Ahmed; Rasker, Johannes J.

2017-01-01

Aim of the work The objective of this clinical report is to describe the detailed magnetic resonance imaging (MRI) findings of the spine, knee and hip joints in two young sisters with Camptodactyly Arthropathy Coxa-vara Pericarditis (CACP) syndrome. Cases report In two young sisters, both had normal

Brothers and Sisters of Adults with Mental Retardation: Gendered Nature of the Sibling Relationship.

Science.gov (United States)

Orsmond, Gael I.; Seltzer, Marsha Mailick

2000-01-01

Differences and similarities between 245 brothers and sisters of adults with mental retardation in the sibling relationship were examined. Sisters scored higher in the caregiving, companionship, and positive affect aspects of the sibling relationship. Sibling involvement increased over time, but was dependent upon changes in maternal health.…

Two Sisters with Idiopathic Pulmonary Hemosiderosis

Directory of Open Access Journals (Sweden)

Mehmet Gencer

2007-01-01

Full Text Available Idiopathic pulmonary hemosiderosis (IPH is a rare cause of diffuse alveolar hemorrhage with unknown etiology. In the present report, the presentations of two sisters are described: one sister had IPH, eosinophilia and a high serum immunoglobulin E (IgE level; and the other had IPH, pneumothorax, eosinophilia and a high serum IgE level. Both cases had quite unusual presentations. The first patient was 23 years of age, and had suffered from dry cough and progressive dyspnea for four years. Her hemoglobin level was 60 g/L, total serum IgE level was 900 U/mL and eosinophilia was 9%. Her chest radiography revealed diffuse infiltration. She died due to respiratory failure. The second patient was 18 years of age. She had also suffered from dry cough and gradually increasing dyspnea for two years. She had partial pneumothorax in the right lung and diffuse infiltration in other pulmonary fields on chest radiography. Her hemoglobin level was 99 g/L, total serum IgE level was 1200 U/mL and eosinophilia was 8%. IPH was diagnosed by open lung biopsy. All these findings suggested that familial or allergic factors, as well as immunological factors, might have contributed to the etiology of IPH.

Identical Twin Primigravid Sisters -Spontaneous Labour and ...

African Journals Online (AJOL)

We report 2 cases of identical twin sisters, the older sibling getting married 14 months earlier but both got pregnant for their first child at about the same time and were managed by the same Obstetrician and fell into spontaneous labour within a few hours of each other. Both were delivered by emergency caesarean section ...

How Big Are "Martin's Big Words"? Thinking Big about the Future.

Science.gov (United States)

Gardner, Traci

"Martin's Big Words: The Life of Dr. Martin Luther King, Jr." tells of King's childhood determination to use "big words" through biographical information and quotations. In this lesson, students in grades 3 to 5 explore information on Dr. King to think about his "big" words, then they write about their own…

Freud on Brothers and Sisters: A Neglected Topic

Science.gov (United States)

Sherwin-White, Susan

2007-01-01

This paper explores Freud's developing thought on brothers and sisters, and their importance in his psychoanalytical writings and clinical work. Freud's work on sibling psychology has been seriously undervalued. This paper aims to give due recognition to Freud's work in this area. (Contains 1 note.)

Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.

Science.gov (United States)

Westra, Bonnie L; Clancy, Thomas R; Sensmeier, Joyce; Warren, Judith J; Weaver, Charlotte; Delaney, Connie W

2015-01-01

The integration of Big Data from electronic health records and other information systems within and across health care enterprises provides an opportunity to develop actionable predictive models that can increase the confidence of nursing leaders' decisions to improve patient outcomes and safety and control costs. As health care shifts to the community, mobile health applications add to the Big Data available. There is an evolving national action plan that includes nursing data in Big Data science, spearheaded by the University of Minnesota School of Nursing. For the past 3 years, diverse stakeholders from practice, industry, education, research, and professional organizations have collaborated through the "Nursing Knowledge: Big Data Science" conferences to create and act on recommendations for inclusion of nursing data, integrated with patient-generated, interprofessional, and contextual data. It is critical for nursing leaders to understand the value of Big Data science and the ways to standardize data and workflow processes to take advantage of newer cutting edge analytics to support analytic methods to control costs and improve patient quality and safety.

Changing the personality of a face: Perceived Big Two and Big Five personality factors modeled in real photographs.

Science.gov (United States)

Walker, Mirella; Vetter, Thomas

2016-04-01

General, spontaneous evaluations of strangers based on their faces have been shown to reflect judgments of these persons' intention and ability to harm. These evaluations can be mapped onto a 2D space defined by the dimensions trustworthiness (intention) and dominance (ability). Here we go beyond general evaluations and focus on more specific personality judgments derived from the Big Two and Big Five personality concepts. In particular, we investigate whether Big Two/Big Five personality judgments can be mapped onto the 2D space defined by the dimensions trustworthiness and dominance. Results indicate that judgments of the Big Two personality dimensions almost perfectly map onto the 2D space. In contrast, at least 3 of the Big Five dimensions (i.e., neuroticism, extraversion, and conscientiousness) go beyond the 2D space, indicating that additional dimensions are necessary to describe more specific face-based personality judgments accurately. Building on this evidence, we model the Big Two/Big Five personality dimensions in real facial photographs. Results from 2 validation studies show that the Big Two/Big Five are perceived reliably across different samples of faces and participants. Moreover, results reveal that participants differentiate reliably between the different Big Two/Big Five dimensions. Importantly, this high level of agreement and differentiation in personality judgments from faces likely creates a subjective reality which may have serious consequences for those being perceived-notably, these consequences ensue because the subjective reality is socially shared, irrespective of the judgments' validity. The methodological approach introduced here might prove useful in various psychological disciplines. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Examining the Big-Fish-Little-Pond Effect on Students' Self-Concept of Learning Science in Taiwan Based on the TIMSS Databases

Science.gov (United States)

Liou, Pey-Yan

2014-08-01

The purpose of this study is to examine the relationship between student self-concept and achievement in science in Taiwan based on the big-fish-little-pond effect (BFLPE) model using the Trends in International Mathematics and Science Study (TIMSS) 2003 and 2007 databases. Hierarchical linear modeling was used to examine the effects of the student-level and school-level science achievement on student self-concept of learning science. The results indicated that student science achievement was positively associated with individual self-concept of learning science in both TIMSS 2003 and 2007. On the contrary, while school-average science achievement was negatively related to student self-concept in TIMSS 2003, it had no statistically significant relationship with student self-concept in TIMSS 2007. The findings of this study shed light on possible explanations for the existence of BFLPE and also lead to an international discussion on the generalization of BFLPE.

Genome-wide mapping of sister chromatid exchange events in single yeast cells using Strand-seq

NARCIS (Netherlands)

Claussin, Clemence; Porubsky, David; Spierings, Diana C. J.; Halsema, Nancy; Rentas, Stefan; Guryev, Victor; Lansdorp, Peter M.; Chang, Michael

2017-01-01

Homologous recombination involving sister chromatids is the most accurate, and thus most frequently used, form of recombination-mediated DNA repair. Despite its importance, sister chromatid recombination is not easily studied because it does not result in a change in DNA sequence, making

BigWig and BigBed: enabling browsing of large distributed datasets.

Science.gov (United States)

Kent, W J; Zweig, A S; Barber, G; Hinrichs, A S; Karolchik, D

2010-09-01

BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu.

[Some reflections on evidenced-based medicine, precision medicine, and big data-based research].

Science.gov (United States)

Tang, J L; Li, L M

2018-01-10

Evidence-based medicine remains the best paradigm for medical practice. However, evidence alone is not decisions; decisions must also consider resources available and the values of people. Evidence shows that most of those treated with blood pressure-lowering, cholesterol-lowering, glucose-lowering and anti-cancer drugs do not benefit from preventing severe complications such as cardiovascular events and deaths. This implies that diagnosis and treatment in modern medicine in many circumstances is imprecise. It has become a dream to identify and treat only those few who can respond to the treatment. Precision medicine has thus come into being. Precision medicine is however not a new idea and cannot rely solely on gene sequencing as it was initially proposed. Neither is the large cohort and multi-factorial approach a new idea; in fact it has been used widely since 1950s. Since its very beginning, medicine has never stopped in searching for more precise diagnostic and therapeutic methods and already made achievements at various levels of our understanding and knowledge, such as vaccine, blood transfusion, imaging, and cataract surgery. Genetic biotechnology is not the only path to precision but merely a new method. Most genes are found only weakly associated with disease and are thus unlikely to lead to great improvement in diagnostic and therapeutic precision. The traditional multi-factorial approach by embracing big data and incorporating genetic factors is probably the most realistic way ahead for precision medicine. Big data boasts of possession of the total population and large sample size and claims correlation can displace causation. They are serious misleading concepts. Science has never had to observe the totality in order to draw a valid conclusion; a large sample size is required only when the anticipated effect is small and clinically less meaningful; emphasis on correlation over causation is equivalent to rejection of the scientific principles and methods

Big Data as Governmentality

DEFF Research Database (Denmark)

Flyverbom, Mikkel; Madsen, Anders Koed; Rasche, Andreas

This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...... data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects...... shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact....

Effect of borax on immune cell proliferation and sister chromatid exchange in human chromosomes.

Science.gov (United States)

Pongsavee, Malinee

2009-10-30

Borax is used as a food additive. It becomes toxic when accumulated in the body. It causes vomiting, fatigue and renal failure. The heparinized blood samples from 40 healthy men were studied for the impact of borax toxicity on immune cell proliferation (lymphocyte proliferation) and sister chromatid exchange in human chromosomes. The MTT assay and Sister Chromatid Exchange (SCE) technic were used in this experiment with the borax concentrations of 0.1, 0.15, 0.2, 0.3 and 0.6 mg/ml. It showed that the immune cell proliferation (lymphocyte proliferation) was decreased when the concentrations of borax increased. The borax concentration of 0.6 mg/ml had the most effectiveness to the lymphocyte proliferation and had the highest cytotoxicity index (CI). The borax concentrations of 0.15, 0.2, 0.3 and 0.6 mg/ml significantly induced sister chromatid exchange in human chromosomes (P Borax had effects on immune cell proliferation (lymphocyte proliferation) and induced sister chromatid exchange in human chromosomes. Toxicity of borax may lead to cellular toxicity and genetic defect in human.

New Data, Old Tensions: Big Data, Personalized Learning, and the Challenges of Progressive Education

Science.gov (United States)

Dishon, Gideon

2017-01-01

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

A paper recommender system based on user's profile in big data ...

African Journals Online (AJOL)

These systems present a personalized proposal to users who seek to find a special kind of relevant data or their priorities through the big number of data. Recommendersystem based on personalization uses the user profile and in view of the fact that the user profile encompass information pertaining to the user priorities; ...

Social uses of prescribed school culture in the secondary education

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Norberto Dallabrida

2012-05-01

Full Text Available This paper seeks to understand the social uses of prescribed school culture nationally in three secondary schools of Florianopolis in the 1950s. Focused on Colégio Catarinense, administered by the Jesuits and dedicated exclusively to men; the Colégio Coração de Jesus, run by the Sisters of Divine Providence and with female customers; and the State College Dias Velho, public, free and for boys and girls. According to Roger Chartier, educational institutions are considered to appropriate themselves of cultural goods in different and creative ways. This socio-historical analysis is based on written documents and testimonials of teachers and students who worked at or attended these schools.

Big Data, Big Problems: A Healthcare Perspective.

Science.gov (United States)

Househ, Mowafa S; Aldosari, Bakheet; Alanazi, Abdullah; Kushniruk, Andre W; Borycki, Elizabeth M

2017-01-01

Much has been written on the benefits of big data for healthcare such as improving patient outcomes, public health surveillance, and healthcare policy decisions. Over the past five years, Big Data, and the data sciences field in general, has been hyped as the "Holy Grail" for the healthcare industry promising a more efficient healthcare system with the promise of improved healthcare outcomes. However, more recently, healthcare researchers are exposing the potential and harmful effects Big Data can have on patient care associating it with increased medical costs, patient mortality, and misguided decision making by clinicians and healthcare policy makers. In this paper, we review the current Big Data trends with a specific focus on the inadvertent negative impacts that Big Data could have on healthcare, in general, and specifically, as it relates to patient and clinical care. Our study results show that although Big Data is built up to be as a the "Holy Grail" for healthcare, small data techniques using traditional statistical methods are, in many cases, more accurate and can lead to more improved healthcare outcomes than Big Data methods. In sum, Big Data for healthcare may cause more problems for the healthcare industry than solutions, and in short, when it comes to the use of data in healthcare, "size isn't everything."

Broad phylogenomic sampling and the sister lineage of land plants.

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Ruth E Timme

Full Text Available The tremendous diversity of land plants all descended from a single charophyte green alga that colonized the land somewhere between 430 and 470 million years ago. Six orders of charophyte green algae, in addition to embryophytes, comprise the Streptophyta s.l. Previous studies have focused on reconstructing the phylogeny of organisms tied to this key colonization event, but wildly conflicting results have sparked a contentious debate over which lineage gave rise to land plants. The dominant view has been that 'stoneworts,' or Charales, are the sister lineage, but an alternative hypothesis supports the Zygnematales (often referred to as "pond scum" as the sister lineage. In this paper, we provide a well-supported, 160-nuclear-gene phylogenomic analysis supporting the Zygnematales as the closest living relative to land plants. Our study makes two key contributions to the field: 1 the use of an unbiased method to collect a large set of orthologs from deeply diverging species and 2 the use of these data in determining the sister lineage to land plants. We anticipate this updated phylogeny not only will hugely impact lesson plans in introductory biology courses, but also will provide a solid phylogenetic tree for future green-lineage research, whether it be related to plants or green algae.

Big data bioinformatics.

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Greene, Casey S; Tan, Jie; Ung, Matthew; Moore, Jason H; Cheng, Chao

2014-12-01

Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. © 2014 Wiley Periodicals, Inc.

Psychopathology, childhood trauma, and personality traits in patients with borderline personality disorder and their sisters.

Science.gov (United States)

Laporte, Lise; Paris, Joel; Guttman, Herta; Russell, Jennifer

2011-08-01

The aim of this study was to document and compare adverse childhood experiences, and personality profiles in women with borderline personality disorder (BPD) and their sisters, and to determine how these factors impact current psychopathology. Fifty-six patients with BPD and their sisters were compared on measures assessing psychopathology, personality traits, and childhood adversities. Most sisters showed little evidence of psychopathology. Both groups reported dysfunctional parent-child relationships and a high prevalence of childhood trauma. Subjects with BPD reported experiencing more emotional abuse and intrafamilial sexual abuse, but more similarities than differences between probands and sisters were found. In multilevel analyses, personality traits of affective instability and impulsivity predicted DIB-R scores and SCL-90-R scores, above and beyond trauma. There were few relationships between childhood adversities and other measures of psychopathology. Sensitivity to adverse experiences, as reflected in the development of psychopathology, appears to be influenced by personality trait profiles.

Recht voor big data, big data voor recht

NARCIS (Netherlands)

Lafarre, Anne

Big data is een niet meer weg te denken fenomeen in onze maatschappij. Het is de hype cycle voorbij en de eerste implementaties van big data-technieken worden uitgevoerd. Maar wat is nu precies big data? Wat houden de vijf V's in die vaak genoemd worden in relatie tot big data? Ter inleiding van

El naturalismo americano: Theodore Dreiser y Sister Carrie

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Dolores G. ALONSO MULAS

2009-08-01

Full Text Available Para situar a un escritor, como Theodore Dreiser, y especialmente su novela Sister Carrie dentro de un movimiento literario y de una etapa determinada de la historia americana, es necesario dar un breve repaso al naturalismo, llegado a América a través de Stephen Crane

Acceptability of Big Books as Mother Tongue-based Reading Materials in Bulusan Dialect

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Magdalena M. Ocbian

2015-11-01

Full Text Available Several studies have proven the superiority of using mother tongue in improving the pupils‟ performance. Research results revealed that using a language familiar to the pupils facilitates reading, writing and learning new concepts. However, at present, teachers are confronted with the insufficiency of instructional materials written in the local dialect and accepted by the end-users as possessing the qualities that could produce the desired learning outcomes. This descriptive evaluative research was conducted to address this problem. It determined the level of acceptability of the six researcher-made big books as mother tongue-based reading materials in Bulusan dialect for Grade 1 pupils. The big books were utilized by 11 Grade 1 teachers of Bulusan District to their pupils and were evaluated along suitability and appropriateness of the materials, visual appeal and quality of the story using checklist and open-ended questionnaire. Same materials were assessed by eight expert jurors. Findings showed that the big books possessed the desired qualities that made them very much acceptable to the Grade 1 teachers and much acceptable to the expert jurors. The comments and suggestions of the respondents served as inputs in the enhancement and revision of the six big books.

Rule based systems for big data a machine learning approach

CERN Document Server

Liu, Han; Cocea, Mihaela

2016-01-01

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

The Predictive Effect of Big Five Factor Model on Social Reactivity ...

African Journals Online (AJOL)

The study tested a model of providing a predictive explanation of Big Five Factor on social reactivity among secondary school adolescents of Cross River State, Nigeria. A sample of 200 students randomly selected across 12 public secondary schools in the State participated in the study (120 male and 80 female). Data ...

"If I only touch her cloak": the Sisters of Charity of St. Joseph in New Orleans hospital, 1834-1860.

Science.gov (United States)

Kong, Hyejung Grace; Kim, Ock-Joo

2015-04-01

This study is about the Sisters of Charity of St. Joseph in New Orleans' Charity Hospital during the years between 1834 and 1860. The Sisters of Charity of St. Joseph was founded in 1809 by Saint Elizabeth Ann Bailey Seton (first native-born North American canonized in 1975) in Emmitsburg, Maryland. Seton's Sisters of Charity was the first community for religious women to be established in the United States and was later incorporated with the French Daughters of Charity of St. Vincent de Paul in 1850. A call to work in New Orleans' Charity Hospital in the 1830s meant a significant achievement for the Sisters of Charity, since it was the second oldest continuously operating public hospitals in the United States until 2005, bearing the same name over the decades. In 1834, Sister Regina Smith and other sisters were officially called to Charity Hospital, in order to supersede the existing "nurses, attendants, and servants," and take a complete charge of the internal management of Charity Hospital. The existing scholarship on the history of hospitals and Catholic nursing has not integrated the concrete stories of the Sisters of Charity into the broader histories of institutionalized medicine, gender, and religion. Along with a variety of primary sources, this study primarily relies on the Charity Hospital History Folder stored at the Daughters of Charity West Center Province Archives. Located in the "Queen city of the South," Charity Hospital was the center of the southern medical profession and the world's fair of people and diseases. Charity Hospital provided the sisters with a unique situation that religion and medicine became intertwined. The Sisters, as nurses, constructed a new atmosphere of caring for patients and even their families inside and outside the hospital, and built their own separate space within the hospital walls. As hospital managers, the Sisters of Charity were put in complete charge of the hospital, which was never seen in other hospitals. By

The BigBOSS Experiment

Energy Technology Data Exchange (ETDEWEB)

Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna

2011-01-01

BigBOSS will obtain observational constraints that will bear on three of the four 'science frontier' questions identified by the Astro2010 Cosmology and Fundamental Phyics Panel of the Decadal Survey: Why is the universe accelerating; what is dark matter and what are the properties of neutrinos? Indeed, the BigBOSS project was recommended for substantial immediate R and D support the PASAG report. The second highest ground-based priority from the Astro2010 Decadal Survey was the creation of a funding line within the NSF to support a 'Mid-Scale Innovations' program, and it used BigBOSS as a 'compelling' example for support. This choice was the result of the Decadal Survey's Program Priorization panels reviewing 29 mid-scale projects and recommending BigBOSS 'very highly'.

The Berlin Inventory of Gambling behavior - Screening (BIG-S): Validation using a clinical sample.

Science.gov (United States)

Wejbera, Martin; Müller, Kai W; Becker, Jan; Beutel, Manfred E

2017-05-18

Published diagnostic questionnaires for gambling disorder in German are either based on DSM-III criteria or focus on aspects other than life time prevalence. This study was designed to assess the usability of the DSM-IV criteria based Berlin Inventory of Gambling Behavior Screening tool in a clinical sample and adapt it to DSM-5 criteria. In a sample of 432 patients presenting for behavioral addiction assessment at the University Medical Center Mainz, we checked the screening tool's results against clinical diagnosis and compared a subsample of n=300 clinically diagnosed gambling disorder patients with a comparison group of n=132. The BIG-S produced a sensitivity of 99.7% and a specificity of 96.2%. The instrument's unidimensionality and the diagnostic improvements of DSM-5 criteria were verified by exploratory and confirmatory factor analysis as well as receiver operating characteristic analysis. The BIG-S is a reliable and valid screening tool for gambling disorder and demonstrated its concise and comprehensible operationalization of current DSM-5 criteria in a clinical setting.

Big Data in Medicine is Driving Big Changes

Science.gov (United States)

Verspoor, K.

2014-01-01

Summary Objectives To summarise current research that takes advantage of “Big Data” in health and biomedical informatics applications. Methods Survey of trends in this work, and exploration of literature describing how large-scale structured and unstructured data sources are being used to support applications from clinical decision making and health policy, to drug design and pharmacovigilance, and further to systems biology and genetics. Results The survey highlights ongoing development of powerful new methods for turning that large-scale, and often complex, data into information that provides new insights into human health, in a range of different areas. Consideration of this body of work identifies several important paradigm shifts that are facilitated by Big Data resources and methods: in clinical and translational research, from hypothesis-driven research to data-driven research, and in medicine, from evidence-based practice to practice-based evidence. Conclusions The increasing scale and availability of large quantities of health data require strategies for data management, data linkage, and data integration beyond the limits of many existing information systems, and substantial effort is underway to meet those needs. As our ability to make sense of that data improves, the value of the data will continue to increase. Health systems, genetics and genomics, population and public health; all areas of biomedicine stand to benefit from Big Data and the associated technologies. PMID:25123716

Effect of borax on immune cell proliferation and sister chromatid exchange in human chromosomes

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Pongsavee Malinee

2009-10-01

Full Text Available Abstract Background Borax is used as a food additive. It becomes toxic when accumulated in the body. It causes vomiting, fatigue and renal failure. Methods The heparinized blood samples from 40 healthy men were studied for the impact of borax toxicity on immune cell proliferation (lymphocyte proliferation and sister chromatid exchange in human chromosomes. The MTT assay and Sister Chromatid Exchange (SCE technic were used in this experiment with the borax concentrations of 0.1, 0.15, 0.2, 0.3 and 0.6 mg/ml. Results It showed that the immune cell proliferation (lymphocyte proliferation was decreased when the concentrations of borax increased. The borax concentration of 0.6 mg/ml had the most effectiveness to the lymphocyte proliferation and had the highest cytotoxicity index (CI. The borax concentrations of 0.15, 0.2, 0.3 and 0.6 mg/ml significantly induced sister chromatid exchange in human chromosomes (P Conclusion Borax had effects on immune cell proliferation (lymphocyte proliferation and induced sister chromatid exchange in human chromosomes. Toxicity of borax may lead to cellular toxicity and genetic defect in human.

A Social Semiotic Analysis of the Discursive Construction of Teacher Identity in the "Book of Rules and Customs" of the Australian Sisters of the Most Sacred Heart of Jesus

Science.gov (United States)

O'Donoghue, Tom; Chapman, Anne

2011-01-01

Up until the 1960s, Catholic schools throughout most of the English-speaking world were dominated by members of religious teaching orders, including female religious. For over a century following their establishment in 1866, one of the most prominent female religious teaching orders in Australia was that of the Sisters of St Joseph of the Most…

Reframing Open Big Data

DEFF Research Database (Denmark)

Marton, Attila; Avital, Michel; Jensen, Tina Blegind

2013-01-01

Recent developments in the techniques and technologies of collecting, sharing and analysing data are challenging the field of information systems (IS) research let alone the boundaries of organizations and the established practices of decision-making. Coined ‘open data’ and ‘big data......’, these developments introduce an unprecedented level of societal and organizational engagement with the potential of computational data to generate new insights and information. Based on the commonalities shared by open data and big data, we develop a research framework that we refer to as open big data (OBD......) by employing the dimensions of ‘order’ and ‘relationality’. We argue that these dimensions offer a viable approach for IS research on open and big data because they address one of the core value propositions of IS; i.e. how to support organizing with computational data. We contrast these dimensions with two...

The BigBoss Experiment

Energy Technology Data Exchange (ETDEWEB)

Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; Bebek, C.; Becerril, S.; Blanton, M.; Bolton, A.; Bromley, B.; Cahn, R.; Carton, P.-H.; Cervanted-Cota, J.L.; Chu, Y.; Cortes, M.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna / /IAC, Mexico / / /Madrid, IFT /Marseille, Lab. Astrophys. / / /New York U. /Valencia U.

2012-06-07

BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = {lambda}/{Delta}{lambda} = 3000-4800. Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy redshifts are obtained to measure the BAO feature, trace the matter power spectrum at smaller scales, and detect redshift space distortions. BigBOSS will provide additional constraints on early dark energy and on the curvature of the universe by measuring the Ly-alpha forest in the spectra of over 600,000 2.2 < z < 3.5 quasars. BigBOSS galaxy BAO measurements combined with an analysis of the broadband power, including the Ly-alpha forest in BigBOSS quasar spectra, achieves a FOM of 395 with Planck plus Stage III priors. This FOM is based on conservative assumptions for the analysis of broad band power (k{sub max} = 0.15), and could grow to over 600 if current work allows us to push the analysis to higher wave numbers (k{sub max} = 0.3). BigBOSS will also place constraints on theories of modified gravity and inflation, and will measure the sum of neutrino masses to 0.024 eV accuracy.

An Efficient Big Data Anonymization Algorithm Based on Chaos and Perturbation Techniques

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Can Eyupoglu

2018-05-01

Full Text Available The topic of big data has attracted increasing interest in recent years. The emergence of big data leads to new difficulties in terms of protection models used for data privacy, which is of necessity for sharing and processing data. Protecting individuals’ sensitive information while maintaining the usability of the data set published is the most important challenge in privacy preserving. In this regard, data anonymization methods are utilized in order to protect data against identity disclosure and linking attacks. In this study, a novel data anonymization algorithm based on chaos and perturbation has been proposed for privacy and utility preserving in big data. The performance of the proposed algorithm is evaluated in terms of Kullback–Leibler divergence, probabilistic anonymity, classification accuracy, F-measure and execution time. The experimental results have shown that the proposed algorithm is efficient and performs better in terms of Kullback–Leibler divergence, classification accuracy and F-measure compared to most of the existing algorithms using the same data set. Resulting from applying chaos to perturb data, such successful algorithm is promising to be used in privacy preserving data mining and data publishing.

Sisters in hereditary breast and ovarian cancer families: communal coping, social integration, and psychological well-being.

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Koehly, Laura M; Peters, June A; Kuhn, Natalia; Hoskins, Lindsey; Letocha, Anne; Kenen, Regina; Loud, Jennifer; Greene, Mark H

2008-08-01

We investigated the association between psychological distress and indices of social integration and communal coping among sisters from hereditary breast and ovarian cancer (HBOC) families. Sixty-five sisters from 31 HBOC families completed the Brief Symptom Inventory-18 and the Colored Eco-Genetic Relationship Map, which identified members of participants' social support networks. Hierarchical linear models were used for all analyses to account for the clustering of sisters within families. Intra-family correlation coefficients suggested that sisters shared perceptions of breast cancer risk and worry, but not ovarian cancer risk and worry. Further, sisters demonstrated shared levels of anxiety and somatization, but not depressive symptoms. Communal coping indices quantifying shared support resources were negatively related to anxiety and somatization. The number of persons with whom cancer risk information was shared exhibited a positive trend with somatization. Social integration, as measured by the size of participants' emotional support network, was negatively associated with anxiety. Lower depression scores were observed among participants with more persons playing multiple support roles and fewer persons providing tangible assistance. Understanding how support relationships impact well-being among persons adjusting to HBOC risk, and the particular role of family in that process, will facilitate developing appropriate management approaches to help cancer-prone families adjust to their cancer risk.

Associations Between the Big Five Personality Traits and a Medical School Admission Interview.

Science.gov (United States)

Lourinho, Isabel; Moreira, André; Mota-Cardoso, Rui; Severo, Milton; Ferreira, Maria Amélia

2016-12-30

Personality has became popular in medical student's selection. However, few research exists about the association between the big five personality traits and the existent medical school selection tools. Our aim was to study which personality traits were selected by a medical school admission interview. One hundred ninety four graduate applicants that had applied to the Faculty of Medicine of the University of Porto through the graduate entry approach, after ranked on previous achievement, were interviewed between the academic years of 2011 and 2013. From these, 181 (93.3%) answered to the NEO Five-Factor Inventory that assesses high order personality traits of openness to experience, conscientiousness, extraversion, agreeableness and neuroticism. Admission interview corresponded to the second phase of the seriation process. Every applicant was interviewed and scored by three interviewers on seven dimensions asesssed by Lickert scale (1-10). Interview score was the sum of the dimensions. Linear mixed effects model and respective regression coefficients were used to estimate the association between personality traits from each interviewer's score. Final models were adjusted for gender, interviewers and previous achievement. Openness to experience (Beta = 0.18: CI 95%: 0.05; 0.30) had the strongest association with interview score followed by the interaction effect between the extraversion and conscientiousness traits (Beta = 0.14; CI 95%: 0.02; 0.25). Also, applicants scored higher when their gender was opposite to the interviewers. Previous achievement and interview score had no association. Our admission interview selected different personality traits when compared to other selection tools. Medical schools should be aware of the implications of the adopted selection tools on the admitted medical student's personality because it can help providing beneficial interventions.

Creation a Geo Big Data Outreach and Training Collaboratory for Wildfire Community

Science.gov (United States)

Altintas, I.; Sale, J.; Block, J.; Cowart, C.; Crawl, D.

2015-12-01

A major challenge for the geoscience community is the training and education of current and next generation big data geoscientists. In wildfire research, there are an increasing number of tools, middleware and techniques to use for data science related to wildfires. The necessary computing infrastructures are often within reach and most of the software tools for big data are freely available. But what has been lacking is a transparent platform and training program to produce data science experts who can use these integrated tools effectively. Scientists well versed to take advantage of big data technologies in geoscience applications is of critical importance to the future of research and knowledge advancement. To address this critical need, we are developing learning modules to teach process-based thinking to capture the value of end-to-end systems of reusable blocks of knowledge and integrate the tools and technologies used in big data analysis in an intuitive manner. WIFIRE is an end-to-end cyberinfrastructure for dynamic data-driven simulation, prediction and visualization of wildfire behavior.To this end, we are openly extending an environment we have built for "big data training" (biobigdata.ucsd.edu) to similar MOOC-based approaches to the wildfire community. We are building an environment that includes training modules for distributed platforms and systems, Big Data concepts, and scalable workflow tools, along with other basics of data science including data management, reproducibility and sharing of results. We also plan to provide teaching modules with analytical and dynamic data-driven wildfire behavior modeling case studies which address the needs not only of standards-based K-12 science education but also the needs of a well-educated and informed citizenry.Another part our outreach mission is to educate our community on all aspects of wildfire research. One of the most successful ways of accomplishing this is through high school and undergraduate

BigBOSS: The Ground-Based Stage IV BAO Experiment

Energy Technology Data Exchange (ETDEWEB)

Schlegel, David; Bebek, Chris; Heetderks, Henry; Ho, Shirley; Lampton, Michael; Levi, Michael; Mostek, Nick; Padmanabhan, Nikhil; Perlmutter, Saul; Roe, Natalie; Sholl, Michael; Smoot, George; White, Martin; Dey, Arjun; Abraham, Tony; Jannuzi, Buell; Joyce, Dick; Liang, Ming; Merrill, Mike; Olsen, Knut; Salim, Samir

2009-04-01

The BigBOSS experiment is a proposed DOE-NSF Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with an all-sky galaxy redshift survey. The project is designed to unlock the mystery of dark energy using existing ground-based facilities operated by NOAO. A new 4000-fiber R=5000 spectrograph covering a 3-degree diameter field will measure BAO and redshift space distortions in the distribution of galaxies and hydrogen gas spanning redshifts from 0.2< z< 3.5. The Dark Energy Task Force figure of merit (DETF FoM) for this experiment is expected to be equal to that of a JDEM mission for BAO with the lower risk and cost typical of a ground-based experiment.

Where Big-City Schools Meet "Microsoft Smarts"

Science.gov (United States)

Borja, Rhea R.

2006-01-01

This article talks about a new school built, which is called "School of the Future," which was born of a partnership between the Philadelphia public schools and the world's leading software-maker, Microsoft Corp. A gleaming white building on the edge of a blighted West Philadelphia neighborhood, the $62 million school garnered wide attention when…

Heritability estimates of the Big Five personality traits based on common genetic variants.

Science.gov (United States)

Power, R A; Pluess, M

2015-07-14

According to twin studies, the Big Five personality traits have substantial heritable components explaining 40-60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527,469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e. = 0.08, P = 0.04) and openness (21%, s.e. = 0.08, P Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.

Relations of the Big-Five personality dimensions to autodestructive behavior in clinical and non-clinical adolescent populations

Science.gov (United States)

Kotrla Topić, Marina; Perković Kovačević, Marina; Mlačić, Boris

2012-01-01

Aim To examine the relationship between the Big-Five personality model and autodestructive behavior symptoms, namely Autodestructiveness and Suicidal Depression in two groups of participants: clinical and non-clinical adolescents. Methods Two groups of participants, clinical (adolescents with diagnosis of psychiatric disorder based on clinical impression and according to valid diagnostic criteria, N = 92) and non-clinical (high-school students, N = 87), completed two sets of questionnaires: the Autodestructiveness Scale which provided data on Autodestructiveness and Suicidal Depression, and the International Personality Item Pool (IPIP), which provided data on the Big -Five personality dimensions. Results Clinical group showed significantly higher values on the Autodestructiveness scale in general, as well as on Suicidal Depression, Aggressiveness, and Borderline subscales than the non-clinical group. Some of the dimensions of the Big-Five personality model, ie, Emotional Stability, Conscientiousness, and Agreeableness showed significant relationship (hierarchical regression analyses, P values for β coefficients from Big-Five model are important when evaluating adolescent psychiatric patients and adolescents from general population at risk of self-destructive behavior. PMID:23100207

Study of alexithymia trait based on Big-Five Personality Dimensions

Directory of Open Access Journals (Sweden)

Rasoul Heshmati

2017-12-01

Full Text Available The purpose of this research was to study the relationship between Big Five personality traits and alexithymia and to determine differences of alexithymic compare with non- alexithymic individuals in these personality traits in university students. In present study, 150 university students at Tabriz University were selected and asked to answer NEO – Five Factor Inventory (NEO - FFI, and Toronto Alexithymia Scale (TAS - 20. Results showed that there are negative and significant relationships between conscientiousness and openness to experiences with alexithymia and positive and significant relationships between neuroticism with alexithymia. As well as, there is significant difference between alexithymic and non-alexithymic individuals in neuroticism and openness to experiences. In one hand, these results suggest that neuroticism, conscientiousness and openness to experiences are determinant of alexithymia; and in the other hand, high level of neuroticism and low level of openness to experiences are the characteristic of alexithymic people based on Big-five. Therefore, it can be conclude that high neuroticism and low openness to experiences are the alexithymic individual’s traits.

Childhood obsessive-compulsive traits in anorexia nervosa patients, their unaffected sisters and healthy controls: a retrospective study.

Science.gov (United States)

Degortes, Daniela; Zanetti, Tatiana; Tenconi, Elena; Santonastaso, Paolo; Favaro, Angela

2014-07-01

Although there is evidence that childhood perfectionistic traits predate the onset of eating disorders, few studies to date have examined the prevalence and clinical correlates of these traits in patients with anorexia nervosa (AN) and their unaffected sisters. The aim of this work was to study the prevalence of childhood obsessive-compulsive traits in patients with lifetime AN, their unaffected sisters and healthy women. A total of 116 AN patients, 32 healthy sisters and 119 controls were assessed by the EATATE Interview to assess traits such as perfectionism, inflexibility, rule-bound traits, drive for order and symmetry, and excessive doubt and cautiousness. Both self-report and maternal reports were collected. AN patients reported more childhood obsessive-compulsive traits than their healthy sisters and controls. In contrast, no differences between healthy controls and unaffected sisters emerged. In patients with AN, a dose-response relationship was found between the number of childhood obsessive-compulsive traits and psychopathology, including body image distortion, thus indicating that these traits are an important feature to be considered in assessing and treating eating disorders. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association.

BigOP: Generating Comprehensive Big Data Workloads as a Benchmarking Framework

OpenAIRE

Zhu, Yuqing; Zhan, Jianfeng; Weng, Chuliang; Nambiar, Raghunath; Zhang, Jinchao; Chen, Xingzhen; Wang, Lei

2014-01-01

Big Data is considered proprietary asset of companies, organizations, and even nations. Turning big data into real treasure requires the support of big data systems. A variety of commercial and open source products have been unleashed for big data storage and processing. While big data users are facing the choice of which system best suits their needs, big data system developers are facing the question of how to evaluate their systems with regard to general big data processing needs. System b...

Water-quality effects on phytoplankton species and density and trophic state indices at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas, June through August, 2015

Science.gov (United States)

Driver, Lucas; Justus, Billy

2016-01-01

Big Base and Little Base Lakes are located on Little Rock Air Force Base, Arkansas, and their close proximity to a dense residential population and an active military/aircraft installation make the lakes vulnerable to water-quality degradation. The U.S. Geological Survey (USGS) conducted a study from June through August 2015 to investigate the effects of water quality on phytoplankton species and density and trophic state in Big Base and Little Base Lakes, with particular regard to nutrient concentrations. Nutrient concentrations, trophic-state indices, and the large part of the phytoplankton biovolume composed of cyanobacteria, indicate eutrophic conditions were prevalent for Big Base and Little Base Lakes, particularly in August 2015. Cyanobacteria densities and biovolumes measured in this study likely pose a low to moderate risk of adverse algal toxicity, and the high proportion of filamentous cyanobacteria in the lakes, in relation to other algal groups, is important from a fisheries standpoint because these algae are a poor food source for many aquatic taxa. In both lakes, total nitrogen to total phosphorus (N:P) ratios declined over the sampling period as total phosphorus concentrations increased relative to nitrogen concentrations. The N:P ratios in the August samples (20:1 and 15:1 in Big Base and Little Base Lakes, respectively) and other indications of eutrophic conditions are of concern and suggest that exposure of the two lakes to additional nutrients could cause unfavorable dissolved-oxygen conditions and increase the risk of cyanobacteria blooms and associated cyanotoxin issues.

Automated Predictive Big Data Analytics Using Ontology Based Semantics.

Science.gov (United States)

Nural, Mustafa V; Cotterell, Michael E; Peng, Hao; Xie, Rui; Ma, Ping; Miller, John A

2015-10-01

Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and considerable expertise which might not always be readily available. In this paper, we propose to use semantic technology to assist data analysts and data scientists in selecting appropriate modeling techniques and building specific models as well as the rationale for the techniques and models selected. To formally describe the modeling techniques, models and results, we developed the Analytics Ontology that supports inferencing for semi-automated model selection. The SCALATION framework, which currently supports over thirty modeling techniques for predictive big data analytics is used as a testbed for evaluating the use of semantic technology.

Sister chromatid exchange in peripheral blood lymphocytes as a ...

African Journals Online (AJOL)

Introduction: Sister chromatid exchanges (SCEs) can be induced by various genotoxic treatments, suggesting that SCEs refl ect a DNA repair process and it may be a good index for assessment of genomic instability. However, the occurrence of genetic instability and in particular, of spontaneous SCEs has been strongly ...

Mechanisms of sister chromatid recombination

International Nuclear Information System (INIS)

Nakai, Sayaka; Machida, Isamu; Tsuji, Satsuki

1985-01-01

Studies using T948 as a model system have been carried out aimed at elucidating the mechanism of sister chromatid recombination (SCR). Characterization of U.V. light- and x-ray-induced SCR, the relationiship between SCR induction and DNA repair using rad mutations, and the relationship between SCR induction and the time of cell division using cdc mutations are presented. It has been supposed that SCR is induced at the phase of S-G 2 following DNA replication, that postreplication break of DNA strands is strongly involved in the induction of SCR, and that induction type of SCR, i.e., conversion type or recombination type, is dependent upon the type of molecular damage of DNA. (Namekawa, K.)

Astronomy in the Big Data Era

Directory of Open Access Journals (Sweden)

Yanxia Zhang

2015-05-01

Full Text Available The fields of Astrostatistics and Astroinformatics are vital for dealing with the big data issues now faced by astronomy. Like other disciplines in the big data era, astronomy has many V characteristics. In this paper, we list the different data mining algorithms used in astronomy, along with data mining software and tools related to astronomical applications. We present SDSS, a project often referred to by other astronomical projects, as the most successful sky survey in the history of astronomy and describe the factors influencing its success. We also discuss the success of Astrostatistics and Astroinformatics organizations and the conferences and summer schools on these issues that are held annually. All the above indicates that astronomers and scientists from other areas are ready to face the challenges and opportunities provided by massive data volume.

Big Data: Philosophy, Emergence, Crowdledge, and Science Education

Science.gov (United States)

dos Santos, Renato P.

2015-01-01

Big Data already passed out of hype, is now a field that deserves serious academic investigation, and natural scientists should also become familiar with Analytics. On the other hand, there is little empirical evidence that any science taught in school is helping people to lead happier, more prosperous, or more politically well-informed lives. In…

An illness in the family: Dr. Maude Abbott and her sister, Alice Abbott.

Science.gov (United States)

Brookes, Barbara

2011-01-01

This paper explores Maude Abbott's internationally significant career in medicine and her parallel commitment to caring for her sister, Alice Abbott. An examination of Abbott's life reveals the difficulties faced by an ambitious Canadian woman in medicine from the 1890s to the 1920s; difficulties compounded by caring for a sister with a mental illness. The Abbott archive suggests that it was far more difficult for a woman doctor to make the kind of sharp distinction between public and private life that might be expected of professional men.

All Heck Breaks Loose at Little Sisters of the Bayou High School

Science.gov (United States)

Fossey, Richard; Trujillo-Jenks, Laura; Eckes, Suzanne

2013-01-01

Public schools are full of incidents that fill newspapers, but when a private school is struck with instances of libel, child abuse, and violations of Title IX, the community is at a loss as to what to do.

Sister chromosome pairing maintains heterozygosity in parthenogenetic lizards.

Science.gov (United States)

Lutes, Aracely A; Neaves, William B; Baumann, Diana P; Wiegraebe, Winfried; Baumann, Peter

2010-03-11

Although bisexual reproduction has proven to be highly successful, parthenogenetic all-female populations occur frequently in certain taxa, including the whiptail lizards of the genus Aspidoscelis. Allozyme analysis revealed a high degree of fixed heterozygosity in these parthenogenetic species, supporting the view that they originated from hybridization events between related sexual species. It has remained unclear how the meiotic program is altered to produce diploid eggs while maintaining heterozygosity. Here we show that meiosis commences with twice the number of chromosomes in parthenogenetic versus sexual species, a mechanism that provides the basis for generating gametes with unreduced chromosome content without fundamental deviation from the classic meiotic program. Our observation of synaptonemal complexes and chiasmata demonstrate that a typical meiotic program occurs and that heterozygosity is not maintained by bypassing recombination. Instead, fluorescent in situ hybridization probes that distinguish between homologues reveal that bivalents form between sister chromosomes, the genetically identical products of the first of two premeiotic replication cycles. Sister chromosome pairing provides a mechanism for the maintenance of heterozygosity, which is critical for offsetting the reduced fitness associated with the lack of genetic diversity in parthenogenetic species.

Umbilical metastasis (Sister Mary Joseph's nodule diagnosed by fine-needle aspiration

Directory of Open Access Journals (Sweden)

Tatomirović Željka

2004-01-01

Full Text Available Sister Mary Joseph’s nodule is the eponym for metastatic involvement of the umbilicus. This less common entity is the sign of disseminated malignant disease, mainly of digestive and gynecologic origin, and is associated with a poor prognosis. A case of Sister Mary Joseph’s nodule in a 76-year-old woman in whom the umbilical metastasis was the first sign of malignant disease in presented. The diagnosis of metastatic adenocarcinoma was established by fine needle aspiration cytology of the umbilical nodule. Radiological and ultrasonographic investigation disclosed carcinoma of the gallbladder with pancreas, stomach, and colon invasion as well as peritoneal dissemination. The diagnosis was confirmed by exploratory laparatomy and histological examination of the excised umbilical nodule.

Relações hierárquicas entre os traços amplos do Big Five Hierarchical relationship between the broad traits of the Big Five

Directory of Open Access Journals (Sweden)

Cristiano Mauro Assis Gomes

2012-01-01

Full Text Available O modelo Big Five sustenta que a personalidade humana é composta por dezenas de fatores específicos. Apesar dessa diversidade, esses fatores confluem para cinco traços amplos que estão em um mesmo nível de hierarquia. O presente estudo apresenta uma hipótese alternativa, postulando níveis entre os traços amplos do modelo. Fizeram parte do estudo 684 estudantes do ensino fundamental e médio de uma escola particular de Belo Horizonte, MG, com idades entre 10 e 18 anos (m = 13,71 e DP= 2,11. Para medir os fatores do Big Five foi utilizado o Inventário de Características de Personalidade, anteriormente chamado de Inventário dos Adjetivos de Personalidade, de Pinheiro, Gomes e Braga (2009. O instrumento mensura oito polaridades das 10 polaridades presentes nos cinco traços amplos do Big Five. Dois modelos foram comparados via método path analysis: um modelo de quatro níveis hierárquicos e um modelo não hierárquico. O modelo hierárquico apresentou adequado grau de ajuste aos dados e mostrou-se superior ao modelo não hierárquico, que não se ajusta aos dados. Implicações são discutidas para o modelo Big Five.The Big Five model sustains that human personality is composed by dozens of specific factors. Despite of diversity, specific factors are integrated in five broad traits that are in the same hierarchical level. The current study presents an alternative hypothesis arguing that there are hierarchical levels between the broad traits of the model. Six hundred and eighty-four junior and high school level students from 10 to 18 years old (M = 13.71 and SD= 2.11 of a private school in the city of Belo Horizonte, Minas Gerais, Brazil participated in the study. The Big Five was measured by an Inventory of Personality Traits, initially named as Personality Adjective Inventory, elaborated by Pinheiro, Gomes and Braga (2009. This instrument measures eight polarities of the ten presented in the Big Five Model. Two models were compared

The Lehman Sisters Hypothesis: an exploration of literature and bankers

NARCIS (Netherlands)

I.P. van Staveren (Irene)

2012-01-01

textabstractAbstract This article tests the Lehman Sisters Hypothesis in two complementary, although incomplete ways. It reviews the diverse empirical literature in behavioral, experimental, and neuroeconomics as well as related fields of behavioral research. And it presents the findings from an

The Lehman Sisters Hypothesis: an exploration of literature and bankers

NARCIS (Netherlands)

I.P. van Staveren (Irene)

2012-01-01

textabstractThis article tests the Lehman Sisters Hypothesis in two complementary, although incomplete ways. It reviews the diverse empirical literature in behavioural, experimental, and neuroeconomics as well as related fields of behavioural research. And it presents the findings from an

Opportunity and Challenges for Migrating Big Data Analytics in Cloud

Science.gov (United States)

Amitkumar Manekar, S.; Pradeepini, G., Dr.

2017-08-01

Big Data Analytics is a big word now days. As per demanding and more scalable process data generation capabilities, data acquisition and storage become a crucial issue. Cloud storage is a majorly usable platform; the technology will become crucial to executives handling data powered by analytics. Now a day’s trend towards “big data-as-a-service” is talked everywhere. On one hand, cloud-based big data analytics exactly tackle in progress issues of scale, speed, and cost. But researchers working to solve security and other real-time problem of big data migration on cloud based platform. This article specially focused on finding possible ways to migrate big data to cloud. Technology which support coherent data migration and possibility of doing big data analytics on cloud platform is demanding in natute for new era of growth. This article also gives information about available technology and techniques for migration of big data in cloud.

Nursing Needs Big Data and Big Data Needs Nursing.

Science.gov (United States)

Brennan, Patricia Flatley; Bakken, Suzanne

2015-09-01

Contemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care. Big data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data. The primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives. Existing approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist. Big data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient. © 2015 Sigma Theta Tau International.

BIG Data - BIG Gains? Understanding the Link Between Big Data Analytics and Innovation

OpenAIRE

Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

2017-01-01

This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance for product innovations. Since big data technologies provide new data information practices, they create new decision-making possibilities, which firms can use to realize innovations. Applying German firm-level data we find suggestive evidence that big data analytics matters for the likelihood of becoming a product innovator as well as the market success of the firms’ product innovat...

Networking for big data

CERN Document Server

Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

2015-01-01

Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

Global fluctuation spectra in big-crunch-big-bang string vacua

International Nuclear Information System (INIS)

Craps, Ben; Ovrut, Burt A.

2004-01-01

We study big-crunch-big-bang cosmologies that correspond to exact world-sheet superconformal field theories of type II strings. The string theory spacetime contains a big crunch and a big bang cosmology, as well as additional 'whisker' asymptotic and intermediate regions. Within the context of free string theory, we compute, unambiguously, the scalar fluctuation spectrum in all regions of spacetime. Generically, the big crunch fluctuation spectrum is altered while passing through the bounce singularity. The change in the spectrum is characterized by a function Δ, which is momentum and time dependent. We compute Δ explicitly and demonstrate that it arises from the whisker regions. The whiskers are also shown to lead to 'entanglement' entropy in the big bang region. Finally, in the Milne orbifold limit of our superconformal vacua, we show that Δ→1 and, hence, the fluctuation spectrum is unaltered by the big-crunch-big-bang singularity. We comment on, but do not attempt to resolve, subtleties related to gravitational back reaction and light winding modes when interactions are taken into account

Sister chromatoid exchanges in atomic bomb survivors

International Nuclear Information System (INIS)

Nakano, Mimako; Awa, Akio

1980-01-01

Sister chromatoid exchange (SCE) frequencies in the peripheral lymphocyte with and without mitomycin-C (MMC) were studied, in the age of tens and thirties for an atomic-bomb survivor group and in thirties, fifties, and seventies for an unexposed group. The observation of 100 cells showed no statistically significant difference of SCE frequencies with aging or irradiation. The increasing rates of SCE frequencies by MMC showed no difference among the groups. The average increasing ratio by MMC was 3.6. (Nakanishi, T.)

What is beyond the big five?

Science.gov (United States)

Saucier, G; Goldberg, L R

1998-08-01

Previous investigators have proposed that various kinds of person-descriptive content--such as differences in attitudes or values, in sheer evaluation, in attractiveness, or in height and girth--are not adequately captured by the Big Five Model. We report on a rather exhaustive search for reliable sources of Big Five-independent variation in data from person-descriptive adjectives. Fifty-three candidate clusters were developed in a college sample using diverse approaches and sources. In a nonstudent adult sample, clusters were evaluated with respect to a minimax criterion: minimum multiple correlation with factors from Big Five markers and maximum reliability. The most clearly Big Five-independent clusters referred to Height, Girth, Religiousness, Employment Status, Youthfulness and Negative Valence (or low-base-rate attributes). Clusters referring to Fashionableness, Sensuality/Seductiveness, Beauty, Masculinity, Frugality, Humor, Wealth, Prejudice, Folksiness, Cunning, and Luck appeared to be potentially beyond the Big Five, although each of these clusters demonstrated Big Five multiple correlations of .30 to .45, and at least one correlation of .20 and over with a Big Five factor. Of all these content areas, Religiousness, Negative Valence, and the various aspects of Attractiveness were found to be represented by a substantial number of distinct, common adjectives. Results suggest directions for supplementing the Big Five when one wishes to extend variable selection outside the domain of personality traits as conventionally defined.

Effect of borax on immune cell proliferation and sister chromatid exchange in human chromosomes

OpenAIRE

Pongsavee Malinee

2009-01-01

Abstract Background Borax is used as a food additive. It becomes toxic when accumulated in the body. It causes vomiting, fatigue and renal failure. Methods The heparinized blood samples from 40 healthy men were studied for the impact of borax toxicity on immune cell proliferation (lymphocyte proliferation) and sister chromatid exchange in human chromosomes. The MTT assay and Sister Chromatid Exchange (SCE) technic were used in this experiment with the borax concentrations of 0.1, 0.15, 0.2, 0...

Una aproximación a Big Data = An approach to Big Data

OpenAIRE

Puyol Moreno, Javier

2014-01-01

Big Data puede ser considerada como una tendencia en el avance de la tecnología que ha abierto la puerta a un nuevo enfoque para la comprensión y la toma de decisiones, que se utiliza para describir las enormes cantidades de datos (estructurados, no estructurados y semi- estructurados) que sería demasiado largo y costoso para cargar una base de datos relacional para su análisis. Así, el concepto de Big Data se aplica a toda la información que no puede ser procesada o analizada utilizando herr...

Big Argumentation?

Directory of Open Access Journals (Sweden)

Daniel Faltesek

2013-08-01

Full Text Available Big Data is nothing new. Public concern regarding the mass diffusion of data has appeared repeatedly with computing innovations, in the formation before Big Data it was most recently referred to as the information explosion. In this essay, I argue that the appeal of Big Data is not a function of computational power, but of a synergistic relationship between aesthetic order and a politics evacuated of a meaningful public deliberation. Understanding, and challenging, Big Data requires an attention to the aesthetics of data visualization and the ways in which those aesthetics would seem to depoliticize information. The conclusion proposes an alternative argumentative aesthetic as the appropriate response to the depoliticization posed by the popular imaginary of Big Data.

Enriching semantic knowledge bases for opinion mining in big data applications

OpenAIRE

Weichselbraun, A.; Gindl, S.; Scharl, A.

2014-01-01

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a doma...

Meiotic sister chromatid cohesion and recombination in two filamentous fungi

NARCIS (Netherlands)

Heemst, van D.

2000-01-01

Homologous recombination and sister chromatid cohesion play important roles in the maintenance of genome integrity and the fidelity of chromosome segregation in mitosis and meiosis. Within the living cell, the integrity of the DNA is threatened by various factors that cause DNA-lesions, of

The development of SisterTalk: a cable TV-delivered weight control program for black women.

Science.gov (United States)

Gans, Kim M; Kumanyika, Shiriki K; Lovell, H Joan; Risica, Patricia M; Goldman, Roberta; Odoms-Young, Angela; Strolla, Leslie O; Decaille, Donna O; Caron, Colleen; Lasater, Thomas M

2003-12-01

Overweight and obesity have reached epidemic proportions in the United States, with black women disproportionately affected. SisterTalk is a weight control program designed specifically for delivery to black women via cable TV. The theoretical and conceptual frameworks and formative research that guided the development and cultural tailoring of SisterTalk are described. Social Action Theory was applied in the development of SisterTalk along with a detailed behavioral analysis of the way that black women view weight and weight loss within the context of their cultural and social realities. The entire intervention development process was framed using this information, rather than by changing only superficial aspects of program delivery. Community networking and both qualitative and quantitative interview techniques from the fields of social marketing and cultural anthropology were used to involve black women from Boston in the design and implementation of a program that would be practical, appealing, and culturally sensitive. Also discussed are strategies for evaluating the program, and lessons learned that might have broader applicability are highlighted. The development of the SisterTalk program could provide a useful starting point for development of successful weight control programs for black women in other parts of the United States as well as for other ethnic and racial groups.

Research on taxi software policy based on big data

Directory of Open Access Journals (Sweden)

Feng Daoming

2017-01-01

Full Text Available Through big data analysis, statistical analysis of a large number of factors affect the establishment of the rally car index set, By establishing a mathematical model to analyze the different space-time taxi resource “to match supply and demand” degree, combined with intelligent deployment to solve the “taxi difficult” this hot social issues. This article takes Shanghai as an example, the central park, Lu Xun park, century park three areas as the object of study. From the “sky drops fast travel intelligence platform” big data, Extracted passenger demand and the number of taxi Kongshi data. Then demand and supply of taxis to establish indicators matrix, get the degree of matching supply needs of the region. Then through the big data relevant policies of each taxi company. Using the method of cluster analysis, to find the decisive role of the three aspects of the factors, using principal component analysis, compare the advantages and disadvantages of the existing company’s programs. Finally, according to the above research to develop a reasonable taxi software related policies.

Remotely Operated Vehicles (ROVs) Provide a "Big Data Progression"

Science.gov (United States)

Oostra, D.; Sanghera, S. S.; Mangosing, D. C., Jr.; Lewis, P. M., Jr.; Chambers, L. H.

2015-12-01

This year, science and technology teams at the NASA Langley Science Directorate were challenged with creating an API-based web application using RockBlock Mobile sensors mounted on a zero pressure high-altitude balloon. The system tracks and collects meteorological data parameters and visualizes this data in near real time, using a MEAN development stack to create an HTML5 based tool that can send commands to the vehicle, parse incoming data, and perform other functions to store and serve data to other devices. NASA developers and science educators working on this project saw an opportunity to use this emerging technology to address a gap identified in science education between middle and high school curricula. As students learn about data analysis in elementary and middle school, they are taught to collect data from in situ sources. In high school, students are then asked to work with remotely sensed data, without always having the experience or understanding of how that data is collected. We believe that using ROVs to create a "big data progression" for students will not only enhance their ability to understand how remote satellite data is collected, but will also provide the outlet for younger students to expand their interest in science and data prior to entering high school. In this presentation, we will share and discuss our experiences with ROVs, APIs and data viz applications, with a focus on the next steps for developing this emerging capability.

A study of pricing and trading model of Blockchain & Big data-based Energy-Internet electricity

Science.gov (United States)

Fan, Tao; He, Qingsu; Nie, Erbao; Chen, Shaozhen

2018-01-01

The development of Energy-Internet is currently suffering from a series of issues, such as the conflicts among high capital requirement, low-cost, high efficiency, the spreading gap between capital demand and supply, as well as the lagged trading & valuation mechanism, any of which would hinder Energy-Internet's evolution. However, with the development of Blockchain and big-data technology, it is possible to work out solutions for these issues. Based on current situation of Energy-Internet and its requirements for future progress, this paper demonstrates the validity of employing blockchain technology to solve the problems encountered by Energy-Internet during its development. It proposes applying the blockchain and big-data technologies to pricing and trading energy products through Energy-Internet and to accomplish cyber-based energy or power's transformation from physic products to financial assets.

Happiness matters : exploring the linkages between personality, personal happiness, and work-related psychological health among priests and sisters in Italy

OpenAIRE

Francis, Leslie J.; Crea, Giuseppe

2017-01-01

This study responds to the challenge posed by Rossetti’s work to explore the antecedents and consequences of individual differences in happiness among priests and religious sisters. The Oxford Happiness Questionnaire was completed together with measures of personality and work-related psychological health by 95 priests and 61 religious sisters. Overall the data demonstrated high levels of personal happiness among priests and religious sisters, but also significant signs of vulnerability. Pers...

Do brothers and sisters of siblings with intelectual disability need the support of social work?

OpenAIRE

Cardová, Michaela

2007-01-01

This thesis explores the experience and support needs of siblings with a brother or sister with intellectual disability. Through review of what is a quite limited literature and from original qualitative research, involving interviews with siblings, the author examines their social reality, focusing especially on their relationships with their disabled brother or sister and with the wider society. Particular attention is given to identifying to what extent the siblings' lives are influenced b...

The challenges of big data.

Science.gov (United States)

Mardis, Elaine R

2016-05-01

The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that currently hamper efforts to harness the power of big data. This Editorial outlines several such challenges as a means of illustrating that the path to big data revelations is paved with perils that the scientific community must overcome to pursue this important quest. © 2016. Published by The Company of Biologists Ltd.

Regulating “big data education” in Europe: lessons learned from the US

Directory of Open Access Journals (Sweden)

Yoni Har Carmel

2016-03-01

Full Text Available European schools are increasingly relying on vendors to collect, process, analyse, and even make decisions based on a considerable amount of student data through big data tools and methods. Consequently, portions of school’s power are gradually shifting from traditional public schools to the hands of for-profit organisations. This article discusses the current and forthcoming European Union (EU data protection regime with respect to the protection of student rights from the potential risk of outsourcing student data utilisation in Kindergarten-12th grade (K-12 educational systems. The article identifies what lessons can be drawn from recent developments in the United States (US “student data affair”. These lessons can provide a new perspective for designing a balanced policy for regulating the shift in school’s power.

Mobilising Mother Cabrini's Educational Practice: The Transnational Context of the London School of the Missionary Sisters of the Sacred Heart of Jesus 1898-1911

Science.gov (United States)

Williams, Maria Patricia

2015-01-01

A schoolteacher from Lombardy, Saint Frances Xavier Cabrini (1850-1917), founded the Institute of Missionary Sisters of the Sacred Heart of Jesus (MSC) in 1880. It was one of the 185 female religious institutes established in Italy in the nineteenth century. In the newly unified Italy, Cabrini found opportunities to formulate progressive Catholic…

Big data

DEFF Research Database (Denmark)

Madsen, Anders Koed; Flyverbom, Mikkel; Hilbert, Martin

2016-01-01

is to outline a research agenda that can be used to raise a broader set of sociological and practice-oriented questions about the increasing datafication of international relations and politics. First, it proposes a way of conceptualizing big data that is broad enough to open fruitful investigations......The claim that big data can revolutionize strategy and governance in the context of international relations is increasingly hard to ignore. Scholars of international political sociology have mainly discussed this development through the themes of security and surveillance. The aim of this paper...... into the emerging use of big data in these contexts. This conceptualization includes the identification of three moments contained in any big data practice. Second, it suggests a research agenda built around a set of subthemes that each deserve dedicated scrutiny when studying the interplay between big data...

178th International School of Physics "Enrico Fermi" : From the Big Bang to the Nucleosynthesis

CERN Document Server

Nappi, E

2011-01-01

Physicists have devoted much effort to reproducing the conditions of the primordial universe in laboratory conditions in their quest to work out a comprehensive theory of the appearance and evolution of nuclear matter. Whether it be trying to recreate the predicted primordial state of high-energy density matter in which quarks and gluons are effectively deconfined - the so-called Quark Gluon Plasma (QGP) - or exploring the structure and reaction properties of very unstable nuclei in experiments using radioactive beams, they have striven to understand the events which characterized the Big Bang and the various nucleosynthesis mechanisms which occur in the stars. This book contains the proceedings of the 2010 Enrico Fermi summer school held in Varenna, Italy, in July 2010, and devoted to the present understanding of the primordial universe and the origin of the elements, as achieved by studying nuclei and their constituents in extreme regimes of energy and composition. Subjects covered include: QGP formation; e...

Big data computing

CERN Document Server

Akerkar, Rajendra

2013-01-01

Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book i

The Big-Fish-Little-Pond Effect: Generalizability of Social Comparison Processes over Two Age Cohorts from Western, Asian, and Middle Eastern Islamic Countries

Science.gov (United States)

Marsh, Herbert W.; Abduljabbar, Adel Salah; Morin, Alexandre J. S.; Parker, Philip; Abdelfattah, Faisal; Nagengast, Benjamin; Abu-Hilal, Maher M.

2015-01-01

Extensive support for the seemingly paradoxical negative effects of school- and class-average achievement on academic self-concept (ASC)-the big-fish-little-pond effect (BFLPE)--is based largely on secondary students in Western countries or on cross-cultural Program for International Student Assessment studies. There is little research testing the…

Sister-chromatid exchanges in nuclear fuel workers

International Nuclear Information System (INIS)

Prabhavathi, P. Aruna; Fatima, Shehla K.; Padmavathi, P.; Kumari, C. Kusuma; Reddy, P.P.

1995-01-01

Peripheral blood lymphocyte cultures of 116 smokers and 80 non-smokers who were occupationally exposed to uranyl compounds were analysed for sister-chromatid exchanges (SCEs). Blood samples were collected from 59 non-smokers (control group I) and 47 smokers (control group II) who were not exposed to uranium for control data. A significant increase in SCEs was observed among both smokers and non-smokers exposed to uranyl compounds when compared to their respective controls. In controls, a significant increase in the frequency of SCEs was observed in smokers when compared to non-smokers

What are sister chromatid exchanges

International Nuclear Information System (INIS)

Evans, H.J.

1977-01-01

The development of new staining techniques to visualise sister chromatid exchange (SCE) in cells exposed to mutagens has led to a better understanding of the mechanisms involved in the formation of such exchanges. SCE are induced by a wide variety of different physical and chemical agents and their incidence provides a sensitive indicator of DNA damage in proliferating mammalian cells. It is shown that lesions which affect one or both strands of the DNA can result in the development of SCE, but only when damaged DNA undergoes replication. The nature of the lesions, the frequency and distribution of SEC in mammalian cells; the sensitivity of the cells to their induction by X-radiation, ultraviolet radiation and chemical mutagens, are discussed and possible mechanisms involved in the formation of SCE during replication considered. (Auth.)

20 CFR 410.340 - Determination of relationship; parent, brother, or sister.

Science.gov (United States)

2010-04-01

... domiciled (see § 410.392) at the time of his death would find, under the law they would apply in determining..., brother, or sister. Where, under such law, the individual does not bear the relationship to the miner of...

From big bang to big crunch and beyond

International Nuclear Information System (INIS)

Elitzur, Shmuel; Rabinovici, Eliezer; Giveon, Amit; Kutasov, David

2002-01-01

We study a quotient Conformal Field Theory, which describes a 3+1 dimensional cosmological spacetime. Part of this spacetime is the Nappi-Witten (NW) universe, which starts at a 'big bang' singularity, expands and then contracts to a 'big crunch' singularity at a finite time. The gauged WZW model contains a number of copies of the NW spacetime, with each copy connected to the preceding one and to the next one at the respective big bang/big crunch singularities. The sequence of NW spacetimes is further connected at the singularities to a series of non-compact static regions with closed timelike curves. These regions contain boundaries, on which the observables of the theory live. This suggests a holographic interpretation of the physics. (author)

BIG data - BIG gains? Empirical evidence on the link between big data analytics and innovation

OpenAIRE

Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

2017-01-01

This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms’ innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likel...

Classical and quantum Big Brake cosmology for scalar field and tachyonic models

Energy Technology Data Exchange (ETDEWEB)

Kamenshchik, A. Yu. [Dipartimento di Fisica e Astronomia and INFN, Via Irnerio 46, 40126 Bologna (Italy) and L.D. Landau Institute for Theoretical Physics of the Russian Academy of Sciences, Kosygin str. 2, 119334 Moscow (Russian Federation); Manti, S. [Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa (Italy)

2013-02-21

We study a relation between the cosmological singularities in classical and quantum theory, comparing the classical and quantum dynamics in some models possessing the Big Brake singularity - the model based on a scalar field and two models based on a tachyon-pseudo-tachyon field . It is shown that the effect of quantum avoidance is absent for the soft singularities of the Big Brake type while it is present for the Big Bang and Big Crunch singularities. Thus, there is some kind of a classical - quantum correspondence, because soft singularities are traversable in classical cosmology, while the strong Big Bang and Big Crunch singularities are not traversable.

Classical and quantum Big Brake cosmology for scalar field and tachyonic models

International Nuclear Information System (INIS)

Kamenshchik, A. Yu.; Manti, S.

2013-01-01

We study a relation between the cosmological singularities in classical and quantum theory, comparing the classical and quantum dynamics in some models possessing the Big Brake singularity - the model based on a scalar field and two models based on a tachyon-pseudo-tachyon field . It is shown that the effect of quantum avoidance is absent for the soft singularities of the Big Brake type while it is present for the Big Bang and Big Crunch singularities. Thus, there is some kind of a classical - quantum correspondence, because soft singularities are traversable in classical cosmology, while the strong Big Bang and Big Crunch singularities are not traversable.

Physical self-concept changes in a selective sport high school: a longitudinal cohort-sequence analysis of the big-fish-little-pond effect.

Science.gov (United States)

Marsh, Herbert W; Morin, Alexandre J; Parker, Philip D

2015-04-01

Elite athletes and nonathletes (N = 1,268) attending the same selective sport high school (4 high school age cohorts, grades 7-10, mean ages varying from 10.9 to 14.1) completed the same physical self-concept instrument 4 times over a 2-year period (multiple waves). We introduce a latent cohort-sequence analysis that provides a stronger basis for assessing developmental stability/change than either cross-sectional (multicohort, single occasion) or longitudinal (single-cohort, multiple occasion) designs, allowing us to evaluate latent means across 10 waves spanning a 5-year period (grades 7-11), although each participant contributed data for only 4 waves, spanning 2 of the 5 years. Consistent with the frame-of-reference effects embodied in the big-fish-little-pond effect (BFLPE), physical self-concepts at the start of high school were much higher for elite athletes than for nonathlete classmates, but the differences declined over time so that by the end of high school there were no differences in the 2 groups. Gender differences in favor of males had a negative linear and quadratic trajectory over time, but the consistently smaller gender differences for athletes than for nonathletes did not vary with time.

Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure

Science.gov (United States)

Asencio-Cortés, G.; Morales-Esteban, A.; Shang, X.; Martínez-Álvarez, F.

2018-06-01

Earthquake magnitude prediction is a challenging problem that has been widely studied during the last decades. Statistical, geophysical and machine learning approaches can be found in literature, with no particularly satisfactory results. In recent years, powerful computational techniques to analyze big data have emerged, making possible the analysis of massive datasets. These new methods make use of physical resources like cloud based architectures. California is known for being one of the regions with highest seismic activity in the world and many data are available. In this work, the use of several regression algorithms combined with ensemble learning is explored in the context of big data (1 GB catalog is used), in order to predict earthquakes magnitude within the next seven days. Apache Spark framework, H2 O library in R language and Amazon cloud infrastructure were been used, reporting very promising results.

Research Intelligent Precision Marketing of E-commerce Based on the Big Data

OpenAIRE

Jianhui Zhang; Junxuan Zhu

2014-01-01

This paper analyzed and summarized the development path of electronic commerce marketing based on the big data; the related aspects of intelligent precision marketing framework has been designed combined with smart technology; and describes its functional structure and operational processes. Taking into account the differences between e-commerce and traditional retail industry; constructed RFMA model combined with characterizes of the electricity suppliers, by means of k-means clustering to a...

Big Data Analytics for Flow-based Anomaly Detection in High-Speed Networks

OpenAIRE

Garofalo, Mauro

2017-01-01

The Cisco VNI Complete Forecast Highlights clearly states that the Internet traffic is growing in three different directions, Volume, Velocity, and Variety, bringing computer network into the big data era. At the same time, sophisticated network attacks are growing exponentially. Such growth making the existing signature-based security tools, like firewall and traditional intrusion detection systems, ineffective against new kind of attacks or variations of known attacks. In this dissertati...

Reducing HIV risk among transgender women in Thailand: a quasi-experimental evaluation of the sisters program.

Directory of Open Access Journals (Sweden)

Duangta Pawa

Full Text Available Transgender women are particularly at risk of HIV infection, but little evidence exists on effective HIV prevention strategies with this population. We evaluated whether Sisters, a peer-led program for transgender women, could reduce HIV risks in Pattaya, Thailand. The study used time-location sampling to recruit 308 transgender women in Pattaya into a behavioral survey in 2011. Coarsened exact matching was used to create statistically equivalent groups of program participants and non-participants, based on factors influencing likelihood of program participation. Using multivariable logistic regression, we estimated effects of any program participation and participation by delivery channel on: condom use at last sex; consistent condom and condom/water-based lubricant use in the past 3 months with commercial, casual, and regular partners; and receipt of HIV testing in the past 6 months. Program coverage reached 75% of the population. In a matched sub-sample (n = 238, participation in outreach was associated with consistent condom/water-based lubricant use with commercial partners (AOR 3.22, 95% CI 1.64-6.31. Attendance at the Sisters drop-in center was associated with receiving an HIV test (AOR 2.58, 95% CI 1.47-4.52. Dedicated transgender-friendly programs are effective at reducing HIV risks and require expansion to better serve this key population and improve HIV prevention strategies.

Pengembangan Aplikasi Antarmuka Layanan Big Data Analysis

Directory of Open Access Journals (Sweden)

Gede Karya

2017-11-01

Full Text Available In the 2016 Higher Competitive Grants Research (Hibah Bersaing Dikti, we have been successfully developed models, infrastructure and modules of Hadoop-based big data analysis application. It has also successfully developed a virtual private network (VPN network that allows integration and access to the infrastructure from outside the FTIS Computer Laboratorium. Infrastructure and application modules of analysis are then wanted to be presented as services to small and medium enterprises (SMEs in Indonesia. This research aims to develop application of big data analysis service interface integrated with Hadoop-Cluster. The research begins with finding appropriate methods and techniques for scheduling jobs, calling for ready-made Java Map-Reduce (MR application modules, and techniques for tunneling input / output and meta-data construction of service request (input and service output. The above methods and techniques are then developed into a web-based service application, as well as an executable module that runs on Java and J2EE based programming environment and can access Hadoop-Cluster in the FTIS Computer Lab. The resulting application can be accessed by the public through the site http://bigdata.unpar.ac.id. Based on the test results, the application has functioned well in accordance with the specifications and can be used to perform big data analysis. Keywords: web based service, big data analysis, Hadop, J2EE Abstrak Pada penelitian Hibah Bersaing Dikti tahun 2016 telah berhasil dikembangkan model, infrastruktur dan modul-modul aplikasi big data analysis berbasis Hadoop. Selain itu juga telah berhasil dikembangkan jaringan virtual private network (VPN yang memungkinkan integrasi dan akses infrastruktur tersebut dari luar Laboratorium Komputer FTIS. Infrastruktur dan modul aplikasi analisis tersebut selanjutnya ingin dipresentasikan sebagai layanan kepada usaha kecil dan menengah (UKM di Indonesia. Penelitian ini bertujuan untuk mengembangkan

Bartter syndrome in two sisters with a novel mutation of the CLCNKB gene, one with deafness.

Science.gov (United States)

Robitaille, Pierre; Merouani, Aicha; He, Ning; Pei, York

2011-09-01

This article describes two sisters with type III Bartter syndrome (BS) due to a novel missense variant of the CLCNKB gene. The phenotypic expression of the disease was very different in these two siblings. In one sister, the disease followed a very severe course, especially in the neonatal period and as a toddler. Both the classic symptoms and the biochemical features of the syndrome were striking. In addition, she presented with sensorineural deafness, a complication yet unreported in this subtype of BS In contrast, the least affected sister was symptom free and the biochemical features of the disease although present remained discrete throughout the prolonged follow-up. It is suggested that such a difference in the phenotypic expression of the disease is possibly secondary to the modifier effect of a gene and/or results from environmental factor(s).

Adult Sibling Relationships with Brothers and Sisters with Severe Disabilities

Science.gov (United States)

Rossetti, Zach; Hall, Sarah

2015-01-01

The purpose of this qualitative study was to examine perceptions of adult sibling relationships with a brother or sister with severe disabilities and the contexts affecting the relationships. Adult siblings without disabilities (N = 79) from 19 to 72 years of age completed an online survey with four open-ended questions about their relationship…

Reducing School Violence: School-Based Curricular Programs and School Climate

Science.gov (United States)

Greene, Michael B.

2008-01-01

This article examines two different, but interrelated approaches to reduce school violence: school-based curricular programs and efforts to change school climate. The state of the research for each is reviewed and the relationship between them is explored.

A schedule to demonstrate radiation-induced sister chromatid exchanges in human lymphocytes

International Nuclear Information System (INIS)

Chaudhuri, J.P.

1982-01-01

The reciprocal interchange between the chromatids of a chromosome, termed sister chromatid exchange (SCE), is considered to be one of the most sensitive and accurate cytogenetic parameters and respond to toxic chemicals at very low doses. But the response of SCE to ionizing radiation is very poor. Human lymphocytes fail to give SCE response when irradiated at G 0 . Probably the primary lesions induced at G 0 do not remain available long enough to find expression as SCEs. Based on this assumption a schedule was developed using caffeine to demonstrate radiation induced SCEs. Following this schedule a dose-dependent increase in the frequency of radiation induced SCEs has been observed. (orig.)

Democracy as a social technology on schools

DEFF Research Database (Denmark)

Kofod, Kasper

2009-01-01

" democracy. The democratic influence in schools thus spans from "big" parliamentary democracy to small participatoruy democracy - a dichotomy schooll leadership must maneuvre within using democratic procedures and leadership as social technologies. This article argues that a positive coinnectiion exists...... between strong leadership and having wello-functioning democratic processes in schools and the introduction of tests, quality reports and these approaches does not weaken democratic processes in schools. This connection is nonetheless changing the logics of the state, market, and the civil society vectors.......On a formal level, the influence og "big" parlamentary democracy is enhanced because parliamentary control in individual schools has become stronger; and the formal democratic influence of parents has been strengthned by their membership on school boards, the latter being an example of "small...

The role of big laboratories

CERN Document Server

Heuer, Rolf-Dieter

2013-01-01

This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward.

The role of big laboratories

International Nuclear Information System (INIS)

Heuer, R-D

2013-01-01

This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward. (paper)

Gossip Management at Universities Using Big Data Warehouse Model Integrated with a Decision Support System

Directory of Open Access Journals (Sweden)

Pelin Vardarlier

2016-01-01

Full Text Available Big Data has recently been used for many purposes like medicine, marketing and sports. It has helped improve management decisions. However, for almost each case a unique data warehouse should be built to benefit from the merits of data mining and Big Data. Hence, each time we start from scratch to form and build a Big Data Warehouse. In this study, we propose a Big Data Warehouse and a model for universities to be used for information management, to be more specific gossip management. The overall model is a decision support system that may help university administraitons when they are making decisions and also provide them with information or gossips being circulated among students and staff. In the model, unsupervised machine learning algorithms have been employed. A prototype of the proposed system has also been presented in the study. User generated data has been collected from students in order to learn gossips and students’ problems related to school, classes, staff and instructors. The findings and results of the pilot study suggest that social media messages among students may give important clues for the happenings at school and this information may be used for management purposes.The model may be developed and implemented by not only universities but also some other organisations.

The implementation of school-based lesson study at elementary school

Directory of Open Access Journals (Sweden)

Purnomo Purnomo

2017-07-01

Full Text Available This study aims to describe and interpret the implementation of school-based lesson study in SDN I Kretek. This study uses the qualitative research. The data were collected through in-depth interviews, participant observation, field notes, and documentation. The data validity was determined through sources and techniques triangulation. The data were analyzed using the Interactive Analysis Model from Miles and Huberman. The results show: (1 the planning of school-based lesson study program at SDN 1 Kretek has been implemented from the beginning of the school year 2014/2015 by establishing school-based lesson study team. This team is responsible for planning, managing, and evaluating school-based lesson study program at SDN 1 Kretek, (2 school-based lesson study at SDN 1 Kretek is implemented in three phases, namely planning, implementation, and reflection, and (3 The evaluation of lesson study is conducted by each teacher who has conducted the open class and conducted thoroughly with a meeting by a team of school-based lesson study SDN 1 Kretek at the end of the school year.

Big Data-Based Approach to Detect, Locate, and Enhance the Stability of an Unplanned Microgrid Islanding

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang; Li, Yan; Zhang, Yingchen; Zhang, Jun Jason; Gao, David Wenzhong; Muljadi, Eduard; Gu, Yi

2017-10-01

In this paper, a big data-based approach is proposed for the security improvement of an unplanned microgrid islanding (UMI). The proposed approach contains two major steps: the first step is big data analysis of wide-area monitoring to detect a UMI and locate it; the second step is particle swarm optimization (PSO)-based stability enhancement for the UMI. First, an optimal synchrophasor measurement device selection (OSMDS) and matching pursuit decomposition (MPD)-based spatial-temporal analysis approach is proposed to significantly reduce the volume of data while keeping appropriate information from the synchrophasor measurements. Second, a random forest-based ensemble learning approach is trained to detect the UMI. When combined with grid topology, the UMI can be located. Then the stability problem of the UMI is formulated as an optimization problem and the PSO is used to find the optimal operational parameters of the UMI. An eigenvalue-based multiobjective function is proposed, which aims to improve the damping and dynamic characteristics of the UMI. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed approach.

Sister broods in the spruce bark beetle, Ips typographus (L.)

Czech Academy of Sciences Publication Activity Database

Davídková, Markéta; Doležal, Petr

2017-01-01

Roč. 405, DEC 01 (2017), s. 13-21 ISSN 0378-1127 Grant - others:Lesy ČR(CZ) 08/2009-2015 Institutional support: RVO:60077344 Keywords : re-emergence * sister broods * Ips typographus Subject RIV: EH - Ecology, Behaviour OBOR OECD: Zoology Impact factor: 3.064, year: 2016 http://www.sciencedirect.com/science/article/pii/S0378112717309507

The BIG Data Center: from deposition to integration to translation.

Science.gov (United States)

2017-01-04

Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Promoting Modeling and Covariational Reasoning among Secondary School Students in the Context of Big Data

Science.gov (United States)

Gil, Einat; Gibbs, Alison L.

2017-01-01

In this study, we follow students' modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings.…

Big data, big knowledge: big data for personalized healthcare.

Science.gov (United States)

Viceconti, Marco; Hunter, Peter; Hose, Rod

2015-07-01

The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority.

BigDataBench: a Big Data Benchmark Suite from Internet Services

OpenAIRE

Wang, Lei; Zhan, Jianfeng; Luo, Chunjie; Zhu, Yuqing; Yang, Qiang; He, Yongqiang; Gao, Wanling; Jia, Zhen; Shi, Yingjie; Zhang, Shujie; Zheng, Chen; Lu, Gang; Zhan, Kent; Li, Xiaona; Qiu, Bizhu

2014-01-01

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purpo...

Phylogenetic conservatism of thermal traits explains dispersal limitation and genomic differentiation of Streptomyces sister-taxa.

Science.gov (United States)

Choudoir, Mallory J; Buckley, Daniel H

2018-06-07

The latitudinal diversity gradient is a pattern of biogeography observed broadly in plants and animals but largely undocumented in terrestrial microbial systems. Although patterns of microbial biogeography across broad taxonomic scales have been described in a range of contexts, the mechanisms that generate biogeographic patterns between closely related taxa remain incompletely characterized. Adaptive processes are a major driver of microbial biogeography, but there is less understanding of how microbial biogeography and diversification are shaped by dispersal limitation and drift. We recently described a latitudinal diversity gradient of species richness and intraspecific genetic diversity in Streptomyces by using a geographically explicit culture collection. Within this geographically explicit culture collection, we have identified Streptomyces sister-taxa whose geographic distribution is delimited by latitude. These sister-taxa differ in geographic distribution, genomic diversity, and ecological traits despite having nearly identical SSU rRNA gene sequences. Comparative genomic analysis reveals genomic differentiation of these sister-taxa consistent with restricted gene flow across latitude. Furthermore, we show phylogenetic conservatism of thermal traits between the sister-taxa suggesting that thermal trait adaptation limits dispersal and gene flow across climate regimes as defined by latitude. Such phylogenetic conservatism of thermal traits is commonly associated with latitudinal diversity gradients for plants and animals. These data provide further support for the hypothesis that the Streptomyces latitudinal diversity gradient was formed as a result of historical demographic processes defined by dispersal limitation and driven by paleoclimate dynamics.

A Big Data Platform for Storing, Accessing, Mining and Learning Geospatial Data

Science.gov (United States)

Yang, C. P.; Bambacus, M.; Duffy, D.; Little, M. M.

2017-12-01

Big Data is becoming a norm in geoscience domains. A platform that is capable to effiently manage, access, analyze, mine, and learn the big data for new information and knowledge is desired. This paper introduces our latest effort on developing such a platform based on our past years' experiences on cloud and high performance computing, analyzing big data, comparing big data containers, and mining big geospatial data for new information. The platform includes four layers: a) the bottom layer includes a computing infrastructure with proper network, computer, and storage systems; b) the 2nd layer is a cloud computing layer based on virtualization to provide on demand computing services for upper layers; c) the 3rd layer is big data containers that are customized for dealing with different types of data and functionalities; d) the 4th layer is a big data presentation layer that supports the effient management, access, analyses, mining and learning of big geospatial data.

Relations of the Big-Five personality dimensions to autodestructive behavior in clinical and non-clinical adolescent populations.

Science.gov (United States)

Kotrla Topic, Marina; Perkovic Kovacevic, Marina; Mlacic, Boris

2012-10-01

To examine the relationship between the Big-Five personality model and autodestructive behavior symptoms, namely Autodestructiveness and Suicidal Depression in two groups of participants: clinical and non-clinical adolescents. Two groups of participants, clinical (adolescents with diagnosis of psychiatric disorder based on clinical impression and according to valid diagnostic criteria, N=92) and non-clinical (high-school students, N=87), completed two sets of questionnaires: the Autodestructiveness Scale which provided data on Autodestructiveness and Suicidal Depression, and the International Personality Item Pool (IPIP), which provided data on the Big -Five personality dimensions. Clinical group showed significantly higher values on the Autodestructiveness scale in general, as well as on Suicidal Depression, Aggressiveness, and Borderline subscales than the non-clinical group. Some of the dimensions of the Big-Five personality model, ie, Emotional Stability, Conscientiousness, and Agreeableness showed significant relationship (hierarchical regression analyses, P values for β coefficients from 0.000 to 0.021) with Autodestructiveness and Suicidal Depression, even after controlling for the sex and group effects or, when analyzing Suicidal Depression, after controlling the effect of other subscales. The results indicate that dimensions of the Big-Five model are important when evaluating adolescent psychiatric patients and adolescents from general population at risk of self-destructive behavior.

BigDansing

KAUST Repository

Khayyat, Zuhair

2015-06-02

Data cleansing approaches have usually focused on detecting and fixing errors with little attention to scaling to big datasets. This presents a serious impediment since data cleansing often involves costly computations such as enumerating pairs of tuples, handling inequality joins, and dealing with user-defined functions. In this paper, we present BigDansing, a Big Data Cleansing system to tackle efficiency, scalability, and ease-of-use issues in data cleansing. The system can run on top of most common general purpose data processing platforms, ranging from DBMSs to MapReduce-like frameworks. A user-friendly programming interface allows users to express data quality rules both declaratively and procedurally, with no requirement of being aware of the underlying distributed platform. BigDansing takes these rules into a series of transformations that enable distributed computations and several optimizations, such as shared scans and specialized joins operators. Experimental results on both synthetic and real datasets show that BigDansing outperforms existing baseline systems up to more than two orders of magnitude without sacrificing the quality provided by the repair algorithms.

Research on the Impact of Big Data on Logistics

Directory of Open Access Journals (Sweden)

Wang Yaxing

2017-01-01

Full Text Available In the context of big data development, a large amount of data will appear at logistics enterprises, especially in the aspect of logistics, such as transportation, warehousing, distribution and so on. Based on the analysis of the characteristics of big data, this paper studies the impact of big data on the logistics and its action mechanism, and gives reasonable suggestions. Through building logistics data center by using the big data technology, some hidden value information behind the data will be digged out, in which the logistics enterprises can benefit from it.

Applied Research on Big-Data-Based Analysis of Chinese Basic Education Integrating Social Values —Taking Chinese Education from 3rd to 6th Grade as Example

Directory of Open Access Journals (Sweden)

Shuqin Zhao

2015-06-01

Full Text Available Primary education is the gold stage of personal growth which is the foundation of the comprehensive development of moral, intelligence, physical, art and labor. Therefore, grasping the daily education of primary students is the focus of primary education. The application of big-data analysis could focus on the micro and overall performance of students. Maybe, these data have no significance to the individuals, but the information of all the students could solve many problems in the teaching process. Accordingly the teachers could acquire the real learning level of most of the students in school and more accurately carry out the personalized education and facilitate the efficient study of students.Using the SAS statistical models, this paper mined and analyzed the 3-6 grade's big testing data on Chinese Language courses through the VOSMaP Database of the EduCube project. In this study, the results of two-way ANOVA analysis model can provide the finding and effectively assist educators to solve the child's learning problems. In China the Chinese Language courses of Basic Education focus on the cultivation of loving the motherland language, cultural and social values; it emphasizes on the development of intellectual, morality and sound personality as well as the balanced development of moral, intellectual, physical, aesthetic, labor and so on. Based on the big data analysis, this paper concludes that the Chinese Language education fused with social values can facilitate the effectiveness of this kind of integration education in China, as well as can provide the educators of this field a new thinking in the big data era.

Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig) proteins.

Science.gov (United States)

Raman, Rajeev; Rajanikanth, V; Palaniappan, Raghavan U M; Lin, Yi-Pin; He, Hongxuan; McDonough, Sean P; Sharma, Yogendra; Chang, Yung-Fu

2010-12-29

Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig) proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big) domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th) (Lig A9) and 10(th) repeats (Lig A10); and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon). All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm), probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.

Characterizing Big Data Management

Directory of Open Access Journals (Sweden)

Rogério Rossi

2015-06-01

Full Text Available Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.

Big science

CERN Multimedia

Nadis, S

2003-01-01

" "Big science" is moving into astronomy, bringing large experimental teams, multi-year research projects, and big budgets. If this is the wave of the future, why are some astronomers bucking the trend?" (2 pages).

Official statistics and Big Data

Directory of Open Access Journals (Sweden)

Peter Struijs

2014-07-01

Full Text Available The rise of Big Data changes the context in which organisations producing official statistics operate. Big Data provides opportunities, but in order to make optimal use of Big Data, a number of challenges have to be addressed. This stimulates increased collaboration between National Statistical Institutes, Big Data holders, businesses and universities. In time, this may lead to a shift in the role of statistical institutes in the provision of high-quality and impartial statistical information to society. In this paper, the changes in context, the opportunities, the challenges and the way to collaborate are addressed. The collaboration between the various stakeholders will involve each partner building on and contributing different strengths. For national statistical offices, traditional strengths include, on the one hand, the ability to collect data and combine data sources with statistical products and, on the other hand, their focus on quality, transparency and sound methodology. In the Big Data era of competing and multiplying data sources, they continue to have a unique knowledge of official statistical production methods. And their impartiality and respect for privacy as enshrined in law uniquely position them as a trusted third party. Based on this, they may advise on the quality and validity of information of various sources. By thus positioning themselves, they will be able to play their role as key information providers in a changing society.

Population-based imaging biobanks as source of big data.

Science.gov (United States)

Gatidis, Sergios; Heber, Sophia D; Storz, Corinna; Bamberg, Fabian

2017-06-01

Advances of computational sciences over the last decades have enabled the introduction of novel methodological approaches in biomedical research. Acquiring extensive and comprehensive data about a research subject and subsequently extracting significant information has opened new possibilities in gaining insight into biological and medical processes. This so-called big data approach has recently found entrance into medical imaging and numerous epidemiological studies have been implementing advanced imaging to identify imaging biomarkers that provide information about physiological processes, including normal development and aging but also on the development of pathological disease states. The purpose of this article is to present existing epidemiological imaging studies and to discuss opportunities, methodological and organizational aspects, and challenges that population imaging poses to the field of big data research.

Toward a Literature-Driven Definition of Big Data in Healthcare.

Science.gov (United States)

Baro, Emilie; Degoul, Samuel; Beuscart, Régis; Chazard, Emmanuel

2015-01-01

The aim of this study was to provide a definition of big data in healthcare. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. A total of 196 papers were included. Big data can be defined as datasets with Log(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.

The Big Improvement in PISA 2009 Reading Achievements in Serbia: Improvement of the Quality of Education or Something Else?

Directory of Open Access Journals (Sweden)

Dragica Pavlović Babić

2011-01-01

Full Text Available The PISA 2009 results in Serbia show a big improvement in reading literacy compared to 2006 – the average score is 41 points higher, which is equal to the effect of a whole year of schooling in OECD countries and represents the second highest improvement ever recorded in a PISA study. In the present paper, we discuss potential reasons for such a big improvement based on analysis of the PISA 2009 reading achievements in different countries, with a special focus on countries from the same region (Croatia, Slovenia, Montenegro, Bulgaria, Romania and Albania. The analysis shows that the largest part of the improvement was realised at lower achieving levels, suggesting that the dominant method of teaching in schools is a traditional method oriented towards the acquisition and reproduction of academic knowledge. Findings of data analysis support the conclusion that the improvement is mainly the result of certain contextual factors, such as higher student motivation and a high level of official support for the PISA study in Serbia, rather than representing a real improvement in the quality of education.

Enhancing Big Data Value Using Knowledge Discovery Techniques

OpenAIRE

Mai Abdrabo; Mohammed Elmogy; Ghada Eltaweel; Sherif Barakat

2016-01-01

The world has been drowned by floods of data due to technological development. Consequently, the Big Data term has gotten the expression to portray the gigantic sum. Different sorts of quick data are doubling every second. We have to profit from this enormous surge of data to convert it to knowledge. Knowledge Discovery (KDD) can enhance detecting the value of Big Data based on some techniques and technologies like Hadoop, MapReduce, and NoSQL. The use of Big D...

Smart Information Management in Health Big Data.

Science.gov (United States)

Muteba A, Eustache

2017-01-01

The smart information management system (SIMS) is concerned with the organization of anonymous patient records in a big data and their extraction in order to provide needful real-time intelligence. The purpose of the present study is to highlight the design and the implementation of the smart information management system. We emphasis, in one hand, the organization of a big data in flat file in simulation of nosql database, and in the other hand, the extraction of information based on lookup table and cache mechanism. The SIMS in the health big data aims the identification of new therapies and approaches to delivering care.

Big data integration: scalability and sustainability

KAUST Repository

Zhang, Zhang

2016-01-26

Integration of various types of omics data is critically indispensable for addressing most important and complex biological questions. In the era of big data, however, data integration becomes increasingly tedious, time-consuming and expensive, posing a significant obstacle to fully exploit the wealth of big biological data. Here we propose a scalable and sustainable architecture that integrates big omics data through community-contributed modules. Community modules are contributed and maintained by different committed groups and each module corresponds to a specific data type, deals with data collection, processing and visualization, and delivers data on-demand via web services. Based on this community-based architecture, we build Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase that integrates a variety of rice omics data from multiple community modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures, and community annotations. Taken together, such architecture achieves integration of different types of data from multiple community-contributed modules and accordingly features scalable, sustainable and collaborative integration of big data as well as low costs for database update and maintenance, thus helpful for building IC4R into a comprehensive knowledgebase covering all aspects of rice data and beneficial for both basic and translational researches.

The Big Sky inside

Science.gov (United States)

Adams, Earle; Ward, Tony J.; Vanek, Diana; Marra, Nancy; Hester, Carolyn; Knuth, Randy; Spangler, Todd; Jones, David; Henthorn, Melissa; Hammill, Brock; Smith, Paul; Salisbury, Rob; Reckin, Gene; Boulafentis, Johna

2009-01-01

The University of Montana (UM)-Missoula has implemented a problem-based program in which students perform scientific research focused on indoor air pollution. The Air Toxics Under the Big Sky program (Jones et al. 2007; Adams et al. 2008; Ward et al. 2008) provides a community-based framework for understanding the complex relationship between poor…

20 CFR 410.380 - Determination of dependency; parent, brother, or sister.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Determination of dependency; parent, brother... MINE HEALTH AND SAFETY ACT OF 1969, TITLE IV-BLACK LUNG BENEFITS (1969- ) Relationship and Dependency § 410.380 Determination of dependency; parent, brother, or sister. An individual who is the miner's...

Scaling Big Data Cleansing

KAUST Repository

Khayyat, Zuhair

2017-07-31

Data cleansing approaches have usually focused on detecting and fixing errors with little attention to big data scaling. This presents a serious impediment since identify- ing and repairing dirty data often involves processing huge input datasets, handling sophisticated error discovery approaches and managing huge arbitrary errors. With large datasets, error detection becomes overly expensive and complicated especially when considering user-defined functions. Furthermore, a distinctive algorithm is de- sired to optimize inequality joins in sophisticated error discovery rather than na ̈ıvely parallelizing them. Also, when repairing large errors, their skewed distribution may obstruct effective error repairs. In this dissertation, I present solutions to overcome the above three problems in scaling data cleansing. First, I present BigDansing as a general system to tackle efficiency, scalability, and ease-of-use issues in data cleansing for Big Data. It automatically parallelizes the user’s code on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also enables parallel execution of serial repair algorithms by exploiting the graph representation of discovered errors. The experimental results show that BigDansing outperforms existing baselines up to more than two orders of magnitude. Although BigDansing scales cleansing jobs, it still lacks the ability to handle sophisticated error discovery requiring inequality joins. Therefore, I developed IEJoin as an algorithm for fast inequality joins. It is based on sorted arrays and space efficient bit-arrays to reduce the problem’s search space. By comparing IEJoin against well- known optimizations, I show that it is more scalable, and several orders of magnitude faster. BigDansing depends on vertex-centric graph systems, i.e., Pregel

Big bang and big crunch in matrix string theory

OpenAIRE

Bedford, J; Papageorgakis, C; Rodríguez-Gómez, D; Ward, J

2007-01-01

Following the holographic description of linear dilaton null Cosmologies with a Big Bang in terms of Matrix String Theory put forward by Craps, Sethi and Verlinde, we propose an extended background describing a Universe including both Big Bang and Big Crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using Matrix String Theory. We provide a simple theory capable of...

Big data in forensic science and medicine.

Science.gov (United States)

Lefèvre, Thomas

2018-07-01

In less than a decade, big data in medicine has become quite a phenomenon and many biomedical disciplines got their own tribune on the topic. Perspectives and debates are flourishing while there is a lack for a consensual definition for big data. The 3Vs paradigm is frequently evoked to define the big data principles and stands for Volume, Variety and Velocity. Even according to this paradigm, genuine big data studies are still scarce in medicine and may not meet all expectations. On one hand, techniques usually presented as specific to the big data such as machine learning techniques are supposed to support the ambition of personalized, predictive and preventive medicines. These techniques are mostly far from been new and are more than 50 years old for the most ancient. On the other hand, several issues closely related to the properties of big data and inherited from other scientific fields such as artificial intelligence are often underestimated if not ignored. Besides, a few papers temper the almost unanimous big data enthusiasm and are worth attention since they delineate what is at stakes. In this context, forensic science is still awaiting for its position papers as well as for a comprehensive outline of what kind of contribution big data could bring to the field. The present situation calls for definitions and actions to rationally guide research and practice in big data. It is an opportunity for grounding a true interdisciplinary approach in forensic science and medicine that is mainly based on evidence. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Bliver big data til big business?

DEFF Research Database (Denmark)

Ritter, Thomas

2015-01-01

Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge.......Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge....

Big data uncertainties.

Science.gov (United States)

Maugis, Pierre-André G

2018-07-01

Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.

BIG DATA IN BUSINESS ENVIRONMENT

Directory of Open Access Journals (Sweden)

Logica BANICA

2015-06-01

Full Text Available In recent years, dealing with a lot of data originating from social media sites and mobile communications among data from business environments and institutions, lead to the definition of a new concept, known as Big Data. The economic impact of the sheer amount of data produced in a last two years has increased rapidly. It is necessary to aggregate all types of data (structured and unstructured in order to improve current transactions, to develop new business models, to provide a real image of the supply and demand and thereby, generate market advantages. So, the companies that turn to Big Data have a competitive advantage over other firms. Looking from the perspective of IT organizations, they must accommodate the storage and processing Big Data, and provide analysis tools that are easily integrated into business processes. This paper aims to discuss aspects regarding the Big Data concept, the principles to build, organize and analyse huge datasets in the business environment, offering a three-layer architecture, based on actual software solutions. Also, the article refers to the graphical tools for exploring and representing unstructured data, Gephi and NodeXL.

"Brothers and Sisters": A Novel Way to Teach Human Resources Management.

Science.gov (United States)

Bumpus, Minnette

2000-01-01

The novel "Brothers and Sisters" by Bebe Moore Campbell was used in a management course to explore human resource management issues, concepts, and theories. The course included prereading and postreading surveys, lecture, book review, and examination. Most of the students (92%) felt the novel was an appropriate way to meet course…

Small decisions with big impact on data analytics

OpenAIRE

Jana Diesner

2015-01-01

Big social data have enabled new opportunities for evaluating the applicability of social science theories that were formulated decades ago and were often based on small- to medium-sized samples. Big Data coupled with powerful computing has the potential to replace the statistical practice of sampling and estimating effects by measuring phenomena based on full populations. Preparing these data for analysis and conducting analytics involves a plethora of decisions, some of which are already em...

Application and Prospect of Big Data in Water Resources

Science.gov (United States)

Xi, Danchi; Xu, Xinyi

2017-04-01

Because of developed information technology and affordable data storage, we h ave entered the era of data explosion. The term "Big Data" and technology relate s to it has been created and commonly applied in many fields. However, academic studies just got attention on Big Data application in water resources recently. As a result, water resource Big Data technology has not been fully developed. This paper introduces the concept of Big Data and its key technologies, including the Hadoop system and MapReduce. In addition, this paper focuses on the significance of applying the big data in water resources and summarizing prior researches by others. Most studies in this field only set up theoretical frame, but we define the "Water Big Data" and explain its tridimensional properties which are time dimension, spatial dimension and intelligent dimension. Based on HBase, the classification system of Water Big Data is introduced: hydrology data, ecology data and socio-economic data. Then after analyzing the challenges in water resources management, a series of solutions using Big Data technologies such as data mining and web crawler, are proposed. Finally, the prospect of applying big data in water resources is discussed, it can be predicted that as Big Data technology keeps developing, "3D" (Data Driven Decision) will be utilized more in water resources management in the future.

Urban Intersection Recognition and Construction Based on Big Trace Data

Directory of Open Access Journals (Sweden)

TANG Luliang

2017-06-01

Full Text Available Intersection is an important part of the generation and renewal of urban traffic network. In this paper, a new method was proposed to detect urban intersections automatically from the spatiotemporal big trace data. Firstly, the turning point pairs were based on tracking the trace data collected by vehicles. Secondly, different types of turning point pairs were clustered by using spatial growing clustering method based on angle and distance differences, and the clustering methods of local connectivity was used to recognize the intersection. Finally, the intersection structure of multi-level road network was constructed with the range of the intersection and turning point pairs. Taking the taxi trajectory data in Wuhan city as an example, the experimental results showed that the method proposed in this paper can automatically detect and recognize the road intersection and its structure.

Volume and Value of Big Healthcare Data.

Science.gov (United States)

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.

Emerging technology and architecture for big-data analytics

CERN Document Server

Chang, Chip; Yu, Hao

2017-01-01

This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.

Toward a Literature-Driven Definition of Big Data in Healthcare

Directory of Open Access Journals (Sweden)

Emilie Baro

2015-01-01

Full Text Available Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n and the number of variables (p for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n*p≥7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR data.

Toward a Literature-Driven Definition of Big Data in Healthcare

Science.gov (United States)

Baro, Emilie; Degoul, Samuel; Beuscart, Régis; Chazard, Emmanuel

2015-01-01

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data. PMID:26137488

A Hierarchical Visualization Analysis Model of Power Big Data

Science.gov (United States)

Li, Yongjie; Wang, Zheng; Hao, Yang

2018-01-01

Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

HARNESSING BIG DATA VOLUMES

Directory of Open Access Journals (Sweden)

Bogdan DINU

2014-04-01

Full Text Available Big Data can revolutionize humanity. Hidden within the huge amounts and variety of the data we are creating we may find information, facts, social insights and benchmarks that were once virtually impossible to find or were simply inexistent. Large volumes of data allow organizations to tap in real time the full potential of all the internal or external information they possess. Big data calls for quick decisions and innovative ways to assist customers and the society as a whole. Big data platforms and product portfolio will help customers harness to the full the value of big data volumes. This paper deals with technical and technological issues related to handling big data volumes in the Big Data environment.

The Big Five at school : The impact of personality on educational attainment

NARCIS (Netherlands)

Eijck, C.J.M. van; Graaf, P.M. de

2004-01-01

We investigated the effects of the Big Five personality traits (extroversion, friendliness, conscientiousness, emotional stability, and openness) on educational attainment in the Netherlands, using data from the '1998 Family Survey Dutch Population'. All five basic personality traits have

[Applications of eco-environmental big data: Progress and prospect].

Science.gov (United States)

Zhao, Miao Miao; Zhao, Shi Cheng; Zhang, Li Yun; Zhao, Fen; Shao, Rui; Liu, Li Xiang; Zhao, Hai Feng; Xu, Ming

2017-05-18

With the advance of internet and wireless communication technology, the fields of ecology and environment have entered a new digital era with the amount of data growing explosively and big data technologies attracting more and more attention. The eco-environmental big data is based airborne and space-/land-based observations of ecological and environmental factors and its ultimate goal is to integrate multi-source and multi-scale data for information mining by taking advantages of cloud computation, artificial intelligence, and modeling technologies. In comparison with other fields, the eco-environmental big data has its own characteristics, such as diverse data formats and sources, data collected with various protocols and standards, and serving different clients and organizations with special requirements. Big data technology has been applied worldwide in ecological and environmental fields including global climate prediction, ecological network observation and modeling, and regional air pollution control. The development of eco-environmental big data in China is facing many problems, such as data sharing issues, outdated monitoring facilities and techno-logies, and insufficient data mining capacity. Despite all this, big data technology is critical to solving eco-environmental problems, improving prediction and warning accuracy on eco-environmental catastrophes, and boosting scientific research in the field in China. We expected that the eco-environmental big data would contribute significantly to policy making and environmental services and management, and thus the sustainable development and eco-civilization construction in China in the coming decades.

Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig proteins.

Directory of Open Access Journals (Sweden)

Rajeev Raman

Full Text Available BACKGROUND: Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. PRINCIPAL FINDINGS: We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th (Lig A9 and 10(th repeats (Lig A10; and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon. All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm, probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. CONCLUSIONS: We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.

Big bang and big crunch in matrix string theory

International Nuclear Information System (INIS)

Bedford, J.; Ward, J.; Papageorgakis, C.; Rodriguez-Gomez, D.

2007-01-01

Following the holographic description of linear dilaton null cosmologies with a big bang in terms of matrix string theory put forward by Craps, Sethi, and Verlinde, we propose an extended background describing a universe including both big bang and big crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using matrix string theory. We provide a simple theory capable of describing the complete evolution of this closed universe

Big data a primer

CERN Document Server

Bhuyan, Prachet; Chenthati, Deepak

2015-01-01

This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from  the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the field of big data handling. The traditional framework of relational databases can no longer provide appropriate solutions for handling big data and making it available and useful to users scattered around the globe. The study of big data covers a wide range of issues including management of heterogeneous data, big data frameworks, change management, finding patterns in data usage and evolution, data as a service, service-generated data, service management, privacy and security. All of these aspects are touched upon in this book. It also discusses big data applications in different domains. The book will prove useful to students, researchers, and practicing database and networking engineers.

Cortical Pathology in RRMS: Taking a Cue from Four Sisters

Directory of Open Access Journals (Sweden)

Massimiliano Calabrese

2012-01-01

Full Text Available Background. Although grey matter pathology is a relevant aspect of multiple sclerosis (MS both with physical and cognitive rebounds, its pathogenesis is still under investigation. To what extent the familial and sporadic cases of MS differ in cortical pathology has not been elucidated yet. Here we present a multiple case report of four sisters affected by MS, all of them having a very high burden of cortical pathology. Methods. The clinical and grey matter MRI parameters of the patients were compared with those of twenty-five-aged matched healthy women and 25 women affected by sporadic MS (matched for age, disease duration, EDSS, and white matter lesion load. Results. Despite their short disease duration (<5 years, the four sisters showed a significant cortical thinning compared to healthy controls ( and sporadic MS ( and higher CLs number ( and volume ( compared to sporadic MS. Discussion. Although limited to a single family, our observation is worth of interest since it suggests that familial factors may account for a peculiar involvement of the cortex in MS pathology. This hypothesis should be further evaluated in a large number of multiplex MS families.

Sibling cigarette smoking and peer network influences on substance use potential among adolescent: a population based study.

Science.gov (United States)

Mahboubi, Samira; Salimi, Yahya; Jorjoran Shushtari, Zahra; Rafiey, Hasan; Sajjadi, Homeira

2017-12-15

Background Peer and parental substance use are established predictors for substance use among adolescent, little is known about influence of sibling cigarette smoking and its interaction with peer network on substance use potential that can introduce an important way for substance use prevention programs. Objective The aim of present study was to explore the association of sibling cigarette smoking and peer network with substance use potential among high school students in Tehran. Subjects Data were drawn from the population-based cross-sectional study of among 650 high schools students. Methods Multiple linear regression was used in order to determine the adjusted association between cigarette smoking among family members, peer network, their interaction and substance use potential. Result Having a sister who smokes (B = 3.19; p peer network quality were associated with substance use potential (B = -0.1; p peer network quality score is much more than in who have a sister with a cigarette smoking habit. Conclusion Having a sister who smokes interacts with peer network quality; appears to be one of the important mechanisms for adolescents' tendency to substance use. These findings can help in a better understanding of substance use potential mechanisms, screening efforts and the formulation of prevention programs.

The big data processing platform for intelligent agriculture

Science.gov (United States)

Huang, Jintao; Zhang, Lichen

2017-08-01

Big data technology is another popular technology after the Internet of Things and cloud computing. Big data is widely used in many fields such as social platform, e-commerce, and financial analysis and so on. Intelligent agriculture in the course of the operation will produce large amounts of data of complex structure, fully mining the value of these data for the development of agriculture will be very meaningful. This paper proposes an intelligent data processing platform based on Storm and Cassandra to realize the storage and management of big data of intelligent agriculture.

Integrative methods for analyzing big data in precision medicine.

Science.gov (United States)

Gligorijević, Vladimir; Malod-Dognin, Noël; Pržulj, Nataša

2016-03-01

We provide an overview of recent developments in big data analyses in the context of precision medicine and health informatics. With the advance in technologies capturing molecular and medical data, we entered the area of "Big Data" in biology and medicine. These data offer many opportunities to advance precision medicine. We outline key challenges in precision medicine and present recent advances in data integration-based methods to uncover personalized information from big data produced by various omics studies. We survey recent integrative methods for disease subtyping, biomarkers discovery, and drug repurposing, and list the tools that are available to domain scientists. Given the ever-growing nature of these big data, we highlight key issues that big data integration methods will face. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[The work of Moscow communities of Sisters of Charity in own medical institutions].

Science.gov (United States)

Zorin, K V

2011-01-01

The article analyses the medical activities of Moscow communities of Sisters of Charity in curative and educational institutions organized by the communities themselves. The social ministration of communities on the territory of Moscow is considered.

S. S. Chern and I

Science.gov (United States)

Yang, Chen Ning

2013-05-01

I do not remember whether I had met Prof. S. S. Chern when he was a graduate student of Tsinghua University in Peking (now Beijing) where my father was a mathematics professor, and I was in elementary school. But I do remember how I had met Mrs. Chern for the first time, in early October, 1929, when I was seven years old and she was in junior high school. Her father, Professor Tsen, had been a professor of Mathematics at Tsinghua University already for a number of years, and the Yangs were new comers that fall. The Tsens invited us to their house for dinner and that was when I first made the acquaintence of "big sister Tsen"...

BIG´s italesættelse af BIG

DEFF Research Database (Denmark)

Brodersen, Anne Mygind; Sørensen, Britta Vilhelmine; Seiding, Mette

2008-01-01

Since Bjarke Ingels established the BIG (Bjarke Ingels Group) architectural firm in 2006, the company has succeeded in making itself heard and in attracting the attention of politicians and the media. BIG did so first and foremost by means of an overall approach to urban development that is both...... close to the political powers that be, and gain their support, but also to attract attention in the public debate. We present the issues this way: How does BIG speak out for itself? How can we explain the way the company makes itself heard, based on an analysis of the big.dk web site, the Clover Block...... by sidestepping the usual democratic process required for local plans. Politicians declared a positive interest in both the building project and a rapid decision process. However, local interest groups felt they were excluded from any influence regarding the proposal and launched a massive resistance campaign...

Maria Carolina and Marie Antoinette: Sisters and Queens in the mirror of Jacobin Public Opinion

Directory of Open Access Journals (Sweden)

Cinzia Recca

2014-09-01

Full Text Available Marie Antoinette of Franceand Maria Carolina of Naples, both consorts, contributed to a flourishing of matronage, reproducing conceptions of royal femininity that embraced both the private and public roles they were expected to fulfil. However, while the political role of the first Queen has been largely reconsidered, her sister Maria Carolina has not yet been adjudicated impartially. This is somewhat curious, because Maria Carolina inherited from her sister the same disregard towards the Revolution and this, as perceived by the Jacobins, was duly proposed in their acrimonious criticism of her political role. This paper aims to focus on this criticism, analysing how the charges against Maria Carolina in the post-French revolutionary period, were a political duplication of the Jacobin attacks on Marie Antoinette from 1791 onwards. From this point of view, the paper will focus on the portrait of Maria Carolina in 1793 revolutionary Parisby Giuseppe Gorani, an Italian Jacobin noble. His Mémoires Secrets – where Maria Carolina was represented as a wicked woman in the same terms previously employed to denounce her sister Marie Antoinette by the French Republicans – was well known across Italy. This subject dominated the main pamphlets and brochures published in Naples in 1799, during the brief duration of the Neapolitan Republic, because it legitimised the rebellion against the monarchy. After the fall of the Neapolitan Republic, the political attacks on Maria Carolina continued likewise in France, where many Neapolitan patriots were obliged to flee. Analysing  Giuseppe Gorani’s Mémoires we gather that the portrait of Marie Antoinette’s sister was painted according to the main stereotypes of  French revolutionary political culture.

Unique geometry of sister kinetochores in human oocytes during meiosis I may explain maternal age-associated increases in chromosomal abnormalities

Directory of Open Access Journals (Sweden)

Jessica Patel

2016-02-01

Full Text Available The first meiotic division in human oocytes is highly error-prone and contributes to the uniquely high incidence of aneuploidy observed in human pregnancies. A successful meiosis I (MI division entails separation of homologous chromosome pairs and co-segregation of sister chromatids. For this to happen, sister kinetochores must form attachments to spindle kinetochore-fibres emanating from the same pole. In mouse and budding yeast, sister kinetochores remain closely associated with each other during MI, enabling them to act as a single unified structure. However, whether this arrangement also applies in human meiosis I oocytes was unclear. In this study, we perform high-resolution imaging of over 1900 kinetochores in human oocytes, to examine the geometry and architecture of the human meiotic kinetochore. We reveal that sister kinetochores in MI are not physically fused, and instead individual kinetochores within a pair are capable of forming independent attachments to spindle k-fibres. Notably, with increasing female age, the separation between kinetochores increases, suggesting a degradation of centromeric cohesion and/or changes in kinetochore architecture. Our data suggest that the differential arrangement of sister kinetochores and dual k-fibre attachments may explain the high proportion of unstable attachments that form in MI and thus indicate why human oocytes are prone to aneuploidy, particularly with increasing maternal age.

Emotion Analysis on Social Big Data

Institute of Scientific and Technical Information of China (English)

REN Fuji; Kazuyuki Matsumoto

2017-01-01

In this paper, we describe a method of emotion analysis on social big data. Social big data means text data that is emerging on In-ternet social networking services.We collect multilingual web corpora and annotated emotion tags to these corpora for the purpose of emotion analysis. Because these data are constructed by manual annotation, their quality is high but their quantity is low. If we create an emotion analysis model based on this corpus with high quality and use the model for the analysis of social big data, we might be able to statistically analyze emotional sensesand behavior of the people in Internet communications, which we could not know before. In this paper, we create an emotion analysis model that integrate the high-quality emotion corpus and the automatic-constructed corpus that we created in our past studies, and then analyze a large-scale corpus consisting of Twitter tweets based on the model. As the result of time-series analysis on the large-scale corpus and the result of model evaluation, we show the effective-ness of our proposed method.

BIG DATA

OpenAIRE

Abhishek Dubey

2018-01-01

The term 'Big Data' portrays inventive methods and advances to catch, store, disseminate, oversee and break down petabyte-or bigger estimated sets of data with high-speed & diverted structures. Enormous information can be organized, non-structured or half-organized, bringing about inadequacy of routine information administration techniques. Information is produced from different distinctive sources and can touch base in the framework at different rates. With a specific end goal to handle this...

Application and Exploration of Big Data Mining in Clinical Medicine.

Science.gov (United States)

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-03-20

To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.

Synergistic convergence and split pons in horizontal gaze palsy and progressive scoliosis in two sisters

Directory of Open Access Journals (Sweden)

Jain Nitin

2011-01-01

Full Text Available Synergistic convergence is an ocular motor anomaly where on attempted abduction or on attempted horizontal gaze, both the eyes converge. It has been related to peripheral causes such as congenital fibrosis of extraocular muscles (CFEOM, congenital cranial dysinnervation syndrome, ocular misinnervation or rarely central causes like horizontal gaze palsy with progressive scoliosis, brain stem dysplasia. We hereby report the occurrence of synergistic convergence in two sisters. Both of them also had kyphoscoliosis. Magnetic resonance imaging (MRI brain and spine in both the patients showed signs of brain stem dysplasia (split pons sign differing in degree (younger sister had more marked changes.

Chiasmata promote monopolar attachment of sister chromatids and their co-segregation toward the proper pole during meiosis I.

Directory of Open Access Journals (Sweden)

Yukinobu Hirose

2011-03-01

Full Text Available The chiasma is a structure that forms between a pair of homologous chromosomes by crossover recombination and physically links the homologous chromosomes during meiosis. Chiasmata are essential for the attachment of the homologous chromosomes to opposite spindle poles (bipolar attachment and their subsequent segregation to the opposite poles during meiosis I. However, the overall function of chiasmata during meiosis is not fully understood. Here, we show that chiasmata also play a crucial role in the attachment of sister chromatids to the same spindle pole and in their co-segregation during meiosis I in fission yeast. Analysis of cells lacking chiasmata and the cohesin protector Sgo1 showed that loss of chiasmata causes frequent bipolar attachment of sister chromatids during anaphase. Furthermore, high time-resolution analysis of centromere dynamics in various types of chiasmate and achiasmate cells, including those lacking the DNA replication checkpoint factor Mrc1 or the meiotic centromere protein Moa1, showed the following three outcomes: (i during the pre-anaphase stage, the bipolar attachment of sister chromatids occurs irrespective of chiasma formation; (ii the chiasma contributes to the elimination of the pre-anaphase bipolar attachment; and (iii when the bipolar attachment remains during anaphase, the chiasmata generate a bias toward the proper pole during poleward chromosome pulling that results in appropriate chromosome segregation. Based on these results, we propose that chiasmata play a pivotal role in the selection of proper attachments and provide a backup mechanism that promotes correct chromosome segregation when improper attachments remain during anaphase I.

RPA Mediates Recruitment of MRX to Forks and Double-Strand Breaks to Hold Sister Chromatids Together.

Science.gov (United States)

Seeber, Andrew; Hegnauer, Anna Maria; Hustedt, Nicole; Deshpande, Ishan; Poli, Jérôme; Eglinger, Jan; Pasero, Philippe; Gut, Heinz; Shinohara, Miki; Hopfner, Karl-Peter; Shimada, Kenji; Gasser, Susan M

2016-12-01

The Mre11-Rad50-Xrs2 (MRX) complex is related to SMC complexes that form rings capable of holding two distinct DNA strands together. MRX functions at stalled replication forks and double-strand breaks (DSBs). A mutation in the N-terminal OB fold of the 70 kDa subunit of yeast replication protein A, rfa1-t11, abrogates MRX recruitment to both types of DNA damage. The rfa1 mutation is functionally epistatic with loss of any of the MRX subunits for survival of replication fork stress or DSB recovery, although it does not compromise end-resection. High-resolution imaging shows that either the rfa1-t11 or the rad50Δ mutation lets stalled replication forks collapse and allows the separation not only of opposing ends but of sister chromatids at breaks. Given that cohesin loss does not provoke visible sister separation as long as the RPA-MRX contacts are intact, we conclude that MRX also serves as a structural linchpin holding sister chromatids together at breaks. Copyright © 2016 Elsevier Inc. All rights reserved.

Empirical Psycho-Aesthetics and Her Sisters: Substantive and Methodological Issues--Part II

Science.gov (United States)

Konecni, Vladimir J.

2013-01-01

Empirical psycho-aesthetics is approached in this two-part article from two directions. Part I, which appeared in the Winter 2012 issue of "JAE," addressed definitional and organizational issues, including the field's origins, its relation to "sister" disciplines (experimental philosophy, cognitive neuroscience of art, and neuroaesthetics), and…

ATLAS BigPanDA Monitoring

CERN Document Server

Padolski, Siarhei; The ATLAS collaboration; Klimentov, Alexei; Korchuganova, Tatiana

2017-01-01

BigPanDA monitoring is a web based application which provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analyzing hundreds of millions of computation entities such as an event or a job BigPanDA monitoring builds different scale and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe system bigger picture such as tracking the computation nucleus and satellites performance or the progress of whole production campaign. PanDA system was originally developed for the Atlas experiment and today effectively managing more than 2 million jobs per day distributed over 170 computing centers worldwide. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about state of their computations and the source of decision support information for shifters, operators and managers. In this wor...

Big Data Analytics in Healthcare.

Science.gov (United States)

Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

2015-01-01

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

ATLAS BigPanDA Monitoring

CERN Document Server

Padolski, Siarhei; The ATLAS collaboration

2017-01-01

BigPanDA monitoring is a web-based application that provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analysing hundreds of millions of computation entities such as an event or a job BigPanDA monitoring builds different scale and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe system bigger picture such as tracking the computation nucleus and satellites performance or the progress of whole production campaign. PanDA system was originally developed for the Atlas experiment and today effectively managing more than 2 million jobs per day distributed over 170 computing centers worldwide. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about state of their computations and the source of decision support information for shifters, operators and managers. In this work...

Big data prediction of durations for online collective actions based on peak's timing

Science.gov (United States)

Nie, Shizhao; Wang, Zheng; Pujia, Wangmo; Nie, Yuan; Lu, Peng

2018-02-01

Peak Model states that each collective action has a life circle, which contains four periods of "prepare", "outbreak", "peak", and "vanish"; and the peak determines the max energy and the whole process. The peak model's re-simulation indicates that there seems to be a stable ratio between the peak's timing (TP) and the total span (T) or duration of collective actions, which needs further validations through empirical data of collective actions. Therefore, the daily big data of online collective actions is applied to validate the model; and the key is to check the ratio between peak's timing and the total span. The big data is obtained from online data recording & mining of websites. It is verified by the empirical big data that there is a stable ratio between TP and T; furthermore, it seems to be normally distributed. This rule holds for both the general cases and the sub-types of collective actions. Given the distribution of the ratio, estimated probability density function can be obtained, and therefore the span can be predicted via the peak's timing. Under the scenario of big data, the instant span (how long the collective action lasts or when it ends) will be monitored and predicted in real-time. With denser data (Big Data), the estimation of the ratio's distribution gets more robust, and the prediction of collective actions' spans or durations will be more accurate.

Big Data en surveillance, deel 1 : Definities en discussies omtrent Big Data

NARCIS (Netherlands)

Timan, Tjerk

2016-01-01

Naar aanleiding van een (vrij kort) college over surveillance en Big Data, werd me gevraagd iets dieper in te gaan op het thema, definities en verschillende vraagstukken die te maken hebben met big data. In dit eerste deel zal ik proberen e.e.a. uiteen te zetten betreft Big Data theorie en

Characterizing Big Data Management

OpenAIRE

Rogério Rossi; Kechi Hirama

2015-01-01

Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: t...

Big data: survey, technologies, opportunities, and challenges.

Science.gov (United States)

Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Ali, Waleed Kamaleldin Mahmoud; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

2014-01-01

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Big Data: Survey, Technologies, Opportunities, and Challenges

Science.gov (United States)

Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Mahmoud Ali, Waleed Kamaleldin; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

2014-01-01

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data. PMID:25136682

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE

Science.gov (United States)

Fernández, Pablo; Suárez, José Pablo; Trujillo, Agustín; Domínguez, Conrado; Santana, José Miguel

2018-03-01

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as "The Internet of Things" solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE

Science.gov (United States)

Fernández, Pablo; Suárez, José Pablo; Trujillo, Agustín; Domínguez, Conrado; Santana, José Miguel

2018-04-01

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as "The Internet of Things" solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.

Analysis of financing efficiency of big data industry in Guizhou province based on DEA models

Science.gov (United States)

Li, Chenggang; Pan, Kang; Luo, Cong

2018-03-01

Taking 20 listed enterprises of big data industry in Guizhou province as samples, this paper uses DEA method to evaluate the financing efficiency of big data industry in Guizhou province. The results show that the pure technical efficiency of big data enterprise in Guizhou province is high, whose mean value reaches to 0.925. The mean value of scale efficiency reaches to 0.749. The average value of comprehensive efficiency reaches 0.693. The comprehensive financing efficiency is low. According to the results of the study, this paper puts forward some policy and recommendations to improve the financing efficiency of the big data industry in Guizhou.

The origin of the Universe by the Big Bang theory applied in the classroom, following the proposal of the school curriculum of the State of São Paulo

Science.gov (United States)

Oliveira, J. F. dos R.

2017-07-01

The purpose of this work is show to a bibliographic study based on the analysis made to the content applied in the first year of High School, through the booklet primer of the educational curriculum of the state of São Paulo, as predicted: "Natural Sciences and their Technologies" (São Paulo, 2010), implemented since 2008 in the public education network. The analysis made compares from the content addressed by the "Student Notebook" versus "Teacher's Notebook", an indispensable tool in the teaching network on the approach of theory of the emergence of the universe. An essential theme for educational knowledge in this cycle, revealing a hypothetical model of the Big Bang, and also curved space and cosmic inflation. Possibly this model may still be a controversial subject for some groups, because it involves belief, religion, science or another perspective of universe. The field of research was carried out in a group of 40 first year students of the High School, at the State School "Professor Rômulo Pero", in the city of São Paulo, supervised by the State Board of Education - Central Region. The completion of this task presents an important tool to be used by the teacher, a Conceptual Map, in order to raise previous knowledge and probing for the established topic, in the teaching of Physics.

PARALLEL PROCESSING OF BIG POINT CLOUDS USING Z-ORDER-BASED PARTITIONING

Directory of Open Access Journals (Sweden)

C. Alis

2016-06-01

Full Text Available As laser scanning technology improves and costs are coming down, the amount of point cloud data being generated can be prohibitively difficult and expensive to process on a single machine. This data explosion is not only limited to point cloud data. Voluminous amounts of high-dimensionality and quickly accumulating data, collectively known as Big Data, such as those generated by social media, Internet of Things devices and commercial transactions, are becoming more prevalent as well. New computing paradigms and frameworks are being developed to efficiently handle the processing of Big Data, many of which utilize a compute cluster composed of several commodity grade machines to process chunks of data in parallel. A central concept in many of these frameworks is data locality. By its nature, Big Data is large enough that the entire dataset would not fit on the memory and hard drives of a single node hence replicating the entire dataset to each worker node is impractical. The data must then be partitioned across worker nodes in a manner that minimises data transfer across the network. This is a challenge for point cloud data because there exist different ways to partition data and they may require data transfer. We propose a partitioning based on Z-order which is a form of locality-sensitive hashing. The Z-order or Morton code is computed by dividing each dimension to form a grid then interleaving the binary representation of each dimension. For example, the Z-order code for the grid square with coordinates (x = 1 = 012, y = 3 = 112 is 10112 = 11. The number of points in each partition is controlled by the number of bits per dimension: the more bits, the fewer the points. The number of bits per dimension also controls the level of detail with more bits yielding finer partitioning. We present this partitioning method by implementing it on Apache Spark and investigating how different parameters affect the accuracy and running time of the k nearest

Big data business models: Challenges and opportunities

Directory of Open Access Journals (Sweden)

Ralph Schroeder

2016-12-01

Full Text Available This paper, based on 28 interviews from a range of business leaders and practitioners, examines the current state of big data use in business, as well as the main opportunities and challenges presented by big data. It begins with an account of the current landscape and what is meant by big data. Next, it draws distinctions between the ways organisations use data and provides a taxonomy of big data business models. We observe a variety of different business models, depending not only on sector, but also on whether the main advantages derive from analytics capabilities or from having ready access to valuable data sources. Some major challenges emerge from this account, including data quality and protectiveness about sharing data. The conclusion discusses these challenges, and points to the tensions and differing perceptions about how data should be governed as between business practitioners, the promoters of open data, and the wider public.

The New Urban High School: A Practitioner's Guide.

Science.gov (United States)

Big Picture Co., Cambridge, MA.

In October 1996, the Big Picture Company set out to find six urban high schools that use school-to-work strategies as a lever for whole-school reform. In the schools finally selected for the New Urban High Schools Project, and in others examined for the study, "school-to-work" is a misnomer, because the majority of students are entering…

Clinical research of traditional Chinese medicine in big data era.

Science.gov (United States)

Zhang, Junhua; Zhang, Boli

2014-09-01

With the advent of big data era, our thinking, technology and methodology are being transformed. Data-intensive scientific discovery based on big data, named "The Fourth Paradigm," has become a new paradigm of scientific research. Along with the development and application of the Internet information technology in the field of healthcare, individual health records, clinical data of diagnosis and treatment, and genomic data have been accumulated dramatically, which generates big data in medical field for clinical research and assessment. With the support of big data, the defects and weakness may be overcome in the methodology of the conventional clinical evaluation based on sampling. Our research target shifts from the "causality inference" to "correlativity analysis." This not only facilitates the evaluation of individualized treatment, disease prediction, prevention and prognosis, but also is suitable for the practice of preventive healthcare and symptom pattern differentiation for treatment in terms of traditional Chinese medicine (TCM), and for the post-marketing evaluation of Chinese patent medicines. To conduct clinical studies involved in big data in TCM domain, top level design is needed and should be performed orderly. The fundamental construction and innovation studies should be strengthened in the sections of data platform creation, data analysis technology and big-data professionals fostering and training.

From Here to There and Back Again: The Story of a Mother, Her Son, Disability, and School Choice

Science.gov (United States)

Mann, Glenys

2016-01-01

Nelly and her children live in Queensland, Australia. When it came time for her second youngest son to start school, Nelly was not prepared for the difficulty that she had enrolling him at the school of her choice. In spite of her son's disability, Nelly thought that it was natural that he would go to his local school with his sister. It is not…

An analysis of cross-sectional differences in big and non-big public accounting firms' audit programs

NARCIS (Netherlands)

Blokdijk, J.H. (Hans); Drieenhuizen, F.; Stein, M.T.; Simunic, D.A.

2006-01-01

A significant body of prior research has shown that audits by the Big 5 (now Big 4) public accounting firms are quality differentiated relative to non-Big 5 audits. This result can be derived analytically by assuming that Big 5 and non-Big 5 firms face different loss functions for "audit failures"

Big Data is invading big places as CERN

CERN Multimedia

CERN. Geneva

2017-01-01

Big Data technologies are becoming more popular with the constant grow of data generation in different fields such as social networks, internet of things and laboratories like CERN. How is CERN making use of such technologies? How machine learning is applied at CERN with Big Data technologies? How much data we move and how it is analyzed? All these questions will be answered during the talk.

The big bang

International Nuclear Information System (INIS)

Chown, Marcus.

1987-01-01

The paper concerns the 'Big Bang' theory of the creation of the Universe 15 thousand million years ago, and traces events which physicists predict occurred soon after the creation. Unified theory of the moment of creation, evidence of an expanding Universe, the X-boson -the particle produced very soon after the big bang and which vanished from the Universe one-hundredth of a second after the big bang, and the fate of the Universe, are all discussed. (U.K.)

Big data analysis framework for healthcare and social sectors in Korea.

Science.gov (United States)

Song, Tae-Min; Ryu, Seewon

2015-01-01

We reviewed applications of big data analysis of healthcare and social services in developed countries, and subsequently devised a framework for such an analysis in Korea. We reviewed the status of implementing big data analysis of health care and social services in developed countries, and strategies used by the Ministry of Health and Welfare of Korea (Government 3.0). We formulated a conceptual framework of big data in the healthcare and social service sectors at the national level. As a specific case, we designed a process and method of social big data analysis on suicide buzz. Developed countries (e.g., the United States, the UK, Singapore, Australia, and even OECD and EU) are emphasizing the potential of big data, and using it as a tool to solve their long-standing problems. Big data strategies for the healthcare and social service sectors were formulated based on an ICT-based policy of current government and the strategic goals of the Ministry of Health and Welfare. We suggest a framework of big data analysis in the healthcare and welfare service sectors separately and assigned them tentative names: 'health risk analysis center' and 'integrated social welfare service network'. A framework of social big data analysis is presented by applying it to the prevention and proactive detection of suicide in Korea. There are some concerns with the utilization of big data in the healthcare and social welfare sectors. Thus, research on these issues must be conducted so that sophisticated and practical solutions can be reached.

Managing Senior Management Team Boundaries and School Improvement: An Investigation of the School Leader Role

Science.gov (United States)

Benoliel, Pascale

2017-01-01

The present study purpose was to investigate the unique role and activities of school principals in managing their senior management team (SMT) boundaries. The study examined how school principals' internal and external activities mediate the relationship of principals' personal factors from the Big Five typology, the team and contextual…

Designing Cloud Infrastructure for Big Data in E-government

Directory of Open Access Journals (Sweden)

Jelena Šuh

2015-03-01

Full Text Available The development of new information services and technologies, especially in domains of mobile communications, Internet of things, and social media, has led to appearance of the large quantities of unstructured data. The pervasive computing also affects the e-government systems, where big data emerges and cannot be processed and analyzed in a traditional manner due to its complexity, heterogeneity and size. The subject of this paper is the design of the cloud infrastructure for big data storage and processing in e-government. The goal is to analyze the potential of cloud computing for big data infrastructure, and propose a model for effective storing, processing and analyzing big data in e-government. The paper provides an overview of current relevant concepts related to cloud infrastructure design that should provide support for big data. The second part of the paper gives a model of the cloud infrastructure based on the concepts of software defined networks and multi-tenancy. The final goal is to support projects in the field of big data in e-government

Big data opportunities and challenges

CERN Document Server

2014-01-01

This ebook aims to give practical guidance for all those who want to understand big data better and learn how to make the most of it. Topics range from big data analysis, mobile big data and managing unstructured data to technologies, governance and intellectual property and security issues surrounding big data.

Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

Directory of Open Access Journals (Sweden)

Zhenlong Li

Full Text Available Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA. Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

Science.gov (United States)

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework

Science.gov (United States)

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists. PMID:25742012

Big Data and Neuroimaging.

Science.gov (United States)

Webb-Vargas, Yenny; Chen, Shaojie; Fisher, Aaron; Mejia, Amanda; Xu, Yuting; Crainiceanu, Ciprian; Caffo, Brian; Lindquist, Martin A

2017-12-01

Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems. We use the field of statistical neuroimaging to demonstrate these points. As such, this paper covers several applications and novel methodological developments of Big Data tools applied to neuroimaging data.

Familial Churg-Strauss Syndrome in a Sister and Brother.

Science.gov (United States)

Alyasin, Soheyla; Khoshkhui, Maryam; Amin, Reza

2015-06-01

Churg-Strauss syndrome (CSS) is a granulomatous small vessel vasculitis. It is characterized by asthma, allergic granulomatosis and vasculitis. This syndrome is rare in children. A 5 years old boy was admitted with cough, fever and dyspnea for 2 weeks. On the basis of laboratory data (peripheral eosinophilia), associated with skin biopsy, and history of CSS in his sister, this disease was eventually diagnosed. The patient had good response to corticosteroid. In every asthmatic patient with prolonged fever, eosinophilia and multisystemic involvment, CSS should be considered.

Big Data; A Management Revolution : The emerging role of big data in businesses

OpenAIRE

Blasiak, Kevin

2014-01-01

Big data is a term that was coined in 2012 and has since then emerged to one of the top trends in business and technology. Big data is an agglomeration of different technologies resulting in data processing capabilities that have been unreached before. Big data is generally characterized by 4 factors. Volume, velocity and variety. These three factors distinct it from the traditional data use. The possibilities to utilize this technology are vast. Big data technology has touch points in differ...

Application and Exploration of Big Data Mining in Clinical Medicine

Science.gov (United States)

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-01-01

Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster–Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine. PMID:26960378

ATLAS BigPanDA Monitoring and Its Evolution

CERN Document Server

Wenaus, Torre; The ATLAS collaboration; Korchuganova, Tatiana

2016-01-01

BigPanDA is the latest generation of the monitoring system for the Production and Distributed Analysis (PanDA) system. The BigPanDA monitor is a core component of PanDA and also serves the monitoring needs of the new ATLAS Production System Prodsys-2. BigPanDA has been developed to serve the growing computation needs of the ATLAS Experiment and the wider applications of PanDA beyond ATLAS. Through a system-wide job database, the BigPanDA monitor provides a comprehensive and coherent view of the tasks and jobs executed by the system, from high level summaries to detailed drill-down job diagnostics. The system has been in production and has remained in continuous development since mid 2014, today effectively managing more than 2 million jobs per day distributed over 150 computing centers worldwide. BigPanDA also delivers web-based analytics and system state views to groups of users including distributed computing systems operators, shifters, physicist end-users, computing managers and accounting services. Provi...

Social big data mining

CERN Document Server

Ishikawa, Hiroshi

2015-01-01

Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.

Cryptography for Big Data Security

Science.gov (United States)

2015-07-13

Cryptography for Big Data Security Book Chapter for Big Data: Storage, Sharing, and Security (3S) Distribution A: Public Release Ariel Hamlin1 Nabil...Email: arkady@ll.mit.edu ii Contents 1 Cryptography for Big Data Security 1 1.1 Introduction...48 Chapter 1 Cryptography for Big Data Security 1.1 Introduction With the amount

Data: Big and Small.

Science.gov (United States)

Jones-Schenk, Jan

2017-02-01

Big data is a big topic in all leadership circles. Leaders in professional development must develop an understanding of what data are available across the organization that can inform effective planning for forecasting. Collaborating with others to integrate data sets can increase the power of prediction. Big data alone is insufficient to make big decisions. Leaders must find ways to access small data and triangulate multiple types of data to ensure the best decision making. J Contin Educ Nurs. 2017;48(2):60-61. Copyright 2017, SLACK Incorporated.

Big Data Revisited

DEFF Research Database (Denmark)

Kallinikos, Jannis; Constantiou, Ioanna

2015-01-01

We elaborate on key issues of our paper New games, new rules: big data and the changing context of strategy as a means of addressing some of the concerns raised by the paper’s commentators. We initially deal with the issue of social data and the role it plays in the current data revolution...... and the technological recording of facts. We further discuss the significance of the very mechanisms by which big data is produced as distinct from the very attributes of big data, often discussed in the literature. In the final section of the paper, we qualify the alleged importance of algorithms and claim...... that the structures of data capture and the architectures in which data generation is embedded are fundamental to the phenomenon of big data....

Leveraging cloud based big data analytics in knowledge management for enhanced decision making in organizations

OpenAIRE

Shorfuzzaman, Mohammad

2017-01-01

In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored and analyzed with traditional data management techniques to generate values for knowledge development. Hence, new technologies and architectures are required to store and analyze this big data through advanced data analytics and in turn generate vital real-t...

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

Science.gov (United States)

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled

Big Data in industry

Science.gov (United States)

Latinović, T. S.; Preradović, D. M.; Barz, C. R.; Latinović, M. T.; Petrica, P. P.; Pop-Vadean, A.

2016-08-01

The amount of data at the global level has grown exponentially. Along with this phenomena, we have a need for a new unit of measure like exabyte, zettabyte, and yottabyte as the last unit measures the amount of data. The growth of data gives a situation where the classic systems for the collection, storage, processing, and visualization of data losing the battle with a large amount, speed, and variety of data that is generated continuously. Many of data that is created by the Internet of Things, IoT (cameras, satellites, cars, GPS navigation, etc.). It is our challenge to come up with new technologies and tools for the management and exploitation of these large amounts of data. Big Data is a hot topic in recent years in IT circles. However, Big Data is recognized in the business world, and increasingly in the public administration. This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.

Big data analytics in immunology: a knowledge-based approach.

Science.gov (United States)

Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

2014-01-01

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

Big Data Analytics in Immunology: A Knowledge-Based Approach

Directory of Open Access Journals (Sweden)

Guang Lan Zhang

2014-01-01

Full Text Available With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

Big Data Analytics An Overview

Directory of Open Access Journals (Sweden)

Jayshree Dwivedi

2015-08-01

Full Text Available Big data is a data beyond the storage capacity and beyond the processing power is called big data. Big data term is used for data sets its so large or complex that traditional data it involves data sets with sizes. Big data size is a constantly moving target year by year ranging from a few dozen terabytes to many petabytes of data means like social networking sites the amount of data produced by people is growing rapidly every year. Big data is not only a data rather it become a complete subject which includes various tools techniques and framework. It defines the epidemic possibility and evolvement of data both structured and unstructured. Big data is a set of techniques and technologies that require new forms of assimilate to uncover large hidden values from large datasets that are diverse complex and of a massive scale. It is difficult to work with using most relational database management systems and desktop statistics and visualization packages exacting preferably massively parallel software running on tens hundreds or even thousands of servers. Big data environment is used to grab organize and resolve the various types of data. In this paper we describe applications problems and tools of big data and gives overview of big data.

Familial Predisposition of Primary Dysmenorrhea among Senior High School Girl Students

Directory of Open Access Journals (Sweden)

Prema Sharlini

2015-12-01

Full Text Available Background: Dysmenorrhea is a common female reproductive problem in women of active reproductive age which is characterized by menstrual pain or cramps in a women’s lower abdomen or back. Dysmenorrhea can be classified into primary and secondary. One of the associated risk factor of primary dysmenorrhoeais the family history, however the study on the family history of primary dysmenorrhea with recurrent menstrual pain is limited. This study was conducted to identify the correlation between family history and primary dysmenorrhea in high school girls. Methods: This cross sectional study was conducted at several senior high schools in Jatinangor from April−June 2013. One hundred and sixty two students were included in this study. The sample size was calculated based on the unpaired−dichotomous variable for the two−sided formula. A self administered questionnaire was distributed to the senior high school girl students who were in their menarche age, menstrual cycle characteristics, presence or absence of dysmenorrhea, severity of pain and presence dysmenorrhea in mothers and in sisters were inquired. Data were analyzed using chi square test. Results: Overall, there were association between positive family history and primary dysmenorrhea among the students with (p<0.001. The prevalence of dysmenorrhea in the students was 92.6% with 95% confidence interval which was 87.5−95.7%. The prevalence rate was 67.9% in mothers with 95% confidence interval which is 60.4−74.6% and 80.2% prevalence of primary dysmenorrhoea in sisters with 95% confidence interval which is 73.4−85.6%. Conclusions: There is a significant association between positive family history and primary dysmenorrhea

BIG DATA RESOURCES, MARKETING CAPABILITIES, AND FIRM PERFORMANCE.

OpenAIRE

Suoniemi, Samppa; Meyer-Waarden, Lars; Munzel, Andreas

2017-01-01

RESEARCH QUESTION Big data may significantly improve the efficiency and effectiveness of the firm's marketing capabilities. However, firms must overcome technological, skill-based and organisational challenges to become data-driven. Academic research has not empirically investigated how strategic big data resources, and to what extent, influence strategic marketing capabilities and, by extension, firm performance. The primary objective of this research is to remedy this crucial knowledge ...

Big Data: Survey, Technologies, Opportunities, and Challenges

Directory of Open Access Journals (Sweden)

Nawsher Khan

2014-01-01

Full Text Available Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

Directory of Open Access Journals (Sweden)

Yoshinobu Tamura

2015-06-01

Full Text Available At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.

Urbanising Big

DEFF Research Database (Denmark)

Ljungwall, Christer

2013-01-01

Development in China raises the question of how big a city can become, and at the same time be sustainable, writes Christer Ljungwall of the Swedish Agency for Growth Policy Analysis.......Development in China raises the question of how big a city can become, and at the same time be sustainable, writes Christer Ljungwall of the Swedish Agency for Growth Policy Analysis....

Big bang nucleosynthesis

International Nuclear Information System (INIS)

Boyd, Richard N.

2001-01-01

The precision of measurements in modern cosmology has made huge strides in recent years, with measurements of the cosmic microwave background and the determination of the Hubble constant now rivaling the level of precision of the predictions of big bang nucleosynthesis. However, these results are not necessarily consistent with the predictions of the Standard Model of big bang nucleosynthesis. Reconciling these discrepancies may require extensions of the basic tenets of the model, and possibly of the reaction rates that determine the big bang abundances

Big Data as Governmentality

DEFF Research Database (Denmark)

Flyverbom, Mikkel; Klinkby Madsen, Anders; Rasche, Andreas

data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects......This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...... of international development agendas to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development efforts, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion...

The ethics of big data in big agriculture

OpenAIRE

Carbonell (Isabelle M.)

2016-01-01

This paper examines the ethics of big data in agriculture, focusing on the power asymmetry between farmers and large agribusinesses like Monsanto. Following the recent purchase of Climate Corp., Monsanto is currently the most prominent biotech agribusiness to buy into big data. With wireless sensors on tractors monitoring or dictating every decision a farmer makes, Monsanto can now aggregate large quantities of previously proprietary farming data, enabling a privileged position with unique in...

Design of Flow Big Data System Based on Smart Pipeline Theory

Directory of Open Access Journals (Sweden)

Zhang Jianqing

2017-01-01

Full Text Available As telecom operators to build intelligent pipe more and more, analysis and processing of big data technology to deal the huge amounts of data intelligent pipeline generated has become an inevitable trend. Intelligent pipe describes operational data, sales data; operator’s pipe flow data make the value for e-commerce business form and business model in mobile e-business environment. Intelligent pipe is the third dimension of 3 D pipeline mobile electronic commerce system. Intelligent operation dimensions make the mobile e-business three-dimensional artifacts. This paper discusses the smart pipeline theory, smart pipeline flow big data system, their system framework and core technology.

Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

Science.gov (United States)

Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

2017-06-20

The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

The big data-big model (BDBM) challenges in ecological research

Science.gov (United States)

Luo, Y.

2015-12-01

The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple

A Study of the Application of Big Data in a Rural Comprehensive Information Service

Directory of Open Access Journals (Sweden)

Leifeng Guo

2015-05-01

Full Text Available Big data has attracted extensive interest due to its potential tremendous social and scientific value. Researchers are also trying to extract potential value from agriculture big data. This paper presents a study of information services based on big data from the perspective of a rural comprehensive information service. First, we introduce the background of the rural comprehensive information service, and then we present in detail the National Rural Comprehensive Information Service Platform (NRCISP, which is supported by the national science and technology support program. Next, we discuss big data in the NRCISP according to data characteristics, data sources, and data processing. Finally, we discuss a service model and services based on big data in the NRCISP.

N.Y.C. System School-Match Gaps Tracked

Science.gov (United States)

Sparks, Sarah D.

2013-01-01

The first round of this year's high-school-match notifications in New York City's massive, district-wide school choice process went out to students this month, sparking celebration, consternation, and a renewal of concerns about unequal access to the city's best schools. The Big Apple's school-matching system is certainly on a New York scale, with…

Identifying Dwarfs Workloads in Big Data Analytics

OpenAIRE

Gao, Wanling; Luo, Chunjie; Zhan, Jianfeng; Ye, Hainan; He, Xiwen; Wang, Lei; Zhu, Yuqing; Tian, Xinhui

2015-01-01

Big data benchmarking is particularly important and provides applicable yardsticks for evaluating booming big data systems. However, wide coverage and great complexity of big data computing impose big challenges on big data benchmarking. How can we construct a benchmark suite using a minimum set of units of computation to represent diversity of big data analytics workloads? Big data dwarfs are abstractions of extracting frequently appearing operations in big data computing. One dwarf represen...

Commentary:Deja vu All Over Again: What Will It Take To Solve Big Instructional Problems.

Science.gov (United States)

Ysseldyke, Jim

2000-01-01

Presents a response to "School Psychology from an Instructional Perspective: Solving Big, Not Little Problems" (this issue). The author supports Shapiro's arguments but worries much about the barriers that would have to be overcome to enable such a paradigm shift to occur. (GCP)

Parent Interest in a School-Based, School Nurse-Led Weight Management Program

Science.gov (United States)

Kubik, Martha Y.; Lee, Jiwoo

2014-01-01

Because one in three children is already overweight or obese, school-based interventions targeting secondary obesity prevention merit consideration. This study assessed parent interest in participating in a school-based, school nurse-led weight management program for young school-aged children. A random sample of parents ("n" = 122) of…

Applications of Big Data in Education

OpenAIRE

Faisal Kalota

2015-01-01

Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners' needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in educa...

Priming the Pump for Big Data at Sentara Healthcare.

Science.gov (United States)

Kern, Howard P; Reagin, Michael J; Reese, Bertram S

2016-01-01

Today's healthcare organizations are facing significant demands with respect to managing population health, demonstrating value, and accepting risk for clinical outcomes across the continuum of care. The patient's environment outside the walls of the hospital and physician's office-and outside the electronic health record (EHR)-has a substantial impact on clinical care outcomes. The use of big data is key to understanding factors that affect the patient's health status and enhancing clinicians' ability to anticipate how the patient will respond to various therapies. Big data is essential to delivering sustainable, highquality, value-based healthcare, as well as to the success of new models of care such as clinically integrated networks (CINs) and accountable care organizations.Sentara Healthcare, based in Norfolk, Virginia, has been an early adopter of the technologies that have readied us for our big data journey: EHRs, telehealth-supported electronic intensive care units, and telehealth primary care support through MDLIVE. Although we would not say Sentara is at the cutting edge of the big data trend, it certainly is among the fast followers. Use of big data in healthcare is still at an early stage compared with other industries. Tools for data analytics are maturing, but traditional challenges such as heightened data security and limited human resources remain the primary focus for regional health systems to improve care and reduce costs. Sentara primarily makes actionable use of big data in our CIN, Sentara Quality Care Network, and at our health plan, Optima Health. Big data projects can be expensive, and justifying the expense organizationally has often been easier in times of crisis. We have developed an analytics strategic plan separate from but aligned with corporate system goals to ensure optimal investment and management of this essential asset.

Toward a Literature-Driven Definition of Big Data in Healthcare

OpenAIRE

Baro, Emilie; Degoul, Samuel; Beuscart, R?gis; Chazard, Emmanuel

2015-01-01

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. ...

Big Data Semantics

NARCIS (Netherlands)

Ceravolo, Paolo; Azzini, Antonia; Angelini, Marco; Catarci, Tiziana; Cudré-Mauroux, Philippe; Damiani, Ernesto; Mazak, Alexandra; van Keulen, Maurice; Jarrar, Mustafa; Santucci, Giuseppe; Sattler, Kai-Uwe; Scannapieco, Monica; Wimmer, Manuel; Wrembel, Robert; Zaraket, Fadi

2018-01-01

Big Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing. It is, however, largely recognized that Big Data impose novel challenges in data and infrastructure management. Indeed, multiple components and procedures must be

TOWARDS EFFECTIVE CUSTOMER RELATIONSHIP MANAGEMENT IN OMAN: ROLE OF BIG DATA

OpenAIRE

Tarek Khalil; Mohammad Al-Refai; Amer Nizar Fayez; Mohammed Sharaf Qudah

2017-01-01

We established a framework to explore the feasibility of enabling big data within the customer relationship management (CRM) strategies in Oman for creating sustainable business profit nationwide. A qualitative evaluation was made based on predictive analytics convergence and big data facilitated CRM. It was found that the big data analytics can meticulously alter the competitive industrial setting, and thereby proffered notable benefits to the business organization in terms of operation, str...

Geodetic observations and modeling of magmatic inflation at the Three Sisters volcanic center, central Oregon Cascade Range, USA

Science.gov (United States)

Dzurisin, Daniel; Lisowski, Michael; Wicks, Charles W.; Poland, Michael P.; Endo, Elliot T.

2006-02-01

Tumescence at the Three Sisters volcanic center began sometime between summer 1996 and summer 1998 and was discovered in April 2001 using interferometric synthetic aperture radar (InSAR). Swelling is centered about 5 km west of the summit of South Sister, a composite basaltic-andesite to rhyolite volcano that last erupted between 2200 and 2000 yr ago, and it affects an area ˜20 km in diameter within the Three Sisters Wilderness. Yearly InSAR observations show that the average maximum displacement rate was 3-5 cm/yr through summer 2001, and the velocity of a continuous GPS station within the deforming area was essentially constant from June 2001 to June 2004. The background level of seismic activity has been low, suggesting that temperatures in the source region are high enough or the strain rate has been low enough to favor plastic deformation over brittle failure. A swarm of about 300 small earthquakes ( Mmax = 1.9) in the northeast quadrant of the deforming area on March 23-26, 2004, was the first notable seismicity in the area for at least two decades. The U.S. Geological Survey (USGS) established tilt-leveling and EDM networks at South Sister in 1985-1986, resurveyed them in 2001, the latter with GPS, and extended them to cover more of the deforming area. The 2001 tilt-leveling results are consistent with the inference drawn from InSAR that the current deformation episode did not start before 1996, i.e., the amount of deformation during 1995-2001 from InSAR fully accounts for the net tilt at South Sister during 1985-2001 from tilt-leveling. Subsequent InSAR, GPS, and leveling observations constrain the source location, geometry, and inflation rate as a function of time. A best-fit source model derived from simultaneous inversion of all three datasets is a dipping sill located 6.5 ± 2.5 km below the surface with a volume increase of 5.0 × 10 6 ± 1.5 × 10 6 m 3/yr (95% confidence limits). The most likely cause of tumescence is a pulse of basaltic magma

Recharge Area, Base-Flow and Quick-Flow Discharge Rates and Ages, and General Water Quality of Big Spring in Carter County, Missouri, 2000-04

Science.gov (United States)

Imes, Jeffrey L.; Plummer, Niel; Kleeschulte, Michael J.; Schumacher, John G.

2007-01-01

during the period of record (water years 1922 through 2004) was 1,170 cubic feet per second on December 7, 1982. The daily mean water temperature of Big Spring was monitored during water years 2001 through 2004 and showed little variability, ranging from 13 to 15? C (degree Celsius). Water temperatures generally vary less than 1? C throughout the year. The warmest temperatures occur during October and November and decrease until April, indicating Big Spring water temperature does show a slight seasonal variation. The use of the traditional hydrograph separation program HYSEP to determine the base flow and quick flow or runoff components at Big Spring failed to yield base-flow and quick-flow discharge curves that matched observations of spring characteristics. Big Spring discharge data were used in combination with specific conductance data to develop an improved hydrograph separation method for the spring. The estimated annual mean quick flow ranged from 15 to 48 cubic feet per second for the HYSEP analysis and ranged from 26 to 154 cubic feet per second for the discharge and specific conductance method for water years 2001 to 2004. Using the discharge and specific conductance method, the estimated base-flow component rises abruptly as the spring hydrograph rises, attains a peak value on the same day as the discharge peak, and then declines abruptly from its peak value. Several days later, base flow begins to increase again at an approximately linear trend, coinciding with the time at which the percentage of quick flow has reached a maximum after each recharge-induced discharge peak. The interval between the discharge peak and the peak in percentage quick flow ranges from 8 to 11 days for seven hydrograph peaks, consistent with quick-flow traveltime estimates by dye-trace tests from the mature karst Hurricane Creek Basin in the central part of the recharge area. Concentrations of environmental tracers chlorofluorocarbons (CFCs: CFC-11, CFC-12, CFC-113)

School-Based Management: Theory and Practice.

Science.gov (United States)

George, Patricia, Ed.; Potter, Eugenia Cooper, Ed.

School-based management (SBM), sometimes called site-based management, is fast becoming the hottest restructuring item in the arsenal of reformers, teachers' unions, governors, and legislators who want to change the traditional ways in which schools and school districts do business. This document comprises three main sections with contributions…

PROTOTYPE OF WEB BASED INFORMATION LITERACY TO ENHANCE STUDENT INFORMATION LITERACY SKILL IN STATE ISLAMIC HIGH SCHOOL INSAN CENDEKIA

Directory of Open Access Journals (Sweden)

Indah Kurnianingsih

2017-07-01

Full Text Available Abstract. Information Literacy (IL Program is a library program that aims to improve the ability of library users to recognize when information is needed and have the ability to locate, evaluate, and use effectively the needed information. Information literacy learning is essential to be taught and applied in education from the beginning of the school so that students are able to find and organize information effectively and efficiently particularly regard to the school assignment and learning process. At present, various educational institutions began to implement online learning model to improve the quality of teaching and research quality. Due to the advancement of information technology, the information literacy program should be adjusted with the needs of library users. The purpose of this study was to design web-based information literacy model for school library. This research conducted through several stages which are: identifying the needs of web-based IL, designing web-based IL, determining the model and the contents of a web-based IL tutorial, and creating a prototype webbased IL. The results showed that 90,74% of respondents stated the need of web-based learning IL. The prototype of web-based learning IL is consisted of six main units using combination of the Big6 Skills model and 7 Concept of Information Literacy by Shapiro and Hughes. The main fiveth units are Library Skill, Resource Skill, Research Skill, Reading Skill, and Presenting Literacy. This prototype web-based information literacy is expected to support the information literacy learning in a holistic approach.

Elementary School Philosophy: A Response

Science.gov (United States)

Wartenberg, Thomas E.

2012-01-01

This article is a response to criticism of my book "Big Ideas for Little Kids." The main topics addressed are: Who is the audience for the book? Can people without formal philosophical training can be good facilitators of elementary school philosophy discussions? Is it important to assess attempts to teach philosophy in elementary school? Should…

Comparative validity of brief to medium-length Big Five and Big Six personality questionnaires

NARCIS (Netherlands)

Thalmayer, A.G.; Saucier, G.; Eigenhuis, A.

2011-01-01

A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five

Reflections on the Law and Curricular Values in American Schools

Science.gov (United States)

Russo, Charles J.; Thro, William E.

2012-01-01

The Supreme Court's 1925 ruling in "Pierce v. Society of the Sisters of the Holy Names of Jesus and Mary" ("Pierce"), striking down a law from Oregon that would have required all children, other than those needing special education, between the ages of 8 and 16 to attend public schools, essentially upheld the right of nonpublic…

Discrete size optimization of steel trusses using a refined big bang-big crunch algorithm

Science.gov (United States)

Hasançebi, O.; Kazemzadeh Azad, S.

2014-01-01

This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang-big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of Steel Construction Allowable Stress Design (AISC-ASD) specifications. Furthermore, the performance of the proposed BB-BC algorithm is compared to its standard version as well as other well-known metaheuristic techniques. The numerical results confirm the efficiency of the proposed algorithm in practical design optimization of truss structures.

The first record of a trans-oceanic sister-group relationship between obligate vertebrate troglobites.

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Prosanta Chakrabarty

Full Text Available We show using the most complete phylogeny of one of the most species-rich orders of vertebrates (Gobiiformes, and calibrations from the rich fossil record of teleost fishes, that the genus Typhleotris, endemic to subterranean karst habitats in southwestern Madagascar, is the sister group to Milyeringa, endemic to similar subterranean systems in northwestern Australia. Both groups are eyeless, and our phylogenetic and biogeographic results show that these obligate cave fishes now found on opposite ends of the Indian Ocean (separated by nearly 7,000 km are each others closest relatives and owe their origins to the break up of the southern supercontinent, Gondwana, at the end of the Cretaceous period. Trans-oceanic sister-group relationships are otherwise unknown between blind, cave-adapted vertebrates and our results provide an extraordinary case of Gondwanan vicariance.

Big-Fish-Little-Pond Effect: Generalizability and Moderation--Two Sides of the Same Coin

Science.gov (United States)

Seaton, Marjorie; Marsh, Herbert W.; Craven, Rhonda G.

2010-01-01

Research evidence for the big-fish-little-pond effect (BFLPE) has demonstrated that attending high-ability schools has a negative effect on academic self-concept. Utilizing multilevel modeling with the 2003 Program for International Student Assessment database, the present investigation evaluated the generalizability and robustness of the BFLPE…

Big Bang! An Evaluation of NASA's Space School Musical Program for Elementary and Middle School Learners

Science.gov (United States)

Haden, C.; Styers, M.; Asplund, S.

2015-12-01

Music and the performing arts can be a powerful way to engage students in learning about science. Research suggests that content-rich songs enhance student understanding of science concepts by helping students develop content-based vocabulary, by providing examples and explanations of concepts, and connecting to personal and situational interest in a topic. Building on the role of music in engaging students in learning, and on best practices in out-of-school time learning, the NASA Discovery and New Frontiers program in association with Jet Propulsion Laboratory, Marshall Space Flight Center, and KidTribe developed Space School Musical. Space School Musical consists of a set of nine songs and 36 educational activities to teach elementary and middle school learners about the solar system and space science through an engaging storyline and the opportunity for active learning. In 2014, NASA's Jet Propulsion Laboratory contracted with Magnolia Consulting, LLC to conduct an evaluation of Space School Musical. Evaluators used a mixed methods approach to address evaluation questions related to educator professional development experiences, program implementation and perceptions, and impacts on participating students. Measures included a professional development feedback survey, facilitator follow-up survey, facilitator interviews, and a student survey. Evaluation results showed that educators were able to use the program in a variety of contexts and in different ways to best meet their instructional needs. They noted that the program worked well for diverse learners and helped to build excitement for science through engaging all learners in the musical. Students and educators reported positive personal and academic benefits to participating students. We present findings from the evaluation and lessons learned about integration of the arts into STEM education.

The relationship of psychosocial factors to mammograms, physical activity, and fruit and vegetable consumption among sisters of breast cancer patients

Directory of Open Access Journals (Sweden)

Hartman SJ

2011-08-01

Full Text Available Sheri J Hartman1, Shira I Dunsiger1, Paul B Jacobsen21Centers for Behavioral and Preventive Medicine, The Miriam Hospital and W Alpert Medical School of Brown University, Providence, RI; 2Department of Health Outcomes and Behavior, H Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USAAbstract: This study examined the relationship of psychosocial factors to health-promoting behaviors in sisters of breast cancer patients. One hundred and twenty sisters of breast cancer patients completed questionnaires assessing response efficacy of mammography screenings, physical activity, and fruit and vegetable consumption on decreasing breast cancer risk, breast cancer worry, involvement in their sister’s cancer care, mammography screenings, physical activity, and fruit and vegetable consumption. Results indicate that greater perceived effectiveness for mammograms was associated with a 67% increase in odds of yearly mammograms. Greater involvement in the patient’s care was associated with a 7% decrease in odds of yearly mammograms. Greater perceived effectiveness for physical activity was significantly related to greater physical activity. There was a trend for greater perceived effectiveness for fruits and vegetables to be associated with consuming more fruits and vegetables. Breast cancer worry was not significantly associated with the outcomes. While perceived effectiveness for a specific health behavior in reducing breast cancer risk was consistently related to engaging in that health behavior, women reported significantly lower perceived effectiveness for physical activity and fruits and vegetables than for mammograms. Making women aware of the health benefits of these behaviors may be important in promoting changes.Keywords: breast cancer risk, mammograms, physical activity, diet, perceived effectiveness

Big data need big theory too.

Science.gov (United States)

Coveney, Peter V; Dougherty, Edward R; Highfield, Roger R

2016-11-13

The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their 'depth' and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote 'blind' big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2015 The Authors.

Cross-Cultural Generalizability of Year in School Effects: Negative Effects of Acceleration and Positive Effects of Retention on Academic Self-Concept

Science.gov (United States)

Marsh, Herbert W.

2016-01-01

Given that the Big-Fish-Little-Pond-Effect, the negative effect of school-average achievement on academic self-concept, is one of the most robust findings in educational psychology (Marsh, Seaton et al., 2007), this research extends the theoretical model, based on social comparison theory, to study relative year in school effects (e.g., being 1…

Big Data and medicine: a big deal?

Science.gov (United States)

Mayer-Schönberger, V; Ingelsson, E

2018-05-01

Big Data promises huge benefits for medical research. Looking beyond superficial increases in the amount of data collected, we identify three key areas where Big Data differs from conventional analyses of data samples: (i) data are captured more comprehensively relative to the phenomenon under study; this reduces some bias but surfaces important trade-offs, such as between data quantity and data quality; (ii) data are often analysed using machine learning tools, such as neural networks rather than conventional statistical methods resulting in systems that over time capture insights implicit in data, but remain black boxes, rarely revealing causal connections; and (iii) the purpose of the analyses of data is no longer simply answering existing questions, but hinting at novel ones and generating promising new hypotheses. As a consequence, when performed right, Big Data analyses can accelerate research. Because Big Data approaches differ so fundamentally from small data ones, research structures, processes and mindsets need to adjust. The latent value of data is being reaped through repeated reuse of data, which runs counter to existing practices not only regarding data privacy, but data management more generally. Consequently, we suggest a number of adjustments such as boards reviewing responsible data use, and incentives to facilitate comprehensive data sharing. As data's role changes to a resource of insight, we also need to acknowledge the importance of collecting and making data available as a crucial part of our research endeavours, and reassess our formal processes from career advancement to treatment approval. © 2017 The Association for the Publication of the Journal of Internal Medicine.

Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

Directory of Open Access Journals (Sweden)

Jiwei Li

2016-11-01

Full Text Available Spring Festival travel rush is a phenomenon in China that population travel intensively surges in a short time around Chinese Spring Festival. This phenomenon, which is a special one in the urbanization process of China, brings a large traffic burden and various kinds of social problems, thereby causing widespread public concern. This study investigates the spatial-temporal characteristics of Spring Festival travel rush in 2015 through time series analysis and complex network analysis based on multisource big travel data derived from Baidu, Tencent, and Qihoo. The main results are as follows: First, big travel data of Baidu and Tencent obtained from location-based services might be more accurate and scientific than that of Qihoo. Second, two travel peaks appeared at five days before and six days after the Spring Festival, respectively, and the travel valley appeared on the Spring Festival. The Spring Festival travel network at the provincial scale did not have small-world and scale-free characteristics. Instead, the travel network showed a multicenter characteristic and a significant geographic clustering characteristic. Moreover, some travel path chains played a leading role in the network. Third, economic and social factors had more influence on the travel network than geographical location factors. The problem of Spring Festival travel rush will not be effectively improved in a short time because of the unbalanced urban-rural development and the unbalanced regional development. However, the development of the modern high-speed transport system and the modern information and communication technology can alleviate problems brought by Spring Festival travel rush. We suggest that a unified real-time traffic platform for Spring Festival travel rush should be established through the government's integration of mobile big data and the official authority data of the transportation department.

I-HASTREAM : density-based hierarchical clustering of big data streams and its application to big graph analytics tools

NARCIS (Netherlands)

Hassani, M.; Spaus, P.; Cuzzocrea, A.; Seidl, T.

2016-01-01

Big Data Streams are very popular at now, as stirred-up by a plethora of modern applications such as sensor networks, scientific computing tools, Web intelligence, social network analysis and mining tools, and so forth. Here, the main research issue consists in how to effectively and efficiently

Big data, big responsibilities

Directory of Open Access Journals (Sweden)

Primavera De Filippi

2014-01-01

Full Text Available Big data refers to the collection and aggregation of large quantities of data produced by and about people, things or the interactions between them. With the advent of cloud computing, specialised data centres with powerful computational hardware and software resources can be used for processing and analysing a humongous amount of aggregated data coming from a variety of different sources. The analysis of such data is all the more valuable to the extent that it allows for specific patterns to be found and new correlations to be made between different datasets, so as to eventually deduce or infer new information, as well as to potentially predict behaviours or assess the likelihood for a certain event to occur. This article will focus specifically on the legal and moral obligations of online operators collecting and processing large amounts of data, to investigate the potential implications of big data analysis on the privacy of individual users and on society as a whole.

Comparative validity of brief to medium-length Big Five and Big Six Personality Questionnaires.

Science.gov (United States)

Thalmayer, Amber Gayle; Saucier, Gerard; Eigenhuis, Annemarie

2011-12-01

A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five inventories when conducting a study and are faced with a variety of options as to inventory length. Furthermore, a 6-factor model has been proposed to extend and update the Big Five model, in part by adding a dimension of Honesty/Humility or Honesty/Propriety. In this study, 3 popular brief to medium-length Big Five measures (NEO Five Factor Inventory, Big Five Inventory [BFI], and International Personality Item Pool), and 3 six-factor measures (HEXACO Personality Inventory, Questionnaire Big Six Scales, and a 6-factor version of the BFI) were placed in competition to best predict important student life outcomes. The effect of test length was investigated by comparing brief versions of most measures (subsets of items) with original versions. Personality questionnaires were administered to undergraduate students (N = 227). Participants' college transcripts and student conduct records were obtained 6-9 months after data was collected. Six-factor inventories demonstrated better predictive ability for life outcomes than did some Big Five inventories. Additional behavioral observations made on participants, including their Facebook profiles and cell-phone text usage, were predicted similarly by Big Five and 6-factor measures. A brief version of the BFI performed surprisingly well; across inventory platforms, increasing test length had little effect on predictive validity. Comparative validity of the models and measures in terms of outcome prediction and parsimony is discussed.

Little Schools on the Prairie Still Teach a Big Lesson.

Science.gov (United States)

Kindley, Mark M.

1985-01-01

Uses Cherry County, Nebraska, to exemplify current experiences of learning and teaching in a one-room school--Nebraska has 350 of the nation's nearly 800 one-room schools. Interviews parents and teachers who cherish their one-room schools because they provide quality education, convenience (relative to consolidated schools), and support for rural…

Big Machines and Big Science: 80 Years of Accelerators at Stanford

Energy Technology Data Exchange (ETDEWEB)

Loew, Gregory

2008-12-16

Longtime SLAC physicist Greg Loew will present a trip through SLAC's origins, highlighting its scientific achievements, and provide a glimpse of the lab's future in 'Big Machines and Big Science: 80 Years of Accelerators at Stanford.'

The Evidence-Based Manifesto for School Librarians

Science.gov (United States)

Todd, Ross

2008-01-01

School Library Journal's 2007 Leadership Summit, "Where's the Evidence? Understanding the Impact of School Libraries," focused on the topic of evidence-based practice. Evidence-based school librarianship is a systematic approach that engages research-derived evidence, school librarian-observed evidence, and user-reported evidence in the processes…

X-ray- and TEM-induced mitotic recombination in Drosophila melanogaster: Unequal and sister-strand recombination

International Nuclear Information System (INIS)

Becker, H.J.

1975-01-01

Twin mosaic spots of dark-apricot and light-apricot ommatidia were found in the eyes of wsup(a)/wsup(a) females, of wsup(a) males, of females homozygous for In(1)sc 4 , wsup(a) and of attached-X females homozygous for wsup(a). The flies were raised from larvae which had been treated with 1,630 R of X-rays at the age of 48-52 hours. An additional group of wsup(a)/wsup(a) females and wsup(a) males came from larvae that had been fed with triethylene melamine (TEM) at the age of 22-24 hours. The twin spots apparently were the result of induced unequal mitotic recombination, i.e. from unequal sister-strand recombination in the males and from unequal sister-strand recombination as well as, possibly, unequal recombination between homologous strands in the females. That is, a duplication resulted in wsup(a)Dpwsup(a)/wsup(a) dark-apricto ommatidia and the corresponding deficiency in an adjacent area of wsup(a)/Dfwsup(a) light-apricot ommatidia. In an additional experiment sister-strand mitotic recombination in the ring-X chromosome of ring-X/rod-X females heterozygous for w and wsup(co) is believed to be the cause for X-ray induced single mosaic spots that show the phenotype of the rod-X marker. (orig.) [de

Big Data Meets Physics Education Research: From MOOCs to University-Led High School Programs

Science.gov (United States)

Seaton, Daniel

2017-01-01

The Massive Open Online Course (MOOC) movement has catalyzed discussions of digital learning on campuses around the world and highlighted the increasingly large, complex datasets related to learning. Physics Education Research can and should play a key role in measuring outcomes of this most recent wave of digital education. In this talk, I will discuss big data and learning analytics through multiple modes of teaching and learning enabled by the open-source edX platform: open-online, flipped, and blended. Open-Online learning will be described through analysis of MOOC offerings from Harvard and MIT, where 2.5 million unique users have led to 9 million enrollments across nearly 300 courses. Flipped instruction will be discussed through an Advanced Placement program at Davidson College that empowers high school teachers to use AP aligned, MOOC content directly in their classrooms with only their students. Analysis of this program will be highlighted, including results from a pilot study showing a positive correlation between content usage and externally validated AP exam scores. Lastly, blended learning will be discussed through specific residential use cases at Davidson College and MIT, highlighting unique course models that blend open-online and residential experiences. My hope for this talk is that listeners will better understand the current wave of digital education and the opportunities it provides for data-driven teaching and learning.

Urban Big Data and Sustainable Development Goals: Challenges and Opportunities

Directory of Open Access Journals (Sweden)

Ali Kharrazi

2016-12-01

Full Text Available Cities are perhaps one of the most challenging and yet enabling arenas for sustainable development goals. The Sustainable Development Goals (SDGs emphasize the need to monitor each goal through objective targets and indicators based on common denominators in the ability of countries to collect and maintain relevant standardized data. While this approach is aimed at harmonizing the SDGs at the national level, it presents unique challenges and opportunities for the development of innovative urban-level metrics through big data innovations. In this article, we make the case for advancing more innovative targets and indicators relevant to the SDGs through the emergence of urban big data. We believe that urban policy-makers are faced with unique opportunities to develop, experiment, and advance big data practices relevant to sustainable development. This can be achieved by situating the application of big data innovations through developing mayoral institutions for the governance of urban big data, advancing the culture and common skill sets for applying urban big data, and investing in specialized research and education programs.

Dual of big bang and big crunch

International Nuclear Information System (INIS)

Bak, Dongsu

2007-01-01

Starting from the Janus solution and its gauge theory dual, we obtain the dual gauge theory description of the cosmological solution by the procedure of double analytic continuation. The coupling is driven either to zero or to infinity at the big-bang and big-crunch singularities, which are shown to be related by the S-duality symmetry. In the dual Yang-Mills theory description, these are nonsingular as the coupling goes to zero in the N=4 super Yang-Mills theory. The cosmological singularities simply signal the failure of the supergravity description of the full type IIB superstring theory

Integrating school-based and therapeutic conflict management models at schools.

Science.gov (United States)

D'Oosterlinck, Franky; Broekaert, Eric

2003-08-01

Including children with emotional and behavioral needs in mainstream school systems leads to growing concern about the increasing number of violent and nonviolent conflicts. Schools must adapt to this evolution and adopt a more therapeutic dimension. This paper explores the possibility of integrating school-based and therapeutic conflict management models and compares two management models: a school-based conflict management program. Teaching Students To Be Peacemakers; and a therapeutic conflict management program, Life Space Crisis Intervention. The authors conclude that integration might be possible, but depends on establishing a positive school atmosphere, the central position of the teacher, and collaborative and social learning for pupils. Further implementation of integrated conflict management models can be considered but must be underpinned by appropriate scientific research.

Military Simulation Big Data: Background, State of the Art, and Challenges

Directory of Open Access Journals (Sweden)

Xiao Song

2015-01-01

Full Text Available Big data technology has undergone rapid development and attained great success in the business field. Military simulation (MS is another application domain producing massive datasets created by high-resolution models and large-scale simulations. It is used to study complicated problems such as weapon systems acquisition, combat analysis, and military training. This paper firstly reviewed several large-scale military simulations producing big data (MS big data for a variety of usages and summarized the main characteristics of result data. Then we looked at the technical details involving the generation, collection, processing, and analysis of MS big data. Two frameworks were also surveyed to trace the development of the underlying software platform. Finally, we identified some key challenges and proposed a framework as a basis for future work. This framework considered both the simulation and big data management at the same time based on layered and service oriented architectures. The objective of this review is to help interested researchers learn the key points of MS big data and provide references for tackling the big data problem and performing further research.

Comparative Validity of Brief to Medium-Length Big Five and Big Six Personality Questionnaires

Science.gov (United States)

Thalmayer, Amber Gayle; Saucier, Gerard; Eigenhuis, Annemarie

2011-01-01

A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five inventories when conducting a study and are…

Big data for health.

Science.gov (United States)

Andreu-Perez, Javier; Poon, Carmen C Y; Merrifield, Robert D; Wong, Stephen T C; Yang, Guang-Zhong

2015-07-01

This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled.

Integrating School-Based and Therapeutic Conflict Management Models at School.

Science.gov (United States)

D'Oosterlinck, Franky; Broekaert, Eric

2003-01-01

Explores the possibility of integrating school-based and therapeutic conflict management models, comparing two management models: a school-based conflict management program, "Teaching Students To Be Peacemakers"; and a therapeutic conflict management program, "Life Space Crisis Intervention." The paper concludes that integration might be possible…

Questioning the "big assumptions". Part II: recognizing organizational contradictions that impede institutional change.

Science.gov (United States)

Bowe, Constance M; Lahey, Lisa; Kegan, Robert; Armstrong, Elizabeth

2003-08-01

Well-designed medical curriculum reforms can fall short of their primary objectives during implementation when unanticipated or unaddressed organizational resistance surfaces. This typically occurs if the agents for change ignore faculty concerns during the planning stage or when the provision of essential institutional safeguards to support new behaviors are neglected. Disappointing outcomes in curriculum reforms then result in the perpetuation of or reversion to the status quo despite the loftiest of goals. Institutional resistance to change, much like that observed during personal development, does not necessarily indicate a communal lack of commitment to the organization's newly stated goals. It may reflect the existence of competing organizational objectives that must be addressed before substantive advances in a new direction can be accomplished. The authors describe how the Big Assumptions process (see previous article) was adapted and applied at the institutional level during a school of medicine's curriculum reform. Reform leaders encouraged faculty participants to articulate their reservations about considered changes to provided insights into the organization's competing commitments. The line of discussion provided an opportunity for faculty to appreciate the gridlock that existed until appropriate test of the school's long held Big Assumptions could be conducted. The Big Assumptions process proved useful in moving faculty groups to recognize and questions the validity of unchallenged institutional beliefs that were likely to undermine efforts toward change. The process also allowed the organization to put essential institutional safeguards in place that ultimately insured that substantive reforms could be sustained.

Database Resources of the BIG Data Center in 2018.

Science.gov (United States)

2018-01-04

The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Educating Rita and Her Sisters: Using Drama to Reimagine Femininities in Schools

Science.gov (United States)

Hatton, Christine

2013-01-01

This article examines drama in relation to girls' education, and considers some of the ways in which drama might be applied in schools to challenge limiting hegemonic narratives about gender and support the emerging understandings and performances of femininities of adolescent girls. It reports on case study research conducted with a Year 9 Drama…

The Effect of School-Based Management on Schools' Culture of Consumption

Science.gov (United States)

Nir, Adam E.

2007-01-01

The purpose of this study was to assess the extent to which the introduction of school-based management (SBM) has affected schools' culture of consumption and the inequalities between schools with different socio-economic backgrounds. An analysis of financial reports from 31 SBM schools over four years reveals that schools have increased rather…

Recent Development in Big Data Analytics for Business Operations and Risk Management.

Science.gov (United States)

Choi, Tsan-Ming; Chan, Hing Kai; Yue, Xiaohang

2017-01-01

"Big data" is an emerging topic and has attracted the attention of many researchers and practitioners in industrial systems engineering and cybernetics. Big data analytics would definitely lead to valuable knowledge for many organizations. Business operations and risk management can be a beneficiary as there are many data collection channels in the related industrial systems (e.g., wireless sensor networks, Internet-based systems, etc.). Big data research, however, is still in its infancy. Its focus is rather unclear and related studies are not well amalgamated. This paper aims to present the challenges and opportunities of big data analytics in this unique application domain. Technological development and advances for industrial-based business systems, reliability and security of industrial systems, and their operational risk management are examined. Important areas for future research are also discussed and revealed.

Dealing with conflict - The role of the ward sister

Directory of Open Access Journals (Sweden)

L.M. Cremer

1980-09-01

Full Text Available In the course of her duties, the ward sister has to contend with many forms of conflict, discord and dissension. These involve conflict of the intrapersonal, interpersonal and intergroup varieties. Conflict is in the main, disruptive and dysfunctional. Skilful management, however, embodying cooperative effort in its reduction can produce constructive and positive results. Conflict management strategies are therefore either restrictive or constructive. Persons in serious conflict suffer varied degrees of personality disequilibrium, which necessitates emotional first aid or crisis intervention. Such primary preventive care is applicable to patients, their relatives, and members of the nursing staff in such need.

[Wolfram syndrome: clinical and genetic analysis in two sisters].

Science.gov (United States)

Conart, J-B; Maalouf, T; Jonveaux, P; Guerci, B; Angioi, K

2011-10-01

Wolfram syndrome is a severe genetic disorder defined by the association of diabetes mellitus, optic atrophy, deafness, and diabetes insipidus. Two sisters complained of progressive visual loss. Fundus examination evidenced optic atrophy. Their past medical history revealed diabetes mellitus and deafness since childhood. The association of these symptoms made the diagnosis of Wolfram syndrome possible. It was confirmed by molecular analysis, which evidenced composite WFS1 heterozygous mutations inherited from both their mother and father. Ophthalmologists should be aware of the possibility of Wolfram syndrome when diagnosing optic atrophy in diabetic children. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

A practical guide to big data research in psychology.

Science.gov (United States)

Chen, Eric Evan; Wojcik, Sean P

2016-12-01

The massive volume of data that now covers a wide variety of human behaviors offers researchers in psychology an unprecedented opportunity to conduct innovative theory- and data-driven field research. This article is a practical guide to conducting big data research, covering data management, acquisition, processing, and analytics (including key supervised and unsupervised learning data mining methods). It is accompanied by walkthrough tutorials on data acquisition, text analysis with latent Dirichlet allocation topic modeling, and classification with support vector machines. Big data practitioners in academia, industry, and the community have built a comprehensive base of tools and knowledge that makes big data research accessible to researchers in a broad range of fields. However, big data research does require knowledge of software programming and a different analytical mindset. For those willing to acquire the requisite skills, innovative analyses of unexpected or previously untapped data sources can offer fresh ways to develop, test, and extend theories. When conducted with care and respect, big data research can become an essential complement to traditional research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Social Functioning among Girls with Fragile X or Turner Syndrome and Their Sisters.

Science.gov (United States)

Mazzocco, Michele M. M.; Baumgardner, Thomas; Freund, Lisa S.; Reiss, Allan L.

1998-01-01

Social behaviors among girls (ages 6-16) with fragile X (n=8) or Turner syndrome (n=9) were examined to address the role of family environment versus biological determinants of social dysfunction. Compared to their sisters, subjects had lower IQS and higher rating of social and attention problems. (Author/CR)

Big Data: Implications for Health System Pharmacy.

Science.gov (United States)

Stokes, Laura B; Rogers, Joseph W; Hertig, John B; Weber, Robert J

2016-07-01

Big Data refers to datasets that are so large and complex that traditional methods and hardware for collecting, sharing, and analyzing them are not possible. Big Data that is accurate leads to more confident decision making, improved operational efficiency, and reduced costs. The rapid growth of health care information results in Big Data around health services, treatments, and outcomes, and Big Data can be used to analyze the benefit of health system pharmacy services. The goal of this article is to provide a perspective on how Big Data can be applied to health system pharmacy. It will define Big Data, describe the impact of Big Data on population health, review specific implications of Big Data in health system pharmacy, and describe an approach for pharmacy leaders to effectively use Big Data. A few strategies involved in managing Big Data in health system pharmacy include identifying potential opportunities for Big Data, prioritizing those opportunities, protecting privacy concerns, promoting data transparency, and communicating outcomes. As health care information expands in its content and becomes more integrated, Big Data can enhance the development of patient-centered pharmacy services.

Climate niches of milkweeds with plesiomorphic traits (Secamonoideae; Apocynaceae) and the milkweed sister group link ancient African climates and floral evolution.

Science.gov (United States)

Livshultz, Tatyana; Mead, Jerry V; Goyder, David J; Brannin, Michelle

2011-12-01

Climate change that increases mortality of plants and pollinators can create mate-finding Allee effects and thus act as a strong selective force on floral morphology. Milkweeds (Secamonoideae and Asclepiadoideae; Apocynaceae) are typically small plants of seasonally dry habitats, with pollinia and high pollen-transfer efficiency. Their sister group (tribe Baisseeae and Dewevrella) is mostly comprised of giant lianas of African rainforests, with pollen in monads. Comparison of the two groups motivated a new hypothesis: milkweeds evolved in the context of African aridification and the shifting of rainforest to dry forest. Pollinia and high pollen-transfer efficiency may have been adaptations that alleviated mate-finding Allee effects generated by high mortality during droughts. We formally tested whether milkweeds have a drier climate niche by comparing milkweeds with plesiomorphic traits (Secamonoideae) and the milkweed sister group in continental Africa. We georeferenced specimens of the milkweed sister group and Secamonoideae in continental Africa, extracted 19 climatic variables from the Worldclim model, conducted factor analysis to identify correlated suites of variables, and compared the frequency distributions of the two lineages relative to each factor. The distributions of Secamonoideae and the milkweed sister group differed significantly relative to four factors, each correlated with a distinct suite of climate parameters: (1) air temperature (Secamonoideae: cooler), (2) total and (3) summer precipitation (Secamonoideae: drier), and (4) temperature seasonality and isothermality (Secamonoideae: more seasonal and less isothermal). Secamonoideae in continental Africa inhabit drier, cooler sites than do the milkweed sister group, consistent with a shift from rainforests to dry forests in a cooling climate.

Generalized formal model of Big Data

OpenAIRE

Shakhovska, N.; Veres, O.; Hirnyak, M.

2016-01-01

This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the “big data” term. The article proposes and describes the elements of the generalized formal model of big data. It is analyzed the peculiarities of the application of the proposed model components. It is described the fundamental differences between Big Data technology and business analytics. Big Data is supported by the distributed file system Google File System ...

On school choice and test-based accountability.

Directory of Open Access Journals (Sweden)

Damian W. Betebenner

2005-10-01

Full Text Available Among the two most prominent school reform measures currently being implemented in The United States are school choice and test-based accountability. Until recently, the two policy initiatives remained relatively distinct from one another. With the passage of the No Child Left Behind Act of 2001 (NCLB, a mutualism between choice and accountability emerged whereby school choice complements test-based accountability. In the first portion of this study we present a conceptual overview of school choice and test-based accountability and explicate connections between the two that are explicit in reform implementations like NCLB or implicit within the market-based reform literature in which school choice and test-based accountability reside. In the second portion we scrutinize the connections, in particular, between school choice and test-based accountability using a large western school district with a popular choice system in place. Data from three sources are combined to explore the ways in which school choice and test-based accountability draw on each other: state assessment data of children in the district, school choice data for every participating student in the district choice program, and a parental survey of both participants and non-participants of choice asking their attitudes concerning the use of school report cards in the district. Results suggest that choice is of benefit academically to only the lowest achieving students, choice participation is not uniform across different ethnic groups in the district, and parents' primary motivations as reported on a survey for participation in choice are not due to test scores, though this is not consistent with choice preferences among parents in the district. As such, our results generally confirm the hypotheses of choice critics more so than advocates. Keywords: school choice; accountability; student testing.

What if the big bang didn't happen?

International Nuclear Information System (INIS)

Narlikar, J.

1991-01-01

Although it has wide support amongst cosmologists, the big bang theory of the origin of the Universe is brought into question in this article because of several recent observations. The large red shift observed in quasars does not fit with Hubble's Law which is so successful for galaxies. Some quasars appear to be linked to companion galaxies by filaments and, again, anomalous red shifts have been observed. The cosmic microwave background, or relic radiation, seems to be too uniform to fit with the big bang model. Lastly, the dark matter, necessary to explain the coalescing of galaxies and clusters, has yet to be established experimentally. A new alternative to the big bang model is offered based on recent work on cosmic grains. (UK)

Characterizing the changes in teaching practice during first semester implementation of an argument-based inquiry approach in a middle school science classroom

Science.gov (United States)

Pinney, Brian Robert John

The purpose of this study was to characterize ways in which teaching practice in classroom undergoing first semester implementation of an argument-based inquiry approach changes in whole-class discussion. Being that argument is explicitly called for in the Next Generation Science Standards and is currently a rare practice in teaching, many teachers will have to transform their teaching practice for inclusion of this feature. Most studies on Argument-Based Inquiry (ABI) agree that development of argument does not come easily and is only acquired through practice. Few studies have examined the ways in which teaching practice changes in relation to the big idea or disciplinary core idea (NGSS), the development of dialogue, and/or the development of argument during first semester implementation of an argument-based inquiry approach. To explore these areas, this study posed three primary research questions: (1) How does a teacher in his first semester of Science Writing Heuristic professional development make use of the "big idea"?, (1a) Is the indicated big idea consistent with NGSS core concepts?, (2) How did the dialogue in whole-class discussion change during the first semester of argument-based inquiry professional development?, (3) How did the argument in whole-class discussion change during the first semester of argument-based inquiry professional development? This semester-long study that took place in a middle school in a rural Midwestern city was grounded in interactive constructivism, and utilized a qualitative design to identify the ways in which the teacher utilized big ideas and how dialogue and argumentative dialogue developed over time. The purposefully selected teacher in this study provided a unique situation where he was in his first semester of professional development using the Science Writing Heuristic Approach to argument-based inquiry with 19 students who had two prior years' experience in ABI. Multiple sources of data were collected, including

How universal is the Big Five? Testing the five-factor model of personality variation among forager-farmers in the Bolivian Amazon.

Science.gov (United States)

Gurven, Michael; von Rueden, Christopher; Massenkoff, Maxim; Kaplan, Hillard; Lero Vie, Marino

2013-02-01

The five-factor model (FFM) of personality variation has been replicated across a range of human societies, suggesting the FFM is a human universal. However, most studies of the FFM have been restricted to literate, urban populations, which are uncharacteristic of the majority of human evolutionary history. We present the first test of the FFM in a largely illiterate, indigenous society. Tsimane forager-horticulturalist men and women of Bolivia (n = 632) completed a translation of the 44-item Big Five Inventory (Benet-Martínez & John, 1998), a widely used metric of the FFM. We failed to find robust support for the FFM, based on tests of (a) internal consistency of items expected to segregate into the Big Five factors, (b) response stability of the Big Five, (c) external validity of the Big Five with respect to observed behavior, (d) factor structure according to exploratory and confirmatory factor analysis, and (e) similarity with a U.S. target structure based on Procrustes rotation analysis. Replication of the FFM was not improved in a separate sample of Tsimane adults (n = 430), who evaluated their spouses on the Big Five Inventory. Removal of reverse-scored items that may have elicited response biases produced factors suggestive of Extraversion, Agreeableness, and Conscientiousness, but fit to the FFM remained poor. Response styles may covary with exposure to education, but we found no better fit to the FFM among Tsimane who speak Spanish or have attended school. We argue that Tsimane personality variation displays 2 principal factors that may reflect socioecological characteristics common to small-scale societies. We offer evolutionary perspectives on why the structure of personality variation may not be invariant across human societies. (c) 2013 APA, all rights reserved.

How Universal Is the Big Five? Testing the Five-Factor Model of Personality Variation Among Forager–Farmers in the Bolivian Amazon

Science.gov (United States)

Gurven, Michael; von Rueden, Christopher; Massenkoff, Maxim; Kaplan, Hillard; Vie, Marino Lero

2014-01-01

The five-factor model (FFM) of personality variation has been replicated across a range of human societies, suggesting the FFM is a human universal. However, most studies of the FFM have been restricted to literate, urban populations, which are uncharacteristic of the majority of human evolutionary history. We present the first test of the FFM in a largely illiterate, indigenous society. Tsimane forager–horticulturalist men and women of Bolivia (n = 632) completed a translation of the 44-item Big Five Inventory (Benet-Martínez & John, 1998), a widely used metric of the FFM. We failed to find robust support for the FFM, based on tests of (a) internal consistency of items expected to segregate into the Big Five factors, (b) response stability of the Big Five, (c) external validity of the Big Five with respect to observed behavior, (d) factor structure according to exploratory and confirmatory factor analysis, and (e) similarity with a U.S. target structure based on Procrustes rotation analysis. Replication of the FFM was not improved in a separate sample of Tsimane adults (n = 430), who evaluated their spouses on the Big Five Inventory. Removal of reverse-scored items that may have elicited response biases produced factors suggestive of Extraversion, Agreeableness, and Conscientiousness, but fit to the FFM remained poor. Response styles may covary with exposure to education, but we found no better fit to the FFM among Tsimane who speak Spanish or have attended school. We argue that Tsimane personality variation displays 2 principal factors that may reflect socioecological characteristics common to small-scale societies. We offer evolutionary perspectives on why the structure of personality variation may not be invariant across human societies. PMID:23245291

Getting started with Greenplum for big data analytics

CERN Document Server

Gollapudi, Sunila

2013-01-01

Standard tutorial-based approach.""Getting Started with Greenplum for Big Data"" Analytics is great for data scientists and data analysts with a basic knowledge of Data Warehousing and Business Intelligence platforms who are new to Big Data and who are looking to get a good grounding in how to use the Greenplum Platform. It's assumed that you will have some experience with database design and programming as well as be familiar with analytics tools like R and Weka.

SETI as a part of Big History

Science.gov (United States)

Maccone, Claudio

2014-08-01

Big History is an emerging academic discipline which examines history scientifically from the Big Bang to the present. It uses a multidisciplinary approach based on combining numerous disciplines from science and the humanities, and explores human existence in the context of this bigger picture. It is taught at some universities. In a series of recent papers ([11] through [15] and [17] through [18]) and in a book [16], we developed a new mathematical model embracing Darwinian Evolution (RNA to Humans, see, in particular, [17] and Human History (Aztecs to USA, see [16]) and then we extrapolated even that into the future up to ten million years (see 18), the minimum time requested for a civilization to expand to the whole Milky Way (Fermi paradox). In this paper, we further extend that model in the past so as to let it start at the Big Bang (13.8 billion years ago) thus merging Big History, Evolution on Earth and SETI (the modern Search for ExtraTerrestrial Intelligence) into a single body of knowledge of a statistical type. Our idea is that the Geometric Brownian Motion (GBM), so far used as the key stochastic process of financial mathematics (Black-Sholes models and related 1997 Nobel Prize in Economics!) may be successfully applied to the whole of Big History. In particular, in this paper we derive the Statistical Drake Equation (namely the statistical extension of the classical Drake Equation typical of SETI) can be regarded as the “frozen in time” part of GBM. This makes SETI a subset of our Big History Theory based on GBMs: just as the GBM is the “movie” unfolding in time, so the Statistical Drake Equation is its “still picture”, static in time, and the GBM is the time-extension of the Drake Equation. Darwinian Evolution on Earth may be easily described as an increasing GBM in the number of living species on Earth over the last 3.5 billion years. The first of them was RNA 3.5 billion years ago, and now 50 million living species or more exist, each

Big Fish, Little Fish: Teaching and Learning in the Middle Years

Science.gov (United States)

Groundwater-Smith, Susan, Ed.; Mockler, Nicole, Ed.

2015-01-01

"Big Fish, Little Fish: Teaching and Learning in the Middle Years" provides pre-service and early career teachers with a pathway to understanding the needs of students as they make the important transition from primary to secondary schooling. The book explores contemporary challenges for teaching and learning in the middle years, with a…

Living with a Brother Who Has an Autism Spectrum Disorder: A Sister's Perspective

Science.gov (United States)

Connell, Zara O.; Halloran, Maeve O.; Doody, Owen

2016-01-01

People with Autism Spectrum Disorder (ASD) are born into families and influence family functioning both positively and negatively. One of the most enduring relationships a person with ASD will have is their relationship with a brother or sister. Services for people with ASD should provide effective support to families, which include brothers,…

Big physics quartet win government backing

Science.gov (United States)

Banks, Michael

2014-09-01

Four major physics-based projects are among 10 to have been selected by Japan’s Ministry of Education, Culture, Sports, Science and Technology for funding in the coming decade as part of its “roadmap” of big-science projects.

Big data-driven business how to use big data to win customers, beat competitors, and boost profits

CERN Document Server

Glass, Russell

2014-01-01

Get the expert perspective and practical advice on big data The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits makes the case that big data is for real, and more than just big hype. The book uses real-life examples-from Nate Silver to Copernicus, and Apple to Blackberry-to demonstrate how the winners of the future will use big data to seek the truth. Written by a marketing journalist and the CEO of a multi-million-dollar B2B marketing platform that reaches more than 90% of the U.S. business population, this book is a comprehens

Small Core, Big Network: A Comprehensive Approach to GIS Teaching Practice Based on Digital Three-Dimensional Campus Reconstruction

Science.gov (United States)

Cheng, Liang; Zhang, Wen; Wang, Jiechen; Li, Manchun; Zhong, Lishan

2014-01-01

Geographic information science (GIS) features a wide range of disciplines and has broad applicability. Challenges associated with rapidly developing GIS technology and the currently limited teaching and practice materials hinder universities from cultivating highly skilled GIS graduates. Based on the idea of "small core, big network," a…

Big Game Reporting Stations

Data.gov (United States)

Vermont Center for Geographic Information — Point locations of big game reporting stations. Big game reporting stations are places where hunters can legally report harvested deer, bear, or turkey. These are...

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

Science.gov (United States)

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

My Sister, Our Stories: Exploring the Lived Experience of School Leavers through Narrative and Poetics

Science.gov (United States)

Davis, C. Amelia; Pepperell, Jennifer L.

2012-01-01

The purpose of this study was to explore the educational experiences of two adult female siblings who are both school leavers. Through the use of thematic narrative analysis, sibling narratives and poetic re-presentations, their stories were developed. These stories represent the participants' experiences of prior schooling and their current…

A Model-Driven Methodology for Big Data Analytics-as-a-Service

OpenAIRE

Damiani, Ernesto; Ardagna, Claudio Agostino; Ceravolo, Paolo; Bellandi, Valerio; Bezzi, Michele; Hebert, Cedric

2017-01-01

The Big Data revolution has promised to build a data-driven ecosystem where better decisions are supported by enhanced analytics and data management. However, critical issues still need to be solved in the road that leads to commodization of Big Data Analytics, such as the management of Big Data complexity and the protection of data security and privacy. In this paper, we focus on the first issue and propose a methodology based on Model Driven Engineering (MDE) that aims to substantially lowe...

Opening Schools to All (Women): Efforts to Overcome Gender Violence in Spain

Science.gov (United States)

Oliver, E.; Soler, M.; Flecha, R.

2009-01-01

This article shows how the dialogic approach adopted by some schools in Spain generates a shift in approaches to gender violence, an issue still not explored in the literature. The shift is from an approach determined mainly by female experts to a dialogic one in which all women, including teachers, mothers, students, sisters, stepsisters,…

School-Based Primary School Sexuality Education for Migrant Children in Beijing, China

Science.gov (United States)

Liu, Wenli; Su, Yufen

2014-01-01

In May 2007, Beijing Normal University launched a programme of school-based sexuality education for migrant children in Xingzhi Primary School in Beijing. Over the past seven years, the project team has developed a school-based sexuality education curriculum using the "International Technical Guidance on Sexuality Education" published by…

A study on decision-making of food supply chain based on big data

OpenAIRE

Ji, Guojun; Hu, Limei; Tan, Kim Hua

2017-01-01

As more and more companies have captured and analyzed huge volumes of data to improve the performance of supply chain, this paper develops a big data harvest model that uses big data as inputs to make more informed production decisions in the food supply chain. By introducing a method of Bayesian network, this paper integrates sample data and finds a cause-and-effect between data to predict market demand. Then the deduction graph model that translates products demand into processes and divide...

A research on the security of wisdom campus based on geospatial big data

Science.gov (United States)

Wang, Haiying

2018-05-01

There are some difficulties in wisdom campus, such as geospatial big data sharing, function expansion, data management, analysis and mining geospatial big data for a characteristic, especially the problem of data security can't guarantee cause prominent attention increasingly. In this article we put forward a data-oriented software architecture which is designed by the ideology of orienting data and data as kernel, solve the problem of traditional software architecture broaden the campus space data research, develop the application of wisdom campus.

Stalin's Big Fleet Program

National Research Council Canada - National Science Library

Mauner, Milan

2002-01-01

Although Dr. Milan Hauner's study 'Stalin's Big Fleet program' has focused primarily on the formation of Big Fleets during the Tsarist and Soviet periods of Russia's naval history, there are important lessons...

Five Big, Big Five Issues : Rationale, Content, Structure, Status, and Crosscultural Assessment

NARCIS (Netherlands)

De Raad, Boele

1998-01-01

This article discusses the rationale, content, structure, status, and crosscultural assessment of the Big Five trait factors, focusing on topics of dispute and misunderstanding. Taxonomic restrictions of the original Big Five forerunner, the "Norman Five," are discussed, and criticisms regarding the

Big data challenges

DEFF Research Database (Denmark)

Bachlechner, Daniel; Leimbach, Timo

2016-01-01

Although reports on big data success stories have been accumulating in the media, most organizations dealing with high-volume, high-velocity and high-variety information assets still face challenges. Only a thorough understanding of these challenges puts organizations into a position in which...... they can make an informed decision for or against big data, and, if the decision is positive, overcome the challenges smoothly. The combination of a series of interviews with leading experts from enterprises, associations and research institutions, and focused literature reviews allowed not only...... framework are also relevant. For large enterprises and startups specialized in big data, it is typically easier to overcome the challenges than it is for other enterprises and public administration bodies....

Big Data and HPC collocation: Using HPC idle resources for Big Data Analytics

OpenAIRE

MERCIER , Michael; Glesser , David; Georgiou , Yiannis; Richard , Olivier

2017-01-01

International audience; Executing Big Data workloads upon High Performance Computing (HPC) infrastractures has become an attractive way to improve their performances. However, the collocation of HPC and Big Data workloads is not an easy task, mainly because of their core concepts' differences. This paper focuses on the challenges related to the scheduling of both Big Data and HPC workloads on the same computing platform. In classic HPC workloads, the rigidity of jobs tends to create holes in ...

The big five of school leadership competencies in the Netherlands

NARCIS (Netherlands)

Krüger, M.

2009-01-01

School leaders have been given an important role in initiating and implementing school improvement, which demands new forms of leadership. This invokes the question of the basic competences for leadership that are presently required. This article focuses on the formulation of competences for school

Teachers' Knowledge and Readiness towards Implementation of School Based Assessment in Secondary Schools

Science.gov (United States)

Veloo, Arsaythamby; Krishnasamy, Hariharan N.; Md-Ali, Ruzlan

2015-01-01

School-Based Assessment (SBA) was implemented in Malaysian secondary schools in 2012. Since its implementation, teachers have faced several challenges to meet the aims and objectives of the School-Based Assessment. Based on these challenges this study aims to find the level of teachers' knowledge and readiness towards the implementation of…

School-Based Drug Abuse Prevention Programs in High School Students

Science.gov (United States)

Sharma, Manoj; Branscum, Paul

2013-01-01

Drug abuse, or substance abuse, is a substantial public health problem in the United States, particularly among high school students. The purpose of this article was to review school-based programs implemented in high schools for substance abuse prevention and to suggest recommendations for future interventions. Included were English language…

Public, Private, and Home School Children's Views of Forgiveness and Retribution in "Cinderella."

Science.gov (United States)

Knafle, June D.; Wescott, Alice Legenza

Fifth Graders (N=626) from public, Catholic, Christian, and home schools reacted to values of forgiveness versus retribution in the two main versions of "Cinderella" by choosing which ending they preferred for themselves, for a 4-year old sister, and for a 4-year old brother. Girls preferred the forgiveness ending for themselves…

Boarding to Big data

Directory of Open Access Journals (Sweden)

Oana Claudia BRATOSIN

2016-05-01

Full Text Available Today Big data is an emerging topic, as the quantity of the information grows exponentially, laying the foundation for its main challenge, the value of the information. The information value is not only defined by the value extraction from huge data sets, as fast and optimal as possible, but also by the value extraction from uncertain and inaccurate data, in an innovative manner using Big data analytics. At this point, the main challenge of the businesses that use Big data tools is to clearly define the scope and the necessary output of the business so that the real value can be gained. This article aims to explain the Big data concept, its various classifications criteria, architecture, as well as the impact in the world wide processes.

Subcortical laminar heterotopia in two sisters and their mother : MRI, clinical findings and pathogenesis

NARCIS (Netherlands)

van der Valk, PHM; Snoeck, [No Value; Meiners, LC; des Portes, [No Value; Chelly, J; Pinard, JM; Ippel, PF; van Nieuwenhuizen, O

MR imaging, clinical data and underlying pathogenesis of subcortical laminar heterotopia (SCLH), also known as band heterotopia, in two sisters and their mother are presented. On MR imaging a different degree of SCLH was found in all three affected family-members. The inversion recovery sequence was

Metazoan Scc4 homologs link sister chromatid cohesion to cell and axon migration guidance

NARCIS (Netherlands)

V.C. Seitan (Vlad); P.A. Banks (Peter); S. Laval (Steve); N.A. Majid (Nazia); D. Dorsett (Dale); A. Rana (Amer); J. Smith (Jeremy); A. Bateman (Alex); S. Krpic (Sanja); A. Hostert (Arnd); S.M. Rollins; H. Erdjument-Bromage (Hediye); P. Tempst (Paul); C.Y. Benard (Claire); S. Hekimi (Siegfried); S.F. Newbury (Sarah); T. Strachan (Tom)

2006-01-01

textabstractSaccharomyces cerevisiae Scc2 binds Scc4 to form an essential complex that loads cohesin onto chromosomes. The prevalence of Scc2 orthologs in eukaryotes emphasizes a conserved role in regulating sister chromatid cohesion, but homologs of Scc4 have not hitherto been identified outside

Concurrence of big data analytics and healthcare: A systematic review.

Science.gov (United States)

Mehta, Nishita; Pandit, Anil

2018-06-01

The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis. The articles on Big Data analytics in healthcare published in English language literature from January 2013 to January 2018 were considered. Descriptive articles and usability studies of Big Data analytics in healthcare and medicine were selected. Two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in healthcare; challenges and strategies to overcome the challenges in healthcare. A total of 58 articles were selected as per the inclusion criteria and analyzed. The analyses of these articles found that: (1) researchers lack consensus about the operational definition of Big Data in healthcare; (2) Big Data in healthcare comes from the internal sources within the hospitals or clinics as well external sources including government, laboratories, pharma companies, data aggregators, medical journals etc.; (3) natural language processing (NLP) is most widely used Big Data analytical technique for healthcare and most of the processing tools used for analytics are based on Hadoop; (4) Big Data analytics finds its application for clinical decision support; optimization of clinical operations and reduction of cost of care (5) major challenge in adoption of Big Data analytics is non-availability of evidence of its practical benefits in healthcare. This review study unveils that there is a paucity of information on evidence of real-world use of

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Science.gov (United States)

Huang, Xiuzhen; Jennings, Steven F; Bruce, Barry; Buchan, Alison; Cai, Liming; Chen, Pengyin; Cramer, Carole L; Guan, Weihua; Hilgert, Uwe Kk; Jiang, Hongmei; Li, Zenglu; McClure, Gail; McMullen, Donald F; Nanduri, Bindu; Perkins, Andy; Rekepalli, Bhanu; Salem, Saeed; Specker, Jennifer; Walker, Karl; Wunsch, Donald; Xiong, Donghai; Zhang, Shuzhong; Zhang, Yu; Zhao, Zhongming; Moore, Jason H

2015-01-01

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.

Big Egos in Big Science

DEFF Research Database (Denmark)

Andersen, Kristina Vaarst; Jeppesen, Jacob

In this paper we investigate the micro-mechanisms governing structural evolution and performance of scientific collaboration. Scientific discovery tends not to be lead by so called lone ?stars?, or big egos, but instead by collaboration among groups of researchers, from a multitude of institutions...

Challenges of Big Data Analysis.

Science.gov (United States)

Fan, Jianqing; Han, Fang; Liu, Han

2014-06-01

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

School Based Health Centers

Science.gov (United States)

Children's Aid Society, 2012

2012-01-01

School Based Health Centers (SBHC) are considered by experts as one of the most effective and efficient ways to provide preventive health care to children. Few programs are as successful in delivering health care to children at no cost to the patient, and where they are: in school. For many underserved children, The Children's Aid Society's…

Big data is not a monolith

CERN Document Server

Ekbia, Hamid R; Mattioli, Michael

2016-01-01

Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies. The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control throu...

Photoreactivation of ultraviolet light-induced sister chromatid exchanges in potorous cells

International Nuclear Information System (INIS)

Ishizaki, K.; Nikaido, O.; Takebe, H.

1980-01-01

Exposure to visible light after UV-irradiation showed a remarkable effect on UV-induced sister chromatid exchanges (SCEs). After 6-h exposure to visible light (3 x 10 5 J/m 2 ), two-thirds of the UV-induced SCEs were prevented, confirming Kato's findings. (Nature 249, 552-3, 1974) Exposure to visible light before UV irradiation had no effect. This effect of visible light on UV-induced CSEs was temperature dependent, suggesting the presence of enzymatic photoreactivation. (author)

Big universe, big data

DEFF Research Database (Denmark)

Kremer, Jan; Stensbo-Smidt, Kristoffer; Gieseke, Fabian Cristian

2017-01-01

, modern astronomy requires big data know-how, in particular it demands highly efficient machine learning and image analysis algorithms. But scalability is not the only challenge: Astronomy applications touch several current machine learning research questions, such as learning from biased data and dealing......, and highlight some recent methodological advancements in machine learning and image analysis triggered by astronomical applications....

Physical Therapists' Perceptions of School-Based Practices.

Science.gov (United States)

Holt, Sheryl L; Kuperstein, Janice; Effgen, Susan K

2015-01-01

Surveys have reported that most school-based physical therapists perceive ideal practices are not commonly implemented in their settings. Our aim was to obtain a more in-depth understanding of these perceptions through open-ended inquiry. Qualitative data were derived from voluntary open-ended responses provided upon completion of a survey regarding school-based physical therapy practice. Of the survey's 561 participants, 250 provided open-ended commentaries that were analyzed using interpretive phenomenology. Six qualitative themes emerged from the open-ended responses, including: In quest: Meeting students' school-based needs via physical therapy; Seeking relatedness: Finding working teams in the school system; Building understanding: Developing a voice/identity in the school context; Stretched beyond limits: Managing workloads; Networking: Coordinating services outside school to meet student needs; Defying definition: What does working in an educational model mean? School-based physical therapists seek to meet educationally relevant physical therapy needs of students, ages 3 to 21 years. Successes appear woven of a multitude of factors such as therapist expertise, team dynamics, and district supports.

Poker Player Behavior After Big Wins and Big Losses

OpenAIRE

Gary Smith; Michael Levere; Robert Kurtzman

2009-01-01

We find that experienced poker players typically change their style of play after winning or losing a big pot--most notably, playing less cautiously after a big loss, evidently hoping for lucky cards that will erase their loss. This finding is consistent with Kahneman and Tversky's (Kahneman, D., A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47(2) 263-292) break-even hypothesis and suggests that when investors incur a large loss, it might be time to take ...

Towards a Set Theoretical Approach to Big Data Analytics

DEFF Research Database (Denmark)

Mukkamala, Raghava Rao; Hussain, Abid; Vatrapu, Ravi

2014-01-01

Formal methods, models and tools for social big data analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by relational sociology. There are no other unified modeling approaches to social big data that integrate the conceptual, formal...... this technique to the data analysis of big social data collected from Facebook page of the fast fashion company, H&M....... and software realms. In this paper, we first present and discuss a theory and conceptual model of social data. Second, we outline a formal model based on set theory and discuss the semantics of the formal model with a real-world social data example from Facebook. Third, we briefly present and discuss...

Big Data and Chemical Education

Science.gov (United States)

Pence, Harry E.; Williams, Antony J.

2016-01-01

The amount of computerized information that organizations collect and process is growing so large that the term Big Data is commonly being used to describe the situation. Accordingly, Big Data is defined by a combination of the Volume, Variety, Velocity, and Veracity of the data being processed. Big Data tools are already having an impact in…

D-branes in a big bang/big crunch universe: Nappi-Witten gauged WZW model

Energy Technology Data Exchange (ETDEWEB)

Hikida, Yasuaki [School of Physics and BK-21 Physics Division, Seoul National University, Seoul 151-747 (Korea, Republic of); Nayak, Rashmi R. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' ' , Rome 00133 (Italy); Panigrahi, Kamal L. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' , Rome 00133 (Italy)

2005-05-01

We study D-branes in the Nappi-Witten model, which is a gauged WZW model based on (SL(2,R) x SU(2))/(U(1) x U(1)). The model describes a four dimensional space-time consisting of cosmological regions with big bang/big crunch singularities and static regions with closed time-like curves. The aim of this paper is to investigate by D-brane probes whether there are pathologies associated with the cosmological singularities and the closed time-like curves. We first classify D-branes in a group theoretical way, and then examine DBI actions for effective theories on the D-branes. In particular, we show that D-brane metric from the DBI action does not include singularities, and wave functions on the D-branes are well behaved even in the presence of closed time-like curves.

Extracting phylogenetic signal and accounting for bias in whole-genome data sets supports the Ctenophora as sister to remaining Metazoa.

Science.gov (United States)

Borowiec, Marek L; Lee, Ernest K; Chiu, Joanna C; Plachetzki, David C

2015-11-23

Understanding the phylogenetic relationships among major lineages of multicellular animals (the Metazoa) is a prerequisite for studying the evolution of complex traits such as nervous systems, muscle tissue, or sensory organs. Transcriptome-based phylogenies have dramatically improved our understanding of metazoan relationships in recent years, although several important questions remain. The branching order near the base of the tree, in particular the placement of the poriferan (sponges, phylum Porifera) and ctenophore (comb jellies, phylum Ctenophora) lineages is one outstanding issue. Recent analyses have suggested that the comb jellies are sister to all remaining metazoan phyla including sponges. This finding is surprising because it suggests that neurons and other complex traits, present in ctenophores and eumetazoans but absent in sponges or placozoans, either evolved twice in Metazoa or were independently, secondarily lost in the lineages leading to sponges and placozoans. To address the question of basal metazoan relationships we assembled a novel dataset comprised of 1080 orthologous loci derived from 36 publicly available genomes representing major lineages of animals. From this large dataset we procured an optimized set of partitions with high phylogenetic signal for resolving metazoan relationships. This optimized data set is amenable to the most appropriate and computationally intensive analyses using site-heterogeneous models of sequence evolution. We also employed several strategies to examine the potential for long-branch attraction to bias our inferences. Our analyses strongly support the Ctenophora as the sister lineage to other Metazoa. We find no support for the traditional view uniting the ctenophores and Cnidaria. Our findings are supported by Bayesian comparisons of topological hypotheses and we find no evidence that they are biased by long-branch attraction. Our study further clarifies relationships among early branching metazoan lineages

Comprehensive School Mental Health: An Integrated "School-Based Pathway to Care" Model for Canadian Secondary Schools

Science.gov (United States)

Wei, Yifeng; Kutcher, Stan; Szumilas, Magdalena

2011-01-01

Adolescence is a critical period for the promotion of mental health and the treatment of mental disorders. Schools are well-positioned to address adolescent mental health. This paper describes a school mental health model, "School-Based Pathway to Care," for Canadian secondary schools that links schools with primary care providers and…

Big data in Finnish financial services

OpenAIRE

Laurila, M. (Mikko)

2017-01-01

Abstract This thesis aims to explore the concept of big data, and create understanding of big data maturity in the Finnish financial services industry. The research questions of this thesis are “What kind of big data solutions are being implemented in the Finnish financial services sector?” and “Which factors impede faster implementation of big data solutions in the Finnish financial services sector?”. ...

Big data in fashion industry

Science.gov (United States)

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.

Nurse-Led School-Based Child Obesity Prevention

Science.gov (United States)

Tucker, Sharon; Lanningham-Foster, Lorraine M.

2015-01-01

School-based childhood obesity prevention programs have grown in response to reductions in child physical activity (PA), increased sedentariness, poor diet, and soaring child obesity rates. Multiple systematic reviews indicate school-based obesity prevention/treatment interventions are effective, yet few studies have examined the school nurse role…

Frequency of sister chromatid exchanges in lymphocyte cultures of human peripheral blood after the combined effect of γ-radiation and caffeine

International Nuclear Information System (INIS)

Nugis, V.Yu.; Pyatkin, E.K.

1986-01-01

Keeping of human peripheral blood lymphocytes, irradiated in vitro with 60 Co-γ-quanta at a dose of 3 Gy at G 0 phase, with caffeine of 16 and 160 μg/ml during cultivation with PHA had no appreciable influence on the fraquency of sister chromatid exchanges. A minor increase in the number of sister chromatid exchanges was only noted when nonirradiated and irradiated lymphocytes were cultured with 160 μg/ml caffeine

BIG DATA IN SUPPLY CHAIN MANAGEMENT: AN EXPLORATORY STUDY

Directory of Open Access Journals (Sweden)

Gheorghe MILITARU

2015-12-01

Full Text Available The objective of this paper is to set a framework for examining the conditions under which the big data can create long-term profitability through developing dynamic operations and digital supply networks in supply chain. We investigate the extent to which big data analytics has the power to change the competitive landscape of industries that could offer operational, strategic and competitive advantages. This paper is based upon a qualitative study of the convergence of predictive analytics and big data in the field of supply chain management. Our findings indicate a need for manufacturers to introduce analytics tools, real-time data, and more flexible production techniques to improve their productivity in line with the new business model. By gathering and analysing vast volumes of data, analytics tools help companies to resource allocation and capital spends more effectively based on risk assessment. Finally, implications and directions for future research are discussed.

What's in a Relationship? An Examination of Social Capital, Race and Class in Mentoring Relationships

Science.gov (United States)

Gaddis, S. Michael

2012-01-01

After 25 years of intense scrutiny, social capital remains an important yet highly debated concept in social science research. This research uses data from youth and mentors in several chapters of Big Brothers/Big Sisters to assess the importance of different mentoring relationship characteristics in creating positive outcomes among youths. The…

Teaching Sisters and Transnational Networks: Recruitment and Education Expansion in the Long Nineteenth Century

Science.gov (United States)

Raftery, Deirdre

2015-01-01

This article examines the management of the education enterprise of teaching Sisters, with reference to their transnational networking. The article suggests that orders of women religious were the first all-female transnational networks, engaged constantly in work that was characterised by "movement, ebb and circulation". The mobility of…

Big Data, Smart Homes and Ambient Assisted Living

Science.gov (United States)

Wass, S.

2014-01-01

Summary Objectives To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. Methods A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. Results The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. Conclusions The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today’s services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability. PMID:25123734

Big data, smart homes and ambient assisted living.

Science.gov (United States)

Vimarlund, V; Wass, S

2014-08-15

To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today's services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability.

Big game hunting practices, meanings, motivations and constraints: a survey of Oregon big game hunters

Science.gov (United States)

Suresh K. Shrestha; Robert C. Burns

2012-01-01

We conducted a self-administered mail survey in September 2009 with randomly selected Oregon hunters who had purchased big game hunting licenses/tags for the 2008 hunting season. Survey questions explored hunting practices, the meanings of and motivations for big game hunting, the constraints to big game hunting participation, and the effects of age, years of hunting...

School-Based Management and Effectiveness of Public Secondary ...

African Journals Online (AJOL)