Big Data in Designing Clinical Trials: Opportunities and Challenges

Directory of Open Access Journals (Sweden)

Charles S. Mayo

2017-08-01

Full Text Available Emergence of big data analytics resource systems (BDARSs as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

p-STAT3 in luminal breast cancer: Integrated RNA-protein pooled analysis and results from the BIG 2-98 phase III trial.

Science.gov (United States)

Sonnenblick, Amir; Salgado, Roberto; Brohée, Sylvain; Zahavi, Tamar; Peretz, Tamar; Van den Eynden, Gert; Rouas, Ghizlane; Salmon, Asher; Francis, Prudence A; Di Leo, Angelo; Crown, John P A; Viale, Giuseppe; Daly, Laura; Javdan, Bahar; Fujisawa, Sho; De Azambuja, Evandro; Lieveke, Ameye; Piccart, Martine J; Bromberg, Jacqueline F; Sotiriou, Christos

2018-02-01

In the present study, in order to investigate the role of signal transducer and activator of transcription 3 (STAT3) in estrogen receptor (ER)-positive breast cancer prognosis, we evaluated the phosphorylated STAT3 (p-STAT3) status and investigated its effect on the outcome in a pooled analysis and in a large prospective adjuvant trial. By using the TCGA repository, we developed gene signatures that reflected the level of p-STAT3. Using pooled analysis of the expression data from luminal breast cancer patients, we assessed the effects of the p-STAT3 expression signature on prognosis. We further validated the p-STAT3 prognostic effect using immunohistochemistry (IHC) and immunofluorescence staining of p-STAT3 tissue microarrays from a large randomised prospective trial. Our analysis demonstrated that p-STAT3 expression was elevated in luminal A-type breast cancer (Kruskal-Wallis test, PBIG 2-98 randomised trial. With a median follow-up of 10.1 years, p-STAT3 was associated with a reduced risk of recurrence in ER-positive/HER2-negative breast cancer (Cox univariate HR, 0.66; 95% CI, 0.44-0.98; P=0.04). On the whole, our data indicate that p-STAT3 is associated with an improved outcome in ER-positive breast cancer.

Corporate plan 1997/98 to 2001/02

International Nuclear Information System (INIS)

1997-01-01

The National Radiological Protection Board is a public authority established by the Radiological Protection Act 1970 with functions concerning the protection of people from radiation hazards. Members of the Board are appointed by the Health Ministers. Officers and employees of the Board are responsible to it for executing the functions. The Board produces a Corporate Plan which is presented to the Department of Health, its sponsoring Department. This is the Corporate Plan for 1997/98 and the subsequent four years to 2001/02. It follows from discussions with Government Departments and other customers and reflects Ministerial priorities. It also takes into account the recommendations of the recent Cabinet Office publication on Objective Setting and Monitoring in Executive Non-Departmental Public Bodies prepared by the Efficiency Unit. And it reflects the outcome of the recent Prior Options Review of the Board. The main purposes of the Corporate Plan are to describe the broad programme of work for the planning period and the manner in which it is to be implemented, to identify the strategic and specific objectives, and to make the necessary financial forecasts. (author)

200 Area effluent treatment facility process control plan 98-02

International Nuclear Information System (INIS)

Le, E.Q.

1998-01-01

This Process Control Plan (PCP) provides a description of the background information, key objectives, and operating criteria defining Effluent Treatment Facility (ETF) Campaign 98-02 as required per HNF-IP-0931 Section 37, Process Control Plans. Campaign 98-62 is expected to process approximately 18 millions gallons of groundwater with an assumption that the UP-1 groundwater pump will be shut down on June 30, 1998. This campaign will resume the UP-1 groundwater treatment operation from Campaign 97-01. The Campaign 97-01 was suspended in November 1997 to allow RCRA waste in LERF Basin 42 to be treated to meet the Land Disposal Restriction Clean Out requirements. The decision to utilize ETF as part of the selected interim remedial action of the 200-UP-1 Operable Unit is documented by the Declaration of the Record of Decision, (Ecology, EPA and DOE 1997). The treatment method was chosen in accordance with the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) as amended by the Superfund Amendments and Reauthorization Act of 1986 (SARA), the Hanford Federal Facility Agreement and Consent Order (known as the Tri-Party Agreement or TPA), and to the extent practicable, the National Oil and Hazardous Substances Pollution Contingency Plan (NCP)

Assessment of letrozole and tamoxifen alone and in sequence for postmenopausal women with steroid hormone receptor-positive breast cancer: the BIG 1-98 randomised clinical trial at 8·1 years median follow-up.

Science.gov (United States)

Regan, Meredith M; Neven, Patrick; Giobbie-Hurder, Anita; Goldhirsch, Aron; Ejlertsen, Bent; Mauriac, Louis; Forbes, John F; Smith, Ian; Láng, István; Wardley, Andrew; Rabaglio, Manuela; Price, Karen N; Gelber, Richard D; Coates, Alan S; Thürlimann, Beat

2011-11-01

Postmenopausal women with hormone receptor-positive early breast cancer have persistent, long-term risk of breast-cancer recurrence and death. Therefore, trials assessing endocrine therapies for this patient population need extended follow-up. We present an update of efficacy outcomes in the Breast International Group (BIG) 1-98 study at 8·1 years median follow-up. BIG 1-98 is a randomised, phase 3, double-blind trial of postmenopausal women with hormone receptor-positive early breast cancer that compares 5 years of tamoxifen or letrozole monotherapy, or sequential treatment with 2 years of one of these drugs followed by 3 years of the other. Randomisation was done with permuted blocks, and stratified according to the two-arm or four-arm randomisation option, participating institution, and chemotherapy use. Patients, investigators, data managers, and medical reviewers were masked. The primary efficacy endpoint was disease-free survival (events were invasive breast cancer relapse, second primaries [contralateral breast and non-breast], or death without previous cancer event). Secondary endpoints were overall survival, distant recurrence-free interval (DRFI), and breast cancer-free interval (BCFI). The monotherapy comparison included patients randomly assigned to tamoxifen or letrozole for 5 years. In 2005, after a significant disease-free survival benefit was reported for letrozole as compared with tamoxifen, a protocol amendment facilitated the crossover to letrozole of patients who were still receiving tamoxifen alone; Cox models and Kaplan-Meier estimates with inverse probability of censoring weighting (IPCW) are used to account for selective crossover to letrozole of patients (n=619) in the tamoxifen arm. Comparison of sequential treatments to letrozole monotherapy included patients enrolled and randomly assigned to letrozole for 5 years, letrozole for 2 years followed by tamoxifen for 3 years, or tamoxifen for 2 years followed by letrozole for 3 years

Symptoms of endocrine treatment and outcome in the BIG 1-98 study.

Science.gov (United States)

Huober, J; Cole, B F; Rabaglio, M; Giobbie-Hurder, A; Wu, J; Ejlertsen, B; Bonnefoi, H; Forbes, J F; Neven, P; Láng, I; Smith, I; Wardley, A; Price, K N; Goldhirsch, A; Coates, A S; Colleoni, M; Gelber, R D; Thürlimann, B

2014-01-01

There may be a relationship between the incidence of vasomotor and arthralgia/myalgia symptoms and treatment outcomes for postmenopausal breast cancer patients with endocrine-responsive disease who received adjuvant letrozole or tamoxifen. Data on patients randomized into the monotherapy arms of the BIG 1-98 clinical trial who did not have either vasomotor or arthralgia/myalgia/carpal tunnel (AMC) symptoms reported at baseline, started protocol treatment and were alive and disease-free at the 3-month landmark (n = 4,798) and at the 12-month landmark (n = 4,682) were used for this report. Cohorts of patients with vasomotor symptoms, AMC symptoms, neither, or both were defined at both 3 and 12 months from randomization. Landmark analyses were performed for disease-free survival (DFS) and for breast cancer free interval (BCFI), using regression analysis to estimate hazard ratios (HR) and 95 % confidence intervals (CI). Median follow-up was 7.0 years. Reporting of AMC symptoms was associated with better outcome for both the 3- and 12-month landmark analyses [e.g., 12-month landmark, HR (95 % CI) for DFS = 0.65 (0.49-0.87), and for BCFI = 0.70 (0.49-0.99)]. By contrast, reporting of vasomotor symptoms was less clearly associated with DFS [12-month DFS HR (95 % CI) = 0.82 (0.70-0.96)] and BCFI (12-month DFS HR (95 % CI) = 0.97 (0.80-1.18). Interaction tests indicated no effect of treatment group on associations between symptoms and outcomes. While reporting of AMC symptoms was clearly associated with better DFS and BCFI, the association between vasomotor symptoms and outcome was less clear, especially with respect to breast cancer-related events.

X-ray photoelectron spectroscopy investigations of band offsets in Ga0.02Zn0.98O/ZnO heterojunction for UV photodetectors

Science.gov (United States)

Singh, Karmvir; Rawal, Ishpal; Punia, Rajesh; Dhar, Rakesh

2017-10-01

Here, we report the valence and conduction band offset measurements in pure ZnO and the Ga0.02Zn0.98O/ZnO heterojunction by X-Ray photoelectron spectroscopy studies for UV photodetector applications. For detailed investigations on the band offsets and UV photodetection behavior of Ga0.02Zn0.98O/ZnO heterostructures, thin films of pristine ZnO, Ga-doped ZnO (Ga0.02Zn0.98O), and heterostructures of Ga-doped ZnO with ZnO (Ga0.02Zn0.98O/ZnO) were deposited using a pulsed laser deposition technique. The deposited thin films were characterized by X-ray diffraction, atomic force microscopy, and UV-Vis spectroscopy. X-ray photoelectron spectroscopy studies were carried out on all the thin films for the investigation of valence and conduction band offsets. The valence band was found to be shifted by 0.28 eV, while the conduction band has a shifting of -0.272 eV in the Ga0.02Zn0.98O/ZnO heterojunction as compared to pristine ZnO thin films. All the three samples were analyzed for photoconduction behavior under UVA light of the intensity of 3.3 mW/cm2, and it was observed that the photoresponse of pristine ZnO (19.75%) was found to increase with 2 wt. % doping of Ga (22.62%) and heterostructured thin films (29.10%). The mechanism of UV photodetection in the deposited samples has been discussed in detail, and the interaction of chemisorbed oxygen on the ZnO surface with holes generated by UV light exposure has been the observed mechanism for the change in electrical conductivity responsible for UV photoresponse on the present deposited ZnO films.

Phase, microstructure and microwave dielectric properties of Mg0:95Ni0:05Ti0:98Zr0:02O3 ceramics

Directory of Open Access Journals (Sweden)

Manan Abdul

2015-03-01

Full Text Available Mg0:95Ni0:05Ti0:98Zr0:02O3 ceramics was prepared via conventional solid-state mixed-oxide route. The phase, microstructure and microwave dielectric properties of the sintered samples were characterized using X-ray diffraction (XRD, scanning electron microscopy (SEM and a vector network analyzer. The microstructure comprised of circular and elongated plate-like grains. The semi quantitative analysis (EDS of the circular and elongated grains revealed the existence of Mg0:95Ni0:05T2O5 as a secondary phase along with the parent Mg0:95Ni0:05Ti0:98Zr0:02O3 phase, which was consistent with the XRD findings. In the present study, εr ~17.1, Qufo~195855 ± 2550 GHz and τf ~ -46 ppm/K was achieved for the synthesized Mg0:95Ni0:05Ti0:98Zr0:02O3 ceramics sintered at 1325 °C for 4 h.

Magnetic properties of the compound Zn(Mnsub(0.98)Fesub(0.02)2O4

International Nuclear Information System (INIS)

Wautelet, M.; Gerard, A.

1975-01-01

Moessbauer spectra were measured of the compound Zn(Mnsub(0.98)Fesub(0.02)) 2 O 4 at several temperatures between 4.2 and 77 K. Evaluation of the spectra showed that the Neel temperature of ZnMn 2 O 4 does not exceed 50 K; the magnetic structure seems to be the same as that of Mn 3 O 4 with predominant B-B interactions. (A.K.)

Nd{sub 39}Ir{sub 10.98}In{sub 36.02}. A complex intergrowth structure with CsCl- and AlB{sub 2}-related slabs

Energy Technology Data Exchange (ETDEWEB)

Dominyuk, Nataliya; Zaremba, Vasyl' I. [Ivan Franko National Univ., Lviv (Ukraine). Dept. of Inorganic Chemistry; Rodewald, Ute C.; Poettgen, Rainer [Muenster Univ. (Germany). Inst. fuer Anorganische und Analytische Chemie

2015-11-01

The ternary indide Nd{sub 39}Ir{sub 10.98}In{sub 36.02} was synthesized by arc-melting and characterized by single crystal X-ray diffraction. Nd{sub 39}Ir{sub 10.98}In{sub 36.02} crystallizes with a new structure type: Pearson code oP172, Pbam, a = 3175.4(6), b = 3762.5(8), c = 378.02(8) pm, wR2 = 0.0828, 5544 F{sup 2} values, and 262 variables. Although the structure contains 44 crystallographically independent sites, it can easily be explained as an intergrowth structure of CsCl and AlB{sub 2} related slabs. The larger indium atoms fill all distorted CsCl slabs. The trigonal prismatic (AlB{sub 2}) slabs have no uniform size. The larger ones are filled by indium and the smaller ones by the iridium atoms. Additionally, one trigonal prism shows a mixed occupancy by indium and iridium. The crystal chemistry of Nd{sub 39}Ir{sub 10.98}In{sub 36.02} is discussed in the context of other intergrowth structures with the same simple slabs.

Final Technical Report for Award DE-FG02-98ER41080

Energy Technology Data Exchange (ETDEWEB)

Chen, Alan

2014-11-14

The prime motivation of the project at McMaster University was to carry out the critical evaluation and compilation of Nuclear Structure and Decay data, and of nuclear astrophysics data with continued participation in the United States Nuclear Data Program (US-NDP). A large body of evaluated and compiled structure data were supplied for databases such as ENSDF, XUNDL, NSR, etc. residing on webpage of National Nuclear Data Center of the Brookhaven National Laboratory, Upton, New York, USA. Thermonuclear reaction rates of importance to stellar explosions, such as novae, x-ray bursts and supernovae, were evaluated as well. This effort was closely coupled to our ongoing experimental effort, which took advantage of radioactive ion beam and stable beam facilities worldwide to study these key reaction rates. This report contains brief descriptions of the various activities together with references to all the publications in peer-reviewed journals which were the result of work carried out with the award DE-FG02-98-ER41080, during 1998-2013.

Is risk of central nervous system (CNS) relapse related to adjuvant taxane treatment in node-positive breast cancer? Results of the CNS substudy in the intergroup Phase III BIG 02-98 Trial

DEFF Research Database (Denmark)

Pestalozzi, B.C.; Francis, P.; Quinaux, E.

2008-01-01

BACKGROUND: Breast cancer central nervous system (CNS) metastases are an increasingly important problem because of high CNS relapse rates in patients treated with trastuzumab and/or taxanes. PATIENTS AND METHODS: We evaluated data from 2887 node-positive breast cancer patients randomised in the BIG...

Prognostic and predictive role of ESR1 status for postmenopausal patients with endocrine-responsive early breast cancer in the Danish cohort of the BIG 1-98 trial

DEFF Research Database (Denmark)

Ejlertsen, B; Aldridge, J; Nielsen, K V

2012-01-01

postmenopausal Danish women with early breast cancer randomly assigned to receive 5 years of letrozole, tamoxifen or a sequence of these agents in the Breast International Group 1-98 trial and who had ER ≥1% after central review. RESULTS: By FISH, 13.6% of patients had an ESR1-to-Centromere-6 (CEN-6) ratio ≥2...... (amplified), and 4.2% had ESR1-to-CEN-6 ratio...

Big-pharmaceuticalisation: clinical trials and Contract Research Organisations in India.

Science.gov (United States)

Sariola, Salla; Ravindran, Deapica; Kumar, Anand; Jeffery, Roger

2015-04-01

The World Trade Organisation's Trade Related Intellectual Property Rights [TRIPS] agreement aimed to harmonise intellectual property rights and patent protection globally. In India, the signing of this agreement resulted in a sharp increase in clinical trials since 2005. The Indian government, along with larger Indian pharmaceutical companies, believed that they could change existing commercial research cultures through the promotion of basic research as well as attracting international clinical trials, and thus create an international level, innovation-based drug industry. The effects of the growth of these outsourced and off-shored clinical trials on local commercial knowledge production in India are still unclear. What has been the impact of the increasing scale and commercialisation of clinical research on corporate science in India? In this paper we describe Big-pharmaceuticalisation in India, whereby the local pharmaceutical industry is moving from generic manufacturing to innovative research. Using conceptual frameworks of pharmaceuticalisation and innovation, this paper analyses data from research conducted in 2010-2012 and describes how Contract Research Organisations (CROs) enable outsourcing of randomised control trials to India. Focussing on twenty-five semi-structured interviews CRO staff, we chart the changes in Indian pharmaceutical industry, and implications for local research cultures. We use Big-pharmaceuticalisation to extend the notion of pharmaceuticalisation to describe the spread of pharmaceutical research globally and illustrate how TRIPS has encouraged a concentration of capital in India, with large companies gaining increasing market share and using their market power to rewrite regulations and introduce new regulatory practices in their own interest. Contract Research Organisations, with relevant, new, epistemic skills and capacities, are both manifestations of the changes in commercial research cultures, as well as the vehicles to

Interventions for treating osteoarthritis of the big toe joint.

Science.gov (United States)

Zammit, Gerard V; Menz, Hylton B; Munteanu, Shannon E; Landorf, Karl B; Gilheany, Mark F

2010-09-08

Osteoarthritis affecting of the big toe joint of the foot (hallux limitus or rigidus) is a common and painful condition. Although several treatments have been proposed, few have been adequately evaluated. To identify controlled trials evaluating interventions for osteoarthritis of the big toe joint and to determine the optimum intervention(s). Literature searches were conducted across the following electronic databases: CENTRAL; MEDLINE; EMBASE; CINAHL; and PEDro (to 14th January 2010). No language restrictions were applied. Randomised controlled trials, quasi-randomised trials, or controlled clinical trials that assessed treatment outcomes for osteoarthritis of the big toe joint. Participants of any age or gender with osteoarthritis of the big toe joint (defined either radiographically or clinically) were included. Two authors examined the list of titles and abstracts identified by the literature searches. One content area expert and one methodologist independently applied the pre-determined inclusion and exclusion criteria to the full text of identified trials. To minimise error and reduce potential bias, data were extracted independently by two content experts. Only one trial satisfactorily fulfilled the inclusion criteria and was included in this review. This trial evaluated the effectiveness of two physical therapy programs in 20 individuals with osteoarthritis of the big toe joint. Assessment outcomes included pain levels, big toe joint range of motion and plantar flexion strength of the hallux. Mean differences at four weeks follow up were 3.80 points (95% CI 2.74 to 4.86) for self reported pain, 28.30 degrees (95% CI 21.37 to 35.23) for big toe joint range of motion, and 2.80 kg (95% CI 2.13 to 3.47) for muscle strength. Although differences in outcomes between treatment and control groups were reported, the risk of bias was high. The trial failed to employ appropriate randomisation or adequate allocation concealment, used a relatively small sample and

Sr{sub 1.98}Eu{sub 0.02}SiO{sub 4} luminescence whisker based on vapor-phase deposition: Facile synthesis, uniform morphology and enhanced luminescence properties

Energy Technology Data Exchange (ETDEWEB)

Xu, Jian, E-mail: xujian@stu.xmu.edu.cn [Department of Materials Science and Engineering, Xiamen University, Xiamen 361005 (China); Hassan, Dhia A. [Department of Materials Science and Engineering, Xiamen University, Xiamen 361005 (China); Department of Chemistry, College of Education for Pure Science, University of Basrah, 61004 (Iraq); Zeng, Renjie; Peng, Dongliang [Department of Materials Science and Engineering, Xiamen University, Xiamen 361005 (China); Fujian Key Lab of Advanced Special Material, Xiamen University, Xiamen 361005 (China); Key Laboratory of High Performance Ceramic Fibers, Ministry of Education, Xiamen 361005 (China)

2015-11-15

Highlights: • For the first time, it is possible to obtain Sr{sub 1.98}Eu{sub 0.02}SiO{sub 4} whisker. • The whiskers are smooth and uniform with L/D ratio over 50. • Durability and thermal stability of the whisker are enhanced. - Abstract: A high performance strontium silicate phosphor has been successfully synthesized though a facile vapor-phase deposition method. The product consists of single crystal whiskers which are smooth and uniform, and with a sectional equivalent diameter of around 5 μm; the aspect ratio is over 50 and no agglomeration can be observed. X-ray diffraction result confirmed that the crystal structure of the whisker was α’-Sr{sub 2}SiO{sub 4}. The exact chemical composition was Sr{sub 1.98}Eu{sub 0.02}SiO{sub 4} which was analyzed by energy dispersive spectrometer and inductively coupled plasma-mass spectrometer. The whisker shows broad green emission with peak at 523 nm ranging from 470 to 600 nm (excited at 370 nm). Compared with traditional Sr{sub 2}SiO{sub 4}:Eu phosphor, durability (at 85% humidity and 85 °C) and thermal stability of the whisker are obviously improved. Moreover, growth mechanism of the Sr{sub 1.98}Eu{sub 0.02}SiO{sub 4} whiskers is Vapor–Liquid–Solid. On a macro-scale, the product is still powder which makes it suitable for the current packaging process of WLEDs.

HER2 status predicts for upfront AI benefit: A TRANS-AIOG meta-analysis of 12,129 patients from ATAC, BIG 1-98 and TEAM with centrally determined HER2.

Science.gov (United States)

Bartlett, John M S; Ahmed, Ikhlaaq; Regan, Meredith M; Sestak, Ivana; Mallon, Elizabeth A; Dell'Orto, Patrizia; Thürlimann, Beat; Seynaeve, Caroline; Putter, Hein; Van de Velde, Cornelis J H; Brookes, Cassandra L; Forbes, John F; Viale, Giuseppe; Cuzick, Jack; Dowsett, Mitchell; Rea, Daniel W

2017-07-01

A meta-analysis of the effects of HER2 status, specifically within the first 2-3 years of adjuvant endocrine therapy, has the potential to inform patient selection for upfront aromatase inhibitor (AI) therapy or switching strategy tamoxifen followed by AI. The pre-existing standardisation of methodology for HER2 (immunohistochemistry/fluorescence in situ hybridization) facilitates analysis of existing data for this key marker. Following a prospectively designed statistical analysis plan, patient data from 3 phase III trials Arimidex, Tamoxifen, Alone or in Combination Trial (ATAC), Breast International Group (BIG) 1-98 and Tamoxifen Exemestane Adjuvant Multicentre Trial (TEAM)] comparing an AI to tamoxifen during the first 2-3 years of adjuvant endocrine treatment were collected and a treatment-by-marker analysis of distant recurrence-free interval-censored at 2-3 years treatment - for HER2 status × AI versus tamoxifen treatment was performed to address the clinical question relating to efficacy of 'upfront' versus 'switch' strategies for AIs. A prospectively planned, patient-level data meta-analysis across 3 trials demonstrated a significant treatment (AI versus tamoxifen) by marker (HER2) interaction in a multivariate analysis; (interaction hazard ratio [HR] = 1.61, 95% CI 1.01-2.57; p data meta-analysis demonstrated a significant interaction between HER2 status and treatment with AI versus tamoxifen in the first 2-3 years of adjuvant endocrine therapy. Patients with HER2-ve cancers experienced improved outcomes (distant relapse) when treated with upfront AI rather than tamoxifen, whilst patients with HER2+ve cancers fared no better or slightly worse in the first 2-3 years. However, the small number of HER2+ve cancers/events may explain a large degree of heterogeneity in the HER2+ve groups across all 3 trials. Other causes, perhaps related to subtle differences between AIs, cannot be excluded and warrant further exploration. Copyright © 2017 Elsevier Ltd

WE-H-BRB-02: Where Do We Stand in the Applications of Big Data in Radiation Oncology?

International Nuclear Information System (INIS)

Xing, L.

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.

WE-H-BRB-02: Where Do We Stand in the Applications of Big Data in Radiation Oncology?

Energy Technology Data Exchange (ETDEWEB)

Xing, L. [Stanford University School of Medicine (United States)

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.

CYP19A1 polymorphisms and clinical outcomes in postmenopausal women with hormone receptor-positive breast cancer in the BIG 1-98 trial

DEFF Research Database (Denmark)

Leyland-Jones, Brian; Gray, Kathryn P; Abramovitz, Mark

2015-01-01

To determine whether CYP19A1 polymorphisms are associated with abnormal activity of aromatase and with musculoskeletal and bone side effects of aromatase inhibitors. DNA was isolated from tumor specimens of 4861 postmenopausal women with hormone receptor-positive breast cancer enrolled in the BIG 1...

Features of the structural and magnetic properties of Pb(TixZr1–xO3-NiFe1.98Co0.02O4 in the polarized state

Directory of Open Access Journals (Sweden)

Baev Vadim

2017-06-01

Full Text Available Composites with a 90%Pb(TixZr1-xO3-10%NiFe1.98Co0.02O4 composition have been synthesized. It has been established that the polarization of samples resulting from exposure to an electric field for 1 hour of 4 kV/mm in strength at a temperature of 400 K leads to crystal structure deformation. The compression of elementary crystal cells in some areas during polarization of the sample creates conditions suitable for the enhancement of magnetic exchange interactions. It has been found that the polarization process of such compositions leads to increases in specific magnetization and magnetic susceptibility. The analysis of Mössbauer spectra has shown that the polarization of the 90%Pb(TixZr1-xO3-10%NiFe1.98Co0.02O4 composite leads to significant changes in the effective magnetic fields of iron subspectra in various positions.

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.

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.

Isovalent substitutes play in different ways: Effects of isovalent substitution on the thermoelectric properties of CoSi{sub 0.98}B{sub 0.02}

Energy Technology Data Exchange (ETDEWEB)

Sun, Hui, E-mail: huisun3@iflytek.com [Department of Basic Teaching, Anhui Institute of Information Technology, Wuhu, Anhui 241000 (China); Lu, Xu [College of Physics, Chongqing University, Chongqing 401331 (China); Morelli, Donald T. [Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, Michigan 48824 (United States)

2016-07-21

Boron-added CoSi, CoSi{sub 0.98}B{sub 0.02}, possesses a very high thermoelectric power factor of 60 μW cm{sup −1} K{sup −2} at room temperature, which is among the highest power factors that have ever been reported for near-room-temperature thermoelectric applications. Since the electrical properties of this material have been tuned properly, isovalent substitution for its host atoms is intentionally employed to reduce the lattice thermal conductivity while maintaining the electronic properties unchanged. In our previous work, the effect of Rh substitution for Co atoms on the thermoelectric properties of CoSi{sub 0.98}B{sub 0.02} has been studied. Here, we present a study of the substitution of Ge for Si atoms in this compound. Even though Ge and Rh are isovalent with their corresponding host atoms, they play different roles in determining the electrical and thermal transport properties. Through the evaluation of the lattice thermal conductivity by the Debye approximation and the comparison between the high-temperature Seebeck coefficients, we propose that Rh substitution leads to a further overlapping of the conduction and the valence bands, while Ge substitution only shifts the Fermi level upward into the conduction band. Our results show that the influence of isovalent substitution on the electronic structure cannot be ignored when the alloying method is used to improve thermoelectric properties.

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

40 CFR 98.7 - What standardized methods are incorporated by reference into this part?

Science.gov (United States)

2010-07-01

... Hydraulic Cement, IBR approved for §§ 98.84(a), 98.84(b), and 98.84(c). (3) ASTM D235-02 (Reapproved 2007... Method for Density, Relative Density (Specific Gravity), or API Gravity of Crude Petroleum and Liquid..., Compressibility Factor, and Relative Density of Gaseous Fuels, IBR approved for §§ 98.34(a) and 98.254(e). (21...

Environmental effects of the Big Rapids dam remnant removal, Big Rapids, Michigan, 2000-02

Science.gov (United States)

Healy, Denis F.; Rheaume, Stephen J.; Simpson, J. Alan

2003-01-01

The U.S. Geological Survey (USGS), in cooperation with the city of Big Rapids, investigated the environmental effects of removal of a dam-foundation remnant and downstream cofferdam from the Muskegon River in Big Rapids, Mich. The USGS applied a multidiscipline approach, which determined the water quality, sediment character, and stream habitat before and after dam removal. Continuous water-quality data and discrete water-quality samples were collected, the movement of suspended and bed sediment were measured, changes in stream habitat were assessed, and streambed elevations were surveyed. Analyses of water upstream and downstream from the dam showed that the dam-foundation remnant did not affect water quality. Dissolved-oxygen concentrations downstream from the dam remnant were depressed for a short period (days) during the beginning of the dam removal, in part because of that removal effort. Sediment transport from July 2000 through March 2002 was 13,800 cubic yards more at the downstream site than the upstream site. This increase in sediment represents the remobilized sediment upstream from the dam, bank erosion when the impoundment was lowered, and contributions from small tributaries between the sites. Five habitat reaches were monitored before and after dam-remnant removal. The reaches consisted of a reference reach (A), upstream from the effects of the impoundment; the impoundment (B); and three sites below the impoundment where habitat changes were expected (C, D, and E, in downstream order). Stream-habitat assessment reaches varied in their responses to the dam-remnant removal. Reference reach A was not affected. In impoundment reach B, Great Lakes and Environmental Assessment Section (GLEAS) Procedure 51 ratings went from fair to excellent. For the three downstream reaches, reach C underwent slight habitat degradation, but ratings remained good; reach D underwent slight habitat degradation with ratings changing from excellent to good; and, in an area

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

Development and processing temperature dependence of ferromagnetism in Zn0.98Co0.02O

International Nuclear Information System (INIS)

Hays, J.; Thurber, A.; Reddy, K. M.; Punnoose, A.; Engelhard, M. H.

2006-01-01

We report the development of room-temperature ferromagnetism (FM), with coercivity H c =2000 Oe and saturation magnetization M s ∼0.01 emu/g, in chemically synthesized powders of Zn 0.98 Co 0.02 O processed at 150 deg. C, and paramagnetism with antiferromagnetic interactions between the Co 2+ spins (S=3/2) in samples processed at higher temperatures 200≤T P ≤900 deg. C. X-ray diffraction data show a decrease in the lattice parameters a and c with T P , indicating a progressive incorporation of 0.58A sized tetrahedral Co 2+ at the substitutional sites of 0.60 A sized Zn 2+ . Diffuse reflectance spectra show three well defined absorption edges at 660, 615, and 568 nm due to the d-d crystal field transitions 4 A 2 (F)→ 2 E(G), 4 A 2 (F)→ 4 T 1 (P), and 4 A 2 (F)→ 2 T 1 (G) of high spin (S=3/2)Co 2+ in a tetrahedral crystal field, whose intensities increase with processing temperature. X-ray photoelectron spectroscopy shows that the doped Co 2+ ions in the 150 deg. C processed samples are located mostly on the surface of the particles and they disperse into the entire volume of the particles when processed at higher temperatures. The observations suggest that the FM most likely results from Co 2+ attached to the surface sites and it is lost in well dispersed samples formed at T P >150 deg. C

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…

Quality assurance audit: a prospective non-randomised trial of chemotherapy and radiotherapy for osteolymphoma (TROG 99.04/ALLG LY02).

Science.gov (United States)

Christie, D; Le, T; Watling, K; Cornes, D; O'Brien, P; Hitchins, R

2009-04-01

A quality assurance (QA) audit of the Trans Tasman Radiation Oncology Group and Australasian Lymphoma and Leukaemia Group trial (TROG 99.04/ALLG LY02) began after accrual of 25 patients. The trial is a prospective non-randomized study of standard treatment for osteolymphoma. Data relating to informed consent, eligibility, chemotherapy and radiotherapy were reviewed. The audit showed a relatively low level of major variations from the protocol, with an overall rate of 3.6%. As this trial has accrued slowly over a long period, the concept of QA has also developed. Amendments were made to the protocol accordingly. In the future, QA procedures should be predetermined, conducted rapidly in real time, and appropriately funded in order to be relevant to the ongoing conduct of the trial.

Generating ekpyrotic curvature perturbations before the big bang

International Nuclear Information System (INIS)

Lehners, Jean-Luc; Turok, Neil; McFadden, Paul; Steinhardt, Paul J.

2007-01-01

We analyze a general mechanism for producing a nearly scale-invariant spectrum of cosmological curvature perturbations during a contracting phase preceding a big bang, which can be entirely described using 4D effective field theory. The mechanism, based on first producing entropic perturbations and then converting them to curvature perturbations, can be naturally incorporated in cyclic and ekpyrotic models in which the big bang is modeled as a brane collision, as well as other types of cosmological models with a pre-big bang phase. We show that the correct perturbation amplitude can be obtained and that the spectral tilt n s tends to range from slightly blue to red, with 0.97 s <1.02 for the simplest models, a range compatible with current observations but shifted by a few percent towards the blue compared to the prediction of the simplest, large-field inflationary models

Effect of small quantity of chromium on the electrical, magnetic and magnetocaloric properties of Pr{sub 0.7}Ca{sub 0.3}Mn{sub 0.98}Cr{sub 0.02}O{sub 3} manganite

Energy Technology Data Exchange (ETDEWEB)

Bettaibi, A.; Rahmouni, H. [Universite de Gabes, Laboratoire de Physique des Materiaux et des Nanomateriaux appliquee a l' Environnement, Faculte des Sciences de Gabes cite Erriadh, Gabes (Tunisia); M' nassri, R. [Kairouan University, Higher Institute of Applied Sciences and Technology of Kasserine, Kasserine (Tunisia); Universite de Monastir, Laboratoire de Physico-Chimie des Materiaux, Departement de Physique, Faculte des Sciences de Monastir, Monastir (Tunisia); Selmi, A.; Cheikhrouhou, A. [Sfax University, Laboratory of Physics of Materials, Faculty of Sciences of Sfax, Sfax (Tunisia); Khirouni, K. [Kairouan University, Higher Institute of Applied Sciences and Technology of Kasserine, Kasserine (Tunisia); Chniba Boudjada, N. [Institut NEEL, Grenoble Cedex 09 (France)

2016-03-15

Structural, electrical and thermomagnetic properties of Pr{sub 0.7}Ca{sub 0.3}Mn{sub 0.98}Cr{sub 0.02}O{sub 3} were investigated. Sample was prepared by solid-state reaction method. X-ray diffraction revealed that the sample crystallizes in the orthorhombic system with Pnma space group. Electrical conductivity and complex impedance studies of Pr{sub 0.7}Ca{sub 0.3}Mn{sub 0.98}Cr{sub 0.02}O{sub 3} system are analyzed. The investigated compound exhibits a semiconductor behavior in the whole explored temperature range. From 100 to 206 K, the increase in DC conductance is more than two decade. At higher temperatures, the conductance varies slowly and a saturation region appears. The conduction mechanism is found to be governed by small polaron hopping process which is explained by the short range thermally activated energy. Conductance spectrum is well described by Jonsher law, and the temperature dependence of the frequency exponent confirms that conduction mechanism is governed by hopping process of the localized carriers. Using complex impedance analysis, the compound is modeled by an electrical equivalent circuit. Also, such analysis confirms the contribution of grain boundary to the transport properties. The substitution of Mn by 2 % Cr destroyed the charge order state observed in the parent compound and induced a ferromagnetic phase at low temperatures. For a magnetic field change of 5 T, the material shows a maximum magnetic entropy change ∇S {sup max} = 2.69 J kg{sup -1} K{sup -1} with a full width at half maximum δ {sub TFWHM} = 145 K, and a relative cooling power RCP = 389 J kg{sup -1}. Pr{sub 0.7}Ca{sub 0.3}Mn{sub 0.98}Cr{sub 0.02}O{sub 3} material demonstrates potential proprieties to be used in electronic and thermal devices and as magnetic refrigerant. (orig.)

Revisiting sample size: are big trials the answer?

Science.gov (United States)

Lurati Buse, Giovanna A L; Botto, Fernando; Devereaux, P J

2012-07-18

The superiority of the evidence generated in randomized controlled trials over observational data is not only conditional to randomization. Randomized controlled trials require proper design and implementation to provide a reliable effect estimate. Adequate random sequence generation, allocation implementation, analyses based on the intention-to-treat principle, and sufficient power are crucial to the quality of a randomized controlled trial. Power, or the probability of the trial to detect a difference when a real difference between treatments exists, strongly depends on sample size. The quality of orthopaedic randomized controlled trials is frequently threatened by a limited sample size. This paper reviews basic concepts and pitfalls in sample-size estimation and focuses on the importance of large trials in the generation of valid evidence.

NCBI nr-aa BLAST: CBRC-DDIS-02-0043 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-DDIS-02-0043 gb|AAL92369.2| similar to Homo sapiens (Human). Testis intercellular mediator... Peas (Sortilin 1) (Hypothetical protein) (Testis intracellular mediator protein) [Dictyostelium discoideum] AAL92369.2 1e-178 98% ...

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…

Bulk amorphous alloys: Preparation and properties of (Mg0.98Al0.02)x(Cu0.75Y0.25)100

DEFF Research Database (Denmark)

Eldrup, Morten Mostgaard; Pedersen, Allan Schrøder; Ohnuma, M.

2000-01-01

New bulk amorphous quaternary alloys of the composition (Mg1-xAlx)(60)Cu30Y10 (x = 0 - 0.17) were recently reported by the authors and preliminary results of the influence of Al content on the ability to form a bulk amorphous phase were presented. In the present note we extend this work to look...... for the influence of the Mg-Al content on the glass forming ability by studying a range of compositions, (Mg0.98Al0.02)(x)(Cu0.75Y0.25)(100-x) for x = 60 - 80 at.%. As previously, the alloys were prepared by a relatively simple technique, i.e. rapid cooling of the melt in a wedge-shaped copper mould. This method...... provides a range of cooling rates within a single ingot during the solidification that link the slowly and rapidly cooled microstructure for each alloy composition. Hence, the maximum thickness of the amorphous part of the cast material will be a measure of the glass forming ability (GFA) of the particular...

Influences of the Big Five personality traits on the treatment response and longitudinal course of depression in patients with acute coronary syndrome: A randomised controlled trial.

Science.gov (United States)

Kim, Seon-Young; Stewart, Robert; Bae, Kyung-Yeol; Kim, Sung-Wan; Shin, Il-Seon; Hong, Young Joon; Ahn, Youngkeun; Jeong, Myung Ho; Yoon, Jin-Sang; Kim, Jae-Min

2016-10-01

Influences of the Big Five personality traits on the treatment response and longitudinal course of depression in patients with acute coronary syndrome: A randomised controlled trial. This naturalistic observational study initially recruited 1152 ACS patients; 685 patients completed personality assessments at baseline, of whom 630 were followed-up one year later. Of the 294 patients with depression, 207 participated in a 24-week double blind trial of escitalopram or placebo. The remaining 87 patients who received medical treatment only and the 391 who had not depression were also followed in a one year naturalistic observational study. The Big five personality traits were assessed using the Big Five Inventory. The influences of personality on the Hamilton Depression Rating Scale score changes were analysed using a mixed-model repeated-measures analysis of covariance. A Cluster analysis identified two personality types: resilient and vulnerable. The vulnerable personality type was characterized by lower extraversion, agreeableness, and conscientiousness - but higher neuroticism - than the resilient type. This personality type was independently associated with a poorer outcome of depression in ACS patients during the 24-week treatment period and the one year longitudinal follow-up period compared to the resilient personality type, irrespective of treatment allocation. Recruitment from a single institution may limit generalisability. Personality traits were investigated 12-weeks after ACS; thus, the responses may have been influenced by the prior receipt of escitalopram. Personality types influences the treatment outcome and longitudinal course of depression in ACS patients independent of antidepressant treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

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

A new organically templated gallium(III)-doped chromium(III) fluorophosphite, (C2H10N2)[Ga0.98Cr0.02(HPO3)F3] hydrothermal synthesis, crystal structure and spectroscopic properties

International Nuclear Information System (INIS)

Fernandez-Armas, Sergio; Mesa, J.L.; Pizarro, J.L.; Lezama, Luis; Arriortua, M.I.; Rojo, T.

2004-01-01

A new organically templated fluoro-phosphite gallium(III)-doped chromium(III) with formula (C 2 H 10 N 2 )[Ga 0.98 Cr 0.02 (HPO 3 )F 3 ] has been synthesized by using mild hydrothermal conditions under autogeneous pressure. The crystal structure has been solved from X-ray single-crystal data. The compound crystallizes in the P2 1 2 1 2 1 orthorhombic space group, with the unit-cell parameters a=12.9417(7) A, b=9.4027(6) A, c=6.3502(4) A and Z=4. The final R factors were R1=0.022 (all data) and wR2=0.050. The crystal structure consists of [Ga 0.98 Cr 0.02 (HPO 3 )F 3 ] 2- anionic chains extended along the c-axis, with the ethylenediammonium cations placed in the cavities of the structure delimited by three different chains. The IR and Raman spectra show the characteristic bands of the phosphite oxoanion. The diffuse reflectance spectroscopy allowed us to calculate the Dq and Racah parameters of the Cr(III) cations in octahedral environment. The values are Dq=1375 cm -1 , B=780 cm -1 and C=3420 cm -1 . The polycrystalline ESR spectra performed at X and Q-bands show the signals belonging to the diluted Cr(III) cation in this phase. From the fit of the X-band ESR spectrum at 4.2 K, the calculated values of the axial (D) and rhombic (E) distortion parameters are 0.075 and 0.042 cm -1 , respectively, the components of the g-tensor being g x =1.98, g y =1.99 and g z =1.90

Big Bang nucleosynthesis in crisis?

International Nuclear Information System (INIS)

Hata, N.; Scherrer, R.J.; Steigman, G.; Thomas, D.; Walker, T.P.; Bludman, S.; Langacker, P.

1995-01-01

A new evaluation of the constraint on the number of light neutrino species (N ν ) from big bang nucleosynthesis suggests a discrepancy between the predicted light element abundances and those inferred from observations, unless the inferred primordial 4 He abundance has been underestimated by 0.014±0.004 (1σ) or less than 10% (95% C.L.) of 3 He survives stellar processing. With the quoted systematic errors in the observed abundances and a conservative chemical evolution parametrization, the best fit to the combined data is N ν =2.1±0.3 (1σ) and the upper limit is N ν ν =3) at the 98.6% C.L. copyright 1995 The American Physical Society

Euratom framework programme research in reactor safety main achievements of FP-4 ('94-'98), some preliminary results of FP-5 ('98-'02) and prospects for beyond 2002

Energy Technology Data Exchange (ETDEWEB)

Goethem, G. van; Martin Bermejo, J.; Zurita, A.; Lemaitre, P. [Commission of the European Communities, Brussels (BE). Directorate General for Science, Research and Development (DG 12)

2001-07-01

In this paper an overview is given of the most important aspects of the research activities organised by the European union (EU) in reactor safety, more specifically in the area ''Operational Safety of Existing Installations'', which is one of the 4 areas of the key action Nuclear Fission in the 5th Euratom framework programme (FP-5). In the introduction, a short description is given of the EU needs and the new boundary conditions for Euratom research. In the next 7 sections, the attention is drawn to a series of technical and socio-economical facts, which generate needs at the EU level and hence justify some actions - especially in terms of research - at the Commission level. The following needs have been identified and are proposed for discussion: to maintain the nuclear option open in order to ensure flexibility in energy supply; to maintain scientific and technical competence; to maintain industrial competitiveness and to prepare the next generation of reactors; to maintain a broad nuclear expertise covering both energetic and non-energetic applications; to develop environment-friendly sustainable solutions for the wastes; to share and improve the safety culture amongst the EU countries and the CEECs; and finally, to focus on public benefit and on added European value in Euratom research actions. A brief overview then is given of the European response - in terms of research - offered up to 2002 to contribute to meet some of the above needs, i.e. the Euratom research actions under FP-4 ('94-'98) and FP-5 ('98-'02). As far as the future beyond 2002 is concerned, the challenge to Euratom research is to identify networks of excellence and to reorganize itself in line with the new ERA concept (European research area). Finally conclusions are drawn on the perceived need to improve the fitness-for-purpose of Euratom research actions in the ''changing world'' and to rethink accordingly the organisation of

Big Data in Drug Discovery.

Science.gov (United States)

Brown, Nathan; Cambruzzi, Jean; Cox, Peter J; Davies, Mark; Dunbar, James; Plumbley, Dean; Sellwood, Matthew A; Sim, Aaron; Williams-Jones, Bryn I; Zwierzyna, Magdalena; Sheppard, David W

2018-01-01

Interpretation of Big Data in the drug discovery community should enhance project timelines and reduce clinical attrition through improved early decision making. The issues we encounter start with the sheer volume of data and how we first ingest it before building an infrastructure to house it to make use of the data in an efficient and productive way. There are many problems associated with the data itself including general reproducibility, but often, it is the context surrounding an experiment that is critical to success. Help, in the form of artificial intelligence (AI), is required to understand and translate the context. On the back of natural language processing pipelines, AI is also used to prospectively generate new hypotheses by linking data together. We explain Big Data from the context of biology, chemistry and clinical trials, showcasing some of the impressive public domain sources and initiatives now available for interrogation. © 2018 Elsevier B.V. All rights reserved.

Excitation functions of the 98Mo+d reactions

International Nuclear Information System (INIS)

Zarubin, P.P.; Padalko, V.Yu.; Khrisanfov, Yu.V.; Lebedev, P.P.; Podkopaev, Yu.N.

The excitation functions of the 98 Mo+d reactions were studied. The energy dependence of (d,p),(d,n) and (d,α) reactions was investigated by the activation analysis. The energies of deuterons in the range (6-12) MeV were determined by means of the aluminium filters. 98 Mo foils with surface densities of 1.02, 0.23 and 0.14 mgxcm -2 with 98 Mo enrichment of 94.1% were used as targets. The gamma spectra were measured by a Ge(Li) detector. The 98 Mo(d,p) 99 Mo reaction excitation function was determined via detection of 739 and 181 keV γ-radiation of 99 Mo (Tsub(1/2)=66.47h); 140 keV γ-radiation of 99 Tc (Tsub(1/2)=6h) was detected for the 98 Mo(d,n) 99 Tc reaction excitation function determination and 460, 568, 1091, 1200 and 1492 keV γ-quanta of 96 Nb (Tsub(1/2)=23.35h) - for the 98 Mo(d,α) 96 Nb reaction. In the excitation function the wide extremum was observed at Esub(d) approximately 10 MeV. The ratio of cross sections σsup(m)(d,n)/σ(d,p) on the 98 Mo target was determined. The ratio σsup(m)(d,n)/σ(d,p) was found to be decreasing function of the deuteron energy. The relative cross sections were determined with an accuracy of +-5%, while for the absolute values of cross sections the accuracy was +-15%

Near-infrared photoluminescence in La0.98AlO3: 0.02Ln3+(Ln = Nd/Yb) for sensitization of c-Si solar cells

Science.gov (United States)

Sawala, N. S.; Koparkar, K. A.; Bajaj, N. S.; Omanwar, S. K.

2016-05-01

The host matrix LaAlO3 was synthesized by conventional solid state reaction method in which the Nd3+ ions and Yb3+ ions successfully doped at 2mol% concentrations. The phase purity was confirmed by X ray powder diffraction (XRD) method. The photoluminescence (PL) properties were studied by spectrophotometer in near infra red (NIR) and ultra violet visible (UV-VIS) region. The Nd3+ ion doped LaAlO3 converts a visible (VIS) green photon (587 nm) into near infrared (NIR) photon (1070 nm) while Yb3+ ion doped converts ultra violet (UV) photon (221 nm) into NIR photon (980 nm). The La0.98AlO3: 0.02Ln3+(Ln = Nd / Yb) can be potentiality used for betterment of photovoltaic (PV) technology. This result further indicates its potential application as a luminescence converter layer for enhancing solar cells performance.

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…

[Big data in imaging].

Science.gov (United States)

Sewerin, Philipp; Ostendorf, Benedikt; Hueber, Axel J; Kleyer, Arnd

2018-04-01

Until now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.

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

Opportunities and Challenges for Drug Development: Public-Private Partnerships, Adaptive Designs and Big Data.

Science.gov (United States)

Yildirim, Oktay; Gottwald, Matthias; Schüler, Peter; Michel, Martin C

2016-01-01

Drug development faces the double challenge of increasing costs and increasing pressure on pricing. To avoid that lack of perceived commercial perspective will leave existing medical needs unmet, pharmaceutical companies and many other stakeholders are discussing ways to improve the efficiency of drug Research and Development. Based on an international symposium organized by the Medical School of the University of Duisburg-Essen (Germany) and held in January 2016, we discuss the opportunities and challenges of three specific areas, i.e., public-private partnerships, adaptive designs and big data. Public-private partnerships come in many different forms with regard to scope, duration and type and number of participants. They range from project-specific collaborations to strategic alliances to large multi-party consortia. Each of them offers specific opportunities and faces distinct challenges. Among types of collaboration, investigator-initiated studies are becoming increasingly popular but have legal, ethical, and financial implications. Adaptive trial designs are also increasingly discussed. However, adaptive should not be used as euphemism for the repurposing of a failed trial; rather it requires carefully planning and specification before a trial starts. Adaptive licensing can be a counter-part of adaptive trial design. The use of Big Data is another opportunity to leverage existing information into knowledge useable for drug discovery and development. Respecting limitations of informed consent and privacy is a key challenge in the use of Big Data. Speakers and participants at the symposium were convinced that appropriate use of the above new options may indeed help to increase the efficiency of future drug development.

Opportunities and challenges for drug development: public-private partnerships, adaptive designs and big data

Directory of Open Access Journals (Sweden)

Oktay Yildirim

2016-12-01

Full Text Available Drug development faces the double challenge of increasing costs and increasing pressure on pricing. To avoid that lack of perceived commercial perspective will leave existing medical needs unmet, pharmaceutical companies and many other stakeholders are discussing ways to improve the efficiency of drug Research & Development. Based on an international symposium organized by the Medical School of the University of Duisburg-Essen (Germany and held in January 2016, we discuss the opportunities and challenges of three specific areas, i.e. public-private partnerships, adaptive designs and big data. Public-private partnerships come in many different forms with regard to scope, duration and type and number of participants. They range from project-specific collaborations to strategic alliances to large multi-party consortia. Each of them offers specific opportunities and faces distinct challenges. Among types of collaboration, investigator-initiated studies are becoming increasingly popular but have legal, ethical and financial implications. Adaptive trial designs are also increasingly discussed. However, adaptive should not be used as euphemism for the repurposing of a failed trial; rather it requires carefully planning and specification before a trial starts. Adaptive licensing can be a counter-part of adaptive trial design. The use of Big Data is another opportunity to leverage existing information into knowledge useable for drug discovery and development. Respecting limitations of informed consent and privacy is a key challenge in the use of Big Data. Speakers and participants at the symposium were convinced that appropriate use of the above new options may indeed help to increase the efficiency of future drug development.

Opportunities and Challenges for Drug Development: Public–Private Partnerships, Adaptive Designs and Big Data

Science.gov (United States)

Yildirim, Oktay; Gottwald, Matthias; Schüler, Peter; Michel, Martin C.

2016-01-01

Drug development faces the double challenge of increasing costs and increasing pressure on pricing. To avoid that lack of perceived commercial perspective will leave existing medical needs unmet, pharmaceutical companies and many other stakeholders are discussing ways to improve the efficiency of drug Research and Development. Based on an international symposium organized by the Medical School of the University of Duisburg-Essen (Germany) and held in January 2016, we discuss the opportunities and challenges of three specific areas, i.e., public–private partnerships, adaptive designs and big data. Public–private partnerships come in many different forms with regard to scope, duration and type and number of participants. They range from project-specific collaborations to strategic alliances to large multi-party consortia. Each of them offers specific opportunities and faces distinct challenges. Among types of collaboration, investigator-initiated studies are becoming increasingly popular but have legal, ethical, and financial implications. Adaptive trial designs are also increasingly discussed. However, adaptive should not be used as euphemism for the repurposing of a failed trial; rather it requires carefully planning and specification before a trial starts. Adaptive licensing can be a counter-part of adaptive trial design. The use of Big Data is another opportunity to leverage existing information into knowledge useable for drug discovery and development. Respecting limitations of informed consent and privacy is a key challenge in the use of Big Data. Speakers and participants at the symposium were convinced that appropriate use of the above new options may indeed help to increase the efficiency of future drug development. PMID:27999543

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.

NCBI nr-aa BLAST: CBRC-DSIM-02-0079 [SEVENS

Lifescience Database Archive (English)

Full Text Available CBRC-DSIM-02-0079 ref|NP_477376.1| CG4585-PA [Drosophila melanogaster] dbj|BAA32689....1| unnamed protein product [Drosophila melanogaster] dbj|BAA32692.1| unnamed protein product [Drosophila mela...nogaster] gb|AAF47081.1| CG4585-PA [Drosophila melanogaster] gb|AAL28300.1| GH20310p [Drosophila melanogaster] NP_477376.1 0.0 98% ...

Developments in clinical trials: a Pharma Matters report.

Science.gov (United States)

Arjona, A; Nuskey, B; Rabasseda, X; Arias, E

2014-08-01

As the pharmaceutical industry strives to meet the ever-increasing complexity of drug development, new technology in clinical trials has become a beacon of hope. With big data comes the promise of accelerated patient recruitment, real-time monitoring of clinical trials, bioinformatics empowerment of quicker phase progression, and the overwhelming benefits of precision medicine for select trials. Risk-based monitoring stands to benefit as well. With a strengthening focus on centralized data by the FDA and industry's transformative initiative, TransCelerate, a new era in trial risk mitigation has begun. The traditional method of intensive on-site monitoring is becoming a thing of the past as statistical, real-time analysis of site and trial-wide data provides the means to monitor with greater efficiency and effectiveness from afar. However, when it comes to big data, there are challenges that lie ahead. Patient privacy, commercial investment protection, technology woes and data variability are all limitations to be met with considerable thought. At the Annual Meeting of the American Academy of Dermatology this year, clinical trials on psoriasis, atopic dermatitis and other skin diseases were discussed in detail. This review of clinical research reports on novel therapies for psoriasis and atopic dermatitis reveals the impact of these diseases and the drug candidates that have been successful in phase II and III studies. Data-focused highlights of novel dermatological trials, as well as real-life big data approaches and an insight on the new methodology of risk-based monitoring, are all discussed in this edition of Developments in Clinical Trials. Copyright 2014 Prous Science, S.A.U. or its licensors. All rights reserved.

Comparison of the effectiveness of 0.5% tea, 2% neem and 0.2% chlorhexidine mouthwashes on oral health: A randomized control trial

Directory of Open Access Journals (Sweden)

Aswini Y Balappanavar

2013-01-01

Full Text Available Background: The aim of this study was to evaluate and compare the effectiveness of 0.5% tea, 2% neem, and 0.2% chlorhexidine mouthwashes on oral health. Materials and Methods: A randomized blinded controlled trial with 30 healthy human volunteers of age group 18-25 years was carried out. The subjects were randomly assigned to 3 groups i.e., group A - 0.2% chlorhexidine gluconate (bench mark control, Group B - 2% neem, and group C - 0.5% tea of 10 subjects per group. Plaque accumulation and gingival condition were recorded using plaque index and gingival index. Oral hygiene was assessed by simplified oral hygiene index (OHIS. Salivary pH was assessed by indikrom pH strips. Plaque, gingival, and simplified OHI scores as well as salivary pH were recorded at baseline, immediately after 1 st rinse, after 1 week, 2 nd week, and 3 rd week. The 3 rd week was skipped for group A. Results: Mean plaque and gingival scores were reduced over the 3 week trial period for experimental and control groups. Anti-plaque effectiveness was observed in all groups and the highest being in group C (P < 0.05. Neem and tea showed comparative effectiveness on gingiva better than chlorhexidine (P < 0.05. The salivary pH rise was sustained and significant in Group B and C compared to Group A. Oral hygiene improvement was better appreciated in Group B and Group C. Conclusion: The effectiveness of 0.5% tea was more compared to 2% neem and 0.2% chlorhexidine mouth rinse.

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...

Oxygen Permeation and Stability Study of (La0.6Ca0.4)0.98(Co0.8Fe0.2)O3-δ Membranes

DEFF Research Database (Denmark)

Salehi, Mehdi; Søgaard, Martin; Esposito, Vincenzo

2017-01-01

) was tested. A small decrease in the flux was observed over 48 h in CO2 at 850 °C. SEM examinations of the cross-section of the tested membrane showed that the Ca rich phase in the membrane showed a tendency to migrate to the feed side. Whereas the material shows a CO2 stability superior to that of Sr or Ba......The perovskite-type oxide (La0.6Ca0.4)0.98(Co0.8Fe0.2)O3-δ (LCCF) was investigated for use as oxygen separation membrane. A 25 µm thick dense membrane on a porous LCCF support with a thickness of around 175 µm was prepared by a tape casting and lamination process. The optimum sintering temperature...... of the component was established to be 1050 °C by analysis of microstructures of membranes sintered at different temperatures. Scanning electron microscopy (SEM) examination of cross-sections of the sintered membrane showed that it consisted of two phases, the main phase being enriched in calcium (Ca) and depleted...

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

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...

A randomised comparison of radical radiotherapy with or without chemotherapy for patients with non-small cell lung cancer: Results from the Big Lung Trial

International Nuclear Information System (INIS)

Fairlamb, David; Milroy, Robert; Gower, Nicole; Parmar, Mahesh; Peake, Michael; Rudd, Robin; Souhami, Robert; Spiro, Stephen; Stephens, Richard; Waller, David

2005-01-01

Background: A meta-analysis of trials comparing primary treatment with or without chemotherapy for patients with non-small cell lung cancer published in 1995 suggested a survival benefit for cisplatin-based chemotherapy in each of the primary treatment settings studied, but it included many small trials, and trials with differing eligibility criteria and chemotherapy regimens. Methods: The Big Lung Trial was a large pragmatic trial designed to confirm the survival benefits seen in the meta-analysis, and this paper reports the findings in the radical radiotherapy setting. The trial closed before the required sample size was achieved due to slow accrual, with a total of 288 patients randomised to receive radical radiotherapy alone (146 patients) or sequential radical radiotherapy and cisplatin-based chemotherapy (142 patients). Results: There was no evidence that patients allocated sequential chemotherapy and radical radiotherapy had a better survival than those allocated radical radiotherapy alone, HR 1.07 (95% CI 0.84-1.38, P=0.57), median survival 13.0 months for the sequential group and 13.2 for the radical radiotherapy alone group. In addition, exploratory analyses could not identify any subgroup that might benefit more or less from chemotherapy. Conclusions: Despite not suggesting a survival benefit for the sequential addition of chemotherapy to radical radiotherapy, possibly because of the relatively small sample size and consequently wide confidence intervals, the results can still be regarded as consistent with the meta-analysis, and other similarly designed recently published large trials. Combining all these results suggests there may be a small median survival benefit with chemotherapy of between 2 and 8 weeks

Using predictive analytics and big data to optimize pharmaceutical outcomes.

Science.gov (United States)

Hernandez, Inmaculada; Zhang, Yuting

2017-09-15

The steps involved, the resources needed, and the challenges associated with applying predictive analytics in healthcare are described, with a review of successful applications of predictive analytics in implementing population health management interventions that target medication-related patient outcomes. In healthcare, the term big data typically refers to large quantities of electronic health record, administrative claims, and clinical trial data as well as data collected from smartphone applications, wearable devices, social media, and personal genomics services; predictive analytics refers to innovative methods of analysis developed to overcome challenges associated with big data, including a variety of statistical techniques ranging from predictive modeling to machine learning to data mining. Predictive analytics using big data have been applied successfully in several areas of medication management, such as in the identification of complex patients or those at highest risk for medication noncompliance or adverse effects. Because predictive analytics can be used in predicting different outcomes, they can provide pharmacists with a better understanding of the risks for specific medication-related problems that each patient faces. This information will enable pharmacists to deliver interventions tailored to patients' needs. In order to take full advantage of these benefits, however, clinicians will have to understand the basics of big data and predictive analytics. Predictive analytics that leverage big data will become an indispensable tool for clinicians in mapping interventions and improving patient outcomes. Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Long term effectiveness on prescribing of two multifaceted educational interventions: results of two large scale randomized cluster trials.

Directory of Open Access Journals (Sweden)

Nicola Magrini

Full Text Available INTRODUCTION: Information on benefits and risks of drugs is a key element affecting doctors' prescribing decisions. Outreach visits promoting independent information have proved moderately effective in changing prescribing behaviours. OBJECTIVES: Testing the short and long-term effectiveness on general practitioners' prescribing of small groups meetings led by pharmacists. METHODS: Two cluster open randomised controlled trials (RCTs were carried out in a large scale NHS setting. Ad hoc prepared evidence based material were used considering a therapeutic area approach--TEA, with information materials on osteoporosis or prostatic hyperplasia--and a single drug oriented approach--SIDRO, with information materials on me-too drugs of 2 different classes: barnidipine or prulifloxacin. In each study, all 115 Primary Care Groups in a Northern Italy area (2.2 million inhabitants, 1737 general practitioners were randomised to educational small groups meetings, in which available evidence was provided together with drug utilization data and clinical scenarios. Main outcomes were changes in the six-months prescription of targeted drugs. Longer term results (24 and 48 months were also evaluated. RESULTS: In the TEA trial, one of the four primary outcomes showed a reduction (prescription of alfuzosin compared to tamsulosin and terazosin in benign prostatic hyperplasia: prescribing ratio -8.5%, p = 0.03. Another primary outcome (prescription of risedronate showed a reduction at 24 and 48 months (-7.6%, p = 0.02; and -9,8%, p = 0.03, but not at six months (-5.1%, p = 0.36. In the SIDRO trial both primary outcomes showed a statistically significant reduction (prescription of barnidipine -9.8%, p = 0.02; prescription of prulifloxacin -11.1%, p = 0.04, which persisted or increased over time. INTERPRETATION: These two cluster RCTs showed the large scale feasibility of a complex educational program in a NHS setting, and its potentially

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...

Intention-to-treat analysis in the chronic suppurative otitis media trials

African Journals Online (AJOL)

There were no attempts in any of the trials to impute for missing responses and carrying out a sensitivity analysis. For trials with a big percentage of protocol deviations, the validity of their results are brought to question. Conclusions: In practice, not all those entered into a randomised-controlled trial will complete the trial.

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).

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.

Machine learning of big data in gaining insight into successful treatment of hypertension.

Science.gov (United States)

Koren, Gideon; Nordon, Galia; Radinsky, Kira; Shalev, Varda

2018-06-01

Despite effective medications, rates of uncontrolled hypertension remain high. Treatment protocols are largely based on randomized trials and meta-analyses of these studies. The objective of this study was to test the utility of machine learning of big data in gaining insight into the treatment of hypertension. We applied machine learning techniques such as decision trees and neural networks, to identify determinants that contribute to the success of hypertension drug treatment on a large set of patients. We also identified concomitant drugs not considered to have antihypertensive activity, which may contribute to lowering blood pressure (BP) control. Higher initial BP predicts lower success rates. Among the medication options and their combinations, treatment with beta blockers appears to be more commonly effective, which is not reflected in contemporary guidelines. Among numerous concomitant drugs taken by hypertensive patients, proton pump inhibitors (PPIs), and HMG CO-A reductase inhibitors (statins) significantly improved the success rate of hypertension. In conclusions, machine learning of big data is a novel method to identify effective antihypertensive therapy and for repurposing medications already on the market for new indications. Our results related to beta blockers, stemming from machine learning of a large and diverse set of big data, in contrast to the much narrower criteria for randomized clinic trials (RCTs), should be corroborated and affirmed by other methods, as they hold potential promise for an old class of drugs which may be presently underutilized. These previously unrecognized effects of PPIs and statins have been very recently identified as effective in lowering BP in preliminary clinical observations, lending credibility to our big data results.

High charge-discharge performance of Pb{sub 0.98}La{sub 0.02}(Zr{sub 0.35}Sn{sub 0.55}Ti{sub 0.10}){sub 0.995}O{sub 3} antiferroelectric ceramics

Energy Technology Data Exchange (ETDEWEB)

Xu, Chenhong [Key Laboratory of Inorganic Functional Materials and Devices, Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai 200050 (China); University of the Chinese Academy of Sciences, Beijing 100049 (China); Liu, Zhen; Chen, Xuefeng; Yan, Shiguang; Cao, Fei; Dong, Xianlin; Wang, Genshui, E-mail: genshuiwang@mail.sic.ac.cn [Key Laboratory of Inorganic Functional Materials and Devices, Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai 200050 (China)

2016-08-21

The energy storage performance and charge-discharge properties of Pb{sub 0.98}La{sub 0.02}(Zr{sub 0.35}Sn{sub 0.55}Ti{sub 0.10}){sub 0.995}O{sub 3} (PLZST) antiferroelectric ceramics were investigated through directly measuring the hysteresis loops and pulse discharge current-time curves. The energy density only varies 0.2% per degree from 25 °C to 85 °C, and the energy efficiency maintains at about 90%. Furthermore, an approximate calculating model of maximum power density p{sub max} was established for the discharge process. Under a relatively high working electric field (8.2 kV/mm), this ceramics possess a greatly enhanced power density of 18 MW/cm{sup 3}. Moreover, the pulse power properties did not show degradation until 1500 times of charge-discharge cycling. The large released energy density, high energy efficiency, good temperature stability, greatly enhanced power density, and excellent fatigue endurance combined together make this PLZST ceramics an ideal candidate for pulse power applications.

Safety, immunogenicity and duration of protection of the RTS,S/AS02(D malaria vaccine: one year follow-up of a randomized controlled phase I/IIb trial.

Directory of Open Access Journals (Sweden)

Pedro Aide

2010-11-01

Full Text Available The RTS,S/AS02(D vaccine has been shown to have a promising safety profile, to be immunogenic and to confer protection against malaria in children and infants.We did a randomized, controlled, phase I/IIb trial of RTS,S/AS02(D given at 10, 14 and 18 weeks of age staggered with routine immunization vaccines in 214 Mozambican infants. The study was double-blind until the young child completed 6 months of follow-up over which period vaccine efficacy against new Plasmodium falciparum infections was estimated at 65.9% (95% CI 42.6-79.8, p<0.0001. We now report safety, immunogenicity and estimated efficacy against clinical malaria up to 14 months after study start. Vaccine efficacy was assessed using Cox regression models. The frequency of serious adverse events was 32.7% in the RTS,S/AS02(D and 31.8% in the control group. The geometric mean titers of anti-circumsporozoite antibodies declined from 199.9 to 7.3 EU/mL from one to 12 months post dose three of RTS,S/AS02(D, remaining 15-fold higher than in the control group. Vaccine efficacy against clinical malaria was 33% (95% CI: -4.3-56.9, p = 0.076 over 14 months of follow-up. The hazard rate of disease per 2-fold increase in anti-CS titters was reduced by 84% (95% CI 35.1-88.2, p = 0.003.The RTS,S/AS02(D malaria vaccine administered to young infants has a good safety profile and remains efficacious over 14 months. A strong association between anti-CS antibodies and risk of clinical malaria has been described for the first time. The results also suggest a decrease of both anti-CS antibodies and vaccine efficacy over time.ClinicalTrials.gov NCT00197028.

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.

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.

Experimental Conditions: SE3_S02_M02_D02 [Metabolonote[Archive

Lifescience Database Archive (English)

Full Text Available SE3_S02_M02_D02 SE3 Comparison of fruit metabolites among tomato varieties 1 SE3_S0...2 Solanum lycopersicum House Momotaro fruit SE3_S02_M02 6.7 mg [MassBase ID] MDLC1_25530 SE3_MS1 LC-FT-ICR-M

Function of Nup98 subtypes and their fusion proteins, Nup98-TopIIβ and Nup98-SETBP1 in nuclear-cytoplasmic transport.

Science.gov (United States)

Saito, Shoko; Yokokawa, Takafumi; Iizuka, Gemmei; Cigdem, Sadik; Okuwaki, Mitsuru; Nagata, Kyosuke

2017-05-20

Nup98 is a component of the nuclear pore complex. The nup98-fusion genes derived by chromosome translocations are involved in hematopoietic malignancies. Here, we investigated the functions of Nup98 isoforms and two unexamined Nup98-fusion proteins, Nup98-TopIIβ and Nup98-SETBP1. We first demonstrated that two Nup98 isoforms are expressed in various mouse tissues and similarly localized in the nucleus and the nuclear envelope. We also showed that Nup98-TopIIβ and Nup98-SETBP1 are localized in the nucleus and partially co-localized with full-length Nup98 and a nuclear export receptor XPO1. We demonstrated that Nup98-TopIIβ and Nup98-SETBP1 negatively regulate the XPO1-mediated protein export. Our results will contribute to the understanding of the molecular mechanism by which the Nup98-fusion proteins induce tumorigenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Seasonal shifts in the diet of the big brown bat (Eptesicus fuscus), Fort Collins, Colorado

Science.gov (United States)

Valdez, Ernest W.; O'Shea, Thomas J.

2014-01-01

Recent analyses suggest that the big brown bat (Eptesicus fuscus) may be less of a beetle specialist (Coleoptera) in the western United States than previously thought, and that its diet might also vary with temperature. We tested the hypothesis that big brown bats might opportunistically prey on moths by analyzing insect fragments in guano pellets from 30 individual bats (27 females and 3 males) captured while foraging in Fort Collins, Colorado, during May, late July–early August, and late September 2002. We found that bats sampled 17–20 May (n = 12 bats) had a high (81–83%) percentage of volume of lepidopterans in guano, with the remainder (17–19% volume) dipterans and no coleopterans. From 28 May–9 August (n = 17 bats) coleopterans dominated (74–98% volume). On 20 September (n = 1 bat) lepidopterans were 99% of volume in guano. Migratory miller moths (Euxoa auxiliaris) were unusually abundant in Fort Collins in spring and autumn of 2002 and are known agricultural pests as larvae (army cutworms), suggesting that seasonal dietary flexibility in big brown bats has economic benefits.

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,

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

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

Development of the Lymphoma Enterprise Architecture Database: a caBIG Silver level compliant system.

Science.gov (United States)

Huang, Taoying; Shenoy, Pareen J; Sinha, Rajni; Graiser, Michael; Bumpers, Kevin W; Flowers, Christopher R

2009-04-03

Lymphomas are the fifth most common cancer in United States with numerous histological subtypes. Integrating existing clinical information on lymphoma patients provides a platform for understanding biological variability in presentation and treatment response and aids development of novel therapies. We developed a cancer Biomedical Informatics Grid (caBIG) Silver level compliant lymphoma database, called the Lymphoma Enterprise Architecture Data-system (LEAD), which integrates the pathology, pharmacy, laboratory, cancer registry, clinical trials, and clinical data from institutional databases. We utilized the Cancer Common Ontological Representation Environment Software Development Kit (caCORE SDK) provided by National Cancer Institute's Center for Bioinformatics to establish the LEAD platform for data management. The caCORE SDK generated system utilizes an n-tier architecture with open Application Programming Interfaces, controlled vocabularies, and registered metadata to achieve semantic integration across multiple cancer databases. We demonstrated that the data elements and structures within LEAD could be used to manage clinical research data from phase 1 clinical trials, cohort studies, and registry data from the Surveillance Epidemiology and End Results database. This work provides a clear example of how semantic technologies from caBIG can be applied to support a wide range of clinical and research tasks, and integrate data from disparate systems into a single architecture. This illustrates the central importance of caBIG to the management of clinical and biological data.

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

Near-infrared photoluminescence in La{sub 0.98}AlO{sub 3}: {sub 0.02}Ln{sup 3+}(Ln = Nd/Yb) for sensitization of c-Si solar cells

Energy Technology Data Exchange (ETDEWEB)

Sawala, N. S., E-mail: nssawala@gmail.com; Koparkar, K. A.; Omanwar, S. K. [Department of Physics, SantGadge Baba Amravati University, Amravati - MH, 444602 (India); Bajaj, N. S. [Department of Physics, Toshniwal Art, Commerce and Science College, Sengoan, Hingoli - MH (India)

2016-05-06

The host matrix LaAlO{sub 3} was synthesized by conventional solid state reaction method in which the Nd{sup 3+} ions and Yb{sup 3+} ions successfully doped at 2mol% concentrations. The phase purity was confirmed by X ray powder diffraction (XRD) method. The photoluminescence (PL) properties were studied by spectrophotometer in near infra red (NIR) and ultra violet visible (UV-VIS) region. The Nd{sup 3+} ion doped LaAlO{sub 3} converts a visible (VIS) green photon (587 nm) into near infrared (NIR) photon (1070 nm) while Yb{sup 3+} ion doped converts ultra violet (UV) photon (221 nm) into NIR photon (980 nm). The La{sub 0.98}AlO{sub 3}: {sub 0.02}Ln{sup 3+}(Ln = Nd / Yb) can be potentiality used for betterment of photovoltaic (PV) technology. This result further indicates its potential application as a luminescence converter layer for enhancing solar cells performance.

Characterizing Big Data Management

OpenAIRE

Rogério Rossi; Kechi Hirama

2015-01-01

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

Big data in medical science--a biostatistical view.

Science.gov (United States)

Binder, Harald; Blettner, Maria

2015-02-27

Inexpensive techniques for measurement and data storage now enable medical researchers to acquire far more data than can conveniently be analyzed by traditional methods. The expression "big data" refers to quantities on the order of magnitude of a terabyte (1012 bytes); special techniques must be used to evaluate such huge quantities of data in a scientifically meaningful way. Whether data sets of this size are useful and important is an open question that currently confronts medical science. In this article, we give illustrative examples of the use of analytical techniques for big data and discuss them in the light of a selective literature review. We point out some critical aspects that should be considered to avoid errors when large amounts of data are analyzed. Machine learning techniques enable the recognition of potentially relevant patterns. When such techniques are used, certain additional steps should be taken that are unnecessary in more traditional analyses; for example, patient characteristics should be differentially weighted. If this is not done as a preliminary step before similarity detection, which is a component of many data analysis operations, characteristics such as age or sex will be weighted no higher than any one out of 10 000 gene expression values. Experience from the analysis of conventional observational data sets can be called upon to draw conclusions about potential causal effects from big data sets. Big data techniques can be used, for example, to evaluate observational data derived from the routine care of entire populations, with clustering methods used to analyze therapeutically relevant patient subgroups. Such analyses can provide complementary information to clinical trials of the classic type. As big data analyses become more popular, various statistical techniques for causality analysis in observational data are becoming more widely available. This is likely to be of benefit to medical science, but specific adaptations will

Big losses lead to irrational decision-making in gambling situations: relationship between deliberation and impulsivity.

Directory of Open Access Journals (Sweden)

Yuji Takano

Full Text Available In gambling situations, we found a paradoxical reinforcing effect of high-risk decision-making after repeated big monetary losses. The computerized version of the Iowa Gambling Task (Bechara et al., 2000, which contained six big loss cards in deck B', was conducted on normal healthy college students. The results indicated that the total number of selections from deck A' and deck B' decreased across trials. However, there was no decrease in selections from deck B'. Detailed analysis of the card selections revealed that some people persisted in selecting from the "risky" deck B' as the number of big losses increased. This tendency was prominent in self-rated deliberative people. However, they were implicitly impulsive, as revealed by the matching familiar figure test. These results suggest that the gap between explicit deliberation and implicit impulsivity drew them into pathological gambling.

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...

Insights into long-lasting protection induced by RTS,S/AS02A malaria vaccine: further results from a phase IIb trial in Mozambican children.

Directory of Open Access Journals (Sweden)

Caterina Guinovart

Full Text Available The pre-erythrocytic malaria vaccine RTS,S/AS02A has shown to confer protection against clinical malaria for at least 21 months in a trial in Mozambican children. Efficacy varied between different endpoints, such as parasitaemia or clinical malaria; however the underlying mechanisms that determine efficacy and its duration remain unknown. We performed a new, exploratory analysis to explore differences in the duration of protection among participants to better understand the protection afforded by RTS,S.The study was a Phase IIb double-blind, randomized controlled trial in 2022 children aged 1 to 4 years. The trial was designed with two cohorts to estimate vaccine efficacy against two different endpoints: clinical malaria (cohort 1 and infection (cohort 2. Participants were randomly allocated to receive three doses of RTS,S/AS02A or control vaccines. We did a retrospective, unplanned sub-analysis of cohort 2 data using information collected for safety through the health facility-based passive case detection system. Vaccine efficacy against clinical malaria was estimated over the first six-month surveillance period (double-blind phase and over the following 12 months (single-blind phase, and analysis was per-protocol. Adjusted vaccine efficacy against first clinical malaria episodes in cohort 2 was of 35.4% (95% CI 4.5-56.3; p = 0.029 over the double-blind phase and of 9.0% (-30.6-36.6; p = 0.609 during the single-blind phase.Contrary to observations in cohort 1, where efficacy against clinical malaria did not wane over time, in cohort 2 the efficacy decreases with time. We hypothesize that this reduced duration of protection is a result of the early diagnosis and treatment of infections in cohort 2 participants, preventing sufficient exposure to asexual-stage antigens. On the other hand, the long-term protection against clinical disease observed in cohort 1 may be a consequence of a prolonged exposure to low-dose blood-stage asexual parasitaemia.ClinicalTrials

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....

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.

Nursing Theory, Terminology, and Big Data: Data-Driven Discovery of Novel Patterns in Archival Randomized Clinical Trial Data.

Science.gov (United States)

Monsen, Karen A; Kelechi, Teresa J; McRae, Marion E; Mathiason, Michelle A; Martin, Karen S

The growth and diversification of nursing theory, nursing terminology, and nursing data enable a convergence of theory- and data-driven discovery in the era of big data research. Existing datasets can be viewed through theoretical and terminology perspectives using visualization techniques in order to reveal new patterns and generate hypotheses. The Omaha System is a standardized terminology and metamodel that makes explicit the theoretical perspective of the nursing discipline and enables terminology-theory testing research. The purpose of this paper is to illustrate the approach by exploring a large research dataset consisting of 95 variables (demographics, temperature measures, anthropometrics, and standardized instruments measuring quality of life and self-efficacy) from a theory-based perspective using the Omaha System. Aims were to (a) examine the Omaha System dataset to understand the sample at baseline relative to Omaha System problem terms and outcome measures, (b) examine relationships within the normalized Omaha System dataset at baseline in predicting adherence, and (c) examine relationships within the normalized Omaha System dataset at baseline in predicting incident venous ulcer. Variables from a randomized clinical trial of a cryotherapy intervention for the prevention of venous ulcers were mapped onto Omaha System terms and measures to derive a theoretical framework for the terminology-theory testing study. The original dataset was recoded using the mapping to create an Omaha System dataset, which was then examined using visualization to generate hypotheses. The hypotheses were tested using standard inferential statistics. Logistic regression was used to predict adherence and incident venous ulcer. Findings revealed novel patterns in the psychosocial characteristics of the sample that were discovered to be drivers of both adherence (Mental health Behavior: OR = 1.28, 95% CI [1.02, 1.60]; AUC = .56) and incident venous ulcer (Mental health Behavior

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

Big Data in radiation therapy: challenges and opportunities.

Science.gov (United States)

Lustberg, Tim; van Soest, Johan; Jochems, Arthur; Deist, Timo; van Wijk, Yvonka; Walsh, Sean; Lambin, Philippe; Dekker, Andre

2017-01-01

Data collected and generated by radiation oncology can be classified by the Volume, Variety, Velocity and Veracity (4Vs) of Big Data because they are spread across different care providers and not easily shared owing to patient privacy protection. The magnitude of the 4Vs is substantial in oncology, especially owing to imaging modalities and unclear data definitions. To create useful models ideally all data of all care providers are understood and learned from; however, this presents challenges in the guise of poor data quality, patient privacy concerns, geographical spread, interoperability and large volume. In radiation oncology, there are many efforts to collect data for research and innovation purposes. Clinical trials are the gold standard when proving any hypothesis that directly affects the patient. Collecting data in registries with strict predefined rules is also a common approach to find answers. A third approach is to develop data stores that can be used by modern machine learning techniques to provide new insights or answer hypotheses. We believe all three approaches have their strengths and weaknesses, but they should all strive to create Findable, Accessible, Interoperable, Reusable (FAIR) data. To learn from these data, we need distributed learning techniques, sending machine learning algorithms to FAIR data stores around the world, learning from trial data, registries and routine clinical data rather than trying to centralize all data. To improve and personalize medicine, rapid learning platforms must be able to process FAIR "Big Data" to evaluate current clinical practice and to guide further innovation.

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...

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

Science.gov (United States)

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

2016-07-01

data from a malaria vaccine trial by big-data-based edge biomarkers from module network rewiring-analysis. The illustrative results show that the identified module biomarkers can accurately distinguish vaccines with or without protection and outperformed previous reported gene signatures in terms of effectiveness and efficiency. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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...

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...

Temperature dependent polarization reversal mechanism in 0.94(Bi1/2Na1/2) TiO3-0.06Ba(Zr0.02Ti0.98)O3 relaxor ceramics

DEFF Research Database (Denmark)

Glaum, Julia; Simons, Hugh; Hudspeth, Jessica

2015-01-01

and structural investigation of the polarization reversal process in the prototypical lead-free relaxor 0.94(Bi1/2Na1/2)TiO3-0.06Ba(Zr0.02Ti0.98)O3 reveals that an applied electric field can trigger depolarization and onset of relaxor-like behavior well below TF-R. The polarization reversal process can...... as such be described as a combination of (1) ferroelectric domain switching and (2) a reversible phase transition between two polar ferroelectric states mediated by a non-polar relaxor state. Furthermore, the threshold fields of the second, mediated polarization reversal mechanism depend strongly on temperature....... These results are concomitant with a continuous ferroelectric to relaxortransition occurring over a broad temperature range, during which mixed behavior is observed. The nature of polarization reversal can be illustrated in electric-field-temperature (E-T) diagrams showing the electric field amplitudes...

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

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

Shape coexistence and evolution in 98Sr

Science.gov (United States)

Park, J.; Garnsworthy, A. B.; Krücken, R.; Andreoiu, C.; Ball, G. C.; Bender, P. C.; Chester, A.; Close, A.; Finlay, P.; Garrett, P. E.; Glister, J.; Hackman, G.; Hadinia, B.; Leach, K. G.; Rand, E. T.; Sjue, S.; Starosta, K.; Svensson, C. E.; Tardiff, E.

2016-01-01

Shape coexistence between the strongly deformed ground state and the weakly deformed 02+ state in 98Sr has been a major topic of interest due to the energy difference of 215 keV, which is the smallest in all even-even nuclei. The electric monopole transition strength ρ2(E 0 ) is an important quantity that can relate the deformation difference and the shape mixing between the two 0+ states, which are admixtures of the vibrational (S) and the rotational (D) states in a simple mixing model. In a β -decay spectroscopy experiment, the experimental ρ2(E 0 ) was measured. A value of 0.053(5) is consistent with the previous measurement and was combined with known electric quadrupole transition strengths B (E 2 ) in calculations of a two-state mixing model. Based on a systematic study on neighboring Kr, Zr, and Mo isotopes, the mixing of the 0+ and 2+ states in 98Sr was determined to be 8.6% and 1.3%, respectively, corresponding to deformation parameters βD=0.38 (1 ) and βS=-0.23 (2 ) . These parameters reproduce experimental transition strengths well except for the 41+→21+ transition, which suggests a smaller D-band deformation for J ≥4 .

Efficacy of laparoscopic subtotal gastrectomy with D2 lymphadenectomy for locally advanced gastric cancer: the protocol of the KLASS-02 multicenter randomized controlled clinical trial

International Nuclear Information System (INIS)

Hur, Hoon; Lee, Hyun Yong; Lee, Hyuk-Joon; Kim, Min Chan; Hyung, Woo Jin; Park, Young Kyu; Kim, Wook; Han, Sang-Uk

2015-01-01

Despite the well-described benefits of laparoscopic surgery such as lower operative blood loss and enhanced postoperative recovery in gastric cancer surgery, the application of laparoscopic surgery in patients with locally advanced gastric cancer (AGC) remains elusive owing to a lack of clinical evidence. Recently, the Korean Laparoscopic Surgical Society Group launched a new multicenter randomized clinical trial (RCT) to compare laparoscopic and open D2 lymphadenectomy for patients with locally AGC. Here, we introduce the protocol of this clinical trial. This trial is an investigator-initiated, randomized, controlled, parallel group, non-inferiority trial. Gastric cancer patients diagnosed with primary tumors that have invaded into the muscle propria and not into an adjacent organ (cT2–cT4a) in preoperative studies are recruited. Another criterion for recruitment is no lymph node metastasis or limited perigastric lymph node (including lymph nodes around the left gastric artery) metastasis. A total 1,050 patients in both groups are required to statistically show non-inferiority of the laparoscopic approach with respect to the primary end-point, relapse-free survival of 3 years. Secondary outcomes include postoperative morbidity and mortality, postoperative recovery, quality of life, and overall survival. Surgeons who are validated through peer-review of their surgery videos can participate in this clinical trial. This clinical trial was designed to maintain the principles of a surgical clinical trial with internal validity for participating surgeons. Through the KLASS-02 RCT, we hope to show the efficacy of laparoscopic D2 lymphadenectomy in AGC patients compared with the open procedure. ClinicalTrial.gov, https://www.clinicaltrials.gov/ct2/show/NCT01456598?term

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.

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

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.

Defect chemistry, thermomechanical and transport properties of (RE₂ - _xSr_x)_0.98(Fe_0.8Co_0.2)_{1 - y}Mg_yO_{4 - δ} (RE = La, Pr)

DEFF Research Database (Denmark)

Chatzichristodoulou, Christodoulos; Schönbeck, C.; Hagen, Anke

2013-01-01

The oxygen nonstoichiometry of Ruddlesden-Popper compounds with chemical composition (RE2 - xSrx)0.98(Fe 0.8Co0.2)1 - yMgyO 4 - δ (RE = La, Pr, x = 0.9-1.2 and y = 0, 0.2) was measured as a function of temperature and oxygen activity (aO2) by coulometric titration and thermogravimetry. All...

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 Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

Science.gov (United States)

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

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...

Clinical Trial Data as Public Goods: Fair Trade and the Virtual Knowledge Bank as a Solution to the Free Rider Problem - A Framework for the Promotion of Innovation by Facilitation of Clinical Trial Data Sharing among Biopharmaceutical Companies in the Era of Omics and Big Data.

Science.gov (United States)

Evangelatos, Nikolaos; Reumann, Matthias; Lehrach, Hans; Brand, Angela

2016-01-01

Knowledge in the era of Omics and Big Data has been increasingly conceptualized as a public good. Sharing of de-identified patient data has been advocated as a means to increase confidence and public trust in the results of clinical trials. On the other hand, research has shown that the current research and development model of the biopharmaceutical industry has reached its innovation capacity. In response to that, the biopharmaceutical industry has adopted open innovation practices, with sharing of clinical trial data being among the most interesting ones. However, due to the free rider problem, clinical trial data sharing among biopharmaceutical companies could undermine their innovativeness. Based on the theory of public goods, we have developed a commons arrangement and devised a model, which enables secure and fair clinical trial data sharing over a Virtual Knowledge Bank based on a web platform. Our model uses data as a virtual currency and treats knowledge as a club good. Fair sharing of clinical trial data over the Virtual Knowledge Bank has positive effects on the innovation capacity of the biopharmaceutical industry without compromising the intellectual rights, proprietary interests and competitiveness of the latter. The Virtual Knowledge Bank is a sustainable and self-expanding model for secure and fair clinical trial data sharing that allows for sharing of clinical trial data, while at the same time it increases the innovation capacity of the biopharmaceutical industry. © 2016 S. Karger AG, Basel.

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 ...

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.

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.

Shock wave compression and self-generated electric field repolarization in ferroelectric ceramics Pb0.99[(Zr0.90Sn0.10)0.96Ti0.04]0.98Nb0.02O3

Science.gov (United States)

Jiang, Dongdong; Du, Jinmei; Gu, Yan; Feng, Yujun

2012-03-01

The shock wave induced depoling current of Pb0.99[(Zr0.90Sn0.10)0.96Ti0.04]0.98Nb0.02O3 ceramics was investigated with a system composed of a resistive load and an unpoled ceramic. Disparity in the depoling current was explained by considering the drawing charge effect of unpoled ceramic. The drawing effect for poled ceramics was analysed by developing a model incorporating a time- and electric-field-dependent repolarization. This model predicts that the high-impedance current eventually becomes higher than the short-circuit current, which is consistent with the experimental results in the literature. This work indicates that both the repolarization of uncompressed ceramics caused by the self-generated electric field and depolarization of compressed ceramics caused by the shock wave govern the output current.

Shock wave compression and self-generated electric field repolarization in ferroelectric ceramics Pb0.99[(Zr0.90Sn0.10)0.96Ti0.04]0.98Nb0.02O3

International Nuclear Information System (INIS)

Jiang Dongdong; Du Jinmei; Gu Yan; Feng Yujun

2012-01-01

The shock wave induced depoling current of Pb 0.99 [(Zr 0.90 Sn 0.10 ) 0.96 Ti 0.04 ] 0.98 Nb 0.02 O 3 ceramics was investigated with a system composed of a resistive load and an unpoled ceramic. Disparity in the depoling current was explained by considering the drawing charge effect of unpoled ceramic. The drawing effect for poled ceramics was analysed by developing a model incorporating a time- and electric-field-dependent repolarization. This model predicts that the high-impedance current eventually becomes higher than the short-circuit current, which is consistent with the experimental results in the literature. This work indicates that both the repolarization of uncompressed ceramics caused by the self-generated electric field and depolarization of compressed ceramics caused by the shock wave govern the output current. (paper)

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...

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

A randomized trial assessing the safety and immunogenicity of AS01 and AS02 adjuvanted RTS,S malaria vaccine candidates in children in Gabon.

Directory of Open Access Journals (Sweden)

Bertrand Lell

2009-10-01

Full Text Available The malaria vaccine candidate antigen RTS,S includes parts of the pre-erythrocytic stage circumsporozoite protein fused to the Hepatitis B surface antigen. Two Adjuvant Systems are in development for this vaccine, an oil-in water emulsion--based formulation (AS02 and a formulation based on liposomes (AS01.In this Phase II, double-blind study (NCT00307021, 180 healthy Gabonese children aged 18 months to 4 years were randomized to receive either RTS,S/AS01(E or RTS,S/AS02(D, on a 0-1-2 month vaccination schedule. The children were followed-up daily for six days after each vaccination and monthly for 14 months. Blood samples were collected at 4 time-points. Both vaccines were well tolerated. Safety parameters were distributed similarly between the two groups. Both vaccines elicited a strong specific immune response after Doses 2 and 3 with a ratio of anti-CS GMT titers (AS02(D/AS01(E of 0.88 (95% CI: 0.68-1.15 post-Dose 3. After Doses 2 and 3 of experimental vaccines, anti-CS and anti-HBs antibody GMTs were higher in children who had been previously vaccinated with at least one dose of hepatitis B vaccine compared to those not previously vaccinated.RTS,S/AS01(E proved similarly as well tolerated and immunogenic as RTS,S/AS02(D, completing an essential step in the age de-escalation process within the RTS,S clinical development plan.ClinicalTrials.gov. NCT00307021.

Bygningers varmebehov 98, Bv98

DEFF Research Database (Denmark)

Bygningers energibehov og i SBI-anvisning 189 Småhuse. Programmet kan anvendes på pc under operativsystemet Microsoft Windows 95, Windows 98 og Windows NT 4.0, Servicepack 3 eller nyere. Pc-programmet er en revideret og moderniseret udgave af pc-programmet Bygningers Varmebehov, BV95, som SBI udgav i 1995....

Beyond the big five: the Dark Triad and the supernumerary personality inventory.

Science.gov (United States)

Veselka, Livia; Schermer, Julie Aitken; Vernon, Philip A

2011-04-01

The Dark Triad of personality, comprising Machiavellianism, narcissism, and psychopathy, was investigated in relation to the Supernumerary Personality Inventory (SPI) traits, because both sets of variables are predominantly distinct from the Big Five model of personality. Correlational and principal factor analyses were conducted to assess the relations between the Dark Triad and SPI traits. Multivariate behavioral genetic model-fitting analyses were also conducted to determine the correlated genetic and/or environmental underpinnings of the observed phenotypic correlations. Participants were 358 monozygotic and 98 same-sex dizygotic adult twin pairs from North America. As predicted, results revealed significant correlations between the Dark Triad and most SPI traits, and these correlations were primarily attributable to common genetic and non-shared environmental factors, except in the case of Machiavellianism, where shared environmental effects emerged. Three correlated factors were extracted during joint factor analysis of the Dark Triad and SPI traits, as well as a heritable general factor of personality - results that clarified the structure of the Dark Triad construct. It is concluded that the Dark Triad represents an exploitative and antisocial construct that extends beyond the Big Five model and shares a theoretical space with the SPI traits.

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

Cosmic ray anisotropy searches with AMS-02

Energy Technology Data Exchange (ETDEWEB)

Zeissler, Stefan; Gebauer, Iris; Trumpf, Ricarda [Karlsruher Institut fuer Technologie (KIT) (Germany)

2016-07-01

The Alpha Magnetic Spectrometer (AMS-02) is a state-of-the-art particle detector designed to operate as an external module on the International Space Station (ISS). In this unique space environment cosmic particles can be measured with high precision over an energy range from GeV up to TeV. The AMS collaboration provided precise measurements of the electron and positron fluxes, which indicate an additional source of positrons among the various cosmic particles. Possible candidates for this source are local pulsars, a local source of positrons produced in proton-gas interactions or dark matter annihilation. In the first two cases a possible anisotropy in the electrons and positrons incoming direction at Earth might be detectable. To determine the level of isotropy the measured data is compared to reference maps, which simulate the measurement of an isotropic sky. A common choice of reference maps are proton count maps or shuffled maps, which redistribute measured incoming directions over the whole measuring time. Both choices lead to difficulties in the reconstruction of a marginal signal with a big expansion over the galactic sky as it would be the case for charged cosmic particles. We developed a method to construct reference maps based on fundamental detector characteristics such as the lifetime and the geometric acceptance. Using this we are able to reconstruct the isotropic sky as it would be seen by the detector. We demonstrate the performance of the method using AMS-02 data.

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.

License - RGP gmap98 | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us RGP gmap98 License License to Use This Database Last updated : 2015/02/12 You may use this database...e license terms regarding the use of this database and the requirements you must follow in using this database.... The license for this database is specified in the Creative Commons Attributio...n-Share Alike 2.1 Japan . If you use data from this database, please be sure attribute this database as foll...on-Share Alike 2.1 Japan is found here . With regard to this database, you are licensed to: freely access part or whole of this datab

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...

ENC 98

International Nuclear Information System (INIS)

1998-01-01

This press dossier document reports on the main points presented by the Framatome group at the ENC'98 colloquium which took place in Nice (France) on September 25 1998. The summary comprises 4 main parts: the 1997-98 highlights (nuclear realizations in France, China and Turkey, nuclear services, nuclear fuels), the international activities in the nuclear domain (USA, China, Eastern Europe), the research and development activities (the French-German joint EPR project, the high temperature reactor (HTR) project), and the service and nuclear fuel activities (maintenance, improvements, control and expertise). (J.S.)

Chinese Herbal Medicine for Acute Mountain Sickness: A Systematic Review of Randomized Controlled Trials

Directory of Open Access Journals (Sweden)

Jie Wang

2013-01-01

Full Text Available Objectives. We aimed to assess the current clinical evidence of Chinese herbal medicine for AMS. Methods. Seven electronic databases were searched until January 2013. We included randomized clinical trials testing Chinese herbal medicine against placebo, no drugs, Western drugs, or a combination of routine treatment drugs against routine treatment drugs. Study selection, data extraction, quality assessment, and data analyses were conducted according to Cochrane standards. Results. Nine randomized trials were included. The methodological quality of the included trials was evaluated as low. Two trials compared prescriptions of Chinese formula used alone with Western drugs. A meta-analysis showed a beneficial effect in decreasing the score of AMS (MD: −2.23 [−3.98, −0.49], P=0.01. Only one trial compared prescriptions of Chinese formula used alone with no drugs. A meta-analysis showed a significant beneficial effect in decreasing the score of AMS (MD: −6.00 [−6.45, −5.55], P<0.00001. Four trials compared Chinese formula used alone with placebo. A meta-analysis also showed a significant beneficial effect in decreasing the score of AMS (MD: −1.10 [−1.64, −0.55], P<0.0001. Two trials compared the combination of Chinese formula plus routine treatment drugs with routine treatment drugs. A meta-analysis showed a beneficial effect in decreasing the score of AMS (MD: −5.99 [−11.11, −0.86], P=0.02. Conclusions. No firm conclusion on the effectiveness and safety of Chinese herbal medicine for AMS can be made. More rigorous high-quality trials are required to generate a high level of evidence and to confirm the results.

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, 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

The complete mitochondrial genome of the cryptic "lineage B" big-fin reef squid, Sepioteuthis lessoniana (Cephalopoda: Loliginidae) in Indo-West Pacific.

Science.gov (United States)

Shen, Kang-Ning; Yen, Ta-Chi; Chen, Ching-Hung; Ye, Jeng-Jia; Hsiao, Chung-Der

2016-05-01

In this study, the complete mitogenome sequence of the cryptic "lineage B" big-fin reef squid, Sepioteuthis lessoniana (Cephalopoda: Loliginidae) has been sequenced by next-generation sequencing method. The assembled mitogenome consisting of 16,694 bp, includes 13 protein coding genes, 25 transfer RNAs, 2 ribosomal RNAs genes. The overall base composition of "lineage B" S. lessoniana is 36.7% for A, 18.9 % for C, 34.5 % for T and 9.8 % for G and show 90% identities to "lineage C" S. lessoniana. It is also exhibits high T + A content (71.2%), two non-coding regions with TA tandem repeats. The complete mitogenome of the cryptic "lineage B" S. lessoniana provides essential and important DNA molecular data for further phylogeography and evolutionary analysis for big-fin reef squid species complex.

Determinación del coeficiente piroeléctrico del sistema ferroeléctrico cerámico de Pb0.88Ln0.08Ti0.98Mn0.02O3 (Ln=La, Sm, Eu y su aplicación en detectores de infrarrojo

Directory of Open Access Journals (Sweden)

Suaste-Gómez, E.

2004-12-01

Full Text Available In this work the dielectric and pyroelectric characteristics of the ferroelectric ceramic system of Pb0.88(Ln0.08Ti0.98Mn0.02O3 (Ln = La, Sm, Eu are studied in order to determine its usefulness as infrared dectectors. Dielectric constant and pyroelectric coefficient of the ceramics were determined. This material with perovskite structure presented a phase transition from tetragonal to cubic on the heating process, besides of presenting high values of dielectric constant. Values of figure of merit for infrared detection Rv=pi/εr were calculated. The results were compared with other materials used as infrared detectors.En este trabajo se estudian las características dieléctricas y piroeléctricas del sistema ferroléctrico cerámico de Pb0.88(Ln0.08Ti0.98 Mn0.02O3 (Ln = La, Sm, Eu para determinar su utilidad como detectores de infrarrojo. Se determinó la constante dieléctrica y el coeficiente piroeléctrico de las cerámicas. Este material con estructura de perovskita presentó una transición de fase tetragonal a cúbica en el proceso de calentamiento, además de presentar altos valores de la constante dieléctrica. Se obtuvieron valores de la figura de mérito para detección infrarroja Rv=pi/εr Los resultados se compararon con otros materiales usados como detectores de infrarrojo.

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.

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.

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)

From big data analysis in the cloud to robotic pot drumming: tales from the Met Office Informatics Lab

Science.gov (United States)

Robinson, Niall; Tomlinson, Jacob; Prudden, Rachel; Hilson, Alex; Arribas, Alberto

2017-04-01

The Met Office Informatics Lab is a small multidisciplinary team which sits between science, technology and design. Our mission is simply "to make Met Office data useful" - a deliberately broad objective. Our prototypes often trial cutting edge technologies, and so far have included projects such as virtual reality data visualisation in the web browser, bots and natural language interfaces, and artificially intelligent weather warnings. In this talk we focus on our latest project, Jade, a big data analysis platform in the cloud. It is a powerful, flexible and simple to use implementation which makes extensive use of technologies such as Jupyter, Dask, containerisation, Infrastructure as Code, and auto-scaling. Crucially, Jade is flexible enough to be used for a diverse set of applications: it can present weather forecast information to meteorologists and allow climate scientists to analyse big data sets, but it is also effective for analysing non-geospatial data. As well as making data useful, the Informatics Lab also trials new working practises. In this presentation, we will talk about our experience of making a group like the Lab successful.

Grounding by Attention Simulation in Peripersonal Space: Pupils Dilate to Pinch Grip But Not Big Size Nominal Classifier.

Science.gov (United States)

Lobben, Marit; Bochynska, Agata

2018-03-01

Grammatical categories represent implicit knowledge, and it is not known if such abstract linguistic knowledge can be continuously grounded in real-life experiences, nor is it known what types of mental states can be simulated. A former study showed that attention bias in peripersonal space (PPS) affects reaction times in grammatical congruency judgments of nominal classifiers, suggesting that simulated semantics may include reenactment of attention. In this study, we contrasted a Chinese nominal classifier used with nouns denoting pinch grip objects with a classifier for nouns with big object referents in a pupil dilation experiment. Twenty Chinese native speakers read grammatical and ungrammatical classifier-noun combinations and made grammaticality judgment while their pupillary responses were measured. It was found that their pupils dilated significantly more to the pinch grip classifier than to the big object classifier, indicating attention simulation in PPS. Pupil dilations were also significantly larger with congruent trials on the whole than in incongruent trials, but crucially, congruency and classifier semantics were independent of each other. No such effects were found in controls. Copyright © 2017 Cognitive Science Society, Inc.

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...

40 CFR 98.418 - Definitions.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Definitions. 98.418 Section 98.418 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) MANDATORY GREENHOUSE GAS REPORTING Suppliers of Industrial Greenhouse Gases § 98.418 Definitions. All terms used in...

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.

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.

In situ X-ray and neutron diffraction of the Ruddlesden-Popper compounds (RE2-xSrx)0.98(Fe0.8Co0.2)1-yMgyO4-δ (RE=La, Pr): Structure and CO2 stability

DEFF Research Database (Denmark)

Chatzichristodoulou, Christodoulos; Hauback, B.C.; Hendriksen, Peter Vang

2013-01-01

The crystal structure of the Ruddlesden-Popper compounds (La 1.0Sr1.0)0.98Fe0.8Co 0.2O4-δ and (La1.2Sr0.8) 0.98(Fe0.8Co0.2)0.8Mg 0.2O4-δ was investigated at 1000 °C in N 2 (aO2=1×10-4) by in-situ powder neutron diffraction. In-situ powder X-ray diffraction (PXD) was also employed to investigate....... The equivalent pseudo-cubic thermal and chemical expansion coefficients are in agreement with values determined by dilatometry. The chemical stability in CO2 containing environments of various Ruddlesden-Popper compounds with chemical formula (RE2-xSr x)0.98(Fe0.8Co0.2) 1-yMgyO4-δ (RE=La, Pr), as well...

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...

45 CFR 98.90 - Monitoring.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Monitoring. 98.90 Section 98.90 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION CHILD CARE AND DEVELOPMENT FUND Monitoring, Non-compliance and Complaints § 98.90 Monitoring. (a) The Secretary will monitor programs funded under...

29 CFR 98.1000 - Respondent.

Science.gov (United States)

2010-07-01

... 29 Labor 1 2010-07-01 2010-07-01 true Respondent. 98.1000 Section 98.1000 Labor Office of the Secretary of Labor GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 98.1000 Respondent. Respondent means a person against whom an agency has initiated a debarment or suspension action. ...

34 CFR 98.6 - Reports.

Science.gov (United States)

2010-07-01

... 34 Education 1 2010-07-01 2010-07-01 false Reports. 98.6 Section 98.6 Education Office of the Secretary, Department of Education STUDENT RIGHTS IN RESEARCH, EXPERIMENTAL PROGRAMS, AND TESTING § 98.6 Reports. The Secretary may require the recipient to submit reports containing information necessary to...

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.

78 FR 32294 - DeltaPoint Capital IV, L.P., DeltaPoint Capital IV (New York), L.P., License No. 02/02-0662,02/02...

Science.gov (United States)

2013-05-29

... Small Business Investment Act of 1958, as amended (``the Act''), in connection with the financing of a... SMALL BUSINESS ADMINISTRATION DeltaPoint Capital IV, L.P., DeltaPoint Capital IV (New York), L.P., License No. 02/02-0662,02/02-0661; Notice Seeking Exemption Under Section 312 of the Small Business...

[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.

Magnetic properties and tunable magneto-caloric effect in La0.8Ce0.2Fe11.5-xCoxSi1.5C0.2 (x = 0.3, 0.5, and 0.7) compounds

Science.gov (United States)

Wu, Qiming; Wang, Xiangjie; Ding, Zan; Li, Lingwei

2018-05-01

The magnetic and magneto-caloric properties in the ternary elementals doped La0.8Ce0.2Fe11.5-xCoxSi1.5C0.2 (x = 0.3, 0.5, and 0.7) compounds were studied. With the increases of Co content x, the Curie temperature TC increases and the thermal hysteresis decreases. All the compounds undergo a second-order magnetic phase transition and exhibit a considerable reversible tunable magneto-caloric effect. The values of maximum magnetic entropy change (-ΔSMmax) and the Relative Cooling Power (RCP) are kept at same high level with different Co content. Under a magnetic field change of 0-5 T, the values of -ΔSMmax for La0.8Ce0.2Fe11.5-xCoxSi1.5C0.2 are 10.5, 10.7, and 9.8 J/kg K for x = 0.3, 0.5, and 0.7, respectively. The corresponding values of RCP are 267.1, 289.9, and 290.2 J/kg.

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, ...

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.

9 CFR 98.30 - Definitions.

Science.gov (United States)

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Definitions. 98.30 Section 98.30... EMBRYOS AND ANIMAL SEMEN Certain Animal Semen § 98.30 Definitions. Whenever in this subpart of the... (England, Scotland, Wales, the Isle of Man, and Northern Ireland). Cattle. Animals of the bovine species...

29 CFR 98.1005 - State.

Science.gov (United States)

2010-07-01

... 29 Labor 1 2010-07-01 2010-07-01 true State. 98.1005 Section 98.1005 Labor Office of the Secretary of Labor GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 98.1005 State. (a) State means— (1) Any of the states of the United States; (2) The District of Columbia; (3) The...

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

Femtosecond laser-assisted deep anterior lamellar keratoplasty in phototherapeutic keratectomy versus the big-bubble technique in keratoconus

Directory of Open Access Journals (Sweden)

Jarbas Pereira de Macedo

2018-05-01

Full Text Available AIM: To compare the functional and anatomic results of femtosecond laser (FSL-assisted deep anterior lamellar keratoplasty (DALK associated with phototherapeutic keratectomy (PTK and FSL-assisted DALK performed using the big-bubble technique in keratoconus. METHODS: During the first phase of the study, an electron microscopy histopathology pilot study was conducted that included four unsuitable donor corneas divided into two groups: in FSL group, FSL lamellar cuts were performed on two corneas and in FSL+PTK group, PTK was performed at the stromal beds of two corneas after FSL lamellar cuts were made. During the second phase of the study, a randomized clinical trial was conducted that included two treatment groups of patients with keratoconus: group 1 (n=14 eyes underwent FSL-assisted DALK associated with PTK and group 2 (n=12 eyes underwent FSL-assisted DALK associated with the big-bubble technique. The main outcome measures were the postoperative visual acuity (VA and optical coherence tomography (OCT measurements, confocal microscopic findings, and contrast sensitivity. RESULTS: In the pilot study, histopathology showed a more regular stromal bed in the FSL+PTK group. In the clinical trial, group 1 had significantly worse best spectacle-corrected VA and contrast sensitivity (P<0.05 for both comparisons. The residual stromal bed measured by OCT was significantly (P<0.05 thicker in group 1. Confocal microscopy detected opacities only at the donor-receptor interface in group 1. CONCLUSION: Patients with keratoconus treated with FSL-assisted DALK performed using the big-bubble technique fare better than treated with FSL-assisted DALK associated with PTK.

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...

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.

Population Analysis of Adverse Events in Different Age Groups Using Big Clinical Trials Data.

Science.gov (United States)

Luo, Jake; Eldredge, Christina; Cho, Chi C; Cisler, Ron A

2016-10-17

Understanding adverse event patterns in clinical studies across populations is important for patient safety and protection in clinical trials as well as for developing appropriate drug therapies, procedures, and treatment plans. The objective of our study was to conduct a data-driven population-based analysis to estimate the incidence, diversity, and association patterns of adverse events by age of the clinical trials patients and participants. Two aspects of adverse event patterns were measured: (1) the adverse event incidence rate in each of the patient age groups and (2) the diversity of adverse events defined as distinct types of adverse events categorized by organ system. Statistical analysis was done on the summarized clinical trial data. The incident rate and diversity level in each of the age groups were compared with the lowest group (reference group) using t tests. Cohort data was obtained from ClinicalTrials.gov, and 186,339 clinical studies were analyzed; data were extracted from the 17,853 clinical trials that reported clinical outcomes. The total number of clinical trial participants was 6,808,619, and total number of participants affected by adverse events in these trials was 1,840,432. The trial participants were divided into eight different age groups to support cross-age group comparison. In general, children and older patients are more susceptible to adverse events in clinical trial studies. Using the lowest incidence age group as the reference group (20-29 years), the incidence rate of the 0-9 years-old group was 31.41%, approximately 1.51 times higher (P=.04) than the young adult group (20-29 years) at 20.76%. The second-highest group is the 50-59 years-old group with an incidence rate of 30.09%, significantly higher (Pgroup. The adverse event diversity also increased with increase in patient age. Clinical studies that recruited older patients (older than 40 years) were more likely to observe a diverse range of adverse events (Page group (older

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

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.

49 CFR 98.10 - Appeal.

Science.gov (United States)

2010-10-01

... Administration of Enforcement Proceedings § 98.10 Appeal. (a) Within 30 working days after receipt of a decision issued under § 98.8 or § 98.9 of this part, either the Departmental counsel or the former employee may appeal the decision to the Secretary. (b) In making a decision on an appeal, the Secretary shall consider...

BigBOSS: The Ground-Based Stage IV BAO Experiment

Energy Technology Data Exchange (ETDEWEB)

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

2009-04-01

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

Methodological issues for designing and conducting a multicenter, international clinical trial in Acute Stroke: Experience from ARTSS-2 trial.

Science.gov (United States)

Rahbar, Mohammad H; Dickerson, Aisha S; Cai, Chunyan; Pedroza, Claudia; Hessabi, Manouchehr; Shen, Loren; Pandurengan, Renganayaki; Jacobs, Amber Nicole M; Indupuru, Hari; Sline, Melvin R; Delgado, Rigoberto I; Macdonald, Claire; Ford, Gary A; Grotta, James C; Barreto, Andrew D

2015-09-01

We describe innovations in the study design and the efficient data coordination of a randomized multicenter trial of Argatroban in Combination with Recombinant Tissue Plasminogen Activator for Acute Stroke (ARTSS-2). ARTSS-2 is a 3-arm, multisite/multiregional randomized controlled trials (RCTs) of two doses of Argatroban injection (low, high) in combination with recombinant tissue plasminogen activator (rt-PA) in acute ischemic stroke patients and rt-PA alone. We developed a covariate adaptive randomization program that balanced the study arms with respect to study site as well as hemorrhage after thrombolysis (HAT) score and presence of distal internal carotid artery occlusion (DICAO). We used simulation studies to validate performance of the randomization program before making any adaptations during the trial. For the first 90 patients enrolled in ARTSS-2, we evaluated performance of our randomization program using chi-square tests of homogeneity or extended Fisher's exact test. We also designed a four-step partly Bayesian safety stopping rule for low and high dose Argatroban arms. Homogeneity of the study arms was confirmed with respect to distribution of study site (UK sites vs. US sites, P=0.98), HAT score (0-2 vs. 3-5, P=1.0), and DICAO (N/A vs. No vs. Yes, P=0.97). Our stopping thresholds for safety of low and high dose Argatroban were not crossed. Despite challenges, data quality was assured. We recommend adaptive designs for randomization and Bayesian safety stopping rules for multisite Phase I/II RCTs for maintaining additional flexibility. Efficient data coordination could lead to improved data quality. Copyright © 2015. Published by Elsevier Inc.

45 CFR 98.14 - Plan process.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Plan process. 98.14 Section 98.14 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION CHILD CARE AND DEVELOPMENT FUND General Application Procedures § 98.14 Plan process. In the development of each Plan, as required pursuant to § 98.17...

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.

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.

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.

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

Shape Evolution in Neutron-Rich Krypton Isotopes Beyond N=60: First Spectroscopy of ^{98,100}Kr.

Science.gov (United States)

Flavigny, F; Doornenbal, P; Obertelli, A; Delaroche, J-P; Girod, M; Libert, J; Rodriguez, T R; Authelet, G; Baba, H; Calvet, D; Château, F; Chen, S; Corsi, A; Delbart, A; Gheller, J-M; Giganon, A; Gillibert, A; Lapoux, V; Motobayashi, T; Niikura, M; Paul, N; Roussé, J-Y; Sakurai, H; Santamaria, C; Steppenbeck, D; Taniuchi, R; Uesaka, T; Ando, T; Arici, T; Blazhev, A; Browne, F; Bruce, A; Carroll, R; Chung, L X; Cortés, M L; Dewald, M; Ding, B; Franchoo, S; Górska, M; Gottardo, A; Jungclaus, A; Lee, J; Lettmann, M; Linh, B D; Liu, J; Liu, Z; Lizarazo, C; Momiyama, S; Moschner, K; Nagamine, S; Nakatsuka, N; Nita, C; Nobs, C R; Olivier, L; Orlandi, R; Patel, Z; Podolyák, Zs; Rudigier, M; Saito, T; Shand, C; Söderström, P A; Stefan, I; Vaquero, V; Werner, V; Wimmer, K; Xu, Z

2017-06-16

We report on the first γ-ray spectroscopy of low-lying states in neutron-rich ^{98,100}Kr isotopes obtained from ^{99,101}Rb(p,2p) reactions at ∼220  MeV/nucleon. A reduction of the 2_{1}^{+} state energies beyond N=60 demonstrates a significant increase of deformation, shifted in neutron number compared to the sharper transition observed in strontium and zirconium isotopes. State-of-the-art beyond-mean-field calculations using the Gogny D1S interaction predict level energies in good agreement with experimental results. The identification of a low-lying (0_{2}^{+}, 2_{2}^{+}) state in ^{98}Kr provides the first experimental evidence of a competing configuration at low energy in neutron-rich krypton isotopes consistent with the oblate-prolate shape coexistence picture suggested by theory.

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.

Prognostic and predictive importance of the estrogen receptor coactivator AIB1 in a randomized trial comparing adjuvant letrozole and tamoxifen therapy in postmenopausal breast cancer

DEFF Research Database (Denmark)

Alkner, S; Jensen, Maj-Britt Raaby; Rasmussen, B B

2017-01-01

PURPOSE: To evaluate the estrogen receptor coactivator amplified in breast cancer 1 (AIB1) as a prognostic marker, as well as a predictive marker for response to adjuvant tamoxifen and/or aromatase inhibitors, in early estrogen receptor-positive breast cancer. METHOD: AIB1 was analyzed...... with immunohistochemistry in tissue microarrays of the Danish subcohort (N = 1396) of the International Breast Cancer Study Group's trial BIG 1-98 (randomization between adjuvant tamoxifen versus letrozole versus the sequence of the two drugs). RESULTS: Forty-six percent of the tumors had a high AIB1 expression. In line...... with previous studies, AIB1 correlated to a more aggressive tumor-phenotype (HER2 amplification and a high malignancy grade). High AIB1 also correlated to higher estrogen receptor expression (80-100 vs. 1-79%), and ductal histological type. High AIB1 expression was associated with a poor disease-free survival...

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...

Study of the potentiometric response of the doped spinel Li1.05Al0.02Mn1.98O4 for the optimization of a selective lithium ion sensor

International Nuclear Information System (INIS)

Freitas, Bruno H.; Amaral, Fabio A.; Bocchi, Nerilso; Teixeira, Marcos F.S.

2010-01-01

In this paper, we studied the development of a selective lithium ion sensor constituted of a carbon paste electrode modified (CPEM) with an aluminum-doped spinel-type manganese oxide (Li 1.05 Al 0.02 Mn 1.98 O 4 ) for investigating the influence of a doping ion in the sensor response. Experimental parameters, such as influence of the lithium concentration in the activation of the sensor by cyclic voltammetry, pH of the carrier solution and selectivity for Li + against other alkali and alkaline-earth ions were investigated. The sensor response to lithium ions was linear in the concentration range 5.62 x 10 -5 to 1.62 x 10 -3 mol L -1 with a slope 100.1 mV/decade over a wide pH 10 (Tris buffer) and detection limit of 2.75 x 10 -5 mol L -1 , without interference of other alkali and alkaline-earth metals, demonstrating that the Al 3+ doping increases the structure stability and improves the potentiometric response and sensitivity of the sensor. The super-Nernstian response of the sensor in pH 10 can be explained by mixed potential arising from two equilibria (redox and ion-exchange) in the spinel-type manganese oxide.

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.

Test Results of the LARP HQ02b Magnet at 1.9 K

CERN Document Server

Bajas, H; Bottura, L; Chiuchiolo, A; Dunkel, O; Ferracin, P; Feuvrier, J; Giloux, Chr; Todesco, E; Ravaioli, E; Caspi, S; Dietderich, D; Felice, H; Hafalia, A R; Marchevsky, M; Sabbi, G L; Wang, X; Salmi, T; Ghosh, A; Schmalzle, J; Wanderer, P; Anerella, M; Ambrosio, G; Bossert, R; Chlachidze, G; Yu, M

2015-01-01

The HQ magnet is a 120 mm aperture, 1-meter-long Nb$_{3}$Sn quadrupole developed by the LARP collaboration in the framework of the High-Luminosity LHC project. A first series of coils was assembled and tested in 5 assemblies of the HQ01 series. The HQ01e model achieved a maximum gradient of 170 T/m at 4.5 K at LBNL in 2010-2011 and reached 184 T/m at 1.9 K at CERN in 2012. A new series of coils incorporating major design changes was fabricated for the HQ02 series. The first model, HQ02a, was tested at Fermilab where it reached 98% of the short sample limit at 4.5 K with a gradient of 182 T/m in 2013. However, the full training of the coils at 1.9 K could not be performed due to a current limit of 15 kA. Following this test, the azimuthal coil pre-load was increased by about 30 MPa and an additional current lead was installed at the electrical center of the magnet for quench protection studies. The test name of this magnet changed to HQ02b. In 2014, HQ02b was then shipped to CERN as the first opportunity for f...

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…

Impact of physical exercise on reaction time in patients with Parkinson's disease-data from the Berlin BIG Study.

Science.gov (United States)

Ebersbach, Georg; Ebersbach, Almut; Gandor, Florin; Wegner, Brigitte; Wissel, Jörg; Kupsch, Andreas

2014-05-01

To determine whether physical activity may affect cognitive performance in patients with Parkinson's disease by measuring reaction times in patients participating in the Berlin BIG study. Randomized controlled trial, rater-blinded. Ambulatory care. Patients with mild to moderate Parkinson's disease (N=60) were randomly allocated to 3 treatment arms. Outcome was measured at the termination of training and at follow-up 16 weeks after baseline in 58 patients (completers). Patients received 16 hours of individual Lee Silverman Voice Treatment-BIG training (BIG; duration of treatment, 4wk), 16 hours of group training with Nordic Walking (WALK; duration of treatment, 8wk), or nonsupervised domestic exercise (HOME; duration of instruction, 1hr). Cued reaction time (cRT) and noncued reaction time (nRT). Differences between treatment groups in improvement in reaction times from baseline to intermediate and baseline to follow-up assessments were observed for cRT but not for nRT. Pairwise t test comparisons revealed differences in change in cRT at both measurements between BIG and HOME groups (intermediate: -52ms; 95% confidence interval [CI], -84/-20; P=.002; follow-up: 55ms; CI, -105/-6; P=.030) and between WALK and HOME groups (intermediate: -61ms; CI, -120/-2; P=.042; follow-up: -78ms; CI, -136/-20; P=.010). There was no difference between BIG and WALK groups (intermediate: 9ms; CI, -49/67; P=.742; follow-up: 23ms; CI, -27/72; P=.361). Supervised physical exercise with Lee Silverman Voice Treatment-BIG or Nordic Walking is associated with improvement in cognitive aspects of movement preparation. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

LEARN 2 MOVE 0-2 years: effects of a new intervention program in infants at very high risk for cerebral palsy; a randomized controlled trial

Directory of Open Access Journals (Sweden)

Verheijden Johannes

2010-11-01

Full Text Available Abstract Background It is widely accepted that infants at risk for cerebral palsy need paediatric physiotherapy. However, there is little evidence for the efficacy of physiotherapeutic intervention. Recently, a new intervention program, COPCA (Coping with and Caring for infants with special needs - a family centered program, was developed. COPCA has educational and motor goals. A previous study indicated that the COPCA-approach is associated with better developmental outcomes for infants at high risk for developmental disorders. LEARN 2 MOVE 0-2 years evaluates the efficacy and the working mechanisms of the COPCA program in infants at very high risk for cerebral palsy in comparison to the efficacy of traditional infant physiotherapy in a randomized controlled trial. The objective is to evaluate the effects of both intervention programs on motor, cognitive and daily functioning of the child and the family and to get insight in the working elements of early intervention methods. Methods/design Infants are included at the corrected age of 1 to 9 months and randomized into a group receiving COPCA and a group receiving traditional infant physiotherapy. Both interventions are given once a week during one year. Measurements are performed at baseline, during and after the intervention period and at the corrected age of 21 months. Primary outcome of the study is the Infant Motor Profile, a qualitative evaluation instrument of motor behaviour in infancy. Secondary measurements focus on activities and participation, body functions and structures, family functioning, quality of life and working mechanisms. To cope with the heterogeneity in physiotherapy, physiotherapeutic sessions are video-recorded three times (baseline, after 6 months and at the end of the intervention period. Physiotherapeutic actions will be quantified and related to outcome. Discussion LEARN 2 MOVE 0-2 years evaluates and explores the effects of COPCA and TIP. Whatever the outcome of

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.

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.

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 ...

RETRAN02/MOD02: an outside perspective

International Nuclear Information System (INIS)

Wei, T.Y.C.

1984-03-01

ANL recently participated in a review of the RETRAN02/MOD02 code to determine the range of accuracy, the reliability and the reproducibility of results obtained with the code for Chapter 15 non-LOCA system transients for both pressurized water reactors (PWRs) and boiling water reactors (BWRs). This paper summarizes the technical aspects of that review

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.

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...

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.

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.

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...

45 CFR 98.33 - Consumer education.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Consumer education. 98.33 Section 98.33 Public... Program Operations (Child Care Services)-Parental Rights and Responsibilities § 98.33 Consumer education... public consumer education information that will promote informed child care choices including, at a...

45 CFR 98.32 - Parental complaints.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Parental complaints. 98.32 Section 98.32 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION CHILD CARE AND DEVELOPMENT FUND Program Operations (Child Care Services)-Parental Rights and Responsibilities § 98.32 Parental complaints...

22 CFR 9.8 - Classification challenges.

Science.gov (United States)

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

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.)

Experimental Conditions: SE3_S02_M02_D03 [Metabolonote[Archive

Lifescience Database Archive (English)

Full Text Available SE3_S02_M02_D03 SE3 Comparison of fruit metabolites among tomato varieties 1 SE3_S0...2 Solanum lycopersicum House Momotaro fruit SE3_S02_M02 6.7 mg [MassBase ID] MDLC1_25530 SE3_MS1 LC-FT-ICR-M

Experimental Conditions: SE3_S02_M02_D01 [Metabolonote[Archive

Lifescience Database Archive (English)

Full Text Available SE3_S02_M02_D01 SE3 Comparison of fruit metabolites among tomato varieties 1 SE3_S0...2 Solanum lycopersicum House Momotaro fruit SE3_S02_M02 6.7 mg [MassBase ID] MDLC1_25530 SE3_MS1 LC-FT-ICR-M

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.

Coastal Flooding in Florida's Big Bend Region with Application to Sea Level Rise Based on Synthetic Storms Analysis

Directory of Open Access Journals (Sweden)

Scott C. Hagen Peter Bacopoulos

2012-01-01

Full Text Available Flooding is examined by comparing maximum envelopes of water against the 0.2% (= 1-in-500-year return-period flooding surface generated as part of revising the Federal Emergency Management Agency¡¦s flood insurance rate maps for Franklin, Wakulla, and Jefferson counties in Florida¡¦s Big Bend Region. The analysis condenses the number of storms to a small fraction of the original 159 used in production. The analysis is performed by assessing which synthetic storms contributed to inundation extent (the extent of inundation into the floodplain, coverage (the overall surface area of the inundated floodplain and the spatially variable 0.2% flooding surface. The results are interpreted in terms of storm attributes (pressure deficit, radius to maximum winds, translation speed, storm heading, and landfall location and the physical processes occurring within the natural system (storms surge and waves; both are contextualized against existing and new hurricane scales. The approach identifies what types of storms and storm attributes lead to what types of inundation, as measured in terms of extent and coverage, in Florida¡¦s Big Bend Region and provides a basis in the identification of a select subset of synthetic storms for studying the impact of sea level rise. The sea level rise application provides a clear contrast between a dynamic approach versus that of a static approach.

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.

45 CFR 98.31 - Parental access.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Parental access. 98.31 Section 98.31 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION CHILD CARE AND DEVELOPMENT FUND Program Operations (Child Care Services)-Parental Rights and Responsibilities § 98.31 Parental access. The...

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.

Classical propagation of strings across a big crunch/big bang singularity

International Nuclear Information System (INIS)

Niz, Gustavo; Turok, Neil

2007-01-01

One of the simplest time-dependent solutions of M theory consists of nine-dimensional Euclidean space times 1+1-dimensional compactified Milne space-time. With a further modding out by Z 2 , the space-time represents two orbifold planes which collide and re-emerge, a process proposed as an explanation of the hot big bang [J. Khoury, B. A. Ovrut, P. J. Steinhardt, and N. Turok, Phys. Rev. D 64, 123522 (2001).][P. J. Steinhardt and N. Turok, Science 296, 1436 (2002).][N. Turok, M. Perry, and P. J. Steinhardt, Phys. Rev. D 70, 106004 (2004).]. When the two planes are near, the light states of the theory consist of winding M2-branes, describing fundamental strings in a particular ten-dimensional background. They suffer no blue-shift as the M theory dimension collapses, and their equations of motion are regular across the transition from big crunch to big bang. In this paper, we study the classical evolution of fundamental strings across the singularity in some detail. We also develop a simple semiclassical approximation to the quantum evolution which allows one to compute the quantum production of excitations on the string and implement it in a simplified example

Biocontrol agent Bacillus amyloliquefaciens LJ02 induces systemic resistance against cucurbits powdery mildew.

Science.gov (United States)

Li, Yunlong; Gu, Yilin; Li, Juan; Xu, Mingzhu; Wei, Qing; Wang, Yuanhong

2015-01-01

Powdery mildew is a fungal disease found in a wide range of plants and can significantly reduce crop yields. Bacterial strain LJ02 is a biocontrol agent (BCA) isolated from a greenhouse in Tianjin, China. In combination of morphological, physiological, biochemical and phylogenetic analyses, strain LJ02 was classified as a new member of Bacillus amyloliquefaciens. Greenhouse trials showed that LJ02 fermentation broth (LJ02FB) can effectively diminish the occurrence of cucurbits powdery mildew. When treated with LJ02FB, cucumber seedlings produced significantly elevated production of superoxide dismutase, peroxidase, polyphenol oxidase and phenylalanine ammonia lyase as compared to that of the control. We further confirmed that the production of free salicylic acid (SA) and expression of one pathogenesis-related (PR) gene PR-1 in cucumber leaves were markedly elevated after treating with LJ02FB, suggesting that SA-mediated defense response was stimulated. Moreover, LJ02FB-treated cucumber leaves could secrete resistance-related substances into rhizosphere that inhibit the germination of fungi spores and the growth of pathogens. Finally, we separated bacterium and its fermented substances to test their respective effects and found that both components have SA-inducing activity and bacterium plays major roles. Altogether, we identified a BCA against powdery mildew and its mode of action by inducing systemic resistance such as SA signaling pathway.

Temperature dependent polarization reversal mechanism in 0.94(Bi1/2Na1/2)TiO3-0.06Ba(Zr0.02Ti0.98)O3 relaxor ceramics

Science.gov (United States)

Glaum, Julia; Simons, Hugh; Hudspeth, Jessica; Acosta, Matias; Daniels, John E.

2015-12-01

The temperature at which the electric field induced long-range ordered ferroelectric state undergoes transition into the short-range ordered relaxor state, TF-R, is commonly defined by the onset of strong dispersion of the dielectric permittivity. However, this combined macroscopic property and structural investigation of the polarization reversal process in the prototypical lead-free relaxor 0.94(Bi1/2Na1/2)TiO3-0.06Ba(Zr0.02Ti0.98)O3 reveals that an applied electric field can trigger depolarization and onset of relaxor-like behavior well below TF-R. The polarization reversal process can as such be described as a combination of (1) ferroelectric domain switching and (2) a reversible phase transition between two polar ferroelectric states mediated by a non-polar relaxor state. Furthermore, the threshold fields of the second, mediated polarization reversal mechanism depend strongly on temperature. These results are concomitant with a continuous ferroelectric to relaxor transition occurring over a broad temperature range, during which mixed behavior is observed. The nature of polarization reversal can be illustrated in electric-field-temperature (E-T) diagrams showing the electric field amplitudes associated with different polarization reversal processes. Such diagrams are useful tools for identifying the best operational temperature regimes for a given composition in actuator applications.

29 CFR 98.920 - Civil judgment.

Science.gov (United States)

2010-07-01

... 29 Labor 1 2010-07-01 2010-07-01 true Civil judgment. 98.920 Section 98.920 Labor Office of the Secretary of Labor GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 98.920 Civil judgment. Civil judgment means the disposition of a civil action by any court of competent jurisdiction...

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.

Recruitment to publicly funded trials--are surgical trials really different?

Science.gov (United States)

Cook, Jonathan A; Ramsay, Craig R; Norrie, John

2008-09-01

Good recruitment is integral to the conduct of a high-quality randomised controlled trial. It has been suggested that recruitment is particularly difficult for evaluations of surgical interventions, a field in which there is a dearth of evidence from randomised comparisons. While there is anecdotal speculation to support the inference that recruitment to surgical trials is more challenging than for medical trials we are unaware of any formal assessment of this. In this paper, we compare recruitment to surgical and medical trials using a cohort of publicly funded trials. Overall recruitment to trials was assessed using of a cohort of publicly funded trials (n=114). Comparisons were made by using the Recruitment Index, a simple measure of recruitment activity for multicentre randomised controlled trials. Recruitment at the centre level was also investigated through three example surgical trials. The Recruitment Index was found to be higher, though not statistically significantly, in the surgical group (n=18, median=38.0 IQR (10.7, 77.4)) versus (n=81, median=34.8 IQR (11.7, 98.0)) days per recruit for the medical group (median difference 1.7 (-19.2, 25.1); p=0.828). For the trials where the comparison was between a surgical and a medical intervention, the Recruitment Index was substantially higher (n=6, 68.3 (23.5, 294.8)) versus (n=93, 34.6 (11.7, 90.0); median difference 25.9 (-35.5, 221.8); p=0.291) for the other trials. There was no clear evidence that surgical trials differ from medical trials in terms of recruitment activity. There was, however, support for the inference that medical versus surgical trials are more difficult to recruit to. Formal exploration of the recruitment data through a modelling approach may go some way to tease out where important differences exist.

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

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...

45 CFR 98.30 - Parental choice.

Science.gov (United States)

2010-10-01

... Program Operations (Child Care Services)-Parental Rights and Responsibilities § 98.30 Parental choice. (a... category of care; or (2) Having the effect of limiting parental access to or choice from among such... 45 Public Welfare 1 2010-10-01 2010-10-01 false Parental choice. 98.30 Section 98.30 Public...

27 CFR 6.98 - Advertising service.

Science.gov (United States)

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Advertising service. 6.98 Section 6.98 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY LIQUORS âTIED-HOUSEâ Exceptions § 6.98 Advertising service. The listing of the names...

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.

29 CFR 1915.98 - First aid.

Science.gov (United States)

2010-07-01

... 29 Labor 7 2010-07-01 2010-07-01 false First aid. 1915.98 Section 1915.98 Labor Regulations...) OCCUPATIONAL SAFETY AND HEALTH STANDARDS FOR SHIPYARD EMPLOYMENT General Working Conditions § 1915.98 First aid...) Unless a first aid room and a qualified attendant are close at hand and prepared to render first aid to...

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.

Big-bang nucleosynthesis revisited

Science.gov (United States)

Olive, Keith A.; Schramm, David N.; Steigman, Gary; Walker, Terry P.

1989-01-01

The homogeneous big-bang nucleosynthesis yields of D, He-3, He-4, and Li-7 are computed taking into account recent measurements of the neutron mean-life as well as updates of several nuclear reaction rates which primarily affect the production of Li-7. The extraction of primordial abundances from observation and the likelihood that the primordial mass fraction of He-4, Y(sub p) is less than or equal to 0.24 are discussed. Using the primordial abundances of D + He-3 and Li-7 we limit the baryon-to-photon ratio (eta in units of 10 exp -10) 2.6 less than or equal to eta(sub 10) less than or equal to 4.3; which we use to argue that baryons contribute between 0.02 and 0.11 to the critical energy density of the universe. An upper limit to Y(sub p) of 0.24 constrains the number of light neutrinos to N(sub nu) less than or equal to 3.4, in excellent agreement with the LEP and SLC collider results. We turn this argument around to show that the collider limit of 3 neutrino species can be used to bound the primordial abundance of He-4: 0.235 less than or equal to Y(sub p) less than or equal to 0.245.

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.

Advanced Modeling in Excel: from Water Jets to Big Bang

Science.gov (United States)

Ignatova, Olga; Chyzhyk, D.; Willis, C.; Kazachkov, A.

2006-12-01

An international students’ project is presented focused on application of Open Office and Excel spreadsheets for modeling of projectile-motion type dynamical systems. Variation of the parameters of plotted and animated families of jets flowing at different angles out of the holes in the wall of water-filled reservoir [1,2] revealed unexpected peculiarities of the envelopes, vertices, intersections and landing points of virtual trajectories. Comparison with real-life systems and rigorous calculations were performed to prove predictions of computer experiments. By same technique, the kinematics of fireworks was analyzed. On this basis two-dimensional ‘firework’ computer model of Big Bang was designed and studied, its relevance and limitations checked. 1.R.Ehrlich, Turning the World Inside Out, (Princeton University Press, Princeton, NJ, 1990), pp. 98-100. 2.A.Kazachkov, Yu.Bogdan, N.Makarovsky, N.Nedbailo. A Bucketful of Physics, in R.Pinto, S.Surinach (eds), International Conference Physics Teacher Education Beyond 2000. Selected Contributions (Elsevier Editions, Paris, 2001), pp.563-564. Sponsored by Courtney Willis.

Different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease.

Science.gov (United States)

Alshiekh, S; Zhao, L P; Lernmark, Å; Geraghty, D E; Naluai, Å T; Agardh, D

2017-08-01

Celiac disease is associated with the HLA-DR3-DQA1*05:01-DQB1*02:01 and DR4-DQA1*03:01-DQB1*03:02 haplotypes. In addition, there are currently over 40 non-HLA loci associated with celiac disease. This study extends previous analyses on different HLA haplotypes in celiac disease using next generation targeted sequencing. Included were 143 patients with celiac disease and 135 non-celiac disease controls investigated at median 9.8 years (1.4-18.3 years). PCR-based amplification of HLA and sequencing with Illumina MiSeq technology were used for extended sequencing of the HLA class II haplotypes HLA-DRB1, DRB3, DRB4, DRB5, DQA1 and DQB1, respectively. Odds ratios were computed marginally for every allele and haplotype as the ratio of allelic frequency in patients and controls as ratio of exposure rates (RR), when comparing a null reference with equal exposure rates in cases and controls. Among the extended HLA haplotypes, the strongest risk haplotype for celiac disease was shown for DRB3*01:01:02 in linkage with DQA1*05:01-DQB1*02:01 (RR = 6.34; P-value celiac disease among non-Scandinavians (RR = 7.94; P = .011). The data also revealed 2 distinct celiac disease risk DR3-DQA1*05:01-DQB*02:01 haplotypes distinguished by either the DRB3*01:01:02 or DRB3*02:02:01 alleles, indicating that different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease. The associated risk of celiac disease for DR3-DRB3*01:01:02-DQA1*05:01-DQB1*02:01 is predominant among patients of Scandinavian ethnicity. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

46 CFR 98.30-7 - Smoking.

Science.gov (United States)

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Smoking. 98.30-7 Section 98.30-7 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) CARGO AND MISCELLANEOUS VESSELS SPECIAL CONSTRUCTION, ARRANGEMENT, AND OTHER PROVISIONS FOR CERTAIN DANGEROUS CARGOES IN BULK Portable Tanks § 98.30-7 Smoking. No person may smoke within 50 feet of a...

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...

Seeing the "Big" Picture: Big Data Methods for Exploring Relationships Between Usage, Language, and Outcome in Internet Intervention Data.

Science.gov (United States)

Carpenter, Jordan; Crutchley, Patrick; Zilca, Ran D; Schwartz, H Andrew; Smith, Laura K; Cobb, Angela M; Parks, Acacia C

2016-08-31

Assessing the efficacy of Internet interventions that are already in the market introduces both challenges and opportunities. While vast, often unprecedented amounts of data may be available (hundreds of thousands, and sometimes millions of participants with high dimensions of assessed variables), the data are observational in nature, are partly unstructured (eg, free text, images, sensor data), do not include a natural control group to be used for comparison, and typically exhibit high attrition rates. New approaches are therefore needed to use these existing data and derive new insights that can augment traditional smaller-group randomized controlled trials. Our objective was to demonstrate how emerging big data approaches can help explore questions about the effectiveness and process of an Internet well-being intervention. We drew data from the user base of a well-being website and app called Happify. To explore effectiveness, multilevel models focusing on within-person variation explored whether greater usage predicted higher well-being in a sample of 152,747 users. In addition, to explore the underlying processes that accompany improvement, we analyzed language for 10,818 users who had a sufficient volume of free-text response and timespan of platform usage. A topic model constructed from this free text provided language-based correlates of individual user improvement in outcome measures, providing insights into the beneficial underlying processes experienced by users. On a measure of positive emotion, the average user improved 1.38 points per week (SE 0.01, t122,455=113.60, Peffect on change in well-being over time, illustrating which topics may be more beneficial than others when engaging with the interventions. In particular, topics that are related to addressing negative thoughts and feelings were correlated with improvement over time. Using observational analyses on naturalistic big data, we can explore the relationship between usage and well-being among

[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.

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.

49 CFR 98.2 - Definitions.

Science.gov (United States)

2010-10-01

... Administration. (5) The National Highway Traffic Safety Administration. (6) The Urban Mass Transportation... 49 Transportation 1 2010-10-01 2010-10-01 false Definitions. 98.2 Section 98.2 Transportation Office of the Secretary of Transportation ENFORCEMENT OF RESTRICTIONS ON POST-EMPLOYMENT ACTIVITIES...

Trial of Immune Globulin in Infant Botulism

Directory of Open Access Journals (Sweden)

J Gordon Millichap

2006-02-01

Full Text Available A 5-year, randomized, double-blind, placebo-controlled trial of the orphan drug Human Botulism Immune Globulin Intravenous (BIG-IV in 122 infants in California with confirmed infant botulism (75 caused by type A Clostridium botulinum toxin, and 47 by type B toxin was conducted at the California Department of Health Services, Richmond, CA; National Botulism Surveillance and Reference Laboratory, CDC and P, Atlanta; and Division of Biostatistics, University of California, Berkeley.

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...

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

49 CFR 98.1 - Purpose.

Science.gov (United States)

2010-10-01

... 49 Transportation 1 2010-10-01 2010-10-01 false Purpose. 98.1 Section 98.1 Transportation Office of the Secretary of Transportation ENFORCEMENT OF RESTRICTIONS ON POST-EMPLOYMENT ACTIVITIES... administrative enforcement procedures that the Department of Transportation will follow when there is an...

[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.

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.

Experimental Conditions: SE3_S02_M01_D02 [Metabolonote[Archive

Lifescience Database Archive (English)

Full Text Available SE3_S02_M01_D02 SE3 Comparison of fruit metabolites among tomato varieties 1 SE3_S0...2 Solanum lycopersicum House Momotaro fruit SE3_S02_M01 6.7mg [MassBase ID] MDLC1_25529 SE3_MS1 LC-FT-ICR-MS

Experimental Conditions: SE3_S02_M03_D02 [Metabolonote[Archive

Lifescience Database Archive (English)

Full Text Available SE3_S02_M03_D02 SE3 Comparison of fruit metabolites among tomato varieties 1 SE3_S0...2 Solanum lycopersicum House Momotaro fruit SE3_S02_M03 6.7 mg [MassBase ID] MDLC1_25531 SE3_MS1 LC-FT-ICR-M

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…

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.

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...

Association between B vitamins supplementation and risk of cardiovascular outcomes: a cumulative meta-analysis of randomized controlled trials.

Directory of Open Access Journals (Sweden)

Chi Zhang

Full Text Available BACKGROUND: Observational studies suggest that B vitamin supplementation reduces cardiovascular risk in adults, but this association remains controversial. This study aimed to summarize the evidence from randomized controlled trials (RCTs investigating B vitamin supplementation for the primary or secondary prevention of major adverse cardiovascular outcomes and to perform a cumulative meta-analysis to determine the evidence base. METHODOLOGY AND PRINCIPAL FINDINGS: In April 2013, we searched PubMed, Embase, and the Cochrane Library to identify relevant RCTs. We included RCTs investigating the effect of B vitamin supplementation on cardiovascular outcome. Relative risk (RR was used to measure the effect using a random-effect model. Statistical heterogeneity scores were assessed using the Q statistic. We included data on 57,952 individuals from 24 RCTs: 12 primary prevention trials and 12 secondary prevention trials. In 23 of these trials, 10,917 major adverse cardiovascular events (MACE occurred; in 20 trials, 7,203 deaths occurred; in 15 trials, 3,422 cardiac deaths occurred; in 19 trials, 3,623 myocardial infarctions (MI occurred; and in 18 trials, 2,465 strokes occurred. B vitamin supplementation had little or no effect on the incidence of MACE (RR, 0.98; 95% confidence interval [CI]: 0.93-1.03; P = 0.37, total mortality (RR, 1.01; 95% CI: 0.97-1.05; P = 0.77, cardiac death (RR, 0.96; 95% CI: 0.90-1.02; P = 0.21, MI (RR, 0.99; 95% CI: 0.93-1.06; P = 0.82, or stroke (RR, 0.94; 95% CI: 0.85-1.03; P = 0.18. CONCLUSION/SIGNIFICANCE: B vitamin supplementation, when used for primary or secondary prevention, is not associated with a reduction in MACE, total mortality, cardiac death, MI, or stroke.

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,...

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...

EFAM GTP-CREEP 02 - the GKSS test procedure for determining the creep crack extension of materials

International Nuclear Information System (INIS)

Schwalbe, K.H.

2002-01-01

This document describes a fracture mechanics method in procedural form for determining the creep crack extension of materials. It is based on the unified fracture mechanics test method EFAM GTP 02, the ASTM standard E 1457-98, activities of VAMAS TWA 19, and GKSS experience in creep crack extension testing. It introduces novel features such as the rate of the δ 5 crack tip opening displacement, the crack tip opening angle, and the middle cracked tension specimen. (orig.) [de

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

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.

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....

40 CFR 98.413 - Calculating GHG emissions.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Calculating GHG emissions. 98.413 Section 98.413 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) MANDATORY GREENHOUSE GAS REPORTING Suppliers of Industrial Greenhouse Gases § 98.413 Calculating...

40 CFR 98.416 - Data reporting requirements.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Data reporting requirements. 98.416 Section 98.416 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) MANDATORY GREENHOUSE GAS REPORTING Suppliers of Industrial Greenhouse Gases § 98.416 Data...

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...

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.

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

Phenomenological description of depoling current in Pb0.99Nb0.02(Zr0.95Ti0.05)0.98O3 ferroelectric ceramics under shock wave compression: Relaxation model

Science.gov (United States)

Jiang, Dongdong; Du, Jinmei; Gu, Yan; Feng, Yujun

2012-05-01

By assuming a relaxation process for depolarization associated with the ferroelectric (FE) to antiferroelectric (AFE) phase transition in Pb0.99Nb0.02(Zr0.95Ti0.05)0.98O3 ferroelectric ceramics under shock wave compression, we build a new model for the depoling current, which is different from both the traditional constant current source (CCS) model and the phase transition kinetics (PTK) model. The characteristic relaxation time and new-equilibrated polarization are dependent on both the shock pressure and electric field. After incorporating a Maxwell s equation, the relaxation model developed applies to all the depoling currents under short-circuit condition and high-impedance condition. Influences of shock pressure, load resistance, dielectric property, and electrical conductivity on the depoling current are also discussed. The relaxation model gives a good description about the suppressing effect of the self-generated electric field on the FE-to-AFE phase transition at low shock pressures, which cannot be described by the traditional models. After incorporating a time- and electric-field-dependent repolarization, this model predicts that the high-impedance current eventually becomes higher than the short-circuit current, which is consistent with the experimental results in the literature. Finally, we make the comparison between our relaxation model and the traditional CCS model and PTK model.

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.

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.”

EXAFS and EPR study of La0.6Sr0.2Ca0.2MnO3 and La0.6Sr0.2Ba0.2MnO3

International Nuclear Information System (INIS)

Yang, D.-K.Dong-Seok; Ulyanov, A.N.; Phan, Manh-Huong; Kim, Ikgyun; Ahn, Byong-Keun; Rhee, Jang Roh; Kim, Jung Sun; Nguyen, Chau; Yu, Seong-Cho

2003-01-01

Extended X-ray absorption fine structure (EXAFS) analysis and electron-paramagnetic resonance (EPR) have been used to examine the local structure and the internal dynamics of La 0.6 Sr 0.2 Ca 0.2 MnO 3 and La 0.6 Sr 0.2 Ba 0.2 MnO 3 lanthanum manganites. The Mn-O bond distance (∼1.94 Angst for both samples) and the Debye-Waller factors (0.36x10 -2 and 0.41x10 -2 Angst 2 for La 0.6 Sr 0.2 Ca 0.2 MnO 3 and for La 0.6 Sr 0.2 Ba 0.2 MnO 3 , respectively) were obtained from the EXAFS analysis. The dependence of the EPR line width on dopant kind (Ca or Ba) showed a decrease of the spin-lattice interaction with an increase of the Curie temperature. For both compositions, the EPR line intensity followed the exponential law I(T)=I 0 exp(E a /k B T), deduced on the basis of the adiabatic polaron hopping model

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...

40 CFR 98.406 - Data reporting requirements.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Data reporting requirements. 98.406 Section 98.406 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) MANDATORY GREENHOUSE GAS REPORTING Suppliers of Natural Gas and Natural Gas Liquids § 98.406 Data...

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.

Poor nutritional status on admission predicts poor outcomes after stroke: observational data from the FOOD trial.

Science.gov (United States)

2003-06-01

Previous studies suggest that undernourished patients with acute stroke do badly. The data, however, are not robust. We aimed to reliably assess the importance of baseline nutritional status as an independent predictor of long-term outcome after stroke in a large prospective cohort enrolled in the Feed Or Ordinary Diet (FOOD) trial, a multicenter randomized trial evaluating various feeding policies. Patients admitted to hospital with a recent stroke were enrolled in the FOOD trial. Data on nutritional status and other clinical predictors of outcome were collected at trial entry. At 6 months, the coordinating center collected data on survival and functional status (modified Rankin Scale). Outcome assessment was done by researchers blinded to baseline assessments and treatment allocation. Between November 1996 and November 2001, 3012 patients were enrolled, and 2955 (98%) were followed up. Of the 275 undernourished patients, 102 (37%) were dead by final follow-up compared with only 445 (20%) of 2194 patients of normal nutritional status (odds ratio [OR], 2.32; 95% CI, 1.78 to 3.02). After adjustment for age, prestroke functional state, and stroke severity, this relationship, although weakened, still held (OR, 1.82; 95% CI, 1.34 to 2.47). Undernourished patients were more likely to develop pneumonia, other infections, and gastrointestinal bleeding during their hospital admission than other patients. These data provide reliable evidence that nutritional status early after stroke is independently associated with long-term outcome. It supports the rationale for the FOOD trial, which continues to recruit and aims to estimate the effect of different feeding regimes on outcome after stroke and thus determine whether the association observed in this study is likely to be causal.

40 CFR 98.38 - Definitions.

Science.gov (United States)

2010-07-01

... Still Gas 0.143 66.72 Kerosene 0.135 75.20 Liquefied petroleum gases (LPG) 0.092 62.98 Propane 0.091 61... GREENHOUSE GAS REPORTING General Stationary Fuel Combustion Sources § 98.38 Definitions. All terms used in... 93.65 Mixed (Industrial sector) 22.35 93.91 Mixed (Electric Power sector) 19.73 94.38 Natural gas mm...

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.

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...

40 CFR 98.412 - GHGs to report.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false GHGs to report. 98.412 Section 98.412 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) MANDATORY GREENHOUSE GAS REPORTING Suppliers of Industrial Greenhouse Gases § 98.412 GHGs to report. You must report...

40 CFR 98.411 - Reporting threshold.

Science.gov (United States)

2010-07-01

...) MANDATORY GREENHOUSE GAS REPORTING Suppliers of Industrial Greenhouse Gases § 98.411 Reporting threshold. Any supplier of industrial greenhouse gases who meets the requirements of § 98.2(a)(4) must report GHG...

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.

Recommendations for Collection and Handling of Specimens From Group Breast Cancer Clinical Trials

Science.gov (United States)

Leyland-Jones, Brian R.; Ambrosone, Christine B.; Bartlett, John; Ellis, Matthew J.C.; Enos, Rebecca A.; Raji, Adekunle; Pins, Michael R.; Zujewski, Jo Anne; Hewitt, Stephen M.; Forbes, John F.; Abramovitz, Mark; Braga, Sofia; Cardoso, Fatima; Harbeck, Nadia; Denkert, Carsten; Jewell, Scott D.

2008-01-01

Recommendations for specimen collection and handling have been developed for adoption across breast cancer clinical trials conducted by the Breast International Group (BIG)-sponsored Groups and the National Cancer Institute (NCI)-sponsored North American Cooperative Groups. These recommendations are meant to promote identifiable standards for specimen collection and handling within and across breast cancer trials, such that the variability in collection/handling practices that currently exists is minimized and specimen condition and quality are enhanced, thereby maximizing results from specimen-based diagnostic testing and research. Three working groups were formed from the Cooperative Group Banking Committee, BIG groups, and North American breast cancer cooperative groups to identify standards for collection and handling of (1) formalin-fixed, paraffin-embedded (FFPE) tissue; (2) blood and its components; and (3) fresh/frozen tissue from breast cancer trials. The working groups collected standard operating procedures from multiple group specimen banks, administered a survey on banking practices to those banks, and engaged in a series of discussions from 2005 to 2007. Their contributions were synthesized into this document, which focuses primarily on collection and handling of specimens to the point of shipment to the central bank, although also offers some guidance to central banks. Major recommendations include submission of an FFPE block, whole blood, and serial serum or plasma from breast cancer clinical trials, and use of one fixative and buffer type (10% neutral phosphate-buffered formalin, pH 7) for FFPE tissue across trials. Recommendations for proper handling and shipping were developed for blood, serum, plasma, FFPE, and fresh/frozen tissue. PMID:18955459

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)

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

A Meta-Analysis of Randomized Controlled Trials of Yiqi Yangyin Huoxue Method in Treating Diabetic Nephropathy

Directory of Open Access Journals (Sweden)

Jiao Ying Ou

2016-01-01

Full Text Available Objective. The purpose of this systematic review is to evaluate the evidence of Yiqi Yangyin Huoxue Method for diabetic nephropathy. Methods. 11 electronic databases, through September 2015, were searched to identify randomized controlled trials of Yiqi Yangyin Huoxue Method for diabetic nephropathy. The quality of the included trials was assessed using the Jadad scale. Results. 26 randomized controlled trials were included in our review. Of all the included trials, most of them were considered as high quality. The aggregated results suggested that Yiqi Yangyin Huoxue Method is beneficial to diabetic nephropathy in bringing down the microalbuminuria (SMD = −0.98, 95% CI −1.22 to −0.74, serum creatinine (SMD = −0.56, 95% CI −0.93 to −0.20, beta-2 microglobulin (MD = 0.06, 95% CI 0.01 to 0.12, fasting plasma glucose (MD = −0.35, 95% CI −0.62 to −0.08, and 2-hour postprandial blood glucose (MD = 1.13, 95% CI 0.07 to 2.20, but not in decreasing blood urea nitrogen (SMD = −0.72, 95% CI −1.47 to 0.02 or 2-hour postprandial blood glucose (SMD = −0.48, 95% CI −1.01 to 0.04. Conclusions. Yiqi Yangyin Huoxue Method should be a valid complementary and alternative therapy in the management of diabetic nephropathy, especially in improving UAER, serum creatinine, fasting blood glucose, and beta-2 microglobulin. However, more studies with long follow-up are warrant to confirm the current findings.

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,…

46 CFR 98.25-65 - Filling density.

Science.gov (United States)

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Filling density. 98.25-65 Section 98.25-65 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) CARGO AND MISCELLANEOUS VESSELS SPECIAL... § 98.25-65 Filling density. (a) The filling density, or the percent ratio of the liquefied gas that may...

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

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.

Big nuclear accidents

International Nuclear Information System (INIS)

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