BLUE OCEAN STRATEGY (BOS SEBAGAI PARADIGMA BARU MANAJEMEN PENDIDIKAN ISLAM

Directory of Open Access Journals (Sweden)

Ikhwan Fuad

2016-08-01

Full Text Available The focus of this article is to describe the Blue Ocean Strategy as a new paradigm of Islamic education management. the author seeks to elaborate on how the adoption of the Blue Ocean strategy of the business world to the world of education and answered the principles of what is accepted and rejected away from the theory. Adoption of blue ocean strategy is done by applying the universal principles are : among others reconstruct market boundaries, focus on the big picture rather than numbers, reach beyond existing demand, perform a series of strategies with appropriate, efforts to overcome organizational constraints and integrate execution into strategy. The principles of Blue Ocean Strategy Indicators that can be absorbed is an indicator that focuses gave excellent service and were not absorbed is a strong indicator of economic motivation. Generally, Blue Ocean Strategy quite well applied as a management paradigm of Islamic education.

Big is not always beautiful - small can be a short cut to blue oceans

DEFF Research Database (Denmark)

Kvistgaard, Peter

2007-01-01

Often it is claimed that big investments are the only way to success in tourism and the experience economy. Only by building some of the world's biggest hotels - like the ones in Dubai or Las Vegas where hotels with 3-4,000 rooms are not uncommon - success can be achieved. It is understandable...... that hotels have to be big in Las Vegas in order to secure a good return on investment. It is also understandable that they build big hotels when 37 million people came to visit and 22,000 conventions were held in Las Vegas in 2004 according to the official website of Las Vegas (www.lasvegasnevada.gov/factsstatistics/funfacts.htm)....

Effect of furosemide and dietary sodium on kidney and plasma big and small renin

International Nuclear Information System (INIS)

Iwao, H.; Michelakis, A.M.

1981-01-01

Renin was found in mouse plasma in high-molecular-weight forms (big big renin, big renin) and a low-molecular-weight form (small renin). They were measuerd by a radioimmunoassay procedure for the direct measurement of renin. In the kidney, 89% of total renin was small renin and the rest was big big and big renin. This distribution pattern of renins was not changed when the kideny tissue was homogenized in the presence of protease inhibitors. Low-sodium or high-sodium diets changed renal renin content, but not the distribution pattern of renins in the kidney. Acute stimulation of renin release by furosemide increased small renin but not big big and big renin in plasma. However, dietary sodium depletion for 2 weeks significantly increased big big, big, and small renin in plasma of mice with or without submaxillary glands. In contrast, high-sodium intake significantly decreased big big, big, and small renin in plasma of mice with or without submaxillary glands

Blue light-induced oxidative stress in live skin.

Science.gov (United States)

Nakashima, Yuya; Ohta, Shigeo; Wolf, Alexander M

2017-07-01

Skin damage from exposure to sunlight induces aging-like changes in appearance and is attributed to the ultraviolet (UV) component of light. Photosensitized production of reactive oxygen species (ROS) by UVA light is widely accepted to contribute to skin damage and carcinogenesis, but visible light is thought not to do so. Using mice expressing redox-sensitive GFP to detect ROS, blue light could produce oxidative stress in live skin. Blue light induced oxidative stress preferentially in mitochondria, but green, red, far red or infrared light did not. Blue light-induced oxidative stress was also detected in cultured human keratinocytes, but the per photon efficacy was only 25% of UVA in human keratinocyte mitochondria, compared to 68% of UVA in mouse skin. Skin autofluorescence was reduced by blue light, suggesting flavins are the photosensitizer. Exposing human skin to the blue light contained in sunlight depressed flavin autofluorescence, demonstrating that the visible component of sunlight has a physiologically significant effect on human skin. The ROS produced by blue light is probably superoxide, but not singlet oxygen. These results suggest that blue light contributes to skin aging similar to UVA. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of the mutagenic potential of hexavalent chromium in the duodenum of big blue® rats.

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Thompson, Chad M; Young, Robert R; Dinesdurage, Harshini; Suh, Mina; Harris, Mark A; Rohr, Annette C; Proctor, Deborah M

2017-09-01

A cancer bioassay on hexavalent chromium Cr(VI) in drinking water reported increased incidences of duodenal tumors in B6C3F1 mice at exposures of 30-180ppm, and oral cavity tumors in F344 rats at 180ppm. A subsequent transgenic rodent (TGR) in vivo mutation assay in Big Blue® TgF344 rats found that exposure to 180ppm Cr(VI) in drinking water for 28days did not increase cII transgene mutant frequency (MF) in the oral cavity (Thompson et al., 2015). Herein, we extend our analysis to the duodenum of these same TgF344 rats. At study termination, duodenum chromium levels were below either the limit of detection or quantification in control rats, but were 24.6±3.8μg/g in Cr(VI)-treated rats. The MF in control (23.2×10 -6 ) and Cr(VI)-treated rats (22.7×10 -6 ) were nearly identical. In contrast, the MF in the duodenum of rats exposed to 1-ethyl-1-nitrosourea for six days (study days 1, 2, 3, 12, 19, 26) increased 24-fold to 557×10 -6 . These findings indicate that mutagenicity is unlikely an early initiating event in Cr(VI)-induced intestinal carcinogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Relatively high rates of G:C → A:T transitions at CpG sites were observed in certain epithelial tissues including pancreas and submaxillary gland of adult big blue® mice.

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Prtenjaca, Anita; Tarnowski, Heather E; Marr, Alison M; Heney, Melanie A; Creamer, Laura; Sathiamoorthy, Sarmitha; Hill, Kathleen A

2014-01-01

With few exceptions, spontaneous mutation frequency and pattern are similar across tissue types and relatively constant in young to middle adulthood in wild type mice. Underrepresented in surveys of spontaneous mutations across murine tissues is the diversity of epithelial tissues. For the first time, spontaneous mutations were detected in pancreas and submaxillary gland and compared with kidney, lung, and male germ cells from five adult male Big Blue® mice. Mutation load was assessed quantitatively through measurement of mutant and mutation frequency and qualitatively through identification of mutations and characterization of recurrent mutations, multiple mutations, mutation pattern, and mutation spectrum. A total of 9.6 million plaque forming units were screened, 226 mutants were collected, and 196 independent mutations were identified. Four novel mutations were discovered. Spontaneous mutation frequency was low in pancreas and high in the submaxillary gland. The submaxillary gland had multiple recurrent mutations in each of the mice and one mutant had two independent mutations. Mutation patterns for epithelial tissues differed from that observed in male germ cells with a striking bias for G:C to A:T transitions at CpG sites. A comprehensive review of lacI spontaneous mutation patterns in young adult mice and rats identified additional examples of this mutational bias. An overarching observation about spontaneous mutation frequency in adult tissues of the mouse remains one of stability. A repeated observation in certain epithelial tissues is a higher rate of G:C to A:T transitions at CpG sites and the underlying mechanisms for this bias are not known. Copyright © 2013 Wiley Periodicals, Inc.

Heart tissue of harlequin (hq)/Big Blue mice has elevated reactive oxygen species without significant impact on the frequency and nature of point mutations in nuclear DNA

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Crabbe, Rory A. [Department of Biology, University of Western Ontario, London, Ontario, N6A 5B7 (Canada); Hill, Kathleen A., E-mail: khill22@uwo.ca [Department of Biology, University of Western Ontario, London, Ontario, N6A 5B7 (Canada)

2010-09-10

Age is a major risk factor for heart disease, and cardiac aging is characterized by elevated mitochondrial reactive oxygen species (ROS) with compromised mitochondrial and nuclear DNA integrity. To assess links between increased ROS levels and mutations, we examined in situ levels of ROS and cII mutation frequency, pattern and spectrum in the heart of harlequin (hq)/Big Blue mice. The hq mouse is a model of premature aging with mitochondrial dysfunction and increased risk of oxidative stress-induced heart disease with the means for in vivo mutation detection. The hq mutation produces a significant downregulation in the X-linked apoptosis-inducing factor gene (Aif) impairing both the antioxidant and oxidative phosphorylation functions of AIF. Brain and skin of hq disease mice have elevated frequencies of point mutations in nuclear DNA and histopathology characterized by cell loss. Reports of associated elevations in ROS in brain and skin have mixed results. Herein, heart in situ ROS levels were elevated in hq disease compared to AIF-proficient mice (p < 0.0001) yet, mutation frequency and pattern were similar in hq disease, hq carrier and AIF-proficient mice. Heart cII mutations were also assessed 15 days following an acute exposure to an exogenous ROS inducer (10 mg paraquat/kg). Acute paraquat exposure with a short mutant manifestation period was insufficient to elevate mutation frequency or alter mutation pattern in the post-mitotic heart tissue of AIF-proficient mice. Paraquat induction of ROS requires mitochondrial complex I and thus is likely compromised in hq mice. Results of this preliminary survey and the context of recent literature suggest that determining causal links between AIF deficiency and the premature aging phenotypes of specific tissues is better addressed with assay of mitochondrial ROS and large-scale changes in mitochondrial DNA in specific cell types.

Heart tissue of harlequin (hq)/Big Blue mice has elevated reactive oxygen species without significant impact on the frequency and nature of point mutations in nuclear DNA

International Nuclear Information System (INIS)

Crabbe, Rory A.; Hill, Kathleen A.

2010-01-01

Age is a major risk factor for heart disease, and cardiac aging is characterized by elevated mitochondrial reactive oxygen species (ROS) with compromised mitochondrial and nuclear DNA integrity. To assess links between increased ROS levels and mutations, we examined in situ levels of ROS and cII mutation frequency, pattern and spectrum in the heart of harlequin (hq)/Big Blue mice. The hq mouse is a model of premature aging with mitochondrial dysfunction and increased risk of oxidative stress-induced heart disease with the means for in vivo mutation detection. The hq mutation produces a significant downregulation in the X-linked apoptosis-inducing factor gene (Aif) impairing both the antioxidant and oxidative phosphorylation functions of AIF. Brain and skin of hq disease mice have elevated frequencies of point mutations in nuclear DNA and histopathology characterized by cell loss. Reports of associated elevations in ROS in brain and skin have mixed results. Herein, heart in situ ROS levels were elevated in hq disease compared to AIF-proficient mice (p < 0.0001) yet, mutation frequency and pattern were similar in hq disease, hq carrier and AIF-proficient mice. Heart cII mutations were also assessed 15 days following an acute exposure to an exogenous ROS inducer (10 mg paraquat/kg). Acute paraquat exposure with a short mutant manifestation period was insufficient to elevate mutation frequency or alter mutation pattern in the post-mitotic heart tissue of AIF-proficient mice. Paraquat induction of ROS requires mitochondrial complex I and thus is likely compromised in hq mice. Results of this preliminary survey and the context of recent literature suggest that determining causal links between AIF deficiency and the premature aging phenotypes of specific tissues is better addressed with assay of mitochondrial ROS and large-scale changes in mitochondrial DNA in specific cell types.

Biological effects of blocking blue and other visible light on the mouse retina.

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Narimatsu, Toshio; Ozawa, Yoko; Miyake, Seiji; Kubota, Shunsuke; Yuki, Kenya; Nagai, Norihiro; Tsubota, Kazuo

2014-08-01

To elucidate the biological effects of blocking fluorescent light on the retina using specific blocking materials. Seven- to 8-week-old BALB/c mice were divided into three groups and placed in one of the three boxes: one blocked ultraviolet and violet wavelengths of light (violet blockade), one blocked ultraviolet, violet, blue and some other visible wavelengths (blue-plus blockade), and one allowed most visible light to pass through (control). They were then exposed to a white fluorescent lamp for 1 h at 5.65E-05 mW/cm(2) /s. After treatment, the electroretinogram, retinal outer nuclear layer thickness and retinal outer segment length were measured. In addition, retinal apoptotic cells were quantified by TdT-mediated dUTP nick-end labelling assay and c-Fos messenger RNA, and protein levels were measured by real-time reverse-transcription polymerase chain reaction and immunoblot analyses, respectively. The blue-plus blockade group retained a significantly better electroretinogram response following light exposure than the control or violet blockade groups. The blue-plus blockade group also exhibited greater outer nuclear layer thickness and greater outer-segment length, and fewer apoptotic cells after light exposure than the other groups. The c-Fos messenger RNA and protein levels were substantially reduced in the blue-plus blockade group and reduced to a lesser extent in the violet blockade group. The blockade of blue plus additional visible wavelengths of light was most effective in protecting the retina from light-induced damage. The blockade of violet light alone was also effective in reducing intracellular molecular responses, but these effects were not sufficient for attenuating retinal degeneration. © 2013 Royal Australian and New Zealand College of Ophthalmologists.

ProSAAS-derived peptides are differentially processed and sorted in mouse brain and AtT-20 cells.

Directory of Open Access Journals (Sweden)

Jonathan H Wardman

Full Text Available ProSAAS is the precursor for some of the most abundant peptides found in mouse brain and other tissues, including peptides named SAAS, PEN, and LEN. Both SAAS and LEN are found in big and little forms due to differential processing. Initial processing of proSAAS is mediated by furin (and/or furin-like enzymes and carboxypeptidase D, while the smaller forms are generated by secretory granule prohormone convertases and carboxypeptidase E. In mouse hypothalamus, PEN and big LEN colocalize with neuropeptide Y. In the present study, little LEN and SAAS were detected in mouse hypothalamus but not in cell bodies of neuropeptide Y-expressing neurons. PEN and big LEN show substantial colocalization in hypothalamus, but big LEN and little LEN do not. An antiserum to SAAS that detects both big and little forms of this peptide did not show substantial colocalization with PEN or big LEN. To further study this, the AtT-20 cells mouse pituitary corticotrophic cell line was transfected with rat proSAAS and the distribution of peptides examined. As found in mouse hypothalamus, only some of the proSAAS-derived peptides colocalized with each other in AtT-20 cells. The two sites within proSAAS that are known to be efficiently cleaved by furin were altered by site-directed mutagenesis to convert the P4 Arg into Lys; this change converts the sequences from furin consensus sites into prohormone convertase consensus sites. Upon expression of the mutated form of proSAAS in AtT-20 cells, there was significantly more colocalization of proSAAS-derived peptides PEN and SAAS. Taken together, these results indicate that proSAAS is initially cleaved in the Golgi or trans-Golgi network by furin and/or furin-like enzymes and the resulting fragments are sorted into distinct vesicles and further processed by additional enzymes into the mature peptides.

Putting Together a Blue Sky: Laying the Foundation for Staff Evaluation

Science.gov (United States)

Searcy, Jeny

2012-01-01

Evaluation time can be like putting together a 5,000-piece jigsaw puzzle that is all sky--what, exactly, is the point? When all is said and done, one ends up with a big blue blob--nothing to show for all the effort. However, it doesn't have to be that way. Performance reviews can and should be an effective means of communication for both parties…

Effects of long-term use by big game and livestock in the Blue Mountains forest ecosystems.

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Larry L. Irwin; John G. Cook; Robert A. Riggs; Jon M. Skovlin

1994-01-01

The effects on eastside forest ecosystems from long-term grazing by large mammals are assessed, because long-term herbivory can reduce or increase ecosystem productivity. The assessment emphasizes elk and cattle in the Blue Mountains of northeast Oregon and southeast Washington. Histories of populations of large mammals and their effects in the Blue Mountains are...

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

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…

Constraints on pre-big-bang parameter space from CMBR anisotropies

International Nuclear Information System (INIS)

Bozza, V.; Gasperini, M.; Giovannini, M.; Veneziano, G.

2003-01-01

The so-called curvaton mechanism--a way to convert isocurvature perturbations into adiabatic ones--is investigated both analytically and numerically in a pre-big-bang scenario where the role of the curvaton is played by a sufficiently massive Kalb-Ramond axion of superstring theory. When combined with observations of CMBR anisotropies at large and moderate angular scales, the present analysis allows us to constrain quite considerably the parameter space of the model: in particular, the initial displacement of the axion from the minimum of its potential and the rate of evolution of the compactification volume during pre-big-bang inflation. The combination of theoretical and experimental constraints favors a slightly blue spectrum of scalar perturbations, and/or a value of the string scale in the vicinity of the SUSY GUT scale

Constraints on pre-big bang parameter space from CMBR anisotropies

CERN Document Server

Bozza, Valerio; Giovannini, Massimo; Veneziano, Gabriele

2003-01-01

The so-called curvaton mechanism --a way to convert isocurvature perturbations into adiabatic ones-- is investigated both analytically and numerically in a pre-big bang scenario where the role of the curvaton is played by a sufficiently massive Kalb--Ramond axion of superstring theory. When combined with observations of CMBR anisotropies at large and moderate angular scales, the present analysis allows us to constrain quite considerably the parameter space of the model: in particular, the initial displacement of the axion from the minimum of its potential and the rate of evolution of the compactification volume during pre-big bang inflation. The combination of theoretical and experimental constraints favours a slightly blue spectrum of scalar perturbations, and/or a value of the string scale in the vicinity of the SUSY-GUT scale.

Gene expression changes induced by the tumorigenic pyrrolizidine alkaloid riddelliine in liver of Big Blue rats

Science.gov (United States)

Mei, Nan; Guo, Lei; Liu, Ruqing; Fuscoe, James C; Chen, Tao

2007-01-01

Background Pyrrolizidine alkaloids (PAs) are probably the most common plant constituents that poison livestock, wildlife, and humans worldwide. Riddelliine is isolated from plants grown in the western United States and is a prototype of genotoxic PAs. Riddelliine was used to investigate the genotoxic effects of PAs via analysis of gene expression in the target tissue of rats in this study. Previously we observed that the mutant frequency in the liver of rats gavaged with riddelliine was 3-fold higher than that in the control group. Molecular analysis of the mutants indicated that there was a statistically significant difference between the mutational spectra from riddelliine-treated and control rats. Results Riddelliine-induced gene expression profiles in livers of Big Blue transgenic rats were determined. The female rats were gavaged with riddelliine at a dose of 1 mg/kg body weight 5 days a week for 12 weeks. Rat whole genome microarray was used to perform genome-wide gene expression studies. When a cutoff value of a two-fold change and a P-value less than 0.01 were used as gene selection criteria, 919 genes were identified as differentially expressed in riddelliine-treated rats compared to the control animals. By analysis with the Ingenuity Pathway Analysis Network, we found that these significantly changed genes were mainly involved in cancer, cell death, tissue development, cellular movement, tissue morphology, cell-to-cell signaling and interaction, and cellular growth and proliferation. We further analyzed the genes involved in metabolism, injury of endothelial cells, liver abnormalities, and cancer development in detail. Conclusion The alterations in gene expression were directly related to the pathological outcomes reported previously. These results provided further insight into the mechanisms involved in toxicity and carcinogenesis after exposure to riddelliine, and permitted us to investigate the interaction of gene products inside the signaling networks

Big Bear Exploration Ltd. 1998 annual report

International Nuclear Information System (INIS)

1999-01-01

During the first quarter of 1998 Big Bear completed a purchase of additional assets in the Rainbow Lake area of Alberta in which light oil purchase was financed with new equity and bank debt. The business plan was to immediately exploit these light oil assets, the result of which would be increased reserves, production and cash flow. Although drilling results in the first quarter on the Rainbow Lake properties was mixed, oil prices started to free fall and drilling costs were much higher than expected. As a result, the company completed a reduced program which resulted in less incremental loss and cash flow than it budgeted for. On April 29, 1998, Big Bear entered into agreement with Belco Oil and Gas Corp. and Moan Investments Ltd. for the issuance of convertible preferred shares at a gross value of $15,750,000, which shares were eventually converted at 70 cents per share to common equity. As a result of the continued plunge in oil prices, the lending value of the company's assets continued to fall, requiring it to take action in order to meet its financial commitments. Late in the third quarter Big Bear issued equity for proceeds of $11,032,000 which further reduced the company's debt. Although the company has been extremely active in identifying and pursuing acquisition opportunities, it became evident that Belco Oil and Gas Corp. and Big Bear did nor share common criteria for acquisitions, which resulted in the restructuring of their relationship in the fourth quarter. With the future of oil prices in question, Big Bear decided that it would change its focus to that of natural gas and would refocus ts efforts to acquire natural gas assets to fuel its growth. The purchase of Blue Range put Big Bear in a difficult position in terms of the latter's growth. In summary, what started as a difficult year ended in disappointment

Forming mechanism and avoiding measures of blue-ring on electronic beam welding sample after water corrosion

International Nuclear Information System (INIS)

Ren Defang; Luo Xiandian; Tong Shenxiu; Guo Xulin; Peng Haiqing

2001-01-01

After water corrosion in compliance with ASTM G2, the blue ring appears on the nuclear fuel rod samples of AFA 2G welded by using a Big Chamber Electron Beam Welder made in Russia. The characteristics, appearance, chemical composition, microstructure of b lue ring a nd some condition test are described. The mechanism of forming blue ring may be depicted as following: welding metal vapor and the splash produced by secondary and scatter electrons on metal clamp and gun body deposit in the area between HAZ and substrate because of the water cooling down effects on the clamp; these deposits, after water corrosion, appears as blue ring on the fuel rod surface. Avoiding measure is that the side of the clamp closing to weld seal is chamfered, while making the welding chamber cleaner

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…

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."

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.

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

Inhibitory effect of blue light emitting diode on migration and invasion of cancer cells.

Science.gov (United States)

Oh, Phil-Sun; Kim, Hyun-Soo; Kim, Eun-Mi; Hwang, Hyosook; Ryu, Hyang Hwa; Lim, SeokTae; Sohn, Myung-Hee; Jeong, Hwan-Jeong

2017-12-01

The aim of this study was to determine the effects and molecular mechanism of blue light emitting diode (LED) in tumor cells. A migration and invasion assay for the metastatic behavior of mouse colon cancer CT-26 and human fibrosarcoma HT-1080 cells was performed. Cancer cell migration-related proteins were identified by obtaining a 2-dimensional gel electrophoresis (2-DE) in total cellular protein profile of blue LED-irradiated cancer cells, followed by matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) analysis of proteins. Protein levels were examined by immunoblotting. Irradiation with blue LED inhibited CT-26 and HT-1080 cell migration and invasion. The anti-metastatic effects of blue LED irradiation were associated with inhibition of matrix metalloproteinase (MMP)-2 and MMP-9 expression. P38 MAPK phosphorylation was increased in blue LED-irradiated CT-26 and HT-1080 cells, but was inhibited after pretreatment with SB203580, a specific inhibitor of p38 MAPK. Inhibition of p38 MAPK phosphorylation by SB203580 treatment increased number of migratory cancer cells in CT-26 and HT-1080 cells, indicating that blue LED irradiation inhibited cancer cell migration via phosphorylation of p38 MAPK. Additionally blue LED irradiation of mice injected with CT-26 cells expressing luciferase decreased early stage lung metastasis compared to untreated control mice. These results indicate that blue LED irradiation inhibits cancer cell migration and invasion in vitro and in vivo. © 2017 Wiley Periodicals, Inc.

Sequencing analysis of mutations induced by N-ethyl-N-nitrosourea at different sampling times in mouse bone marrow.

Science.gov (United States)

Wang, Jianyong; Chen, Tao

2010-03-01

In our previous study (Wang et al., 2004, Toxicol. Sci. 82: 124-128), we observed that the cII gene mutant frequency (MF) in the bone marrow of Big Blue mice showed significant increase as early as day 1, reached the maximum at day 3 and then decreased to a plateau by day 15 after a single dose of carcinogen N-ethyl-N-nitrosourea (ENU) treatment, which is different from the longer mutation manifestation time and the constancy of MFs after reaching their maximum in some other tissues. To determine the mechanism underlying the quick increase in MF and the peak formation in the mutant manifestation, we examined the mutation frequencies and spectra of the ENU-induced mutants collected from different sampling times in this study. The cII mutants from days 1, 3 and 120 after ENU treatment were randomly selected from different animals. The mutation frequencies were 33, 217, 305 and 144 x 10(-6) for control, days 1, 3, and 120, respectively. The mutation spectra at days 1 and 3 were significantly different from that at day 120. Considering that stem cells are responsible for the ultimate MF plateau (day 120) and transit cells are accountable for the earlier MF induction (days 1 or 3) in mouse bone marrow, we conclude that transit cells are much more sensitive to mutation induction than stem cells in mouse bone marrow, which resulted in the specific mutation manifestation induced by ENU.

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...

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…

2,6-Dithiopurine, a nucleophilic scavenger, protects against mutagenesis in mouse skin treated in vivo with 2-(chloroethyl) ethyl sulfide, a mustard gas analog

Energy Technology Data Exchange (ETDEWEB)

Boulware, Stephen [Division of Pharmacy and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Pediatric Research Institute, 1400 Barbara Jordan Blvd., Austin, TX 78723 (United States); Fields, Tammy; McIvor, Elizabeth; Powell, K. Leslie; Abel, Erika L. [Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Science Park, Smithville, TX 78957 (United States); Vasquez, Karen M. [Division of Pharmacy and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Pediatric Research Institute, 1400 Barbara Jordan Blvd., Austin, TX 78723 (United States); MacLeod, Michael C., E-mail: mcmacleod@mdanderson.org [Department of Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Science Park, Smithville, TX 78957 (United States)

2012-09-01

Sulfur mustard [bis(2-chloroethyl)sulfide, SM] is a well-known DNA-damaging agent that has been used in chemical warfare since World War I, and is a weapon that could potentially be used in a terrorist attack on a civilian population. Dermal exposure to high concentrations of SM produces severe, long-lasting burns. Topical exposure to high concentrations of 2-(chloroethyl) ethyl sulfide (CEES), a monofunctional analog of SM, also produces severe skin lesions in mice. Utilizing a genetically engineered mouse strain, Big Blue, that allows measurement of mutation frequencies in mouse tissues, we now show that topical treatment with much lower concentrations of CEES induces significant dose- and time-dependent increases in mutation frequency in mouse skin; the mutagenic exposures produce minimal toxicity as determined by standard histopathology and immunohistochemical analysis for cytokeratin 6 and the DNA-damage induced phosphorylation of histone H2AX (γ-H2AX). We attempted to develop a therapeutic that would inhibit the CEES-induced increase in mutation frequency in the skin. We observe that multi-dose, topical treatment with 2,6-dithiopurine (DTP), a known chemical scavenger of CEES, beginning 1 h post-exposure to CEES, completely abolishes the CEES-induced increase in mutation frequency. These findings suggest the possibility that DTP, previously shown to be non-toxic in mice, may be useful as a therapeutic agent in accidental or malicious human exposures to SM. -- Highlights: ► 200 mM 2-(chloroethyl) ethyl sulfide (CEES) induces mutations in mouse skin. ► This dose of CEES is not overtly toxic, as assayed by histopathology. ► 2,6-Dithiopurine (DTP), applied after CEES-treatment, abolishes CEES-mutagenesis. ► This supports the idea that sulfur mustards exhibit long biological half-lives.

2,6-Dithiopurine, a nucleophilic scavenger, protects against mutagenesis in mouse skin treated in vivo with 2-(chloroethyl) ethyl sulfide, a mustard gas analog

International Nuclear Information System (INIS)

Boulware, Stephen; Fields, Tammy; McIvor, Elizabeth; Powell, K. Leslie; Abel, Erika L.; Vasquez, Karen M.; MacLeod, Michael C.

2012-01-01

Sulfur mustard [bis(2-chloroethyl)sulfide, SM] is a well-known DNA-damaging agent that has been used in chemical warfare since World War I, and is a weapon that could potentially be used in a terrorist attack on a civilian population. Dermal exposure to high concentrations of SM produces severe, long-lasting burns. Topical exposure to high concentrations of 2-(chloroethyl) ethyl sulfide (CEES), a monofunctional analog of SM, also produces severe skin lesions in mice. Utilizing a genetically engineered mouse strain, Big Blue, that allows measurement of mutation frequencies in mouse tissues, we now show that topical treatment with much lower concentrations of CEES induces significant dose- and time-dependent increases in mutation frequency in mouse skin; the mutagenic exposures produce minimal toxicity as determined by standard histopathology and immunohistochemical analysis for cytokeratin 6 and the DNA-damage induced phosphorylation of histone H2AX (γ-H2AX). We attempted to develop a therapeutic that would inhibit the CEES-induced increase in mutation frequency in the skin. We observe that multi-dose, topical treatment with 2,6-dithiopurine (DTP), a known chemical scavenger of CEES, beginning 1 h post-exposure to CEES, completely abolishes the CEES-induced increase in mutation frequency. These findings suggest the possibility that DTP, previously shown to be non-toxic in mice, may be useful as a therapeutic agent in accidental or malicious human exposures to SM. -- Highlights: ► 200 mM 2-(chloroethyl) ethyl sulfide (CEES) induces mutations in mouse skin. ► This dose of CEES is not overtly toxic, as assayed by histopathology. ► 2,6-Dithiopurine (DTP), applied after CEES-treatment, abolishes CEES-mutagenesis. ► This supports the idea that sulfur mustards exhibit long biological half-lives.

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

Regeneration in United States Department of Agriculture Forest Service mixed conifer partial cuttings in the Blue Mountains of Oregon and Washington.

Science.gov (United States)

K.W. Seidel; S. Conrade. Head

1983-01-01

A survey in the Blue Mountains of north-eastern Oregon and southeastern Washington showed that, on the average, partial cuts in the grand fir/big huckleberry community were well stocked with a mixture of advance, natural post-harvest, and planted reproduction of a number of species. Partial cuts in the mixed conifer/pinegrass community had considerably fewer seedlings...

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.

Near-infrared fluorescence glucose sensing based on glucose/galactose-binding protein coupled to 651-Blue Oxazine

Energy Technology Data Exchange (ETDEWEB)

Khan, Faaizah; Pickup, John C., E-mail: john.pickup@kcl.ac.uk

2013-08-30

Highlights: •We showed that the NIR fluorophore, 651-Blue Oxazine, is solvatochromic (polarity sensitive). •Blue Oxazine was covalently attached to mutants of glucose/galactose-binding protein (GBP). •Fluorescence intensity of GBP-Blue Oxazine increased with addition of glucose. •Fluorescence from bead-immobilised GBP-Blue Oxazine was detectable through skin in vitro. •This shows proof-of-concept for non-invasive glucose sensing using GBP-Blue Oxazine. -- Abstract: Near-infrared (NIR) fluorescent dyes that are environmentally sensitive or solvatochromic are useful tools for protein labelling in in vivo biosensor applications such as glucose monitoring in diabetes since their spectral properties are mostly independent of tissue autofluorescence and light scattering, and they offer potential for non-invasive analyte sensing. We showed that the fluorophore 651-Blue Oxazine is polarity-sensitive, with a marked reduction in NIR fluorescence on increasing solvent polarity. Mutants of glucose/galactose-binding protein (GBP) used as the glucose receptor were site-specifically and covalently labelled with Blue Oxazine using click chemistry. Mutants H152C/A213R and H152C/A213R/L238S showed fluorescence increases of 15% and 21% on addition of saturating glucose concentrations and binding constants of 6 and 25 mM respectively. Fluorescence responses to glucose were preserved when GBP-Blue Oxazine was immobilised to agarose beads, and the beads were excited by NIR light through a mouse skin preparation studied in vitro. We conclude GBP-Blue Oxazine shows proof-of-concept as a non-invasive continuous glucose sensing system.

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...

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

'Blue bubble' technique: an ab interno approach for Descemet separation in deep anterior lamellar keratoplasty using trypan blue stained viscoelastic device.

Science.gov (United States)

Livny, Eitan; Bahar, Irit; Hammel, Naama; Nahum, Yoav

2018-04-01

In this study, we examined a novel variant of 'big-bubble' deep anterior lamellar keratoplasty using trypan-blue-stained viscoelastic device for the creation of a pre-descemetic bubble. Ten corneoscleral rims were mounted on an artificial anterior chamber (AC). The AC was filled with air through a limbal paracentesis. A Melles' triangulated spatula was inserted through the paracentesis, with its tip penetrating the AC, was then slightly retracted and pushed into the deep stroma above the roof of the paracentesis. A mixture of trypan blue and viscoelastic device (Healon, Abbott Medical Optics, Abbott Park, Illinois) was injected into this intra-stromal pocket using a 27-G cannula to create a pre-descemetic separation bubble. Bubble type and visualization of dyed viscoelastic device were noted. The method was later employed in three cases. In all 10 corneoscleral rims, the technique successfully created a visible pre-descemetic (type 1) bubble that could be expanded up to the predicted diameter of trephination. Subsequent trephination and the removal of corneal stroma were uneventful. In two out of four clinical cases, a type 1 bubble was created, while in two others, visco-dissection failed and dyed viscoelastic was seen in the AC. The presented technique holds promise of being a relatively easy to perform, predictable and well-controlled alternative for achieving a type 1 bubble during deep anterior lamellar keratoplasty surgery. The trypan-blue-stained viscoelastic device facilitates proper visualization and control of the separation bubble and assists in identifying the penetrance to the separation bubble prior to removal of the stromal cap. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

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...

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.

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...

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.

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.

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).

String theory and pre-big bang cosmology

Science.gov (United States)

Gasperini, M.; Veneziano, G.

2016-09-01

In string theory, the traditional picture of a Universe that emerges from the inflation of a very small and highly curved space-time patch is a possibility, not a necessity: quite different initial conditions are possible, and not necessarily unlikely. In particular, the duality symmetries of string theory suggest scenarios in which the Universe starts inflating from an initial state characterized by very small curvature and interactions. Such a state, being gravitationally unstable, will evolve towards higher curvature and coupling, until string-size effects and loop corrections make the Universe "bounce" into a standard, decreasing-curvature regime. In such a context, the hot big bang of conventional cosmology is replaced by a "hot big bounce" in which the bouncing and heating mechanisms originate from the quantum production of particles in the high-curvature, large-coupling pre-bounce phase. Here we briefly summarize the main features of this inflationary scenario, proposed a quarter century ago. In its simplest version (where it represents an alternative and not a complement to standard slow-roll inflation) it can produce a viable spectrum of density perturbations, together with a tensor component characterized by a "blue" spectral index with a peak in the GHz frequency range. That means, phenomenologically, a very small contribution to a primordial B-mode in the CMB polarization, and the possibility of a large enough stochastic background of gravitational waves to be measurable by present or future gravitational wave detectors.

Tracing the origin of 'blue Weimaraner' dogs by molecular genetics.

Science.gov (United States)

Gerding, W M; Schreiber, S; Dekomien, G; Epplen, J T

2011-04-01

Weimaraner dogs are defined by light brown coat colour termed grey including several shadings ranging from silver and deer to mouse grey. In contrast, the so-called blue Weimaraners (BW) with lightened black-pigmented coat have been proposed to represent spontaneous revertants in the Weimaraner breed. In order to investigate the genetic determinants of the characteristic grey coat colour versus those of BW, known variation in coat colour genes including TYRP1 and MLPH were analysed in a number of grey and blue dogs. Variations at the B locus cause grey coat colour in Weimaraners via two non-functional TYRP1 copies (bb) including the b(s), b(d) and b(c) alleles. In all BW, at least one functional TYRP1 allele (Bb or BB genotype) was identified. Defined microsatellite alleles in TYRP1 intron 4 are linked to this functional B allele in BW. These alleles were also detected in various other dog breeds, but not in grey Weimaraners. The combination of a dominant trait for blue versus grey together with a specific TYRP1 haplotype in BW suggests that blue coat colour is not the result of spontaneous (back-) mutation in grey Weimaraners. This inference is even emphasized by the presence of a unique Y-chomosomal haplotype in a male offspring of the supposed ancestor of the BW population which - according to pedigree information - carries a copy of the original Y chromosome. Thus, molecular genetic analyses of coat colours combined with Y-chromosomal haplotypes allow tracing the origin of atypical dogs in respective canine populations. © 2010 Blackwell Verlag GmbH.

High-luminosity blue and blue-green gallium nitride light-emitting diodes.

Science.gov (United States)

Morkoç, H; Mohammad, S N

1995-01-06

Compact and efficient sources of blue light for full color display applications and lighting eluded and tantalized researchers for many years. Semiconductor light sources are attractive owing to their reliability and amenability to mass manufacture. However, large band gaps are required to achieve blue color. A class of compound semiconductors formed by metal nitrides, GaN and its allied compounds AIGaN and InGaN, exhibits properties well suited for not only blue and blue-green emitters, but also for ultraviolet emitters and detectors. What thwarted engineers and scientists from fabricating useful devices from these materials in the past was the poor quality of material and lack of p-type doping. Both of these obstacles have recently been overcome to the point where highluminosity blue and blue-green light-emitting diodes are now available in the marketplace.

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...

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.

A mild mutator phenotype arises in a mouse model for malignancies associated with neurofibromatosis type 1

International Nuclear Information System (INIS)

Garza, Rene; Hudson, Robert A.; McMahan, C. Alex; Walter, Christi A.; Vogel, Kristine S.

2007-01-01

Defects in genes that control DNA repair, proliferation, and apoptosis can increase genomic instability, and thus promote malignant progression. Although most tumors that arise in humans with neurofibromatosis type 1 (NF1) are benign, these individuals are at increased risk for malignant peripheral nerve sheath tumors (MPNST). To characterize additional mutations required for the development of MPNST from benign plexiform neurofibromas, we generated a mouse model for these tumors by combining targeted null mutations in Nf1 and p53, in cis. CisNf1+/-; p53+/- mice spontaneously develop PNST, and these tumors exhibit loss-of-heterozygosity at both the Nf1 and p53 loci. Because p53 has well-characterized roles in the DNA damage response, DNA repair, and apoptosis, and because DNA repair genes have been proposed to act as modifiers in NF1, we used the cisNf1+/-; p53+/- mice to determine whether a mutator phenotype arises in NF1-associated malignancies. To quantitate spontaneous mutant frequencies (MF), we crossed the Big Blue mouse, which harbors a lacI transgene, to the cisNf1+/-; p53+/- mice, and isolated genomic DNA from both tumor and normal tissues in compound heterozygotes and wild-type siblings. Many of the PNST exhibited increased mutant frequencies (MF = 4.70) when compared to normal peripheral nerve and brain (MF = 2.09); mutations occurred throughout the entire lacI gene, and included base substitutions, insertions, and deletions. Moreover, the brains, spleens, and livers of these cisNf1+/-; p53+/- animals exhibited increased mutant frequencies when compared to tissues from wild-type littermates. We conclude that a mild mutator phenotype arises in the tumors and tissues of cisNf1+/-; p53+/- mice, and propose that genomic instability influences NF1 tumor progression and disease severity

Blue ocean strategy.

Science.gov (United States)

Kim, W Chan; Mauborgne, Renée

2004-10-01

Despite a long-term decline in the circus industry, Cirque du Soleil profitably increased revenue 22-fold over the last ten years by reinventing the circus. Rather than competing within the confines of the existing industry or trying to steal customers from rivals, Cirque developed uncontested market space that made the competition irrelevant. Cirque created what the authors call a blue ocean, a previously unknown market space. In blue oceans, demand is created rather than fought over. There is ample opportunity for growth that is both profitable and rapid. In red oceans--that is, in all the industries already existing--companies compete by grabbing for a greater share of limited demand. As the market space gets more crowded, prospects for profits and growth decline. Products turn into commodities, and increasing competition turns the water bloody. There are two ways to create blue oceans. One is to launch completely new industries, as eBay did with online auctions. But it's much more common for a blue ocean to be created from within a red ocean when a company expands the boundaries of an existing industry. In studying more than 150 blue ocean creations in over 30 industries, the authors observed that the traditional units of strategic analysis--company and industry--are of limited use in explaining how and why blue oceans are created. The most appropriate unit of analysis is the strategic move, the set of managerial actions and decisions involved in making a major market-creating business offering. Creating blue oceans builds brands. So powerful is blue ocean strategy, in fact, that a blue ocean strategic move can create brand equity that lasts for decades.

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.

Electronic properties of blue phosphorene/graphene and blue phosphorene/graphene-like gallium nitride heterostructures.

Science.gov (United States)

Sun, Minglei; Chou, Jyh-Pin; Yu, Jin; Tang, Wencheng

2017-07-05

Blue phosphorene (BlueP) is a graphene-like phosphorus nanosheet which was synthesized very recently for the first time [Nano Lett., 2016, 16, 4903-4908]. The combination of electronic properties of two different two-dimensional materials in an ultrathin van der Waals (vdW) vertical heterostructure has been proved to be an effective approach to the design of novel electronic and optoelectronic devices. Therefore, we used density functional theory to investigate the structural and electronic properties of two BlueP-based heterostructures - BlueP/graphene (BlueP/G) and BlueP/graphene-like gallium nitride (BlueP/g-GaN). Our results showed that the semiconducting nature of BlueP and the Dirac cone of G are well preserved in the BlueP/G vdW heterostructure. Moreover, by applying a perpendicular electric field, it is possible to tune the position of the Dirac cone of G with respect to the band edge of BlueP, resulting in the ability to control the Schottky barrier height. For the BlueP/g-GaN vdW heterostructure, BlueP forms an interface with g-GaN with a type-II band alignment, which is a promising feature for unipolar electronic device applications. Furthermore, we discovered that both G and g-GaN can be used as an active layer for BlueP to facilitate charge injection and enhance the device performance.

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.

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,

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

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

Dermatoscopy of blue vitiligo.

Science.gov (United States)

Chandrashekar, L

2009-07-01

Blue vitiligo is a distinct variant of vitiligo characterized by a blue-grey appearance of the skin, which corresponds histologically with absence of epidermal melanocytes and presence of numerous dermal melanophages. A 23-year-old woman of Indian origin with Fitzpatrick skin type V presented with a 1-month history of normoaesthetic depigmented macules over the right forearm, dorsa of the hands and right areola. The macule over the right forearm had a bluish tinge. A clinical diagnosis of vitiligo vulgaris with blue vitiligo was made. Dermatoscopy of the interface between the blue macule and the hypopigmented macule revealed a linear depigmented macule in the centre with multiple blue dots and absence of epidermal melanin on the side of the blue macule, and reticular pigmentation with a few depigmented macules and scattered blue dots over the side of the hypopigmented macule. Blue vitiligo was described previously in a patient seropositive for human immunodeficiency virus, and believed to represent postinflammatory hyperpigmentation in areas bordering the vitiliginous patches as a result of psoralen ultraviolet A treatment. This case is unusual because of its rarity and the description of the associated dermatoscopical findings.

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...

Use and selection of bridges as day roosts by Rafinesque's Big Eared Bats.

Energy Technology Data Exchange (ETDEWEB)

Bennett, Frances, M.; Loeb, Susan, C.; Bunch, Mary, S.; Bowerman, William, W.

2008-03-01

ABSTRACT.—Rafinesque’s big-eared bats (Corynorhinus rafinesquii) use bridges as day roosts in parts of their range, but information on bridge use across their range is lacking. From May to Aug. 2002 we surveyed 1129 bridges (12.5%) within all 46 counties of South Carolina to determine use and selection of bridges as day roosts by big-eared bats and to document their distribution across the state. During summer 2003, we visited 235 bridges in previously occupied areas of the state to evaluate short-term fidelity to bridge roosts. We found colonies and solitary big-eared bats beneath 38 bridges in 2002 and 54 bridges in 2003. Construction type and size of bridges strongly influenced use in both years; bats selected large, concrete girder bridges and avoided flat-bottomed slab bridges. The majority of occupied bridges (94.7%) were in the Upper and Lower Coastal Plains, but a few bridges (5.3%) were located in the Piedmont. Rafinesque’s big-eared bats were absent beneath bridges in the Blue Ridge Mountains. We established new records of occurrence for 10 counties. In the Coastal Plains, big-eared bats exhibited a high degree of short-term fidelity to roosts in highway bridges. For bridges that were occupied at least once, mean frequency of use was 65.9%. Probability of finding bats under a bridge ranged from 0.46 to 0.73 depending on whether the bridge was occupied in the previous year. Thus, bridges should be inspected three to five times in a given year to determine whether they are being used. Regional bridge roost surveys may be a good method for determining the distribution of C. rafinesquii, particularly in the Coastal Plains, and protection of suitable bridges may be a viable conservation strategy where natural roost sites are limited.

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)...

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.)

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

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.

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.

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...

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....

Origin of colour stability in blue/orange/blue stacked phosphorescent white organic light-emitting diodes

International Nuclear Information System (INIS)

Kim, Sung Hyun; Jang, Jyongsik; Yook, Kyoung Soo; Lee, Jun Yeob

2009-01-01

The origin of colour stability in phosphorescent white organic light-emitting diodes (PHWOLEDs) with a blue/orange/blue stacked emitting structure was studied by monitoring the change in a recombination zone. A balanced recombination zone shift between the blue and the orange light-emitting layers was found to be responsible for the colour stability in the blue/orange/blue stacked PHWOLEDs.

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 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.

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

Corneal edema and permanent blue discoloration of a silicone intraocular lens by methylene blue.

Science.gov (United States)

Stevens, Scott; Werner, Liliana; Mamalis, Nick

2007-01-01

To report a silicone intraocular lens (IOL) stained blue by inadvertent intraoperative use of methylene blue instead of trypan blue and the results of experimental staining of various lens materials with different concentrations of the same dye. A "blue dye" was used to enhance visualization during capsulorhexis in a patient undergoing phacoemulsification with implantation of a three-piece silicone lens. Postoperatively, the patient presented with corneal edema and a discolored IOL. Various IOL materials were experimentally stained using methylene blue. Sixteen lenses (4 silicone, 4 hydrophobic acrylic, 4 hydrophilic acrylic, and 4 polymethylmethacrylate) were immersed in 0.5 mL of methylene blue at concentrations of 1%, 0.1%, 0.01%, and 0.001%. These lenses were grossly and microscopically evaluated for discoloration 6 and 24 hours after immersion. The corneal edema resolved within 1 month after the initial surgical procedure. After explantation, gross and microscopic analyses of the explanted silicone lens revealed that its surface and internal substance had been permanently stained blue. In the experimental study, all of the lenses except the polymethylmethacrylate lenses were permanently stained by methylene blue. The hydrophilic acrylic lenses showed the most intense blue staining in all dye concentrations. This is the first clinicopathological report of IOL discoloration due to intraocular use of methylene blue. This and other tissue dyes may be commonly found among surgical supplies in the operating room and due diligence is necessary to avoid mistaking these dyes for those commonly used during ocular surgery.

Lidar quantification of bank erosion in Blue Earth County, Minnesota.

Science.gov (United States)

Kessler, A C; Gupta, S C; Dolliver, H A S; Thoma, D P

2012-01-01

Sediment and phosphorus (P) transport from the Minnesota River Basin to Lake Pepin on the upper Mississippi River has garnered much attention in recent years. However, there is lack of data on the extent of sediment and P contributions from riverbanks vis-à-vis uplands and ravines. Using two light detection and ranging (lidar) data sets taken in 2005 and 2009, a study was undertaken to quantify sediment and associated P losses from riverbanks in Blue Earth County, Minnesota. Volume change in river valleys as a result of bank erosion amounted to 1.71 million m over 4 yr. Volume change closely followed the trend: the Blue Earth River > the Minnesota River at the county's northern edge > the Le Sueur River > the Maple River > the Watonwan River > the Big Cobb River > Perch Creek > Little Cobb River. Using fine sediment content (silt + clay) and bulk density of 37 bank samples representing three parent materials, we estimate bank erosion contributions of 48 to 79% of the measured total suspended solids at the mouth of the Blue Earth and the Le Sueur rivers. Corresponding soluble P and total P contributions ranged from 0.13 to 0.20% and 40 to 49%, respectively. Although tall banks (>3 m high) accounted for 33% of the total length and 63% of the total area, they accounted for 75% of the volume change in river valleys. We conclude that multitemporal lidar data sets are useful in estimating bank erosion and associated P contributions over large scales, and for riverbanks that are not readily accessible for conventional surveying equipment. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

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...

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 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...

Analysis of gene expression changes in relation to toxicity and tumorigenesis in the livers of Big Blue transgenic rats fed comfrey (Symphytum officinale).

Science.gov (United States)

Mei, Nan; Guo, Lei; Zhang, Lu; Shi, Leming; Sun, Yongming Andrew; Fung, Chris; Moland, Carrie L; Dial, Stacey L; Fuscoe, James C; Chen, Tao

2006-09-06

Comfrey is consumed by humans as a vegetable and a tea, and has been used as an herbal medicine for more than 2000 years. Comfrey, however, is hepatotoxic in livestock and humans and carcinogenic in experimental animals. Our previous study suggested that comfrey induces liver tumors by a genotoxic mechanism and that the pyrrolizidine alkaloids in the plant are responsible for mutation induction and tumor initiation in rat liver. In this study, we identified comfrey-induced gene expression profile in the livers of rats. Groups of 6 male transgenic Big Blue rats were fed a basal diet and a diet containing 8% comfrey roots, a dose that resulted in liver tumors in a previous carcinogenicity bioassay. The animals were treated for 12 weeks and sacrificed one day after the final treatment. We used a rat microarray containing 26,857 genes to perform genome-wide gene expression studies. Dietary comfrey resulted in marked changes in liver gene expression, as well as in significant decreases in the body weight and increases in liver mutant frequency. When a two-fold cutoff value and a P-value less than 0.01 were selected, 2,726 genes were identified as differentially expressed in comfrey-fed rats compared to control animals. Among these genes, there were 1,617 genes associated by Ingenuity Pathway Analysis with particular functions, and the differentially expressed genes in comfrey-fed rat livers were involved in metabolism, injury of endothelial cells, and liver injury and abnormalities, including liver fibrosis and cancer development. The gene expression profile provides us a better understanding of underlying mechanisms for comfrey-induced hepatic toxicity. Integration of gene expression changes with known pathological changes can be used to formulate a mechanistic scheme for comfrey-induced liver toxicity and tumorigenesis.

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...

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...

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

Blue-Green Algae

Science.gov (United States)

... that taking a specific blue-green algae product (Super Blue-Green Algae, Cell Tech, Klamath Falls, OR) ... system. Premenstrual syndrome (PMS). Depression. Digestion. Heart disease. Memory. Wound healing. Other conditions. More evidence is needed ...

Blue gods, blue oil, and blue people.

Science.gov (United States)

Fairbanks, V F

1994-09-01

Studies of the composition of coal tar, which began in Prussia in 1834, profoundly affected the economies of Germany, Great Britain, India, and the rest of the world, as well as medicine and surgery. Such effects include the collapse of the profits of the British indigo monopoly, the growth in economic power of Germany based on coal tar chemistry, and an economic crisis in India that led to more humane tax laws and, ultimately, the independence of India and the end of the British Empire. Additional consequences were the development of antiseptic surgery and the synthesis of a wide variety of useful drugs that have eradicated infections and alleviated pain. Many of these drugs, particularly the commonly used analgesics, sulfonamides, sulfones, and local anesthetics, are derivatives of aniline, originally called "blue oil" or "kyanol." Some of these aniline derivatives, however, have also caused aplastic anemia, agranulocytosis, and methemoglobinemia (that is, "blue people"). Exposure to aniline drugs, particularly when two or three aniline drugs are taken concurrently, seems to be the commonest cause of methemoglobinemia today.

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

Antimicrobial blue light inactivation of Methicillin-resistant Staphylococcus aureus

Science.gov (United States)

Wang, Yucheng; Dai, Tianhong; Gu, Ying

2016-10-01

Background: With the increasing emergence of multidrug-resistant (MDR) bacterial strains, there is a pressing need for the development of alternative treatment for infections. Antimicrobial blue light (aBL) has provided a simple and effective approach. Methods: We first investigated the effectiveness of aBL (415 nm) inactivation of USA300 LAClux (a communityacquired Methicillin-resistant Staphylococcus aureus strain) both in the planktonic and biofilm forms. The survival of the bacteria in suspensions was determined by serial dilution and that of the biofilm-embedded bacteria was determined by bioluminescence quantification. Using a mouse model of thermal burn infected with USA300 LAClux, we further assessed the effectiveness of aBL for treating localized infections. Bioluminescence imaging was performed to monitor in real time bacterial viability in vivo. Results: In vitro study showed that, for the planktonic counterpart of the bacteria or the 24-h-old biofilms, an irradiance of 55 mW/cm2 for 60 min resulted in a 4.61 log10 or 2.56 log10 inactivation, respectively. In vivo study using infected mouse burns demonstrated that a 2.56-log10 inactivation was achieved after 100-mW/cm2 irradiation for 62 min. Conclusions: aBL is a potential alternative approach for treating Methicillin-resistant Staphylococcus aureus infections.

[Acute blue urticaria following subcutaneous injection of patent blue dye].

Science.gov (United States)

Hamelin, A; Vial-Dupuy, A; Lebrun-Vignes, B; Francès, C; Soria, A; Barete, S

2015-11-01

Patent blue (PB) is a lymphatic vessel dye commonly used in France for sentinel lymph node detection in breast cancer, and less frequently in melanoma, and which may induce hypersensitivity reactions. We report a case of acute blue urticaria occurring within minutes of PB injection. Ten minutes after PB injection for sentinel lymph node detection during breast cancer surgery, a 49-year-old woman developed generalised acute blue urticaria and eyelid angioedema without bronchospasm or haemodynamic disturbance, but requiring discontinuation of surgery. Skin testing using PB and the anaesthetics given were run 6 weeks after the episode and confirmed PB allergy. PB was formally contra-indicated. Immediate hypersensitivity reactions to PB have been reported for between 0.24 and 2.2% of procedures. Such reactions are on occasion severe, chiefly involving anaphylactic shock. Two mechanisms are probably associated: non-specific histamine release and/or an IgE-mediated mechanism. Skin tests are helpful in confirming the diagnosis of PB allergy. Blue acute urticaria is one of the clinical manifestations of immediate hypersensitivity reactions to patent blue dye. Skin tests must be performed 6 weeks after the reaction in order to confirm the diagnosis and formally contra-indicate this substance. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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.

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.

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....

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.

Jagua blue derived from Genipa americana L. fruit: A natural alternative to commonly used blue food colorants?

Science.gov (United States)

Brauch, J E; Zapata-Porras, S P; Buchweitz, M; Aschoff, J K; Carle, R

2016-11-01

Due to consumers' increasing health awareness, food industry aims at replacing synthetic dyes by natural counterparts. The substitution of blue synthetic dyes is particularly challenging since current natural alternatives such as phycocyanin (Spirulina) suffer from poor stability. Jagua blue (produced from Genipa americana L. fruit) might represent a potential novel blue pigment source. However, only little is known about its color properties, and application in food systems. Therefore, the blue color and the stability of Jagua blue were assessed for the first time and compared to commonly used colorants, namely, Spirulina, brilliant blue FCF (Blue no. 1), and indigo carmine (Blue no. 2). The reaction rate of Jagua blue was independent of its concentration, confirming thermal degradation to follow first-order kinetics. Between pH 3.6 and 5.0, the color hue of Jagua blue solutions was similar to that of Blue no. 2. However, Jagua blue revealed markedly higher storage stabilities (t 1/2 =86-105days) than Blue no. 2 (t 1 /2 ≤9days) and was less susceptible to acidic pH of 3.6 (t 1 /2 =86days) than Spirulina (t 1 /2 =70days). High negative b* values (blueness) of colored gelatin gels were only obtained for Jagua blue and Spirulina, and the former exhibited higher light stabilities (t 1 /2 =15days) than Spirulina gels (t 1 /2 =4days). Our findings indicate Jagua blue to be a most promising alternative to synthetic dyes, providing relevant information regarding potential food applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.'

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

The Fictional Black Blues Figure: Blues Music and the Art of Narrative Self-Invention

OpenAIRE

Mack, Kimberly

2015-01-01

The Fictional Black Blues Figure: Blues Music and the Art of Narrative Self-Invention, Kimberly MackMy dissertation examines representations of black American blues musicians in contemporary American fiction, drama, and popular music, and it argues that blues music can be examined as a narrative art rooted in the tradition of fictionalized autobiographical self-fashioning. I contend that the contemporary, multi-racial, literary and musical characters in my project who participate in so-called...

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.

Coomassie Brilliant Blue G is a more potent antagonist of P2 purinergic responses than Reactive Blue 2 (Cibacron Blue 3GA) in rat parotid acinar cells

International Nuclear Information System (INIS)

Soltoff, S.P.; McMillian, M.K.; Talamo, B.R.

1989-01-01

The ability of Brilliant Blue G (Coomassie Brilliant Blue G) and Reactive Blue 2 (Cibacron Blue 3GA) to block the effects of extracellular ATP on rat parotid acinar cells was examined by evaluating their effects on ATP-stimulated 45Ca 2+ entry and the elevation of [Ca 2+ ]i (Fura 2 fluorescence). ATP (300 microM) increased the rate of Ca 2+ entry to more than 25-times the basal rate and elevated [Ca 2+ ]i to levels more than three times the basal value. Brilliant Blue G and Reactive Blue 2 greatly reduced the entry of 45 Ca 2+ into parotid cells, but the potency of Brilliant Blue G (IC50 approximately 0.4 microM) was about 100-times that of Reactive Blue 2. Fura 2 studies demonstrated that inhibitory concentrations of these compounds did not block the cholinergic response of these cells, thus demonstrating the selectivity of the dye compounds for purinergic receptors. Unlike Reactive Blue 2, effective concentrations of Brilliant Blue G did not substantially quench Fura 2 fluorescence. The greater potency of Brilliant Blue G suggests that it may be very useful in identifying P2-type purinergic receptors, especially in studies which utilize fluorescent probes

Measuring Blue Space Visibility and 'Blue Recreation' in the Everyday Lives of Children in a Capital City.

Science.gov (United States)

Pearson, Amber L; Bottomley, Ross; Chambers, Tim; Thornton, Lukar; Stanley, James; Smith, Moira; Barr, Michelle; Signal, Louise

2017-05-26

Blue spaces (water bodies) may promote positive mental and physical health through opportunities for relaxation, recreation, and social connections. However, we know little about the nature and extent of everyday exposure to blue spaces, particularly in settings outside the home or among children, nor whether exposure varies by individual or household characteristics. Wearable cameras offer a novel, reliable method for blue space exposure measurement. In this study, we used images from cameras worn over two days by 166 children in Wellington, New Zealand, and conducted content and blue space quantification analysis on each image ( n = 749,389). Blue space was identified in 24,721 images (3.6%), with a total of 23 blue recreation events. Visual exposure and participation in blue recreation did not differ by ethnicity, weight status, household deprivation, or residential proximity to the coastline. Significant differences in both visual exposure to blue space and participation in blue recreation were observed, whereby children from the most deprived schools had significantly higher rates of blue space exposure than children from low deprivation schools. Schools may be important settings to promote equitable blue space exposures. Childhood exposures to blue space may not follow the expected income inequality trends observed among adults.

75 FR 65525 - Anthem Blue Cross Blue Shield, Claim Management Services, Inc. Operations, a Division of...

Science.gov (United States)

2010-10-25

... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-74,327] Anthem Blue Cross Blue Shield, Claim Management Services, Inc. Operations, a Division of Wellpoint, Inc., Green Bay, WI; Notice... former workers of Anthem Blue Cross Blue Shield, Claim Management Services, Inc. Operations, a Division...

Dyes adsorption blue vegetable and blue watercolor by natural zeolites modified with surfactants

International Nuclear Information System (INIS)

Jardon S, C. C.; Olguin G, M. T.; Diaz N, M. C.

2009-01-01

In this work was carried out the dyes removal blue vegetable and blue watercolor of aqueous solutions, to 20 C, at different times and using a zeolite mineral of Parral (Chihuahua, Mexico) modified with hexadecyl trimethyl ammonium bromide or dodecyl trimethyl ammonium bromide. The zeolite was characterized before and after of its adaptation with NaCl and later with HDTMABr and DTMABr. For the materials characterization were used the scanning electron microscopy of high vacuum; elementary microanalysis by X-ray spectroscopy of dispersed energy and X-ray diffraction techniques. It was found that the surfactant type absorbed in the zeolite material influences on the adsorption process of the blue dye. Likewise, the chemical structure between the vegetable blue dye and the blue watercolor, determines the efficiency of the color removal of the water, by the zeolites modified with the surfactants. (Author)

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.

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 ...

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.

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

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...

Chromosome-wise dissection of the genome of the extremely big mouse line DU6i

NARCIS (Netherlands)

M.R. Bevova (Marianna); Y.S. Aulchenko (Yurii); G. Aksu (Guzide); U. Renne (Ulla); K. Brockmann

2006-01-01

textabstractThe extreme high-body-weight-selected mouse line DU6i is a polygenic model for growth research, harboring many small-effect QTL. We dissected the genome of this line into 19 autosomes and the Y chromosome by the construction of a new panel of chromosome substitution strains (CSS). The

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 ...

Early Changes of Articular Cartilage and Subchondral Bone in The DMM Mouse Model of Osteoarthritis

OpenAIRE

Fang, Hang; Huang, Lisi; Welch, Ian; Norley, Chris; Holdsworth, David W.; Beier, Frank; Cai, Daozhang

2018-01-01

To examine the early changes of articular cartilage and subchondral bone in the DMM mouse model of osteoarthritis, mice were subjected to DMM or SHAM surgery and sacrificed at 2-, 5- and 10-week post-surgery. Catwalk gait analyses, Micro-Computed Tomography, Toluidine Blue, Picrosirius Red and Tartrate-Resistant Acid Phosphatase (TRAP) staining were used to investigate gait patterns, joint morphology, subchondral bone, cartilage, collagen organization and osteoclasts activity, respectively. R...

Blue Ocean Thinking

Science.gov (United States)

Orem, Donna

2016-01-01

This article describes a concept called the "blue ocean thinking strategy," developed by W. Chan Kim and Renée Mauborgne, professors at INSEAD, an international graduate school of business in France. The "blue ocean" thinking strategy considers opportunities to create new markets for services, rather than focusing solely on…

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....

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.

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...

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.

Blue Emission in Proteins

OpenAIRE

Sarkar, Sohini; Sengupta, Abhigyan; Hazra, Partha; Mandal, Pankaj

2014-01-01

Recent literatures reported blue-green emission from amyloid fibril as exclusive signature of fibril formation. This unusual visible luminescence is regularly used to monitor fibril growth. Blue-green emission has also been observed in crystalline protein and in solution. However, the origin of this emission is not known exactly. Our spectroscopic study of serum proteins reveals that the blue-green emission is a property of protein monomer. Evidences suggest that semiconductor-like band struc...

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.

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...

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....

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 ...

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…

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.

Evaluation of Code Blue Implementation Outcomes

Directory of Open Access Journals (Sweden)

Bengü Özütürk

2015-09-01

Full Text Available Aim: In this study, we aimed to emphasize the importance of Code Blue implementation and to determine deficiencies in this regard. Methods: After obtaining the ethics committee approval, 225 patient’s code blue call data between 2012 and 2014 January were retrospectively analyzed. Age and gender of the patients, date and time of the call and the clinics giving Code Blue, the time needed for the Code Blue team to arrive, the rates of false Code Blue calls, reasons for Code Blue calls and patient outcomes were investigated. Results: A total of 225 patients (149 male, 76 female were evaluated in the study. The mean age of the patients was 54.1 years. 142 (67.2% Code Blue calls occurred after hours and by emergency unit. The mean time for the Code Blue team to arrive was 1.10 minutes. Spontaneous circulation was provided in 137 patients (60.8%; 88 (39.1% died. The most commonly identified possible causes were of cardiac origin. Conclusion: This study showed that Code Blue implementation with a professional team within an efficient and targeted time increase the survival rate. Therefore, we conclude that the application of Code Blue carried out by a trained team is an essential standard in hospitals. (The Medical Bulletin of Haseki 2015; 53:204-8

Big data bioinformatics.

Science.gov (United States)

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.

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).

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'.

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...

Tunable photonic crystals with partial bandgaps from blue phase colloidal crystals and dielectric-doped blue phases.

Science.gov (United States)

Stimulak, Mitja; Ravnik, Miha

2014-09-07

Blue phase colloidal crystals and dielectric nanoparticle/polymer doped blue phases are demonstrated to combine multiple components with different symmetries in one photonic material, creating a photonic crystal with variable and micro-controllable photonic band structure. In this composite photonic material, one contribution to the band structure is determined by the 3D periodic birefringent orientational profile of the blue phases, whereas the second contribution emerges from the regular array of the colloidal particles or from the dielectric/nanoparticle-doped defect network. Using the planewave expansion method, optical photonic bands of the blue phase I and II colloidal crystals and related nanoparticle/polymer doped blue phases are calculated, and then compared to blue phases with no particles and to face-centred-cubic and body-centred-cubic colloidal crystals in isotropic background. We find opening of local band gaps at particular points of Brillouin zone for blue phase colloidal crystals, where there were none in blue phases without particles or dopants. Particle size and filling fraction of the blue phase defect network are demonstrated as parameters that can directly tune the optical bands and local band gaps. In the blue phase I colloidal crystal with an additionally doped defect network, interestingly, we find an indirect total band gap (with the exception of one point) at the entire edge of SC irreducible zone. Finally, this work demonstrates the role of combining multiple - by symmetry - differently organised components in one photonic crystal material, which offers a novel approach towards tunable soft matter photonic materials.

Google BigQuery analytics

CERN Document Server

Tigani, Jordan

2014-01-01

How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addit

Big data for dummies

CERN Document Server

Hurwitz, Judith; Halper, Fern; Kaufman, Marcia

2013-01-01

Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it m

Endogenous estrogen status, but not genistein supplementation, modulates 7,12-dimethylbenz[a]anthracene-induced mutation in the liver cII gene of transgenic big blue rats.

Science.gov (United States)

Chen, Tao; Hutts, Robert C; Mei, Nan; Liu, Xiaoli; Bishop, Michelle E; Shelton, Sharon; Manjanatha, Mugimane G; Aidoo, Anane

2005-06-01

A growing number of studies suggest that isoflavones found in soybeans have estrogenic activity and may safely alleviate the symptoms of menopause. One of these isoflavones, genistein, is commonly used by postmenopausal women as an alternative to hormone replacement therapy. Although sex hormones have been implicated as an important risk factor for the development of hepatocellular carcinoma, there are limited data on the potential effects of the estrogens, including phytoestrogens, on chemical mutagenesis in liver. Because of the association between mutation induction and the carcinogenesis process, we investigated whether endogenous estrogen and supplemental genistein affect 7,12-dimethylbenz[a]anthracene (DMBA)-induced mutagenesis in rat liver. Intact and ovariectomized female Big Blue rats were treated with 80 mg DMBA/kg body weight. Some of the rats also received a supplement of 1,000 ppm genistein. Sixteen weeks after the carcinogen treatment, the rats were sacrificed, their livers were removed, and mutant frequencies (MFs) and types of mutations were determined in the liver cII gene. DMBA significantly increased the MFs in liver for both the intact and ovariectomized rats. While there was no significant difference in MF between the ovariectomized and intact control animals, the mutation induction by DMBA in the ovariectomized groups was significantly higher than that in the intact groups. Dietary genistein did not alter these responses. Molecular analysis of the mutants showed that DMBA induced chemical-specific types of mutations in the liver cII gene. These results suggest that endogenous ovarian hormones have an inhibitory effect on liver mutagenesis by DMBA, whereas dietary genistein does not modulate spontaneous or DMBA-induced mutagenesis in either intact or ovariectomized rats.

Exploring complex and big data

Directory of Open Access Journals (Sweden)

Stefanowski Jerzy

2017-12-01

Full Text Available This paper shows how big data analysis opens a range of research and technological problems and calls for new approaches. We start with defining the essential properties of big data and discussing the main types of data involved. We then survey the dedicated solutions for storing and processing big data, including a data lake, virtual integration, and a polystore architecture. Difficulties in managing data quality and provenance are also highlighted. The characteristics of big data imply also specific requirements and challenges for data mining algorithms, which we address as well. The links with related areas, including data streams and deep learning, are discussed. The common theme that naturally emerges from this characterization is complexity. All in all, we consider it to be the truly defining feature of big data (posing particular research and technological challenges, which ultimately seems to be of greater importance than the sheer data volume.

Was there a big bang

International Nuclear Information System (INIS)

Narlikar, J.

1981-01-01

In discussing the viability of the big-bang model of the Universe relative evidence is examined including the discrepancies in the age of the big-bang Universe, the red shifts of quasars, the microwave background radiation, general theory of relativity aspects such as the change of the gravitational constant with time, and quantum theory considerations. It is felt that the arguments considered show that the big-bang picture is not as soundly established, either theoretically or observationally, as it is usually claimed to be, that the cosmological problem is still wide open and alternatives to the standard big-bang picture should be seriously investigated. (U.K.)

BIG DATA-DRIVEN MARKETING: AN ABSTRACT

OpenAIRE

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

2017-01-01

Customer information plays a key role in managing successful relationships with valuable customers. Big data customer analytics use (BD use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study addresses three research questions: What are the key antecedents of big data customer analytics use? How, and to what extent, does big data customer an...

Big Data Analytics in Medicine and Healthcare.

Science.gov (United States)

Ristevski, Blagoj; Chen, Ming

2018-05-10

This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.

The trashing of Big Green

International Nuclear Information System (INIS)

Felten, E.

1990-01-01

The Big Green initiative on California's ballot lost by a margin of 2-to-1. Green measures lost in five other states, shocking ecology-minded groups. According to the postmortem by environmentalists, Big Green was a victim of poor timing and big spending by the opposition. Now its supporters plan to break up the bill and try to pass some provisions in the Legislature

The Big Bang Singularity

Science.gov (United States)

Ling, Eric

The big bang theory is a model of the universe which makes the striking prediction that the universe began a finite amount of time in the past at the so called "Big Bang singularity." We explore the physical and mathematical justification of this surprising result. After laying down the framework of the universe as a spacetime manifold, we combine physical observations with global symmetrical assumptions to deduce the FRW cosmological models which predict a big bang singularity. Next we prove a couple theorems due to Stephen Hawking which show that the big bang singularity exists even if one removes the global symmetrical assumptions. Lastly, we investigate the conditions one needs to impose on a spacetime if one wishes to avoid a singularity. The ideas and concepts used here to study spacetimes are similar to those used to study Riemannian manifolds, therefore we compare and contrast the two geometries throughout.

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...

Medical big data: promise and challenges.

Science.gov (United States)

Lee, Choong Ho; Yoon, Hyung-Jin

2017-03-01

The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

Medical big data: promise and challenges

Directory of Open Access Journals (Sweden)

Choong Ho Lee

2017-03-01

Full Text Available The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

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.

Big Data Analytics and Its Applications

Directory of Open Access Journals (Sweden)

Mashooque A. Memon

2017-10-01

Full Text Available The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, banking, data mining, education, chemistry, finance, cloud computing, marketing, health care stocks. Big data analytics is the method for looking at big data to reveal hidden patterns, incomprehensible relationship and other important data that can be utilize to resolve on enhanced decisions. There has been a perpetually expanding interest for big data because of its fast development and since it covers different areas of applications. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used. The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use. Later on, there emerge to be a required for an analytical review of new developments in the big data technology. Healthcare is one of the best concerns of the world. Big data in healthcare imply to electronic health data sets that are identified with patient healthcare and prosperity. Data in the healthcare area is developing past managing limit of the healthcare associations and is relied upon to increment fundamentally in the coming years.

Measuring the Promise of Big Data Syllabi

Science.gov (United States)

Friedman, Alon

2018-01-01

Growing interest in Big Data is leading industries, academics and governments to accelerate Big Data research. However, how teachers should teach Big Data has not been fully examined. This article suggests criteria for redesigning Big Data syllabi in public and private degree-awarding higher education establishments. The author conducted a survey…

77 FR 27245 - Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN

Science.gov (United States)

2012-05-09

... DEPARTMENT OF THE INTERIOR Fish and Wildlife Service [FWS-R3-R-2012-N069; FXRS1265030000S3-123-FF03R06000] Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN AGENCY: Fish and... plan (CCP) and environmental assessment (EA) for Big Stone National Wildlife Refuge (Refuge, NWR) for...

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.

Big data and educational research

OpenAIRE

Beneito-Montagut, Roser

2017-01-01

Big data and data analytics offer the promise to enhance teaching and learning, improve educational research and progress education governance. This chapter aims to contribute to the conceptual and methodological understanding of big data and analytics within educational research. It describes the opportunities and challenges that big data and analytics bring to education as well as critically explore the perils of applying a data driven approach to education. Despite the claimed value of the...

Thick-Big Descriptions

DEFF Research Database (Denmark)

Lai, Signe Sophus

The paper discusses the rewards and challenges of employing commercial audience measurements data – gathered by media industries for profitmaking purposes – in ethnographic research on the Internet in everyday life. It questions claims to the objectivity of big data (Anderson 2008), the assumption...... communication systems, language and behavior appear as texts, outputs, and discourses (data to be ‘found’) – big data then documents things that in earlier research required interviews and observations (data to be ‘made’) (Jensen 2014). However, web-measurement enterprises build audiences according...... to a commercial logic (boyd & Crawford 2011) and is as such directed by motives that call for specific types of sellable user data and specific segmentation strategies. In combining big data and ‘thick descriptions’ (Geertz 1973) scholars need to question how ethnographic fieldwork might map the ‘data not seen...

Big Data's Role in Precision Public Health.

Science.gov (United States)

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

Big Data, indispensable today

Directory of Open Access Journals (Sweden)

Radu-Ioan ENACHE

2015-10-01

Full Text Available Big data is and will be used more in the future as a tool for everything that happens both online and offline. Of course , online is a real hobbit, Big Data is found in this medium , offering many advantages , being a real help for all consumers. In this paper we talked about Big Data as being a plus in developing new applications, by gathering useful information about the users and their behaviour.We've also presented the key aspects of real-time monitoring and the architecture principles of this technology. The most important benefit brought to this paper is presented in the cloud section.

Antigravity and the big crunch/big bang transition

Science.gov (United States)

Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

2012-08-01

We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

Antigravity and the big crunch/big bang transition

Energy Technology Data Exchange (ETDEWEB)

Bars, Itzhak [Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089-2535 (United States); Chen, Shih-Hung [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada); Department of Physics and School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1404 (United States); Steinhardt, Paul J., E-mail: steinh@princeton.edu [Department of Physics and Princeton Center for Theoretical Physics, Princeton University, Princeton, NJ 08544 (United States); Turok, Neil [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada)

2012-08-29

We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

Antigravity and the big crunch/big bang transition

International Nuclear Information System (INIS)

Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

2012-01-01

We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

Big data: een zoektocht naar instituties

NARCIS (Netherlands)

van der Voort, H.G.; Crompvoets, J

2016-01-01

Big data is a well-known phenomenon, even a buzzword nowadays. It refers to an abundance of data and new possibilities to process and use them. Big data is subject of many publications. Some pay attention to the many possibilities of big data, others warn us for their consequences. This special

Data, Data, Data : Big, Linked & Open

NARCIS (Netherlands)

Folmer, E.J.A.; Krukkert, D.; Eckartz, S.M.

2013-01-01

De gehele business en IT-wereld praat op dit moment over Big Data, een trend die medio 2013 Cloud Computing is gepasseerd (op basis van Google Trends). Ook beleidsmakers houden zich actief bezig met Big Data. Neelie Kroes, vice-president van de Europese Commissie, spreekt over de ‘Big Data

"Blue-Collar Blues" uurib töösuhteid uutes oludes / Janar Ala

Index Scriptorium Estoniae

Ala, Janar, 1979-

2009-01-01

Tööproblemaatikat käsitlev näitus "Blue-Collar Blues" Tallinna Kunstihoones ja Tallinna Kunstihoone galeriis 31. jaanuarini 2010, kuraator Anders Härm. Lähemalt belgia-mehhiko kunstniku Francis Alys'e videost, austria kunstniku Oliver Ressleri ning venetsueela-saksa politoloogi Dario Azzelini videost "Viis tehast. Tööliste kontroll Venezuelas"

The spectrum of dermatoscopic patterns in blue nevi.

Science.gov (United States)

Di Cesare, Antonella; Sera, Francesco; Gulia, Andrea; Coletti, Gino; Micantonio, Tamara; Fargnoli, Maria Concetta; Peris, Ketty

2012-08-01

Blue nevi are congenital or acquired, dermal dendritic melanocytic proliferations that can simulate melanocytic and nonmelanocytic lesions including melanoma, cutaneous metastasis of melanoma, Spitz/Reed nevi, and basal cell carcinoma. We sought to investigate global and local dermatoscopic patterns of blue nevi compared with melanomas and basal cell carcinomas. We retrospectively analyzed global and local features in 95 dermatoscopic images of blue nevi and in 190 melanomas and basal cell carcinomas that were selected as control lesions on the basis of similar pigmentation. Lesion pigmentation was classified as monochromatic, dichromatic, or multichromatic. A global pattern characterized by homogeneous pigmentation was observed in all of 95 (100%) blue nevi. Eighty of 95 (84.2%) blue nevi presented a homogeneous pattern consisting of one color (blue, black, or brown) or two colors (blue-brown, blue-gray, or blue-black). Fifteen of 95 (15.8%) blue nevi had a multichromatic (blue, gray, black, brown, and/or red) pigmentation. In all, 47 of 95 (49.5%) blue nevi were characterized by pigmentation in the absence of pigment network or any other local dermatoscopic features. And 48 of 95 (50.5%) blue nevi showed local dermatoscopic patterns including whitish scarlike depigmentation, dots/globules, vascular pattern, streaks, and networklike pattern. The study was retrospective and involved only Caucasian people of Italian origin. The characteristic feature of blue nevi is a homogeneous pigmentation that is blue, blue-gray, blue-brown, or blue-black. We showed that a wide spectrum of local dermatoscopic features (whitish scarlike depigmentation, dots/globules, peripheral streaks or vessels) may also be present. In such cases, clinical and dermatoscopic distinction from melanoma or nonmelanocytic lesions may be difficult or impossible, and surgical excision is necessary. Copyright © 2011 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Methods and tools for big data visualization

OpenAIRE

Zubova, Jelena; Kurasova, Olga

2015-01-01

In this paper, methods and tools for big data visualization have been investigated. Challenges faced by the big data analysis and visualization have been identified. Technologies for big data analysis have been discussed. A review of methods and tools for big data visualization has been done. Functionalities of the tools have been demonstrated by examples in order to highlight their advantages and disadvantages.

The Blue Coma: The Role of Methylene Blue in Unexplained Coma After Cardiac Surgery.

Science.gov (United States)

Martino, Enrico Antonio; Winterton, Dario; Nardelli, Pasquale; Pasin, Laura; Calabrò, Maria Grazia; Bove, Tiziana; Fanelli, Giovanna; Zangrillo, Alberto; Landoni, Giovanni

2016-04-01

Methylene blue commonly is used as a dye or an antidote, but also can be used off label as a vasopressor. Serotonin toxicity is a potentially lethal and often misdiagnosed condition that can result from drug interaction. Mild serotonin toxicity previously was reported in settings in which methylene blue was used as a dye. The authors report 3 cases of life-threatening serotonin toxicity in patients undergoing chronic selective serotonin reuptake inhibitor (SSRI) therapy who also underwent cardiac surgery and received methylene blue to treat vasoplegic syndrome. An observational study. A cardiothoracic intensive care unit (ICU) in a teaching hospital. Three patients who received methylene blue after cardiac surgery, later discovered to be undergoing chronic SSRI therapy. None. All 3 patients received high doses of fentanyl during general anesthesia. They all developed vasoplegic syndrome and consequently were given methylene blue in the ICU. All 3 patients developed serotonin toxicity, including coma, after this administration and diagnostic tests were negative for acute intracranial pathology. Coma lasted between 1 and 5 days. Two patients were discharged from the ICU shortly after awakening, whereas the third patient experienced a complicated postoperative course for concomitant refractory low-cardiac-output syndrome. Patients undergoing chronic SSRI therapy should not be administered methylene blue to treat vasoplegic syndrome. Copyright © 2016 Elsevier Inc. All rights reserved.

Big data analytics methods and applications

CERN Document Server

Rao, BLS; Rao, SB

2016-01-01

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

The Big bang and the Quantum

Science.gov (United States)

Ashtekar, Abhay

2010-06-01

General relativity predicts that space-time comes to an end and physics comes to a halt at the big-bang. Recent developments in loop quantum cosmology have shown that these predictions cannot be trusted. Quantum geometry effects can resolve singularities, thereby opening new vistas. Examples are: The big bang is replaced by a quantum bounce; the `horizon problem' disappears; immediately after the big bounce, there is a super-inflationary phase with its own phenomenological ramifications; and, in presence of a standard inflation potential, initial conditions are naturally set for a long, slow roll inflation independently of what happens in the pre-big bang branch. As in my talk at the conference, I will first discuss the foundational issues and then the implications of the new Planck scale physics near the Big Bang.

Evans blue dye-enhanced imaging of the brain microvessels using spectral focusing coherent anti-Stokes Raman scattering microscopy.

Directory of Open Access Journals (Sweden)

Bo-Ram Lee

Full Text Available We performed dye-enhanced imaging of mouse brain microvessels using spectral focusing coherent anti-Stokes Raman scattering (SF-CARS microscopy. The resonant signals from C-H stretching in forward CARS usually show high background intensity in tissues, which makes CARS imaging of microvessels difficult. In this study, epi-detection of back-scattered SF-CARS signals showed a negligible background, but the overall intensity of resonant CARS signals was too low to observe the network of brain microvessels. Therefore, Evans blue (EB dye was used as contrasting agent to enhance the back-scattered SF-CARS signals. Breakdown of brain microvessels by inducing hemorrhage in a mouse was clearly visualized using backward SF-CARS signals, following intravenous injection of EB. The improved visualization of brain microvessels with EB enhanced the sensitivity of SF-CARS, detecting not only the blood vessels themselves but their integrity as well in the brain vasculature.

Big Bang baryosynthesis

International Nuclear Information System (INIS)

Turner, M.S.; Chicago Univ., IL

1983-01-01

In these lectures I briefly review Big Bang baryosynthesis. In the first lecture I discuss the evidence which exists for the BAU, the failure of non-GUT symmetrical cosmologies, the qualitative picture of baryosynthesis, and numerical results of detailed baryosynthesis calculations. In the second lecture I discuss the requisite CP violation in some detail, further the statistical mechanics of baryosynthesis, possible complications to the simplest scenario, and one cosmological implication of Big Bang baryosynthesis. (orig./HSI)

Exploiting big data for critical care research.

Science.gov (United States)

Docherty, Annemarie B; Lone, Nazir I

2015-10-01

Over recent years the digitalization, collection and storage of vast quantities of data, in combination with advances in data science, has opened up a new era of big data. In this review, we define big data, identify examples of critical care research using big data, discuss the limitations and ethical concerns of using these large datasets and finally consider scope for future research. Big data refers to datasets whose size, complexity and dynamic nature are beyond the scope of traditional data collection and analysis methods. The potential benefits to critical care are significant, with faster progress in improving health and better value for money. Although not replacing clinical trials, big data can improve their design and advance the field of precision medicine. However, there are limitations to analysing big data using observational methods. In addition, there are ethical concerns regarding maintaining confidentiality of patients who contribute to these datasets. Big data have the potential to improve medical care and reduce costs, both by individualizing medicine, and bringing together multiple sources of data about individual patients. As big data become increasingly mainstream, it will be important to maintain public confidence by safeguarding data security, governance and confidentiality.

Empathy and the Big Five

OpenAIRE

Paulus, Christoph

2016-01-01

Del Barrio et al. (2004) haben vor mehr als 10 Jahren versucht, eine direkte Beziehung zwischen Empathie und den Big Five herzustellen. Im Mittel hatten in ihrer Stichprobe Frauen höhere Werte in der Empathie und auf den Big Five-Faktoren mit Ausnahme des Faktors Neurotizismus. Zusammenhänge zu Empathie fanden sie in den Bereichen Offenheit, Verträglichkeit, Gewissenhaftigkeit und Extraversion. In unseren Daten besitzen Frauen sowohl in der Empathie als auch den Big Five signifikant höhere We...

UVA-induced mutational spectra in the laci gene from transgenic mouse skin

International Nuclear Information System (INIS)

Gorelick, N.J.; O'Kelly, J.A.; Biedermann, K.A.

1995-01-01

The UVB (295-320 nm) component of sunlight was once thought to be the sole cause of photoaging and skin cancer. However, there is now compelling evidence to suggest that chronic irradiation with UVA (320-400 nm) is a significant component of the etiologies of these diseases. To identify acute markers of UVA damage, we investigated UVA-induced mutagenesis in vivo by using a lacI transgenic mouse mutation assay. The backs of adult female C57BL/6 Big Blue reg-sign mice were shaved and exposed daily to a low or a high dose of UVA for 5 consecutive days. One group remained unexposed. The high dose of UVA significantly increased the mutant frequency in skin determined 12 days after the last exposure. Mutant frequencies were (Avg ± SEM, n=7-8/group): 6.1 ± 0.5 x 10 -5 (high dose). DNA sequence analysis of mutant lacI genes demonstrated that the high dose of UVA produced a different mutational spectrum compared to control. The mutational spectrum from the low dose mutants was not different from the control spectrum in skin generated previously; the predominant classes of recovered mutations were GC→At transitions at CpG sites (11/35) and GC →TA transversions (12/35). In contrast, in the high dose group, GC →AT transitions at non-CpG sites predominated (61/97 mutations); three tandem base substitutions (1 GG →AA; 2 CC→TT) were uniquely recovered; and an increased frequency of recovered GC→CG substitutions was observed (12/97 vs. none in controls). The recovered high dose spectrum is consistent with the types of DNA damage generated by UVA as well as by reactive oxygen species. These studies demonstrate that UVA is mutagenic in vivo and that this assay can be used to study early events in UVA-induced skin damage

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.

Why Blue-Collar Blacks Help Less

OpenAIRE

Smith, Sandra Susan; Young, Kara Alexis

2013-01-01

Why are blue-collar blacks less likely to help jobseekers than jobholders from other ethnoracial groups or even than more affluent blacks? Drawing from in-depth, semi-structured interviews with 97 black and Latino workers at one large, public sector employer, we find that blue-collar black workers both helped less proactively and rejected more requests for assistance than did blue-collar Latino and white-collar black workers. We attribute blue-collar blacks’ more passive engagement to their...

Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores

OpenAIRE

Konstantopoulos, Stasinos; Charalambidis, Angelos; Mouchakis, Giannis; Troumpoukis, Antonis; Jakobitsch, Jürgen; Karkaletsis, Vangelis

2016-01-01

The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges invo...

Quantum fields in a big-crunch-big-bang spacetime

International Nuclear Information System (INIS)

Tolley, Andrew J.; Turok, Neil

2002-01-01

We consider quantum field theory on a spacetime representing the big-crunch-big-bang transition postulated in ekpyrotic or cyclic cosmologies. We show via several independent methods that an essentially unique matching rule holds connecting the incoming state, in which a single extra dimension shrinks to zero, to the outgoing state in which it reexpands at the same rate. For free fields in our construction there is no particle production from the incoming adiabatic vacuum. When interactions are included the particle production for fixed external momentum is finite at the tree level. We discuss a formal correspondence between our construction and quantum field theory on de Sitter spacetime

Turning big bang into big bounce: II. Quantum dynamics

Energy Technology Data Exchange (ETDEWEB)

Malkiewicz, Przemyslaw; Piechocki, Wlodzimierz, E-mail: pmalk@fuw.edu.p, E-mail: piech@fuw.edu.p [Theoretical Physics Department, Institute for Nuclear Studies, Hoza 69, 00-681 Warsaw (Poland)

2010-11-21

We analyze the big bounce transition of the quantum Friedmann-Robertson-Walker model in the setting of the nonstandard loop quantum cosmology (LQC). Elementary observables are used to quantize composite observables. The spectrum of the energy density operator is bounded and continuous. The spectrum of the volume operator is bounded from below and discrete. It has equally distant levels defining a quantum of the volume. The discreteness may imply a foamy structure of spacetime at a semiclassical level which may be detected in astro-cosmo observations. The nonstandard LQC method has a free parameter that should be fixed in some way to specify the big bounce transition.

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

The ethics of big data in big agriculture

Directory of Open Access Journals (Sweden)

Isabelle M. Carbonell

2016-03-01

Full Text Available 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 insights on a field-by-field basis into a third or more of the US farmland. This power asymmetry may be rebalanced through open-sourced data, and publicly-funded data analytic tools which rival Climate Corp. in complexity and innovation for use in the public domain.

Homogeneous and isotropic big rips?

CERN Document Server

Giovannini, Massimo

2005-01-01

We investigate the way big rips are approached in a fully inhomogeneous description of the space-time geometry. If the pressure and energy densities are connected by a (supernegative) barotropic index, the spatial gradients and the anisotropic expansion decay as the big rip is approached. This behaviour is contrasted with the usual big-bang singularities. A similar analysis is performed in the case of sudden (quiescent) singularities and it is argued that the spatial gradients may well be non-negligible in the vicinity of pressure singularities.

Rate Change Big Bang Theory

Science.gov (United States)

Strickland, Ken

2013-04-01

The Rate Change Big Bang Theory redefines the birth of the universe with a dramatic shift in energy direction and a new vision of the first moments. With rate change graph technology (RCGT) we can look back 13.7 billion years and experience every step of the big bang through geometrical intersection technology. The analysis of the Big Bang includes a visualization of the first objects, their properties, the astounding event that created space and time as well as a solution to the mystery of anti-matter.

Intelligent Test Mechanism Design of Worn Big Gear

Directory of Open Access Journals (Sweden)

Hong-Yu LIU

2014-10-01

Full Text Available With the continuous development of national economy, big gear was widely applied in metallurgy and mine domains. So, big gear plays an important role in above domains. In practical production, big gear abrasion and breach take place often. It affects normal production and causes unnecessary economic loss. A kind of intelligent test method was put forward on worn big gear mainly aimed at the big gear restriction conditions of high production cost, long production cycle and high- intensity artificial repair welding work. The measure equations transformations were made on involute straight gear. Original polar coordinate equations were transformed into rectangular coordinate equations. Big gear abrasion measure principle was introduced. Detection principle diagram was given. Detection route realization method was introduced. OADM12 laser sensor was selected. Detection on big gear abrasion area was realized by detection mechanism. Tested data of unworn gear and worn gear were led in designed calculation program written by Visual Basic language. Big gear abrasion quantity can be obtained. It provides a feasible method for intelligent test and intelligent repair welding on worn big gear.

[Big data in medicine and healthcare].

Science.gov (United States)

Rüping, Stefan

2015-08-01

Healthcare is one of the business fields with the highest Big Data potential. According to the prevailing definition, Big Data refers to the fact that data today is often too large and heterogeneous and changes too quickly to be stored, processed, and transformed into value by previous technologies. The technological trends drive Big Data: business processes are more and more executed electronically, consumers produce more and more data themselves - e.g. in social networks - and finally ever increasing digitalization. Currently, several new trends towards new data sources and innovative data analysis appear in medicine and healthcare. From the research perspective, omics-research is one clear Big Data topic. In practice, the electronic health records, free open data and the "quantified self" offer new perspectives for data analytics. Regarding analytics, significant advances have been made in the information extraction from text data, which unlocks a lot of data from clinical documentation for analytics purposes. At the same time, medicine and healthcare is lagging behind in the adoption of Big Data approaches. This can be traced to particular problems regarding data complexity and organizational, legal, and ethical challenges. The growing uptake of Big Data in general and first best-practice examples in medicine and healthcare in particular, indicate that innovative solutions will be coming. This paper gives an overview of the potentials of Big Data in medicine and healthcare.

Radiation effects of electromagnetic pulses on mouse blood-testis barrier

International Nuclear Information System (INIS)

Hou Wugang; Zhao Jie; Zhang Yuanqiang

2005-01-01

Radiation effects caused by 100 kV/m and 400 kV/m electromagnetic pulse (EMP) irradiations on mouse blood-testis barrier were studied by means of routine HE staining, Lanthanum traced electron microscope and injection of caudal vein with Evans Blue. The EMP irradiation of different dose rates damaged Sertoli's cell and blood-testis barrier of mouse testis in different levels. Severe injuries were observed with the 400 kV/m irradiation group, with apoptosis and necrosis in a large quantity of the spermatogenic cells, shape and structural changes of the Sertoli's cells, and serious injuries to the blood-testis barrier, one day after the irradiation. The basal compartment separated from the adluminal compartment in most of the VIII stage seminiferous epithelium, and a great number of apoptosis and necrosis spermatogenic cells were released into the cavities. Injuries of blood-testis barrier could be observed 21 days after the 400 kV/m irradiation. The injuries of 100 kV/m irradiation groups were less severe than the 400 kV/m groups, in which the damages to the Sertoli's cells, the seminiferous epithelium and blood-testis barrier recovered to some extent 14 days after the irradiation. The authors conclude that EMP irradiation can damage mouse blood-tests barrier. The injuries, and the time for recovery, are related to EMP power intensity. (authors)

From Big Data to Big Business

DEFF Research Database (Denmark)

Lund Pedersen, Carsten

2017-01-01

Idea in Brief: Problem: There is an enormous profit potential for manufacturing firms in big data, but one of the key barriers to obtaining data-driven growth is the lack of knowledge about which capabilities are needed to extract value and profit from data. Solution: We (BDBB research group at C...

Raman analysis of cobalt blue pigment in blue and white porcelain: A reassessment

Science.gov (United States)

Jiang, Xiaochenyang; Ma, Yanying; Chen, Yue; Li, Yuanqiu; Ma, Qinglin; Zhang, Zhaoxia; Wang, Changsui; Yang, Yimin

2018-02-01

Cobalt blue is a famous pigment in human history. In the past decade it is widely reported that the cobalt aluminate has been detected in ancient ceramics as blue colorant in glaze, yet the acquired Raman spectra are incredibly different from that of synthesised references, necessitating a reassessment of such contradictory scenario with more accurate analytic strategies. In this study, micro-Raman spectroscopy (MRS) and scanning electron microscopy (SEM) in association with energy dispersive spectrometry (EDS) were performed on under-glaze cobalt pigments from one submerged blue and white porcelain shard dated from Wanli reign (1573-1620 CE) of Ming dynasty (1365-1644 CE) excavated at Nan'ao I shipwreck off the southern coast of China. The micro-structural inspection reveals that the pigment particles have characteristics of small account, tiny size, heterogeneously distribution, and more importantly, been completely enwrapped by well-developed anorthite crystals in the glaze, indicating that the signals recorded in previous publications are probably not from cobalt pigments themselves but from outside thickset anorthite shell. The further spectromicroscopic analyses confirm this presumption when the accurate spectra of cobalt aluminate pigment and surrounding anorthite were obtained separately with precise optical positioning. Accordingly, we reassess and clarify the previous Raman studies dedicated to cobalt blue pigment in ancient ceramics, e.g. cobalt blue in celadon glaze, and in turn demonstrate the superiority and necessity of coupling spectroscopic analysis with corresponding structure observation, especially in the characterization of pigments from complicated physico-chemical environment like antiquities. Thus, this study promotes a better understanding of Raman spectroscopy study of cobalt blue pigments in art and archaeology field.

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.

[Big data in official statistics].

Science.gov (United States)

Zwick, Markus

2015-08-01

The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.

Big-Leaf Mahogany on CITES Appendix II: Big Challenge, Big Opportunity

Science.gov (United States)

JAMES GROGAN; PAULO BARRETO

2005-01-01

On 15 November 2003, big-leaf mahogany (Swietenia macrophylla King, Meliaceae), the most valuable widely traded Neotropical timber tree, gained strengthened regulatory protection from its listing on Appendix II of the Convention on International Trade in Endangered Species ofWild Fauna and Flora (CITES). CITES is a United Nations-chartered agreement signed by 164...

Big Data as Information Barrier

Directory of Open Access Journals (Sweden)

Victor Ya. Tsvetkov

2014-07-01

Full Text Available The article covers analysis of ‘Big Data’ which has been discussed over last 10 years. The reasons and factors for the issue are revealed. It has proved that the factors creating ‘Big Data’ issue has existed for quite a long time, and from time to time, would cause the informational barriers. Such barriers were successfully overcome through the science and technologies. The conducted analysis refers the “Big Data” issue to a form of informative barrier. This issue may be solved correctly and encourages development of scientific and calculating methods.

Big Data in Space Science

OpenAIRE

Barmby, Pauline

2018-01-01

It seems like “big data” is everywhere these days. In planetary science and astronomy, we’ve been dealing with large datasets for a long time. So how “big” is our data? How does it compare to the big data that a bank or an airline might have? What new tools do we need to analyze big datasets, and how can we make better use of existing tools? What kinds of science problems can we address with these? I’ll address these questions with examples including ESA’s Gaia mission, ...

Blue Creek Winter Range: Wildlife Mitigation Project. Final environmental assessment

International Nuclear Information System (INIS)

1994-11-01

Bonneville Power Administration (BPA) proposes to fund that portion of the Washington Wildlife Agreement pertaining to the Blue Creek Winter Range Wildlife Mitigation Project (Project) in a cooperative effort with the Spokane Tribe, Upper Columbia United Tribes, and the Bureau of Indian Affairs (BIA). If fully implemented, the proposed action would allow the sponsors to protect and enhance 2,631 habitat units of big game winter range and riparian shrub habitat on 2,185 hectares (5,400 acres) of Spokane Tribal trust lands, and to conduct long term wildlife management activities within the Spokane Indian Reservation project area. This Final Environmental Assessment (EA) examines the potential environmental effects of securing land and conducting wildlife habitat enhancement and long term management activities within the boundaries of the Spokane Indian Reservation. Four proposed activities (habitat protection, habitat enhancement, operation and maintenance, and monitoring and evaluation) are analyzed. The proposed action is intended to meet the need for mitigation of wildlife and wildlife habitat adversely affected by the construction of Grand Coulee Dam and its reservoir

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

Main Issues in Big Data Security

Directory of Open Access Journals (Sweden)

Julio Moreno

2016-09-01

Full Text Available Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through the creation of a new paradigm: Big Data. However, Big Data originated new issues related not only to the volume or the variety of the data, but also to data security and privacy. In order to obtain a full perspective of the problem, we decided to carry out an investigation with the objective of highlighting the main issues regarding Big Data security, and also the solutions proposed by the scientific community to solve them. In this paper, we explain the results obtained after applying a systematic mapping study to security in the Big Data ecosystem. It is almost impossible to carry out detailed research into the entire topic of security, and the outcome of this research is, therefore, a big picture of the main problems related to security in a Big Data system, along with the principal solutions to them proposed by the research community.

Harnessing the Power of Big Data to Improve Graduate Medical Education: Big Idea or Bust?

Science.gov (United States)

Arora, Vineet M

2018-06-01

With the advent of electronic medical records (EMRs) fueling the rise of big data, the use of predictive analytics, machine learning, and artificial intelligence are touted as transformational tools to improve clinical care. While major investments are being made in using big data to transform health care delivery, little effort has been directed toward exploiting big data to improve graduate medical education (GME). Because our current system relies on faculty observations of competence, it is not unreasonable to ask whether big data in the form of clinical EMRs and other novel data sources can answer questions of importance in GME such as when is a resident ready for independent practice.The timing is ripe for such a transformation. A recent National Academy of Medicine report called for reforms to how GME is delivered and financed. While many agree on the need to ensure that GME meets our nation's health needs, there is little consensus on how to measure the performance of GME in meeting this goal. During a recent workshop at the National Academy of Medicine on GME outcomes and metrics in October 2017, a key theme emerged: Big data holds great promise to inform GME performance at individual, institutional, and national levels. In this Invited Commentary, several examples are presented, such as using big data to inform clinical experience and provide clinically meaningful data to trainees, and using novel data sources, including ambient data, to better measure the quality of GME training.

A SWOT Analysis of Big Data

Science.gov (United States)

Ahmadi, Mohammad; Dileepan, Parthasarati; Wheatley, Kathleen K.

2016-01-01

This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…

A survey of big data research

Science.gov (United States)

Fang, Hua; Zhang, Zhaoyang; Wang, Chanpaul Jin; Daneshmand, Mahmoud; Wang, Chonggang; Wang, Honggang

2015-01-01

Big data create values for business and research, but pose significant challenges in terms of networking, storage, management, analytics and ethics. Multidisciplinary collaborations from engineers, computer scientists, statisticians and social scientists are needed to tackle, discover and understand big data. This survey presents an overview of big data initiatives, technologies and research in industries and academia, and discusses challenges and potential solutions. PMID:26504265

Big Data in Action for Government : Big Data Innovation in Public Services, Policy, and Engagement

OpenAIRE

World Bank

2017-01-01

Governments have an opportunity to harness big data solutions to improve productivity, performance and innovation in service delivery and policymaking processes. In developing countries, governments have an opportunity to adopt big data solutions and leapfrog traditional administrative approaches

Unraveling the Mystery of the Blue Fog: Structure, Properties, and Applications of Amorphous Blue Phase III.

Science.gov (United States)

Gandhi, Sahil Sandesh; Chien, Liang-Chy

2017-12-01

The amorphous blue phase III of cholesteric liquid crystals, also known as the "blue fog," are among the rising stars in materials science that can potentially be used to develop next-generation displays with the ability to compete toe-to-toe with disruptive technologies like organic light-emitting diodes. The structure and properties of the practically unobservable blue phase III have eluded scientists for more than a century since it was discovered. This progress report reviews the developments in this field from both fundamental and applied research perspectives. The first part of this progress report gives an overview of the 130-years-long scientific tour-de-force that very recently resulted in the revelation of the mysterious structure of blue phase III. The second part reviews progress made in the past decade in developing electrooptical, optical, and photonic devices based on blue phase III. The strong and weak aspects of the development of these devices are underlined and criticized, respectively. The third- and-final part proposes ideas for further improvement in blue phase III technology to make it feasible for commercialization and widespread use. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel bioinformatics method for efficient knowledge discovery by BLSOM from big genomic sequence data.

Science.gov (United States)

Bai, Yu; Iwasaki, Yuki; Kanaya, Shigehiko; Zhao, Yue; Ikemura, Toshimichi

2014-01-01

With remarkable increase of genomic sequence data of a wide range of species, novel tools are needed for comprehensive analyses of the big sequence data. Self-Organizing Map (SOM) is an effective tool for clustering and visualizing high-dimensional data such as oligonucleotide composition on one map. By modifying the conventional SOM, we have previously developed Batch-Learning SOM (BLSOM), which allows classification of sequence fragments according to species, solely depending on the oligonucleotide composition. In the present study, we introduce the oligonucleotide BLSOM used for characterization of vertebrate genome sequences. We first analyzed pentanucleotide compositions in 100 kb sequences derived from a wide range of vertebrate genomes and then the compositions in the human and mouse genomes in order to investigate an efficient method for detecting differences between the closely related genomes. BLSOM can recognize the species-specific key combination of oligonucleotide frequencies in each genome, which is called a "genome signature," and the specific regions specifically enriched in transcription-factor-binding sequences. Because the classification and visualization power is very high, BLSOM is an efficient powerful tool for extracting a wide range of information from massive amounts of genomic sequences (i.e., big sequence data).

78 FR 3911 - Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN; Final Comprehensive...

Science.gov (United States)

2013-01-17

... DEPARTMENT OF THE INTERIOR Fish and Wildlife Service [FWS-R3-R-2012-N259; FXRS1265030000-134-FF03R06000] Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN; Final Comprehensive... significant impact (FONSI) for the environmental assessment (EA) for Big Stone National Wildlife Refuge...

Permeation of lysosomal membranes in the course of photo-sensitization with methylene blue and hematoporphyrin: study by cellular microspectrofluorometry

International Nuclear Information System (INIS)

Santus, R.; Kohen, C.; Kohen, E.; Morliere, P.; Dubertret, L.; Tocci, P.M.

1983-01-01

The photodynamically-induced liberation of lysosomal enzymes using β-galactosidase as marker for the lysosomal enzymes has been studied by microspectrofluorometry on mouse L cells. Similar studies have been carried out using N-acetyl-β-glucosaminidase as marker for the lysosomal enzymes of human fibroblasts. The high sensitivity of the fluorescence detection makes it possible to use 4-methylumbelliferyl substrates for the enzymes contained in a single cell. Methylene blue and hematoporphyrin readily incorporate into both cells and upon excitation, sensitize lysosomal membrane damages, leading to enzyme release accompanying strong morphological changes. (author)

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.

"Blue-Collar Blues" : kõigi maade töötud, ühinege! / Ants Juske

Index Scriptorium Estoniae

Juske, Ants, 1956-2016

2009-01-01

Rahvusvaheline näitus "Blue-Collar Blues" Tallinna Kunstihoones ja Kunstihoone galeriis 31. jaanuarini 2010. Kuraator Anders Härm. Näituse ajendiks on 1. juulist 2009 Eestis kehtima hakanud töölepinguseadus, näituse fookus on töösuhetel

New 'bigs' in cosmology

International Nuclear Information System (INIS)

Yurov, Artyom V.; Martin-Moruno, Prado; Gonzalez-Diaz, Pedro F.

2006-01-01

This paper contains a detailed discussion on new cosmic solutions describing the early and late evolution of a universe that is filled with a kind of dark energy that may or may not satisfy the energy conditions. The main distinctive property of the resulting space-times is that they make to appear twice the single singular events predicted by the corresponding quintessential (phantom) models in a manner which can be made symmetric with respect to the origin of cosmic time. Thus, big bang and big rip singularity are shown to take place twice, one on the positive branch of time and the other on the negative one. We have also considered dark energy and phantom energy accretion onto black holes and wormholes in the context of these new cosmic solutions. It is seen that the space-times of these holes would then undergo swelling processes leading to big trip and big hole events taking place on distinct epochs along the evolution of the universe. In this way, the possibility is considered that the past and future be connected in a non-paradoxical manner in the universes described by means of the new symmetric solutions

Glycoconjugates distribution during developing mouse spinal cord motor organizers.

Science.gov (United States)

Vojoudi, Elham; Ebrahimi, Vahid; Ebrahimzadeh-Bideskan, Alireza; Fazel, Alireza

2015-01-01

The aim of this research was to study the distribution and changes of glycoconjugates particularly their terminal sugars by using lectin histochemistry during mouse spinal cord development. Formalin-fixed sections of mouse embryo (10-16 fetal days) were processed for lectin histochemical method. In this study, two groups of horseradish peroxidase-labeled specific lectins were used: N-acetylgalactosamine, including Dolichos biflorus, Wisteria floribunda agglutinin (WFA), Vicia villosa, Glycine max as well as focuse-binding lectins, including tetragonolobus, Ulex europaeus, and Orange peel fungus (OFA). All sections were counterstained with alcian blue (pH 2.5). Our results showed that only WFA and OFA reacted strongly with the floor plate cells from early to late embryonic period of developing spinal cord. The strongest reactions were related to the 14, 15, and 16 days of tissue sections incubated with OFA and WFA lectins. The present study demonstrated that cellular and molecular differentiation of the spinal cord organizers is a wholly regulated process, and α-L-fucose, α-D-GalNAc, and α/β-D-GalNAc terminal sugars play a significant role during the prenatal spinal cord development.

2nd INNS Conference on Big Data

CERN Document Server

Manolopoulos, Yannis; Iliadis, Lazaros; Roy, Asim; Vellasco, Marley

2017-01-01

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.

Poporodní blues – česká adaptace dotazníku „Maternity blues questionnaire“

Czech Academy of Sciences Publication Activity Database

Takács, L.; Smolík, Filip; Mlíková Seidlerová, J.; Čepický, P.; Hoskovcová, S.

2016-01-01

Roč. 81, č. 5 (2016), s. 355-368 ISSN 1210-7832 Institutional support: RVO:68081740 Keywords : EPDS postpartum mood * Maternity Blues Questionnaire * postnatal depression * postpartum blues * postpartum depression Subject RIV: AN - Psychology

The ethics of biomedical big data

CERN Document Server

Mittelstadt, Brent Daniel

2016-01-01

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understan...

Scalable privacy-preserving big data aggregation mechanism

Directory of Open Access Journals (Sweden)

Dapeng Wu

2016-08-01

Full Text Available As the massive sensor data generated by large-scale Wireless Sensor Networks (WSNs recently become an indispensable part of ‘Big Data’, the collection, storage, transmission and analysis of the big sensor data attract considerable attention from researchers. Targeting the privacy requirements of large-scale WSNs and focusing on the energy-efficient collection of big sensor data, a Scalable Privacy-preserving Big Data Aggregation (Sca-PBDA method is proposed in this paper. Firstly, according to the pre-established gradient topology structure, sensor nodes in the network are divided into clusters. Secondly, sensor data is modified by each node according to the privacy-preserving configuration message received from the sink. Subsequently, intra- and inter-cluster data aggregation is employed during the big sensor data reporting phase to reduce energy consumption. Lastly, aggregated results are recovered by the sink to complete the privacy-preserving big data aggregation. Simulation results validate the efficacy and scalability of Sca-PBDA and show that the big sensor data generated by large-scale WSNs is efficiently aggregated to reduce network resource consumption and the sensor data privacy is effectively protected to meet the ever-growing application requirements.

Ethische aspecten van big data

NARCIS (Netherlands)

N. (Niek) van Antwerpen; Klaas Jan Mollema

2017-01-01

Big data heeft niet alleen geleid tot uitdagende technische vraagstukken, ook gaat het gepaard met allerlei nieuwe ethische en morele kwesties. Om verantwoord met big data om te gaan, moet ook over deze kwesties worden nagedacht. Want slecht datagebruik kan nadelige gevolgen hebben voor

Epidemiology in wonderland: Big Data and precision medicine.

Science.gov (United States)

Saracci, Rodolfo

2018-03-01

Big Data and precision medicine, two major contemporary challenges for epidemiology, are critically examined from two different angles. In Part 1 Big Data collected for research purposes (Big research Data) and Big Data used for research although collected for other primary purposes (Big secondary Data) are discussed in the light of the fundamental common requirement of data validity, prevailing over "bigness". Precision medicine is treated developing the key point that high relative risks are as a rule required to make a variable or combination of variables suitable for prediction of disease occurrence, outcome or response to treatment; the commercial proliferation of allegedly predictive tests of unknown or poor validity is commented. Part 2 proposes a "wise epidemiology" approach to: (a) choosing in a context imprinted by Big Data and precision medicine-epidemiological research projects actually relevant to population health, (b) training epidemiologists, (c) investigating the impact on clinical practices and doctor-patient relation of the influx of Big Data and computerized medicine and (d) clarifying whether today "health" may be redefined-as some maintain in purely technological terms.

Big Data and Analytics in Healthcare.

Science.gov (United States)

Tan, S S-L; Gao, G; Koch, S

2015-01-01

This editorial is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". The amount of data being generated in the healthcare industry is growing at a rapid rate. This has generated immense interest in leveraging the availability of healthcare data (and "big data") to improve health outcomes and reduce costs. However, the nature of healthcare data, and especially big data, presents unique challenges in processing and analyzing big data in healthcare. This Focus Theme aims to disseminate some novel approaches to address these challenges. More specifically, approaches ranging from efficient methods of processing large clinical data to predictive models that could generate better predictions from healthcare data are presented.

Big Data for Business Ecosystem Players

Directory of Open Access Journals (Sweden)

Perko Igor

2016-06-01

Full Text Available In the provided research, some of the Big Data most prospective usage domains connect with distinguished player groups found in the business ecosystem. Literature analysis is used to identify the state of the art of Big Data related research in the major domains of its use-namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement. System theory was used to identify business ecosystem major player types disrupted by Big Data: individuals, small and mid-sized enterprises, large organizations, information providers, and regulators. Relationships between the domains and players were explained through new Big Data opportunities and threats and by players’ responsive strategies. System dynamics was used to visualize relationships in the provided model.

"Big data" in economic history.

Science.gov (United States)

Gutmann, Myron P; Merchant, Emily Klancher; Roberts, Evan

2018-03-01

Big data is an exciting prospect for the field of economic history, which has long depended on the acquisition, keying, and cleaning of scarce numerical information about the past. This article examines two areas in which economic historians are already using big data - population and environment - discussing ways in which increased frequency of observation, denser samples, and smaller geographic units allow us to analyze the past with greater precision and often to track individuals, places, and phenomena across time. We also explore promising new sources of big data: organically created economic data, high resolution images, and textual corpora.

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.

GEOSS: Addressing Big Data Challenges

Science.gov (United States)

Nativi, S.; Craglia, M.; Ochiai, O.

2014-12-01

In the sector of Earth Observation, the explosion of data is due to many factors including: new satellite constellations, the increased capabilities of sensor technologies, social media, crowdsourcing, and the need for multidisciplinary and collaborative research to face Global Changes. In this area, there are many expectations and concerns about Big Data. Vendors have attempted to use this term for their commercial purposes. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This presentation tries to explore and discuss the impact of Big Data challenges and new capabilities on the Global Earth Observation System of Systems (GEOSS) and particularly on its common digital infrastructure called GCI. GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information at their desk. The impact of the Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on GEOSS is discussed. The main solutions and experimentation developed by GEOSS along these axes are introduced and analyzed. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the Earth Observation realm; its experience on Big Data is valuable for the many lessons learned.

Big data for bipolar disorder.

Science.gov (United States)

Monteith, Scott; Glenn, Tasha; Geddes, John; Whybrow, Peter C; Bauer, Michael

2016-12-01

The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

BIG DATA IN TAMIL: OPPORTUNITIES, BENEFITS AND CHALLENGES

OpenAIRE

R.S. Vignesh Raj; Babak Khazaei; Ashik Ali

2015-01-01

This paper gives an overall introduction on big data and has tried to introduce Big Data in Tamil. It discusses the potential opportunities, benefits and likely challenges from a very Tamil and Tamil Nadu perspective. The paper has also made original contribution by proposing the ‘big data’s’ terminology in Tamil. The paper further suggests a few areas to explore using big data Tamil on the lines of the Tamil Nadu Government ‘vision 2023’. Whilst, big data has something to offer everyone, it ...

Big data in biomedicine.

Science.gov (United States)

Costa, Fabricio F

2014-04-01

The increasing availability and growth rate of biomedical information, also known as 'big data', provides an opportunity for future personalized medicine programs that will significantly improve patient care. Recent advances in information technology (IT) applied to biomedicine are changing the landscape of privacy and personal information, with patients getting more control of their health information. Conceivably, big data analytics is already impacting health decisions and patient care; however, specific challenges need to be addressed to integrate current discoveries into medical practice. In this article, I will discuss the major breakthroughs achieved in combining omics and clinical health data in terms of their application to personalized medicine. I will also review the challenges associated with using big data in biomedicine and translational science. Copyright © 2013 Elsevier Ltd. All rights reserved.

76 FR 22923 - Wellpoint, Inc. D/B/A/Anthem Blue Cross & Blue Shield Enterprise Provider Data Management Team...

Science.gov (United States)

2011-04-25

.../B/A/Anthem Blue Cross & Blue Shield Enterprise Provider Data Management Team Including On-Site... & Blue Shield, Enterprise Provider Data Management Team, Including On-Site Leased Workers From Kelly... Of Kentucky, Enterprise Provider Data Management Team, Louisville, Kentucky TA-W-74,895B Wellpoint...

Big Data’s Role in Precision Public Health

Science.gov (United States)

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts. PMID:29594091

Big inquiry

Energy Technology Data Exchange (ETDEWEB)

Wynne, B [Lancaster Univ. (UK)

1979-06-28

The recently published report entitled 'The Big Public Inquiry' from the Council for Science and Society and the Outer Circle Policy Unit is considered, with especial reference to any future enquiry which may take place into the first commercial fast breeder reactor. Proposals embodied in the report include stronger rights for objectors and an attempt is made to tackle the problem that participation in a public inquiry is far too late to be objective. It is felt by the author that the CSS/OCPU report is a constructive contribution to the debate about big technology inquiries but that it fails to understand the deeper currents in the economic and political structure of technology which so influence the consequences of whatever formal procedures are evolved.

Fast Blue RR—Siloxane Derivatized Materials Indicate Wound Infection Due to a Deep Blue Color Development

Directory of Open Access Journals (Sweden)

Doris Schiffer

2015-09-01

Full Text Available There is a strong need for simple and fast methods for wound infection determination. Myeloperoxidase, an immune system-derived enzyme was found to be a suitable biomarker for wound infection. Hence, alkoxysilane-derivatized Fast Blue RR was immobilized via simple hydrolytic polymerization. The resulting enzyme-responsive siloxane layers were incubated with myeloperoxidase, wound fluid or hemoglobin. The reaction was monitored via HPLC measurements and the color development quantified spectrophotometrically. Myeloperoxidase was indeed able to oxidize immobilized Fast Blue RR leading to a blue colored product. No conversion was detected in non-infected wound fluids. The visible color changes of these novel materials towards blue enable an easy distinction between infected and non-infected wound fluids.

Big data analytics with R and Hadoop

CERN Document Server

Prajapati, Vignesh

2013-01-01

Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

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.

Genomic copy number analysis of a spectrum of blue nevi identifies recurrent aberrations of entire chromosomal arms in melanoma ex blue nevus.

Science.gov (United States)

Chan, May P; Andea, Aleodor A; Harms, Paul W; Durham, Alison B; Patel, Rajiv M; Wang, Min; Robichaud, Patrick; Fisher, Gary J; Johnson, Timothy M; Fullen, Douglas R

2016-03-01

Blue nevi may display significant atypia or undergo malignant transformation. Morphologic diagnosis of this spectrum of lesions is notoriously difficult, and molecular tools are increasingly used to improve diagnostic accuracy. We studied copy number aberrations in a cohort of cellular blue nevi, atypical cellular blue nevi, and melanomas ex blue nevi using Affymetrix's OncoScan platform. Cases with sufficient DNA were analyzed for GNAQ, GNA11, and HRAS mutations. Copy number aberrations were detected in 0 of 5 (0%) cellular blue nevi, 3 of 12 (25%) atypical cellular blue nevi, and 6 of 9 (67%) melanomas ex blue nevi. None of the atypical cellular blue nevi displayed more than one aberration, whereas complex aberrations involving four or more regions were seen exclusively in melanomas ex blue nevi. Gains and losses of entire chromosomal arms were identified in four of five melanomas ex blue nevi with copy number aberrations. In particular, gains of 1q, 4p, 6p, and 8q, and losses of 1p and 4q were each found in at least two melanomas. Whole chromosome aberrations were also common, and represented the sole finding in one atypical cellular blue nevus. When seen in melanomas, however, whole chromosome aberrations were invariably accompanied by partial aberrations of other chromosomes. Three melanomas ex blue nevi harbored aberrations, which were absent or negligible in their precursor components, suggesting progression in tumor biology. Gene mutations involving GNAQ and GNA11 were each detected in two of eight melanomas ex blue nevi. In conclusion, copy number aberrations are more common and often complex in melanomas ex blue nevi compared with cellular and atypical cellular blue nevi. Identification of recurrent gains and losses of entire chromosomal arms in melanomas ex blue nevi suggests that development of new probes targeting these regions may improve detection and risk stratification of these lesions.

NASA's Big Data Task Force

Science.gov (United States)

Holmes, C. P.; Kinter, J. L.; Beebe, R. F.; Feigelson, E.; Hurlburt, N. E.; Mentzel, C.; Smith, G.; Tino, C.; Walker, R. J.

2017-12-01

Two years ago NASA established the Ad Hoc Big Data Task Force (BDTF - https://science.nasa.gov/science-committee/subcommittees/big-data-task-force), an advisory working group with the NASA Advisory Council system. The scope of the Task Force included all NASA Big Data programs, projects, missions, and activities. The Task Force focused on such topics as exploring the existing and planned evolution of NASA's science data cyber-infrastructure that supports broad access to data repositories for NASA Science Mission Directorate missions; best practices within NASA, other Federal agencies, private industry and research institutions; and Federal initiatives related to big data and data access. The BDTF has completed its two-year term and produced several recommendations plus four white papers for NASA's Science Mission Directorate. This presentation will discuss the activities and results of the TF including summaries of key points from its focused study topics. The paper serves as an introduction to the papers following in this ESSI session.

Big Data Technologies

Science.gov (United States)

Bellazzi, Riccardo; Dagliati, Arianna; Sacchi, Lucia; Segagni, Daniele

2015-01-01

The so-called big data revolution provides substantial opportunities to diabetes management. At least 3 important directions are currently of great interest. First, the integration of different sources of information, from primary and secondary care to administrative information, may allow depicting a novel view of patient’s care processes and of single patient’s behaviors, taking into account the multifaceted nature of chronic care. Second, the availability of novel diabetes technologies, able to gather large amounts of real-time data, requires the implementation of distributed platforms for data analysis and decision support. Finally, the inclusion of geographical and environmental information into such complex IT systems may further increase the capability of interpreting the data gathered and extract new knowledge from them. This article reviews the main concepts and definitions related to big data, it presents some efforts in health care, and discusses the potential role of big data in diabetes care. Finally, as an example, it describes the research efforts carried on in the MOSAIC project, funded by the European Commission. PMID:25910540

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.

The lithium abundance of M67 blue stragglers - A constraint on the blue straggler phenomenon

International Nuclear Information System (INIS)

Pritchet, C.J.; Glaspey, J.W.

1991-01-01

Upper limits have been placed on the line strength of the 6707 A Li I resonance doublet in seven blue stragglers in M67. The corresponding upper limits on abundances range from log N(Li) less than about 1.3 to less than about 2.3. This result is significantly below the level of log N(Li) about 3.1 + or - 0.1 found in field main-sequence stars of comparable temperature. It is concluded that some form of mixing has affected the outer envelopes of blue stragglers. (Such mixing has been proposed as the mechanism needed to prolong the lifetimes of blue stragglers relative to normal main-sequence stars at the same luminosity). Virtually all mechanisms for the production of blue stragglers other than mixing, binary mass transfer, or binary coalescence appear to be ruled out by the present observations. 45 refs

Traffic information computing platform for big data

Energy Technology Data Exchange (ETDEWEB)

Duan, Zongtao, E-mail: ztduan@chd.edu.cn; Li, Ying, E-mail: ztduan@chd.edu.cn; Zheng, Xibin, E-mail: ztduan@chd.edu.cn; Liu, Yan, E-mail: ztduan@chd.edu.cn; Dai, Jiting, E-mail: ztduan@chd.edu.cn; Kang, Jun, E-mail: ztduan@chd.edu.cn [Chang' an University School of Information Engineering, Xi' an, China and Shaanxi Engineering and Technical Research Center for Road and Traffic Detection, Xi' an (China)

2014-10-06

Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.

Traffic information computing platform for big data

International Nuclear Information System (INIS)

Duan, Zongtao; Li, Ying; Zheng, Xibin; Liu, Yan; Dai, Jiting; Kang, Jun

2014-01-01

Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users

Fremtidens landbrug bliver big business

DEFF Research Database (Denmark)

Hansen, Henning Otte

2016-01-01

Landbrugets omverdensforhold og konkurrencevilkår ændres, og det vil nødvendiggøre en udvikling i retning af “big business“, hvor landbrugene bliver endnu større, mere industrialiserede og koncentrerede. Big business bliver en dominerende udvikling i dansk landbrug - men ikke den eneste...

Quantum nature of the big bang.

Science.gov (United States)

Ashtekar, Abhay; Pawlowski, Tomasz; Singh, Parampreet

2006-04-14

Some long-standing issues concerning the quantum nature of the big bang are resolved in the context of homogeneous isotropic models with a scalar field. Specifically, the known results on the resolution of the big-bang singularity in loop quantum cosmology are significantly extended as follows: (i) the scalar field is shown to serve as an internal clock, thereby providing a detailed realization of the "emergent time" idea; (ii) the physical Hilbert space, Dirac observables, and semiclassical states are constructed rigorously; (iii) the Hamiltonian constraint is solved numerically to show that the big bang is replaced by a big bounce. Thanks to the nonperturbative, background independent methods, unlike in other approaches the quantum evolution is deterministic across the deep Planck regime.

Mentoring in Schools: An Impact Study of Big Brothers Big Sisters School-Based Mentoring

Science.gov (United States)

Herrera, Carla; Grossman, Jean Baldwin; Kauh, Tina J.; McMaken, Jennifer

2011-01-01

This random assignment impact study of Big Brothers Big Sisters School-Based Mentoring involved 1,139 9- to 16-year-old students in 10 cities nationwide. Youth were randomly assigned to either a treatment group (receiving mentoring) or a control group (receiving no mentoring) and were followed for 1.5 school years. At the end of the first school…

Lean Big Data integration in systems biology and systems pharmacology.

Science.gov (United States)

Ma'ayan, Avi; Rouillard, Andrew D; Clark, Neil R; Wang, Zichen; Duan, Qiaonan; Kou, Yan

2014-09-01

Data sets from recent large-scale projects can be integrated into one unified puzzle that can provide new insights into how drugs and genetic perturbations applied to human cells are linked to whole-organism phenotypes. Data that report how drugs affect the phenotype of human cell lines and how drugs induce changes in gene and protein expression in human cell lines can be combined with knowledge about human disease, side effects induced by drugs, and mouse phenotypes. Such data integration efforts can be achieved through the conversion of data from the various resources into single-node-type networks, gene-set libraries, or multipartite graphs. This approach can lead us to the identification of more relationships between genes, drugs, and phenotypes as well as benchmark computational and experimental methods. Overall, this lean 'Big Data' integration strategy will bring us closer toward the goal of realizing personalized medicine. Copyright © 2014 Elsevier Ltd. All rights reserved.

Big data processing in the cloud - Challenges and platforms

Science.gov (United States)

Zhelev, Svetoslav; Rozeva, Anna

2017-12-01

Choosing the appropriate architecture and technologies for a big data project is a difficult task, which requires extensive knowledge in both the problem domain and in the big data landscape. The paper analyzes the main big data architectures and the most widely implemented technologies used for processing and persisting big data. Clouds provide for dynamic resource scaling, which makes them a natural fit for big data applications. Basic cloud computing service models are presented. Two architectures for processing big data are discussed, Lambda and Kappa architectures. Technologies for big data persistence are presented and analyzed. Stream processing as the most important and difficult to manage is outlined. The paper highlights main advantages of cloud and potential problems.

Ecology of blue straggler stars

CERN Document Server

Carraro, Giovanni; Beccari, Giacomo

2015-01-01

The existence of blue straggler stars, which appear younger, hotter, and more massive than their siblings, is at odds with a simple picture of stellar evolution. Such stars should have exhausted their nuclear fuel and evolved long ago to become cooling white dwarfs. They are found to exist in globular clusters, open clusters, dwarf spheroidal galaxies of the Local Group, OB associations and as field stars. This book summarises the many advances in observational and theoretical work dedicated to blue straggler stars. Carefully edited extended contributions by well-known experts in the field cover all the relevant aspects of blue straggler stars research: Observations of blue straggler stars in their various environments; Binary stars and formation channels; Dynamics of globular clusters; Interpretation of observational data and comparison with models. The book also offers an introductory chapter on stellar evolution written by the editors of the book.

Ethics and Epistemology in Big Data Research.

Science.gov (United States)

Lipworth, Wendy; Mason, Paul H; Kerridge, Ian; Ioannidis, John P A

2017-12-01

Biomedical innovation and translation are increasingly emphasizing research using "big data." The hope is that big data methods will both speed up research and make its results more applicable to "real-world" patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals.

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...

Big Data: Concept, Potentialities and Vulnerabilities

Directory of Open Access Journals (Sweden)

Fernando Almeida

2018-03-01

Full Text Available The evolution of information systems and the growth in the use of the Internet and social networks has caused an explosion in the amount of available data relevant to the activities of the companies. Therefore, the treatment of these available data is vital to support operational, tactical and strategic decisions. This paper aims to present the concept of big data and the main technologies that support the analysis of large data volumes. The potential of big data is explored considering nine sectors of activity, such as financial, retail, healthcare, transports, agriculture, energy, manufacturing, public, and media and entertainment. In addition, the main current opportunities, vulnerabilities and privacy challenges of big data are discussed. It was possible to conclude that despite the potential for using the big data to grow in the previously identified areas, there are still some challenges that need to be considered and mitigated, namely the privacy of information, the existence of qualified human resources to work with Big Data and the promotion of a data-driven organizational culture.

Big data analytics a management perspective

CERN Document Server

Corea, Francesco

2016-01-01

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth st...

Human factors in Big Data

NARCIS (Netherlands)

Boer, J. de

2016-01-01

Since 2014 I am involved in various (research) projects that try to make the hype around Big Data more concrete and tangible for the industry and government. Big Data is about multiple sources of (real-time) data that can be analysed, transformed to information and be used to make 'smart' decisions.

Slaves to Big Data. Or Are We?

Directory of Open Access Journals (Sweden)

Mireille Hildebrandt

2013-10-01

Full Text Available

In this contribution, the notion of Big Data is discussed in relation to the monetisation of personal data. The claim of some proponents, as well as adversaries, that Big Data implies that ‘n = all’, meaning that we no longer need to rely on samples because we have all the data, is scrutinised and found to be both overly optimistic and unnecessarily pessimistic. A set of epistemological and ethical issues is presented, focusing on the implications of Big Data for our perception, cognition, fairness, privacy and due process. The article then looks into the idea of user-centric personal data management to investigate to what extent it provides solutions for some of the problems triggered by the Big Data conundrum. Special attention is paid to the core principle of data protection legislation, namely purpose binding. Finally, this contribution seeks to inquire into the influence of Big Data politics on self, mind and society, and asks how we can prevent ourselves from becoming slaves to Big Data.

Natural Blue Food Colour

DEFF Research Database (Denmark)

Roda-Serrat, Maria Cinta

In recent years, there has been a growing tendency to avoid the use of artificial colorants and additives in food products, especially after some studies linked their consumption with behavioural changes in children. However, the incorporation of colorants from natural origin remains a challenge...... for food technologists, as these are typically less vivid and less stable than their synthetic alternatives. Regarding blue colorants, phycocyanins from cyanobacteria are currently in the spotlight as promising new natural blue colorants. Phycocyanins are proteins which blue colour results from...... the presence of the chromophore phycocyanobilin (PCB), a covalently attached linear tetrapyrrole. The applications of phycocyanins as food colorants are however limited, as they show poor stability in certain conditions of pH, light and temperature. Cleavage of PCB from the protein followed by careful product...

Will Organization Design Be Affected By Big Data?

Directory of Open Access Journals (Sweden)

Giles Slinger

2014-12-01

Full Text Available Computing power and analytical methods allow us to create, collate, and analyze more data than ever before. When datasets are unusually large in volume, velocity, and variety, they are referred to as “big data.” Some observers have suggested that in order to cope with big data (a organizational structures will need to change and (b the processes used to design organizations will be different. In this article, we differentiate big data from relatively slow-moving, linked people data. We argue that big data will change organizational structures as organizations pursue the opportunities presented by big data. The processes by which organizations are designed, however, will be relatively unaffected by big data. Instead, organization design processes will be more affected by the complex links found in people data.

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.

Big Data

OpenAIRE

Bútora, Matúš

2017-01-01

Cieľom bakalárskej práca je popísať problematiku Big Data a agregačné operácie OLAP pre podporu rozhodovania, ktoré sú na ne aplikované pomocou technológie Apache Hadoop. Prevažná časť práce je venovaná popisu práve tejto technológie. Posledná kapitola sa zaoberá spôsobom aplikovania agregačných operácií a problematikou ich realizácie. Nasleduje celkové zhodnotenie práce a možnosti využitia výsledného systému do budúcna. The aim of the bachelor thesis is to describe the Big Data issue and ...

Identification of muscle necrosis in the mdx mouse model of Duchenne muscular dystrophy using three-dimensional optical coherence tomography

Science.gov (United States)

Klyen, Blake R.; Shavlakadze, Thea; Radley-Crabb, Hannah G.; Grounds, Miranda D.; Sampson, David D.

2011-07-01

Three-dimensional optical coherence tomography (3D-OCT) was used to image the structure and pathology of skeletal muscle tissue from the treadmill-exercised mdx mouse model of human Duchenne muscular dystrophy. Optical coherence tomography (OCT) images of excised muscle samples were compared with co-registered hematoxylin and eosin-stained and Evans blue dye fluorescence histology. We show, for the first time, structural 3D-OCT images of skeletal muscle dystropathology well correlated with co-located histology. OCT could identify morphological features of interest and necrotic lesions within the muscle tissue samples based on intrinsic optical contrast. These findings demonstrate the utility of 3D-OCT for the evaluation of small-animal skeletal muscle morphology and pathology, particularly for studies of mouse models of muscular dystrophy.

BigDansing

KAUST Repository

Khayyat, Zuhair; Ilyas, Ihab F.; Jindal, Alekh; Madden, Samuel; Ouzzani, Mourad; Papotti, Paolo; Quiané -Ruiz, Jorge-Arnulfo; Tang, Nan; Yin, Si

2015-01-01

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

Leveraging Mobile Network Big Data for Developmental Policy ...

International Development Research Centre (IDRC) Digital Library (Canada)

Some argue that big data and big data users offer advantages to generate evidence. ... Supported by IDRC, this research focused on transportation planning in urban ... Using mobile network big data for land use classification CPRsouth 2015.

Can greening of aquaculture sequester blue carbon?

Science.gov (United States)

Ahmed, Nesar; Bunting, Stuart W; Glaser, Marion; Flaherty, Mark S; Diana, James S

2017-05-01

Globally, blue carbon (i.e., carbon in coastal and marine ecosystems) emissions have been seriously augmented due to the devastating effects of anthropogenic pressures on coastal ecosystems including mangrove swamps, salt marshes, and seagrass meadows. The greening of aquaculture, however, including an ecosystem approach to Integrated Aquaculture-Agriculture (IAA) and Integrated Multi-Trophic Aquaculture (IMTA) could play a significant role in reversing this trend, enhancing coastal ecosystems, and sequestering blue carbon. Ponds within IAA farming systems sequester more carbon per unit area than conventional fish ponds, natural lakes, and inland seas. The translocation of shrimp culture from mangrove swamps to offshore IMTA could reduce mangrove loss, reverse blue carbon emissions, and in turn increase storage of blue carbon through restoration of mangroves. Moreover, offshore IMTA may create a barrier to trawl fishing which in turn could help restore seagrasses and further enhance blue carbon sequestration. Seaweed and shellfish culture within IMTA could also help to sequester more blue carbon. The greening of aquaculture could face several challenges that need to be addressed in order to realize substantial benefits from enhanced blue carbon sequestration and eventually contribute to global climate change mitigation.

Practice Variation in Big-4 Transparency Reports

DEFF Research Database (Denmark)

Girdhar, Sakshi; Klarskov Jeppesen, Kim

2018-01-01

Purpose: The purpose of this paper is to examine the transparency reports published by the Big-4 public accounting firms in the UK, Germany and Denmark to understand the determinants of their content within the networks of big accounting firms. Design/methodology/approach: The study draws...... on a qualitative research approach, in which the content of transparency reports is analyzed and semi-structured interviews are conducted with key people from the Big-4 firms who are responsible for developing the transparency reports. Findings: The findings show that the content of transparency reports...... is inconsistent and the transparency reporting practice is not uniform within the Big-4 networks. Differences were found in the way in which the transparency reporting practices are coordinated globally by the respective central governing bodies of the Big-4. The content of the transparency reports...

The fading of irradiated blue-colored pearls

International Nuclear Information System (INIS)

Okamoto, Shinichi

1982-01-01

The fading of irradiated and natural blue-colored pearls was investigated in this experiment. Thirty natural blue-colored pearls and sixty irradiated blue-colored pearls were used. Some of them were placed at a light position of RT. Another pearls were placed at a dark position of 50 0 C. The irradiated pearls placed at a light position of RT didn't show remarkable fading in their color in 294 days. But the natural blue-colored pearls showed a little recovery from 4% to 8% in reflection factors in 223 days at RT. The irradiated pearls placed at a dark position of 50 0 C showed the recovery from 9% to 14% in 264 days independently of irradiation times. The natural blue-colored pearls also showed the bleaching from 5% to 10% in reflection factor in 86 days at 50 0 C. Both irradiated and natural blue-colored pearls hardly showed their remarkable changes in their chromaticities independently of temperatures. (author)

Blue space geographies: Enabling health in place.

Science.gov (United States)

Foley, Ronan; Kistemann, Thomas

2015-09-01

Drawing from research on therapeutic landscapes and relationships between environment, health and wellbeing, we propose the idea of 'healthy blue space' as an important new development Complementing research on healthy green space, blue space is defined as; 'health-enabling places and spaces, where water is at the centre of a range of environments with identifiable potential for the promotion of human wellbeing'. Using theoretical ideas from emotional and relational geographies and critical understandings of salutogenesis, the value of blue space to health and wellbeing is recognised and evaluated. Six individual papers from five different countries consider how health can be enabled in mixed blue space settings. Four sub-themes; embodiment, inter-subjectivity, activity and meaning, document multiple experiences within a range of healthy blue spaces. Finally, we suggest a considerable research agenda - theoretical, methodological and applied - for future work within different forms of blue space. All are suggested as having public health policy relevance in social and public space. Copyright © 2015 Elsevier Ltd. All rights reserved.

Big data and biomedical informatics: a challenging opportunity.

Science.gov (United States)

Bellazzi, R

2014-05-22

Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations.

Was the big bang hot

International Nuclear Information System (INIS)

Wright, E.L.

1983-01-01

The author considers experiments to confirm the substantial deviations from a Planck curve in the Woody and Richards spectrum of the microwave background, and search for conducting needles in our galaxy. Spectral deviations and needle-shaped grains are expected for a cold Big Bang, but are not required by a hot Big Bang. (Auth.)

Passport to the Big Bang

CERN Multimedia

De Melis, Cinzia

2013-01-01

Le 2 juin 2013, le CERN inaugure le projet Passeport Big Bang lors d'un grand événement public. Affiche et programme. On 2 June 2013 CERN launches a scientific tourist trail through the Pays de Gex and the Canton of Geneva known as the Passport to the Big Bang. Poster and Programme.

Starbursts in Blue compact dwarf galaxies

International Nuclear Information System (INIS)

Thuan, T.X.

1987-01-01

We summarize all the arguments for a bursting mode of star formation in blue compact dwarf galaxies. We show in particular how spectral synthesis of far ultraviolet spectra of Blue compact dwarf galaxy constitutes a powerful way for studying the star formation history in these galaxies. Blue compact dwarf galaxy luminosity functions show jumps and discontinuities. These jumps act like fossil records of the star-forming bursts, helping us to count and date the bursts

Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

Science.gov (United States)

Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva

2017-01-01

No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as

Hubble's View of Little Blue Dots

Science.gov (United States)

Kohler, Susanna

2018-02-01

The recent discovery of a new type of tiny, star-forming galaxy is the latest in a zoo of detections shedding light on our early universe. What can we learn from the unique little blue dots found in archival Hubble data?Peas, Berries, and DotsGreen pea galaxies identified by citizen scientists with Galaxy Zoo. [Richard Nowell Carolin Cardamone]As telescope capabilities improve and we develop increasingly deeper large-scale surveys of our universe, we continue to learn more about small, faraway galaxies. In recent years, increasing sensitivity first enabled the detection of green peas luminous, compact, low-mass (10 billion solar masses; compare this to the Milky Ways 1 trillion solar masses!) galaxies with high rates of star formation.Not long thereafter, we discovered galaxies that form stars similarly rapidly, but are even smaller only 330 million solar masses, spanning less than 3,000 light-years in size. These tiny powerhouses were termed blueberries for their distinctive color.Now, scientists Debra and Bruce Elmegreen (of Vassar College and IBM Research Division, respectively) report the discovery of galaxies that have even higher star formation rates and even lower masses: little blue dots.Exploring Tiny Star FactoriesThe Elmegreens discovered these unique galaxies by exploring archival Hubble data. The Hubble Frontier Fields data consist of deep images of six distant galaxy clusters and the parallel fields next to them. It was in the archival data for two Frontier Field Parallels, those for clusters Abell 2744 and MAS J0416.1-2403, that the authors noticed several galaxies that stand out as tiny, bright, blue objects that are nearly point sources.Top: a few examples of the little blue dots recently identified in two Hubble Frontier Field Parallels. Bottom: stacked images for three different groups of little blue dots. [Elmegreen Elmegreen 2017]The authors performed a search through the two Frontier Field Parallels, discovering a total of 55 little blue dots

Keynote: Big Data, Big Opportunities

OpenAIRE

Borgman, Christine L.

2014-01-01

The enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the challenges for stewardship. Inside the black box of data are a plethora of research, technology, and policy issues. Data are not shiny objects that are easily exchanged. Rather, data are representations of observations, objects, or other entities used as evidence of phenomena for the purposes of research or scholarship. Data practices are local, varying from field to field, individual to indiv...

Integrating R and Hadoop for Big Data Analysis

OpenAIRE

Bogdan Oancea; Raluca Mariana Dragoescu

2014-01-01

Analyzing and working with big data could be very diffi cult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with hundreds or even thousands of computing nodes. Offi cial statistics is increasingly considering big data for deriving new statistics because big data sources could produce more relevant and timely statistics than traditional sources. One of the software tools ...

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.

Big³. Editorial.

Science.gov (United States)

Lehmann, C U; Séroussi, B; Jaulent, M-C

2014-05-22

To provide an editorial introduction into the 2014 IMIA Yearbook of Medical Informatics with an overview of the content, the new publishing scheme, and upcoming 25th anniversary. A brief overview of the 2014 special topic, Big Data - Smart Health Strategies, and an outline of the novel publishing model is provided in conjunction with a call for proposals to celebrate the 25th anniversary of the Yearbook. 'Big Data' has become the latest buzzword in informatics and promise new approaches and interventions that can improve health, well-being, and quality of life. This edition of the Yearbook acknowledges the fact that we just started to explore the opportunities that 'Big Data' will bring. However, it will become apparent to the reader that its pervasive nature has invaded all aspects of biomedical informatics - some to a higher degree than others. It was our goal to provide a comprehensive view at the state of 'Big Data' today, explore its strengths and weaknesses, as well as its risks, discuss emerging trends, tools, and applications, and stimulate the development of the field through the aggregation of excellent survey papers and working group contributions to the topic. For the first time in history will the IMIA Yearbook be published in an open access online format allowing a broader readership especially in resource poor countries. For the first time, thanks to the online format, will the IMIA Yearbook be published twice in the year, with two different tracks of papers. We anticipate that the important role of the IMIA yearbook will further increase with these changes just in time for its 25th anniversary in 2016.

[Octanol preconditioning alleviates mouse cardiomyocyte swelling induced by simulated ischemia/reperfusion challenge in vitro].

Science.gov (United States)

Luo, Yukun; Fang, Jun; Fan, Lin; Lin, Chaogui; Chen, Zhaoyang; Chen, Lianglong

2012-10-01

To investigate the role of connexin 43-formed hemichannels in cell volume regulation induced by simulated ischemia/reperfusion (SI/R). Mouse cardiomyocytes isolated on a Langendorff apparatus with enzyme solution were aliquoted into control, SI/R and SI/R +octanol groups. Calcein-AM was used to stain the cells and the cell volume was measured with confocal microscope by stack scanning. Trypan blue was used to measure the cell viability after the treatments. Calcein-AM staining and cofocal microscopy yielded stable and reproducible results for cell volume measurement. Mouse cardiomyocytes subjected to simulated SI/R showed obvious cell swelling as compared with the control cells [(126∓6)% vs 100%, Poctanol preconditioning significantly attenuated the cell swelling [(113∓6)%, Poctanol preconditioning obviously reduced the viability of the cells with SI/R challenge [(31∓2)%, Poctanol can alleviate the cell swelling to enhance the viability of the cardiomyocytes following SI/R.

Cloud Based Big Data Infrastructure: Architectural Components and Automated Provisioning

OpenAIRE

Demchenko, Yuri; Turkmen, Fatih; Blanchet, Christophe; Loomis, Charles; Laat, Caees de

2016-01-01

This paper describes the general architecture and functional components of the cloud based Big Data Infrastructure (BDI). The proposed BDI architecture is based on the analysis of the emerging Big Data and data intensive technologies and supported by the definition of the Big Data Architecture Framework (BDAF) that defines the following components of the Big Data technologies: Big Data definition, Data Management including data lifecycle and data structures, Big Data Infrastructure (generical...

Physics with Big Karl Brainstorming. Abstracts

International Nuclear Information System (INIS)

Machner, H.; Lieb, J.

2000-08-01

Before summarizing details of the meeting, a short description of the spectrometer facility Big Karl is given. The facility is essentially a new instrument using refurbished dipole magnets from its predecessor. The large acceptance quadrupole magnets and the beam optics are new. Big Karl has a design very similar as the focussing spectrometers at MAMI (Mainz), AGOR (Groningen) and the high resolution spectrometer (HRS) in Hall A at Jefferson Laboratory with ΔE/E = 10 -4 but at some lower maximum momentum. The focal plane detectors consisting of multiwire drift chambers and scintillating hodoscopes are similar. Unlike HRS, Big Karl still needs Cerenkov counters and polarimeters in its focal plane; detectors which are necessary to perform some of the experiments proposed during the brainstorming. In addition, BIG KARL allows emission angle reconstruction via track measurements in its focal plane with high resolution. In the following the physics highlights, the proposed and potential experiments are summarized. During the meeting it became obvious that the physics to be explored at Big Karl can be grouped into five distinct categories, and this summary is organized accordingly. (orig.)

Variable blue straggler stars in NGC 5466

International Nuclear Information System (INIS)

Harris, H.C.; Mateo, M.; Olszewski, E.W.; Nemec, J.M.

1990-01-01

Nine variable blue stragglers have been found in the globular cluster NGC 5466. The six dwarf Cepheids in this cluster coexist in the instability strip with other nonvariable stars. The three eclipsing binaries are among the hottest of the blue stragglers. The hypothesis is discussed that all blue stragglers in this cluster have undergone mass transfer in close binaries. Under this hypothesis, rotation and spin-down play important roles in controlling the evolution of blue stragglers in old clusters and in affecting some of their observational properties. 14 refs

Seed bank and big sagebrush plant community composition in a range margin for big sagebrush

Science.gov (United States)

Martyn, Trace E.; Bradford, John B.; Schlaepfer, Daniel R.; Burke, Ingrid C.; Laurenroth, William K.

2016-01-01

The potential influence of seed bank composition on range shifts of species due to climate change is unclear. Seed banks can provide a means of both species persistence in an area and local range expansion in the case of increasing habitat suitability, as may occur under future climate change. However, a mismatch between the seed bank and the established plant community may represent an obstacle to persistence and expansion. In big sagebrush (Artemisia tridentata) plant communities in Montana, USA, we compared the seed bank to the established plant community. There was less than a 20% similarity in the relative abundance of species between the established plant community and the seed bank. This difference was primarily driven by an overrepresentation of native annual forbs and an underrepresentation of big sagebrush in the seed bank compared to the established plant community. Even though we expect an increase in habitat suitability for big sagebrush under future climate conditions at our sites, the current mismatch between the plant community and the seed bank could impede big sagebrush range expansion into increasingly suitable habitat in the future.

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.

Big Data in food and agriculture

Directory of Open Access Journals (Sweden)

Kelly Bronson

2016-06-01

Full Text Available Farming is undergoing a digital revolution. Our existing review of current Big Data applications in the agri-food sector has revealed several collection and analytics tools that may have implications for relationships of power between players in the food system (e.g. between farmers and large corporations. For example, Who retains ownership of the data generated by applications like Monsanto Corproation's Weed I.D . “app”? Are there privacy implications with the data gathered by John Deere's precision agricultural equipment? Systematically tracing the digital revolution in agriculture, and charting the affordances as well as the limitations of Big Data applied to food and agriculture, should be a broad research goal for Big Data scholarship. Such a goal brings data scholarship into conversation with food studies and it allows for a focus on the material consequences of big data in society.

Big data optimization recent developments and challenges

CERN Document Server

2016-01-01

The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

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...

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.

Big Data Analytic, Big Step for Patient Management and Care in Puerto Rico.

Science.gov (United States)

Borrero, Ernesto E

2018-01-01

This letter provides an overview of the application of big data in health care system to improve quality of care, including predictive modelling for risk and resource use, precision medicine and clinical decision support, quality of care and performance measurement, public health and research applications, among others. The author delineates the tremendous potential for big data analytics and discuss how it can be successfully implemented in clinical practice, as an important component of a learning health-care system.

Molecular evidence for the subspecific differentiation of blue sheep (Pseudois nayaur) and polyphyletic origin of dwarf blue sheep (Pseudois schaeferi).

Science.gov (United States)

Tan, Shuai; Zou, Dandan; Tang, Lei; Wang, Gaochao; Peng, Quekun; Zeng, Bo; Zhang, Chen; Zou, Fangdong

2012-06-01

Blue sheep (Pseudois nayaur), a Central Asian ungulate with restricted geographic distribution, exhibits unclear variation in morphology and phylogeographic structure. The composition of species and subspecies in the genus Pseudois is controversial, particularly with respect to the taxonomic designation of geographically restricted populations. Here, 26 specimens including 5 dwarf blue sheep (Pseudois schaeferi), which were collected from a broad geographic region in China, were analyzed for 2 mitochondrial DNA fragments (cytochrome b and control region sequences). In a pattern consistent with geographically defined subspecies, we found three deeply divergent mitochondrial lineages restricted to different geographic regions. The currently designated two subspecies of blue sheep, Pseudois nayaur nayaur and Pseudois nayaur szechuanensis, were recognized in the phylogenetic trees. In addition, the Helan Mountain population showed distinct genetic characteristics from other geographic populations, and thus should be classified as a new subspecies. In contrast, dwarf blue sheep clustered closely with some blue sheep from Sichuan Province in the phylogenetic trees. Therefore, dwarf blue sheep appear to be a subset of Pseudois nayaur szechuanensis. After considering both population genetic information and molecular clock analysis, we obtained some relevant molecular phylogeographic information concerning the historical biogeography of blue sheep. These results also indicate that western Sichuan was a potential refugium for blue sheep during the Quaternary period.

Big Data and Biomedical Informatics: A Challenging Opportunity

Science.gov (United States)

2014-01-01

Summary Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations. PMID:24853034

Big data governance an emerging imperative

CERN Document Server

Soares, Sunil

2012-01-01

Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management-big data and information governance-by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes,

Big Data and historical social science

Directory of Open Access Journals (Sweden)

Peter Bearman

2015-11-01

Full Text Available “Big Data” can revolutionize historical social science if it arises from substantively important contexts and is oriented towards answering substantively important questions. Such data may be especially important for answering previously largely intractable questions about the timing and sequencing of events, and of event boundaries. That said, “Big Data” makes no difference for social scientists and historians whose accounts rest on narrative sentences. Since such accounts are the norm, the effects of Big Data on the practice of historical social science may be more limited than one might wish.

The Inverted Big-Bang

OpenAIRE

Vaas, Ruediger

2004-01-01

Our universe appears to have been created not out of nothing but from a strange space-time dust. Quantum geometry (loop quantum gravity) makes it possible to avoid the ominous beginning of our universe with its physically unrealistic (i.e. infinite) curvature, extreme temperature, and energy density. This could be the long sought after explanation of the big-bang and perhaps even opens a window into a time before the big-bang: Space itself may have come from an earlier collapsing universe tha...

Minsky on "Big Government"

Directory of Open Access Journals (Sweden)

Daniel de Santana Vasconcelos

2014-03-01

Full Text Available This paper objective is to assess, in light of the main works of Minsky, his view and analysis of what he called the "Big Government" as that huge institution which, in parallels with the "Big Bank" was capable of ensuring stability in the capitalist system and regulate its inherently unstable financial system in mid-20th century. In this work, we analyze how Minsky proposes an active role for the government in a complex economic system flawed by financial instability.

The discrimination of (non-denim) blue cotton.

Science.gov (United States)

Palmer, Ray; Hutchinson, William; Fryer, Verity

2009-03-01

This study was conducted to determine the degree of discrimination obtained between non-denim blue cotton fibres using visible-UV range microspectrophotometry alone. To this end, samples of fibres were taken from 100, nondenim, blue cotton, outer garments, including t-shirts, trousers and jumpers and subjected to analysis by both visible and UV range microspectrophotometry. The results obtained from the samples of each garment were compared to determine if they 'matched' or not. From an initial visual comparison of the garments it was possible to subdivide the samples into two populations consisting of 73 'dark blue' garments and 27 'mid-blue' garments. It was found that of the 73 'dark blue' garments, 22 distinct sub-populations could be distinguished using visible range MSP, this figure being increased to 43 when the analysis was extended into the UVW range. In the case of the 27 'mid-blue' garments, 9 distinct sub-populations were discriminated using visible range MSP, this figure being increased to 17 when the analysis was extended into the UV range. The discriminating power (i.e., the number of discriminated pairs divided by the number of possible pairs) of visible range microspectrophotometry was calculated as 0.89 for 'mid-blue' garments and 0.87 for 'dark blue' garments. Extending microspectrophotometry into the UV range increased discrimination by 7%, giving a discriminating power of 0.96 for both mid and dark blue cotton fibres which was similar to that reported by a previous study where this method was combined with light and fluorescence microscopy. Intra-garment variation was found to be negligible. The implications of this study for casework are discussed and a revised analytical pathway for the comparison of this fibre type/colour combination using microspectrophotometry as a primary screening tool, is proposed.

The Information Panopticon in the Big Data Era

Directory of Open Access Journals (Sweden)

Martin Berner

2014-04-01

Full Text Available Taking advantage of big data opportunities is challenging for traditional organizations. In this article, we take a panoptic view of big data – obtaining information from more sources and making it visible to all organizational levels. We suggest that big data requires the transformation from command and control hierarchies to post-bureaucratic organizational structures wherein employees at all levels can be empowered while simultaneously being controlled. We derive propositions that show how to best exploit big data technologies in organizations.

WE-H-BRB-00: Big Data in Radiation Oncology

Energy Technology Data Exchange (ETDEWEB)

NONE

2016-06-15

Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

WE-H-BRB-00: Big Data in Radiation Oncology

International Nuclear Information System (INIS)

2016-01-01

Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

De impact van Big Data op Internationale Betrekkingen

NARCIS (Netherlands)

Zwitter, Andrej

Big Data changes our daily lives, but does it also change international politics? In this contribution, Andrej Zwitter (NGIZ chair at Groningen University) argues that Big Data impacts on international relations in ways that we only now start to understand. To comprehend how Big Data influences

Epidemiology in the Era of Big Data

Science.gov (United States)

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-01-01

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called ‘3 Vs’: variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that, while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field’s future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future. PMID:25756221

BLUES function method in computational physics

Science.gov (United States)

Indekeu, Joseph O.; Müller-Nedebock, Kristian K.

2018-04-01

We introduce a computational method in physics that goes ‘beyond linear use of equation superposition’ (BLUES). A BLUES function is defined as a solution of a nonlinear differential equation (DE) with a delta source that is at the same time a Green’s function for a related linear DE. For an arbitrary source, the BLUES function can be used to construct an exact solution to the nonlinear DE with a different, but related source. Alternatively, the BLUES function can be used to construct an approximate piecewise analytical solution to the nonlinear DE with an arbitrary source. For this alternative use the related linear DE need not be known. The method is illustrated in a few examples using analytical calculations and numerical computations. Areas for further applications are suggested.

Big data and analytics strategic and organizational impacts

CERN Document Server

Morabito, Vincenzo

2015-01-01

This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners...

Big Science and Long-tail Science

CERN Document Server

2008-01-01

Jim Downing and I were privileged to be the guests of Salavtore Mele at CERN yesterday and to see the Atlas detector of the Large Hadron Collider . This is a wow experience - although I knew it was big, I hadnt realised how big.

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

Big-Eyed Bugs Have Big Appetite for Pests

Science.gov (United States)

Many kinds of arthropod natural enemies (predators and parasitoids) inhabit crop fields in Arizona and can have a large negative impact on several pest insect species that also infest these crops. Geocoris spp., commonly known as big-eyed bugs, are among the most abundant insect predators in field c...

Big Data - What is it and why it matters.

Science.gov (United States)

Tattersall, Andy; Grant, Maria J

2016-06-01

Big data, like MOOCs, altmetrics and open access, is a term that has been commonplace in the library community for some time yet, despite its prevalence, many in the library and information sector remain unsure of the relationship between big data and their roles. This editorial explores what big data could mean for the day-to-day practice of health library and information workers, presenting examples of big data in action, considering the ethics of accessing big data sets and the potential for new roles for library and information workers. © 2016 Health Libraries Group.

Research on information security in big data era

Science.gov (United States)

Zhou, Linqi; Gu, Weihong; Huang, Cheng; Huang, Aijun; Bai, Yongbin

2018-05-01

Big data is becoming another hotspot in the field of information technology after the cloud computing and the Internet of Things. However, the existing information security methods can no longer meet the information security requirements in the era of big data. This paper analyzes the challenges and a cause of data security brought by big data, discusses the development trend of network attacks under the background of big data, and puts forward my own opinions on the development of security defense in technology, strategy and product.

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.

Fuzzy 2-partition entropy threshold selection based on Big Bang–Big Crunch Optimization algorithm

Directory of Open Access Journals (Sweden)

Baljit Singh Khehra

2015-03-01

Full Text Available The fuzzy 2-partition entropy approach has been widely used to select threshold value for image segmenting. This approach used two parameterized fuzzy membership functions to form a fuzzy 2-partition of the image. The optimal threshold is selected by searching an optimal combination of parameters of the membership functions such that the entropy of fuzzy 2-partition is maximized. In this paper, a new fuzzy 2-partition entropy thresholding approach based on the technology of the Big Bang–Big Crunch Optimization (BBBCO is proposed. The new proposed thresholding approach is called the BBBCO-based fuzzy 2-partition entropy thresholding algorithm. BBBCO is used to search an optimal combination of parameters of the membership functions for maximizing the entropy of fuzzy 2-partition. BBBCO is inspired by the theory of the evolution of the universe; namely the Big Bang and Big Crunch Theory. The proposed algorithm is tested on a number of standard test images. For comparison, three different algorithms included Genetic Algorithm (GA-based, Biogeography-based Optimization (BBO-based and recursive approaches are also implemented. From experimental results, it is observed that the performance of the proposed algorithm is more effective than GA-based, BBO-based and recursion-based approaches.

A little big history of Tiananmen

NARCIS (Netherlands)

Quaedackers, E.; Grinin, L.E.; Korotayev, A.V.; Rodrigue, B.H.

2011-01-01

This contribution aims at demonstrating the usefulness of studying small-scale subjects such as Tiananmen, or the Gate of Heavenly Peace, in Beijing - from a Big History perspective. By studying such a ‘little big history’ of Tiananmen, previously overlooked yet fundamental explanations for why

Isolation of an 18,000-dalton hypusine-containing protein from cultured mouse neuroblastoma cells

International Nuclear Information System (INIS)

Dou, Q.P.; Chen, K.Y.

1987-01-01

An 18,000-dalton protein can be metabolically labeled by [ 3 H]putrescine or spermidine in mammalian cells. The labeling is due to a post-translational conversion of a lysine residue to hypusine residue. Previous studies indicated that the labeling is growth-dependent and is greatly diminished in mouse neuroblastoma cells after differentiation. To further study the physiological functions of this protein in the differentiation of mouse neuroblastoma cells, they have developed a simple procedure to purify this protein from cultured NB-15 mouse neuroblastoma cells. The 4-steps procedure included a Cibacron-Blue column, an omega-diaminooctyl-agarose column, a Sephadex G-50 column, and a Mono Q column. The procedure resulted in a 500-fold purification and the preparation appeared to be homogenous as judged by SDS-PAGE. Peptide map analysis using V-8 protease digestion method indicated that the 18,000-dalton hypusine-containing protein from NB-15 cells was identical to eukaryotic initiation factor 4D isolated from rabbit reticulocytes. This purification scheme also enabled them to detect a very faintly labeled protein in NB-15 cells. This weakly labeled protein had an apparent molecular weight of 22,000-dalton and pI of 5.0

Addressing big data issues in Scientific Data Infrastructure

NARCIS (Netherlands)

Demchenko, Y.; Membrey, P.; Grosso, P.; de Laat, C.; Smari, W.W.; Fox, G.C.

2013-01-01

Big Data are becoming a new technology focus both in science and in industry. This paper discusses the challenges that are imposed by Big Data on the modern and future Scientific Data Infrastructure (SDI). The paper discusses a nature and definition of Big Data that include such features as Volume,

Improving Healthcare Using Big Data Analytics

Directory of Open Access Journals (Sweden)

Revanth Sonnati

2017-03-01

Full Text Available In daily terms we call the current era as Modern Era which can also be named as the era of Big Data in the field of Information Technology. Our daily lives in todays world are rapidly advancing never quenching ones thirst. The fields of science engineering and technology are producing data at an exponential rate leading to Exabytes of data every day. Big data helps us to explore and re-invent many areas not limited to education health and law. The primary purpose of this paper is to provide an in-depth analysis in the area of Healthcare using the big data and analytics. The main purpose is to emphasize on the usage of the big data which is being stored all the time helping to look back in the history but this is the time to emphasize on the analyzation to improve the medication and services. Although many big data implementations happen to be in-house development this proposed implementation aims to propose a broader extent using Hadoop which just happen to be the tip of the iceberg. The focus of this paper is not limited to the improvement and analysis of the data it also focusses on the strengths and drawbacks compared to the conventional techniques available.

Big Data - Smart Health Strategies

Science.gov (United States)

2014-01-01

Summary Objectives To select best papers published in 2013 in the field of big data and smart health strategies, and summarize outstanding research efforts. Methods A systematic search was performed using two major bibliographic databases for relevant journal papers. The references obtained were reviewed in a two-stage process, starting with a blinded review performed by the two section editors, and followed by a peer review process operated by external reviewers recognized as experts in the field. Results The complete review process selected four best papers, illustrating various aspects of the special theme, among them: (a) using large volumes of unstructured data and, specifically, clinical notes from Electronic Health Records (EHRs) for pharmacovigilance; (b) knowledge discovery via querying large volumes of complex (both structured and unstructured) biological data using big data technologies and relevant tools; (c) methodologies for applying cloud computing and big data technologies in the field of genomics, and (d) system architectures enabling high-performance access to and processing of large datasets extracted from EHRs. Conclusions The potential of big data in biomedicine has been pinpointed in various viewpoint papers and editorials. The review of current scientific literature illustrated a variety of interesting methods and applications in the field, but still the promises exceed the current outcomes. As we are getting closer towards a solid foundation with respect to common understanding of relevant concepts and technical aspects, and the use of standardized technologies and tools, we can anticipate to reach the potential that big data offer for personalized medicine and smart health strategies in the near future. PMID:25123721

About Big Data and its Challenges and Benefits in Manufacturing

OpenAIRE

Bogdan NEDELCU

2013-01-01

The aim of this article is to show the importance of Big Data and its growing influence on companies. It also shows what kind of big data is currently generated and how much big data is estimated to be generated. We can also see how much are the companies willing to invest in big data and how much are they currently gaining from their big data. There are also shown some major influences that big data has over one major segment in the industry (manufacturing) and the challenges that appear.

Big Data Management in US Hospitals: Benefits and Barriers.

Science.gov (United States)

Schaeffer, Chad; Booton, Lawrence; Halleck, Jamey; Studeny, Jana; Coustasse, Alberto

Big data has been considered as an effective tool for reducing health care costs by eliminating adverse events and reducing readmissions to hospitals. The purposes of this study were to examine the emergence of big data in the US health care industry, to evaluate a hospital's ability to effectively use complex information, and to predict the potential benefits that hospitals might realize if they are successful in using big data. The findings of the research suggest that there were a number of benefits expected by hospitals when using big data analytics, including cost savings and business intelligence. By using big data, many hospitals have recognized that there have been challenges, including lack of experience and cost of developing the analytics. Many hospitals will need to invest in the acquiring of adequate personnel with experience in big data analytics and data integration. The findings of this study suggest that the adoption, implementation, and utilization of big data technology will have a profound positive effect among health care providers.

Big Data Strategy for Telco: Network Transformation

OpenAIRE

F. Amin; S. Feizi

2014-01-01

Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and ...

Big Data in Shipping - Challenges and Opportunities

OpenAIRE

Rødseth, Ørnulf Jan; Perera, Lokukaluge Prasad; Mo, Brage

2016-01-01

Big Data is getting popular in shipping where large amounts of information is collected to better understand and improve logistics, emissions, energy consumption and maintenance. Constraints to the use of big data include cost and quality of on-board sensors and data acquisition systems, satellite communication, data ownership and technical obstacles to effective collection and use of big data. New protocol standards may simplify the process of collecting and organizing the data, including in...

New insights into the role of Mn and Fe in coloring origin of blue decorations of blue-and-white porcelains by XANES spectroscopy

International Nuclear Information System (INIS)

Zhu, Jian; Luo, Wugan; Ming, Chaofang; Wang, Changsui; Chen, Dongliang; Xu, Wei; Wang, Lihua

2013-01-01

Blue and white porcelain is one of the most valuable ancient ceramics varieties in ancient China. It is well known for its beautiful blue decorations. However, the origin of its blue color has not been very clear till now. In this research, two blue and white porcelains from Jingdezhen, Jiangxi province were selected and Mn and Fe K-edge XANES spectra were recorded from blue decorations with or without transparent glaze. Results showed that Mn K-edge XANES features were almost identical between different samples while that of iron changed. The above findings indicated the positive role of iron in the variation of blue decorations. As for manganese, although more system researches were need, its negative role on the variations of the tone of blue decorations was obtained. On the other hand, the paper also revealed the XAFS results will be affect by the glaze layer above the pigment. These findings provided us more information to understand the coloring origin of blue decorations of blue-and-white porcelain by means of XANES spectroscopy.

New insights into the role of Mn and Fe in coloring origin of blue decorations of blue-and-white porcelains by XANES spectroscopy

Science.gov (United States)

Zhu, Jian; Luo, Wugan; Chen, Dongliang; Xu, Wei; Ming, Chaofang; Wang, Changsui; Wang, Lihua

2013-04-01

Blue and white porcelain is one of the most valuable ancient ceramics varieties in ancient China. It is well known for its beautiful blue decorations. However, the origin of its blue color has not been very clear till now. In this research, two blue and white porcelains from Jingdezhen, Jiangxi province were selected and Mn and Fe K-edge XANES spectra were recorded from blue decorations with or without transparent glaze. Results showed that Mn K-edge XANES features were almost identical between different samples while that of iron changed. The above findings indicated the positive role of iron in the variation of blue decorations. As for manganese, although more system researches were need, its negative role on the variations of the tone of blue decorations was obtained. On the other hand, the paper also revealed the XAFS results will be affect by the glaze layer above the pigment. These findings provided us more information to understand the coloring origin of blue decorations of blue-and-white porcelain by means of XANES spectroscopy.

[Relevance of big data for molecular diagnostics].

Science.gov (United States)

Bonin-Andresen, M; Smiljanovic, B; Stuhlmüller, B; Sörensen, T; Grützkau, A; Häupl, T

2018-04-01

Big data analysis raises the expectation that computerized algorithms may extract new knowledge from otherwise unmanageable vast data sets. What are the algorithms behind the big data discussion? In principle, high throughput technologies in molecular research already introduced big data and the development and application of analysis tools into the field of rheumatology some 15 years ago. This includes especially omics technologies, such as genomics, transcriptomics and cytomics. Some basic methods of data analysis are provided along with the technology, however, functional analysis and interpretation requires adaptation of existing or development of new software tools. For these steps, structuring and evaluating according to the biological context is extremely important and not only a mathematical problem. This aspect has to be considered much more for molecular big data than for those analyzed in health economy or epidemiology. Molecular data are structured in a first order determined by the applied technology and present quantitative characteristics that follow the principles of their biological nature. These biological dependencies have to be integrated into software solutions, which may require networks of molecular big data of the same or even different technologies in order to achieve cross-technology confirmation. More and more extensive recording of molecular processes also in individual patients are generating personal big data and require new strategies for management in order to develop data-driven individualized interpretation concepts. With this perspective in mind, translation of information derived from molecular big data will also require new specifications for education and professional competence.

Nature's palette: the search for natural blue colorants.

Science.gov (United States)

Newsome, Andrew G; Culver, Catherine A; van Breemen, Richard B

2014-07-16

The food and beverage industry is seeking to broaden the palette of naturally derived colorants. Although considerable effort has been devoted to the search for new blue colorants in fruits and vegetables, less attention has been directed toward blue compounds from other sources such as bacteria and fungi. The current work reviews known organic blue compounds from natural plant, animal, fungal, and microbial sources. The scarcity of blue-colored metabolites in the natural world relative to metabolites of other colors is discussed, and structural trends common among natural blue compounds are identified. These compounds are grouped into seven structural classes and evaluated for their potential as new color additives.

Big data in psychology: A framework for research advancement.

Science.gov (United States)

Adjerid, Idris; Kelley, Ken

2018-02-22

The potential for big data to provide value for psychology is significant. However, the pursuit of big data remains an uncertain and risky undertaking for the average psychological researcher. In this article, we address some of this uncertainty by discussing the potential impact of big data on the type of data available for psychological research, addressing the benefits and most significant challenges that emerge from these data, and organizing a variety of research opportunities for psychology. Our article yields two central insights. First, we highlight that big data research efforts are more readily accessible than many researchers realize, particularly with the emergence of open-source research tools, digital platforms, and instrumentation. Second, we argue that opportunities for big data research are diverse and differ both in their fit for varying research goals, as well as in the challenges they bring about. Ultimately, our outlook for researchers in psychology using and benefiting from big data is cautiously optimistic. Although not all big data efforts are suited for all researchers or all areas within psychology, big data research prospects are diverse, expanding, and promising for psychology and related disciplines. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

'Big data' in pharmaceutical science: challenges and opportunities.

Science.gov (United States)

Dossetter, Al G; Ecker, Gerhard; Laverty, Hugh; Overington, John

2014-05-01

Future Medicinal Chemistry invited a selection of experts to express their views on the current impact of big data in drug discovery and design, as well as speculate on future developments in the field. The topics discussed include the challenges of implementing big data technologies, maintaining the quality and privacy of data sets, and how the industry will need to adapt to welcome the big data era. Their enlightening responses provide a snapshot of the many and varied contributions being made by big data to the advancement of pharmaceutical science.

Soft computing in big data processing

CERN Document Server

Park, Seung-Jong; Lee, Jee-Hyong

2014-01-01

Big data is an essential key to build a smart world as a meaning of the streaming, continuous integration of large volume and high velocity data covering from all sources to final destinations. The big data range from data mining, data analysis and decision making, by drawing statistical rules and mathematical patterns through systematical or automatically reasoning. The big data helps serve our life better, clarify our future and deliver greater value. We can discover how to capture and analyze data. Readers will be guided to processing system integrity and implementing intelligent systems. With intelligent systems, we deal with the fundamental data management and visualization challenges in effective management of dynamic and large-scale data, and efficient processing of real-time and spatio-temporal data. Advanced intelligent systems have led to managing the data monitoring, data processing and decision-making in realistic and effective way. Considering a big size of data, variety of data and frequent chan...

Phototherapy with blue and green mixed-light is as effective against unconjugated jaundice as blue light and reduces oxidative stress in the Gunn rat model.

Science.gov (United States)

Uchida, Yumiko; Morimoto, Yukihiro; Uchiike, Takao; Kamamoto, Tomoyuki; Hayashi, Tamaki; Arai, Ikuyo; Nishikubo, Toshiya; Takahashi, Yukihiro

2015-07-01

Phototherapy using blue light-emitting diodes (LED) is effective against neonatal jaundice. However, green light phototherapy also reduces unconjugated jaundice. We aimed to determine whether mixed blue and green light can relieve jaundice with minimal oxidative stress as effectively as either blue or green light alone in a rat model. Gunn rats were exposed to phototherapy with blue (420-520 nm), filtered blue (FB; 440-520 nm without 1.00), respectively. Blue plus green phototherapy is as effective as blue phototherapy and it attenuates irradiation-induced oxidative stress. Combined blue and green spectra might be effective against neonatal hyperbilirubinemia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Solution of a braneworld big crunch/big bang cosmology

International Nuclear Information System (INIS)

McFadden, Paul L.; Turok, Neil; Steinhardt, Paul J.

2007-01-01

We solve for the cosmological perturbations in a five-dimensional background consisting of two separating or colliding boundary branes, as an expansion in the collision speed V divided by the speed of light c. Our solution permits a detailed check of the validity of four-dimensional effective theory in the vicinity of the event corresponding to the big crunch/big bang singularity. We show that the four-dimensional description fails at the first nontrivial order in (V/c) 2 . At this order, there is nontrivial mixing of the two relevant four-dimensional perturbation modes (the growing and decaying modes) as the boundary branes move from the narrowly separated limit described by Kaluza-Klein theory to the well-separated limit where gravity is confined to the positive-tension brane. We comment on the cosmological significance of the result and compute other quantities of interest in five-dimensional cosmological scenarios

[Big data and their perspectives in radiation therapy].

Science.gov (United States)

Guihard, Sébastien; Thariat, Juliette; Clavier, Jean-Baptiste

2017-02-01

The concept of big data indicates a change of scale in the use of data and data aggregation into large databases through improved computer technology. One of the current challenges in the creation of big data in the context of radiation therapy is the transformation of routine care items into dark data, i.e. data not yet collected, and the fusion of databases collecting different types of information (dose-volume histograms and toxicity data for example). Processes and infrastructures devoted to big data collection should not impact negatively on the doctor-patient relationship, the general process of care or the quality of the data collected. The use of big data requires a collective effort of physicians, physicists, software manufacturers and health authorities to create, organize and exploit big data in radiotherapy and, beyond, oncology. Big data involve a new culture to build an appropriate infrastructure legally and ethically. Processes and issues are discussed in this article. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Current applications of big data in obstetric anesthesiology.

Science.gov (United States)

Klumpner, Thomas T; Bauer, Melissa E; Kheterpal, Sachin

2017-06-01

The narrative review aims to highlight several recently published 'big data' studies pertinent to the field of obstetric anesthesiology. Big data has been used to study rare outcomes, to identify trends within the healthcare system, to identify variations in practice patterns, and to highlight potential inequalities in obstetric anesthesia care. Big data studies have helped define the risk of rare complications of obstetric anesthesia, such as the risk of neuraxial hematoma in thrombocytopenic parturients. Also, large national databases have been used to better understand trends in anesthesia-related adverse events during cesarean delivery as well as outline potential racial/ethnic disparities in obstetric anesthesia care. Finally, real-time analysis of patient data across a number of disparate health information systems through the use of sophisticated clinical decision support and surveillance systems is one promising application of big data technology on the labor and delivery unit. 'Big data' research has important implications for obstetric anesthesia care and warrants continued study. Real-time electronic surveillance is a potentially useful application of big data technology on the labor and delivery unit.

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.

MOCK OBSERVATIONS OF BLUE STRAGGLERS IN GLOBULAR CLUSTER MODELS

International Nuclear Information System (INIS)

Sills, Alison; Glebbeek, Evert; Chatterjee, Sourav; Rasio, Frederic A.

2013-01-01

We created artificial color-magnitude diagrams of Monte Carlo dynamical models of globular clusters and then used observational methods to determine the number of blue stragglers in those clusters. We compared these blue stragglers to various cluster properties, mimicking work that has been done for blue stragglers in Milky Way globular clusters to determine the dominant formation mechanism(s) of this unusual stellar population. We find that a mass-based prescription for selecting blue stragglers will select approximately twice as many blue stragglers than a selection criterion that was developed for observations of real clusters. However, the two numbers of blue stragglers are well-correlated, so either selection criterion can be used to characterize the blue straggler population of a cluster. We confirm previous results that the simplified prescription for the evolution of a collision or merger product in the BSE code overestimates their lifetimes. We show that our model blue stragglers follow similar trends with cluster properties (core mass, binary fraction, total mass, collision rate) as the true Milky Way blue stragglers as long as we restrict ourselves to model clusters with an initial binary fraction higher than 5%. We also show that, in contrast to earlier work, the number of blue stragglers in the cluster core does have a weak dependence on the collisional parameter Γ in both our models and in Milky Way globular clusters

Using Big Book to Teach Things in My House

OpenAIRE

Effrien, Intan; Lailatus, Sa’diyah; Nuruliftitah Maja, Neneng

2017-01-01

The purpose of this study to determine students' interest in learning using the big book media. Big book is a big book from the general book. The big book contains simple words and images that match the content of sentences and spelling. From here researchers can know the interest and development of students' knowledge. As well as train researchers to remain crative in developing learning media for students.

Big Data Analytics Methodology in the Financial Industry

Science.gov (United States)

Lawler, James; Joseph, Anthony

2017-01-01

Firms in industry continue to be attracted by the benefits of Big Data Analytics. The benefits of Big Data Analytics projects may not be as evident as frequently indicated in the literature. The authors of the study evaluate factors in a customized methodology that may increase the benefits of Big Data Analytics projects. Evaluating firms in the…

Alcian blue-stained particles in a eutrophic lake

DEFF Research Database (Denmark)

Worm, J.; Søndergaard, Morten

1998-01-01

We used a neutral solution of Alcian Blue to stain transparent particles in eutrophic Lake Frederiksborg Slotss0, Denmark. Alcian Blue-stained particles (ABSP) appeared to be similar to the so-called transparent exopolymer particles (TEP) identified with an acidic solution of Alcian Blue. Our...

FIXED-BED COLUMN ADSORPTION OF METHYL BLUE USING ...

African Journals Online (AJOL)

userpc

Axle Wood Carbon (AWC) was used to study the removal of Methyl Blue (MB) from ... height, initial methyl blue (MB) concentration, .... colour from blue to dark purple- .... Environ. Earth Sci. 13; 1–13. Yagub, M. T., Sen, T. K., Afroze, S., and Ang,.

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

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.

Hot big bang or slow freeze?

Science.gov (United States)

Wetterich, C.

2014-09-01

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze - a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple ;crossover model; without a big bang singularity. In the infinite past space-time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

Big Data

DEFF Research Database (Denmark)

Aaen, Jon; Nielsen, Jeppe Agger

2016-01-01

Big Data byder sig til som en af tidens mest hypede teknologiske innovationer, udråbt til at rumme kimen til nye, værdifulde operationelle indsigter for private virksomheder og offentlige organisationer. Mens de optimistiske udmeldinger er mange, er forskningen i Big Data i den offentlige sektor...... indtil videre begrænset. Denne artikel belyser, hvordan den offentlige sundhedssektor kan genanvende og udnytte en stadig større mængde data under hensyntagen til offentlige værdier. Artiklen bygger på et casestudie af anvendelsen af store mængder sundhedsdata i Dansk AlmenMedicinsk Database (DAMD......). Analysen viser, at (gen)brug af data i nye sammenhænge er en flerspektret afvejning mellem ikke alene økonomiske rationaler og kvalitetshensyn, men også kontrol over personfølsomme data og etiske implikationer for borgeren. I DAMD-casen benyttes data på den ene side ”i den gode sags tjeneste” til...

Curating Big Data Made Simple: Perspectives from Scientific Communities.

Science.gov (United States)

Sowe, Sulayman K; Zettsu, Koji

2014-03-01

The digital universe is exponentially producing an unprecedented volume of data that has brought benefits as well as fundamental challenges for enterprises and scientific communities alike. This trend is inherently exciting for the development and deployment of cloud platforms to support scientific communities curating big data. The excitement stems from the fact that scientists can now access and extract value from the big data corpus, establish relationships between bits and pieces of information from many types of data, and collaborate with a diverse community of researchers from various domains. However, despite these perceived benefits, to date, little attention is focused on the people or communities who are both beneficiaries and, at the same time, producers of big data. The technical challenges posed by big data are as big as understanding the dynamics of communities working with big data, whether scientific or otherwise. Furthermore, the big data era also means that big data platforms for data-intensive research must be designed in such a way that research scientists can easily search and find data for their research, upload and download datasets for onsite/offsite use, perform computations and analysis, share their findings and research experience, and seamlessly collaborate with their colleagues. In this article, we present the architecture and design of a cloud platform that meets some of these requirements, and a big data curation model that describes how a community of earth and environmental scientists is using the platform to curate data. Motivation for developing the platform, lessons learnt in overcoming some challenges associated with supporting scientists to curate big data, and future research directions are also presented.

Big data analytics in healthcare: promise and potential.

Science.gov (United States)

Raghupathi, Wullianallur; Raghupathi, Viju

2014-01-01

To describe the promise and potential of big data analytics in healthcare. The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Data warehousing in the age of big data

CERN Document Server

Krishnan, Krish

2013-01-01

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture

The Death of the Big Men

DEFF Research Database (Denmark)

Martin, Keir

2010-01-01

Recently Tolai people og Papua New Guinea have adopted the term 'Big Shot' to decribe an emerging post-colonial political elite. The mergence of the term is a negative moral evaluation of new social possibilities that have arisen as a consequence of the Big Shots' privileged position within a glo...

Big data and software defined networks

CERN Document Server

Taheri, Javid

2018-01-01

Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). This new book investigates areas where Big-Data and SDN can help each other in delivering more efficient services.

Compact and efficient blue laser sheet for measurement

Science.gov (United States)

Qi, Yan; Wang, Yu; Wu, Bin; Wang, Yanwei; Yan, Boxia

2017-10-01

Compact and efficient blue laser sheet has important applications in the field of measurement, with laser diode end pumped Nd:YAG directly and LBO intracavity frequency doubling, a compact and efficient CW 473nm blue laser sheet composed of dual path liner blue laser is realized. At an incident pump power of 12.4W, up to 1.4W output power of the compound blue laser is achieved, the optical-to-optical conversion efficiency is as high as 11.3%.

Big Data-Survey

Directory of Open Access Journals (Sweden)

P.S.G. Aruna Sri

2016-03-01

Full Text Available Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

OpenAIRE

Garattini, C.; Raffle, J.; Aisyah, D. N.; Sartain, F.; Kozlakidis, Z.

2017-01-01

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes ...

Evaluation of Data Management Systems for Geospatial Big Data

OpenAIRE

Amirian, Pouria; Basiri, Anahid; Winstanley, Adam C.

2014-01-01

Big Data encompasses collection, management, processing and analysis of the huge amount of data that varies in types and changes with high frequency. Often data component of Big Data has a positional component as an important part of it in various forms, such as postal address, Internet Protocol (IP) address and geographical location. If the positional components in Big Data extensively used in storage, retrieval, analysis, processing, visualization and knowledge discovery (geospatial Big Dat...

A Blue Lagoon Function

DEFF Research Database (Denmark)

Markvorsen, Steen

2007-01-01

We consider a specific function of two variables whose graph surface resembles a blue lagoon. The function has a saddle point $p$, but when the function is restricted to any given straight line through $p$ it has a {\\em{strict local minimum}} along that line at $p$.......We consider a specific function of two variables whose graph surface resembles a blue lagoon. The function has a saddle point $p$, but when the function is restricted to any given straight line through $p$ it has a {\\em{strict local minimum}} along that line at $p$....

The Structure of the Blue Whirl

Science.gov (United States)

Hariharan, Sriram Bharath; Hu, Yu; Xiao, Huahua; Gollner, Michael; Oran, Elaine

2017-11-01

Recent experiments have led to the discovery of the blue whirl, a small, stable regime of the fire whirl that burns typically sooty liquid hydrocarbons without producing soot. The physical structure consists of three regions - the blue cone, the vortex rim and the purple haze. The physical nature of the flame was further investigated through digital imaging techniques, which suggest that the transition (from the fire whirl to the blue whirl) and shape of the flame may be influenced by vortex breakdown. The flame was found to develop over a variety of surfaces, which indicates that the formation of the blue whirl is strongly influenced by the flow structure over the incoming boundary layer. The thermal structure was investigated using micro-thermocouples, thin-filament pyrometry and OH* spectroscopy. These revealed a peak temperature around 2000 K, and that most of the combustion occurs in the relatively small, visibly bright vortex rim. The results of these investigations provide a platform to develop a theory on the structure of the blue whirl, a deeper understanding of which may affirm potential for applications in the energy industry. This work was supported by an NSF EAGER award and Minta Martin Endowment Funds in the Department of Aerospace Engineering at the University of Maryland.

A New Look at Big History

Science.gov (United States)

Hawkey, Kate

2014-01-01

The article sets out a "big history" which resonates with the priorities of our own time. A globalizing world calls for new spacial scales to underpin what the history curriculum addresses, "big history" calls for new temporal scales, while concern over climate change calls for a new look at subject boundaries. The article…

West Virginia's big trees: setting the record straight

Science.gov (United States)

Melissa Thomas-Van Gundy; Robert. Whetsell

2016-01-01

People love big trees, people love to find big trees, and people love to find big trees in the place they call home. Having been suspicious for years, my coauthor and historian Rob Whetsell, approached me with a species identification challenge. There are several photographs of giant trees used by many people to illustrate the past forests of West Virginia,...

Blue whales Balaenoptera musculus off Angola: recent sightings ...

African Journals Online (AJOL)

Further survey work is required to better clarify the status of blue whales in Angolan waters, particularly with regard to population structure and potential calving grounds. Keywords: Antarctic blue whale, calving, catch data, pygmy blue whale, South-East Atlantic, stomach contents. African Journal of Marine Science 2014, ...

Sosiaalinen asiakassuhdejohtaminen ja big data

OpenAIRE

Toivonen, Topi-Antti

2015-01-01

Tässä tutkielmassa käsitellään sosiaalista asiakassuhdejohtamista sekä hyötyjä, joita siihen voidaan saada big datan avulla. Sosiaalinen asiakassuhdejohtaminen on terminä uusi ja monille tuntematon. Tutkimusta motivoi aiheen vähäinen tutkimus, suomenkielisen tutkimuksen puuttuminen kokonaan sekä sosiaalisen asiakassuhdejohtamisen mahdollinen olennainen rooli yritysten toiminnassa tulevaisuudessa. Big dataa käsittelevissä tutkimuksissa keskitytään monesti sen tekniseen puoleen, eikä sovellutuk...

Geothermal Technologies Program Blue Ribbon Panel Recommendations

Energy Technology Data Exchange (ETDEWEB)

none,

2011-06-17

The Geothermal Technologies Program assembled a geothermal Blue Ribbon Panel on March 22-23, 2011 in Albuquerque, New Mexico for a guided discussion on the future of geothermal energy in the United States and the role of the DOE Program. The Geothermal Blue Ribbon Panel Report captures the discussions and recommendations of the experts. An addendum is available here: http://www.eere.energy.gov/geothermal/pdfs/gtp_blue_ribbon_panel_report_addendum10-2011.pdf

D-branes in a big bang/big crunch universe: Misner space

International Nuclear Information System (INIS)

Hikida, Yasuaki; Nayak, Rashmi R.; Panigrahi, Kamal L.

2005-01-01

We study D-branes in a two-dimensional lorentzian orbifold R 1,1 /Γ with a discrete boost Γ. This space is known as Misner or Milne space, and includes big crunch/big bang singularity. In this space, there are D0-branes in spiral orbits and D1-branes with or without flux on them. In particular, we observe imaginary parts of partition functions, and interpret them as the rates of open string pair creation for D0-branes and emission of winding closed strings for D1-branes. These phenomena occur due to the time-dependence of the background. Open string 2→2 scattering amplitude on a D1-brane is also computed and found to be less singular than closed string case

D-branes in a big bang/big crunch universe: Misner space

Energy Technology Data Exchange (ETDEWEB)

Hikida, Yasuaki [Theory Group, High Energy Accelerator Research Organization (KEK), Tukuba, Ibaraki 305-0801 (Japan); 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)

2005-09-01

We study D-branes in a two-dimensional lorentzian orbifold R{sup 1,1}/{gamma} with a discrete boost {gamma}. This space is known as Misner or Milne space, and includes big crunch/big bang singularity. In this space, there are D0-branes in spiral orbits and D1-branes with or without flux on them. In particular, we observe imaginary parts of partition functions, and interpret them as the rates of open string pair creation for D0-branes and emission of winding closed strings for D1-branes. These phenomena occur due to the time-dependence of the background. Open string 2{yields}2 scattering amplitude on a D1-brane is also computed and found to be less singular than closed string case.

Astroinformatics: the big data of the universe

OpenAIRE

Barmby, Pauline

2016-01-01

In astrophysics we like to think that our field was the originator of big data, back when it had to be carried around in big sky charts and books full of tables. These days, it's easier to move astrophysics data around, but we still have a lot of it, and upcoming telescope  facilities will generate even more. I discuss how astrophysicists approach big data in general, and give examples from some Western Physics & Astronomy research projects.  I also give an overview of ho...

Recent big flare

International Nuclear Information System (INIS)

Moriyama, Fumio; Miyazawa, Masahide; Yamaguchi, Yoshisuke

1978-01-01

The features of three big solar flares observed at Tokyo Observatory are described in this paper. The active region, McMath 14943, caused a big flare on September 16, 1977. The flare appeared on both sides of a long dark line which runs along the boundary of the magnetic field. Two-ribbon structure was seen. The electron density of the flare observed at Norikura Corona Observatory was 3 x 10 12 /cc. Several arc lines which connect both bright regions of different magnetic polarity were seen in H-α monochrome image. The active region, McMath 15056, caused a big flare on December 10, 1977. At the beginning, several bright spots were observed in the region between two main solar spots. Then, the area and the brightness increased, and the bright spots became two ribbon-shaped bands. A solar flare was observed on April 8, 1978. At first, several bright spots were seen around the solar spot in the active region, McMath 15221. Then, these bright spots developed to a large bright region. On both sides of a dark line along the magnetic neutral line, bright regions were generated. These developed to a two-ribbon flare. The time required for growth was more than one hour. A bright arc which connects two ribbons was seen, and this arc may be a loop prominence system. (Kato, T.)

Big Bang Day : The Great Big Particle Adventure - 3. Origins

CERN Multimedia

2008-01-01

In this series, comedian and physicist Ben Miller asks the CERN scientists what they hope to find. If the LHC is successful, it will explain the nature of the Universe around us in terms of a few simple ingredients and a few simple rules. But the Universe now was forged in a Big Bang where conditions were very different, and the rules were very different, and those early moments were crucial to determining how things turned out later. At the LHC they can recreate conditions as they were billionths of a second after the Big Bang, before atoms and nuclei existed. They can find out why matter and antimatter didn't mutually annihilate each other to leave behind a Universe of pure, brilliant light. And they can look into the very structure of space and time - the fabric of the Universe

Spectra and ages of blue stragglers

International Nuclear Information System (INIS)

Abt, H.A.

1985-01-01

A mechanism similar to Wheeler's quasi-homogeneous evolution and Finzi and Wolf's proposal for blue stragglers is proposed as the origin of the blue stragglers in intermediate-age clusters. Blue stragglers are stars whose positions in color-magnitude diagrams of open and globular clusters are significantly above the turn-off points and in the region of the (former) main sequence; they seem to represent a conflict with the general conclusion that all stars in a cluster originated at about the same time. It is concluded that there are at least two kinds of blue stragglers: (1) those stars of types about B3-A2 are primarily Ap stars and slow rotators, occur in the intermediate age clusters and remain in the main sequence region probably through magnetic mixing; and (2) the stars of type O6-B2 frequently have emission lines, are rapid rotators, occur in the young cluster, and remain in the main sequence region probably by rotational mixing. 30 references

Inflated granularity: Spatial “Big Data” and geodemographics

Directory of Open Access Journals (Sweden)

Craig M Dalton

2015-08-01

Full Text Available Data analytics, particularly the current rhetoric around “Big Data”, tend to be presented as new and innovative, emerging ahistorically to revolutionize modern life. In this article, we situate one branch of Big Data analytics, spatial Big Data, through a historical predecessor, geodemographic analysis, to help develop a critical approach to current data analytics. Spatial Big Data promises an epistemic break in marketing, a leap from targeting geodemographic areas to targeting individuals. Yet it inherits characteristics and problems from geodemographics, including a justification through the market, and a process of commodification through the black-boxing of technology. As researchers develop sustained critiques of data analytics and its effects on everyday life, we must so with a grounding in the cultural and historical contexts from which data technologies emerged. This article and others (Barnes and Wilson, 2014 develop a historically situated, critical approach to spatial Big Data. This history illustrates connections to the critical issues of surveillance, redlining, and the production of consumer subjects and geographies. The shared histories and structural logics of spatial Big Data and geodemographics create the space for a continued critique of data analyses’ role in society.

Big data analysis for smart farming

NARCIS (Netherlands)

Kempenaar, C.; Lokhorst, C.; Bleumer, E.J.B.; Veerkamp, R.F.; Been, Th.; Evert, van F.K.; Boogaardt, M.J.; Ge, L.; Wolfert, J.; Verdouw, C.N.; Bekkum, van Michael; Feldbrugge, L.; Verhoosel, Jack P.C.; Waaij, B.D.; Persie, van M.; Noorbergen, H.

2016-01-01

In this report we describe results of a one-year TO2 institutes project on the development of big data technologies within the milk production chain. The goal of this project is to ‘create’ an integration platform for big data analysis for smart farming and to develop a show case. This includes both

A survey on Big Data Stream Mining

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... Big Data can be static on one machine or distributed ... decision making, and process automation. Big data .... Concept Drifting: concept drifting mean the classifier .... transactions generated by a prefix tree structure. EstDec ...

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.

Ultrasound enhanced delivery of molecular imaging and therapeutic agents in Alzheimer's disease mouse models.

Directory of Open Access Journals (Sweden)

Scott B Raymond

Full Text Available Alzheimer's disease is a neurodegenerative disorder typified by the accumulation of a small protein, beta-amyloid, which aggregates and is the primary component of amyloid plaques. Many new therapeutic and diagnostic agents for reducing amyloid plaques have limited efficacy in vivo because of poor transport across the blood-brain barrier. Here we demonstrate that low-intensity focused ultrasound with a microbubble contrast agent may be used to transiently disrupt the blood-brain barrier, allowing non-invasive, localized delivery of imaging fluorophores and immunotherapeutics directly to amyloid plaques. We administered intravenous Trypan blue, an amyloid staining red fluorophore, and anti-amyloid antibodies, concurrently with focused ultrasound therapy in plaque-bearing, transgenic mouse models of Alzheimer's disease with amyloid pathology. MRI guidance permitted selective treatment and monitoring of plaque-heavy anatomical regions, such as the hippocampus. Treated brain regions exhibited 16.5+/-5.4-fold increase in Trypan blue fluorescence and 2.7+/-1.2-fold increase in anti-amyloid antibodies that localized to amyloid plaques. Ultrasound-enhanced delivery was consistently reproduced in two different transgenic strains (APPswe:PSEN1dE9, PDAPP, across a large age range (9-26 months, with and without MR guidance, and with little or no tissue damage. Ultrasound-mediated, transient blood-brain barrier disruption allows the delivery of both therapeutic and molecular imaging agents in Alzheimer's mouse models, which should aid pre-clinical drug screening and imaging probe development. Furthermore, this technique may be used to deliver a wide variety of small and large molecules to the brain for imaging and therapy in other neurodegenerative diseases.

Toward a manifesto for the 'public understanding of big data'.

Science.gov (United States)

Michael, Mike; Lupton, Deborah

2016-01-01

In this article, we sketch a 'manifesto' for the 'public understanding of big data'. On the one hand, this entails such public understanding of science and public engagement with science and technology-tinged questions as follows: How, when and where are people exposed to, or do they engage with, big data? Who are regarded as big data's trustworthy sources, or credible commentators and critics? What are the mechanisms by which big data systems are opened to public scrutiny? On the other hand, big data generate many challenges for public understanding of science and public engagement with science and technology: How do we address publics that are simultaneously the informant, the informed and the information of big data? What counts as understanding of, or engagement with, big data, when big data themselves are multiplying, fluid and recursive? As part of our manifesto, we propose a range of empirical, conceptual and methodological exhortations. We also provide Appendix 1 that outlines three novel methods for addressing some of the issues raised in the article. © The Author(s) 2015.

What do Big Data do in Global Governance?

DEFF Research Database (Denmark)

Krause Hansen, Hans; Porter, Tony

2017-01-01

Two paradoxes associated with big data are relevant to global governance. First, while promising to increase the capacities of humans in governance, big data also involve an increasingly independent role for algorithms, technical artifacts, the Internet of things, and other objects, which can...... reduce the control of human actors. Second, big data involve new boundary transgressions as data are brought together from multiple sources while also creating new boundary conflicts as powerful actors seek to gain advantage by controlling big data and excluding competitors. These changes are not just...... about new data sources for global decision-makers, but instead signal more profound changes in the character of global governance....

Characteristics of Alcian-blue Dye Adsorption of Natural Biofilm Matrix

Science.gov (United States)

Kurniawan, A.; Yamamoto, T.; Sukandar; Guntur

2018-01-01

In this study, natural biofilm matrices formed on stones have been used for the adsorption of Alcian blue dye. Alcian blue is a member of polyvalent basic dyes that largely used from laboratory until industrial dying purposes. The adsorption of the dye onto the biofilm matrix has been carried out at different experimental conditions such as adsorption isotherm and kinetic of adsorption. The electric charge properties of biofilm matrix and its changes related to the adsorption of Alcian blue have been also investigated. Moreover, the results of Alcian blue adsorption to the biofilm were compared to those onto the acidic and neutral resin. The kinetics of adsorption result showed that the adsorption of the Alcian blue dye reached to a maximum adsorption amount within 60 minutes. The adsorption amount of Alcian blue to biofilm increased monotonously, and the maximum adsorption amount was greater compared to the resins. On the contrary, Alcian blue did not attach to the neutral resin having no electric charge. It seems that Alcian blue attached to the acidic resins due to electrostatic attractive force, and the same seems to be the case for adsorption of Alcian blue to biofilm. The adsorption of Alcian blue to the biofilm and acidic resins fitted to Langmuir type indicates that the binding of Alcian blue to the biofilm and acidic resins occurred in a monolayer like form. The maximum adsorption amount of Alcian blue on the biofilm (0.24 mmol/dry-g) was greater than those of acidic resin (0.025 mmol/dry-g). This indicates that the biofilm has many more sites for Alcian blue attachment than acidic resins. According to the result of this study, the biofilm matrix can be a good adsorbent for dye such as Alcian blue or other dyes that causing hazards in nature.

Big Data in Caenorhabditis elegans: quo vadis?

Science.gov (United States)

Hutter, Harald; Moerman, Donald

2015-11-05

A clear definition of what constitutes "Big Data" is difficult to identify, but we find it most useful to define Big Data as a data collection that is complete. By this criterion, researchers on Caenorhabditis elegans have a long history of collecting Big Data, since the organism was selected with the idea of obtaining a complete biological description and understanding of development. The complete wiring diagram of the nervous system, the complete cell lineage, and the complete genome sequence provide a framework to phrase and test hypotheses. Given this history, it might be surprising that the number of "complete" data sets for this organism is actually rather small--not because of lack of effort, but because most types of biological experiments are not currently amenable to complete large-scale data collection. Many are also not inherently limited, so that it becomes difficult to even define completeness. At present, we only have partial data on mutated genes and their phenotypes, gene expression, and protein-protein interaction--important data for many biological questions. Big Data can point toward unexpected correlations, and these unexpected correlations can lead to novel investigations; however, Big Data cannot establish causation. As a result, there is much excitement about Big Data, but there is also a discussion on just what Big Data contributes to solving a biological problem. Because of its relative simplicity, C. elegans is an ideal test bed to explore this issue and at the same time determine what is necessary to build a multicellular organism from a single cell. © 2015 Hutter and Moerman. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

76 FR 7810 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2011-02-11

..., Wyoming 82801. Comments may also be sent via e-mail to [email protected] , with the words Big... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

Thin blue lines: product placement and the drama of pregnancy testing in British cinema and television.

Science.gov (United States)

Olszynko-Gryn, Jesse

2017-09-01

This article uses the case of pregnancy testing in Britain to investigate the process whereby new and often controversial reproductive technologies are made visible and normalized in mainstream entertainment media. It shows how in the 1980s and 1990s the then nascent product placement industry was instrumental in embedding pregnancy testing in British cinema and television's dramatic productions. In this period, the pregnancy-test close-up became a conventional trope and the thin blue lines associated with Unilever's Clearblue rose to prominence in mainstream consumer culture. This article investigates the aestheticization of pregnancy testing and shows how increasingly visible public concerns about 'schoolgirl mums', abortion and the biological clock, dramatized on the big and small screen, propelled the commercial rise of Clearblue. It argues that the Clearblue close-up ambiguously concealed as much as it revealed; abstraction, ambiguity and flexibility were its keys to success.

Hot big bang or slow freeze?

Energy Technology Data Exchange (ETDEWEB)

Wetterich, C.

2014-09-07

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

Hot big bang or slow freeze?

International Nuclear Information System (INIS)

Wetterich, C.

2014-01-01

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe

Hot big bang or slow freeze?

Directory of Open Access Journals (Sweden)

C. Wetterich

2014-09-01

Full Text Available We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

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.

The role of the mesenchyme in mouse neural fold elevation. II. Patterns of hyaluronate synthesis and distribution in embryos developing in vitro

International Nuclear Information System (INIS)

Morris-Wiman, J.; Brinkley, L.L.

1990-01-01

Hyaluronate (HA) distribution patterns were examined in the cranial mesenchyme underlying the mesencephalic neural folds of mouse embryos maintained in roller tube culture. Using standard image-processing techniques, the digitized images of Alcian blue-stained or 3H-glucosamine-labeled sections digested with an enzyme specific for HA, were subtracted from adjacent, undigested sections. The resultant difference picture images (DPI) accurately depicted the distribution of stained or labeled HA within the cranial mesenchyme. 3H-glucosamine-labeled HA was distributed uniformly throughout the cranial mesenchyme as 12, 18, and 24 hr of culture. By contrast, the mesenchyme was uniformly stained with Alcian blue at 12 hr, but stain intensity decreased in the central regions of the mesenchyme at 18 and 24 hr. HA distribution patterns were also examined in the cranial mesenchyme of embryos cultured in the presence of diazo-oxo-norleucine (DON), a glutamine analogue that inhibits glycosaminoglycan and glycoprotein synthesis. In DON-treated mesenchyme, Alcian blue staining of HA was decreased from that in controls at 12, 18, and 24 hr. However, incorporation of 3H-glucosamine into HA was increased. The distribution of labeled HA within treated mesenchyme as 12, 18, and 24 hr resembled that in controls at 12 hr. These results indicate that the distribution of HA within the cranial mesenchyme of normal mouse embryos during neural fold elevation and convergence is not determined solely by regional differences in HA synthesis. We propose that HA distribution patterns result from the expansion of the HA-rich extracellular matrix of the central mesenchyme regions. This expansion may play a major role in fold elevation. These results also suggest that DON treatment reversibly inhibits HA synthesis

Effects of blue light and caffeine on mood.

Science.gov (United States)

Ekström, Johan G; Beaven, C Martyn

2014-09-01

Both short wavelength (blue) light and caffeine have been studied for their mood enhancing effects on humans. The ability of blue light to increase alertness, mood and cognitive function via non-image forming neuropathways has been suggested as a non-pharmacological countermeasure for depression across a range of occupational settings. This experimental study compared blue light and caffeine and aimed to test the effects of blue light/placebo (BLU), white light/240-mg caffeine (CAF), blue light/240-mg caffeine (BCAF) and white light/placebo (PLA), on mood. A randomised, controlled, crossover design study was used, in a convenience population of 20 healthy volunteers. The participants rated their mood on the Swedish Core Affect Scales (SCAS) prior to and after each experimental condition to assess the dimensions of valence and activation. There was a significant main effect of light (p = 0.009), and the combination of blue light and caffeine had clear positive effects on core effects (ES, ranging from 0.41 to 1.20) and global mood (ES, 0.61 ± 0.53). The benefits of the combination of blue light and caffeine should be further investigated across a range of applications due to the observed effects on the dimensions of arousal, valence and pleasant activation.

Pre-big bang cosmology and quantum fluctuations

International Nuclear Information System (INIS)

Ghosh, A.; Pollifrone, G.; Veneziano, G.

2000-01-01

The quantum fluctuations of a homogeneous, isotropic, open pre-big bang model are discussed. By solving exactly the equations for tensor and scalar perturbations we find that particle production is negligible during the perturbative Pre-Big Bang phase

Occupational contact dermatitis in blue-collar workers

DEFF Research Database (Denmark)

Schwensen, Jakob F; Menné, Torkil; Veien, Niels K

2014-01-01

BACKGROUND: Blue-collar workers have a high risk of occupational contact dermatitis, but epidemiological studies are scarce. OBJECTIVES: To investigate allergic contact dermatitis in blue-collar workers with dermatitis registered by the Danish Contact Dermatitis Group. METHODS: A retrospective...... analysis of patch test data from 1471 blue-collar workers and 1471 matched controls tested between 2003 and 2012 was performed. A logistic regression was used to test for associations. RESULTS: The blue-collar workers often had occupational hand dermatitis (p dermatitis was less commonly......, and methylchloroisothiazolinone (MCI)/methylisothiazolinone (MI). The following occupations were additionally identified as risk factors for contact sensitization to MCI/MI and MI, epoxy resins, and potassium dichromate, respectively: painting, construction work, and tile setting/terrazzo work. CONCLUSION: Contact allergy...

Centralized mouse repositories.

Science.gov (United States)

Donahue, Leah Rae; Hrabe de Angelis, Martin; Hagn, Michael; Franklin, Craig; Lloyd, K C Kent; Magnuson, Terry; McKerlie, Colin; Nakagata, Naomi; Obata, Yuichi; Read, Stuart; Wurst, Wolfgang; Hörlein, Andreas; Davisson, Muriel T

2012-10-01

Because the mouse is used so widely for biomedical research and the number of mouse models being generated is increasing rapidly, centralized repositories are essential if the valuable mouse strains and models that have been developed are to be securely preserved and fully exploited. Ensuring the ongoing availability of these mouse strains preserves the investment made in creating and characterizing them and creates a global resource of enormous value. The establishment of centralized mouse repositories around the world for distributing and archiving these resources has provided critical access to and preservation of these strains. This article describes the common and specialized activities provided by major mouse repositories around the world.

Analysis of Big Data Maturity Stage in Hospitality Industry

OpenAIRE

Shabani, Neda; Munir, Arslan; Bose, Avishek

2017-01-01

Big data analytics has an extremely significant impact on many areas in all businesses and industries including hospitality. This study aims to guide information technology (IT) professionals in hospitality on their big data expedition. In particular, the purpose of this study is to identify the maturity stage of the big data in hospitality industry in an objective way so that hotels be able to understand their progress, and realize what it will take to get to the next stage of big data matur...

A Multidisciplinary Perspective of Big Data in Management Research

OpenAIRE

Sheng, Jie; Amankwah-Amoah, J.; Wang, X.

2017-01-01

In recent years, big data has emerged as one of the prominent buzzwords in business and management. In spite of the mounting body of research on big data across the social science disciplines, scholars have offered little synthesis on the current state of knowledge. To take stock of academic research that contributes to the big data revolution, this paper tracks scholarly work's perspectives on big data in the management domain over the past decade. We identify key themes emerging in manageme...

An embedding for the big bang

Science.gov (United States)

Wesson, Paul S.

1994-01-01

A cosmological model is given that has good physical properties for the early and late universe but is a hypersurface in a flat five-dimensional manifold. The big bang can therefore be regarded as an effect of a choice of coordinates in a truncated higher-dimensional geometry. Thus the big bang is in some sense a geometrical illusion.

Degradation of phosphorescent blue organic light-emitting diodes

Energy Technology Data Exchange (ETDEWEB)

Chiu, Chien-Shu [Department of Electrical Engineering and Information Technology, Technical University of Braunschweig (Germany); Siemens AG, CT MM 1, Erlangen (Germany); Steinbacher, Frank [Department of Materials Science VI, University of Erlangen-Nuernberg (Germany); Siemens AG, CT MM 1, Erlangen (Germany); Krause, Ralf; Hunze, Arvid [Siemens AG, CT MM 1, Erlangen (Germany); Kowalsky, Wolfgang [Department of Electrical Engineering and Information Technology, Technical University of Braunschweig (Germany)

2009-07-01

Development of phosphorescent materials has significantly improved the efficiency of organic light-emitting diodes (OLEDs). By using efficient red, green and blue phosphorescent emitter materials high efficient white OLEDs can be achieved. However, due to low stability of blue phosphorescent materials the lifetime of phosphorescent white OLEDs remains an issue. As a result, degradation of blue phosphorescent materials needs to be further investigated and improved. In this work, blue OLED devices based on the phosphorescent emitter FIrpic were investigated. Single-carrier hole-only as well as electron-only devices were fabricated. For investigation of degradation process the devices were stressed with electrical current and UV-light to study the impact of charge carriers as well as excitons and exciton-polaron quenching on the stability of the blue dye.

Big Data as Governmentality in International Development

DEFF Research Database (Denmark)

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

2017-01-01

Statistics have long shaped the field of visibility for the governance of development projects. The introduction of big data has altered the field of visibility. Employing Dean's “analytics of government” framework, we analyze two cases—malaria tracking in Kenya and monitoring of food prices...... in Indonesia. Our analysis shows that big data introduces a bias toward particular types of visualizations. What problems are being made visible through big data depends to some degree on how the underlying data is visualized and who is captured in the visualizations. It is also influenced by technical factors...

A Brief Review on Leading Big Data Models

Directory of Open Access Journals (Sweden)

Sugam Sharma

2014-11-01

Full Text Available Today, science is passing through an era of transformation, where the inundation of data, dubbed data deluge is influencing the decision making process. The science is driven by the data and is being termed as data science. In this internet age, the volume of the data has grown up to petabytes, and this large, complex, structured or unstructured, and heterogeneous data in the form of “Big Data” has gained significant attention. The rapid pace of data growth through various disparate sources, especially social media such as Facebook, has seriously challenged the data analytic capabilities of traditional relational databases. The velocity of the expansion of the amount of data gives rise to a complete paradigm shift in how new age data is processed. Confidence in the data engineering of the existing data processing systems is gradually fading whereas the capabilities of the new techniques for capturing, storing, visualizing, and analyzing data are evolving. In this review paper, we discuss some of the modern Big Data models that are leading contributors in the NoSQL era and claim to address Big Data challenges in reliable and efficient ways. Also, we take the potential of Big Data into consideration and try to reshape the original operationaloriented definition of “Big Science” (Furner, 2003 into a new data-driven definition and rephrase it as “The science that deals with Big Data is Big Science.”

75 FR 71069 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2010-11-22

....us , with the words Big Horn County RAC in the subject line. Facsimilies may be sent to 307-674-2668... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

76 FR 26240 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2011-05-06

... words Big Horn County RAC in the subject line. Facsimilies may be sent to 307-674-2668. All comments... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

Big Science

Energy Technology Data Exchange (ETDEWEB)

Anon.

1986-05-15

Astronomy, like particle physics, has become Big Science where the demands of front line research can outstrip the science budgets of whole nations. Thus came into being the European Southern Observatory (ESO), founded in 1962 to provide European scientists with a major modern observatory to study the southern sky under optimal conditions.

Crystalline liquids: the blue phases

Science.gov (United States)

Wright, David C.; Mermin, N. David

1989-04-01

The blue phases of cholesteric liquid crystals are liquids that exhibit orientational order characterized by crystallographic space-group symmetries. We present here a pedagogical introduction to the current understanding of the equilibrium structure of these phases accompanied by a general overview of major experimental results. Using the Ginzburg-Landau free energy appropriate to the system, we first discuss in detail the character and stability of the usual helical phase of cholesterics, showing that for certain parameter ranges the helical phase is unstable to the appearance of one or more blue phases. The two principal models for the blue phases are two limiting cases of the Ginzburg-Landau theory. We explore each limit and conclude with some general considerations of defects in both models and an exact minimization of the free energy in a curved three-dimensional space.

Intraoral blue (Jadassohn-Tieche) nevus.

Science.gov (United States)

Hasse, C D; Zoutendam, G L; Gombas, O F

1978-05-01

Blue nevus of the oral mucosa is a distinctly uncommon clincial entity. Careful review of the literature yielded thirty-one previously reported cases. The present article reports the occurrence of a blue nevus of the hard palate in a 58-year-old man. It is of interest since it is the smallest (1 by 1 mm.) intraoral blue nevus to be reported. A clinicopathologic study of the previous thirty-one cases and of our case suggests that this lesion has no age or sex predilection. The most common site of occurrence was the hard palate. There appears to be no tendency toward recurrence. A brief review of the historical background, clinical features, theories of possible origin, and differential diagnosis is presented. Excisional biopsy of localized areas of oral pibmentation, together with histopathologic study, is indicated to rule out melanoma.

Commentary: Epidemiology in the era of big data.

Science.gov (United States)

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-05-01

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called "three V's": variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field's future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future.

New York Blue

Data.gov (United States)

Federal Laboratory Consortium — New York Blue is used cooperatively by the Laboratory and Stony Brook University as part of the New York Center for Computation Sciences. Ranked as the 28th fastest...

Natural regeneration processes in big sagebrush (Artemisia tridentata)

Science.gov (United States)

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

2014-01-01

Big sagebrush, Artemisia tridentata Nuttall (Asteraceae), is the dominant plant species of large portions of semiarid western North America. However, much of historical big sagebrush vegetation has been removed or modified. Thus, regeneration is recognized as an important component for land management. Limited knowledge about key regeneration processes, however, represents an obstacle to identifying successful management practices and to gaining greater insight into the consequences of increasing disturbance frequency and global change. Therefore, our objective is to synthesize knowledge about natural big sagebrush regeneration. We identified and characterized the controls of big sagebrush seed production, germination, and establishment. The largest knowledge gaps and associated research needs include quiescence and dormancy of embryos and seedlings; variation in seed production and germination percentages; wet-thermal time model of germination; responses to frost events (including freezing/thawing of soils), CO2 concentration, and nutrients in combination with water availability; suitability of microsite vs. site conditions; competitive ability as well as seedling growth responses; and differences among subspecies and ecoregions. Potential impacts of climate change on big sagebrush regeneration could include that temperature increases may not have a large direct influence on regeneration due to the broad temperature optimum for regeneration, whereas indirect effects could include selection for populations with less stringent seed dormancy. Drier conditions will have direct negative effects on germination and seedling survival and could also lead to lighter seeds, which lowers germination success further. The short seed dispersal distance of big sagebrush may limit its tracking of suitable climate; whereas, the low competitive ability of big sagebrush seedlings may limit successful competition with species that track climate. An improved understanding of the

Digital humanitarians how big data is changing the face of humanitarian response

CERN Document Server

Meier, Patrick

2015-01-01

The Rise of Digital HumanitariansMapping Haiti LiveSupporting Search And Rescue EffortsPreparing For The Long Haul Launching An SMS Life Line Sending In The Choppers Openstreetmap To The Rescue Post-Disaster Phase The Human Story Doing Battle With Big Data Rise Of Digital Humanitarians This Book And YouThe Rise of Big (Crisis) DataBig (Size) Data Finding Needles In Big (Size) Data Policy, Not Simply Technology Big (False) Data Unpacking Big (False) Data Calling 991 And 999 Big (

Big Data Provenance: Challenges, State of the Art and Opportunities.

Science.gov (United States)

Wang, Jianwu; Crawl, Daniel; Purawat, Shweta; Nguyen, Mai; Altintas, Ilkay

2015-01-01

Ability to track provenance is a key feature of scientific workflows to support data lineage and reproducibility. The challenges that are introduced by the volume, variety and velocity of Big Data, also pose related challenges for provenance and quality of Big Data, defined as veracity. The increasing size and variety of distributed Big Data provenance information bring new technical challenges and opportunities throughout the provenance lifecycle including recording, querying, sharing and utilization. This paper discusses the challenges and opportunities of Big Data provenance related to the veracity of the datasets themselves and the provenance of the analytical processes that analyze these datasets. It also explains our current efforts towards tracking and utilizing Big Data provenance using workflows as a programming model to analyze Big Data.

[Embracing medical innovation in the era of big data].

Science.gov (United States)

You, Suning

2015-01-01

Along with the advent of big data era worldwide, medical field has to place itself in it inevitably. The current article thoroughly introduces the basic knowledge of big data, and points out the coexistence of its advantages and disadvantages. Although the innovations in medical field are struggling, the current medical pattern will be changed fundamentally by big data. The article also shows quick change of relevant analysis in big data era, depicts a good intention of digital medical, and proposes some wise advices to surgeons.

Big Data and Health Economics: Opportunities, Challenges and Risks

Directory of Open Access Journals (Sweden)

Diego Bodas-Sagi

2018-03-01

Full Text Available Big Data offers opportunities in many fields. Healthcare is not an exception. In this paper we summarize the possibilities of Big Data and Big Data technologies to offer useful information to policy makers. In a world with tight public budgets and ageing populations we feel necessary to save costs in any production process. The use of outcomes from Big Data could be in the future a way to improve decisions at a lower cost than today. In addition to list the advantages of properly using data and technologies from Big Data, we also show some challenges and risks that analysts could face. We also present an hypothetical example of the use of administrative records with health information both for diagnoses and patients.

Speaking sociologically with big data: symphonic social science and the future for big data research

OpenAIRE

Halford, Susan; Savage, Mike

2017-01-01

Recent years have seen persistent tension between proponents of big data analytics, using new forms of digital data to make computational and statistical claims about ‘the social’, and many sociologists sceptical about the value of big data, its associated methods and claims to knowledge. We seek to move beyond this, taking inspiration from a mode of argumentation pursued by Putnam (2000), Wilkinson and Pickett (2009) and Piketty (2014) that we label ‘symphonic social science’. This bears bot...

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.

Big Data in Public Health: Terminology, Machine Learning, and Privacy.

Science.gov (United States)

Mooney, Stephen J; Pejaver, Vikas

2018-04-01

The digital world is generating data at a staggering and still increasing rate. While these "big data" have unlocked novel opportunities to understand public health, they hold still greater potential for research and practice. This review explores several key issues that have arisen around big data. First, we propose a taxonomy of sources of big data to clarify terminology and identify threads common across some subtypes of big data. Next, we consider common public health research and practice uses for big data, including surveillance, hypothesis-generating research, and causal inference, while exploring the role that machine learning may play in each use. We then consider the ethical implications of the big data revolution with particular emphasis on maintaining appropriate care for privacy in a world in which technology is rapidly changing social norms regarding the need for (and even the meaning of) privacy. Finally, we make suggestions regarding structuring teams and training to succeed in working with big data in research and practice.

Big Sites, Big Questions, Big Data, Big Problems: Scales of Investigation and Changing Perceptions of Archaeological Practice in the Southeastern United States

Directory of Open Access Journals (Sweden)

Cameron B Wesson

2014-08-01

Full Text Available Since at least the 1930s, archaeological investigations in the southeastern United States have placed a priority on expansive, near-complete, excavations of major sites throughout the region. Although there are considerable advantages to such large–scale excavations, projects conducted at this scale are also accompanied by a series of challenges regarding the comparability, integrity, and consistency of data recovery, analysis, and publication. We examine the history of large–scale excavations in the southeast in light of traditional views within the discipline that the region has contributed little to the ‘big questions’ of American archaeology. Recently published analyses of decades old data derived from Southeastern sites reveal both the positive and negative aspects of field research conducted at scales much larger than normally undertaken in archaeology. Furthermore, given the present trend toward the use of big data in the social sciences, we predict an increased use of large pre–existing datasets developed during the New Deal and other earlier periods of archaeological practice throughout the region.

The secret of the blue fog

Science.gov (United States)

Henrich, Oliver; Marenduzzo, Davide

2017-04-01

Why certain liquids turn blue when cooled was a mystery that stumped scientists for more than a century. As Oliver Henrich and Davide Marenduzzo explain, solving the secret of the “blue fog” proved to be an intellectual tour de force - and one that could lead to new types of display devices

Tapered photonic crystal fibers for blue-enhanced supercontinuum generation

DEFF Research Database (Denmark)

Møller, Uffe; Sørensen, Simon Toft; Larsen, Casper

2012-01-01

Tapering of photonic crystal fibers is an effective way of shifting the blue edge of a supercontinuum spectrum down in the deep-blue. We discuss the optimum taper profile for enhancing the power in the blue edge....

A proposed framework of big data readiness in public sectors

Science.gov (United States)

Ali, Raja Haslinda Raja Mohd; Mohamad, Rosli; Sudin, Suhizaz

2016-08-01

Growing interest over big data mainly linked to its great potential to unveil unforeseen pattern or profiles that support organisation's key business decisions. Following private sector moves to embrace big data, the government sector has now getting into the bandwagon. Big data has been considered as one of the potential tools to enhance service delivery of the public sector within its financial resources constraints. Malaysian government, particularly, has considered big data as one of the main national agenda. Regardless of government commitment to promote big data amongst government agencies, degrees of readiness of the government agencies as well as their employees are crucial in ensuring successful deployment of big data. This paper, therefore, proposes a conceptual framework to investigate perceived readiness of big data potentials amongst Malaysian government agencies. Perceived readiness of 28 ministries and their respective employees will be assessed using both qualitative (interview) and quantitative (survey) approaches. The outcome of the study is expected to offer meaningful insight on factors affecting change readiness among public agencies on big data potentials and the expected outcome from greater/lower change readiness among the public sectors.

Big data analytics to improve cardiovascular care: promise and challenges.

Science.gov (United States)

Rumsfeld, John S; Joynt, Karen E; Maddox, Thomas M

2016-06-01

The potential for big data analytics to improve cardiovascular quality of care and patient outcomes is tremendous. However, the application of big data in health care is at a nascent stage, and the evidence to date demonstrating that big data analytics will improve care and outcomes is scant. This Review provides an overview of the data sources and methods that comprise big data analytics, and describes eight areas of application of big data analytics to improve cardiovascular care, including predictive modelling for risk and resource use, population management, drug and medical device safety surveillance, disease and treatment heterogeneity, precision medicine and clinical decision support, quality of care and performance measurement, and public health and research applications. We also delineate the important challenges for big data applications in cardiovascular care, including the need for evidence of effectiveness and safety, the methodological issues such as data quality and validation, and the critical importance of clinical integration and proof of clinical utility. If big data analytics are shown to improve quality of care and patient outcomes, and can be successfully implemented in cardiovascular practice, big data will fulfil its potential as an important component of a learning health-care system.

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)

A Rare Case of Multifocal Prostatic Blue Nevus

Directory of Open Access Journals (Sweden)

Elias J. Farran

2018-01-01

Full Text Available Prostatic blue nevus is a rare benign pathologic diagnosis most commonly diagnosed incidentally on many different types of prostate specimens. Blue nevus is the deposition of stromal melanin characterized by spindle cells within the fibromuscular stroma which stains positive for melanin-specific stains Fontana-Masson and S100 and stains negative for CD68, HMB45, and iron stains. We report the case of a multifocal and bilateral blue nevus in a 52-year-old Hispanic male who presented with an elevated prostate-specific antigen of 4.3 and mild obstructive lower urinary tract symptoms, found by transrectal ultrasound-guided prostate needle biopsy. The biopsy also revealed benign prostatic tissue with postatrophic hyperplasia and chronic inflammation. This is the 35th reported case of prostatic blue nevus and the third to show multifocal blue nevus.

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...

Probing the pre-big bang universe

International Nuclear Information System (INIS)

Veneziano, G.

2000-01-01

Superstring theory suggests a new cosmology whereby a long inflationary phase preceded a non singular big bang-like event. After discussing how pre-big bang inflation naturally arises from an almost trivial initial state of the Universe, I will describe how present or near-future experiments can provide sensitive probes of how the Universe behaved in the pre-bang era

CERN: A big year for LEP

International Nuclear Information System (INIS)

Anon.

1991-01-01

In April this year's data-taking period for CERN's big LEP electron-positron collider got underway, and is scheduled to continue until November. The immediate objective of the four big experiments - Aleph, Delphi, L3 and Opal - will be to increase considerably their stock of carefully recorded Z decays, currently totalling about three-quarters of a million

Blue Light Protects Against Temporal Frequency Sensitive Refractive Changes.

Science.gov (United States)

Rucker, Frances; Britton, Stephanie; Spatcher, Molly; Hanowsky, Stephan

2015-09-01

Time spent outdoors is protective against myopia. The outdoors allows exposure to short-wavelength (blue light) rich sunlight, while indoor illuminants can be deficient at short-wavelengths. In the current experiment, we investigate the role of blue light, and temporal sensitivity, in the emmetropization response. Five-day-old chicks were exposed to sinusoidal luminance modulation of white light (with blue; N = 82) or yellow light (without blue; N = 83) at 80% contrast, at one of six temporal frequencies: 0, 0.2, 1, 2, 5, 10 Hz daily for 3 days. Mean illumination was 680 lux. Changes in ocular components and corneal curvature were measured. Refraction, eye length, and choroidal changes were dependent on the presence of blue light (P light, refraction did not change across frequencies (mean change -0.24 [diopters] D), while in the absence of blue light, we observed a hyperopic shift (>1 D) at high frequencies, and a myopic shift (>-0.6 D) at low frequencies. With blue light there was little difference in eye growth across frequencies (77 μm), while in the absence of blue light, eyes grew more at low temporal frequencies and less at high temporal frequencies (10 vs. 0.2 Hz: 145 μm; P light. Illuminants rich in blue light can protect against myopic eye growth when the eye is exposed to slow changes in luminance contrast as might occur with near work.

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.

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

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...

Solution structure of leptospiral LigA4 Big domain

Energy Technology Data Exchange (ETDEWEB)

Mei, Song; Zhang, Jiahai [Hefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026 (China); Zhang, Xuecheng [School of Life Sciences, Anhui University, Hefei, Anhui 230039 (China); Tu, Xiaoming, E-mail: xmtu@ustc.edu.cn [Hefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026 (China)

2015-11-13

Pathogenic Leptospiraspecies express immunoglobulin-like proteins which serve as adhesins to bind to the extracellular matrices of host cells. Leptospiral immunoglobulin-like protein A (LigA), a surface exposed protein containing tandem repeats of bacterial immunoglobulin-like (Big) domains, has been proved to be involved in the interaction of pathogenic Leptospira with mammalian host. In this study, the solution structure of the fourth Big domain of LigA (LigA4 Big domain) from Leptospira interrogans was solved by nuclear magnetic resonance (NMR). The structure of LigA4 Big domain displays a similar bacterial immunoglobulin-like fold compared with other Big domains, implying some common structural aspects of Big domain family. On the other hand, it displays some structural characteristics significantly different from classic Ig-like domain. Furthermore, Stains-all assay and NMR chemical shift perturbation revealed the Ca{sup 2+} binding property of LigA4 Big domain. - Highlights: • Determining the solution structure of a bacterial immunoglobulin-like domain from a surface protein of Leptospira. • The solution structure shows some structural characteristics significantly different from the classic Ig-like domains. • A potential Ca{sup 2+}-binding site was identified by strains-all and NMR chemical shift perturbation.

Solution structure of leptospiral LigA4 Big domain

International Nuclear Information System (INIS)

Mei, Song; Zhang, Jiahai; Zhang, Xuecheng; Tu, Xiaoming

2015-01-01

Pathogenic Leptospiraspecies express immunoglobulin-like proteins which serve as adhesins to bind to the extracellular matrices of host cells. Leptospiral immunoglobulin-like protein A (LigA), a surface exposed protein containing tandem repeats of bacterial immunoglobulin-like (Big) domains, has been proved to be involved in the interaction of pathogenic Leptospira with mammalian host. In this study, the solution structure of the fourth Big domain of LigA (LigA4 Big domain) from Leptospira interrogans was solved by nuclear magnetic resonance (NMR). The structure of LigA4 Big domain displays a similar bacterial immunoglobulin-like fold compared with other Big domains, implying some common structural aspects of Big domain family. On the other hand, it displays some structural characteristics significantly different from classic Ig-like domain. Furthermore, Stains-all assay and NMR chemical shift perturbation revealed the Ca"2"+ binding property of LigA4 Big domain. - Highlights: • Determining the solution structure of a bacterial immunoglobulin-like domain from a surface protein of Leptospira. • The solution structure shows some structural characteristics significantly different from the classic Ig-like domains. • A potential Ca"2"+-binding site was identified by strains-all and NMR chemical shift perturbation.

Implementing the “Big Data” Concept in Official Statistics

Directory of Open Access Journals (Sweden)

О. V.

2017-02-01

Full Text Available Big data is a huge resource that needs to be used at all levels of economic planning. The article is devoted to the study of the development of the concept of “Big Data” in the world and its impact on the transformation of statistical simulation of economic processes. Statistics at the current stage should take into account the complex system of international economic relations, which functions in the conditions of globalization and brings new forms of economic development in small open economies. Statistical science should take into account such phenomena as gig-economy, common economy, institutional factors, etc. The concept of “Big Data” and open data are analyzed, problems of implementation of “Big Data” in the official statistics are shown. The ways of implementation of “Big Data” in the official statistics of Ukraine through active use of technological opportunities of mobile operators, navigation systems, surveillance cameras, social networks, etc. are presented. The possibilities of using “Big Data” in different sectors of the economy, also on the level of companies are shown. The problems of storage of large volumes of data are highlighted. The study shows that “Big Data” is a huge resource that should be used across the Ukrainian economy.

New Evidence on the Development of the Word "Big."

Science.gov (United States)

Sena, Rhonda; Smith, Linda B.

1990-01-01

Results indicate that curvilinear trend in children's understanding of word "big" is not obtained in all stimulus contexts. This suggests that meaning and use of "big" is complex, and may not refer simply to larger objects in a set. Proposes that meaning of "big" constitutes a dynamic system driven by many perceptual,…

Blue whales respond to anthropogenic noise.

Directory of Open Access Journals (Sweden)

Mariana L Melcón

Full Text Available Anthropogenic noise may significantly impact exposed marine mammals. This work studied the vocalization response of endangered blue whales to anthropogenic noise sources in the mid-frequency range using passive acoustic monitoring in the Southern California Bight. Blue whales were less likely to produce calls when mid-frequency active sonar was present. This reduction was more pronounced when the sonar source was closer to the animal, at higher sound levels. The animals were equally likely to stop calling at any time of day, showing no diel pattern in their sensitivity to sonar. Conversely, the likelihood of whales emitting calls increased when ship sounds were nearby. Whales did not show a differential response to ship noise as a function of the time of the day either. These results demonstrate that anthropogenic noise, even at frequencies well above the blue whales' sound production range, has a strong probability of eliciting changes in vocal behavior. The long-term implications of disruption in call production to blue whale foraging and other behaviors are currently not well understood.

Starting Small, Thinking Big - Continuum Magazine | NREL

Science.gov (United States)

, Thinking Big Stories NREL Helps Agencies Target New Federal Sustainability Goals Student Engagements Help solar power in the territory. Photo by Don Buchanan, VIEO Starting Small, Thinking Big NREL helps have used these actions to optimize that energy use.'" NREL's cross-organizational work supports

Investigating Seed Longevity of Big Sagebrush (Artemisia tridentata)

Science.gov (United States)

Wijayratne, Upekala C.; Pyke, David A.

2009-01-01

The Intermountain West is dominated by big sagebrush communities (Artemisia tridentata subspecies) that provide habitat and forage for wildlife, prevent erosion, and are economically important to recreation and livestock industries. The two most prominent subspecies of big sagebrush in this region are Wyoming big sagebrush (A. t. ssp. wyomingensis) and mountain big sagebrush (A. t. ssp. vaseyana). Increased understanding of seed bank dynamics will assist with sustainable management and persistence of sagebrush communities. For example, mountain big sagebrush may be subjected to shorter fire return intervals and prescribed fire is a tool used often to rejuvenate stands and reduce tree (Juniperus sp. or Pinus sp.) encroachment into these communities. A persistent seed bank for mountain big sagebrush would be advantageous under these circumstances. Laboratory germination trials indicate that seed dormancy in big sagebrush may be habitat-specific, with collections from colder sites being more dormant. Our objective was to investigate seed longevity of both subspecies by evaluating viability of seeds in the field with a seed retrieval experiment and sampling for seeds in situ. We chose six study sites for each subspecies. These sites were dispersed across eastern Oregon, southern Idaho, northwestern Utah, and eastern Nevada. Ninety-six polyester mesh bags, each containing 100 seeds of a subspecies, were placed at each site during November 2006. Seed bags were placed in three locations: (1) at the soil surface above litter, (2) on the soil surface beneath litter, and (3) 3 cm below the soil surface to determine whether dormancy is affected by continued darkness or environmental conditions. Subsets of seeds were examined in April and November in both 2007 and 2008 to determine seed viability dynamics. Seed bank samples were taken at each site, separated into litter and soil fractions, and assessed for number of germinable seeds in a greenhouse. Community composition data

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.

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.

Differential expression of isoproterenol-induced salivary polypeptides in two mouse strains that are congenic for the H-2 histocompatibility gene complex.

Science.gov (United States)

López Solís, Remigio O; Weis, Ulrike Kemmerling; Ceballos, Alicia Ramos; Salas, Gustavo Hoecker

2003-12-01

Two inbred mouse strains, A/Snell and A.Swiss, which were produced as congenic with regard to the H-2 histocompatibility gene complex, are homozygous for two different groups of isoproterenol-induced salivary polypeptides (IISP). These polypeptides, which have been considered as markers of the hypertrophic growth of the parotid acinar cells, are members of the complex family of salivary proline-rich proteins (PRP) on the basis of both their massive accumulation in the parotid acinar cells in response to chronic isoproterenol, secretory character, high solubility in trichloroacetic acid and metachromatic staining by Coomassie blue. IISP expressed in both mouse strains were identified by unidimensional SDS-polyacrylamide electrophoresis and Coomassie blue staining both in parotid gland homogenates and in whole salivas obtained from mice repeatedly stimulated at 24-h intervals with isoproterenol. Parotid glands from 40 mice (20 A/Snell and 20 A.Swiss) and salivas from 270 mice (200 A/Snell and 70 A.Swiss) were analyzed. One of the congenic strains (A/Snell) expressed five IISP (Mr 65, 61, 51.5, 38, and 37 kDa) and the other strain (A.Swiss) expressed six IISP (Mr 59, 57, 54.5, 46, 36, and 34 kDa). No inter-individual intra-strain variations were observed, thus defining strain-associated patterns of IISP (PRP). Copyright 2003 Wiley-Liss, Inc.

Blue-light emitting triazolopyridinium and triazoloquinolinium salts

KAUST Repository

Carboni, Valentina; Su, Xin; Qian, Hai; Aprahamian, Ivan; Credi, Alberto

2017-01-01

Compounds that emit blue light are of interest for applications that include optoelectronic devices and chemo/biosensing and imaging. The design and synthesis of small organic molecules that can act as high-efficiency deep-blue-light emitters

Big nuclear accidents

International Nuclear Information System (INIS)

Marshall, W.; Billingon, D.E.; Cameron, R.F.; Curl, S.J.

1983-09-01

Much of the debate on the safety of nuclear power focuses on the large number of fatalities that could, in theory, be caused by extremely unlikely but just imaginable reactor accidents. This, along with the nuclear industry's inappropriate use of vocabulary during public debate, has given the general public a distorted impression of the risks of nuclear power. The paper reviews the way in which the probability and consequences of big nuclear accidents have been presented in the past and makes recommendations for the future, including the presentation of the long-term consequences of such accidents in terms of 'loss of life expectancy', 'increased chance of fatal cancer' and 'equivalent pattern of compulsory cigarette smoking'. The paper presents mathematical arguments, which show the derivation and validity of the proposed methods of presenting the consequences of imaginable big nuclear accidents. (author)

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…

John C. Mather, the Big Bang, and the COBE

Science.gov (United States)

Bang theory and showing that the Big Bang was complete in the first instants, with only a tiny fraction dropdown arrow Site Map A-Z Index Menu Synopsis John C. Mather, the Big Bang, and the COBE Resources with collaborative work on understanding the Big Bang. Mather and Smoot analyzed data from NASA's Cosmic Background

Determinants of Colour Constancy and the Blue Bias

Science.gov (United States)

Gegenfurtner, Karl

2017-01-01

We investigated several sensory and cognitive determinants of colour constancy across 40 illumination hues. In the first experiment, we measured colour naming for the illumination and for the colour induced by the illumination on the colorimetric grey. Results confirmed that the induced colours are approximately complementary to the colour of the illumination. In the second experiment, we measured colour constancy using achromatic adjustments. Average colour constancy was perfect under the blue daylight illumination and decreased in colour directions away from the blue daylight illumination due to undershooting and a strong blue bias. Apart from this blue bias, colour constancy was not related to illumination discrimination and to chromatic detection measured previously with the same setup and stimuli. We also observed a strong negative relationship between the degree of colour constancy and the consensus of naming the illumination colour. Constancy coincided with a low naming consensus, in particular because bluish illumination colours were sometimes seen as achromatic. Blue bias and category consensus alone explained >68%, and all determinants together explained >94% of the variance of achromatic adjustments. These findings suggest that colour constancy is optimised for blue daylight. PMID:29348910

Hypnosis-associated blue-tinted vision: a case report

Directory of Open Access Journals (Sweden)

Savedoff Aaron D

2005-12-01

Full Text Available Abstract Background Self-hypnosis has been taught routinely at the SUNY Upstate Medical University for treatment of pulmonary symptoms thought to be amenable to psychological therapy. While using hypnosis for relaxation, four individuals, including a patient with cystic fibrosis, reported development of blue-tinted vision. Based on a search of the literature, we believe this is the first published report of hypnosis-associated blue-tinted vision. Case presentation The patient reported blue-tinted vision when he used hypnosis on an almost daily basis for seven years. The visual change typically occurred when he was relaxed. Moreover, a concurrent erection in the absence of sexual thoughts usually was present. The other three individuals reported blue-tinted vision after learning how to use hypnosis for relaxation as part of a group hypnosis instruction. Conclusion The blue-tinted vision experienced by the individuals in this report may be the result of an hypnosis-induced primary change in cognitive processing. Additionally, as the relaxing effect of hypnosis can be associated with a reduction in blood pressure and increased blood flow, hypnosis-associated blue-tinted vision also may be related to retinal vasodilation.

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

Translating Big Data into Smart Data for Veterinary Epidemiology.

Science.gov (United States)

VanderWaal, Kimberly; Morrison, Robert B; Neuhauser, Claudia; Vilalta, Carles; Perez, Andres M

2017-01-01

The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having "big data" to create "smart data," with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

Baryon symmetric big-bang cosmology

Energy Technology Data Exchange (ETDEWEB)

Stecker, F.W.

1978-04-01

The framework of baryon-symmetric big-bang cosmology offers the greatest potential for deducing the evolution of the universe as a consequence of physical laws and processes with the minimum number of arbitrary assumptions as to initial conditions in the big-bang. In addition, it offers the possibility of explaining the photon-baryon ratio in the universe and how galaxies and galaxy clusters are formed, and also provides the only acceptable explanation at present for the origin of the cosmic gamma ray background radiation.

Baryon symmetric big-bang cosmology

International Nuclear Information System (INIS)

Stecker, F.W.

1978-04-01

The framework of baryon-symmetric big-bang cosmology offers the greatest potential for deducing the evolution of the universe as a consequence of physical laws and processes with the minimum number of arbitrary assumptions as to initial conditions in the big-bang. In addition, it offers the possibility of explaining the photon-baryon ratio in the universe and how galaxies and galaxy clusters are formed, and also provides the only acceptable explanation at present for the origin of the cosmic gamma ray background radiation

Machine learning for Big Data analytics in plants.

Science.gov (United States)

Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

2014-12-01

Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

33 CFR 117.677 - Big Sunflower River.

Science.gov (United States)

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Big Sunflower River. 117.677 Section 117.677 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES DRAWBRIDGE OPERATION REGULATIONS Specific Requirements Mississippi § 117.677 Big Sunflower River. The draw of...

Anti-prion activity of Brilliant Blue G.

Directory of Open Access Journals (Sweden)

Yoshifumi Iwamaru

Full Text Available BACKGROUND: Prion diseases are fatal neurodegenerative disorders with no effective therapy currently available. Accumulating evidence has implicated over-activation of P2X7 ionotropic purinergic receptor (P2X7R in the progression of neuronal loss in several neurodegenerative diseases. This has led to the speculation that simultaneous blockade of this receptor and prion replication can be an effective therapeutic strategy for prion diseases. We have focused on Brilliant Blue G (BBG, a well-known P2X7R antagonist, possessing a chemical structure expected to confer anti-prion activity and examined its inhibitory effect on the accumulation of pathogenic isoforms of prion protein (PrPres in a cellular and a mouse model of prion disease in order to determine its therapeutic potential. PRINCIPAL FINDINGS: BBG prevented PrPres accumulation in infected MG20 microglial and N2a neural cells at 50% inhibitory concentrations of 14.6 and 3.2 µM, respectively. Administration of BBG in vivo also reduced PrPres accumulation in the brains of mice with prion disease. However, it did not appear to alleviate the disease progression compared to the vehicle-treated controls, implying a complex role of P2X7R on the neuronal degeneration in prion diseases. SIGNIFICANCE: These results provide novel insights into the pathophysiology of prion diseases and have important implications for the treatment.

How does the blue-ringed octopus (Hapalochlaena lunulata) flash its blue rings?

Science.gov (United States)

Mäthger, Lydia M; Bell, George R R; Kuzirian, Alan M; Allen, Justine J; Hanlon, Roger T

2012-11-01

The blue-ringed octopus (Hapalochlaena lunulata), one of the world's most venomous animals, has long captivated and endangered a large audience: children playing at the beach, divers turning over rocks, and biologists researching neurotoxins. These small animals spend much of their time in hiding, showing effective camouflage patterns. When disturbed, the octopus will flash around 60 iridescent blue rings and, when strongly harassed, bite and deliver a neurotoxin that can kill a human. Here, we describe the flashing mechanism and optical properties of these rings. The rings contain physiologically inert multilayer reflectors, arranged to reflect blue-green light in a broad viewing direction. Dark pigmented chromatophores are found beneath and around each ring to enhance contrast. No chromatophores are above the ring; this is unusual for cephalopods, which typically use chromatophores to cover or spectrally modify iridescence. The fast flashes are achieved using muscles under direct neural control. The ring is hidden by contraction of muscles above the iridophores; relaxation of these muscles and contraction of muscles outside the ring expose the iridescence. This mechanism of producing iridescent signals has not previously been reported in cephalopods and we suggest that it is an exceptionally effective way to create a fast and conspicuous warning display.

Big Data, Big Consequences? Een verkenning naar privacy en big data gebruik binnen de opsporing, vervolging en rechtspraak

NARCIS (Netherlands)

Lodder, A.R.; van der Meulen, N.S.; Wisman, T.H.A.; Meij, Lisette; Zwinkels, C.M.M.

2014-01-01

In deze verkenning is ingegaan op de privacy aspecten van Big Data analysis binnen het domein Veiligheid en Justitie. Besproken zijn toepassingen binnen de rechtspraak zoals voorspellen van uitspraken en gebruik in rechtszaken. Met betrekking tot opsporing is onder andere ingegaan op predictive

Big Data Components for Business Process Optimization

Directory of Open Access Journals (Sweden)

Mircea Raducu TRIFU

2016-01-01

Full Text Available In these days, more and more people talk about Big Data, Hadoop, noSQL and so on, but very few technical people have the necessary expertise and knowledge to work with those concepts and technologies. The present issue explains one of the concept that stand behind two of those keywords, and this is the map reduce concept. MapReduce model is the one that makes the Big Data and Hadoop so powerful, fast, and diverse for business process optimization. MapReduce is a programming model with an implementation built to process and generate large data sets. In addition, it is presented the benefits of integrating Hadoop in the context of Business Intelligence and Data Warehousing applications. The concepts and technologies behind big data let organizations to reach a variety of objectives. Like other new information technologies, the main important objective of big data technology is to bring dramatic cost reduction.

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 structure of the big magnetic storms

International Nuclear Information System (INIS)

Mihajlivich, J. Spomenko; Chop, Rudi; Palangio, Paolo

2010-01-01

The records of geomagnetic activity during Solar Cycles 22 and 23 (which occurred from 1986 to 2006) indicate several extremely intensive A-class geomagnetic storms. These were storms classified in the category of the Big Magnetic Storms. In a year of maximum solar activity during Solar Cycle 23, or more precisely, during a phase designated as a post-maximum phase in solar activity (PPM - Phase Post maximum), near the autumn equinox, on 29, October 2003, an extremely strong and intensive magnetic storm was recorded. In the first half of November 2004 (7, November 2004) an intensive magnetic storm was recorded (the Class Big Magnetic Storm). The level of geomagnetic field variations which were recorded for the selected Big Magnetic Storms, was ΔD st=350 nT. For the Big Magnetic Storms the indicated three-hour interval indices geomagnetic activity was Kp = 9. This study presents the spectral composition of the Di - variations which were recorded during magnetic storms in October 2003 and November 2004. (Author)

Big data analytics a practical guide for managers

CERN Document Server

Pries, Kim H

2015-01-01

IntroductionSo What Is Big Data?Growing Interest in Decision MakingWhat This Book AddressesThe Conversation about Big DataTechnological Change as a Driver of Big DataThe Central Question: So What?Our Goals as AuthorsReferencesThe Mother of Invention's Triplets: Moore's Law, the Proliferation of Data, and Data Storage TechnologyMoore's LawParallel Computing, Between and Within MachinesQuantum ComputingRecap of Growth in Computing PowerStorage, Storage EverywhereGrist for the Mill: Data Used and

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.

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.

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

Big Cities, Big Problems: Reason for the Elderly to Move?

NARCIS (Netherlands)

Fokkema, T.; de Jong-Gierveld, J.; Nijkamp, P.

1996-01-01

In many European countries, data on geographical patterns of internal elderly migration show that the elderly (55+) are more likely to leave than to move to the big cities. Besides emphasising the attractive features of the destination areas (pull factors), it is often assumed that this negative

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...

Integrating R and Hadoop for Big Data Analysis

Directory of Open Access Journals (Sweden)

Bogdan Oancea

2014-06-01

Full Text Available Analyzing and working with big data could be very difficult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with hundreds or even thousands of computing nodes. Official statistics is increasingly considering big data for deriving new statistics because big data sources could produce more relevant and timely statistics than traditional sources. One of the software tools successfully and wide spread used for storage and processing of big data sets on clusters of commodity hardware is Hadoop. Hadoop framework contains libraries, a distributed file-system (HDFS, a resource-management platform and implements a version of the MapReduce programming model for large scale data processing. In this paper we investigate the possibilities of integrating Hadoop with R which is a popular software used for statistical computing and data visualization. We present three ways of integrating them: R with Streaming, Rhipe and RHadoop and we emphasize the advantages and disadvantages of each solution.

Practice variation in Big-4 transparency reports

NARCIS (Netherlands)

Girdhar, Sakshi; Jeppesen, K.K.

2018-01-01

Purpose The purpose of this paper is to examine the transparency reports published by the Big-4 public accounting firms in the UK, Germany and Denmark to understand the determinants of their content within the networks of big accounting firms. Design/methodology/approach The study draws on a

In Vitro Chondrogenesis Transformation Study of Mouse Dental Pulp Stem Cells

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Shahrul Hisham Zainal Ariffin

2012-01-01

Full Text Available A major challenge in the application of mesenchymal stem cells in cartilage reconstruction is that whether the cells are able to differentiate into fully mature chondrocytes before grafting. The aim of this study was to isolate mouse dental pulp stem cells (DPSC and differentiate them into chondrocytes. For this investigation, morphological, molecular, and biochemical analyses for differentiated cells were used. To induce the chondrocyte differentiation, DPSC were cultured in chondrogenic medium (Zen-Bio, Inc.. Based on morphological analyses using toluidine blue staining, proteoglycan products appear in DPSC after 21 days of chondrocyte induction. Biochemical analyses in differentiated group showed that alkaline phosphatase activity was significantly increased at day 14 as compared to control (P<0.05. Cell viability analyses during the differentiation to chondrocytes also showed that these cells were viable during differentiation. However, after the 14th day of differentiation, there was a significant decrease (P<0.05 in the viability proportion among differentiated cells as compared to the control cells. In RT-PCR molecular analyses, mouse DPSC expressed Cd146 and Cd166 which indicated that these cells belong to mesenchymal stem cells. Coll I and Coll II markers showed high expression after 14 and 21 days, respectively. In conclusion, this study showed that DPSC successfully differentiated into chondrocytes.

Analyzing Big Data with the Hybrid Interval Regression Methods

Directory of Open Access Journals (Sweden)

Chia-Hui Huang

2014-01-01

Full Text Available Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM to analyze big data. Recently, the smooth support vector machine (SSVM was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes.

Do big gods cause anything?

DEFF Research Database (Denmark)

Geertz, Armin W.

2014-01-01

Dette er et bidrag til et review symposium vedrørende Ara Norenzayans bog Big Gods: How Religion Transformed Cooperation and Conflict (Princeton University Press 2013). Bogen er spændende men problematisk i forhold til kausalitet, ateisme og stereotyper om jægere-samlere.......Dette er et bidrag til et review symposium vedrørende Ara Norenzayans bog Big Gods: How Religion Transformed Cooperation and Conflict (Princeton University Press 2013). Bogen er spændende men problematisk i forhold til kausalitet, ateisme og stereotyper om jægere-samlere....