Sample records for anulus fibrosus predicted

  1. 1990 Volvo Award in experimental studies. Anulus tears and intervertebral disc degeneration. An experimental study using an animal model. (United States)

    Osti, O L; Vernon-Roberts, B; Fraser, R D


    An animal model was developed to test the hypothesis that discrete peripheral tears within the anulus lead to secondary degenerative changes in other disc components. In 21 adult sheep, a cut was made in the left anterolateral anulus of three randomly selected lumbar discs. The cut was parallel and adjacent to the inferior end-plate, and had a controlled depth of 5 mm. This left the inner third of the anulus and the nucleus pulposus intact and closely reproduced the rim Lear lesion described by Schmorl. Animals were randomly allocated to different groups in relation to the length of time interval between operation and death, varying from 1 to 18 months. At death, the lumbar spine was cut into individual joint units and each disc sectioned into six parasagittal slabs. After observation of the slabs under the dissecting microscope, two of the six slabs, the one containing the anulus lesion and a contralateral, were processed for histology. The results of this study suggest that, despite the great care taken at operation to ensure that the inner anulus was left intact, progressive failure of the inner anulus was seen in all sheep and occurred in the majority of discs between 4 and 12 months after the operation. Although the outermost anulus showed the ability to heal, the defect induced by the cut led initially to deformation and bulging of the collagen bundles, and eventually to inner extension of the tear and complete failure. These findings suggest that discrete tears of the outer anulus may have a role in the formation of concentric clefts and in accelerating the development of radiating clefts. Peripheral tears of the anulus fibrosus therefore may play an important role in the degeneration of the intervertebral joint complex.

  2. Comparison of decellularization protocols for preparing a decellularized porcine annulus fibrosus scaffold.

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    Haiwei Xu

    Full Text Available Tissue-specific extracellular matrix plays an important role in promoting tissue regeneration and repair. We hypothesized that decellularized annular fibrosus matrix may be an appropriate scaffold for annular fibrosus tissue engineering. We aimed to determine the optimal decellularization method suitable for annular fibrosus. Annular fibrosus tissue was treated with 3 different protocols with Triton X-100, sodium dodecyl sulfate (SDS and trypsin. After the decellularization process, we examined cell removal and preservation of the matrix components, microstructure and mechanical function with the treatments to determine which method is more efficient. All 3 protocols achieved decellularization; however, SDS or trypsin disturbed the structure of the annular fibrosus. All protocols maintained collagen content, but glycosaminoglycan content was lost to different degrees, with the highest content with TritonX-100 treatment. Furthermore, SDS decreased the tensile mechanical property of annular fibrosus as compared with the other 2 protocols. MTT assay revealed that the decellularized annular fibrosus was not cytotoxic. Annular fibrosus cells seeded into the scaffold showed good viability. The Triton X-100-treated annular fibrosus retained major extracellular matrix components after thorough cell removal and preserved the concentric lamellar structure and tensile mechanical properties. As well, it possessed favorable biocompatibility, so it may be a suitable candidate as a scaffold for annular fibrosus tissue engineering.


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    Reinaldy Nazar


    Full Text Available ABSTRAK KARAKTERISTIK PERPINDAHAN PANAS KONVEKSI ALAMIAH ALIRAN NANOFLUIDA AL2O3-AIR DI DALAM PIPA ANULUS VERTIKAL. Hasil beberapa penelitian menunjukan bahwa nanofluida memiliki karakteristik termal yang lebih baik dibandingkan dengan fluida konvensional (air. Berkaitan dengan hal tersebut, saat ini sedang berkembang pemikiran untuk menggunakan nanofluida sebagai fluida perpindahan panas alternatif pada sistem pedingin reaktor. Sementara itu, konveksi alamiah di dalam pipa anulus vertikal merupakan salah satu mekanisme perpindahan panas yang penting dan banyak ditemukan pada reaktor riset TRIGA, reaktor daya generasi baru dan alat konversi energi lainnya. Namun disisi lain karakteristik perpindahan panas nanofluida di dalam pipa anulus vertikal belum banyak diketahui. Oleh karena itu penting dilakukan secara berkesinambungan penelitian-penelitian untuk menganalisis perpindahan panas nanofluida di dalam pipa anulus vertikal. Pada penelitian telah dilakukan analisis numerik menggunakan program computer CFD (computational of fluids dynamic terhadap karakteristik perpindahan panas konveksi alamiah aliran nanofluida Al2O3-air konsentrasi 2% volume di dalam pipa anulus vertikal. Hasil kajian ini menunjukkan terjadi peningkatan kinerja perpindahan panas (bilangan Nuselt- NU sebesar 20,5% - 35%. Pada moda konveksi alamiah dengan bilangan 2,4708e+09 £ Ra £ 1,9554e+13 diperoleh korelasi empirik untuk air adalah dan korelasi empirik untuk nanofluida Al2O3-air adalah   Kata kunci: Nanofluida Al2O3-air, konveksi alamiah, pipa anulus vertikal     ABSTRACT THE CHARACTERISTICS OF NATURAL CONVECTIVE HEAT TRANSFER OF AL2O3–WATER NANOFLUIDS FLOW IN A VERTICAL ANNULUS PIPE. Results of several research have shown that nanofluids have better thermal characteristics compared to conventional fluid (water. In this regard, currently developing ideas for using nanofluids as an alternative heat transfer fluid in the reactor coolant system. Meanwhile the natural

  4. Bovine annulus fibrosus cell lines isolated from intervertebral discs

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    Petra Kraus


    Full Text Available The adult bovine (Bos taurus intervertebral disc is primarily comprised of two major tissue types: The outer annulus fibrosus (AF and the central nucleus pulposus (NP. We isolated several primary cell lineages of passage (P 0 cells from the AF tissue omitting typically used enzymatic tissue digestion protocols. The cells grow past p10 without signs of senescence in DMEM + 10% FCS on 0.1% gelatin coated/uncoated surfaces of standard cell culture plates and survive freeze-thawing. Preliminary analysis of the AF derived cells for expression of the two structural genes Col1a1 and Col2a1 was performed by PISH recapitulating the expression observed in vivo.

  5. Identification of rabbit annulus fibrosus-derived stem cells.

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    Chen Liu

    Full Text Available Annulus fibrosus (AF injuries can lead to substantial deterioration of intervertebral disc (IVD which characterizes degenerative disc disease (DDD. However, treatments for AF repair/regeneration remain challenging due to the intrinsic heterogeneity of AF tissue at cellular, biochemical, and biomechanical levels. In this study, we isolated and characterized a sub-population of cells from rabbit AF tissue which formed colonies in vitro and could self-renew. These cells showed gene expression of typical surface antigen molecules characterizing mesenchymal stem cells (MSCs, including CD29, CD44, and CD166. Meanwhile, they did not express negative markers of MSCs such as CD4, CD8, and CD14. They also expressed Oct-4, nucleostemin, and SSEA-4 proteins. Upon induced differentiation they showed typical osteogenesis, chondrogenesis, and adipogenesis potential. Together, these AF-derived colony-forming cells possessed clonogenicity, self-renewal, and multi-potential differentiation capability, the three criteria characterizing MSCs. Such AF-derived stem cells may potentially be an ideal candidate for DDD treatments using cell therapies or tissue engineering approaches.

  6. An annulus fibrosus closure device based on a biodegradable shape-memory polymer network

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    Sharifi, Shahriar; van Kooten, Theo G.; Kranenburg, Hendrik-Jan C.; Meij, Bjorn P.; Behl, Marc; Lendlein, Andreas; Grijpma, Dirk W.


    Injuries to the intervertebral disc caused by degeneration or trauma often lead to tearing of the annulus fibrosus (AF) and extrusion of the nucleus pulposus (NP). This can compress nerves and cause lower back pain. In this study, the characteristics of poly(D,L-lactide-co-trimethylene carbonate)

  7. Origin and Evolution of Allopolyploid Wheatgrass Elymus fibrosus (Schrenk Tzvelev (Poaceae: Triticeae Reveals the Effect of Its Origination on Genetic Diversity.

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    De-Chuan Wu

    Full Text Available Origin and evolution of tetraploid Elymus fibrosus (Schrenk Tzvelev were characterized using low-copy nuclear gene Rpb2 (the second largest subunit of RNA polymerase II, and chloroplast region trnL-trnF (spacer between the tRNA Leu (UAA gene and the tRNA-Phe (GAA gene. Ten accessions of E. fibrosus along with 19 Elymus species with StH genomic constitution and diploid species in the tribe Triticeae were analyzed. Chloroplast trnL-trnF sequence data suggested that Pseudoroegneria (St genome was the maternal donor of E. fibrosus. Rpb2 data confirmed the presence of StH genomes in E. fibrosus, and suggested that St and H genomes in E. fibrosus each is more likely originated from single gene pool. Single origin of E. fibrosus might be one of the reasons causing genetic diversity in E. fibrosus lower than those in E. caninus and E. trachycaulus, which have similar ecological preferences and breeding systems with E. fibrosus, and each was originated from multiple sources. Convergent evolution of St and H copy Rpb2 sequences in some accessions of E. fibrosus might have occurred during the evolutionary history of this allotetraploid.

  8. Human adipose stem cells in chondrogenic differentiation medium without growth factors differentiate towards annulus fibrosus phenotype in vitro

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    Gebraad, Arjen; Miettinen, S.; Grijpma, Dirk W.; Haimi, Suvi


    Intervertebral disc degeneration is the main cause of chronic back pain. Disc degeneration mainly leads to tearing of annulus fibrosus (AF), which is with current methods difficult to restore and impossible to regenerate. Stem cell technology offers a potential technique to repair the ruptured AF by

  9. Lacertus fibrosus augmentation for distal biceps brachii rupture repair: surgical technique. (United States)

    Fontana, M; Trimarchi, A; Colozza, A


    Repair of distal biceps tendon ruptures has become widely accepted. Unfortunately, care of retracted-degenerated injuries remains a challenge for orthopedic surgeons. Complication rates appear to increase when surgery is performed in chronic cases compared to those operated acutely. Multiple techniques for chronic reconstruction with the use of grafts have been described. Recently Morrey, from the Mayo Clinic, proposed a direct anatomic repair of retracted distal biceps tendon ruptures in extreme flexion (60°-90°) to avoid grafting. The authors propose and describe a new surgical technique using the lacertus fibrosus (LF) as augmentation-elongation for retracted-degenerated distal biceps tendon tears. We present four cases with chronic ruptures with 2-year follow-up. The mean age was 45 years old (33-51), the time of surgery was 13 weeks (4-24) after the trauma, dominant arm was involved in two cases. The mean MEPS was 95/100 at 2-year follow-up. With this technique we increase the length of the tendon up to 2.5 cm. The major complication in our study was transient sensitive radial nerve paresthesia. We did not have any hardware mobilization or muscular herniation. With this study we want to present our experience in the treatment of retracted distal biceps tendon tear with lacertus fibrosus augmentation. Our surgical technique is an effective and cheap option for chronic-retracted distal biceps tendon lesions. Recovery time is quicker, and integration is faster due to the use of an autologous vascularized graft. Preoperative ultrasound scan is mandatory in order to evaluate LF integrity, thickness and size.

  10. Intervertebral Disc Degeneration : The Role of the Mitochondrial Pathway in Annulus Fibrosus Cell Apoptosis Induced by Overload


    Rannou, François; Lee, Tzong-Shyuan; Zhou, Rui-Hai; Chin, Jennie; Lotz, Jeffrey C.; Mayoux-Benhamou, Marie-Anne; Barbet, Jacques Patrick; Chevrot, Alain; Shyy, John Y.-J.


    Degeneration of the intervertebral disk (IVD) is a major pathological process implicated in low back pain and is a prerequisite to disk herniation. Although mechanical stress is an important modulator of the degeneration, the underlying molecular mechanism remains unclear. The association of human IVD degeneration, assessed by magnetic resonance imaging, with annulus fibrosus cell apoptosis and anti-cytochrome c staining revealed that the activation of the mitochondria-dependent apoptosome wa...

  11. Mechanics of oriented electrospun nanofibrous scaffolds for annulus fibrosus tissue engineering. (United States)

    Nerurkar, Nandan L; Elliott, Dawn M; Mauck, Robert L


    Engineering a functional replacement for the annulus fibrosus (AF) of the intervertebral disc is contingent upon recapitulation of AF structure, composition, and mechanical properties. In this study, we propose a new paradigm for AF tissue engineering that focuses on the reconstitution of anatomic fiber architecture and uses constitutive modeling to evaluate construct function. A modified electrospinning technique was utilized to generate aligned nanofibrous polymer scaffolds for engineering the basic functional unit of the AF, a single lamella. Scaffolds were tested in uniaxial tension at multiple fiber orientations, demonstrating a nonlinear dependence of modulus on fiber angle that mimicked the nonlinearity and anisotropy of native AF. A homogenization model previously applied to native AF successfully described scaffold mechanical response, and parametric studies demonstrated that nonfibrillar matrix, along with fiber connectivity, are key contributors to tensile mechanics for engineered AF. We demonstrated that AF cells orient themselves along the aligned scaffolds and deposit matrix that contributes to construct mechanics under loading conditions relevant to the in vivo environment. The homogenization model was applied to cell-seeded constructs and provided quantitative measures for the evolution of matrix and interfibrillar interactions. Finally, the model demonstrated that at fiber angles of the AF (28 degrees -44 degrees ), engineered material behaved much like native tissue, suggesting that engineered constructs replicate the physiologic behavior of the single AF lamella. Constitutive modeling provides a powerful tool for analysis of engineered AF neo-tissue and native AF tissue alike, highlighting key mechanical design criteria for functional AF tissue engineering.

  12. Molecular Imaging Agents Specific for the Annulus Fibrosus of the Intervertebral Disk

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    Summer L. Gibbs-Strauss


    Full Text Available Low back pain is a prevalent medical condition that is difficult to diagnose and treat. Current imaging methods are unable to correlate pain reliably with spinal structures, and surgical removal of painful damaged or degenerating disks is technically challenging. A contrast agent specific for the intervertebral disk could assist in the detection, diagnosis, and surgical treatment of low back pain. The styryl pyridinium (FM fluorophores were characterized and structure-activity relationships between chemical structure and in vivo uptake were established. Two novel FM fluorophores with improved optical properties for imaging the intervertebral disks were synthesized and evaluated in mice, rats, and pigs. After a single systemic injection, eight of eight FM fluorophores provided high-contrast imaging of the trigeminal ganglia, whereas six of eight provided high-contrast imaging of the dorsal root ganglia. Unexpectedly, three of eight FM fluorophores provided high-contrast imaging of annulus fibrosus tissue of the intervertebral disks, confirmed histologically. We present the first known contrast agent specific for the intervertebral disks and identify the chemical structural motif that mediates uptake. FM fluorophores could be used for image-guided surgery to assist in the removal of intervertebral disk and lay the foundation for derivatives for magnetic resonance imaging and positron emission tomography.

  13. Human annulus fibrosus material properties from biaxial testing and constitutive modeling are altered with degeneration. (United States)

    O'Connell, Grace D; Sen, Sounok; Elliott, Dawn M


    The annulus fibrosus (AF) of the intervertebral disk undergoes large and multidirectional stresses and strains. Uniaxial tensile tests are limited for measuring AF material properties, because freely contracting edges can prevent fiber stretch and are not representative of in situ boundary conditions. The objectives of this study were to measure human AF biaxial tensile mechanics and to apply and validate a constitutive model to determine material properties. Biaxial tensile tests were performed on samples oriented along the circumferential-axial and the radial-axial directions. Data were fit to a structurally motivated anisotropic hyperelastic model composed of isotropic extra-fibrillar matrix, nonlinear fibers, and fiber-matrix interactions (FMI) normal to the fibers. The validated model was used to simulate shear and uniaxial tensile behavior, to investigate AF structure-function, and to quantify the effect of degeneration. The biaxial stress-strain response was described well by the model (R (2) > 0.9). The model showed that the parameters for fiber nonlinearity and the normal FMI correlated with degeneration, resulting in an elongated toe-region and lower stiffness with degeneration. The model simulations in shear and uniaxial tension successfully matched previously published circumferential direction Young's modulus, provided an explanation for the low values in previously published axial direction Young's modulus, and was able to simulate shear mechanics. The normal FMI were important contributors to stress and changed with degeneration, therefore, their microstructural and compositional source should be investigated. Finally, the biaxial mechanical data and constitutive model can be incorporated into a disk finite element model to provide improved quantification of disk mechanics.

  14. Differentiation of adipose stem cells seeded towards annulus fibrosus cells on a designed poly(trimethylene carbonate) scaffold prepared by stereolithography

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    Blanquer, Sebastien B. G.; Gebraad, Arjen W. H.; Miettinen, Susanna; Poot, Andre A.; Grijpma, Dirk W.; Haimi, Suvi P.


    Cell-based therapies could potentially restore the biomechanical function and enhance the self-repair capacity of annulus fibrosus (AF) tissue. However, choosing a suitable cell source and scaffold design are still key challenges. In this study, we assessed the in vitro ability of human adipose stem

  15. Annulus fibrosus cells express and utilize C-C chemokine receptor 5 (CCR5) for migration. (United States)

    Liu, Weijun; Liu, David; Zheng, Justin; Shi, Peng; Chou, Po-Hsin; Oh, Chundo; Chen, Di; An, Howard S; Chee, Ana


    Disc degeneration is associated with the progressive loss of the proteoglycan content of the intervertebral disc, decreased matrix synthesis, higher concentrations of proteolytic enzymes, and increased levels of proinflammatory cytokines. In previous studies, we have shown that C-C chemokine ligand (CCL)2, CCL3, and CCL5 are highly expressed by cultured nucleus pulposus (NP) and annulus fibrosus (AF) cells that have been treated by interleukin-1. The major function of these chemokines is to recruit immune cells into the disc. It is unclear if disc cells can respond to these chemokines. Recent studies by Phillips et al. (2015) showed that NP cells express a number of cytokines and chemokine receptors. The purpose of this study is to determine the gene and protein expression of C-C chemokine receptor (CCR)1, CCR2, and CCR5 in NP and AF cells, and to test if these receptors can respond to their ligands in these cells by cell signaling and migration. This is an in vitro study. For RNA, surface expression, and cell signaling studies, human cells were isolated from the NP and AF tissues collected after spine surgery or from donated spine segments (Gift of Hope Human Donor & Tissue Network of Illinois) and cultured in monolayer. The gene expression of human CCR1, CCR2, and CCR5 was analyzed using real-time polymerase chain reaction. The surface expression of CCR1, CCR2, and CCR5 was analyzed using flow cytometry and fluorescently tagged antibodies specific for these proteins. Extracellular signal-regulated kinase (ERK) phosphorylation was analyzed from the cell lysates of NP and AF cells treated with CCL2 and CCL5 for 1 hour using enzyme-linked immunosorbent assay. Migration of primary rabbit AF cells was assayed using 8-µm Corning Transwell inserts in the presence or absence of CCL5. This study was partially funded by a North American Spine Society 2014 Basic Research Grant Award ($50,000). RNA analysis showed that gene expression of CCR1, CCR2, and CCR5 was evident in

  16. Protective effect of niacinamide on interleukin-1beta-induced annulus fibrosus type II collagen degeneration in vitro. (United States)

    Duan, Deyu; Yang, Shuhua; Shao, Zengwu; Wang, Hong; Xiong, Xiaoqian


    The protective effect of niacinamide on interleukin-1beta (IL-1beta)-induced annulus fibrosus (AF) type II collagen degeneration in vitro and the mechanism were investigated. Chiba's intervertebral disc (IVD) culture models in rabbits were established and 48 IVDs from 12 adult Japanese white rabbits were randomly divided into 4 groups: normal control group, niacinamide-treated group, type II collagen degneration group (IL-1beta) and treatment group (niacinamide+IL-1beta). After culture for one week, AFs were collected for inducible nitric oxide synthase (iNOS), cysteine containing aspartate specific protease-3 (Caspase-3) and type II collagen immunohistochemical examination, and type II collagen reverse transcription polymerase chain reaction (RT-PCR). The results showed that rate of iNOS positive staining AF cells in the 4 groups was 17.6%, 10.9%, 73.9% and 19.3% respectively. The positive rate in treatment group was significantly lower than in the type II collagen degeneration group (Pniacinamide could effectively inhibit IL-1beta stimulated increase of iNOS and Caspase-3 in AF, and alleviate IL-1beta-caused destruction and synthesis inhibition of type II collagen. Niacinamide is of potential for clinical treatment of IVD degeneration.

  17. Effect of orientation and targeted extracellular matrix degradation on the shear mechanical properties of the annulus fibrosus. (United States)

    Jacobs, Nathan T; Smith, Lachlan J; Han, Woojin M; Morelli, Jeffrey; Yoder, Jonathon H; Elliott, Dawn M


    The intervertebral disc experiences combinations of compression, torsion, and bending that subject the disc substructures, particularly the annulus fibrosus (AF), to multidirectional loads and deformations. Combined tensile and shear loading is a particularly important loading paradigm, as compressive loads place the AF in circumferential hoop tension, and spine torsion or bending induces AF shear. Yet the anisotropy of AF mechanical properties in shear, as well as important structure-function mechanisms governing this response, are not well-understood. The objective of this study, therefore, was to investigate the effects of tissue orientation and enzymatic degradation of glycosaminoglycan (GAG) and elastin on AF shear mechanical properties. Significant anisotropy was found: the circumferential shear modulus, Gθz, was an order of magnitude greater than the radial shear modulus, Grθ. In the circumferential direction, prestrain significantly increased the shear modulus, suggesting an important role for collagen fiber stretch in shear properties for this orientation. While not significant and highly variable, ChABC treatment to remove GAG increased the circumferential shear modulus compared to PBS control (p=0.15). Together with the established literature for tensile loading of fiber-reinforced GAG-rich tissues, the trends for changes in shear modulus with ChABC treatment reflect complex, structure-function relationships between GAG and collagen that potentially occur over several hierarchical scales. Elastase digestion did not significantly affect shear modulus with respect to PBS control; further contributing to the notion that circumferential shear modulus is dominated by collagen fiber stretch. The results of this study highlight the complexity of the structure-function relationships that govern the mechanical response of the AF in radial and circumferential shear, and provide new and more accurate data for the validation of material models and tissue

  18. Three-dimensional development of tensile pre-strained annulus fibrosus cells for tissue regeneration: An in-vitro study

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    Chuah, Yon Jin [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459 (Singapore); Lee, Wu Chean [University Hospital Conventry & Warwickshire NHS Trust, Clifford Bridge Road, West Midlands CV2, 2DX (United Kingdom); Wong, Hee Kit [Department of Orthopedic Surgery, National University Health System, NUHS Tower Block Level 11, 1E Kent Ridge Road, Singapore 119228 (Singapore); Kang, Yuejun, E-mail: [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459 (Singapore); Hee, Hwan Tak, E-mail: [School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459 (Singapore); Pinnacle Spine & Scoliosis Centre, 3 Mount Elizabeth, Mount Elizabeth Medical Centre, #04-07, Singapore 228510 (Singapore); School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637459 (Singapore)


    Prior research has investigated the immediate response after application of tensile strain on annulus fibrosus (AF) cells for the past decade. Although mechanical strain can produce either catabolic or anabolic consequences to the cell monolayer, little is known on how to translate these findings into further tissue engineering applications. Till to date, the application and effect of tensile pre-strained cells to construct a three-dimensional (3D) AF tissue remains unknown. This study aims to investigate the effect of tensile pre-strained exposure of 1 to 24 h on the development of AF pellet culture for 3 weeks. Equibiaxial cyclic tensile strain was applied on AF monolayer cells over a period of 24 h, which was subsequently developed into a cell pellet. Investigation on cellular proliferation, phenotypic gene expression, and histological changes revealed that tensile pre-strain for 24 h had significant and lasting effect on the AF tissue development, with enhanced cell proliferation, and up-regulation of collagen type I, II, and aggrecan expression. Our results demonstrated the regenerative ability of AF cell pellets subjected to 24 h tensile pre-straining. Knowledge on the effects of tensile pre-strain exposure is necessary to optimize AF development for tissue reconstruction. Moreover, the tensile pre-strained cells may further be utilized in either cell therapy to treat mild disc degeneration disease, or the development of a disc construct for total disc replacement. - Highlights: • Establishment of tensile pre-strained cell line population for annulus development. • Tensile strain limits collagen gene expression declination in monolayer culture. • Tensile pre-strained cells up-regulate their matrix protein in 3D pellet culture.

  19. Beta1 integrin inhibits apoptosis induced by cyclic stretch in annulus fibrosus cells via ERK1/2 MAPK pathway. (United States)

    Zhang, Kai; Ding, Wei; Sun, Wei; Sun, Xiao-jiang; Xie, You-zhuan; Zhao, Chang-qing; Zhao, Jie


    Low back pain is associated with intervertebral disc degeneration (IVDD) due to cellular loss through apoptosis. Mechanical factors play an important role in maintaining the survival of the annulus fibrosus (AF) cells and the deposition of extracellular matrix. However, the mechanisms that excessive mechanical forces lead to AF cell apoptosis are not clear. The present study was to look for how AF cells sense mechanical changes. In vivo experiments, the involvement of mechanoreceptors in apoptosis was examined by RT-PCR and/or immunoblotting in the lumbar spine of rats subjected to unbalanced dynamic and static forces. In vitro experiments, we investigated apoptotic signaling pathways in untransfected and transfected AF cells with the lentivirus vector for rat β1 integrin overexpression after cyclic stretch. Apoptosis in AF cells was assessed using flow cytometry, Hoechst 33258 nuclear staining. Western blotting was used to analyze expression of β1 integrin and caspase-3 and ERK1/2 MAPK signaling molecules. In the rat IVDD model, unbalanced dynamic and static forces induced apoptosis of disc cells, which corresponded to decreased expression of β1 integrin. Cyclic stretch-induced apoptosis in rat AF cells correlated with the activation of caspase-3 and with decreased levels of β1 integrin and the phosphorylation levels of ERK1/2 activation level. However, the overexpression of β1 integrin in AF cells ameliorated cyclic stretch-induced apoptosis and decreased caspase-3 activation. Furthermore, ERK1/2-specific inhibitor promotes apoptosis in vector β1-infected AF cells. These results suggest that the disruption of β1 integrin signaling may underlie disc cell apoptosis induced by mechanical stress. Further work is necessary to fully elucidate the pathophysiological mechanisms that underlie IVDD caused by unbalanced dynamic and static forces.

  20. Formation of lamellar cross bridges in the annulus fibrosus of the intervertebral disc is a consequence of vascular regression. (United States)

    Smith, Lachlan J; Elliott, Dawn M


    Cross bridges are radial structures within the highly organized lamellar structure of the annulus fibrosus of the intervertebral disc that connect two or more non-consecutive lamellae. Their origin and function are unknown. During fetal development, blood vessels penetrate deep within the AF and recede during postnatal growth. We hypothesized that cross bridges are the pathways left by these receding blood vessels. Initially, the presence of cross bridges was confirmed in cadaveric human discs aged 25 and 53 years. Next, L1-L2 intervertebral discs (n=4) from sheep ranging in age from 75 days fetal gestation to adult were processed for paraffin histology. Mid-sagittal sections were immunostained for endothelial cell marker PECAM-1. The anterior and posterior AF were imaged using differential interference contrast microscopy, and the following parameters were quantified: total number of distinct lamellae, total number of cross bridges, percentage of cross bridges staining positive for PECAM-1, cross bridge penetration depth (% total lamellae), and PECAM-1 positive cross bridge penetration depth. Cross bridges were first observed at 100 days fetal gestation. The overall number peaked in neonates then remained relatively unchanged. The percentage of PECAM-1 positive cross bridges declined progressively from almost 100% at 100 days gestation to less than 10% in adults. Cross bridge penetration depth peaked in neonates then remained unchanged at subsequent ages. Depth of PECAM-1 positive cross bridges decreased progressively after birth. Findings were similar for both the anterior and posterior. The AF lamellar architecture is established early in development. It later becomes disrupted as a consequence of vascularization. Blood vessels then recede, perhaps due to increasing mechanical stresses in the surrounding matrix. In this study we present evidence that the pathways left by receding blood vessels remain as lamellar cross bridges. It is unclear whether the presence

  1. Accelerated premature stress-induced senescence of young annulus fibrosus cells of rats by high glucose-induced oxidative stress. (United States)

    Park, Jong-Soo; Park, Jong-Beom; Park, In-Joo; Park, Eun-Young


    Diabetes mellitus (DM) is thought to be an important aetiological factor in intervertebral disc degeneration. A glucose-mediated increase of oxidative stress is a major causative factor in development of diseases associated with DM. The aim of this study was to investigate the effect of high glucose on mitochondrial damage, oxidative stress and senescence of young annulus fibrosus (AF) cells. AF cells were isolated from four-week-old young rats, cultured, and placed in either 10 % FBS (normal control) or 10 % FBS plus two different high glucose concentrations (0.1 M and 0.2 M) (experimental conditions) for one and three days. We identified and quantified the mitochondrial damage and reactive oxygen species (ROS) (oxidative stress). We also identified and quantified the occurrence of senescence and telomerase activity. Finally, the expressions of proteins were determined related to replicative senescence (p53-p21-pRB) and stress-induced senescence (p16-pRB). Two high glucoses enhanced the mitochondrial damage in young rat AF cells, which resulted in an excessive generation of ROS in a dose- and time-dependent manner for one and three days compared to normal control. Two high glucose concentrations increased the occurrence of senescence of young AF cells in a dose- and time-dependent manner. Telomerase activity declined in a dose- and time-dependent manner. Both high glucose treatments increased the expressions of p16 and pRB proteins in young rat AF cells for one and three days. However, compared to normal control, the expressions of p53 and p21 proteins were decreased in young rat AF cells treated with both high glucoses for one and three days. The present study demonstrated that high glucose-induced oxidative stress accelerates premature stress-induced senescence in young rat AF cells in a dose- and time-dependent manner rather than replicative senescence. These results suggest that prevention of excessive generation of oxidative stress by strict blood glucose

  2. Do mechanical strain and TNF-α interact to amplify pro-inflammatory cytokine production in human annulus fibrosus cells? (United States)

    Likhitpanichkul, Morakot; Torre, Olivia M; Gruen, Jadry; Walter, Benjamin A; Hecht, Andrew C; Iatridis, James C


    During intervertebral disc (IVD) injury and degeneration, annulus fibrosus (AF) cells experience large mechanical strains in a pro-inflammatory milieu. We hypothesized that TNF-α, an initiator of IVD inflammation, modifies AF cell mechanobiology via cytoskeletal changes, and interacts with mechanical strain to enhance pro-inflammatory cytokine production. Human AF cells (N=5, Thompson grades 2-4) were stretched uniaxially on collagen-I coated chambers to 0%, 5% (physiological) or 15% (pathologic) strains at 0.5Hz for 24h under hypoxic conditions with or without TNF-α (10ng/mL). AF cells were treated with anti-TNF-α and anti-IL-6. ELISA assessed IL-1β, IL-6, and IL-8 production and immunocytochemistry measured F-actin, vinculin and α-tubulin in AF cells. TNF-α significantly increased AF cell pro-inflammatory cytokine production compared to basal conditions (IL-1β:2.0±1.4-84.0±77.3, IL-6:10.6±9.9-280.9±214.1, IL-8:23.9±26.0-5125.1±4170.8pg/ml for basal and TNF-α treatment, respectively) as expected, but mechanical strain did not. Pathologic strain in combination with TNF-α increased IL-1β, and IL-8 but not IL-6 production of AF cells. TNF-α treatment altered F-actin and α-tubulin in AF cells, suggestive of altered cytoskeletal stiffness. Anti-TNF-α (infliximab) significantly inhibited pro-inflammatory cytokine production while anti-IL-6 (atlizumab) did not. In conclusion, TNF-α altered AF cell mechanobiology with cytoskeletal remodeling that potentially sensitized AF cells to mechanical strain and increased TNF-α-induced pro-inflammatory cytokine production. Results suggest an interaction between TNF-α and mechanical strain and future mechanistic studies are required to validate these observations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. [Effects of electroacupuncture on Wnt-β-catenin signal pathway in annulus fibrosus cells in intervertebral disc in rats with cervical spondylosis]. (United States)

    Liao, Jun; Xie, Qiao-Yu; Zhang, Le; Ke, Mei-Gui


    To observe the effects of electroacupuncture (EA) at "Dazhui" (GV 14) on Wnt-β-catenin signal pathway in annulus fibrosus cells in intervertebral disc in rats with cervical spondylosis. Forty SD rats were randomized into a control group, a model group, an EA group and a medication group, 10 rats in each one. Rats in the control group were treated with sham operation, only incision on local skin; rats in the remaining groups were made into cervical spondylosis models. After model establishment, rats in the control group and model group received fixed treatment under identical condition; rats in the EA group were treated with EA at "Dazhui" (GV 14), 30 min per treatment; rats in the medication group were treated with intragastric administration of meloxicam tablets. Treatments were both given once a day, and 14 days were taken as one session; there was an interval of 2 days between two sessions, and totally two sessions were given. After the treatments, immunohistochemistry was applied to measure the expression of Wnt, glycogen synthase kinase-3β (GSK-3β) and Axin in annulus fibrosus cells; western blot was used to test the expression of P-β-catenin. In the control group, there were more positive cells of Wnt, GSK-3β and Axin, which were intensively distributed, deeply colored, and strongly positive; In the model group, there were less positive cells of Wnt, GSK-3β and Axin, which were sparsely distributed and weakly positive. The expression of Wnt, GSK-3β, Axin and P-β-catenin in the model group was less than that in the control group (all P 0.05). EA could delay the degeneration of intervertebral disc, which may be related to EA inhibiting signal pathway of Wnt-β-catenin.

  4. Myxomatous degeneration of the lumbar intervertebral disc. (United States)

    Beatty, R A


    Sixteen patients were operated on for lumbar pain and pain radiating into the sciatic nerve distribution. In all 16, when the anulus fibrosus was incised, soft, gray disc material extruded under pressure like toothpaste being squeezed from a tube. This syndrome of myxomatous degeneration is a distinct entity, different from classical fibrotic disc degeneration or herniated nucleus pulposus. Surgical removal associated with partial facetectomy produced excellent results. The concept of incompetence of the anulus fibrosis is discussed.

  5. Does T2 mapping of the posterior annulus fibrosus indicate the presence of lumbar intervertebral disc herniation? A 3.0 Tesla magnetic resonance study. (United States)

    Messner, Alina; Stelzeneder, David; Trattnig, Stefan; Welsch, Götz H; Schinhan, Martina; Apprich, Sebastian; Brix, Martin; Windhager, Reinhard; Trattnig, Siegfried


    Indicating lumbar disc herniation via magnetic resonance imaging (MRI) T2 mapping in the posterior annulus fibrosus (AF). Sagittal T2 maps of 313 lumbar discs of 64 patients with low back pain were acquired at 3.0 Tesla (3T). The discs were rated according to disc herniation and bulging. Region of interest (ROI) analysis was performed on median, sagittal T2 maps. T2 values of the AF, in the most posterior 10% (PAF-10) and 20% of the disc (PAF-20), were compared. A significant increase in the T2 values of discs with herniations affecting the imaged area, compared to bulging discs and discs with lateral herniation, was shown in the PAF-10, where no association to the NP was apparent. The PAF-20 exhibited a moderate correlation to the nucleus pulposus (NP). High T2 values in the PAF-10 suggest the presence of disc herniation (DH). The results indicate that T2 values in the PAF-20 correspond more to changes in the NP.

  6. Biaxial mechanics and inter-lamellar shearing of stem-cell seeded electrospun angle-ply laminates for annulus fibrosus tissue engineering. (United States)

    Driscoll, Tristan P; Nakasone, Ryan H; Szczesny, Spencer E; Elliott, Dawn M; Mauck, Robert L


    The annulus fibrosus (AF) of the intervertebral disk plays a critical role in vertebral load transmission that is heavily dependent on the microscale structure and composition of the tissue. With degeneration, both structure and composition are compromised, resulting in a loss of AF mechanical function. Numerous tissue engineering strategies have addressed the issue of AF degeneration, but few have focused on recapitulation of AF microstructure and function. One approach that allows for generation of engineered AF with appropriate (+/-)30° lamellar microstructure is the use of aligned electrospun scaffolds seeded with mesenchymal stem cells (MSCs) and assembled into angle-ply laminates (APL). Previous work indicates that opposing lamellar orientation is necessary for development of near native uniaxial tensile properties. However, most native AF tensile loads are applied biaxially, as the disk is subjected to multi-axial loads and is constrained by its attachments to the vertebral bodies. Thus, the objective of this study was to evaluate the biaxial mechanical response of engineered AF bilayers, and to determine the importance of opposing lamellar structure under this loading regime. Opposing bilayers, which replicate native AF structure, showed a significantly higher modulus in both testing directions compared to parallel bilayers, and reached ∼60% of native AF biaxial properties. Associated with this increase in biaxial properties, significantly less shear, and significantly higher stretch in the fiber direction, was observed. These results provide additional insight into native tissue structure-function relationships, as well as new benchmarks for engineering functional AF tissue constructs. Copyright © 2013 Orthopaedic Research Society.

  7. Fibrin-genipin adhesive hydrogel for annulus fibrosus repair: performance evaluation with large animal organ culture, in situ biomechanics, and in vivo degradation tests

    Directory of Open Access Journals (Sweden)

    M Likhitpanichkul


    Full Text Available Annulus fibrosus (AF defects from annular tears, herniation, and discectomy procedures are associated with painful conditions and accelerated intervertebral disc (IVD degeneration. Currently, no effective treatments exist to repair AF damage, restore IVD biomechanics and promote tissue regeneration. An injectable fibrin-genipin adhesive hydrogel (Fib-Gen was evaluated for its performance repairing large AF defects in a bovine caudal IVD model using ex vivo organ culture and biomechanical testing of motion segments, and for its in vivo longevity and biocompatibility in a rat model by subcutaneous implantation. Fib-Gen sealed AF defects, prevented IVD height loss, and remained well-integrated with native AF tissue following approximately 14,000 cycles of compression in 6-day organ culture experiments. Fib-Gen repair also retained high viability of native AF cells near the repair site, reduced nitric oxide released to the media, and showed evidence of AF cell migration into the gel. Biomechanically, Fib-Gen fully restored compressive stiffness to intact levels validating organ culture findings. However, only partial restoration of tensile and torsional stiffness was obtained, suggesting opportunities to enhance this formulation. Subcutaneous implantation results, when compared with the literature, suggested Fib-Gen exhibited similar biocompatibility behaviour to fibrin alone but degraded much more slowly. We conclude that injectable Fib-Gen successfully sealed large AF defects, promoted functional restoration with improved motion segment biomechanics, and served as a biocompatible adhesive biomaterial that had greatly enhanced in vivo longevity compared to fibrin. Fib-Gen offers promise for AF repairs that may prevent painful conditions and accelerated degeneration of the IVD, and warrants further material development and evaluation.

  8. Closure of the annulus fibrosus of the intervertebral disc using a novel suture application device-in vivo porcine and ex vivo biomechanical evaluation. (United States)

    Bateman, Antony H; Balkovec, Christian; Akens, Margarete K; Chan, Andrea H W; Harrison, Robert D; Oakden, Wendy; Yee, Albert J M; McGill, Stuart M


    Defects in the annulus fibrosus (AF) remain a challenge in the surgical treatment of lumbar disc herniations with persistent defects, allowing potential re herniation of nucleus pulposus (NP) tissue. A cervical porcine model was chosen to simulate human lumbar intervertebral disc (IVD). The aim of this study was to determine the technical feasibility of closure of the AF of the IVD using a novel minimally invasive Kerrison-shaped suture application device. Ex vivo biomechanical and in vivo porcine device evaluations were performed. Ex vivo biomechanical evaluation: 15 porcine spinal units were explanted and subjected to mock discectomy. The annular defect was closed using 2-0 non-absorbable (ultra-high molecular-weight polyethylene, UHMWPE) suture and Dines knot. The knot was backed up with two, three, or four throws. The spinal unit was subject to 4000 cycles of flexion/extension with 1500 N of axial load, and assessed for knot slippage. In vivo porcine device evaluation: three pigs (53-57 kg) were anesthetized and underwent a ventral surgical approach to the cervical spine. The AF of two discs was incised, and simulated partial NP discectomy was performed. The defect was closed at one level using the AnchorKnot device to apply the suture with a Dines knot and four throws. The pigs were observed for 4 weeks before euthanasia, allowing 7T magnetic resonance imaging (MRI) and histological evaluation. A Dines knot with four throws experienced no slippage after 4000 cycles. This configuration was tested in vivo. Clinically, the neurological examination in treated pigs was normal following surgery. Histological and MRI assessment confirmed sustained defect closure at 4 weeks. There was no reaction to the suture material and no NP extrusion at any of the sutured levels. This study demonstrates that it is technically feasible to perform AF defect closure in a porcine model. This novel device achieved AF defect closure that was maintained through 4 weeks in vivo

  9. [Prediction of round window visibility in cochlear implantation with temporal bone high resolution computed tomography]. (United States)

    Sun, S P; Lu, W; Lei, Y B; Men, X M; Zuo, B; Ding, S G


    Objective: To discuss the prediction of round window(RW) visibility in cochlear implantation(CI) with temporal bone high resolution computed tomography(HRCT). Methods: From January 2013 to January 2017, 130 cases underwent both HRCT and CI in our hospital were analyzed. The distance from facial nerve to posterior canal wall(FWD), the angle between facial nerve and inner margin of round window(FRA), and the angle between facial nerve and tympanic anulus to inner margin of round window(FRAA) were detected at the level of round window on axial temporal bone HRCT. A line parallel to the posterior wall of ear canal was drawn from the anterior wall of facial nerve at the level of round window on axial temporal bone HRCT and its relationship with round window was detected (facial-round window line, FRL): type0-posterior to the round window, type1-between the round window, type2-anterior to the round window. Their(FWD, FRA, FRAA, FRL) relationships with intra-operative round window visibility were analyzed by SPSS 17.0 software. Results: FWD( F =18.76, P =0.00), FRA( F =34.57, P =0.00), FRAA ( F =14.24, P =0.00) could affect the intra-operative RW visibility significantly. RW could be exposed completely during CI when preoperative HRCT showing type0 FRL. RW might be partly exposed and not exposed when preoperative HRCT showing type1 and type2 FRL respectively. Conclusion: FWD, FRA, FRAA and FRL of temporal bone HRCT can predict intra-operative round window visibility effectively in CI surgery.

  10. Comparison of transcatheter laser and direct-current shock ablation of endocardium near tricuspid anulus (United States)

    Zhang, Yu-Zhen; Wang, Shi-Wen; Li, Junheng


    Forty to eighty percent of the patients with accessory pathways (APs) manifest themselves by tachyarrhythmias. Many of these patients needed either life-long medical therapy or surgery. In order to avoid the discomfort and expenses in surgical procedures, closed chest percutaneous catheter ablation of APs became a potentially desirable therapeutic approach. Many investigations indicated that ablation of right APs by transcatheter direct current (dc) shock could cause life-threatening arrhythmias, right coronary arterical (RCA) spasm, etc. With the development of transcatheter laser technique, it has been used in drug-incurable arrhythmias. The results show that laser ablation is much safer than surgery and electric shock therapy. The purpose of this study is to explore the effectiveness, advantages, and complications with transcatheter Nd:YAG laser and dc shock in the ablation of right atrioventricular accessory pathways in the atrium near the tricuspid annulus (TA) in 20 dogs.

  11. ENSO Prediction and Predictability (United States)

    Cane, M. A.


    In 1986 there was one dynamical forecasting model for ENSO and a small handful of statistical and hybrid schemes. Now there are more than 40 models in the IRI-CPC forecast plume, many of them coupled GCMs. Why hasn't forecasting improved more in 30 years? In a 1982 landmark paper, Rasmussen and Carpenter created the canonical El Niño, transforming the inchoate view of the time. Now much research is focuses on ENSO diversity. Is our understanding deeper for this? Has this work properly incorporated the ENSO life cycle of the canonical event? Some eras are more predictable than others. Why? Is it random, or is there a systematic difference in background state? Do we have any idea how predictable ENSO is? Why is the ENSO band 2-7 years? What will become of ENSO in the next century?

  12. WALS Prediction

    NARCIS (Netherlands)

    Magnus, J.R.; Wang, W.; Zhang, Xinyu


    Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty

  13. Predictive Testing (United States)

    ... you want to learn. Search form Search Predictive testing You are here Home Testing & Services Testing for ... you make the decision. What Is Predictive Genetic Testing Predictive genetic testing searches for genetic changes, or ...

  14. Climate prediction and predictability (United States)

    Allen, Myles


    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the project, running multiple versions of climate models on personal computers.

  15. Earthquake prediction

    International Nuclear Information System (INIS)

    Ward, P.L.


    The state of the art of earthquake prediction is summarized, the possible responses to such prediction are examined, and some needs in the present prediction program and in research related to use of this new technology are reviewed. Three basic aspects of earthquake prediction are discussed: location of the areas where large earthquakes are most likely to occur, observation within these areas of measurable changes (earthquake precursors) and determination of the area and time over which the earthquake will occur, and development of models of the earthquake source in order to interpret the precursors reliably. 6 figures

  16. Predictive medicine

    NARCIS (Netherlands)

    Boenink, Marianne; ten Have, Henk


    In the last part of the twentieth century, predictive medicine has gained currency as an important ideal in biomedical research and health care. Research in the genetic and molecular basis of disease suggested that the insights gained might be used to develop tests that predict the future health

  17. Proinflammatory cytokine expression profile in degenerated and herniated human intervertebral disc tissues. (United States)

    Shamji, Mohammed F; Setton, Lori A; Jarvis, Wingrove; So, Stephen; Chen, Jun; Jing, Liufang; Bullock, Robert; Isaacs, Robert E; Brown, Christopher; Richardson, William J


    Prior reports document macrophage and lymphocyte infiltration with proinflammatory cytokine expression in pathologic intervertebral disc (IVD) tissues. Nevertheless, the role of the Th17 lymphocyte lineage in mediating disc disease remains uninvestigated. We undertook this study to evaluate the immunophenotype of pathologic IVD specimens, including interleukin-17 (IL-17) expression, from surgically obtained IVD tissue and from nondegenerated autopsy control tissue. Surgical IVD tissues were procured from patients with degenerative disc disease (n = 25) or herniated IVDs (n = 12); nondegenerated autopsy control tissue was also obtained (n = 8) from the anulus fibrosus and nucleus pulposus regions. Immunohistochemistry was performed for cell surface antigens (CD68 for macrophages, CD4 for lymphocytes) and various cytokines, with differences in cellularity and target immunoreactivity scores analyzed between surgical tissue groups and between autopsy control tissue regions. Immunoreactivity for IL-4, IL-6, IL-12, and interferon-gamma (IFNgamma) was modest in surgical IVD tissue, although expression was higher in herniated IVD samples and virtually nonexistent in control samples. The Th17 lymphocyte product IL-17 was present in >70% of surgical tissue fields, and among control samples was detected rarely in anulus fibrosus regions and modestly in nucleus pulposus regions. Macrophages were prevalent in surgical tissues, particularly herniated IVD samples, and lymphocytes were expectedly scarce. Control tissue revealed lesser infiltration by macrophages and a near absence of lymphocytes. Greater IFNgamma positivity, macrophage presence, and cellularity in herniated IVDs suggests a pattern of Th1 lymphocyte activation in this pathology. Remarkable pathologic IVD tissue expression of IL-17 is a novel finding that contrasts markedly with low levels of IL-17 in autopsy control tissue. These findings suggest involvement of Th17 lymphocytes in the pathomechanism of disc

  18. Prediction Markets

    DEFF Research Database (Denmark)

    Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael


    In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...... works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results...

  19. Genetic Prediction. (United States)

    Turkheimer, Eric


    The fundamental reason that the genetics of behavior has remained so controversial for so long is that the layer of theory between data and their interpretation is thicker and more opaque than in more established areas of science. The finding that variations in tiny snippets of DNA have small but detectable relations to variation in behavior surprises no one, at least no one who was paying attention to the twin studies. How such snippets of DNA are related to differences in behavior-known as the gene-to-behavior pathway-is the great theoretical problem of modern behavioral genetics. Given that intentional human breeding is a horrific prospect, what kind of technology might we want (or fear) out of human behavioral genetics? One possibility is a technology that could predict important behavioral characteristics of humans based on their genomes alone. A moment's thought suggests significant benefits and risks that might be associated with such a possibility, but for the moment, just consider how convincing it would be if on the day of a baby's birth we could make meaningful predictions about whether he or she would become a concert pianist or an alcoholic. This article will consider where we are right now as regards that possibility, using human height and intelligence as the primary examples. © 2015 The Hastings Center.

  20. Diagnostics and therapy of spinal disc herniation; Diagnostik und Therapie des Bandscheibenvorfalls

    Energy Technology Data Exchange (ETDEWEB)

    Zimmer, A.; Reith, W. [Universitaetsklinikum des Saarlandes, Klinik fuer Diagnostische und Interventionelle Neuroradiologie, Homburg/Saar (Germany)


    Degenerative processes in a movement segment of the vertebral column, which can potentially give rise to herniation of elements of the nucleus pulposus, are complex and of variable clinical and radiological dimensions; however the mere assumption that degenerative changes precede disc herniation remains a matter of debate. By definition, spinal disc herniation (SDH) refers to components of the gelatinous nucleus pulposus protruding beyond the dorsal level of the vertebral body margin through tears in the annulus fibrosus. Clinical presentation may include pain, paresis and sensory disturbances. Magnetic resonance imaging (MRI) is considered the gold standard in the diagnosis of SDH. In the majority of patients a conservative approach with physical therapy exercises and adequate analgesic and antiphlogistic medical treatment results in a substantial improvement of symptoms. (orig.) [German] Degenerative Prozesse eines Bewegungssegments, die in einem Prolaps des Nucleus pulposus resultieren koennen, sind vielschichtig und von unterschiedlicher klinischer und radiologischer Auspraegung. Selbst die Annahme, dass Bandscheibenvorfaellen eine Degeneration vorangeht, ist keineswegs unumstritten. Definitionsgemaess spricht man von einem Bandscheibenvorfall (BSV), wenn das Gewebe des gelatinoesen Nucleus pulposus durch eine Dehiszenz im Anulus fibrosus ueber das Niveau der normalen dorsalen Begrenzung des Bandscheibenfachs hinaus prolabiert. Klinisch kann dies mit Schmerzen, Paresen und Sensibilitaetsstoerungen einhergehen. Die Magnetresonanztomographie gilt als Goldstandard in der Diagnostik eines BSV. In der Mehrzahl der Faelle fuehrt ein konservatives Vorgehen zu einer deutlichen Besserung der Symptomatik im Verlauf. (orig.)

  1. Predictable Medea

    Directory of Open Access Journals (Sweden)

    Elisabetta Bertolino


    Full Text Available By focusing on the tragedy of the 'unpredictable' infanticide perpetrated by Medea, the paper speculates on the possibility of a non-violent ontological subjectivity for women victims of gendered violence and whether it is possible to respond to violent actions in non-violent ways; it argues that Medea did not act in an unpredictable way, rather through the very predictable subject of resentment and violence. 'Medea' represents the story of all of us who require justice as retribution against any wrong. The presupposition is that the empowered female subjectivity of women’s rights contains the same desire of mastering others of the masculine current legal and philosophical subject. The subject of women’s rights is grounded on the emotions of resentment and retribution and refuses the categories of the private by appropriating those of the righteous, masculine and public subject. The essay opposes the essentialised stereotypes of the feminine and the maternal with an ontological approach of people as singular, corporeal, vulnerable and dependent. There is therefore an emphasis on the excluded categories of the private. Forgiveness is taken into account as a category of the private and a possibility of responding to violence with newness. A violent act is seen in relations to the community of human beings rather than through an isolated setting as in the case of the individual of human rights. In this context, forgiveness allows to risk again and being with. The result is also a rethinking of feminist actions, feminine subjectivity and of the maternal. Overall the paper opens up the Arendtian category of action and forgiveness and the Cavarerian unique and corporeal ontology of the selfhood beyond gendered stereotypes.

  2. Predictable earthquakes? (United States)

    Martini, D.


    acceleration) and global number of earthquake for this period from published literature which give us a great picture about the dynamical geophysical phenomena. Methodology: The computing of linear correlation coefficients gives us a chance to quantitatively characterise the relation among the data series, if we suppose a linear dependence in the first step. The correlation coefficients among the Earth's rotational acceleration and Z-orbit acceleration (perpendicular to the ecliptic plane) and the global number of the earthquakes were compared. The results clearly demonstrate the common feature of both the Earth's rotation and Earth's Z-acceleration around the Sun and also between the Earth's rotational acceleration and the earthquake number. This fact might means a strong relation among these phenomena. The mentioned rather strong correlation (r = 0.75) and the 29 year period (Saturn's synodic period) was clearly shown in the counted cross correlation function, which gives the dynamical characteristic of correlation, of Earth's orbital- (Z-direction) and rotational acceleration. This basic period (29 year) was also obvious in the earthquake number data sets with clear common features in time. Conclusion: The Core, which involves the secular variation of the Earth's magnetic field, is the only sufficiently mobile part of the Earth with a sufficient mass to modify the rotation which probably effects on the global time distribution of the earthquakes. Therefore it might means that the secular variation of the earthquakes is inseparable from the changes in Earth's magnetic field, i.e. the interior process of the Earth's core belongs to the dynamical state of the solar system. Therefore if the described idea is real the global distribution of the earthquakes in time is predictable.

  3. Making detailed predictions makes (some) predictions worse (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  4. PREDICT: Satellite tracking and orbital prediction (United States)

    Magliacane, John A.


    PREDICT is an open-source, multi-user satellite tracking and orbital prediction program written under the Linux operating system. PREDICT provides real-time satellite tracking and orbital prediction information to users and client applications through: the system console the command line a network socket the generation of audio speechData such as a spacecraft's sub-satellite point, azimuth and elevation headings, Doppler shift, path loss, slant range, orbital altitude, orbital velocity, footprint diameter, orbital phase (mean anomaly), squint angle, eclipse depth, the time and date of the next AOS (or LOS of the current pass), orbit number, and sunlight and visibility information are provided on a real-time basis. PREDICT can also track (or predict the position of) the Sun and Moon. PREDICT has the ability to control AZ/EL antenna rotators to maintain accurate orientation in the direction of communication satellites. As an aid in locating and tracking satellites through optical means, PREDICT can articulate tracking coordinates and visibility information as plain speech.

  5. Predictive modeling of complications. (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P


    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  6. Predicting outdoor sound

    CERN Document Server

    Attenborough, Keith; Horoshenkov, Kirill


    1. Introduction  2. The Propagation of Sound Near Ground Surfaces in a Homogeneous Medium  3. Predicting the Acoustical Properties of Outdoor Ground Surfaces  4. Measurements of the Acoustical Properties of Ground Surfaces and Comparisons with Models  5. Predicting Effects of Source Characteristics on Outdoor Sound  6. Predictions, Approximations and Empirical Results for Ground Effect Excluding Meteorological Effects  7. Influence of Source Motion on Ground Effect and Diffraction  8. Predicting Effects of Mixed Impedance Ground  9. Predicting the Performance of Outdoor Noise Barriers  10. Predicting Effects of Vegetation, Trees and Turbulence  11. Analytical Approximations including Ground Effect, Refraction and Turbulence  12. Prediction Schemes  13. Predicting Sound in an Urban Environment.

  7. The occurrence and regional distribution of DR4 on herniated disc cells: a potential apoptosis pathway in lumbar intervertebral disc. (United States)

    Zhang, Liang; Niu, Tao; Yang, Shang-You; Lu, Zhenhua; Chen, Bohua


    Intervertebral discs surgically obtained from 60 herniated patients and 5 normal individuals were examined to correlate the regional distribution of DR4-receptor and apoptosis. To explore the role of a tumor necrosis factor superfamily member DR4 and the TRAIL/DR4 mediated apoptosis in the human lumbar intervertebral disc. The pathogenesis of lumbar degenerative intervertebral discs remains not completely understood. In herniated lumbar disc tissues, increased apoptosis and higher expression of Fas/Fas ligand and caspase-3 have been reported, suggesting a pivotal role of apoptotic mechanisms in intervertebral disc degeneration. However, it is not clear that apoptosis mediators such as TRAIL and Death Receptor 4 (DR4), which often represent different apoptosis signal pathways, contribute to the apoptosis process during the development of the degenerated intervertebral discs. Apoptosis was determined by poly(ADP-ribose) polymerase (PARP) p85 immunohistochemistry. Expression of DR4 was revealed by immunohistochemistry analysis. Statistical difference among groups was analyzed using one-way ANOVA with LSD post hoc multiple comparisons and the bivariate correlations. Apoptotic cells were detected in the nucleus pulposus and anulus fibrosus of all samples. However, the number of apoptotic cells was significantly higher in the nucleus compared with the anulus. Further, there were significantly more apoptotic cells in the herniated discs compared with the normal discs. Within herniated discs, a remarkably higher percentage of positive staining cells were detected in the uncontained discs than the contained ones. Strong expression of DR4 was detected in all samples of degenerative herniated discs, whereasmuch weaker expression was sporadically identified in normal discs. In addition, the prevalence of apoptosis positively correlated with the severity of disc degeneration. The concomitant increase of DR4 expression in the regions of heavy apoptotic cell aggregation suggests

  8. Applied predictive control

    CERN Document Server

    Sunan, Huang; Heng, Lee Tong


    The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

  9. Predictable or not predictable? The MOV question

    International Nuclear Information System (INIS)

    Thibault, C.L.; Matzkiw, J.N.; Anderson, J.W.; Kessler, D.W.


    Over the past 8 years, the nuclear industry has struggled to understand the dynamic phenomena experienced during motor-operated valve (MOV) operation under differing flow conditions. For some valves and designs, their operational functionality has been found to be predictable; for others, unpredictable. Although much has been accomplished over this period of time, especially on modeling valve dynamics, the unpredictability of many valves and designs still exists. A few valve manufacturers are focusing on improving design and fabrication techniques to enhance product reliability and predictability. However, this approach does not address these issues for installed and inpredictable valves. This paper presents some of the more promising techniques that Wyle Laboratories has explored with potential for transforming unpredictable valves to predictable valves and for retrofitting installed MOVs. These techniques include optimized valve tolerancing, surrogated material evaluation, and enhanced surface treatments

  10. [Prediction in cerebrovascular diseases]. (United States)

    Hamann, G F


    Prediction of the outcome of cerebrovascular diseases or of the effects and complications of various forms of treatment are essential components of all stroke treatment regimens. This review focuses on the prediction of the stroke risk in primary prevention, the prediction of the risk of secondary stroke following a transient ischemic attack (TIA), the estimation of the outcome following manifest stroke and the treatment effects, the prediction of secondary cerebrovascular events and the prediction of vascular cognitive impairment following stroke. All predictive activities in cerebrovascular disease are hindered by the translation of predictive results from studies and patient populations to the individual patient. Future efforts in genetic analyses may be able to overcome this barrier and to enable individual prediction in the area of so-called personalized medicine. In all the various fields of prediction in cerebrovascular diseases, three major variables are always important: age of the patient, severity and subtype of the stroke. Increasing age, more severe stroke symptoms and the cardioembolic stroke subtype predict a poor outcome regarding both survival and permanent disability. This finding is somewhat banal and will therefore never replace the well experienced clinician judging the chances of a patient and taking into account the personal situation of this patient, e.g. for initiation of a rehabilitation program. Besides the individualized prediction, in times of restricted economic resources and increasing tendency to clarify questions of medical treatment in court, it seems unavoidable to use prediction in economic and medicolegal interaction with clinical medicine. This tendency will be accompanied by difficult ethical problems which neurologists must be aware of. Improved prediction should not be used to allocate or restrict resources or to restrict medically indicated treatment.

  11. Predictive systems ecology. (United States)

    Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G


    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

  12. Solar Cycle Predictions (United States)

    Pesnell, William Dean


    Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

  13. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin


    Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only...... compare the worst-case execution time bounds of different architectures....

  14. Archaeological predictive model set. (United States)


    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  15. Seismology for rockburst prediction.

    CSIR Research Space (South Africa)

    De Beer, W


    Full Text Available . . . . . . . . . . . . . . . . . . . . . . . . 9 Time to failure prediction algorithm . . . . . . . . . . . . . . . 9 3.1.4 Testing for deterministic components of time series of interest, noise reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3... component of seismic time series, noise reduction and limits of predictability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 A3.1 False nearest strands...

  16. The Prediction Value

    NARCIS (Netherlands)

    Koster, M.; Kurz, S.; Lindner, I.; Napel, S.


    We introduce the prediction value (PV) as a measure of players’ informational importance in probabilistic TU games. The latter combine a standard TU game and a probability distribution over the set of coalitions. Player i’s prediction value equals the difference between the conditional expectations

  17. Predicting AD conversion

    DEFF Research Database (Denmark)

    Liu, Yawu; Mattila, Jussi; Ruiz, Miguel �ngel Mu�oz


    To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI...

  18. Predictability of Stock Returns

    Directory of Open Access Journals (Sweden)

    Ahmet Sekreter


    Full Text Available Predictability of stock returns has been shown by empirical studies over time. This article collects the most important theories on forecasting stock returns and investigates the factors that affecting behavior of the stocks’ prices and the market as a whole. Estimation of the factors and the way of estimation are the key issues of predictability of stock returns.

  19. 'Red Flag' Predictions

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    -generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external...

  20. Cultural Resource Predictive Modeling (United States)


    refining formal, inductive predictive models is the quality of the archaeological and environmental data. To build models efficiently, relevant...geomorphology, and historic information . Lessons Learned: The original model was focused on the identification of prehistoric resources. This...system but uses predictive modeling informally . For example, there is no probability for buried archaeological deposits on the Burton Mesa, but there is

  1. Protein Sorting Prediction

    DEFF Research Database (Denmark)

    Nielsen, Henrik


    Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global-property-based and homology-based prediction. In this chapter, the strengths...

  2. Predicting occupational lung diseases

    NARCIS (Netherlands)

    Suarthana, E.


    This thesis aims at demonstrating the development, validation, and application of prediction models for occupational lung diseases. Prediction models are developed to estimate an individual’s probability of the presence or future likelihood of occurrence of an outcome (i.e. disease of interest or

  3. Predicting protein structure classes from function predictions

    DEFF Research Database (Denmark)

    Sommer, I.; Rahnenfuhrer, J.; de Lichtenberg, Ulrik


    membership. Even for structural families of small size, family members receive significantly higher scores. For some examples, we show that the relevant functional features identified by this method are biologically meaningful. The proposed approach can be used to improve existing sequence......We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories; for given...... query sequences these probabilities are obtained by a neural net that has previously been trained on a variety of functionally important features. On a training set of sequences we assess the relevance of individual functional categories for identifying a given structural family. Using a combination...

  4. Evaluating prediction uncertainty

    International Nuclear Information System (INIS)

    McKay, M.D.


    The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented

  5. Ground motion predictions

    International Nuclear Information System (INIS)

    Loux, P.C.


    Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

  6. Structural prediction in aphasia

    Directory of Open Access Journals (Sweden)

    Tessa Warren


    Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

  7. Prediction of bull fertility. (United States)

    Utt, Matthew D


    Prediction of male fertility is an often sought-after endeavor for many species of domestic animals. This review will primarily focus on providing some examples of dependent and independent variables to stimulate thought about the approach and methodology of identifying the most appropriate of those variables to predict bull (bovine) fertility. Although the list of variables will continue to grow with advancements in science, the principles behind making predictions will likely not change significantly. The basic principle of prediction requires identifying a dependent variable that is an estimate of fertility and an independent variable or variables that may be useful in predicting the fertility estimate. Fertility estimates vary in which parts of the process leading to conception that they infer about and the amount of variation that influences the estimate and the uncertainty thereof. The list of potential independent variables can be divided into competence of sperm based on their performance in bioassays or direct measurement of sperm attributes. A good prediction will use a sample population of bulls that is representative of the population to which an inference will be made. Both dependent and independent variables should have a dynamic range in their values. Careful selection of independent variables includes reasonable measurement repeatability and minimal correlation among variables. Proper estimation and having an appreciation of the degree of uncertainty of dependent and independent variables are crucial for using predictions to make decisions regarding bull fertility. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Bootstrap prediction and Bayesian prediction under misspecified models


    Fushiki, Tadayoshi


    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  9. Wind power prediction models (United States)

    Levy, R.; Mcginness, H.


    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  10. Predictable return distributions

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard

    This paper provides detailed insights into predictability of the entire stock and bond return distribution through the use of quantile regression. This allows us to examine speci…c parts of the return distribution such as the tails or the center, and for a suf…ciently …ne grid of quantiles we can...... trace out the entire distribution. A univariate quantile regression model is used to examine stock and bond return distributions individually, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that certain parts of the return distributions...... are predictable as a function of economic state variables. The results are, however, very different for stocks and bonds. The state variables primarily predict only location shifts in the stock return distribution, while they also predict changes in higher-order moments in the bond return distribution. Out...

  11. Methane prediction in collieries

    CSIR Research Space (South Africa)

    Creedy, DP


    Full Text Available The primary aim of the project was to assess the current status of research on methane emission prediction for collieries in South Africa in comparison with methods used and advances achieved elsewhere in the world....

  12. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D


    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribute...... to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from Illumina....... Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  13. CMAQ predicted concentration files (United States)

    U.S. Environmental Protection Agency — CMAQ predicted ozone. This dataset is associated with the following publication: Gantt, B., G. Sarwar, J. Xing, H. Simon, D. Schwede, B. Hutzell, R. Mathur, and A....

  14. CMAQ predicted concentration files (United States)

    U.S. Environmental Protection Agency — model predicted concentrations. This dataset is associated with the following publication: Muñiz-Unamunzaga, M., R. Borge, G. Sarwar, B. Gantt, D. de la Paz, C....

  15. Stuck pipe prediction

    KAUST Repository

    Alzahrani, Majed


    Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

  16. Genomic prediction using subsampling


    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin


    Background Genome-wide assisted selection is a critical tool for the?genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each rou...

  17. Predicting Ideological Prejudice


    Brandt, Mark J.


    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants? ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions for this association. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship...

  18. Predicting Ideological Prejudice


    Brandt, Mark


    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants’ ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship was developed with a...

  19. Predicting ideological prejudice


    Brandt, M.J.


    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants’ ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions for this association. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship...

  20. Multimodal Emoji Prediction


    Barbieri, Francesco; Ballesteros, Miguel; Ronzano, Francesco; Saggion, Horacio


    Emojis are small images that are commonly included in social media text messages. The combination of visual and textual content in the same message builds up a modern way of communication, that automatic systems are not used to deal with. In this paper we extend recent advances in emoji prediction by putting forward a multimodal approach that is able to predict emojis in Instagram posts. Instagram posts are composed of pictures together with texts which sometimes include emojis. We show that ...

  1. Genomic prediction using subsampling. (United States)

    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin


    Genome-wide assisted selection is a critical tool for the genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each round of a Markov Chain Monte Carlo. We evaluated the effect of subsampling bootstrap on prediction and computational parameters. Across datasets, we observed an optimal subsampling proportion of observations around 50% with replacement, and around 33% without replacement. Subsampling provided a substantial decrease in computation time, reducing the time to fit the model by half. On average, losses on predictive properties imposed by subsampling were negligible, usually below 1%. For each dataset, an optimal subsampling point that improves prediction properties was observed, but the improvements were also negligible. Combining subsampling with Gibbs sampling is an interesting ensemble algorithm. The investigation indicates that the subsampling bootstrap Markov chain algorithm substantially reduces computational burden associated with model fitting, and it may slightly enhance prediction properties.

  2. Empirical ground motion prediction

    Directory of Open Access Journals (Sweden)

    R. J. Archuleta


    Full Text Available New methods of site-specific ground motion prediction in the time and frequency domains are presented. A large earthquake is simulated as a composite (linear combination of observed small earthquakes (subevents assuming Aki-Brune functional models of the source time functions (spectra. Source models incorporate basic scaling relations between source and spectral parameters. Ground motion predictions are consistent with the entire observed seismic spectrum from the lowest to the highest frequencies. These methods are designed to use all the available empirical Green’s functions (or any subset of observations at a site. Thus a prediction is not biased by a single record, and different possible source-receiver paths are taken into account. Directivity is accounted for by adjusting the apparent source duration at each site. Our time-series prediction algorithm is based on determination of a non-uniform distribution of rupture times of subevents. By introducing a specific rupture velocity we avoid the major problem of deficiency of predictions around the main event's corner frequency. A novel notion of partial coherence allows us to sum subevents' amplitude spectra directly without using any information on their rupture times and phase histories. Predictions by this spectral method are not Jependent on details of rupture nucleation and propagation, location of asperities and other predominantly phase-affecting factors, responsible for uncertainties in time-domain simulations.

  3. Deep Visual Attention Prediction (United States)

    Wang, Wenguan; Shen, Jianbing


    In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

  4. Predictability of geomagnetic series

    Directory of Open Access Journals (Sweden)

    E. Bellanger

    Full Text Available The aim of this paper is to lead a practical, rational and rigorous approach concerning what can be done, based on the knowledge of magnetic series, in the field of prediction of the extreme geomagnetic events. We compare the magnetic vector differential at different locations computed with different resolutions, from an entire day to minutes. We study the classical correlations and the simplest possible prediction scheme to conclude a high level of predictability of the magnetic vector variation. The results obtained are far from a random guessing: the error diagrams are either comparable with earthquake prediction studies or out-perform them when the minute sampling is used in accounting for hourly magnetic vector variation. We demonstrate how the magnetic extreme events can be predicted from the hourly value of the magnetic variation with a lead time of several hours. We compute the 2-D empirical distribution of consecutive values of the magnetic vector variation for the estimation of conditional probabilities of different types. The achieved results encourage further development of the approach to prediction of the extreme geomagnetic events.

    Key words. Ionosphere (modeling and forecasting – Magnetospheric physics (storms and substorms

  5. Cytomics in predictive medicine (United States)

    Tarnok, Attila; Valet, Guenther K.


    Predictive Medicine aims at the detection of changes in patient's disease state prior to the manifestation of deterioration or improvement of the current status. Patient-specific, disease-course predictions with >95% or >99% accuracy during therapy would be highly valuable for everyday medicine. If these predictors were available, disease aggravation or progression, frequently accompanied by irreversible tissue damage or therapeutic side effects, could then potentially be avoided by early preventive therapy. The molecular analysis of heterogeneous cellular systems (Cytomics) by cytometry in conjunction with pattern-oriented bioinformatic analysis of the multiparametric cytometric and other data provides a promising approach to individualized or personalized medical treatment or disease management. Predictive medicine is best implemented by cell oriented measurements e.g. by flow or image cytometry. Cell oriented gene or protein arrays as well as bead arrays for the capture of solute molecules form serum, plasma, urine or liquor are equally of high value. Clinical applications of predictive medicine by Cytomics will include multi organ failure in sepsis or non infectious posttraumatic shock in intensive care, or the pretherapeutic identification of high risk patients in cancer cytostatic. Early individualized therapy may provide better survival chances for individual patient at concomitant cost containment. Predictive medicine guided early reduction or stop of therapy may lower or abrogate potential therapeutic side effects. Further important aspects of predictive medicine concern the preoperative identification of patients with a tendency for postoperative complications or coronary artery disease patients with an increased tendency for restenosis. As a consequence, better patient care and new forms of inductive scientific hypothesis development based on the interpretation of predictive data patterns are at reach.

  6. Transionospheric propagation predictions (United States)

    Klobucher, J. A.; Basu, S.; Basu, S.; Bernhardt, P. A.; Davies, K.; Donatelli, D. E.; Fremouw, E. J.; Goodman, J. M.; Hartmann, G. K.; Leitinger, R.


    The current status and future prospects of the capability to make transionospheric propagation predictions are addressed, highlighting the effects of the ionized media, which dominate for frequencies below 1 to 3 GHz, depending upon the state of the ionosphere and the elevation angle through the Earth-space path. The primary concerns are the predictions of time delay of signal modulation (group path delay) and of radio wave scintillation. Progress in these areas is strongly tied to knowledge of variable structures in the ionosphere ranging from the large scale (thousands of kilometers in horizontal extent) to the fine scale (kilometer size). Ionospheric variability and the relative importance of various mechanisms responsible for the time histories observed in total electron content (TEC), proportional to signal group delay, and in irregularity formation are discussed in terms of capability to make both short and long term predictions. The data base upon which predictions are made is examined for its adequacy, and the prospects for prediction improvements by more theoretical studies as well as by increasing the available statistical data base are examined.

  7. Tide Predictions, California, 2014, NOAA (United States)

    U.S. Environmental Protection Agency — The predictions from the web based NOAA Tide Predictions are based upon the latest information available as of the date of the user's request. Tide predictions...

  8. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)


    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  9. Predicting tile drainage discharge

    DEFF Research Database (Denmark)

    Iversen, Bo Vangsø; Kjærgaard, Charlotte; Petersen, Rasmus Jes

    More than 50 % of Danish agricultural areas are expected to be artificial tile drained. Transport of water and nutrients through the tile drain system to the aquatic environment is expected to be significant. For different mitigation strategies such as constructed wetlands an exact knowledge...... of the water load coming from the tile drainage system is therefore essential. This work aims at predicting tile drainage discharge using dynamic as well as a statistical predictive models. A large dataset of historical tile drain discharge data, daily discharge values as well as yearly average values were...... used in the analysis. For the dynamic modelling, a simple linear reservoir model was used where different outlets in the model represented tile drain as well as groundwater discharge outputs. This modelling was based on daily measured tile drain discharge values. The statistical predictive model...

  10. Predicting Ideological Prejudice. (United States)

    Brandt, Mark J


    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants' ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions for this association. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship was developed with a representative sample of Americans ( N = 4,940) and tested against models using the perceived status of and choice to belong to the target group as predictors. In four studies (total N = 2,093), ideology-prejudice associations were estimated, and these observed estimates were compared with the models' predictions. The model that was based only on perceived ideology was the most parsimonious with the smallest errors.

  11. Permeability prediction in chalks

    DEFF Research Database (Denmark)

    Alam, Mohammad Monzurul; Fabricius, Ida Lykke; Prasad, Manika


    The velocity of elastic waves is the primary datum available for acquiring information about subsurface characteristics such as lithology and porosity. Cheap and quick (spatial coverage, ease of measurement) information of permeability can be achieved, if sonic velocity is used for permeability...... prediction, so we have investigated the use of velocity data to predict permeability. The compressional velocity fromwireline logs and core plugs of the chalk reservoir in the South Arne field, North Sea, has been used for this study. We compared various methods of permeability prediction from velocities....... The relationships between permeability and porosity from core data were first examined using Kozeny’s equation. The data were analyzed for any correlations to the specific surface of the grain, Sg, and to the hydraulic property defined as the flow zone indicator (FZI). These two methods use two different approaches...

  12. Predicting the Sunspot Cycle (United States)

    Hathaway, David H.


    The 11-year sunspot cycle was discovered by an amateur astronomer in 1844. Visual and photographic observations of sunspots have been made by both amateurs and professionals over the last 400 years. These observations provide key statistical information about the sunspot cycle that do allow for predictions of future activity. However, sunspots and the sunspot cycle are magnetic in nature. For the last 100 years these magnetic measurements have been acquired and used exclusively by professional astronomers to gain new information about the nature of the solar activity cycle. Recently, magnetic dynamo models have evolved to the stage where they can assimilate past data and provide predictions. With the advent of the Internet and open data policies, amateurs now have equal access to the same data used by professionals and equal opportunities to contribute (but, alas, without pay). This talk will describe some of the more useful prediction techniques and reveal what they say about the intensity of the upcoming sunspot cycle.

  13. Predictive maintenance primer

    International Nuclear Information System (INIS)

    Flude, J.W.; Nicholas, J.R.


    This Predictive Maintenance Primer provides utility plant personnel with a single-source reference to predictive maintenance analysis methods and technologies used successfully by utilities and other industries. It is intended to be a ready reference to personnel considering starting, expanding or improving a predictive maintenance program. This Primer includes a discussion of various analysis methods and how they overlap and interrelate. Additionally, eighteen predictive maintenance technologies are discussed in sufficient detail for the user to evaluate the potential of each technology for specific applications. This document is designed to allow inclusion of additional technologies in the future. To gather the information necessary to create this initial Primer the Nuclear Maintenance Applications Center (NMAC) collected experience data from eighteen utilities plus other industry and government sources. NMAC also contacted equipment manufacturers for information pertaining to equipment utilization, maintenance, and technical specifications. The Primer includes a discussion of six methods used by analysts to study predictive maintenance data. These are: trend analysis; pattern recognition; correlation; test against limits or ranges; relative comparison data; and statistical process analysis. Following the analysis methods discussions are detailed descriptions for eighteen technologies analysts have found useful for predictive maintenance programs at power plants and other industrial facilities. Each technology subchapter has a description of the operating principles involved in the technology, a listing of plant equipment where the technology can be applied, and a general description of the monitoring equipment. Additionally, these descriptions include a discussion of results obtained from actual equipment users and preferred analysis techniques to be used on data obtained from the technology. 5 refs., 30 figs

  14. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg


    utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models.......This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish...

  15. Towards Predictive Association Theories

    DEFF Research Database (Denmark)

    Kontogeorgis, Georgios; Tsivintzelis, Ioannis; Michelsen, Michael Locht


    . We use the term predictive in two situations: (i) with no use of binary interaction parameters, and (ii) multicomponent calculations using binary interaction parameters based solely on binary data. It is shown that the CPA equation of state can satisfactorily predict CO2–water–glycols–alkanes VLE...... and water–MEG–aliphatic hydrocarbons LLE using interaction parameters obtained from the binary data alone. Moreover, it is demonstrated that the NRHB equation of state is a versatile tool which can be employed equally well to mixtures with pharmaceuticals and solvents, including mixed solvents, as well...

  16. Basis of predictive mycology. (United States)

    Dantigny, Philippe; Guilmart, Audrey; Bensoussan, Maurice


    For over 20 years, predictive microbiology focused on food-pathogenic bacteria. Few studies concerned modelling fungal development. On one hand, most of food mycologists are not familiar with modelling techniques; on the other hand, people involved in modelling are developing tools dedicated to bacteria. Therefore, there is a tendency to extend the use of models that were developed for bacteria to moulds. However, some mould specificities should be taken into account. The use of specific models for predicting germination and growth of fungi was advocated previously []. This paper provides a short review of fungal modelling studies.

  17. Linguistic Structure Prediction

    CERN Document Server

    Smith, Noah A


    A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

  18. Predicting Marital Therapy Dropouts. (United States)

    Allgood, Scot M.; Crane, D. Russell


    Attempted to predict therapy dropouts using data gathered at marital therapy intake with 474 couples seeking marital therapy who attended at least 1 session. Significant predictors of dropping out included having less than two children, having a male intake clinician, and presenting problem relating only to one spouse. (Author/ABL)

  19. Predicting Sustainable Work Behavior

    DEFF Research Database (Denmark)

    Hald, Kim Sundtoft


    Sustainable work behavior is an important issue for operations managers – it has implications for most outcomes of OM. This research explores the antecedents of sustainable work behavior. It revisits and extends the sociotechnical model developed by Brown et al. (2000) on predicting safe behavior...... condition influence their sustainable work behavior. A new definition of sustainable work behavior is proposed....

  20. Vertebral Fracture Prediction

    DEFF Research Database (Denmark)


    Vertebral Fracture Prediction A method of processing data derived from an image of at least part of a spine is provided for estimating the risk of a future fracture in vertebraeof the spine. Position data relating to at least four neighbouring vertebrae of the spine is processed. The curvature...

  1. Predicting Intrinsic Motivation (United States)

    Martens, Rob; Kirschner, Paul A.


    Intrinsic motivation can be predicted from participants' perceptions of the social environment and the task environment (Ryan & Deci, 2000)in terms of control, relatedness and competence. To determine the degree of independence of these factors 251 students in higher vocational education (physiotherapy and hotel management) indicated the…

  2. Gate valve performance prediction

    International Nuclear Information System (INIS)

    Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.


    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  3. Predicting Pilot Retention (United States)


    forever… Gig ‘Em! Dale W. Stanley III vii Table of Contents Page Acknowledgments...over the last 20 years. Airbus predicted that these trends would continue as emerging economies , especially in Asia, were creating a fast growing...US economy , pay differential and hiring by the major airlines contributed most to the decision to separate from the Air Force (Fullerton, 2003: 354

  4. Predicting coronary heart disease

    DEFF Research Database (Denmark)

    Sillesen, Henrik; Fuster, Valentin


    Atherosclerosis is the leading cause of death and disabling disease. Whereas risk factors are well known and constitute therapeutic targets, they are not useful for prediction of risk of future myocardial infarction, stroke, or death. Therefore, methods to identify atherosclerosis itself have bee...

  5. Prediction method abstracts

    Energy Technology Data Exchange (ETDEWEB)



    This conference was held December 4--8, 1994 in Asilomar, California. The purpose of this meeting was to provide a forum for exchange of state-of-the-art information concerning the prediction of protein structure. Attention if focused on the following: comparative modeling; sequence to fold assignment; and ab initio folding.

  6. Predicting visibility of aircraft. (United States)

    Watson, Andrew; Ramirez, Cesar V; Salud, Ellen


    Visual detection of aircraft by human observers is an important element of aviation safety. To assess and ensure safety, it would be useful to be able to be able to predict the visibility, to a human observer, of an aircraft of specified size, shape, distance, and coloration. Examples include assuring safe separation among aircraft and between aircraft and unmanned vehicles, design of airport control towers, and efforts to enhance or suppress the visibility of military and rescue vehicles. We have recently developed a simple metric of pattern visibility, the Spatial Standard Observer (SSO). In this report we examine whether the SSO can predict visibility of simulated aircraft images. We constructed a set of aircraft images from three-dimensional computer graphic models, and measured the luminance contrast threshold for each image from three human observers. The data were well predicted by the SSO. Finally, we show how to use the SSO to predict visibility range for aircraft of arbitrary size, shape, distance, and coloration.

  7. Predicting ideological prejudice

    NARCIS (Netherlands)

    Brandt, M.J.


    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants’ ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models

  8. Predicting Reasoning from Memory (United States)

    Heit, Evan; Hayes, Brett K.


    In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the…

  9. Steering smog prediction

    NARCIS (Netherlands)

    R. van Liere (Robert); J.J. van Wijk (Jack)


    textabstractThe use of computational steering for smog prediction is described. This application is representative for many underlying issues found in steering high performance applications: high computing times, large data sets, and many different input parameters. After a short description of the

  10. Predicting Lotto Numbers

    NARCIS (Netherlands)

    Jorgensen, C.B.; Suetens, S.; Tyran, J.R.


    We investigate the "law of small numbers" using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto

  11. The accuracy of MRI in the detection of Lumbar Disc Containment

    Directory of Open Access Journals (Sweden)

    Weiner Bradley K


    Full Text Available Abstract Background MRI has proven to be an extremely valuable tool in the assessment of normal and pathological spinal anatomy. Accordingly, it is commonly used to assess containment of discal material by the outer fibers of the anulus fibrosus and posterior longitudinal ligaments. Determination of such containment is important to determine candidacy for intradiscal techniques and has prognostic significance. The accuracy of MRI in detecting containment has been insufficiently documented. Methods The MRI's of fifty consecutive patients undergoing open lumbar microdiscectomy were prospectively evaluated for disc containment by a neuroradiologist and senior spinal surgeon using criteria available in the literature and the classification of Macnab/McCulloch. An independent surgeon then performed the surgery and documented the actual containment status using the same methods. Statistical evaluation of accuracy was undertaken. Results MRI was found to be 72% sensitive, 68% specific, and 70% accurate in detecting containment status of lumbar herniated discs. Conclusion MRI may be inaccurate in assessing containment status of lumbar disc herniations in 30% of cases. Given the importance of containment for patient selection for indirect discectomy techniques and intradiscal therapies, coupled with prognostic significance; other methods to assess containment should be employed to assess containment when such alternative interventions are being considered.

  12. [The study of the role of intervertebral disc neovascularization and immune response in the pathogenesis of lumbar discopathy]. (United States)

    Słowiński, J; Pieniazek, J; Szydlik, W; Mrówka, R; Harabin-Słowińska, M; Myrcik, G; Pinocy, E


    In adult humans moral intervertebral disc (id) is an avascular tissue and becomes so called sequestrated autoantigen. Any acquired defect of anulus fibrosus may potentially lead to contact of immunocompetent cells circulating in the blood with id antigens thus inducing autoimmune reaction. 34 patients operated on because of lumbar discopathy were studied. The id injury was divided into: a) protrusion, B) simple prolapse, c) subligamentous prolapse, d) sequester. The samples of surgically removed id were subjected to histopathological and immunohistochemical study. Presence of granulation tissue, neovascularization and humoral response (confirmed by immunopositive reaction to factor VIII and IgG) was found in decreasing pattern in the following groups: I) sequesters, 2) simple prolapses, and 3) subligamentous prolapses. Among protrusions there were only two cases positive for IgG. A negative reaction to C3bR was seen in all the groups of id. The obtained results suggest that immune reaction against lumbar id is rather an effect than a cause of its herniation.

  13. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik


    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...

  14. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Jørgensen, Claus Bjørn; Suetens, Sigrid; Tyran, Jean-Robert

    numbers based on recent drawings. While most players pick the same set of numbers week after week without regards of numbers drawn or anything else, we find that those who do change, act on average in the way predicted by the law of small numbers as formalized in recent behavioral theory. In particular......We investigate the “law of small numbers” using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto......, on average they move away from numbers that have recently been drawn, as suggested by the “gambler’s fallacy”, and move toward numbers that are on streak, i.e. have been drawn several weeks in a row, consistent with the “hot hand fallacy”....

  15. Chaos detection and predictability

    CERN Document Server

    Gottwald, Georg; Laskar, Jacques


    Distinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics.   To address these issues there exists a plethora of methods for chaos detection and predictability. The most commonly employed technique for investigating chaotic dynamics, i.e. the computation of Lyapunov exponents, however, may suffer a number of problems and drawbacks, for example when applied to noisy experimental data.   In the last two decades, several novel methods have been developed for the fast and reliable determination of the regular or chaotic nature of orbits, aimed at overcoming the shortcomings of more traditional techniques. This set of lecture notes and tutorial reviews serves as an introduction to and overview of modern chaos detection and predictability techniques for graduate students and non-specialists.   The book cover...

  16. Predicting Bankruptcy in Pakistan

    Directory of Open Access Journals (Sweden)

    Abdul RASHID


    Full Text Available This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the time period 1996-2006. Twenty four financial ratios covering four important financial attributes, namely profitability, liquidity, leverage, and turnover ratios, were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z-value below zero fall into the “bankrupt” whereas the firms with Z-value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

  17. Airframe noise prediction evaluation (United States)

    Yamamoto, Kingo J.; Donelson, Michael J.; Huang, Shumei C.; Joshi, Mahendra C.


    The objective of this study is to evaluate the accuracy and adequacy of current airframe noise prediction methods using available airframe noise measurements from tests of a narrow body transport (DC-9) and a wide body transport (DC-10) in addition to scale model test data. General features of the airframe noise from these aircraft and models are outlined. The results of the assessment of two airframe prediction methods, Fink's and Munson's methods, against flight test data of these aircraft and scale model wind tunnel test data are presented. These methods were extensively evaluated against measured data from several configurations including clean, slat deployed, landing gear-deployed, flap deployed, and landing configurations of both DC-9 and DC-10. They were also assessed against a limited number of configurations of scale models. The evaluation was conducted in terms of overall sound pressure level (OASPL), tone corrected perceived noise level (PNLT), and one-third-octave band sound pressure level (SPL).

  18. Urban pluvial flood prediction

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer


    Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events – especially in the future climate – it is valuable to be able to simulate these events numerically both...... historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper radar data observations with different spatial and temporal resolution, radar nowcasts of 0–2 h lead time, and numerical weather models with lead times up to 24 h are used as inputs...... to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on a small town Lystrup in Denmark, which has been flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps...

  19. Crystal structure and prediction. (United States)

    Thakur, Tejender S; Dubey, Ritesh; Desiraju, Gautam R


    The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

  20. Comparing Spatial Predictions

    KAUST Repository

    Hering, Amanda S.


    Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two sets of predictions, and the loss function chosen by the researcher. The test assumes only isotropy and short-range spatial dependence of the loss differential but does allow it to be non-Gaussian, non-zero-mean, and spatially correlated. Constant and nonconstant spatial trends in the loss differential are treated in two separate cases. Monte Carlo simulations illustrate the size and power properties of this test, and an example based on daily average wind speeds in Oklahoma is used for illustration. Supplemental results are available online. © 2011 American Statistical Association and the American Society for Qualitys.

  1. Essays on Earnings Predictability

    DEFF Research Database (Denmark)

    Bruun, Mark

    This dissertation addresses the prediction of corporate earnings. The thesis aims to examine whether the degree of precision in earnings forecasts can be increased by basing them on historical financial ratios. Furthermore, the intent of the dissertation is to analyze whether accounting standards...... affect the accuracy of analysts´earnings forecasts. Finally, the objective of the dissertation is to investigate how the stock market is affected by the accuracy of corporate earnings projections. The dissertation contributes to a deeper understanding of these issues. First, it is shown how earnings...... forecasts are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy...

  2. Time-predictable architectures

    CERN Document Server

    Rochange, Christine; Uhrig , Sascha


    Building computers that can be used to design embedded real-time systems is the subject of this title. Real-time embedded software requires increasingly higher performances. The authors therefore consider processors that implement advanced mechanisms such as pipelining, out-of-order execution, branch prediction, cache memories, multi-threading, multicorearchitectures, etc. The authors of this book investigate the timepredictability of such schemes.

  3. Predictive Game Theory (United States)

    Wolpert, David H.


    Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

  4. From Prediction to Process

    DEFF Research Database (Denmark)

    Nielsen, Kristian Steensen


    behavior or value-belief-norm theory), as it focuses on the dynamic psychological mechanisms that result in either success or failure in acting relative to a certain standard or goal. Similar to the intention-behavior gap, self-regulation research recognizes the occasional failure of people to adhere...... to their own environmental standards and goals. However, unlike prediction models, self-regulation research gives directions on how to reduce the frequency by which these failures occur....

  5. Are Emojis Predictable?


    Barbieri, Francesco; Ballesteros, Miguel; Saggion, Horacio


    Emojis are ideograms which are naturally combined with plain text to visually complement or condense the meaning of a message. Despite being widely used in social media, their underlying semantics have received little attention from a Natural Language Processing standpoint. In this paper, we investigate the relation between words and emojis, studying the novel task of predicting which emojis are evoked by text-based tweet messages. We train several models based on Long Short-Term Memory netwo...

  6. Predictive Systems Toxicology

    KAUST Repository

    Kiani, Narsis A.


    In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

  7. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences


    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  8. Predicting Anthracycline Benefit

    DEFF Research Database (Denmark)

    Bartlett, John M S; McConkey, Christopher C; Munro, Alison F


    PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as measu......PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite...... as measured with a centromere enumeration probe (CEP17) predicted sensitivity to anthracyclines, we report here an individual patient-level pooled analysis of data from five trials comparing anthracycline-based chemotherapy with CMF (cyclophosphamide, methotrexate, and fluorouracil) as adjuvant chemotherapy...... trials for both recurrence-free (hazard ratio, 0.64; 95% CI, 0.51 to 0.82; P = .001) and overall survival (hazard ratio, 0.66; 95% CI, 0.51 to 0.85; P = .005). CONCLUSION: This prospectively planned individual-patient pooled analysis of patient cases from five adjuvant trials confirms that patients whose...

  9. Predicting Human Cooperation.

    Directory of Open Access Journals (Sweden)

    John J Nay

    Full Text Available The Prisoner's Dilemma has been a subject of extensive research due to its importance in understanding the ever-present tension between individual self-interest and social benefit. A strictly dominant strategy in a Prisoner's Dilemma (defection, when played by both players, is mutually harmful. Repetition of the Prisoner's Dilemma can give rise to cooperation as an equilibrium, but defection is as well, and this ambiguity is difficult to resolve. The numerous behavioral experiments investigating the Prisoner's Dilemma highlight that players often cooperate, but the level of cooperation varies significantly with the specifics of the experimental predicament. We present the first computational model of human behavior in repeated Prisoner's Dilemma games that unifies the diversity of experimental observations in a systematic and quantitatively reliable manner. Our model relies on data we integrated from many experiments, comprising 168,386 individual decisions. The model is composed of two pieces: the first predicts the first-period action using solely the structural game parameters, while the second predicts dynamic actions using both game parameters and history of play. Our model is successful not merely at fitting the data, but in predicting behavior at multiple scales in experimental designs not used for calibration, using only information about the game structure. We demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation.

  10. Noncausal predictive image codec. (United States)

    Balram, N; Moura, J F


    The paper describes a lossy image codec that uses a noncausal (or bilateral) prediction model coupled with vector quantization. The noncausal prediction model is an alternative to the causal (or unilateral) model that is commonly used in differential pulse code modulation (DPCM) and other codecs with a predictive component. We show how to obtain a recursive implementation of the noncausal image model without compromising its optimality and how to apply this in coding in much the same way as a causal predictor. We report experimental compression results that demonstrate the superiority of using a noncausal model based predictor over using traditional causal predictors. The codec is shown to produce high-quality compressed images at low bit rates such as 0.375 b/pixel. This quality is contrasted with the degraded images that are produced at the same bit rates by codecs using causal predictors or standard discrete cosine transform/Joint Photographic Experts Group-based (DCT/JPEG-based) algorithms.

  11. Predictive Dynamic Digital Holography (United States)

    Sulaiman, Sennan David

    Digital holography has received recent attention for many imaging and sensing applications, including imaging through turbulent and turbid media, adaptive optics, three-dimensional projective display technology and optical tweezing. It holds several advantages over conventional imaging and wavefront sensing, chief among these being significantly fewer and simpler optical components and the retrieval of complex field. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high-energy laser systems and high-speed imaging for target tracking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing algorithms to optimize sharpness criteria. This research demonstrates real-time methods for digital holography based on approaches for optimal and adaptive identification, prediction, and control of optical wavefronts. The methods presented integrate minimum-variance wavefront prediction into dynamic digital holography schemes to accelerate the wavefront correction and image sharpening algorithms. Further gains in computational efficiency are demonstrated in this work with a variant of localized sharpening in conjunction with predictive dynamic digital holography for real-time applications. This "subspace correction" method optimizes sharpness of local regions in a detector plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a spectral plane.

  12. Predicting big bang deuterium

    Energy Technology Data Exchange (ETDEWEB)

    Hata, N.; Scherrer, R.J.; Steigman, G.; Thomas, D.; Walker, T.P. [Department of Physics, Ohio State University, Columbus, Ohio 43210 (United States)


    We present new upper and lower bounds to the primordial abundances of deuterium and {sup 3}He based on observational data from the solar system and the interstellar medium. Independent of any model for the primordial production of the elements we find (at the 95{percent} C.L.): 1.5{times}10{sup {minus}5}{le}(D/H){sub {ital P}}{le}10.0{times}10{sup {minus}5} and ({sup 3}He/H){sub {ital P}}{le}2.6{times}10{sup {minus}5}. When combined with the predictions of standard big bang nucleosynthesis, these constraints lead to a 95{percent} C.L. bound on the primordial abundance deuterium: (D/H){sub best}=(3.5{sup +2.7}{sub {minus}1.8}){times}10{sup {minus}5}. Measurements of deuterium absorption in the spectra of high-redshift QSOs will directly test this prediction. The implications of this prediction for the primordial abundances of {sup 4}He and {sup 7}Li are discussed, as well as those for the universal density of baryons. {copyright} {ital 1996 The American Astronomical Society.}

  13. Disruption prediction at JET

    International Nuclear Information System (INIS)

    Milani, F.


    The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus). Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. O'Brien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as l i and q ψ with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of

  14. On identified predictive control (United States)

    Bialasiewicz, Jan T.


    Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

  15. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Suetens, Sigrid; Galbo-Jørgensen, Claus B.; Tyran, Jean-Robert Karl


    as formalized in recent behavioral theory. In particular, players tend to bet less on numbers that have been drawn in the preceding week, as suggested by the ‘gambler’s fallacy’, and bet more on a number if it was frequently drawn in the recent past, consistent with the ‘hot-hand fallacy’.......We investigate the ‘law of small numbers’ using a data set on lotto gambling that allows us to measure players’ reactions to draws. While most players pick the same set of numbers week after week, we find that those who do change react on average as predicted by the law of small numbers...

  16. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    on machine learning techniques. Several MHC class I binding prediction algorithms have been developed and due to their high accuracy they are used by many immunologists to facilitate the conventional experimental process of epitope discovery. However, the accuracy of these methods depends on data defining...... the NetMHCIIpan-3.0 predictor based on artificial neural networks, which is capable of giving binding affinities to any human MHC class II molecule. Chapter 4 of this thesis gives an overview of bioinformatics tools developed by the Immunological Bioinformatics group at Center for Biological Sequence...

  17. Predicting chaotic time series

    International Nuclear Information System (INIS)

    Farmer, J.D.; Sidorowich, J.J.


    We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow

  18. Lattice of quantum predictions (United States)

    Drieschner, Michael


    What is the structure of reality? Physics is supposed to answer this question, but a purely empiristic view is not sufficient to explain its ability to do so. Quantum mechanics has forced us to think more deeply about what a physical theory is. There are preconditions every physical theory must fulfill. It has to contain, e.g., rules for empirically testable predictions. Those preconditions give physics a structure that is “a priori” in the Kantian sense. An example is given how the lattice structure of quantum mechanics can be understood along these lines.

  19. Foundations of predictive analytics

    CERN Document Server

    Wu, James


    Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish--Fisher expansion and o

  20. Predicting Sustainable Work Behavior

    DEFF Research Database (Denmark)

    Hald, Kim Sundtoft


    Sustainable work behavior is an important issue for operations managers – it has implications for most outcomes of OM. This research explores the antecedents of sustainable work behavior. It revisits and extends the sociotechnical model developed by Brown et al. (2000) on predicting safe behavior....... Employee characteristics and general attitudes towards safety and work condition are included in the extended model. A survey was handed out to 654 employees in Chinese factories. This research contributes by demonstrating how employee- characteristics and general attitudes towards safety and work...... condition influence their sustainable work behavior. A new definition of sustainable work behavior is proposed....

  1. Nuclear criticality predictability

    International Nuclear Information System (INIS)

    Briggs, J.B.


    As a result of lots of efforts, a large portion of the tedious and redundant research and processing of critical experiment data has been eliminated. The necessary step in criticality safety analyses of validating computer codes with benchmark critical data is greatly streamlined, and valuable criticality safety experimental data is preserved. Criticality safety personnel in 31 different countries are now using the 'International Handbook of Evaluated Criticality Safety Benchmark Experiments'. Much has been accomplished by the work of the ICSBEP. However, evaluation and documentation represents only one element of a successful Nuclear Criticality Safety Predictability Program and this element only exists as a separate entity, because this work was not completed in conjunction with the experimentation process. I believe; however, that the work of the ICSBEP has also served to unify the other elements of nuclear criticality predictability. All elements are interrelated, but for a time it seemed that communications between these elements was not adequate. The ICSBEP has highlighted gaps in data, has retrieved lost data, has helped to identify errors in cross section processing codes, and has helped bring the international criticality safety community together in a common cause as true friends and colleagues. It has been a privilege to associate with those who work so diligently to make the project a success. (J.P.N.)

  2. Predicting Microsurgical Aptitude. (United States)

    Osborn, Heather A; Kuthubutheen, Jafri; Yao, Christopher; Chen, Joseph M; Lin, Vincent Y


    Microscopic techniques are an essential part of otolaryngologic practice. These procedures demand advanced psychomotor and visuospatial skills, and trainees possess these abilities to varying degrees. No method currently exists to predict who will possess an aptitude for microscopic surgery. Our goal was to determine whether performance can be predicted by background experiences or skills. Retrospective cohort study. Tertiary academic hospital. Students with no previous surgical experience. Subjects were surveyed on a wide range characteristics thought to affect surgical aptitude, with a primary focus on video gaming and musical training. Subjects performed a microsurgical task using a novel simulator and their performance was assessed by blinded investigators. Forty-six students were assessed. There was no correlation between video gaming and improved microsurgical performance. Rather, video gamers obtained worse scores, although this difference did not reach significance. The majority of students played a musical instrument. Within this group, musicians who began playing at younger ages obtained higher scores, with the highest scores obtained by musicians who began playing before age 6. However, musicians did not obtain higher scores than non-musicians, regardless of their age of initiation. No improvement in microsurgical aptitude was seen in subjects who had a history of video gaming or musical instrument playing.

  3. Ratchetting strain prediction

    International Nuclear Information System (INIS)

    Noban, Mohammad; Jahed, Hamid


    A time-efficient method for predicting ratchetting strain is proposed. The ratchetting strain at any cycle is determined by finding the ratchetting rate at only a few cycles. This determination is done by first defining the trajectory of the origin of stress in the deviatoric stress space and then incorporating this moving origin into a cyclic plasticity model. It is shown that at the beginning of the loading, the starting point of this trajectory coincides with the initial stress origin and approaches the mean stress, displaying a power-law relationship with the number of loading cycles. The method of obtaining this trajectory from a standard uniaxial asymmetric cyclic loading is presented. Ratchetting rates are calculated with the help of this trajectory and through the use of a constitutive cyclic plasticity model which incorporates deviatoric stresses and back stresses that are measured with respect to this moving frame. The proposed model is used to predict the ratchetting strain of two types of steels under single- and multi-step loadings. Results obtained agree well with the available experimental measurements

  4. Predicting gangrenous cholecystitis. (United States)

    Wu, Bin; Buddensick, Thomas J; Ferdosi, Hamid; Narducci, Dusty Marie; Sautter, Amanda; Setiawan, Lisa; Shaukat, Haroon; Siddique, Mustafa; Sulkowski, Gisela N; Kamangar, Farin; Kowdley, Gopal C; Cunningham, Steven C


    Gangrenous cholecystitis (GC) is often challenging to treat. The objectives of this study were to determine the accuracy of pre-operative diagnosis, to assess the rate of post-cholecystectomy complications and to assess models to predict GC. A retrospective single-institution review identified patients undergoing a cholecystectomy. Logistic regression models were used to examine the association of variables with GC and to build risk-assessment models. Of 5812 patients undergoing a cholecystectomy, 2219 had acute, 4837 chronic and 351 GC. Surgeons diagnosed GC pre-operatively in only 9% of cases. Patients with GC had more complications, including bile-duct injury, increased estimated blood loss (EBL) and more frequent open cholecystectomies. In unadjusted analyses, variables significantly associated with GC included: age >45 years, male gender, heart rate (HR) >90, white blood cell count (WBC) >13,000/mm(3), gallbladder wall thickening (GBWT) ≥ 4 mm, pericholecystic fluid (PCCF) and American Society of Anesthesiology (ASA) >2. In adjusted analyses, age, WBC, GBWT and HR, but not gender, PCCF or ASA remained statistically significant. A 5-point scoring system was created: 0 points gave a 2% probability of GC and 5 points a 63% probability. Using models can improve a diagnosis of GC pre-operatively. A prediction of GC pre-operatively may allow surgeons to be better prepared for a difficult operation. © 2014 International Hepato-Pancreato-Biliary Association.

  5. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna


    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  6. Energy Predictions 2011

    International Nuclear Information System (INIS)


    Even as the recession begins to subside, the energy sector is still likely to experience challenging conditions as we enter 2011. It should be remembered how very important a role energy plays in driving the global economy. Serving as a simple yet global and unified measure of economic recovery, it is oil's price range and the strength and sustainability of the recovery which will impact the ways in which all forms of energy are produced and consumed. The report aims for a closer insight into these predictions: What will happen with M and A (Mergers and Acquisitions) in the energy industry?; What are the prospects for renewables?; Will the water-energy nexus grow in importance?; How will technological leaps and bounds affect E and P (exploration and production) operations?; What about electric cars? This is the second year Deloitte's Global Energy and Resources Group has published its predictions for the year ahead. The report is based on in-depth interviews with clients, industry analysts, and senior energy practitioners from Deloitte member firms around the world.

  7. Predicting Alloreactivity in Transplantation

    Directory of Open Access Journals (Sweden)

    Kirsten Geneugelijk


    Full Text Available Human leukocyte Antigen (HLA mismatching leads to severe complications after solid-organ transplantation and hematopoietic stem-cell transplantation. The alloreactive responses underlying the posttransplantation complications include both direct recognition of allogeneic HLA by HLA-specific alloantibodies and T cells and indirect T-cell recognition. However, the immunogenicity of HLA mismatches is highly variable; some HLA mismatches lead to severe clinical B-cell- and T-cell-mediated alloreactivity, whereas others are well tolerated. Definition of the permissibility of HLA mismatches prior to transplantation allows selection of donor-recipient combinations that will have a reduced chance to develop deleterious host-versus-graft responses after solid-organ transplantation and graft-versus-host responses after hematopoietic stem-cell transplantation. Therefore, several methods have been developed to predict permissible HLA-mismatch combinations. In this review we aim to give a comprehensive overview about the current knowledge regarding HLA-directed alloreactivity and several developed in vitro and in silico tools that aim to predict direct and indirect alloreactivity.

  8. [Predicting chance of disease: calculation using prediction rules]. (United States)

    Verbeek, Anna J M; Verbeek, Jan F M; van Dijck, Jos A A M; Verbeek, André L M


    A prediction rule is a statistical model that can be used to predict the presence or absence of a disease based on a limited number of tests or predictive factors. One of the mathematical methods used to formulate prediction rules is a logistic regression analysis of patient data. The discriminatory power of a model is visualizable using box-whisker plots and ROC curves; calibration plots show the match between the predicted chance and the observed frequency of a disease. These graphs are used to assess whether a model adequately reproduces reality. On publication of prediction rules it is important that the regression function is written out and that the chances of a disease on the basis of diagnostic scores are displayed in a histogram. For the practical significance of the model, it is also important to know how often the predicted low, medium or high probabilities of a disease do actually occur in comparison with the advance chance of occurrence.

  9. Protein docking prediction using predicted protein-protein interface

    Directory of Open Access Journals (Sweden)

    Li Bin


    Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

  10. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica


    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents experimentally based design parameters for Portland cement concretes with and without silica fume and fly ash...... in marine atmospheric and submersed South Scandinavian environment. The design parameters are based on sequential measurements of 86 chloride profiles taken over ten years from 13 different types of concrete. The design parameters provide the input for an analytical model for chloride profiles as function...... of depth and time, when both the surface chloride concentration and the diffusion coefficient are allowed to vary in time. The model is presented in a companion paper....

  11. Filter replacement lifetime prediction (United States)

    Hamann, Hendrik F.; Klein, Levente I.; Manzer, Dennis G.; Marianno, Fernando J.


    Methods and systems for predicting a filter lifetime include building a filter effectiveness history based on contaminant sensor information associated with a filter; determining a rate of filter consumption with a processor based on the filter effectiveness history; and determining a remaining filter lifetime based on the determined rate of filter consumption. Methods and systems for increasing filter economy include measuring contaminants in an internal and an external environment; determining a cost of a corrosion rate increase if unfiltered external air intake is increased for cooling; determining a cost of increased air pressure to filter external air; and if the cost of filtering external air exceeds the cost of the corrosion rate increase, increasing an intake of unfiltered external air.

  12. Motor degradation prediction methods

    Energy Technology Data Exchange (ETDEWEB)

    Arnold, J.R.; Kelly, J.F.; Delzingaro, M.J.


    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor`s duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures.

  13. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica


    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents the state-of-the art: an analytical model which describes chloride profiles in concrete as function of depth...... makes physical sense for the design engineer, i.e. the achieved chloride diffusion coefficients at 1 year and 100 years, D1 and D100 respectively, and the corresponding achieved chloride concentrations at the exposed concrete surface, C1 and C100. Data from field exposure supports the assumption of time...... dependent surface chloride concentrations and the diffusion coefficients. Model parameters for Portland cement concretes with and without silica fume and fly ash in marine atmospheric and submerged South Scandinavian environment are suggested in a companion paper based on 10 years field exposure data....

  14. Motor degradation prediction methods

    International Nuclear Information System (INIS)

    Arnold, J.R.; Kelly, J.F.; Delzingaro, M.J.


    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor's duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures

  15. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

    Poggesi, Anna; Gouw, Alida; van der Flier, Wiesje


    To investigate the role of neurological abnormalities and magnetic resonance imaging (MRI) lesions in predicting global functional decline in a cohort of initially independent-living elderly subjects. The Leukoaraiosis And DISability (LADIS) Study, involving 11 European centres, was primarily aimed...... at evaluating age-related white matter changes (ARWMC) as an independent predictor of the transition to disability (according to Instrumental Activities of Daily Living scale) or death in independent elderly subjects that were followed up for 3 years. At baseline, a standardized neurological examination.......0 years, 45 % males), 327 (51.7 %) presented at the initial visit with ≥1 neurological abnormality and 242 (38 %) reached the main study outcome. Cox regression analyses, adjusting for MRI features and other determinants of functional decline, showed that the baseline presence of any neurological...

  16. Plume rise predictions

    International Nuclear Information System (INIS)

    Briggs, G.A.


    Anyone involved with diffusion calculations becomes well aware of the strong dependence of maximum ground concentrations on the effective stack height, h/sub e/. For most conditions chi/sub max/ is approximately proportional to h/sub e/ -2 , as has been recognized at least since 1936 (Bosanquet and Pearson). Making allowance for the gradual decrease in the ratio of vertical to lateral diffusion at increasing heights, the exponent is slightly larger, say chi/sub max/ approximately h/sub e/ - 2 . 3 . In inversion breakup fumigation, the exponent is somewhat smaller; very crudely, chi/sub max/ approximately h/sub e/ -1 . 5 . In any case, for an elevated emission the dependence of chi/sub max/ on h/sub e/ is substantial. It is postulated that a really clever ignorant theoretician can disguise his ignorance with dimensionless constants. For most sources the effective stack height is considerably larger than the actual source height, h/sub s/. For instance, for power plants with no downwash problems, h/sub e/ is more than twice h/sub s/ whenever the wind is less than 10 m/sec, which is most of the time. This is unfortunate for anyone who has to predict ground concentrations, for he is likely to have to calculate the plume rise, Δh. Especially when using h/sub e/ = h/sub s/ + Δh instead of h/sub s/ may reduce chi/sub max/ by a factor of anywhere from 4 to infinity. Factors to be considered in making plume rise predictions are discussed

  17. Update on protein structure prediction

    DEFF Research Database (Denmark)

    Hubbard, T; Tramontano, A; Barton, G


    Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a number...... of proteins of biological interest using ab initio pre!diction of fold recognition methods. 112 protein sequences were collected via an open invitation for target submissions. 17 were selected for prediction during the workshop and for 11 of these a prediction of some reliability could be made. We believe...

  18. Data-Based Predictive Control with Multirate Prediction Step (United States)

    Barlow, Jonathan S.


    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  19. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA


    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation......, then rival strategies can still be compared based on repeated bootstraps of the same data. Often, however, the overall performance of rival strategies is similar and it is thus difficult to decide for one model. Here, we investigate the variability of the prediction models that results when the same...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...

  20. Performance Prediction Toolkit

    Energy Technology Data Exchange (ETDEWEB)


    The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes, cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few

  1. Introduction: Long term prediction

    International Nuclear Information System (INIS)

    Beranger, G.


    Making a decision upon the right choice of a material appropriate to a given application should be based on taking into account several parameters as follows: cost, standards, regulations, safety, recycling, chemical properties, supplying, transformation, forming, assembly, mechanical and physical properties as well as the behaviour in practical conditions. Data taken from a private communication (J.H.Davidson) are reproduced presenting the life time range of materials from a couple of minutes to half a million hours corresponding to applications from missile technology up to high-temperature nuclear reactors or steam turbines. In the case of deep storage of nuclear waste the time required is completely different from these values since we have to ensure the integrity of the storage system for several thousand years. The vitrified nuclear wastes should be stored in metallic canisters made of iron and carbon steels, stainless steels, copper and copper alloys, nickel alloys or titanium alloys. Some of these materials are passivating metals, i.e. they develop a thin protective film, 2 or 3 nm thick - the so-called passive films. These films prevent general corrosion of the metal in a large range of chemical condition of the environment. In some specific condition, localized corrosion such as the phenomenon of pitting, occurs. Consequently, it is absolutely necessary to determine these chemical condition and their stability in time to understand the behavior of a given material. In other words the corrosion system is constituted by the complex material/surface/medium. For high level nuclear wastes the main features for resolving problem are concerned with: geological disposal; deep storage in clay; waste metallic canister; backfill mixture (clay-gypsum) or concrete; long term behavior; data needed for modelling and for predicting; choice of appropriate solution among several metallic candidates. The analysis of the complex material/surface/medium is of great importance

  2. Can we predict the unpredictable? (United States)

    Golestani, Abbas; Gras, Robin


    Time series forecasting is of fundamental importance for a variety of domains including the prediction of earthquakes, financial market prediction, and the prediction of epileptic seizures. We present an original approach that brings a novel perspective to the field of long-term time series forecasting. Nonlinear properties of a time series are evaluated and used for long-term predictions. We used financial time series, medical time series and climate time series to evaluate our method. The results we obtained show that the long-term prediction of complex nonlinear time series is no longer unrealistic. The new method has the ability to predict the long-term evolutionary trend of stock market time series, and it attained an accuracy level with 100% sensitivity and specificity for the prediction of epileptic seizures up to 17 minutes in advance based on data from 21 epileptic patients. Our new method also predicted the trend of increasing global temperature in the last 30 years with a high level of accuracy. Thus, our method for making long-term time series predictions is vastly superior to existing methods. We therefore believe that our proposed method has the potential to be applied to many other domains to generate accurate and useful long-term predictions.

  3. Predictability of blocking

    International Nuclear Information System (INIS)

    Tosi, E.; Ruti, P.; Tibaldi, S.; D'Andrea, F.


    Tibaldi and Molteni (1990, hereafter referred to as TM) had previously investigated operational blocking predictability by the ECMWF model and the possible relationships between model systematic error and blocking in the winter season of the Northern Hemisphere, using seven years of ECMWF operational archives of analyses and day 1 to 10 forecasts. They showed that fewer blocking episodes than in the real atmosphere were generally simulated by the model, and that this deficiency increased with increasing forecast time. As a consequence of this, a major contribution to the systematic error in the winter season was shown to derive from the inability of the model to properly forecast blocking. In this study, the analysis performed in TM for the first seven winter seasons of the ECMWF operational model is extended to the subsequent five winters, during which model development, reflecting both resolution increases and parametrisation modifications, continued unabated. In addition the objective blocking index developed by TM has been applied to the observed data to study the natural low frequency variability of blocking. The ability to simulate blocking of some climate models has also been tested

  4. GABA predicts visual intelligence. (United States)

    Cook, Emily; Hammett, Stephen T; Larsson, Jonas


    Early psychological researchers proposed a link between intelligence and low-level perceptual performance. It was recently suggested that this link is driven by individual variations in the ability to suppress irrelevant information, evidenced by the observation of strong correlations between perceptual surround suppression and cognitive performance. However, the neural mechanisms underlying such a link remain unclear. A candidate mechanism is neural inhibition by gamma-aminobutyric acid (GABA), but direct experimental support for GABA-mediated inhibition underlying suppression is inconsistent. Here we report evidence consistent with a global suppressive mechanism involving GABA underlying the link between sensory performance and intelligence. We measured visual cortical GABA concentration, visuo-spatial intelligence and visual surround suppression in a group of healthy adults. Levels of GABA were strongly predictive of both intelligence and surround suppression, with higher levels of intelligence associated with higher levels of GABA and stronger surround suppression. These results indicate that GABA-mediated neural inhibition may be a key factor determining cognitive performance and suggests a physiological mechanism linking surround suppression and intelligence. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  5. Predictive Food Microbiology

    DEFF Research Database (Denmark)

    Østergaard, Nina Bjerre

    Listeria monocytogenes is a well-known food borne pathogen that potentially causes listeriosis. No outbreaks or cases of listeriosis have been associated with cottage cheese, but several confirmed cases and outbreaks in the EU and the US have been related to dairy products made from raw or pasteu......Listeria monocytogenes is a well-known food borne pathogen that potentially causes listeriosis. No outbreaks or cases of listeriosis have been associated with cottage cheese, but several confirmed cases and outbreaks in the EU and the US have been related to dairy products made from raw...... or pasteurised milk. This, in combination with the fact that cottage cheese support growth of Listeria monocytogenes, induces a documentation requirement on the food producer. In the EU regulatory framework, mathematical models are recognised as a suitable supplement to traditional microbiological methods...... was clearly important to include when predicting growth response of Listeria monocytogenes in fermented dairy products. Alternative, semi-mechanistic, iimodelling approaches were evaluated based on methods applied in the fermentation technology. The dynamics of lactic acid concentration and product p...

  6. Prediction of mill performance

    Energy Technology Data Exchange (ETDEWEB)

    P.A. Bennett [CoalTech Pty Ltd. (Australia)


    This Australian Coal Association Research Program (ACARP) project aimed to demonstrate that the Hardgrove Grindability Index (HGI) coupled with standard Petrographic Analysis can be used to greatly improve the prediction of mill power requirements, mill throughput and product size. The project examined the mill test data from ACIRL's pilot scale vertical spindle mill on 96 coals. A total of 360 mill tests, conducted under a wide range of throughputs, roll pressures and classifier settings, were included into the data set. The mill performance of maceral groups or microlithotypes was assumed to be additive, that is, each maceral group or microlithotype behaved independently and a size fraction of the product PF was the volume weighted sum of the petrographic components of that size fraction. Based on this assumption it was possible to determine the size distribution of the product PF, for a wide range of milling conditions, based solely on petrographic analysis. Microlithotypes were not determined directly but were estimated from the maceral analysis. The size distribution of individual maceral groups or microlithotypes can also be estimated based on developed correlations. Size distribution determined from petrographic analysis proved to be a better estimate than that determined from the HGI. Mill power can be estimated from petrographic analysis, but the HGI was found to be a better predictor of mill power. 19 refs., 4 figs., 1 tab.

  7. Long Range Aircraft Trajectory Prediction


    Magister, Tone


    The subject of the paper is the improvement of the aircraft future trajectory prediction accuracy for long-range airborne separation assurance. The strategic planning of safe aircraft flights and effective conflict avoidance tactics demand timely and accurate conflict detection based upon future four–dimensional airborne traffic situation prediction which is as accurate as each aircraft flight trajectory prediction. The improved kinematics model of aircraft relative flight considering flight ...

  8. Prospects for decadal climate prediction


    Keenlyside, Noel; Ba, Jin


    During the last decade, global surface temperatures did not increase as rapidly as in the preceding decades. Although relatively small compared to the observed centennial scale global warming, it has renewed interest in understanding and even predicting climate on time scales of decades, and sparked a community initiative on near‐term prediction that will feature in the fifth intergovernmental panel on climate change assessment report. Decadal prediction, however, is in its infancy, with only...

  9. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena


    Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were

  10. Predicting periodontitis progression? (United States)

    Ferraiolo, Debra M


    Cochrane Library, Ovid, Medline, Embase and LILACS were searched using no language restrictions and included information up to July 2014. Bibliographic references of included articles and related review articles were hand searched. On-line hand searching of recent issues of key periodontal journals was performed (Journal of Clinical Periodontology, Journal of Dental Research, Journal of Periodontal Research, Journal of Periodontology, Oral Health and Preventive Dentistry). Prospective and retrospective cohort studies were used for answering the question of prediction since there were no randomised controlled trials on this topic. Risk of bias was assessed using the validated Newcastle-Ottawa quality assessment scale for non-randomised studies. Cross-sectional studies were included in the summary of currently reported risk assessment tools but not for risk of progression of disease, due to the inability to properly assess bias in these types of studies. Titles and abstracts were scanned by two reviewers independently.Full reports were obtained for those articles meeting inclusion criteria or those with insufficient information in the title to make a decision. Any published risk assessment tool was considered. The tool was defined to include any composite measure of patient-level risk directed towards determining the probability for further disease progression in adults with periodontitis. Periodontitis was defined to include both chronic and aggressive forms in the adult population. Outcomes included changes in attachment levels and/or deepening of periodontal pockets in millimeters in study populations undergoing supportive periodontal therapy. Data extraction was performed independently and in collaboration by two reviewers; completed evidence tables were reviewed by three reviewers. Studies were each given a descriptive summary to assess the quantity of data as well as further assessment of study variations within study characteristics. This also allowed for

  11. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    We show that dividend growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our...... findings suggest that the apparent lack of dividend predictability in the U.S. does not uniformly extend to other countries. Rather, cross-country patterns in dividend predictability are driven by differences in firm characteristics and the extent to which dividends are smoothed....

  12. Total Ozone Prediction: Stratospheric Dynamics (United States)

    Jackman, Charles H.; Kawa, S. Ramdy; Douglass, Anne R.


    The correct prediction of total ozone as a function of latitude and season is extremely important for global models. This exercise tests the ability of a particular model to simulate ozone. The ozone production (P) and loss (L) will be specified from a well- established global model and will be used in all GCMs for subsequent prediction of ozone. This is the "B-3 Constrained Run" from M&MII. The exercise mostly tests a model stratospheric dynamics in the prediction of total ozone. The GCM predictions will be compared and contrasted with TOMS measurements.

  13. Predictability of Forced Lorenz Systems (United States)

    Li, Baosheng; Ding, Ruiqiang; Li, Jianping; Zhong, Quanjia


    Based on the nonlinear local Lyapunov exponent (NLLE) approach, the influences of external forcing on the predictability are studied in the Lorenz systems with constant and quasi-periodic forces in this paper. The results indicate that for the Lorenz systems with constant and quasi-periodic forces, their predictability limits increase with the forcing strength. With the same magnitude and different directions, the constant or quasi-periodic forcing shows different effects on the predictability limit in the Lorenz system, and these effects become significant with the increase of the forcing strength. Generally speaking, the positive forcing leads to a higher predictability limit than the negative forcing. Therefore, when we think about the effects of positive and negative elements and phases in the atmosphere and ocean research, the predictability problems driven by different phases should be considered separately. In addition, the influences of constant and quasi-periodic forces on the predictability are different in the Lorenz system. The effect of the constant forcing on the predictability is mainly reflected in the linear phase of error growth, while the nonlinear phase should also be considered for the situation of the quasi-periodic forcing. The predictability limit of the system under constant forcing is longer than the system under quasi-periodic forcing. These results based on simple chaotic model could provide insight into the studies of the actual atmosphere predictability.

  14. Prediction based on mean subset

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Brown, P. J.; Madsen, Henrik


    , it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction......Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...

  15. Predicting Financial Crime: Augmenting the Predictive Policing Arsenal


    Lavigne, Sam; Clifton, Brian; Tseng, Francis


    Financial crime is a rampant but hidden threat. In spite of this, predictive policing systems disproportionately target "street crime" rather than white collar crime. This paper presents the White Collar Crime Early Warning System (WCCEWS), a white collar crime predictive model that uses random forest classifiers to identify high risk zones for incidents of financial crime.

  16. Predicting epileptic seizures in advance.

    Directory of Open Access Journals (Sweden)

    Negin Moghim

    Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

  17. Quadratic prediction of factor scores

    NARCIS (Netherlands)

    Wansbeek, T


    Factor scores are naturally predicted by means of their conditional expectation given the indicators y. Under normality this expectation is linear in y but in general it is an unknown function of y. II is discussed that under nonnormality factor scores can be more precisely predicted by a quadratic

  18. The Challenge of Weather Prediction

    Indian Academy of Sciences (India)

    weather and climate prediction. His interests include understanding variability and predictability of all tropical phenomena including the monsoon. B N Goswami .... change the global average annual mean surface temperature Ts' the external solar forcing ..... Colombia, Toronto, London, Sydney. p 532, 1981. •. A Miller, J C ...

  19. Predictions for Excited Strange Baryons

    Energy Technology Data Exchange (ETDEWEB)

    Fernando, Ishara P.; Goity, Jose L. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)


    An assessment is made of predictions for excited hyperon masses which follow from flavor symmetry and consistency with a 1/N c expansion of QCD. Such predictions are based on presently established baryonic resonances. Low lying hyperon resonances which do not seem to fit into the proposed scheme are discussed.

  20. Decadal climate prediction (project GCEP). (United States)

    Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug


    Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

  1. Predicting landslides in clearcut patches (United States)

    Raymond M. Rice; Norman H. Pillsbury


    Abstract - Accelerated erosion in the form of landslides can be an undesirable consequence of clearcut logging on steep slopes. Forest managers need a method of predicting the risk of such erosion. Data collected after logging in a granitic area of northwestern California were used to develop a predictive equation. A linear discriminant function was developed that...

  2. The Challenge of Weather Prediction

    Indian Academy of Sciences (India)

    B N Goswami is with the. Centre for Atmospheric and Oceanic Sciences at the Indian Institute of. Science, Bangalore. After his PhD in Plasma Physics he was attracted to this field by the challenges in weather and climate prediction. His interests include understanding variability and predictability of all tropical phenomena.

  3. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas


    We show that dividend-growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our f...

  4. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik


    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...... the performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms...... are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production...

  5. Prediction of molecular crystal structures

    CERN Document Server

    Beyer, T


    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of parac...

  6. Slip Prediction through Tactile Sensing

    Directory of Open Access Journals (Sweden)



    Full Text Available This paper introduces a new way to predict contact slip using a resistive tactile sensor. The prototype sensor can be used to provide intrinsic information relating to geometrical features situated on the surface of grasped objects. Information along the gripper finger surface is obtained with a measurement resolution dependant on the number of discrete tactile elements. The tactile sensor predicts the partial slip of a tactile surface by sensing micro vibrations in tangential forces which are caused by an expansion of the slip regions within the contact area. The location of the local slip is not specified but its occurrence can be predicted immediately following micro vibration detection. Predictive models have been used to develop a set of rules which predict the slip based on fluctuations in tactile signal data.

  7. Predictive Biomarkers for Asthma Therapy. (United States)

    Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A


    Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

  8. Psychometric prediction of penitentiary recidivism. (United States)

    Medina García, Pedro M; Baños Rivera, Rosa M


    Attempts to predict prison recidivism based on the personality have not been very successful. This study aims to provide data on recidivism prediction based on the scores on a personality questionnaire. For this purpose, a predictive model combining the actuarial procedure with a posteriori probability was developed, consisting of the probabilistic calculation of the effective verification of the event once it has already occurred. Cuestionario de Personalidad Situacional (CPS; Fernández, Seisdedos, & Mielgo, 1998) was applied to 978 male inmates classified as recidivists or non-recidivists. High predictive power was achieved, with the area under the curve (AUC) of 0.85 (p <.001; Se = 0.012; 95% CI [0.826, 0.873]. The answers to the CPS items made it possible to properly discriminate 77.3% of the participants. These data indicate the important role of the personality as a key factor in understanding delinquency and predicting recidivism.

  9. Dividend Predictability around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    demonstrate that aggregate dividend growth rates are highly predictable by the dividend yield and that dividend predictability is clearly stronger than return predictability in medium-sized and smaller countries that account for the majority of countries in the world. We show that this is true both...... in the time-series dimension (time variation in dividend yields strongly predicts future dividend growth rates) and in the cross- country dimension (sorting countries into portfolios depending on their lagged dividend yield produces a spread in dividend growth rates of more than 20% p.a.). In an economic...... assessment of this finding, we show that cash flow predictability is stronger in smaller and medium- sized countries because these countries also have more volatile cash flow growth and higher idiosyncratic return volatility....

  10. Are abrupt climate changes predictable? (United States)

    Ditlevsen, Peter


    It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope

  11. Predictive Manufacturing: A Classification Strategy to Predict Product Failures

    DEFF Research Database (Denmark)

    Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat


    manufacturing analytics model that employs a big data approach to predicting product failures; third, we illustrate the issue of high dimensionality, along with statistically redundant information; and, finally, our proposed method will be compared against the well-known classification methods (SVM, K......-nearest neighbor, artificial neural networks). The results from real data show that our predictive manufacturing analytics approach, using genetic algorithms and Voronoi tessellations, is capable of predicting product failure with reasonable accuracy. The potential application of this method contributes......Predicting failures can be considered a meaningful insight for the optimal planning of an industrial manufacturing process. In this era of advanced sensor technologies, when the collection of data from each step of the manufacturing process is common practice and advanced analytical skills enable...

  12. Collective motion of predictive swarms.

    Directory of Open Access Journals (Sweden)

    Nathaniel Rupprecht

    Full Text Available Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

  13. The Theory of Linear Prediction

    CERN Document Server

    Vaidyanathan, PP


    Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vecto

  14. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C


    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  15. Practical aspects of geological prediction

    International Nuclear Information System (INIS)

    Mallio, W.J.; Peck, J.H.


    Nuclear waste disposal requires that geology be a predictive science. The prediction of future events rests on (1) recognizing the periodicity of geologic events; (2) defining a critical dimension of effect, such as the area of a drainage basin, the length of a fault trace, etc; and (3) using our understanding of active processes the project the frequency and magnitude of future events in the light of geological principles. Of importance to nuclear waste disposal are longer term processes such as continental denudation and removal of materials by glacial erosion. Constant testing of projections will allow the practical limits of predicting geological events to be defined. 11 refs

  16. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    DeBey, T.M.


    The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

  17. Predictions models with neural nets

    Directory of Open Access Journals (Sweden)

    Vladimír Konečný


    Full Text Available The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way prediction learning. The contribution contains two basic models that use structure of multilayer neural nets and way of determination their configuration. It is postulate a simple rule for teaching period of neural net, to get most credible prediction.Experiments are executed with really data evolution of exchange rate Kč/Euro. The main reason of choice this time series is their availability for sufficient long period. In carry out of experiments the both given basic kind of prediction models with most frequent use functions of neurons are verified. Achieve prediction results are presented as in numerical and so in graphical forms.

  18. Trading Network Predicts Stock Price (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi


    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  19. Fatigue life prediction in composites

    CSIR Research Space (South Africa)

    Huston, RJ


    Full Text Available epoxy were used to test residual strength and residual stiffness models. Further fatigue tests were carried out under spectrum loading so that the results could be correlated with the cumulative damage predicted by the residual strength model....

  20. In silico prediction of genotoxicity. (United States)

    Wichard, Jörg D


    The in silico prediction of genotoxicity has made considerable progress during the last years. The main driver for the pharmaceutical industry is the ICH M7 guideline about the assessment of DNA reactive impurities. An important component of this guideline is the use of in silico models as an alternative approach to experimental testing. The in silico prediction of genotoxicity provides an established and accepted method that defines the first step in the assessment of DNA reactive impurities. This was made possible by the growing amount of reliable Ames screening data, the attempts to understand the activity pathways and the subsequent development of computer-based prediction systems. This paper gives an overview of how the in silico prediction of genotoxicity is performed under the ICH M7 guideline. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. EPRI MOV performance prediction program

    International Nuclear Information System (INIS)

    Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.


    An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

  2. Dynamical Predictability of Monthly Means. (United States)

    Shukla, J.


    We have attempted to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. We have extended the concept of `classical' predictability, which primarily refers to the lack of predictability due mainly to the instabilities of synoptic-scale disturbances, to the predictability of time averages, which are determined by the predictability of low-frequency planetary waves. We have carded out 60-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperature, snow, sea ice and soil moisture. Three of these initial conditions are the observed atmospheric conditions on 1 January of 1975, 1976 and 1977. The other six initial conditions are obtained by superimposing over the observed initial conditions a random perturbation comparable to the errors of observation. The root-mean-square (rms) error of random perturbations at all the grid points and all the model levels is 3 m s1 in u and v components of wind. The rms vector wind error between the observed initial conditions is >15 m s1.It is hypothesized that for a given averaging period, if the rms error among the time averages predicted from largely different initial conditions becomes comparable to the rms error among the time averages predicted from randomly perturbed initial conditions, the time averages are dynamically unpredictable. We have carried out the analysis of variance to compare the variability, among the three groups, due to largely different initial conditions, and within each group due to random perturbations.It is found that the variances among the first 30-day means, predicted from largely different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, whereas the variances among 30-day means for days 31-60 are not distinguishable from the variances due to random initial

  3. Improving Predictive Accuracy in Elections. (United States)

    Sathiaraj, David; Cassidy, William M; Rohli, Eric


    The problem of accurately predicting vote counts in elections is considered in this article. Typically, small-sample polls are used to estimate or predict election outcomes. In this study, a machine-learning hybrid approach is proposed. This approach utilizes multiple sets of static data sources, such as voter registration data, and dynamic data sources, such as polls and donor data, to develop individualized voter scores for each member of the population. These voter scores are used to estimate expected vote counts under different turnout scenarios. The proposed technique has been tested with data collected during U.S. Senate and Louisiana gubernatorial elections. The predicted results (expected vote counts, predicted several days before the actual election) were accurate within 1%.

  4. Data for decay Heat Predictions

    International Nuclear Information System (INIS)


    These proceedings of a specialists' meeting on data for decay heat predictions are based on fission products yields, on delayed neutrons and on comparative evaluations on evaluated and experimental data for thermal and fast fission. Fourteen conferences were analysed

  5. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    completely. Thus, in systems with hard deadlines the worst-case execution time (WCET) of the real-time software running on them needs to be bounded. Modern architectures use features such as pipelining and caches for improving the average performance. These features, however, make the WCET analysis more...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...... keeping the timepredictability of the design intact. Moreover, we provide a solution for reducing the cost of context switching in a system using the stack cache. In design of these caches, we use custom hardware and compiler support for delivering time-predictable stack data accesses. Furthermore...

  6. Predictive Models and Computational Embryology (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  7. Trading network predicts stock price. (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi


    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  8. Human Behavior is Extremely Predictable (United States)

    de Deo, Simon

    The basic goal of the sciences is to point to, and explain, emergent phenomena: what we would not have guessed given what we knew before. This lack of predictability can come from a change of scale (more is different; physics), a change of descriptive language (lost in translation; the human sciences), or just patience on the part of the observer (self-organization; biology). Nothing worth knowing can be predicted...

  9. Prediction of molecular crystal structures

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, Theresa


    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  10. Predictive markers of radiation pneumonitis. (United States)

    Provatopoulou, X; Athanasiou, E; Gounaris, A


    Radiation pneumonitis is an acute-phase response to radiation therapy and a common complication that affects a patient's quality of life. Under the need to reduce the incidence and severity of radiation-induced pulmonary complications as well as to identify patients at risk, several investigations on potential predictive markers of radiation pneumonitis have been conducted. The present study reviews the currently available knowledge on biomolecules of potential predictive value for radiation pneumonitis.

  11. Predictive coding in Agency Detection

    DEFF Research Database (Denmark)

    Andersen, Marc Malmdorf


    Agency detection is a central concept in the cognitive science of religion (CSR). Experimental studies, however, have so far failed to lend support to some of the most common predictions that follow from current theories on agency detection. In this article, I argue that predictive coding, a high...... for the effects of culture on the detection of supernatural agency and a range of other religious and spiritual perceptual phenomena....

  12. Prediction of interannual climate variations

    International Nuclear Information System (INIS)

    Shukla, J.


    It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. (orig./KW)

  13. Prediction of highly cited papers (United States)

    Newman, M. E. J.


    In an article in the pages of this journal five years ago, we described a method for predicting which scientific papers will be highly cited in the future, even if they are currently not highly cited. Applying the method to real citation data we made predictions about papers we believed would end up being well cited. Here we revisit those predictions, five years on, to see how well we did. Among the over 2000 papers in our original data set, we examine the fifty that, by the measures of our previous study, were predicted to do best and we find that they have indeed received substantially more citations in the intervening years than other papers, even after controlling for the number of prior citations. On average these top fifty papers have received 23 times as many citations in the last five years as the average paper in the data set as a whole, and 15 times as many as the average paper in a randomly drawn control group that started out with the same number of citations. Applying our prediction technique to current data, we also make new predictions of papers that we believe will be well cited in the next few years.

  14. Reward positivity: Reward prediction error or salience prediction error? (United States)

    Heydari, Sepideh; Holroyd, Clay B


    The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. © 2016 Society for Psychophysiological Research.

  15. Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems (United States)

    Kelkar, Atul G.


    The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

  16. Weighted-Average Least Squares Prediction

    NARCIS (Netherlands)

    Magnus, Jan R.; Wang, Wendun; Zhang, Xinyu


    Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty from the

  17. The predictive consequences of parameterization (United States)

    White, J.; Hughes, J. D.; Doherty, J. E.


    In numerical groundwater modeling, parameterization is the process of selecting the aspects of a computer model that will be allowed to vary during history matching. This selection process is dependent on professional judgment and is, therefore, inherently subjective. Ideally, a robust parameterization should be commensurate with the spatial and temporal resolution of the model and should include all uncertain aspects of the model. Limited computing resources typically require reducing the number of adjustable parameters so that only a subset of the uncertain model aspects are treated as estimable parameters; the remaining aspects are treated as fixed parameters during history matching. We use linear subspace theory to develop expressions for the predictive error incurred by fixing parameters. The predictive error is comprised of two terms. The first term arises directly from the sensitivity of a prediction to fixed parameters. The second term arises from prediction-sensitive adjustable parameters that are forced to compensate for fixed parameters during history matching. The compensation is accompanied by inappropriate adjustment of otherwise uninformed, null-space parameter components. Unwarranted adjustment of null-space components away from prior maximum likelihood values may produce bias if a prediction is sensitive to those components. The potential for subjective parameterization choices to corrupt predictions is examined using a synthetic model. Several strategies are evaluated, including use of piecewise constant zones, use of pilot points with Tikhonov regularization and use of the Karhunen-Loeve transformation. The best choice of parameterization (as defined by minimum error variance) is strongly dependent on the types of predictions to be made by the model.

  18. Geophysical Anomalies and Earthquake Prediction (United States)

    Jackson, D. D.


    Finding anomalies is easy. Predicting earthquakes convincingly from such anomalies is far from easy. Why? Why have so many beautiful geophysical abnormalities not led to successful prediction strategies? What is earthquake prediction? By my definition it is convincing information that an earthquake of specified size is temporarily much more likely than usual in a specific region for a specified time interval. We know a lot about normal earthquake behavior, including locations where earthquake rates are higher than elsewhere, with estimable rates and size distributions. We know that earthquakes have power law size distributions over large areas, that they cluster in time and space, and that aftershocks follow with power-law dependence on time. These relationships justify prudent protective measures and scientific investigation. Earthquake prediction would justify exceptional temporary measures well beyond those normal prudent actions. Convincing earthquake prediction would result from methods that have demonstrated many successes with few false alarms. Predicting earthquakes convincingly is difficult for several profound reasons. First, earthquakes start in tiny volumes at inaccessible depth. The power law size dependence means that tiny unobservable ones are frequent almost everywhere and occasionally grow to larger size. Thus prediction of important earthquakes is not about nucleation, but about identifying the conditions for growth. Second, earthquakes are complex. They derive their energy from stress, which is perniciously hard to estimate or model because it is nearly singular at the margins of cracks and faults. Physical properties vary from place to place, so the preparatory processes certainly vary as well. Thus establishing the needed track record for validation is very difficult, especially for large events with immense interval times in any one location. Third, the anomalies are generally complex as well. Electromagnetic anomalies in particular require

  19. Neural Elements for Predictive Coding

    Directory of Open Access Journals (Sweden)

    Stewart SHIPP


    Full Text Available Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backwards in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forwards and backwards pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a updates in the microcircuitry of primate visual cortex, and (b rapid technical advances made

  20. Neural Elements for Predictive Coding. (United States)

    Shipp, Stewart


    Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many 'illusory' instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry - that neurons with extrinsically bifurcating axons do not project in both directions - has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic 'canonical microcircuit' and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural

  1. Phosphorylation site prediction in plants. (United States)

    Yao, Qiuming; Schulze, Waltraud X; Xu, Dong


    Protein phosphorylation events on serine, threonine, and tyrosine residues are the most pervasive protein covalent bond modifications in plant signaling. Both low and high throughput studies reveal the importance of phosphorylation in plant molecular biology. Although becoming more and more common, the proteome-wide screening on phosphorylation by experiments remains time consuming and costly. Therefore, in silico prediction methods are proposed as a complementary analysis tool to enhance the phosphorylation site identification, develop biological hypothesis, or help experimental design. These methods build statistical models based on the experimental data, and they do not have some of the technical-specific bias, which may have advantage in proteome-wide analysis. More importantly computational methods are very fast and cheap to run, which makes large-scale phosphorylation identifications very practical for any types of biological study. Thus, the phosphorylation prediction tools become more and more popular. In this chapter, we will focus on plant specific phosphorylation site prediction tools, with essential illustration of technical details and application guidelines. We will use Musite, PhosPhAt and PlantPhos as the representative tools. We will present the results on the prediction of the Arabidopsis protein phosphorylation events to give users a general idea of the performance range of the three tools, together with their strengths and limitations. We believe these prediction tools will contribute more and more to the plant phosphorylation research community.

  2. Quantifying prognosis with risk predictions. (United States)

    Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R


    Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.


    Directory of Open Access Journals (Sweden)

    SALAS-MOLINA Francisco


    Full Text Available Predicting demand for fashion products is crucial for textile manufacturers. In an attempt to both avoid out-of-stocks and minimize holding costs, different forecasting techniques are used by production managers. Both linear and non-linear time-series analysis techniques are suitable options for forecasting purposes. However, demand for fashion products presents a number of particular characteristics such as short life-cycles, short selling seasons, high impulse purchasing, high volatility, low predictability, tremendous product variety and a high number of stock-keeping-units. In this paper, we focus on predicting demand for cotton yarns using a non-linear forecasting technique that has been fruitfully used in many areas, namely, random forests. To this end, we first identify a number of explanatory variables to be used as a key input to forecasting using random forests. We consider explanatory variables usually labeled either as causal variables, when some correlation is expected between them and the forecasted variable, or as time-series features, when extracted from time-related attributes such as seasonality. Next, we evaluate the predictive power of each variable by means of out-of-sample accuracy measurement. We experiment on a real data set from a textile company in Spain. The numerical results show that simple time-series features present more predictive ability than other more sophisticated explanatory variables.

  4. Human motion simulation predictive dynamics

    CERN Document Server

    Abdel-Malek, Karim


    Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures, such as speed and energy, which act as objective functions to be optimized. Constraints on joint torques and angles are imposed quite easily. Predicting motion in this way allows one to use avatars to study how and why humans move the way they do, given specific scenarios. It also enables avatars to react to infinitely many scenarios with substantial autonomy. With this approach it is possible to predict dynamic motion without having to integrate equations of motion -- rather than solving equations of motion, this approach solves for a continuous time-dependent curve characterizing joint variables (also called joint profiles) for every degree of freedom. Introduces rigorous mathematical methods for digital human modelling and simulation Focuses on understanding and representing spatial relationships (3D) of biomechanics Develops an i...

  5. Economic Culture and Prediction Markets

    Directory of Open Access Journals (Sweden)

    Khalid N. Alhayyan


    Full Text Available How do individual characteristics, such as economic culture, influence the trading behaviors and the acceptance of any consensus reached through prediction market mechanisms? This research explores variations in the usage of prediction (or information markets that are explained by some of the traders' cultural differences. Four forms of capitalism: state-guided, oligarchic, big-firm, and entrepreneurial, proposed by Baumol et al, are employed to capture aspects of traders' differences. To assess participants' economic culture along the spectrum of capitalist forms a survey instrument has been developed, validated, and tested. Moreover, several concepts related to trading participation, trading patterns, trader's overall performance and trader's acceptance of market outcomes are described and hypothesized against the economic culture forms. A series of research questions are proposed that explore how trader economic culture may affect prediction market use. The research landscape specified by Jones et al. is extended to recognize the potential differences between trader and market outcomes.

  6. Sweetness prediction of natural compounds. (United States)

    Chéron, Jean-Baptiste; Casciuc, Iuri; Golebiowski, Jérôme; Antonczak, Serge; Fiorucci, Sébastien


    Based on the most exhaustive database of sweeteners with known sweetness values, a new quantitative structure-activity relationship model for sweetness prediction has been set up. Analysis of the physico-chemical properties of sweeteners in the database indicates that the structure of most potent sweeteners combines a hydrophobic scaffold functionalized by a limited number of hydrogen bond sites (less than 4 hydrogen bond donors and 10 acceptors), with a moderate molecular weight ranging from 350 to 450g·mol -1 . Prediction of sweetness, bitterness and toxicity properties of the largest database of natural compounds have been performed. In silico screening reveals that the majority of the predicted natural intense sweeteners comprise saponin or stevioside scaffolds. The model highlights that their sweetness potency is comparable to known natural sweeteners. The identified compounds provide a rational basis to initiate the design and chemosensory analysis of new low-calorie sweeteners. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Sentence-Level Attachment Prediction (United States)

    Albakour, M.-Dyaa; Kruschwitz, Udo; Lucas, Simon

    Attachment prediction is the task of automatically identifying email messages that should contain an attachment. This can be useful to tackle the problem of sending out emails but forgetting to include the relevant attachment (something that happens all too often). A common Information Retrieval (IR) approach in analyzing documents such as emails is to treat the entire document as a bag of words. Here we propose a finer-grained analysis to address the problem. We aim at identifying individual sentences within an email that refer to an attachment. If we detect any such sentence, we predict that the email should have an attachment. Using part of the Enron corpus for evaluation we find that our finer-grained approach outperforms previously reported document-level attachment prediction in similar evaluation settings.

  8. BBN predictions for 4He

    International Nuclear Information System (INIS)

    Walker, T.P.


    The standard model of the hot big bang assumes a homogeneous and isotropic Universe with gravity described by General Relativity and strong and electroweak interactions described by the Standard Model of particle physics. The hot big bang model makes the unavoidable prediction that the production of primordial elements occurred about one minute after the big band (referred to as big bang or primordial nucleosynthesis BBN). This review concerns the range of the primordial abundance of 4 He as predicted by standard BBN (i.e., primordial nucleosynthesis assuming a homogeneous distribution of baryons). In it the author discusses: (1) Uncertainties in the calculation of Y p (the mass fraction of primordial 4 He), (2) The expected range of Y p , (3) How the predictions stack up against the latest observations, and (4) The latest BBN bounds on Ω B h 2 and N ν . 13 refs., 2 figs

  9. State-space predictive control

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen


    Full Text Available This paper deals with a predictive control strategy based on state-space models. Important issues concerning inherent model identification and optimal control computation are briefly discussed. Predictive control relies heavily on a model with satisfactory predictive capabilities. An off-line identification procedure must be accomplished to obtain a proper model structure and a parameter set, which is required for on-line adjustment. The control calculation is based on a general performance index and parameterization of the control variables in a nonlinear model, which includes the relevant constraints. This results in a finite-dimensional optimization problem which can be repetitively solved on-line. Simulation studies on two very different, typical industrial processes are presented. The simulations show that this MPC technique offers a major improvement in the control of many industrial processes.

  10. Prediction, Regression and Critical Realism

    DEFF Research Database (Denmark)

    Næss, Petter


    This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

  11. Evaluating the Predictive Value of Growth Prediction Models (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.


    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  12. Evoked emotions predict food choice. (United States)

    Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry


    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

  13. Ensemble method for dengue prediction. (United States)

    Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan


    In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  14. Prediction of eyespot infection risks

    Directory of Open Access Journals (Sweden)

    M. Váòová


    Full Text Available The objective of the study was to design a prediction model for eyespot (Tapesia yallundae infection based on climatic factors (temperature, precipitation, air humidity. Data from experiment years 1994-2002 were used to study correlations between the eyespot infection index and individual weather characteristics. The model of prediction was constructed using multiple regression when a separate parameter is assigned to each factor, i.e. the frequency of days with optimum temperatures, humidity, and precipitation. The correlation between relative air humidity and precipitation and the infection index is significant.

  15. Dinosaur Fossils Predict Body Temperatures (United States)

    Allen, Andrew P; Charnov, Eric L


    Perhaps the greatest mystery surrounding dinosaurs concerns whether they were endotherms, ectotherms, or some unique intermediate form. Here we present a model that yields estimates of dinosaur body temperature based on ontogenetic growth trajectories obtained from fossil bones. The model predicts that dinosaur body temperatures increased with body mass from approximately 25 °C at 12 kg to approximately 41 °C at 13,000 kg. The model also successfully predicts observed increases in body temperature with body mass for extant crocodiles. These results provide direct evidence that dinosaurs were reptiles that exhibited inertial homeothermy. PMID:16817695

  16. Dinosaur fossils predict body temperatures.

    Directory of Open Access Journals (Sweden)

    James F Gillooly


    Full Text Available Perhaps the greatest mystery surrounding dinosaurs concerns whether they were endotherms, ectotherms, or some unique intermediate form. Here we present a model that yields estimates of dinosaur body temperature based on ontogenetic growth trajectories obtained from fossil bones. The model predicts that dinosaur body temperatures increased with body mass from approximately 25 degrees C at 12 kg to approximately 41 degrees C at 13,000 kg. The model also successfully predicts observed increases in body temperature with body mass for extant crocodiles. These results provide direct evidence that dinosaurs were reptiles that exhibited inertial homeothermy.

  17. Can we predict nuclear proliferation

    International Nuclear Information System (INIS)

    Tertrais, Bruno


    The author aims at improving nuclear proliferation prediction capacities, i.e. the capacities to identify countries susceptible to acquire nuclear weapons, to interpret sensitive activities, and to assess nuclear program modalities. He first proposes a retrospective assessment of counter-proliferation actions since 1945. Then, based on academic studies, he analyzes what causes and motivates proliferation, with notably the possibility of existence of a chain phenomenon (mechanisms driving from one program to another). He makes recommendations for a global approach to proliferation prediction, and proposes proliferation indices and indicators

  18. Calorimetry end-point predictions

    International Nuclear Information System (INIS)

    Fox, M.A.


    This paper describes a portion of the work presently in progress at Rocky Flats in the field of calorimetry. In particular, calorimetry end-point predictions are outlined. The problems associated with end-point predictions and the progress made in overcoming these obstacles are discussed. The two major problems, noise and an accurate description of the heat function, are dealt with to obtain the most accurate results. Data are taken from an actual calorimeter and are processed by means of three different noise reduction techniques. The processed data are then utilized by one to four algorithms, depending on the accuracy desired to determined the end-point

  19. Wind energy prediction; Prediccion eolica

    Energy Technology Data Exchange (ETDEWEB)

    Xiberta, B. J.; Florez, M. V. E.


    On March 12th, 2004 the Spanish Government modified the legal situation of the renewable energies following the approval of RD 436/2004. This makes necessary the development of wind energy prediction models for its entrance to the daily electricity market like the conventional energies. The improvement of physical models, meteorological models, or a combination of both, is necessary for the prediction of the wind generation. This will guarantee the wind energy full utilization and the participation in the electrical market, as well as the remuneration of the complementary services and the regulation of reactive electricity. In this way wind energy turns into a perfectly manageable one. (Author)

  20. HWVP melter lifetime prediction letter

    Energy Technology Data Exchange (ETDEWEB)

    Eyler, L.L.; Mahoney, L.A.; Elliott, M.L.


    Preliminary predictions were made of the time to reach hypothesized operational limits of the HWVP melter due to build up of a noble metals sludge layer on the melter floor. Predictions were made with the TEMPEST computer program, Version T2.9h, for use in the MPA activity in the Pacific Northwest Laboratory`s (PNL) Hanford Waste Vitrification Plant (HWVP) Technology Development (PHTD) effort. The NWEST computer program (Trent and Eyler 1993) is a PNL-MA-70/Part 2 -- Good Practices Standard (QA Level III) research and development software tool.

  1. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

  2. Framework for Traffic Congestion Prediction

    NARCIS (Netherlands)

    Zaki, J.F.W.; Ali-Eldin, A.M.T.; Hussein, S.E.; Saraya, S.F.; Areed, F.F.


    Traffic Congestion is a complex dilemma facing most major cities. It has undergone a lot of research since the early 80s in an attempt to predict traffic in the short-term. Recently, Intelligent Transportation Systems (ITS) became an integral part of traffic research which helped in modeling and

  3. Solution Patterns Predicting Pythagorean Triples (United States)

    Ezenweani, Ugwunna Louis


    Pythagoras Theorem is an old mathematical treatise that has traversed the school curricula from secondary to tertiary levels. The patterns it produced are quite interesting that many researchers have tried to generate a kind of predictive approach to identifying triples. Two attempts, namely Diophantine equation and Brahmagupta trapezium presented…

  4. Predictive models of moth development (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  5. Evoked Emotions Predict Food Choice

    NARCIS (Netherlands)

    Dalenberg, Jelle R.; Gutjar, Swetlana; ter Horst, Gert J.; de Graaf, Kees; Renken, Remco J.; Jager, Gerry


    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments.

  6. Predicting confidence in flashbulb memories. (United States)

    Day, Martin V; Ross, Michael


    Years after a shocking news event many people confidently report details of their flashbulb memories (e.g., what they were doing). People's confidence is a defining feature of their flashbulb memories, but it is not well understood. We tested a model that predicted confidence in flashbulb memories. In particular we examined whether people's social bond with the target of a news event predicts confidence. At a first session shortly after the death of Michael Jackson participants reported their sense of attachment to Michael Jackson, as well as their flashbulb memories and emotional and other reactions to Jackson's death. At a second session approximately 18 months later they reported their flashbulb memories and confidence in those memories. Results supported our proposed model. A stronger sense of attachment to Jackson was related to reports of more initial surprise, emotion, and rehearsal during the first session. Participants' bond with Michael Jackson predicted their confidence but not the consistency of their flashbulb memories 18 months later. We also examined whether participants' initial forecasts regarding the persistence of their flashbulb memories predicted the durability of their memories. Participants' initial forecasts were more strongly related to participants' subsequent confidence than to the actual consistency of their memories.

  7. Bankruptcy Prediction with Rough Sets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); V. Popova (Viara)


    textabstractThe bankruptcy prediction problem can be considered an or dinal classification problem. The classical theory of Rough Sets describes objects by discrete attributes, and does not take into account the order- ing of the attributes values. This paper proposes a modification of the Rough Set

  8. Detecting failure of climate predictions (United States)

    Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve


    The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

  9. Multimodal Imaging Measures Predict Rearrest

    Directory of Open Access Journals (Sweden)

    Vaughn R Steele


    Full Text Available Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC during error-processing (Aharoni et al., 2013. Here we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. Event-related potentials (ERPs and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne and the error positivity (Pe. Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%. Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.

  10. Predicting Student Misconceptions in Science (United States)

    Fouché, Jaunine


    Two challenges science teachers face are identifying misconceptions students have about how the world operates and getting past those misconceptions. Students' prior conceptions often conflict with the content educators are trying to teach. The gateway to revealing and changing such misconceptions, Fouché says, is predictive questioning. As they…

  11. The Challenge of Weather Prediction

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. The Challenge of Weather Prediction Old and Modern Ways of Weather Forecasting. B N Goswami. Series Article Volume 2 Issue 3 March 1997 pp 8-15. Fulltext. Click here to view fulltext PDF. Permanent link:

  12. Predicting Volleyball Serve-Reception

    NARCIS (Netherlands)

    Paulo, Ana; Zaal, Frank T J M; Fonseca, Sofia; Araujo, Duarte


    Serve and serve-reception performance have predicted success in volleyball. Given the impact of serve-reception on the game, we aimed at understanding what it is in the serve and receiver's actions that determines the selection of the type of pass used in serve-reception and its efficacy. Four


    Energy Technology Data Exchange (ETDEWEB)

    Lam, P.S.; Morgan, M.J


    The burst test is used to assess the material performance of tritium reservoirs in the surveillance program in which reservoirs have been in service for extended periods of time. A materials system model and finite element procedure were developed under a Savannah River Site Plant-Directed Research and Development (PDRD) program to predict the structural response under a full range of loading and aged material conditions of the reservoir. The results show that the predicted burst pressure and volume ductility are in good agreement with the actual burst test results for the unexposed units. The material tensile properties used in the calculations were obtained from a curved tensile specimen harvested from a companion reservoir by Electric Discharge Machining (EDM). In the absence of exposed and aged material tensile data, literature data were used for demonstrating the methodology in terms of the helium-3 concentration in the metal and the depth of penetration in the reservoir sidewall. It can be shown that the volume ductility decreases significantly with the presence of tritium and its decay product, helium-3, in the metal, as was observed in the laboratory-controlled burst tests. The model and analytical procedure provides a predictive tool for reservoir structural integrity under aging conditions. It is recommended that benchmark tests and analysis for aged materials be performed. The methodology can be augmented to predict performance for reservoir with flaws.

  14. Can Creativity Predict Cognitive Reserve? (United States)

    Palmiero, Massimiliano; Di Giacomo, Dina; Passafiume, Domenico


    Cognitive reserve relies on the ability to effectively cope with aging and brain damage by using alternate processes to approach tasks when standard approaches are no longer available. In this study, the issue if creativity can predict cognitive reserve has been explored. Forty participants (mean age: 61 years) filled out: the Cognitive Reserve…

  15. Predictive medical information and underwriting. (United States)

    Dodge, John H


    Medical underwriting involves the application of actuarial science by analyzing medical information to predict the future risk of a claim. The objective is that individuals with like risk are treated in a like manner so that the premium paid is proportional to the risk of future claim.

  16. Working postures: prediction and evaluation

    NARCIS (Netherlands)

    Delleman, N.J.


    To date, workstation designers cannot see the effects of a design on working posture before a mock-up/prototype is available. At that moment, usually the margin for creating the conditions required for adopting favourable working postures is still very limited. Posture prediction at an early design

  17. Evaluation of environmental impact predictions

    International Nuclear Information System (INIS)

    Cunningham, P.A.; Adams, S.M.; Kumar, K.D.


    An analysis and evaluation of the ecological monitoring program at the Surry Nuclear Power Plant showed that predictions of potential environmental impact made in the Final Environmental Statement (FES), which were based on generally accepted ecological principles, were not completely substantiated by environmental monitoring data. The Surry Nuclear Power Plant (Units 1 and 2) was chosen for study because of the facility's relatively continuous operating history and the availability of environmental data adequate for analysis. Preoperational and operational fish monitoring data were used to assess the validity of the FES prediction that fish would congregate in the thermal plume during winter months and would avoid the plume during summer months. Analysis of monitoring data showed that fish catch per unit effort (CPE) was generally high in the thermal plume during winter months; however, the highest fish catches occurred in the plume during the summer. Possible explanations for differences between the FES prediction and results observed in analysis of monitoring data are discussed, and general recommendations are outlined for improving impact assessment predictions

  18. Predictability of weather and climate

    National Research Council Canada - National Science Library

    Palmer, Tim; Hagedorn, Renate


    ... and anthropogenic climate change are among those included. Ensemble systems for forecasting predictability are discussed extensively. Ed Lorenz, father of chaos theory, makes a contribution to theoretical analysis with a previously unpublished paper. This well-balanced volume will be a valuable resource for many years. High-quality chapter autho...

  19. Prediction of electric vehicle penetration. (United States)


    The object of this report is to present the current market status of plug-in-electric : vehicles (PEVs) and to predict their future penetration within the world and U.S. : markets. The sales values for 2016 show a strong year of PEV sales both in the...

  20. What do saliency models predict? (United States)

    Koehler, Kathryn; Guo, Fei; Zhang, Sheng; Eckstein, Miguel P.


    Saliency models have been frequently used to predict eye movements made during image viewing without a specified task (free viewing). Use of a single image set to systematically compare free viewing to other tasks has never been performed. We investigated the effect of task differences on the ability of three models of saliency to predict the performance of humans viewing a novel database of 800 natural images. We introduced a novel task where 100 observers made explicit perceptual judgments about the most salient image region. Other groups of observers performed a free viewing task, saliency search task, or cued object search task. Behavior on the popular free viewing task was not best predicted by standard saliency models. Instead, the models most accurately predicted the explicit saliency selections and eye movements made while performing saliency judgments. Observers' fixations varied similarly across images for the saliency and free viewing tasks, suggesting that these two tasks are related. The variability of observers' eye movements was modulated by the task (lowest for the object search task and greatest for the free viewing and saliency search tasks) as well as the clutter content of the images. Eye movement variability in saliency search and free viewing might be also limited by inherent variation of what observers consider salient. Our results contribute to understanding the tasks and behavioral measures for which saliency models are best suited as predictors of human behavior, the relationship across various perceptual tasks, and the factors contributing to observer variability in fixational eye movements. PMID:24618107

  1. Using Predictability for Lexical Segmentation. (United States)

    Çöltekin, Çağrı


    This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.

  2. Predictability of Mobile Phone Associations

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Larsen, Jan; Hansen, Lars Kai


    Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how the predi......Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how...... the predictability of mobile sensors, acting as proxies for humans, change with time scale and sensor type such as GSM and WLAN. Applying recent information theoretic methods, it is demonstrated that an upper bound on predictability is relatively high for all sensors given the complete history (typically above 90...... representation, and general behavior. This is of vital interest in the development of context-aware services which rely on forecasting based on mobile phone sensors....

  3. Prediction of Subsidence Depression Development

    Czech Academy of Sciences Publication Activity Database

    Doležalová, Hana; Kajzar, Vlastimil


    Roč. 6, č. 4 (2017), s. 208-214 E-ISSN 2391-9361. [Cross-border Exchange of Experience in Production Engineering Using Principles of Mathematics. Rybnik, 07.06.2017-09.06.2017] Institutional support: RVO:68145535 Keywords : undermining * prediction * regression analysis Subject RIV: DH - Mining, incl. Coal Mining OBOR OECD: Mining and mineral processing

  4. Predicting the Divorce Rate: Down? (United States)

    Kemper, Theodore D.


    Predicted a decline in the divorce rate based on 10 factors including: decline in marriage rate, older age at marriage, mental health improvement, upper limit on employed women, less migration, end of the cultural revolution, exhaustion of latency effect of no-fault divorce, and fear of the consequences of divorce. (JAC)

  5. Prospects for Predicting Cycle 24

    Indian Academy of Sciences (India)


    feeding' information about the polar field at the minima. Following this process, we find that our model fits the observed sunspot numbers of cycles 21–23 reasonably well and predicts that cycle 24 will be the weakest in a century.

  6. Predicting Character Traits Through Reddit (United States)


    and even employers (Res). Companies like Netflix also use personality classification algorithms in order to provide users with predictions of behind the netflix algorithms that decide what to watch next, August 2013. Reza Zafarani and Huan Liu. Evaluation without ground truth in social media research. Communications Of The ACM, 58(6):54–60, June 2015. 12

  7. Focus on astronomical predictable events

    DEFF Research Database (Denmark)

    Jacobsen, Aase Roland


    At the Steno Museum Planetarium we have for many occasions used a countdown clock to get focus om astronomical events. A countdown clock can provide actuality to predictable events, for example The Venus Transit, Opportunity landing on Mars and The Solar Eclipse. The movement of the clock attracs...

  8. Cast iron - a predictable material

    Directory of Open Access Journals (Sweden)

    Jorg C. Sturm


    Full Text Available High strength compacted graphite iron (CGI or alloyed cast iron components are substituting previously used non-ferrous castings in automotive power train applications. The mechanical engineering industry has recognized the value in substituting forged or welded structures with stiff and light-weight cast iron castings. New products such as wind turbines have opened new markets for an entire suite of highly reliable ductile iron cast components. During the last 20 years, casting process simulation has developed from predicting hot spots and solidification to an integral assessment tool for foundries for the entire manufacturing route of castings. The support of the feeding related layout of the casting is still one of the most important duties for casting process simulation. Depending on the alloy poured, different feeding behaviors and self-feeding capabilities need to be considered to provide a defect free casting. Therefore, it is not enough to base the prediction of shrinkage defects solely on hot spots derived from temperature fields. To be able to quantitatively predict these defects, solidification simulation had to be combined with density and mass transport calculations, in order to evaluate the impact of the solidification morphology on the feeding behavior as well as to consider alloy dependent feeding ranges. For cast iron foundries, the use of casting process simulation has become an important instrument to predict the robustness and reliability of their processes, especially since the influence of alloying elements, melting practice and metallurgy need to be considered to quantify the special shrinkage and solidification behavior of cast iron. This allows the prediction of local structures, phases and ultimately the local mechanical properties of cast irons, to asses casting quality in the foundry but also to make use of this quantitative information during design of the casting. Casting quality issues related to thermally driven

  9. Contextual predictability shapes signal autonomy. (United States)

    Winters, James; Kirby, Simon; Smith, Kenny


    Aligning on a shared system of communication requires senders and receivers reach a balance between simplicity, where there is a pressure for compressed representations, and informativeness, where there is a pressure to be communicatively functional. We investigate the extent to which these two pressures are governed by contextual predictability: the amount of contextual information that a sender can estimate, and therefore exploit, in conveying their intended meaning. In particular, we test the claim that contextual predictability is causally related to signal autonomy: the degree to which a signal can be interpreted in isolation, without recourse to contextual information. Using an asymmetric communication game, where senders and receivers are assigned fixed roles, we manipulate two aspects of the referential context: (i) whether or not a sender shares access to the immediate contextual information used by the receiver in interpreting their utterance; (ii) the extent to which the relevant solution in the immediate referential context is generalisable to the aggregate set of contexts. Our results demonstrate that contextual predictability shapes the degree of signal autonomy: when the context is highly predictable (i.e., the sender has access to the context in which their utterances will be interpreted, and the semantic dimension which discriminates between meanings in context is consistent across communicative episodes), languages develop which rely heavily on the context to reduce uncertainty about the intended meaning. When the context is less predictable, senders favour systems composed of autonomous signals, where all potentially relevant semantic dimensions are explicitly encoded. Taken together, these results suggest that our pragmatic faculty, and how it integrates information from the context in reducing uncertainty, plays a central role in shaping language structure. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. Ocean eddies and climate predictability. (United States)

    Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo


    A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

  11. Predicting outcome of status epilepticus. (United States)

    Leitinger, M; Kalss, G; Rohracher, A; Pilz, G; Novak, H; Höfler, J; Deak, I; Kuchukhidze, G; Dobesberger, J; Wakonig, A; Trinka, E


    Status epilepticus (SE) is a frequent neurological emergency complicated by high mortality and often poor functional outcome in survivors. The aim of this study was to review available clinical scores to predict outcome. Literature review. PubMed Search terms were "score", "outcome", and "status epilepticus" (April 9th 2015). Publications with abstracts available in English, no other language restrictions, or any restrictions concerning investigated patients were included. Two scores were identified: "Status Epilepticus Severity Score--STESS" and "Epidemiology based Mortality score in SE--EMSE". A comprehensive comparison of test parameters concerning performance, options, and limitations was performed. Epidemiology based Mortality score in SE allows detailed individualization of risk factors and is significantly superior to STESS in a retrospective explorative study. In particular, EMSE is very good at detection of good and bad outcome, whereas STESS detecting bad outcome is limited by a ceiling effect and uncertainty of correct cutoff value. Epidemiology based Mortality score in SE can be adapted to different regions in the world and to advances in medicine, as new data emerge. In addition, we designed a reporting standard for status epilepticus to enhance acquisition and communication of outcome relevant data. A data acquisition sheet used from patient admission in emergency room, from the EEG lab to intensive care unit, is provided for optimized data collection. Status Epilepticus Severity Score is easy to perform and predicts bad outcome, but has a low predictive value for good outcomes. Epidemiology based Mortality score in SE is superior to STESS in predicting good or bad outcome but needs marginally more time to perform. Epidemiology based Mortality score in SE may prove very useful for risk stratification in interventional studies and is recommended for individual outcome prediction. Prospective validation in different cohorts is needed for EMSE, whereas

  12. Ensemble streamflow predictions: from climate scenarios to probabilistic weather predictions (United States)

    Fortin, V.; Evora, N.; Perreault, L.; Trinh, N.; Favre, A.; Benoit, H.


    Ensemble streamflow predictions (ESP) are obtained by processing an ensemble of meteorological scenarios through a rainfall-runoff hydrological model to obtain hydrological scenarios. Until recently, these scenarios were typically taken from the climatology. Now that more accurate medium- and long-term numerical weather predictions (NWP) are available, it is tempting to replace climatology by numerical weather forecasts. At least two approaches are possible to take into account the uncerta1000 inty on the meteorological forecast: (1) let a meteorologist propose a subjective probabilistic forecast based on one or more deterministic NWPs, or (2) take advantage of ensemble meteorological forecasts, which are built precisely to assess the level of uncertainty on the deterministic forecast. Practical solutions to problems encountered with both types of meteorological forecasts are discussed, and the methodology used by Hydro-Québec to score the resulting streamflow forecasts is presented.

  13. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik


    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

  14. MPC-Relevant Prediction-Error Identification

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay


    A prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space m...

  15. Semen analysis and prediction of natural conception

    NARCIS (Netherlands)

    Leushuis, Esther; van der Steeg, Jan Willem; Steures, Pieternel; Repping, Sjoerd; Bossuyt, Patrick M. M.; Mol, Ben Willem J.; Hompes, Peter G. A.; van der Veen, Fulco


    Do two semen analyses predict natural conception better than a single semen analysis and will adding the results of repeated semen analyses to a prediction model for natural pregnancy improve predictions? A second semen analysis does not add helpful information for predicting natural conception

  16. 1997 Volvo Award winner in basic science studies. Immunohistologic markers for age-related changes of human lumbar intervertebral discs. (United States)

    Nerlich, A G; Schleicher, E D; Boos, N


    The authors performed a correlative macroscopic, histologic, and immunohistochemical investigation on human lumbar intervertebral discs using complete motion segment slices, including all age groups and stages of degeneration. To identify markers for age-related changes of human lumbar intervertebral discs. In particular, to investigate changes in the distribution pattern of collagen Types I, II, III, IV, V, VI, IX, and X. In addition, to study posttranslational protein modification by the immunolocalization of N-(carboxylmethyl)lysine (CML), which is regarded as a biomarker for oxidative stress. Data on a correlation of age-related changes in disc morphology and disc matrix composition is sparse. So far, no comprehensive analysis considered a correlation of macroscopic, histologic, and biochemical age-related alterations using complete sections of intervertebral discs (i.e., including nucleus pulposus, anulus fibrosus, endplates, and vertebral bodies). In addition, there is need for specific markers for these disc changes to allow for a better correlation with disc function. After photodocumentation of the macroscopic appearance, 229 sagittal lumbar motion segments obtained from 47 individuals (fetal to 86 years) during routine autopsy were processed for histologic and immunohistochemical analysis. All slices were investigated for histologic alterations of disc degeneration. A randomly selected subset of these specimens (n = 45) was used for a correlative analysis of interstitial collagens and molecular modifications of matrix proteins. The presence of CML-modification of extracellular matrix proteins, mainly collagen, was observed first in the nucleus pulposus of a 13-year-old individual and increased significantly with age. In elderly people, both the nucleus pulposus and the anulus fibrosus showed extensive CML deposition. This CML deposition was accentuated in areas of macroscopic and histologic disc degeneration. After the occurrence of CML in the nucleus

  17. Multiphase, multicomponent phase behavior prediction (United States)

    Dadmohammadi, Younas

    Accurate prediction of phase behavior of fluid mixtures in the chemical industry is essential for designing and operating a multitude of processes. Reliable generalized predictions of phase equilibrium properties, such as pressure, temperature, and phase compositions offer an attractive alternative to costly and time consuming experimental measurements. The main purpose of this work was to assess the efficacy of recently generalized activity coefficient models based on binary experimental data to (a) predict binary and ternary vapor-liquid equilibrium systems, and (b) characterize liquid-liquid equilibrium systems. These studies were completed using a diverse binary VLE database consisting of 916 binary and 86 ternary systems involving 140 compounds belonging to 31 chemical classes. Specifically the following tasks were undertaken: First, a comprehensive assessment of the two common approaches (gamma-phi (gamma-ϕ) and phi-phi (ϕ-ϕ)) used for determining the phase behavior of vapor-liquid equilibrium systems is presented. Both the representation and predictive capabilities of these two approaches were examined, as delineated form internal and external consistency tests of 916 binary systems. For the purpose, the universal quasi-chemical (UNIQUAC) model and the Peng-Robinson (PR) equation of state (EOS) were used in this assessment. Second, the efficacy of recently developed generalized UNIQUAC and the nonrandom two-liquid (NRTL) for predicting multicomponent VLE systems were investigated. Third, the abilities of recently modified NRTL model (mNRTL2 and mNRTL1) to characterize liquid-liquid equilibria (LLE) phase conditions and attributes, including phase stability, miscibility, and consolute point coordinates, were assessed. The results of this work indicate that the ϕ-ϕ approach represents the binary VLE systems considered within three times the error of the gamma-ϕ approach. A similar trend was observed for the for the generalized model predictions using

  18. Predictive Analytics in Information Systems Research


    Shmueli, Galit; Koppius, Otto


    textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory bu...

  19. Time-Predictable Virtual Memory

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang; Schoeberl, Martin


    Virtual memory is an important feature of modern computer architectures. For hard real-time systems, memory protection is a particularly interesting feature of virtual memory. However, current memory management units are not designed for time-predictability and therefore cannot be used...... in such systems. This paper investigates the requirements on virtual memory from the perspective of hard real-time systems and presents the design of a time-predictable memory management unit. Our evaluation shows that the proposed design can be implemented efficiently. The design allows address translation...... and address range checking in constant time of two clock cycles on a cache miss. This constant time is in strong contrast to the possible cost of a miss in a translation look-aside buffer in traditional virtual memory organizations. Compared to a platform without a memory management unit, these two additional...

  20. Time-Predictable Computer Architecture

    Directory of Open Access Journals (Sweden)

    Schoeberl Martin


    Full Text Available Today's general-purpose processors are optimized for maximum throughput. Real-time systems need a processor with both a reasonable and a known worst-case execution time (WCET. Features such as pipelines with instruction dependencies, caches, branch prediction, and out-of-order execution complicate WCET analysis and lead to very conservative estimates. In this paper, we evaluate the issues of current architectures with respect to WCET analysis. Then, we propose solutions for a time-predictable computer architecture. The proposed architecture is evaluated with implementation of some features in a Java processor. The resulting processor is a good target for WCET analysis and still performs well in the average case.

  1. Serious Gaming for Predictive Analytics

    Energy Technology Data Exchange (ETDEWEB)

    Riensche, Roderick M.; Paulson, Patrick R.; Danielson, Gary R.; Unwin, Stephen D.; Butner, R. Scott; Miller, Sarah M.; Franklin, Lyndsey; Zuljevic, Nino


    We describe a methodology and architecture to support the development of games in a predictive analytics context. These games serve as part of an overall family of systems designed to gather input knowledge, calculate results of complex predictive technical and social models, and explore those results in an engaging fashion. The games provide an environment shaped and driven in part by the outputs of the models, allowing users to exert influence over a limited set of parameters, and displaying the results when those actions cause changes in the underlying model. We have crafted a prototype system in which we are implementing test versions of games driven by models in such a fashion, using a flexible architecture to allow for future continuation and expansion of this work.

  2. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

    ) and contact number (CN) measures only. We show that the HSE measure is much more information-rich than CN, nevertheless, HSE does not appear to provide enough information to reconstruct the C-traces of real-sized proteins. Our experiments also show that using tabu search (with our novel tabu definition......The problem of predicting the three-dimensional structure of a protein given its amino acid sequence is one of the most important open problems in bioinformatics. One of the carbon atoms in amino acids is the C-atom and the overall structure of a protein is often represented by a so-called C...... is competitive in quality and speed with other state-of-the-art decoy generation algorithms. Our third C-trace reconstruction approach is based on bee-colony optimization [24]. We demonstrate why this algorithm has some important properties that makes it suitable for protein structure prediction. Our approach...

  3. Predicting responses from Rasch measures. (United States)

    Linacre, John M


    There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

  4. Butterfly valve torque prediction methodology

    International Nuclear Information System (INIS)

    Eldiwany, B.H.; Sharma, V.; Kalsi, M.S.; Wolfe, K.


    As part of the Motor-Operated Valve (MOV) Performance Prediction Program, the Electric Power Research Institute has sponsored the development of methodologies for predicting thrust and torque requirements of gate, globe, and butterfly MOVs. This paper presents the methodology that will be used by utilities to calculate the dynamic torque requirements for butterfly valves. The total dynamic torque at any disc position is the sum of the hydrodynamic torque, bearing torque (which is induced by the hydrodynamic force), as well as other small torque components (such as packing torque). The hydrodynamic torque on the valve disc, caused by the fluid flow through the valve, depends on the disc angle, flow velocity, upstream flow disturbances, disc shape, and the disc aspect ratio. The butterfly valve model provides sets of nondimensional flow and torque coefficients that can be used to predict flow rate and hydrodynamic torque throughout the disc stroke and to calculate the required actuation torque and the maximum transmitted torque throughout the opening and closing stroke. The scope of the model includes symmetric and nonsymmetric discs of different shapes and aspects ratios in compressible and incompressible fluid applications under both choked and nonchoked flow conditions. The model features were validated against test data from a comprehensive flowloop and in situ test program. These tests were designed to systematically address the effect of the following parameters on the required torque: valve size, disc shapes and disc aspect ratios, upstream elbow orientation and its proximity, and flow conditions. The applicability of the nondimensional coefficients to valves of different sizes was validated by performing tests on 42-in. valve and a precisely scaled 6-in. model. The butterfly valve model torque predictions were found to bound test data from the flow-loop and in situ testing, as shown in the examples provided in this paper

  5. Predicting progression of Alzheimer's disease. (United States)

    Doody, Rachelle S; Pavlik, Valory; Massman, Paul; Rountree, Susan; Darby, Eveleen; Chan, Wenyaw


    Clinicians need to predict prognosis of Alzheimer's disease (AD), and researchers need models of progression to develop biomarkers and clinical trials designs. We tested a calculated initial progression rate to see whether it predicted performance on cognition, function and behavior over time, and to see whether it predicted survival. We used standardized approaches to assess baseline characteristics and to estimate disease duration, and calculated the initial (pre-progression) rate in 597 AD patients followed for up to 15 years. We designated slow, intermediate and rapidly progressing groups. Using mixed effects regression analysis, we examined the predictive value of a pre-progression group for longitudinal performance on standardized measures. We used Cox survival analysis to compare survival time by progression group. Patients in the slow and intermediate groups maintained better performance on the cognitive (ADAScog and VSAT), global (CDR-SB) and complex activities of daily living measures (IADL) (P values < 0.001 slow versus fast; P values < 0.003 to 0.03 intermediate versus fast). Interaction terms indicated that slopes of ADAScog and PSMS change for the slow group were smaller than for the fast group, and that rates of change on the ADAScog were also slower for the intermediate group, but that CDR-SB rates increased in this group relative to the fast group. Slow progressors survived longer than fast progressors (P = 0.024). A simple, calculated progression rate at the initial visit gives reliable information regarding performance over time on cognition, global performance and activities of daily living. The slowest progression group also survives longer. This baseline measure should be considered in the design of long duration Alzheimer's disease clinical trials.

  6. Dim prospects for earthquake prediction (United States)

    Geller, Robert J.

    I was misquoted by C. Lomnitz's [1998] Forum letter (Eos, August 4, 1998, p. 373), which said: [I wonder whether Sasha Gusev [1998] actually believes that branding earthquake prediction a ‘proven nonscience’ [Geller, 1997a] is a paradigm for others to copy.”Readers are invited to verify for themselves that neither “proven nonscience” norv any similar phrase was used by Geller [1997a].

  7. Asthma exacerbation prediction: recent insights. (United States)

    Fleming, Louise


    Asthma attacks are frequent in children with asthma and can lead to significant adverse outcomes including time off school, hospital admission and death. Identifying children at risk of an asthma attack affords the opportunity to prevent attacks and improve outcomes. Clinical features, patient behaviours and characteristics, physiological factors, environmental data and biomarkers are all associated with asthma attacks and can be used in asthma exacerbation prediction models. Recent studies have better characterized children at risk of an attack: history of a severe exacerbation in the previous 12 months, poor adherence and current poor control are important features which should alert healthcare professionals to the need for remedial action. There is increasing interest in the use of biomarkers. A number of novel biomarkers, including patterns of volatile organic compounds in exhaled breath, show promise. Biomarkers are likely to be of greatest utility if measured frequently and combined with other measures. To date, most prediction models are based on epidemiological data and population-based risk. The use of digital technology affords the opportunity to collect large amounts of real-time data, including clinical and physiological measurements and combine these with environmental data to develop personal risk scores. These developments need to be matched by changes in clinical guidelines away from a focus on current asthma control and stepwise escalation in drug therapy towards inclusion of personal risk scores and tailored management strategies including nonpharmacological approaches. There have been significant steps towards personalized prediction models of asthma attacks. The utility of such models needs to be tested in the ability not only to predict attacks but also to reduce them.

  8. Shoulder Dystocia: Prediction and Management


    Hill, Meghan G; Cohen, Wayne R


    Shoulder dystocia is a complication of vaginal delivery and the primary factor associated with brachial plexus injury. In this review, we discuss the risk factors for shoulder dystocia and propose a framework for the prediction and prevention of the complication. A recommended approach to management when shoulder dystocia occurs is outlined, with review of the maneuvers used to relieve the obstruction with minimal risk of fetal and maternal injury.

  9. Shoulder dystocia: prediction and management. (United States)

    Hill, Meghan G; Cohen, Wayne R


    Shoulder dystocia is a complication of vaginal delivery and the primary factor associated with brachial plexus injury. In this review, we discuss the risk factors for shoulder dystocia and propose a framework for the prediction and prevention of the complication. A recommended approach to management when shoulder dystocia occurs is outlined, with review of the maneuvers used to relieve the obstruction with minimal risk of fetal and maternal injury.

  10. Nonparametric predictive inference in reliability

    International Nuclear Information System (INIS)

    Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.


    We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere

  11. Calibration of decadal ensemble predictions (United States)

    Pasternack, Alexander; Rust, Henning W.; Bhend, Jonas; Liniger, Mark; Grieger, Jens; Müller, Wolfgang; Ulbrich, Uwe


    Decadal climate predictions are of great socio-economic interest due to the corresponding planning horizons of several political and economic decisions. Due to uncertainties of weather and climate, forecasts (e.g. due to initial condition uncertainty), they are issued in a probabilistic way. One issue frequently observed for probabilistic forecasts is that they tend to be not reliable, i.e. the forecasted probabilities are not consistent with the relative frequency of the associated observed events. Thus, these kind of forecasts need to be re-calibrated. While re-calibration methods for seasonal time scales are available and frequently applied, these methods still have to be adapted for decadal time scales and its characteristic problems like climate trend and lead time dependent bias. Regarding this, we propose a method to re-calibrate decadal ensemble predictions that takes the above mentioned characteristics into account. Finally, this method will be applied and validated to decadal forecasts from the MiKlip system (Germany's initiative for decadal prediction).

  12. Predicting human gaze beyond pixels. (United States)

    Xu, Juan; Jiang, Ming; Wang, Shuo; Kankanhalli, Mohan S; Zhao, Qi


    A large body of previous models to predict where people look in natural scenes focused on pixel-level image attributes. To bridge the semantic gap between the predictive power of computational saliency models and human behavior, we propose a new saliency architecture that incorporates information at three layers: pixel-level image attributes, object-level attributes, and semantic-level attributes. Object- and semantic-level information is frequently ignored, or only a few sample object categories are discussed where scaling to a large number of object categories is not feasible nor neurally plausible. To address this problem, this work constructs a principled vocabulary of basic attributes to describe object- and semantic-level information thus not restricting to a limited number of object categories. We build a new dataset of 700 images with eye-tracking data of 15 viewers and annotation data of 5,551 segmented objects with fine contours and 12 semantic attributes (publicly available with the paper). Experimental results demonstrate the importance of the object- and semantic-level information in the prediction of visual attention.

  13. Fas ligand exists on intervertebral disc cells: a potential molecular mechanism for immune privilege of the disc. (United States)

    Takada, Toru; Nishida, Kotaro; Doita, Minoru; Kurosaka, Masahiro


    Rat and human intervertebral disc specimens were examined immunohistochemically. Reverse transcription polymerase chain reaction (RT-PCR) analysis was also performed on rat disc tissue to demonstrate the existence of Fas ligand. To clarify the existence of Fas ligand on intact intervertebral disc cells. The nucleus pulposus has been reported to be an immune-privileged site. The immune-privileged characteristic in other tissues such as the retina and testis has been attributed to the local expression of Fas ligand, which acts by inducing apoptosis of invading Fas-positive T-cells. The existence of Fas ligand in normal disc cells has not yet been addressed. Skeletally mature SD male rats were killed, and the coccygeal discs were harvested. Human disc specimens were obtained from idiopathic scoliosis patients during surgical procedures. Immunohistochemical staining for Fas ligand was performed for cross-sections of the discs by standard procedures. Reverse transcription polymerase chain reaction analysis was also carried out to demonstrate Fas ligand mRNA expression on rat intervertebral discs. Testes of the rats were used for positive controls, and muscles were used for negative controls. The sections were observed by light microscopy. The nucleus pulposus cells exhibited intense positive immune staining for Fas ligand. The outer anulus fibrosus cells and notochordal cells exhibited little immunopositivity. The positive controls exhibited positive immune staining, and the negative control showed no immunopositivity. The result of RT-PCR confirmed the existence of Fas ligand in disc cells. The human nucleus pulposus cells showed a similar predilection to rat disc cells. We demonstrated the existence of Fas ligand on disc cells, which should play a key role in the potential molecular mechanism to maintain immune privilege of the disc. Immune privilege and Fas ligand expression of the intervertebral disc may provide a new insight for basic science research as well as

  14. A potential role of thymic stromal lymphopoietin in the recruitment of macrophages to mouse intervertebral disc cells via monocyte chemotactic protein 1 induction: implications for herniated discs. (United States)

    Ohba, Tetsuro; Haro, Hirotaka; Ando, Takashi; Koyama, Kensuke; Hatsushika, Kyosuke; Suenaga, Fumiko; Ohnuma, Yuko; Nakamura, Yuki; Katoh, Ryohei; Ogawa, Hideoki; Hamada, Yoshiki; Nakao, Atsuhito


    To determine whether thymic stromal lymphopoietin (TSLP) plays a role in the resorption of herniated disc tissue. The expression of TSLP messenger RNA (mRNA) and protein in mouse intervertebral disc cells was assessed by quantitative real-time polymerase chain reaction, enzyme-linked immunosorbent assay (ELISA), and immunohistochemical analysis. The ability of mouse intervertebral disc cells to respond to TSLP stimulation was examined by Western blot analysis, ELISA, and protein array analysis. Intracellular signaling pathways involved in TSLP signaling in mouse intervertebral disc cells were investigated using several chemical inhibitors. The role of TSLP in macrophage migration into the intervertebral disc was assessed by in vitro migration assay. Finally, TSLP expression in clinical specimens derived from patients with a herniated disc was examined by immunohistochemistry. Mouse intervertebral disc cells expressed TSLP mRNA and protein upon stimulation with NF-kappaB-activating ligands such as tumor necrosis factor alpha. In addition, the mouse intervertebral disc cells expressed the TSLP receptor and produced monocyte chemotactic protein 1 (MCP-1; CCL2) and macrophage colony-stimulating factor in response to TSLP stimulation. Both anulus fibrosus and nucleus pulposus intervertebral disc cells expressed MCP-1 upon TSLP stimulation, which was mediated via the phosphatidylinositol 3-kinase/Akt pathway. Consistently, the supernatants of TSLP-activated intervertebral disc cultures had the capacity to induce macrophage migration in an MCP-1-dependent manner. Finally, TSLP and MCP-1 were coexpressed in human herniated disc specimens in which macrophage infiltration into the tissue was observed. TSLP induced by NF-kappaB-activating ligands in intervertebral discs may contribute to the recruitment of macrophages to the intervertebral disc by stimulating MCP-1 production and may be involved in the resorption of herniated disc tissue.

  15. MR imaging of lumbar herniated intervertebral disc and spinal stenosis: Correlation with CT

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Won Jae; Park, Kil Sun; Chang, Kee Hyun; Han, Moon Hee; Kim, Hyun Jip; Han, Man Chung; Kim, Chu Wan [Seoul National University College of Medicine, Seoul (Korea, Republic of)


    MR imagings obtained in 40 patients with surgically proven lumbar herniated intervertebral disc (HIVD) and/or spinal stenosis were retrospectively analysed and compared with CT scans, in order to evaluate the MR findings of HIVD and spinal stenosis, and to assess the diagnostic accuracy of MR. The MR imaging was performed on a 2.0 T superconducting unit, using multislice spin echo (SE) and gradient echo (GE) techniques. The results were as follows: 1. The texture of vertebral body with spinal stenosis had the tendency to be more heterogeneous than that with HIVD. 2. The signal intensity of the diseased disc was isointense relative to normal disc in 81 % (60/74) and the remainder (19%) was hypointense on both T1 weighted SE and GE images. There was no significant difference in signal intensity among HIVD, HIVD combined with spinal stenosis and spinal stenosis groups, but there was the tendency of lower signal intensity of the diseased disc in patients with severe degenerative change of spine in both T1 weighted SE imaged and GE image. 3. The diagnostic accuracy of MR was 92%, which was similar to that of CT. 4. T1 weighted SE image appears superior to GE image in evaluation of most of the structural differentiation, but as for differentiating between lumina and ligamentum flavum, and for the vacuum phenomenon, GE image seems to be better than T1 weighted SE image. In conclusion, MR appears to be better than CT as a initial imaging modality in evaluation of the patients with suspected lumbar spinal stenosis or HIVD because MR has the capability of demonstrating rupture of anulus fibrosus in sagittal plane.

  16. Using Predictive Analytics to Predict Power Outages from Severe Weather (United States)

    Wanik, D. W.; Anagnostou, E. N.; Hartman, B.; Frediani, M. E.; Astitha, M.


    The distribution of reliable power is essential to businesses, public services, and our daily lives. With the growing abundance of data being collected and created by industry (i.e. outage data), government agencies (i.e. land cover), and academia (i.e. weather forecasts), we can begin to tackle problems that previously seemed too complex to solve. In this session, we will present newly developed tools to aid decision-support challenges at electric distribution utilities that must mitigate, prepare for, respond to and recover from severe weather. We will show a performance evaluation of outage predictive models built for Eversource Energy (formerly Connecticut Light & Power) for storms of all types (i.e. blizzards, thunderstorms and hurricanes) and magnitudes (from 20 to >15,000 outages). High resolution weather simulations (simulated with the Weather and Research Forecast Model) were joined with utility outage data to calibrate four types of models: a decision tree (DT), random forest (RF), boosted gradient tree (BT) and an ensemble (ENS) decision tree regression that combined predictions from DT, RF and BT. The study shows that the ENS model forced with weather, infrastructure and land cover data was superior to the other models we evaluated, especially in terms of predicting the spatial distribution of outages. This research has the potential to be used for other critical infrastructure systems (such as telecommunications, drinking water and gas distribution networks), and can be readily expanded to the entire New England region to facilitate better planning and coordination among decision-makers when severe weather strikes.

  17. Wine Expertise Predicts Taste Phenotype (United States)

    Hayes, John E; Pickering, Gary J


    Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance – with appropriate caveats about populations tested, outcomes measured and psychophysical methods used – an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli. PMID:22888174

  18. Developmental dyslexia: predicting individual risk. (United States)

    Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J


    Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as 'dyslexic' or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by

  19. Laser line scan performance prediction (United States)

    Mahoney, Kevin L.; Schofield, Oscar; Kerfoot, John; Giddings, Tom; Shirron, Joe; Twardowski, Mike


    The effectiveness of sensors that use optical measurements for the laser detection and identification of subsurface mines is directly related to water clarity. The primary objective of the work presented here was to use the optical data collected by UUV (Slocum Glider) surveys of an operational areas to estimate the performance of an electro-optical identification (EOID) Laser Line Scan (LLS) system during RIMPAC 06, an international naval exercise off the coast of Hawaii. Measurements of optical backscattering and beam attenuation were made with a Wet Labs, Inc. Scattering Absorption Meter (SAM), mounted on a Rutgers University/Webb Research Slocum glider. The optical data universally indicated extremely clear water in the operational area, except very close to shore. The beam-c values from the SAM sensor were integrated to three attenuation lengths to provide an estimate of how well the LLS would perform in detecting and identifying mines in the operational areas. Additionally, the processed in situ optical data served as near-real-time input to the Electro-Optic Detection Simulator, ver. 3 (EODES-3; Metron, Inc.) model for EOID performance prediction. Both methods of predicting LLS performance suggested a high probability of detection and probability of identification. These predictions were validated by the actual performance of the LLS as the EOID system yielded imagery from which reliable mine identification could be made. Future plans include repeating this work in more optically challenging water types to demonstrate the utility of pre-mission UUV surveys of operational areas as a tactical decision aid for planning EOID missions.

  20. Zephyr - the next generation prediction

    DEFF Research Database (Denmark)

    Giebel, G.; Landberg, L.; Nielsen, Torben Skov


    Technical University. This paper will describe a new project funded by the Danish Ministry of Energy where the largest Danish utilities (Elkraft, Elsam, Eltra and SEAS) are participating. Two advantages can be achieved by combining the effort: The software architecture will be state-of-the-art, using...... the Java2TM platform and Enterprise Java Beans technology, and it will ensure that the best forecasts are given on all prediction horizons from the short range (0-9 hours) to the long range (36-48 hours). This is because the IMM approach uses online data and advanced statistical methods, which...

  1. Making predictions in the multiverse

    Energy Technology Data Exchange (ETDEWEB)

    Freivogel, Ben, E-mail: [Center for Theoretical Physics and Laboratory for Nuclear Science, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)


    I describe reasons to think we are living in an eternally inflating multiverse where the observable 'constants' of nature vary from place to place. The major obstacle to making predictions in this context is that we must regulate the infinities of eternal inflation. I review a number of proposed regulators, or measures. Recent work has ruled out a number of measures by showing that they conflict with observation, and focused attention on a few proposals. Further, several different measures have been shown to be equivalent. I describe some of the many nontrivial tests these measures will face as we learn more from theory, experiment and observation.

  2. Aviation turbulence processes, detection, prediction

    CERN Document Server

    Lane, Todd


    Anyone who has experienced turbulence in flight knows that it is usually not pleasant, and may wonder why this is so difficult to avoid. The book includes papers by various aviation turbulence researchers and provides background into the nature and causes of atmospheric turbulence that affect aircraft motion, and contains surveys of the latest techniques for remote and in situ sensing and forecasting of the turbulence phenomenon. It provides updates on the state-of-the-art research since earlier studies in the 1960s on clear-air turbulence, explains recent new understanding into turbulence generation by thunderstorms, and summarizes future challenges in turbulence prediction and avoidance.

  3. Flooding Fragility Experiments and Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Tahhan, Antonio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Muchmore, Cody [Idaho National Lab. (INL), Idaho Falls, ID (United States); Nichols, Larinda [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bhandari, Bishwo [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pope, Chad [Idaho National Lab. (INL), Idaho Falls, ID (United States)


    This report describes the work that has been performed on flooding fragility, both the experimental tests being carried out and the probabilistic fragility predictive models being produced in order to use the text results. Flooding experiments involving full-scale doors have commenced in the Portal Evaluation Tank. The goal of these experiments is to develop a full-scale component flooding experiment protocol and to acquire data that can be used to create Bayesian regression models representing the fragility of these components. This work is in support of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluation research and development.

  4. Mach's predictions and relativistic cosmology

    International Nuclear Information System (INIS)

    Heller, M.


    Deep methodological insight of Ernst Mach into the structure of the Newtonian mechanics allowed him to ask questions, the importance of which can be appreciated only today. Three such Mach's ''predictions'' are briefly presented, namely: the possibility of the existence of an allpervading medium which could serve as an universal frame of reference and which has actually been discovered in the form of the microwave background radiation, a certain ''smoothness'' of the Universe which is now recognized as the Robertson-Walker symmetries and the possibility of the experimental verification of the mass anisotropy. 11 refs. (author)

  5. Flooding Fragility Experiments and Prediction

    International Nuclear Information System (INIS)

    Smith, Curtis L.; Tahhan, Antonio; Muchmore, Cody; Nichols, Larinda; Bhandari, Bishwo; Pope, Chad


    This report describes the work that has been performed on flooding fragility, both the experimental tests being carried out and the probabilistic fragility predictive models being produced in order to use the text results. Flooding experiments involving full-scale doors have commenced in the Portal Evaluation Tank. The goal of these experiments is to develop a full-scale component flooding experiment protocol and to acquire data that can be used to create Bayesian regression models representing the fragility of these components. This work is in support of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluation research and development.

  6. Making predictions in the multiverse (United States)

    Freivogel, Ben


    I describe reasons to think we are living in an eternally inflating multiverse where the observable 'constants' of nature vary from place to place. The major obstacle to making predictions in this context is that we must regulate the infinities of eternal inflation. I review a number of proposed regulators, or measures. Recent work has ruled out a number of measures by showing that they conflict with observation, and focused attention on a few proposals. Further, several different measures have been shown to be equivalent. I describe some of the many nontrivial tests these measures will face as we learn more from theory, experiment and observation.

  7. Prediction of dislocation boundary characteristics

    DEFF Research Database (Denmark)

    Winther, Grethe

    orientation of the grain [1]. For selected boundaries it has been experimentally verified that the boundaries consist of fairly regular networks of dislocations, which come from the active slip systems [2]. The networks have been analyzed within the framework of Low-Energy-Dislocation-Structures (LEDS......, such as the dislocation content and misorientation. The prediction is based on the expected active slip systems and assumptions of mutual stress screening. In general, networks of dislocations with three linearly independent Burgers vectors fulfilling the criterion of mutual stress screening may form on any plane...

  8. Predicting word sense annotation agreement

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector; Johannsen, Anders Trærup; Lopez de Lacalle, Oier


    High agreement is a common objective when annotating data for word senses. However, a number of factors make perfect agreement impossible, e.g. the limitations of the sense inventories, the difficulty of the examples or the interpretation preferences of the annotations. Estimating potential...... agreement is thus a relevant task to supplement the evaluation of sense annotations. In this article we propose two methods to predict agreement on word-annotation instances. We experiment with a continuous representation and a three-way discretization of observed agreement. In spite of the difficulty...

  9. Predicting response to epigenetic therapy

    DEFF Research Database (Denmark)

    Treppendahl, Marianne B; Kristensen, Lasse S; Grønbæk, Kirsten


    Drugs targeting the epigenome are new promising cancer treatment modalities; however, not all patients receive the same benefit from these drugs. In contrast to conventional chemotherapy, responses may take several months after the initiation of treatment to occur. Accordingly, identification...... of good pretreatment predictors of response is of great value. Many clinical parameters and molecular targets have been tested in preclinical and clinical studies with varying results, leaving room for optimization. Here we provide an overview of markers that may predict the efficacy of FDA- and EMA...

  10. Expansion tube test time predictions (United States)

    Gourlay, Christopher M.


    The interaction of an interface between two gases and strong expansion is investigated and the effect on flow in an expansion tube is examined. Two mechanisms for the unsteady Pitot-pressure fluctuations found in the test section of an expansion tube are proposed. The first mechanism depends on the Rayleigh-Taylor instability of the driver-test gas interface in the presence of a strong expansion. The second mechanism depends on the reflection of the strong expansion from the interface. Predictions compare favorably with experimental results. The theory is expected to be independent of the absolute values of the initial expansion tube filling pressures.

  11. De Novo Chromosome Structure Prediction (United States)

    di Pierro, Michele; Cheng, Ryan R.; Lieberman-Aiden, Erez; Wolynes, Peter G.; Onuchic, Jose'n.

    Chromatin consists of DNA and hundreds of proteins that interact with the genetic material. In vivo, chromatin folds into nonrandom structures. The physical mechanism leading to these characteristic conformations, however, remains poorly understood. We recently introduced MiChroM, a model that generates chromosome conformations by using the idea that chromatin can be subdivided into types based on its biochemical interactions. Here we extend and complete our previous finding by showing that structural chromatin types can be inferred from ChIP-Seq data. Chromatin types, which are distinct from DNA sequence, are partially epigenetically controlled and change during cell differentiation, thus constituting a link between epigenetics, chromosomal organization, and cell development. We show that, for GM12878 lymphoblastoid cells we are able to predict accurate chromosome structures with the only input of genomic data. The degree of accuracy achieved by our prediction supports the viability of the proposed physical mechanism of chromatin folding and makes the computational model a powerful tool for future investigations.

  12. Prediction of low birth weight

    DEFF Research Database (Denmark)

    Sinding, Marianne; Peters, David A; Frøkjær, Jens B


    operating characteristic curves demonstrated a significantly higher performance of T2* (AUC of 0.92; 95% CI, 0.85-0.98) than UtA PI (AUC of 0.74; 95% CI, 0.60-0.89) in the prediction of low birth weight (p = 0.010). Placental pathological findings were closely related to the T2* values. CONCLUSIONS...... placental function. Therefore, we aimed to evaluate the performance of placental T2* in the prediction of low birth weight using the uterine artery (UtA) pulsatility index (PI) as gold standard. METHODS: This was a prospective observational study of 100 singleton pregnancies included at 20-40 weeks......' gestation. Placental T2* was obtained using a gradient recalled multi-echo MRI sequence and UtA PI was measured using Doppler ultrasound. Placental pathological examination was performed in 57 of the pregnancies. Low birth weight was defined by a Z-score ≤ -2.0. RESULTS: The incidence of low birth weight...

  13. Menopause prediction and potential implications. (United States)

    Daan, Nadine M P; Fauser, Bart C J M


    Reproductive ageing in women is characterized by a decline in both the quantity and quality of oocytes. Menopause is reached upon exhaustion of the resting primordial follicle pool, occurring on average at 51 years of age (range 40-60 years). The mean global age at natural menopause (ANM) appears robust, suggesting a distinct genetic control. Accordingly, a strong correlation in ANM is observed between mothers and daughters. Few specific genetic determinants of ANM have been identified. Substantial efforts have been made to predict ANM by using anti-Müllerian hormone (AMH) levels. AMH serum concentrations at reproductive age predict ANM, but precision is currently limited. Early ANM is associated with early preceding fertility loss, whereas late menopause is associated with reduced morbidity and mortality later in life. Menopause affects various women's health aspects, including bone density, breast, the cardiovascular system, mood/cognitive function and sexual well-being. If the current trend of increasing human life expectancy persists, women will soon spend half their life postmenopause. Unfortunately, increased longevity does not coincide with an equal increase in years spend in good health. Future research should focus on determinants of long term health effects of ANM, and efforts to improve women's postmenopausal health and quality of life. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Predicting educational achievement from DNA. (United States)

    Selzam, S; Krapohl, E; von Stumm, S; O'Reilly, P F; Rimfeld, K; Kovas, Y; Dale, P S; Lee, J J; Plomin, R


    A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences.

  15. Finite Unification: Theory and Predictions

    CERN Document Server

    Heinemeyer, S; Zoupanos, G


    All-loop Finite Unified Theories (FUTs) are very interesting N=1 supersymmetric Grand Unified Theories (GUTs) which not only realise an old field theoretic dream but also have a remarkable predictive power due to the required reduction of couplings. The reduction of the dimensionless couplings in N=1 GUTs is achieved by searching for renormalization group invariant (RGI) relations among them holding beyond the unification scale. Finiteness results from the fact that there exist RGI relations among dimensionless couplings that guarantee the vanishing of all beta-functions in certain N=1 GUTs even to all orders. Furthermore developments in the soft supersymmetry breaking sector of N=1 GUTs and FUTs lead to exact RGI relations, i.e. reduction of couplings, in this dimensionful sector of the theory too. Based on the above theoretical framework phenomenologically consistent FUTS have been constructed. Here we present FUT models based on the SU(5) and SU(3)^3 gauge groups and their predictions. Of particular intere...

  16. Prediction Reweighting for Domain Adaptation. (United States)

    Shuang Li; Shiji Song; Gao Huang


    There are plenty of classification methods that perform well when training and testing data are drawn from the same distribution. However, in real applications, this condition may be violated, which causes degradation of classification accuracy. Domain adaptation is an effective approach to address this problem. In this paper, we propose a general domain adaptation framework from the perspective of prediction reweighting, from which a novel approach is derived. Different from the major domain adaptation methods, our idea is to reweight predictions of the training classifier on testing data according to their signed distance to the domain separator, which is a classifier that distinguishes training data (from source domain) and testing data (from target domain). We then propagate the labels of target instances with larger weights to ones with smaller weights by introducing a manifold regularization method. It can be proved that our reweighting scheme effectively brings the source and target domains closer to each other in an appropriate sense, such that classification in target domain becomes easier. The proposed method can be implemented efficiently by a simple two-stage algorithm, and the target classifier has a closed-form solution. The effectiveness of our approach is verified by the experiments on artificial datasets and two standard benchmarks, a visual object recognition task and a cross-domain sentiment analysis of text. Experimental results demonstrate that our method is competitive with the state-of-the-art domain adaptation algorithms.

  17. Iowa calibration of MEPDG performance prediction models. (United States)


    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  18. Predicting Performance Ratings Using Motivational Antecedents

    National Research Council Canada - National Science Library

    Zazania, Michelle


    .... LISREL8 was used to test a path model predicting performance ratings. Results showed observer ratings of effort and self-reported task sell-efficacy played a role in predicting ratings of task-specific performance...

  19. Prediction of Unsteady Transonic Aerodynamics, Phase I (United States)

    National Aeronautics and Space Administration — An accurate prediction of aero-elastic effects depends on an accurate prediction of the unsteady aerodynamic forces. Perhaps the most difficult speed regime is...

  20. Dissociating Prediction Failure: Considerations from Music Perception

    DEFF Research Database (Denmark)

    Ross, Suzi; Hansen, Niels Christian


    Dissociating Prediction Failure: Considerations from Music Perception The Journal of Neuroscience, 16 March 2016, 36(11): 3103-3105;......Dissociating Prediction Failure: Considerations from Music Perception The Journal of Neuroscience, 16 March 2016, 36(11): 3103-3105;...

  1. Advanced Refractive Effects Prediction System (AREPS)

    National Research Council Canada - National Science Library

    Patterson, Wayne L


    ...), the world's first electromagnetic prediction system for shipboard use. Advances in research and technology have led to the replacement of IREPS with the Advanced Refractive Effects Prediction System (AREPS...

  2. Are we ready to predict late effects?

    DEFF Research Database (Denmark)

    Salz, Talya; Baxi, Shrujal S; Raghunathan, Nirupa


    to patient characteristics, late effects, the prediction model and model evaluation. DATA SYNTHESIS: Across 14 studies identified for review, nine late effects were predicted: erectile dysfunction and urinary incontinence after prostate cancer; arm lymphoedema, psychological morbidity, cardiomyopathy...

  3. BDDCS Class Prediction for New Molecular Entities

    DEFF Research Database (Denmark)

    Broccatelli, Fabio; Cruciani, Gabriele; Benet, Leslie Z.


    descriptors calculated or derived from the VolSurf+ software. For each molecule, a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction...

  4. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay


    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

  5. Efficient marker data utilization in genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid

    Genomic prediction is a novel method to recognize the best animals for breeding. The aim of this PhD is to improve the accuracy of genomic prediction in dairy cattle by effeiently utilizing marker data. The thesis focuses on three aspects for improving the genomc prediction, which are: criteria...

  6. Based on BP Neural Network Stock Prediction (United States)

    Liu, Xiangwei; Ma, Xin


    The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…


    Directory of Open Access Journals (Sweden)

    Jerzy Balicki


    Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

  8. Predictive Analytics in Information Systems Research

    NARCIS (Netherlands)

    G. Shmueli (Galit); O.R. Koppius (Otto)


    textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as

  9. Applications for predictive microbiology to food packaging (United States)

    Predictive microbiology has been used for several years in the food industry to predict microbial growth, inactivation and survival. Predictive models provide a useful tool in risk assessment, HACCP set-up and GMP for the food industry to enhance microbial food safety. This report introduces the c...

  10. Hydrological Ensemble Prediction System (HEPS) (United States)

    Thielen-Del Pozo, J.; Schaake, J.; Martin, E.; Pailleux, J.; Pappenberger, F.


    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Following on the success of the use of ensembles for weather forecasting, the hydrological community now moves increasingly towards Hydrological Ensemble Prediction Systems (HEPS) for improved flood forecasting using operationally available NWP products as inputs. However, these products are often generated on relatively coarse scales compared to hydrologically relevant basin units and suffer systematic biases that may have considerable impact when passed through the non-linear hydrological filters. Therefore, a better understanding on how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes is necessary. The "Hydrologic Ensemble Prediction Experiment" (HEPEX), is an international initiative consisting of hydrologists, meteorologist and end-users to advance probabilistic hydrologic forecast techniques for flood, drought and water management applications. Different aspects of the hydrological ensemble processor are being addressed including • Production of useful meteorological products relevant for hydrological applications, ranging from nowcasting products to seasonal forecasts. The importance of hindcasts that are consistent with the operational weather forecasts will be discussed to support bias correction and downscaling, statistically meaningful verification of HEPS, and the development and testing of operating rules; • Need for downscaling and post-processing of weather ensembles to reduce bias before entering hydrological applications; • Hydrological model and parameter uncertainty and how to correct and

  11. Predicting casualties implied by TIPs (United States)

    Trendafiloski, G.; Wyss, M.; Wyss, B. M.


    When an earthquake is predicted, forecast, or expected with a higher than normal probability, losses are implied. We estimated the casualties (fatalities plus injured) that should be expected if earthquakes in TIPs (locations of Temporarily Increased Probability of earthquakes) defined by Kossobokov et al. (2009) should occur. We classified the predictions of losses into the categories red (more than 400 fatalities or more than 1,000 injured), yellow (between 100 and 400 fatalities), green (fewer than 100 fatalities), and gray (undetermined). TIPs in Central Chile, the Philippines, Papua, and Taiwan are in the red class, TIPs in Southern Sumatra, Nicaragua, Vanatu, and Honshu in the yellow class, and TIPs in Tonga, Loyalty Islands, Vanatu, S. Sandwich Islands, Banda Sea, and the Kuriles, are classified as green. TIPs where the losses depend moderately on the assumed point of major energy release were classified as yellow; TIPs such as in the Talaud Islands and in Tonga, where the losses depend very strongly on the location of the epicenter, were classified as gray. The accuracy of loss estimates after earthquakes with known hypocenter and magnitude are affected by uncertainties in transmission and soil properties, the composition of the building stock, the population present, and the method by which the numbers of casualties are calculated. In the case of TIPs, uncertainties in magnitude and location are added, thus we calculate losses for a range of these two parameters. Therefore, our calculations can only be considered order of magnitude estimates. Nevertheless, our predictions can come to within a factor of two of the observed numbers, as in the case of the M7.6 earthquake of October 2005 in Pakistan that resulted in 85,000 fatalities (Wyss, 2005). In subduction zones, the geometrical relationship between the earthquake source capable of a great earthquake and the population is clear because there is only one major fault plane available, thus the epicentral

  12. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database. (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M


    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  13. Academic Training: Predicting Natural Catastrophes

    CERN Multimedia

    Françoise Benz


    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 12, 13, 14, 15, 16 December from 11:00 to 12:00 - Main Auditorium, bldg. 500 Predicting Natural Catastrophes E. OKAL / Northwestern University, Evanston, USA 1. Tsunamis -- Introduction Definition of phenomenon - basic properties of the waves Propagation and dispersion Interaction with coasts - Geological and societal effects Origin of tsunamis - natural sources Scientific activities in connection with tsunamis. Ideas about simulations 2. Tsunami generation The earthquake source - conventional theory The earthquake source - normal mode theory The landslide source Near-field observation - The Plafker index Far-field observation - Directivity 3. Tsunami warning General ideas - History of efforts Mantle magnitudes and TREMOR algorithms The challenge of 'tsunami earthquakes' Energy-moment ratios and slow earthquakes Implementation and the components of warning centers 4. Tsunami surveys Principles and methodologies Fifteen years of field surveys and re...

  14. The PredictAD project

    DEFF Research Database (Denmark)

    Antila, Kari; Lötjönen, Jyrki; Thurfjell, Lennart


    can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main...... objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data...... candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials....

  15. Meditation experience predicts introspective accuracy.

    Directory of Open Access Journals (Sweden)

    Kieran C R Fox

    Full Text Available The accuracy of subjective reports, especially those involving introspection of one's own internal processes, remains unclear, and research has demonstrated large individual differences in introspective accuracy. It has been hypothesized that introspective accuracy may be heightened in persons who engage in meditation practices, due to the highly introspective nature of such practices. We undertook a preliminary exploration of this hypothesis, examining introspective accuracy in a cross-section of meditation practitioners (1-15,000 hrs experience. Introspective accuracy was assessed by comparing subjective reports of tactile sensitivity for each of 20 body regions during a 'body-scanning' meditation with averaged, objective measures of tactile sensitivity (mean size of body representation area in primary somatosensory cortex; two-point discrimination threshold as reported in prior research. Expert meditators showed significantly better introspective accuracy than novices; overall meditation experience also significantly predicted individual introspective accuracy. These results suggest that long-term meditators provide more accurate introspective reports than novices.

  16. Numerical prediction of slamming loads

    DEFF Research Database (Denmark)

    Seng, Sopheak; Jensen, Jørgen J; Pedersen, Preben T


    It is important to include the contribution of the slamming-induced response in the structural design of large vessels with a significant bow flare. At the same time it is a challenge to develop rational tools to determine the slamming-induced loads and the prediction of their occurrence. Today...... it is normal practice to apply a standard sea-keeping procedure to determine the relative velocity distribution between the water surface and the hull and then to estimate the bottom slamming loads and the bow-flare slamming loads based on two-dimensional formulations similarly to water-entry problems....... The pressure distribution as well as the total force is then determined by integration over a pseudo-three-dimensional presentation of the hull geometry.In this paper the evaluation of the slamming load is taken one step further by performing direct three-dimensional, fully non-linear numerical calculations...

  17. Predicting tuberculosis among migrant groups. (United States)

    Watkins, R. E.; Plant, A. J.


    In industrialized countries migrants remain a high-risk group for tuberculosis (TB). Multiple linear regression analysis was used to determine the ability of indicators of TB incidence in the country of birth to predict the incidence of TB among migrants in Australia during 1997. World Health Organization total case notifications, new smear-positive case notifications and the estimated incidence of TB by country of birth explained 55, 69 and 87% of the variance in TB incidence in Australia, respectively. Gross national income of the country of birth and unemployment level in Australia were also significant predictors of TB in migrant groups. Indicators of the incidence of TB in the country of birth are the most important group-level predictors of the rate of TB among migrants in Australia. PMID:12558347

  18. Predicting soil respiration from peatlands. (United States)

    Rowson, J G; Worrall, F; Evans, M G; Dixon, S D


    This study considers the relative performance of six different models to predict soil respiration from upland peat. Predicting soil respiration is important for global carbon budgets and gap filling measured data from eddy covariance and closed chamber measurements. Further to models previously published new models are presented using two sub-soil zones and season. Models are tested using data from the Bleaklow plateau, southern Pennines, UK. Presented literature models include ANOVA using logged environmental data, the Arrhenius equation, modified versions of the Arrhenius equation to include soil respiration activation energy and water table depth. New models are proposed including the introduction of two soil zones in the peat profile, and season. The first new model proposes a zone of high CO(2) productivity related to increased soil microbial CO(2) production due to the supply of labile carbon from plant root exudates and root respiration. The second zone is a deeper zone where CO(2) production is lower with less labile carbon. A final model allows the zone of high CO(2) production to become dormant during winter months when plants will senesce and will vary depending upon vegetation type within a fixed location. The final model accounted for, on average, 31.9% of variance in net ecosystem respiration within 11 different restoration sites whilst, using the same data set, the best fitting literature equation only accounted for 18.7% of the total variance. Our results demonstrate that soil respiration models can be improved by explicitly accounting for seasonality and the vertically stratified nature of soil processes. These improved models provide an enhanced basis for calculating the peatland carbon budgets which are essential in understanding the role of peatlands in the global C cycle. Copyright © 2012 Elsevier B.V. All rights reserved.

  19. PEMS. Advanced predictive emission monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Sandvig Nielsen, J.


    In the project PEMS have been developed for boilers, internal combustion engines and gas turbines. The PEMS models have been developed using two principles: The one called ''first principles'' is based on thermo-kinetic modeling of the NO{sub x}-formation by modeling conditions (like temperature, pressure and residence time) in the reaction zones. The other one is data driven using artificial neural network (ANN) and includes no physical properties and no thermo-kinetic formulation. Models of first principles have been developed for gas turbines and gas engines. Data driven models have been developed for gas turbines, gas engines and boilers. The models have been tested on data from sites located in Denmark and the Middle East. Weel and Sandvig has conducted the on-site emission measurements used for development and testing the PEMS models. For gas turbines, both the ''first principles'' and the data driven models have performed excellent considering the ability to reproduce the emission levels of NO{sub x} according to the input variables used for calibration. Data driven models for boilers and gas engines have performed excellent as well. The rather comprehensive first principle model, developed for gas engines, did not perform as well in the prediction of NO{sub x}. Possible a more complex model formulation is required for internal combustion engines. In general, both model types have been validated on data extracted from the data set used for calibration. The data for validation have been selected randomly as individual samplings, and is scattered over the entire measuring campaign. For one natural gas engine a secondary measuring campaign was conducted half a year later than the campaign used for training the data driven model. In the meantime, this engine had been through a refurbishment that included new pistons, piston rings and cylinder linings and cleaning of the cylinder heads. Despite the refurbishment, the

  20. Sports Tournament Predictions Using Direct Manipulation. (United States)

    Vuillemot, Romain; Perin, Charles


    An advanced interface for sports tournament predictions uses direct manipulation to allow users to make nonlinear predictions. Unlike previous interface designs, the interface helps users focus on their prediction tasks by enabling them to first choose a winner and then fill out the rest of the bracket. In real-world tests of the proposed interface (for the 2014 FIFA World Cup tournament and 2015/2016 UEFA Champions League), the authors validated the use of direct manipulation as an alternative to widgets. Using visitor interaction logs, they were able to determine the strategies people use to perform predictions and identify potential areas of improvement for further prediction interfaces.

  1. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

    Salonen, Mikko; Hansen, Claus Thorp; Perttula, Matti


    A product is designed with the purpose of possessing certain properties, which are prescribed as requirements in the design specification. This paper studies the evolution of property predictability during the early phases of design in a case study context. By the term property predictability, we...... refer to the designers’ confidence in predicting product properties based on the available information. In the case study, with use of the produced design models at four different stages of concept concretisation, the designers evaluated their confidence in predicting product properties related...... to the requirements set for the task. As a result, we identified three different patterns of property predictability behaviour. These patterns consist of properties of which predictability is relatively high throughout the early phases of the design process, properties of which predictability shows a high increase...

  2. Potential for western US seasonal snowpack prediction (United States)

    Kapnick, Sarah B.; Yang, Xiaosong; Vecchi, Gabriel A.; Delworth, Thomas L.; Gudgel, Rich; Malyshev, Sergey; Milly, Paul C.; Shevliakova, Elena; Underwood, Seth; Margulis, Steven A.


    Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of th ecentury and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 month sin advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.

  3. Spatiotemporal Bayesian networks for malaria prediction. (United States)

    Haddawy, Peter; Hasan, A H M Imrul; Kasantikul, Rangwan; Lawpoolsri, Saranath; Sa-Angchai, Patiwat; Kaewkungwal, Jaranit; Singhasivanon, Pratap


    Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating village level models with weekly temporal resolution for Tha Song Yang district in northern Thailand. The networks are learned using data on cases and environmental covariates. Three types of networks are explored: networks for numeric prediction, networks for outbreak prediction, and networks that incorporate spatial autocorrelation. Evaluation of the numeric prediction network shows that the Bayes net has prediction accuracy in terms of mean absolute error of about 1.4 cases for 1 week prediction and 1.7 cases for 6 week prediction. The network for outbreak prediction has an ROC AUC above 0.9 for all prediction horizons. Comparison of prediction accuracy of both Bayes nets against several traditional modeling approaches shows the Bayes nets to outperform the other models for longer time horizon prediction of high incidence transmission. To model spread of malaria over space, we elaborate the models with links between the village networks. This results in some very large models which would be far too laborious to build by hand. So we represent the models as collections of probability logic rules and automatically generate the networks. Evaluation of the models shows that the autocorrelation links significantly improve prediction accuracy for some villages in regions of high incidence. We conclude that spatiotemporal Bayesian networks are a highly promising modeling alternative for prediction

  4. Which method predicts recidivism best?: A comparison of statistical, machine learning, and data mining predictive models


    Tollenaar, N.; van der Heijden, P.G.M.


    Using criminal population conviction histories of recent offenders, prediction mod els are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining and machine learning provide an improvement in predictive performance over classical statistical methods, namely logistic regression and linear discrim inant analysis. These models are compared ...

  5. Similarities and Differences Between Warped Linear Prediction and Laguerre Linear Prediction

    NARCIS (Netherlands)

    Brinker, Albertus C. den; Krishnamoorthi, Harish; Verbitskiy, Evgeny A.


    Linear prediction has been successfully applied in many speech and audio processing systems. This paper presents the similarities and differences between two classes of linear prediction schemes, namely, Warped Linear Prediction (WLP) and Laguerre Linear Prediction (LLP). It is shown that both

  6. Entropy and the Predictability of Online Life

    Directory of Open Access Journals (Sweden)

    Roberta Sinatra


    Full Text Available Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can, to some extent, be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability, negative behavior has a wider variety than positive actions. The actions that contain the information to best predict an individual’s subsequent action are negative, such as attacks or enemy markings, while the positive actions of friendship marking, trade and communication contain the least amount of predictive information. These observations show that predicting behavioral actions requires less information than predicting the mobility patterns of humans for which the additional knowledge of past visited locations is crucial and that the type and sign of a social relation has an essential impact on the ability to determine future behavior.

  7. Hypoparathyroidism following thyroidectomy: Predictive factors. (United States)

    Coimbra, Cristiana; Monteiro, Francisco; Oliveira, Pedro; Ribeiro, Leandro; de Almeida, Mário Giesteira; Condé, Artur

    To evaluate the incidence and predictive factors for transient and permanent hypocalcemia and hypoparathyroidism following thyroidectomy. We studied all the 162 patients that underwent thyroid surgery in the ENT department of the Centro Hospitalar Vila Nova Gaia/Espinho from January 2005 to December 2014. We reviewed pre-operative, 6h and 12h after surgery ionized calcium and PTH levels. All patients were reviewed and evaluated according to the following criteria: gender, age, thyroid function, histologic diagnosis of the specimen, surgery extension and presence or absence of hypoparathyroidism. There were 31 (19.1%) cases of transient hypoparathyroidism and 8 (5%) of permanent hypoparathyroidism. No significant difference was found for transient hypoparathyroidism when patients were analyzed by gender. However, all cases of permanent hypoparathyroidism were observed in female individuals. Comparing hemithyroidectomy with all other surgical procedures, we found that extension of surgery was a great predictor of transient (p=0.0001) and permanent (p=0.001) hypoparathyroidism. Diagnosis of malignancy was a strong predictor of transient hypoparathyroidism (p=0.002). It was also associated with permanent hypoparathyroidism, although differences did not reach statistical significance (p=0.096). Extension of surgery (total thyroidectomy) and diagnosis of malignancy are predictors of transient and permanent hypoparathyroidism. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Otorrinolaringología y Cirugía de Cabeza y Cuello. All rights reserved.

  8. Parallel Prediction of Stock Volatility

    Directory of Open Access Journals (Sweden)

    Priscilla Jenq


    Full Text Available Volatility is a measurement of the risk of financial products. A stock will hit new highs and lows over time and if these highs and lows fluctuate wildly, then it is considered a high volatile stock. Such a stock is considered riskier than a stock whose volatility is low. Although highly volatile stocks are riskier, the returns that they generate for investors can be quite high. Of course, with a riskier stock also comes the chance of losing money and yielding negative returns. In this project, we will use historic stock data to help us forecast volatility. Since the financial industry usually uses S&P 500 as the indicator of the market, we will use S&P 500 as a benchmark to compute the risk. We will also use artificial neural networks as a tool to predict volatilities for a specific time frame that will be set when we configure this neural network. There have been reports that neural networks with different numbers of layers and different numbers of hidden nodes may generate varying results. In fact, we may be able to find the best configuration of a neural network to compute volatilities. We will implement this system using the parallel approach. The system can be used as a tool for investors to allocating and hedging assets.

  9. Time estimation predicts mathematical intelligence.

    Directory of Open Access Journals (Sweden)

    Peter Kramer

    Full Text Available BACKGROUND: Performing mental subtractions affects time (duration estimates, and making time estimates disrupts mental subtractions. This interaction has been attributed to the concurrent involvement of time estimation and arithmetic with general intelligence and working memory. Given the extant evidence of a relationship between time and number, here we test the stronger hypothesis that time estimation correlates specifically with mathematical intelligence, and not with general intelligence or working-memory capacity. METHODOLOGY/PRINCIPAL FINDINGS: Participants performed a (prospective time estimation experiment, completed several subtests of the WAIS intelligence test, and self-rated their mathematical skill. For five different durations, we found that time estimation correlated with both arithmetic ability and self-rated mathematical skill. Controlling for non-mathematical intelligence (including working memory capacity did not change the results. Conversely, correlations between time estimation and non-mathematical intelligence either were nonsignificant, or disappeared after controlling for mathematical intelligence. CONCLUSIONS/SIGNIFICANCE: We conclude that time estimation specifically predicts mathematical intelligence. On the basis of the relevant literature, we furthermore conclude that the relationship between time estimation and mathematical intelligence is likely due to a common reliance on spatial ability.

  10. Predictable repair of provisional restorations. (United States)

    Hammond, Barry D; Cooper, Jeril R; Lazarchik, David A


    The importance of provisional restorations is often downplayed, as they are thought of by some as only "temporaries." As a result, a less-than-ideal provisional is sometimes fabricated, in part because of the additional chair time required to make provisional modifications when using traditional techniques. Additionally, in many dental practices, these provisional restorations are often fabricated by auxillary personnel who may not be as well trained in the fabrication process. Because provisionals play an important role in achieving the desired final functional and esthetic result, a high-quality provisional restoration is essential to fabricating a successful definitive restoration. This article describes a method for efficiently and predictably repairing both methacrylate and bis-acryl provisional restorations using flowable composite resin. By use of this relatively simple technique, provisional restorations can now be modified or repaired in a timely and productive manner to yield an exceptional result. Successful execution of esthetic and restorative dentistry requires attention to detail in every aspect of the case. Fabrication of high-quality provisional restorations can, at times, be challenging and time consuming. The techniques for optimizing resin provisional restorations as described in this paper are pragmatic and will enhance the delivery of dental treatment.

  11. Incorrect predictions reduce switch costs. (United States)

    Kleinsorge, Thomas; Scheil, Juliane


    In three experiments, we combined two sources of conflict within a modified task-switching procedure. The first source of conflict was the one inherent in any task switching situation, namely the conflict between a task set activated by the recent performance of another task and the task set needed to perform the actually relevant task. The second source of conflict was induced by requiring participants to guess aspects of the upcoming task (Exps. 1 & 2: task identity; Exp. 3: position of task precue). In case of an incorrect guess, a conflict accrues between the representation of the guessed task and the actually relevant task. In Experiments 1 and 2, incorrect guesses led to an overall increase of reaction times and error rates, but they reduced task switch costs compared to conditions in which participants predicted the correct task. In Experiment 3, incorrect guesses resulted in faster performance overall and to a selective decrease of reaction times in task switch trials when the cue-target interval was long. We interpret these findings in terms of an enhanced level of controlled processing induced by a combination of two sources of conflict converging upon the same target of cognitive control. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Prediction of twin-arginine signal peptides

    DEFF Research Database (Denmark)

    Bendtsen, Jannick Dyrløv; Nielsen, Henrik; Widdick, D.


    a publicly available method, TatP, for prediction of bacterial Tat signal peptides. Results: We have retrieved sequence data for Tat substrates in order to train a computational method for discrimination of Sec and Tat signal peptides. The TatP method is able to positively classify 91% of 35 known Tat signal...... peptides and 84% of the annotated cleavage sites of these Tat signal peptides were correctly predicted. This method generates far less false positive predictions on various datasets than using simple pattern matching. Moreover, on the same datasets TatP generates less false positive predictions than...... expressions, whereas hydrophobicity discrimination of Tat- and Sec- signal peptides is carried out by an artificial neural network. A potential cleavage site of the predicted Tat signal peptide is also reported. The TatP prediction server is available as a public web server at

  13. Predictability engenders more efficient neural responses


    David M. Eagleman; Vani Pariyadath; Sara J. Churchill


    The neural response to a stimulus diminishes with repeated presentations, a phenomenon known as repetition suppression. We here use neuroimaging to demonstrate that repetition suppression appears to be a special case of "prediction suppression"--that is, the brain shows diminishing activity when subsequent stimuli in a train are predictable. This demonstration supports the hypothesis that the brain dynamically leverages prediction to minimize energy consumption.

  14. Evaluating Prediction Markets for Internal Control Applications (United States)


    would influence the survey indicators, the prediction market prices, and their sensitivity to misinformation. Finally, this study reveal s the results...realized in an academ ic setting. With a controll able number of influencing factors, the prediction markets were installed in several uni versity courses...of acceptance and the limited number of influencing factors in an academic setting, it is expected that the prediction market will perform

  15. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

    Andersen, Claus A.; Bohr, Henrik; Brunak, Søren


    In the last decade, the prediction of protein secondary structure has been optimized using essentially one and the same assignment scheme known as DSSP. We present here a different scheme, which is more predictable. This scheme predicts directly the hydrogen bonds, which stabilize the secondary......-forward neural network with one hidden layer on a data set identical to the one used in earlier work....

  16. Sports Tournament Predictions Using Direct Manipulation


    Vuillemot , Romain; Perin , Charles


    An advanced interface for sports tournament predictions uses direct manipulation to allow users to make nonlinear predictions. Unlike previous interface designs, the interface helps users focus on their prediction tasks by enabling them to first choose a winner and then fill out the rest of the bracket. In real-world tests of the proposed interface (for the 2014 FIFA World Cup tournament and 2015/2016 UEFA Champions League), the authors validated the use of direct manipulation as an alternati...

  17. Predictive Trip Detection for Nuclear Power Plants (United States)

    Rankin, Drew J.; Jiang, Jin


    This paper investigates the use of a Kalman filter (KF) to predict, within the shutdown system (SDS) of a nuclear power plant (NPP), whether safety parameter measurements have reached a trip set-point. In addition, least squares (LS) estimation compensates for prediction error due to system-model mismatch. The motivation behind predictive shutdown is to reduce the amount of time between the occurrence of a fault or failure and the time of trip detection, referred to as time-to-trip. These reductions in time-to-trip can ultimately lead to increases in safety and productivity margins. The proposed predictive SDS differs from conventional SDSs in that it compares point-predictions of the measurements, rather than sensor measurements, against trip set-points. The predictive SDS is validated through simulation and experiments for the steam generator water level safety parameter. Performance of the proposed predictive SDS is compared against benchmark conventional SDS with respect to time-to-trip. In addition, this paper analyzes: prediction uncertainty, as well as; the conditions under which it is possible to achieve reduced time-to-trip. Simulation results demonstrate that on average the predictive SDS reduces time-to-trip by an amount of time equal to the length of the prediction horizon and that the distribution of times-to-trip is approximately Gaussian. Experimental results reveal that a reduced time-to-trip can be achieved in a real-world system with unknown system-model mismatch and that the predictive SDS can be implemented with a scan time of under 100ms. Thus, this paper is a proof of concept for KF/LS-based predictive trip detection.

  18. Forecasting hotspots using predictive visual analytics approach (United States)

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David


    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  19. Probabilistic approach to earthquake prediction.

    Directory of Open Access Journals (Sweden)

    G. D'Addezio


    Full Text Available The evaluation of any earthquake forecast hypothesis requires the application of rigorous statistical methods. It implies a univocal definition of the model characterising the concerned anomaly or precursor, so as it can be objectively recognised in any circumstance and by any observer.A valid forecast hypothesis is expected to maximise successes and minimise false alarms. The probability gain associated to a precursor is also a popular way to estimate the quality of the predictions based on such precursor. Some scientists make use of a statistical approach based on the computation of the likelihood of an observed realisation of seismic events, and on the comparison of the likelihood obtained under different hypotheses. This method can be extended to algorithms that allow the computation of the density distribution of the conditional probability of earthquake occurrence in space, time and magnitude. Whatever method is chosen for building up a new hypothesis, the final assessment of its validity should be carried out by a test on a new and independent set of observations. The implementation of this test could, however, be problematic for seismicity characterised by long-term recurrence intervals. Even using the historical record, that may span time windows extremely variable between a few centuries to a few millennia, we have a low probability to catch more than one or two events on the same fault. Extending the record of earthquakes of the past back in time up to several millennia, paleoseismology represents a great opportunity to study how earthquakes recur through time and thus provide innovative contributions to time-dependent seismic hazard assessment. Sets of paleoseimologically dated earthquakes have been established for some faults in the Mediterranean area: the Irpinia fault in Southern Italy, the Fucino fault in Central Italy, the El Asnam fault in Algeria and the Skinos fault in Central Greece. By using the age of the

  20. Bronchial thermoplasty: activations predict response. (United States)

    Langton, David; Sha, Joy; Ing, Alvin; Fielding, David; Thien, Francis; Plummer, Virginia


    Bronchial thermoplasty (BT) is an emerging bronchoscopic intervention for the treatment of severe asthma. The predictive factors for clinical response to BT are unknown. We examined the relationship between the number of radiofrequency activations applied and the treatment response observed. Data were collected from 24 consecutive cases treated at three Australian centres from June 2014 to March 2016. The baseline characteristics were collated along with the activations delivered. The primary response measure was change in the Asthma Control Questionnaire-5 (ACQ-5) score measured at 6 months post BT. The relationship between change in outcome parameters and the number of activations delivered was explored. All patients met the ERS/ATS definition for severe asthma. At 6 months post treatment, mean ACQ-5 improved from 3.3 ± 1.1 to 1.5 ± 1.1, p < 0.001. The minimal clinically significant improvement in ACQ-5 of ≥0.5 was observed in 21 out of 24 patients. The only significant variable that differed between the 21 responders and the three non-responders was the number of activations delivered, with 139 ± 11 activations in the non-responders, compared to 221 ± 45 activations in the responders (p < 0.01). A significant inverse correlation was found between change in ACQ-5 score and the number of activations, r = -0.43 (p < 0.05). The number of activations delivered during BT has a role in determining clinical response to treatment.

  1. Can we predict shoulder dystocia? (United States)

    Revicky, Vladimir; Mukhopadhyay, Sambit; Morris, Edward P; Nieto, Jose J


    To analyse the significance of risk factors and the possibility of prediction of shoulder dystocia. This was a retrospective cohort study. There were 9,767 vaginal deliveries at 37 and more weeks of gestation analysed during 2005-2007. Studied population included 234 deliveries complicated by shoulder dystocia. Shoulder dystocia was defined as a delivery that required additional obstetric manoeuvres to release the shoulders after gentle downward traction has failed. First, a univariate analysis was done to identify the factors that had a significant association with shoulder dystocia. Parity, age, gestation, induction of labour, epidural analgesia, birth weight, duration of second stage of labour and mode of delivery were studied factors. All factors were then combined in a multivariate logistic regression analysis. Adjusted odds ratios (Adj. OR) with 95% confidence intervals (CI) were calculated. The incidence of shoulder dystocia was 2.4% (234/9,767). Only mode of delivery and birth weight were independent risk factors for shoulder dystocia. Parity, age, gestation, induction of labour, epidural analgesia and duration of second stage of labour were not independent risk factors. Ventouse delivery increases the risk of shoulder dystocia almost 3 times, forceps delivery comparing to the ventouse delivery increases risk almost 3.4 times. Risk of shoulder dystocia is minimal with the birth weight of 3,000 g or less. It is difficult to foretell the exact birth weight and the mode of delivery, therefore occurrence of shoulder dystocia is highly unpredictable. Regular drills for shoulder dystocia and awareness of increased incidence with instrumental deliveries are important to reduce fetal and maternal morbidity and mortality.

  2. Prediction of tar ball formation

    International Nuclear Information System (INIS)

    Khelifa, A.; Gamble, L.


    The presence of small tar balls ranging in size from less than a millimetre to 60 centimetres have been observed during cleanup assessment operations following accidental oil spills on water. The tar balls are composed of heavy oil residues and suspended particulate matter (SPM) from the water column. They can be found on shorelines, settled on the seafloor and floating at or near the water surface. Their abundance on the shorelines varies from site to site and depends on the conditions of the spill and mixing conditions. Aggregation between SPM and micro-sized oil droplets occurs naturally in coastal waters and enhances the dispersion of spilled oil. Although tar balls are among the important end states of spilled oil in the marine environment, no model exists to estimate the percentage of the spilled oil that becomes tar balls. This paper offered some insight into the modeling of tar ball formation. Current modeling understanding of oil-SPM aggregate formation was used to predict tar ball formation. The formation of oil droplets was examined with respect to a range of conditions under which the formation of large droplets is expected. The role of aggregation was then presented to demonstrate the effects of concentration and type of SPM on the buoyancy of tar balls. Good agreement was found between modeling results and field data reported in the literature regarding the size and density of tar balls. Oil viscosity and mixing energy were found to be the main factors controlling the formation of tar balls. The aggregation of tar balls with SPM and shoreline material results in significant increases or decreases in density, depending on the type and concentration of SPM. 42 refs., 2 tabs., 6 figs

  3. Predicting language: MEG evidence for lexical preactivation. (United States)

    Dikker, Suzanne; Pylkkänen, Liina


    It is widely assumed that prediction plays a substantial role in language processing. However, despite numerous studies demonstrating that contextual information facilitates both syntactic and lexical-semantic processing, there exists no direct evidence pertaining to the neural correlates of the prediction process itself. Using magnetoencephalography (MEG), this study found that brain activity was modulated by whether or not a specific noun could be predicted, given a picture prime. Specifically, before the noun was presented, predictive contexts triggered enhanced activation in left mid-temporal cortex (implicated in lexical access), ventro-medial prefrontal cortex (previously associated with top-down processing), and visual cortex (hypothesized to index the preactivation of predicted form features), successively. This finding suggests that predictive language processing recruits a top-down network where predicted words are activated at different levels of representation, from more 'abstract' lexical-semantic representations in temporal cortex, all the way down to visual word form features. The same brain regions that exhibited enhanced activation for predictive contexts before the onset of the noun showed effects of congruence during the target word. To our knowledge, this study is one of the first to directly investigate the anticipatory stage of predictive language processing. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Predictability of extreme values in geophysical models

    Directory of Open Access Journals (Sweden)

    A. E. Sterk


    Full Text Available Extreme value theory in deterministic systems is concerned with unlikely large (or small values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical models. We study whether finite-time Lyapunov exponents are larger or smaller for initial conditions leading to extremes. General statements on whether extreme values are better or less predictable are not possible: the predictability of extreme values depends on the observable, the attractor of the system, and the prediction lead time.

  5. Implementation of short-term prediction

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L.; Joensen, A.; Giebel, G. [and others


    This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

  6. Predictions of High Energy Experimental Results

    Directory of Open Access Journals (Sweden)

    Comay E.


    Full Text Available Eight predictions of high energy experimental results are presented. The predictions contain the + charge radius and results of two kinds of experiments using energetic pionic beams. In addition, predictions of the failure to find the following objects are presented: glueballs, pentaquarks, Strange Quark Matter, magnetic monopoles searched by their direct interaction with charges and the Higgs boson. The first seven predictions rely on the Regular Charge-Monopole Theory and the last one relies on mathematical inconsistencies of the Higgs Lagrangian density.

  7. Improved interpretation and validation of CFD predictions

    DEFF Research Database (Denmark)

    Popiolek, Z.; Melikov, Arsen Krikor


    The mean velocity in rooms predicted by CFD simulations based on RANS equations differs from the mean (in time) magnitude of the velocity, i.e. the mean speed, in rooms measured by low velocity thermal anemometers with omnidirectional sensor. This discrepancy results in incorrect thermal comfort...... assessment by the CFD predictions as well as incorrect validation of the predicted velocity field. In this paper the discrepancies are discussed and identified, and a method for estimating of the mean speed based on the CFD predictions of mean velocity and kinetic turbulence energy is suggested. The method...

  8. MHC Class II epitope predictive algorithms

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lund, Ole; Buus, S


    in the predictions. All attempts to make ab initio predictions based on protein structure have failed to reach predictive performances similar to those that can be obtained by data-driven methods. Thousands of different MHC-II alleles exist in humans. Recently developed pan-specific methods have been able to make...... reasonably accurate predictions for alleles that were not included in the training data. These methods can be used to define supertypes (clusters) of MHC-II alleles where alleles within each supertype have similar binding specificities. Furthermore, the pan-specific methods have been used to make a graphical...

  9. Predicting Social Behavior from Personality Traits (United States)

    Jaccard, James J.


    The classic view of traits as dispositions was examined and a number of ambiguities noted. When clarified, implication for predicting social behaviors from personality variables were derived. (Editor)

  10. Predicting gene expression from sequence: a reexamination.

    Directory of Open Access Journals (Sweden)

    Yuan Yuan


    Full Text Available Although much of the information regarding genes' expressions is encoded in the genome, deciphering such information has been very challenging. We reexamined Beer and Tavazoie's (BT approach to predict mRNA expression patterns of 2,587 genes in Saccharomyces cerevisiae from the information in their respective promoter sequences. Instead of fitting complex Bayesian network models, we trained naïve Bayes classifiers using only the sequence-motif matching scores provided by BT. Our simple models correctly predict expression patterns for 79% of the genes, based on the same criterion and the same cross-validation (CV procedure as BT, which compares favorably to the 73% accuracy of BT. The fact that our approach did not use position and orientation information of the predicted binding sites but achieved a higher prediction accuracy, motivated us to investigate a few biological predictions made by BT. We found that some of their predictions, especially those related to motif orientations and positions, are at best circumstantial. For example, the combinatorial rules suggested by BT for the PAC and RRPE motifs are not unique to the cluster of genes from which the predictive model was inferred, and there are simpler rules that are statistically more significant than BT's ones. We also show that CV procedure used by BT to estimate their method's prediction accuracy is inappropriate and may have overestimated the prediction accuracy by about 10%.

  11. Decadel climate prediction: challenges and opportunities

    International Nuclear Information System (INIS)

    Hurrell, J W


    The scientific understanding of climate change is now sufficiently clear to show that climate change from global warming is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. Uncertainties remain, however, especially regarding how climate will change at regional and local scales where the signal of natural variability is large. Addressing many of these uncertainties will require a movement toward high resolution climate system predictions, with a blurring of the distinction between shorter-term predictions and longer-term climate projections. The key is the realization that climate system predictions, regardless of timescale, will require initialization of coupled general circulation models with best estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface. Formidable challenges exist: for instance, what is the best method of initialization given imperfect observations and systematic errors in models? What effect does initialization have on climate predictions? What predictions should be attempted, and how would they be verified? Despite such challenges, the unrealized predictability that resides in slowly evolving phenomena, such as ocean current systems, is of paramount importance for society to plan and adapt for the next few decades. Moreover, initialized climate predictions will require stronger collaboration with shared knowledge, infrastructure and technical capabilities among those in the weather and climate prediction communities. The potential benefits include improved understanding and predictions on all time scales

  12. Recent Advances in Predictive (Machine) Learning

    Energy Technology Data Exchange (ETDEWEB)

    Friedman, J


    Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that have revitalized the field. These are support vector machines and boosted decision trees. This paper provides an introduction to these two new methods tracing their respective ancestral roots to standard kernel methods and ordinary decision trees.

  13. Understanding predictability and exploration in human mobility

    DEFF Research Database (Denmark)

    Cuttone, Andrea; Jørgensen, Sune Lehmann; González, Marta C.


    Predictive models for human mobility have important applications in many fields including traffic control, ubiquitous computing, and contextual advertisement. The predictive performance of models in literature varies quite broadly, from over 90% to under 40%. In this work we study which underlying...... strong influence on the accuracy of prediction. Finally we reveal that the exploration of new locations is an important factor in human mobility, and we measure that on average 20-25% of transitions are to new places, and approx. 70% of locations are visited only once. We discuss how these mechanisms...... are important factors limiting our ability to predict human mobility....

  14. Tail Risk Premia and Return Predictability

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Todorov, Viktor; Xu, Lai

    The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be attribu......The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

  15. Final Technical Report: Increasing Prediction Accuracy.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)


    PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

  16. Programming Useful Life Prediction (PULP) Project (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements....

  17. Stock price prediction using geometric Brownian motion (United States)

    Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM


    Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

  18. Deterministic prediction of surface wind speed variations

    Directory of Open Access Journals (Sweden)

    G. V. Drisya


    Full Text Available Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.

  19. Predictions of High Energy Experimental Results

    Directory of Open Access Journals (Sweden)

    Comay E.


    Full Text Available Eight predictions of high energy experimental results are presented. The predictions contain the $Sigma ^+$ charge radius and results of two kinds of experiments using energetic pionic beams. In addition, predictions of the failure to find the following objects are presented: glueballs, pentaquarks, Strange Quark Matter, magnetic monopoles searched by their direct interaction with charges and the Higgs boson. The first seven predictions rely on the Regular Charge-Monopole Theory and the last one relies on mathematical inconsistencies of the Higgs Lagrangian density.

  20. Protein conformational flexibility prediction using machine learning. (United States)

    Trott, Oleg; Siggers, Keri; Rost, Burkhard; Palmer, Arthur G


    Using a data set of 16 proteins, a neural network has been trained to predict backbone 15N generalized order parameters from the three-dimensional structures of proteins. The final network parameterization contains six input features. The average prediction accuracy, as measured by the Pearson's correlation coefficient between experimental and predicted values of the square of the generalized order parameter is >0.70. Predicted order parameters for non-terminal amino acid residues depends most strongly on the local packing density and the probability that the residue is located in regular secondary structure.

  1. Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities (United States)

    Schubert, Siegfried


    Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

  2. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay


    A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...... model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model...

  3. Computer loss experience and predictions (United States)

    Parker, Donn B.


    The types of losses organizations must anticipate have become more difficult to predict because of the eclectic nature of computers and the data communications and the decrease in news media reporting of computer-related losses as they become commonplace. Total business crime is conjectured to be decreasing in frequency and increasing in loss per case as a result of increasing computer use. Computer crimes are probably increasing, however, as their share of the decreasing business crime rate grows. Ultimately all business crime will involve computers in some way, and we could see a decline of both together. The important information security measures in high-loss business crime generally concern controls over authorized people engaged in unauthorized activities. Such controls include authentication of users, analysis of detailed audit records, unannounced audits, segregation of development and production systems and duties, shielding the viewing of screens, and security awareness and motivation controls in high-value transaction areas. Computer crimes that involve highly publicized intriguing computer misuse methods, such as privacy violations, radio frequency emanations eavesdropping, and computer viruses, have been reported in waves that periodically have saturated the news media during the past 20 years. We must be able to anticipate such highly publicized crimes and reduce the impact and embarrassment they cause. On the basis of our most recent experience, I propose nine new types of computer crime to be aware of: computer larceny (theft and burglary of small computers), automated hacking (use of computer programs to intrude), electronic data interchange fraud (business transaction fraud), Trojan bomb extortion and sabotage (code security inserted into others' systems that can be triggered to cause damage), LANarchy (unknown equipment in use), desktop forgery (computerized forgery and counterfeiting of documents), information anarchy (indiscriminate use of

  4. Intelligent Predictive Control of Nonlienar Processes Using

    DEFF Research Database (Denmark)

    Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad


    This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has...


    African Journals Online (AJOL)

    As pressure data was not acquired in the water leg of the reservoir, pressure gradient analysis was done with the field-wide hydrostatic profile for contact and fluid prediction. Also, an evaluation of the possibility of having an oil rim within the region of fluid-type uncertainty was carried out. The predicted results revealed that ...

  6. Infants Generate Goal-Based Action Predictions (United States)

    Cannon, Erin N.; Woodward, Amanda L.


    Predicting the actions of others is critical to smooth social interactions. Prior work suggests that both understanding and anticipation of goal-directed actions appears early in development. In this study, on-line goal prediction was tested explicitly using an adaptation of Woodward's (1998) paradigm for an eye-tracking task. Twenty 11-month-olds…

  7. Predicting Information Flows in Network Traffic. (United States)

    Hinich, Melvin J.; Molyneux, Robert E.


    Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

  8. Predictive Model of Systemic Toxicity (SOT) (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  9. Predictive models for arteriovenous fistula maturation. (United States)

    Al Shakarchi, Julien; McGrogan, Damian; Van der Veer, Sabine; Sperrin, Matthew; Inston, Nicholas


    Haemodialysis (HD) is a lifeline therapy for patients with end-stage renal disease (ESRD). A critical factor in the survival of renal dialysis patients is the surgical creation of vascular access, and international guidelines recommend arteriovenous fistulas (AVF) as the gold standard of vascular access for haemodialysis. Despite this, AVFs have been associated with high failure rates. Although risk factors for AVF failure have been identified, their utility for predicting AVF failure through predictive models remains unclear. The objectives of this review are to systematically and critically assess the methodology and reporting of studies developing prognostic predictive models for AVF outcomes and assess them for suitability in clinical practice. Electronic databases were searched for studies reporting prognostic predictive models for AVF outcomes. Dual review was conducted to identify studies that reported on the development or validation of a model constructed to predict AVF outcome following creation. Data were extracted on study characteristics, risk predictors, statistical methodology, model type, as well as validation process. We included four different studies reporting five different predictive models. Parameters identified that were common to all scoring system were age and cardiovascular disease. This review has found a small number of predictive models in vascular access. The disparity between each study limits the development of a unified predictive model.

  10. Model Predictive Control Fundamentals | Orukpe | Nigerian Journal ...

    African Journals Online (AJOL)

    Model Predictive Control (MPC) has developed considerably over the last two decades, both within the research control community and in industries. MPC strategy involves the optimization of a performance index with respect to some future control sequence, using predictions of the output signal based on a process model, ...

  11. Huntington's disease : Psychological aspects of predictive testing

    NARCIS (Netherlands)

    Timman, Reinier


    Predictive testing for Huntington's disease appears to have long lasting psychological effects. The predictive test for Huntington's disease (HD), a hereditary disease of the nervous system, was introduced in the Netherlands in the late eighties. As adverse consequences of the test were

  12. Preoperative Prediction of Difficult Laparoscopic Cholecystectomy: A ...

    African Journals Online (AJOL)

    ... collection (P - 0.04), and abdominal scar due to previous abdominal surgery (P ‑ 0.009) were found statistically significant in predicting difficult LC. Conclusion: The proposed scoring system is reliable with a sensitivity of 76.47% and specificity of 100%. Keywords: Difficult, laparoscopic cholecystectomy, prediction, scoring ...

  13. Differential Prediction Generalization in College Admissions Testing (United States)

    Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.


    We introduce the concept of "differential prediction generalization" in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student's ethnicity and gender and whether this…

  14. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp


    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optim...

  15. An Improved Algorithm for Predicting Free Recalls (United States)

    Laming, Donald


    Laming [Laming, D. (2006). "Predicting free recalls." "Journal of Experimental Psychology: Learning, Memory, and Cognition," 32, 1146-1163] has shown that, in a free-recall experiment in which the participants rehearsed out loud, entire sequences of recalls could be predicted, to a useful degree of precision, from the prior sequences of stimuli…

  16. Verification, validation, and reliability of predictions

    International Nuclear Information System (INIS)

    Pigford, T.H.; Chambre, P.L.


    The objective of predicting long-term performance should be to make reliable determinations of whether the prediction falls within the criteria for acceptable performance. Establishing reliable predictions of long-term performance of a waste repository requires emphasis on valid theories to predict performance. The validation process must establish the validity of the theory, the parameters used in applying the theory, the arithmetic of calculations, and the interpretation of results; but validation of such performance predictions is not possible unless there are clear criteria for acceptable performance. Validation programs should emphasize identification of the substantive issues of prediction that need to be resolved. Examples relevant to waste package performance are predicting the life of waste containers and the time distribution of container failures, establishing the criteria for defining container failure, validating theories for time-dependent waste dissolution that depend on details of the repository environment, and determining the extent of congruent dissolution of radionuclides in the UO 2 matrix of spent fuel. Prediction and validation should go hand in hand and should be done and reviewed frequently, as essential tools for the programs to design and develop repositories. 29 refs

  17. Predicting formation enthalpies of metal hydrides

    DEFF Research Database (Denmark)

    Andreasen, A.


    of elements from the periodic table are yet to beexplored. Since experimental determination of thermodynamic properties of the vast combinations of elements is tedious it may be advantagous to have a predictive tool for this task. In this report different ways of predicting #DELTA#H_f for binary andternary...

  18. Predicting alcohol use by adolescent males. (United States)

    Udry, J R


    An attempt was made to predict alcohol use among 101 American white boys aged 13-16. The model combined genetic and social variables. The analysis revealed evidence of a genotype-environment interaction and thus the use of either the biological or social variables alone poorly predicts alcohol use.

  19. The relative value of operon predictions

    NARCIS (Netherlands)

    Brouwer, Rutger W. W.; Kuipers, Oscar P.; van Hijum, Sacha A. F. T.

    For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation,

  20. Predictability in models of the atmospheric circulation

    NARCIS (Netherlands)

    Houtekamer, P.L.


    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error

  1. Predictability of Returns and Cash Flows


    Ralph S.J. Koijen; Stijn Van Nieuwerburgh


    We review the literature on return and cash-flow growth predictability from the perspective of the present-value identity. We focus predominantly on recent work. Our emphasis is on U.S. aggregate stock return predictability, but we also discuss evidence from other asset classes and countries.

  2. Fuzzy Predictions for Strategic Decision Making

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    This article theorizes a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans. We frame the approach in the context of first- and second-generation prediction markets and outline its...

  3. Predictability of the terrestrial carbon cycle. (United States)

    Luo, Yiqi; Keenan, Trevor F; Smith, Matthew


    Terrestrial ecosystems sequester roughly 30% of anthropogenic carbon emission. However this estimate has not been directly deduced from studies of terrestrial ecosystems themselves, but inferred from atmospheric and oceanic data. This raises a question: to what extent is the terrestrial carbon cycle intrinsically predictable? In this paper, we investigated fundamental properties of the terrestrial carbon cycle, examined its intrinsic predictability, and proposed a suite of future research directions to improve empirical understanding and model predictive ability. Specifically, we isolated endogenous internal processes of the terrestrial carbon cycle from exogenous forcing variables. The internal processes share five fundamental properties (i.e., compartmentalization, carbon input through photosynthesis, partitioning among pools, donor pool-dominant transfers, and the first-order decay) among all types of ecosystems on the Earth. The five properties together result in an emergent constraint on predictability of various carbon cycle components in response to five classes of exogenous forcing. Future observational and experimental research should be focused on those less predictive components while modeling research needs to improve model predictive ability for those highly predictive components. We argue that an understanding of predictability should provide guidance on future observational, experimental and modeling research. © 2014 John Wiley & Sons Ltd.

  4. Surgical Apgar Score predicts postoperative complications in ...

    African Journals Online (AJOL)

    Background: Predicting complications in neurotrauma patients by using an effective scoring system can reduce morbidity and mortality while facilitating objective clinical decision making during recovery. Compared to existing morbidity and mortality predictive scores, the Surgical Apgar Score (SAS) is simple and effective.

  5. Nucleic acid secondary structure prediction and display.


    Stüber, K


    A set of programs has been developed for the prediction and display of nucleic acid secondary structures. Information from experimental data can be used to restrict or enforce secondary structural elements. The predictions can be displayed either on normal line printers or on graphic devices like plotters or graphic terminals.

  6. Relationship between water temperature predictability and aquatic ...

    African Journals Online (AJOL)

    Variable seasonal stream temperatures are a critical factor in maintaining aquatic invertebrate community patterns. We investigated whether the degree of predictability in a stream's water temperature profile provides insights into the structure and functional predictability of macroinvertebrate communities. Quarterly ...


    African Journals Online (AJOL)

    Preferred Customer

    vapor pressure prediction and saturated volume prediction in vicinity of critical point. KEY WORDS. KEY WORDS: Equation of state, Saturated properties, ..... The AARD between experimental and calculated saturated vapor molar volume given by. Trebble [18] were 5.81, 5.34, 5.08, and 10.62 for SRK, PR, CCOR, and PT, ...

  8. Gaussian processes for prediction in intensive care


    Guiza Grandas, Fabian; Ramon, Jan; Blockeel, Hendrik


    In this paper we present the use of Gaussian Processes for regression in the application of prediction in Intensive Care. We propose a preliminary solution to predicting the evolution of a patient's state during his stay in intensive care by means of defined patient specific characteristics.

  9. Prediction of twin-arginine signal peptides

    Directory of Open Access Journals (Sweden)

    Widdick David


    Full Text Available Abstract Background Proteins carrying twin-arginine (Tat signal peptides are exported into the periplasmic compartment or extracellular environment independently of the classical Sec-dependent translocation pathway. To complement other methods for classical signal peptide prediction we here present a publicly available method, TatP, for prediction of bacterial Tat signal peptides. Results We have retrieved sequence data for Tat substrates in order to train a computational method for discrimination of Sec and Tat signal peptides. The TatP method is able to positively classify 91% of 35 known Tat signal peptides and 84% of the annotated cleavage sites of these Tat signal peptides were correctly predicted. This method generates far less false positive predictions on various datasets than using simple pattern matching. Moreover, on the same datasets TatP generates less false positive predictions than a complementary rule based prediction method. Conclusion The method developed here is able to discriminate Tat signal peptides from cytoplasmic proteins carrying a similar motif, as well as from Sec signal peptides, with high accuracy. The method allows filtering of input sequences based on Perl syntax regular expressions, whereas hydrophobicity discrimination of Tat- and Sec-signal peptides is carried out by an artificial neural network. A potential cleavage site of the predicted Tat signal peptide is also reported. The TatP prediction server is available as a public web server at

  10. Deformation Prediction Using Linear Polynomial Functions ...

    African Journals Online (AJOL)

    The predictions are compared with measured data reported in literature and the results are discussed. The computational aspects of implementation of the model are also discussed briefly. Keywords: Linear Polynomial, Structural Deformation, Prediction Journal of the Nigerian Association of Mathematical Physics, Volume ...

  11. Adaptive prediction applied to seismic event detection

    International Nuclear Information System (INIS)

    Clark, G.A.; Rodgers, P.W.


    Adaptive prediction was applied to the problem of detecting small seismic events in microseismic background noise. The Widrow-Hoff LMS adaptive filter used in a prediction configuration is compared with two standard seismic filters as an onset indicator. Examples demonstrate the technique's usefulness with both synthetic and actual seismic data

  12. Adaptive prediction applied to seismic event detection

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Rodgers, P.W.


    Adaptive prediction was applied to the problem of detecting small seismic events in microseismic background noise. The Widrow-Hoff LMS adaptive filter used in a prediction configuration is compared with two standard seismic filters as an onset indicator. Examples demonstrate the technique's usefulness with both synthetic and actual seismic data.

  13. Prediction of mirror performance from laboratory measurements

    International Nuclear Information System (INIS)

    Church, E.L.; Takacs, P.Z.


    This paper describes and illustrates a simple method of predicting the imaging performance of synchrotron mirrors from laboratory measurements of their profiles. It discusses the important role of the transverse coherence length of the incident radiation, the fractal-like form of the mirror roughness, mirror characterization, and the use of closed-form expressions for the predicted image intensities

  14. Seasonal predictions for wildland fire severity (United States)

    Shyh-Chin Chen; Haiganoush Preisler; Francis Fujioka; John W. Benoit; John O. Roads


    The National Fire Danger Rating System (NFDRS) indices deduced from the monthly to seasonal predictions of a meteorological climate model at 50-km grid space from January 1998 through December 2003 were used in conjunction with a probability model to predict the expected number of fire occurrences and large fires over the U.S. West. The short-term climate forecasts are...

  15. Prediction of pain sensitivity in healthy volunteers

    DEFF Research Database (Denmark)

    Ravn, Pernille; Frederiksen, R; Skovsen, AP


    The primary objective of the present study was to evaluate predictive parameters of the acute pain score during induction of an inflammatory heat injury.......The primary objective of the present study was to evaluate predictive parameters of the acute pain score during induction of an inflammatory heat injury....

  16. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  17. Characterization of uncertainty in ETMS flight events predictions and its effect on traffic demand predictions (United States)


    This report presents the results of analysis and characterization of uncertainty in traffic demand predictions using ETMS data and probabilistic representation of the predictions. Our previous research, described in two prior reports, was focused on ...

  18. Customer Churn Prediction for Broadband Internet Services (United States)

    Huang, B. Q.; Kechadi, M.-T.; Buckley, B.

    Although churn prediction has been an area of research in the voice branch of telecommunications services, more focused studies on the huge growth area of Broadband Internet services are limited. Therefore, this paper presents a new set of features for broadband Internet customer churn prediction, based on Henley segments, the broadband usage, dial types, the spend of dial-up, line-information, bill and payment information, account information. Then the four prediction techniques (Logistic Regressions, Decision Trees, Multilayer Perceptron Neural Networks and Support Vector Machines) are applied in customer churn, based on the new features. Finally, the evaluation of new features and a comparative analysis of the predictors are made for broadband customer churn prediction. The experimental results show that the new features with these four modelling techniques are efficient for customer churn prediction in the broadband service field.

  19. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E


    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  20. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil


    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  1. Predicting the duration of the Syrian insurgency

    Directory of Open Access Journals (Sweden)

    Ulrich Pilster


    Full Text Available While there were several relatively short uprisings in Northern Africa and the Middle East during the Arab Spring, the dispute between the rebels and government forces in Syria has evolved into a full-scale civil war. We try to predict the length of the Syrian insurgency with a three-stage technique. Using out-of-sample techniques, we first assess the predictive capacity of 69 explanatory variables for insurgency duration. After determining the model with the highest predictive power, we categorize Syria according to the variables in this final model. Based on in-sample approaches, we then predict the duration of the Syrian uprising for three different scenarios. The most realistic point prediction is 5.12 years from the insurgency’s start, which suggests an end date between the end of 2016 and early 2017.

  2. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang


    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  3. Ellipsoidal prediction regions for multivariate uncertainty characterization

    DEFF Research Database (Denmark)

    Golestaneh, Faranak; Pinson, Pierre; Azizipanah-Abarghooee, Rasoul


    , for classes of decision-making problems based on robust, interval chance-constrained optimization, necessary inputs take the form of multivariate prediction regions rather than scenarios. The current literature is at very primitive stage of characterizing multivariate prediction regions to be employed...... in these classes of optimization problems. To address this issue, we introduce a new class of multivariate forecasts which form as multivariate ellipsoids for non-Gaussian variables. We propose a data-driven systematic framework to readily generate and evaluate ellipsoidal prediction regions, with predefined...... probability guarantees and minimum conservativeness. A skill score is proposed for quantitative assessment of the quality of prediction ellipsoids. A set of experiments is used to illustrate the discrimination ability of the proposed scoring rule for potential misspecification of ellipsoidal prediction regions...

  4. Emotional intelligence predicts success in medical school. (United States)

    Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane


    Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  5. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    CERN. Geneva


    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  6. Genomic Prediction of Barley Hybrid Performance

    Directory of Open Access Journals (Sweden)

    Norman Philipp


    Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

  7. Machine learning methods for metabolic pathway prediction

    Directory of Open Access Journals (Sweden)

    Karp Peter D


    Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

  8. Machine learning methods for metabolic pathway prediction (United States)


    Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML) methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations. PMID:20064214

  9. Adaptive Outlier-tolerant Exponential Smoothing Prediction Algorithms with Applications to Predict the Temperature in Spacecraft


    Hu Shaolin; Zhang Wei; Li Ye; Fan Shunxi


    The exponential smoothing prediction algorithm is widely used in spaceflight control and in process monitoring as well as in economical prediction. There are two key conundrums which are open: one is about the selective rule of the parameter in the exponential smoothing prediction, and the other is how to improve the bad influence of outliers on prediction. In this paper a new practical outlier-tolerant algorithm is built to select adaptively proper parameter, and the exponential smoothing pr...

  10. "When does making detailed predictions make predictions worse?": Correction to Kelly and Simmons (2016). (United States)


    Reports an error in "When Does Making Detailed Predictions Make Predictions Worse" by Theresa F. Kelly and Joseph P. Simmons ( Journal of Experimental Psychology: General , Advanced Online Publication, Aug 8, 2016, np). In the article, the symbols in Figure 2 were inadvertently altered in production. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-37952-001.) In this article, we investigate whether making detailed predictions about an event worsens other predictions of the event. Across 19 experiments, 10,896 participants, and 407,045 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes useless or redundant information more accessible and thus more likely to be incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of events will and will not be susceptible to the negative effect of making detailed predictions. PsycINFO Database Record (c) 2016 APA, all rights reserved

  11. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu


    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  12. DPRESS: Localizing estimates of predictive uncertainty

    Directory of Open Access Journals (Sweden)

    Clark Robert D


    Full Text Available Abstract Background The need to have a quantitative estimate of the uncertainty of prediction for QSAR models is steadily increasing, in part because such predictions are being widely distributed as tabulated values disconnected from the models used to generate them. Classical statistical theory assumes that the error in the population being modeled is independent and identically distributed (IID, but this is often not actually the case. Such inhomogeneous error (heteroskedasticity can be addressed by providing an individualized estimate of predictive uncertainty for each particular new object u: the standard error of prediction su can be estimated as the non-cross-validated error st* for the closest object t* in the training set adjusted for its separation d from u in the descriptor space relative to the size of the training set. The predictive uncertainty factor γt* is obtained by distributing the internal predictive error sum of squares across objects in the training set based on the distances between them, hence the acronym: Distributed PRedictive Error Sum of Squares (DPRESS. Note that st* and γt*are characteristic of each training set compound contributing to the model of interest. Results The method was applied to partial least-squares models built using 2D (molecular hologram or 3D (molecular field descriptors applied to mid-sized training sets (N = 75 drawn from a large (N = 304, well-characterized pool of cyclooxygenase inhibitors. The observed variation in predictive error for the external 229 compound test sets was compared with the uncertainty estimates from DPRESS. Good qualitative and quantitative agreement was seen between the distributions of predictive error observed and those predicted using DPRESS. Inclusion of the distance-dependent term was essential to getting good agreement between the estimated uncertainties and the observed distributions of predictive error. The uncertainty estimates derived by DPRESS were

  13. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo


    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  14. Development of a Climate Prediction Market (United States)

    Roulston, M. S.


    Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.

  15. Evaluation of protein dihedral angle prediction methods.

    Directory of Open Access Journals (Sweden)

    Harinder Singh

    Full Text Available Tertiary structure prediction of a protein from its amino acid sequence is one of the major challenges in the field of bioinformatics. Hierarchical approach is one of the persuasive techniques used for predicting protein tertiary structure, especially in the absence of homologous protein structures. In hierarchical approach, intermediate states are predicted like secondary structure, dihedral angles, Cα-Cα distance bounds, etc. These intermediate states are used to restraint the protein backbone and assist its correct folding. In the recent years, several methods have been developed for predicting dihedral angles of a protein, but it is difficult to conclude which method is better than others. In this study, we benchmarked the performance of dihedral prediction methods ANGLOR and SPINE X on various datasets, including independent datasets. TANGLE dihedral prediction method was not benchmarked (due to unavailability of its standalone and was compared with SPINE X and ANGLOR on only ANGLOR dataset on which TANGLE has reported its results. It was observed that SPINE X performed better than ANGLOR and TANGLE, especially in case of prediction of dihedral angles of glycine and proline residues. The analysis suggested that angle shifting was the foremost reason of better performance of SPINE X. We further evaluated the performance of the methods on independent ccPDB30 dataset and observed that SPINE X performed better than ANGLOR.

  16. Fingerprint verification prediction model in hand dermatitis. (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah


    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  17. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria


    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  18. Climate predictability in the second year. (United States)

    Hermanson, Leon; Sutton, Rowan T


    In this paper, the predictability of climate arising from ocean heat content (OHC) anomalies is investigated in the HadCM3 coupled atmosphere-ocean model. An ensemble of simulations of the twentieth century are used to provide initial conditions for a case study. The case study consists of two ensembles started from initial conditions with large differences in regional OHC in the North Atlantic, the Southern Ocean and parts of the West Pacific. Surface temperatures and precipitation are on average not predictable beyond seasonal time scales, but for certain initial conditions there may be longer predictability. It is shown that, for the case study examined here, some aspects of tropical precipitation, European surface temperatures and North Atlantic sea-level pressure are potentially predictable 2 years ahead. Predictability also exists in the other case studies, but the climate variables and regions, which are potentially predictable, differ. This work was done as part of the Grid for Coupled Ensemble Prediction (GCEP) eScience project.

  19. Clustered linear prediction for lossless compression of hyperspectral images using adaptive prediction length (United States)

    Mielikainen, Jarno


    This paper extends clustered differential pulse code modulation (C-DPCM) lossless compression method for hyperspectral images. In C-DPCM method the spectra of a hyperspectral image is clustered, and an optimized predictor is calculated for each cluster. Prediction is performed using a linear predictor. After prediction, the difference between the predicted and original values is computed. The difference is entropy-coded using an adaptive entropy coder for each cluster. The proposed use of adaptive prediction length is shown have lower bits/pixel value than the original C-DPCM method for new AVIRIS test images. Both calibrated are uncalibrated images showed improvement over fixed prediction length.

  20. Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding


    Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing


    This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

  1. Trust-based collective view prediction

    CERN Document Server

    Luo, Tiejian; Xu, Guandong; Zhou, Jia


    Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

  2. Link prediction in complex networks: A survey (United States)

    Lü, Linyuan; Zhou, Tao


    Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labeled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  3. Predictive Navigation by Understanding Human Motion Patterns

    Directory of Open Access Journals (Sweden)

    Shu-Yun Chung


    Full Text Available To make robots coexist and share the environments with humans, robots should understand the behaviors or the intentions of humans and further predict their motions. In this paper, an A*-based predictive motion planner is represented for navigation tasks. A generalized pedestrian motion model is proposed and trained by the statistical learning method. To deal with the uncertainty, a localization, tracking and prediction framework is also introduced. The corresponding recursive Bayesian formula represented as DBNs (Dynamic Bayesian Networks is derived for real time operation. Finally, the simulations and experiments are shown to validate the idea of this paper.

  4. Predicting facial characteristics from complex polygenic variations

    DEFF Research Database (Denmark)

    Fagertun, Jens; Wolffhechel, Karin Marie Brandt; Pers, Tune


    traits in a linear regression. We show in this proof-of-concept study for facial trait prediction from genome-wide SNP data that some facial characteristics can be modeled by genetic information: facial width, eyebrow width, distance between eyes, and features involving mouth shape are predicted......Research into the importance of the human genome in the context of facial appearance is receiving increasing attention and has led to the detection of several Single Nucleotide Polymorphisms (SNPs) of importance. In this work we attempt a holistic approach predicting facial characteristics from...

  5. Bursting frequency prediction in turbulent boundary layers

    Energy Technology Data Exchange (ETDEWEB)



    The frequencies of the bursting events associated with the streamwise coherent structures of spatially developing incompressible turbulent boundary layers were predicted using global numerical solution of the Orr-Sommerfeld and the vertical vorticity equations of hydrodynamic stability problems. The structures were modeled as wavelike disturbances associated with the turbulent mean flow. The global method developed here involves the use of second and fourth order accurate finite difference formula for the differential equations as well as the boundary conditions. An automated prediction tool, BURFIT, was developed. The predicted resonance frequencies were found to agree very well with previous results using a local shooting technique and measured data.

  6. Mixing time prediction using spherical microphone arrays. (United States)

    Götz, Philipp; Kowalczyk, Konrad; Silzle, Andreas; Habets, Emanuël A P


    Human perception of room acoustics depends among others on the time of transition from early reflections to late reverberation in room impulse responses, which is known as mixing time. In this letter, a multi-channel mixing time prediction method is proposed, which in contrast to state-of-the-art channel-based predictors accounts for spatiotemporal properties of the sound field. The proposed diffuseness-based method is compared with existing model- and channel-based prediction methods through measurements and acoustic simulations, and is shown to correlate well with the perceptual mixing time. Furthermore, insights into relations between prediction methods and mixing time definitions based on reflection density are presented.

  7. Computational predictions of zinc oxide hollow structures (United States)

    Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi


    Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

  8. Predictive power of nuclear-mass models

    Directory of Open Access Journals (Sweden)

    Yu. A. Litvinov


    Full Text Available Ten different theoretical models are tested for their predictive power in the description of nuclear masses. Two sets of experimental masses are used for the test: the older set of 2003 and the newer one of 2011. The predictive power is studied in two regions of nuclei: the global region (Z, N ≥ 8 and the heavy-nuclei region (Z ≥ 82, N ≥ 126. No clear correlation is found between the predictive power of a model and the accuracy of its description of the masses.

  9. Calorimeter prediction based on multiple exponentials

    International Nuclear Information System (INIS)

    Smith, M.K.; Bracken, D.S.


    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented

  10. Predicting Dyspnea Inducers by Molecular Topology

    Directory of Open Access Journals (Sweden)

    María Gálvez-Llompart


    Full Text Available QSAR based on molecular topology (MT is an excellent methodology used in predicting physicochemical and biological properties of compounds. This approach is applied here for the development of a mathematical model capable to recognize drugs showing dyspnea as a side effect. Using linear discriminant analysis, it was found a four-variable regression equations enabling a predictive rate of about 81% and 73% in the training and test sets of compounds, respectively. These results demonstrate that QSAR-MT is an efficient tool to predict the appearance of dyspnea associated with drug consumption.

  11. Fast Computing for LURR of Earthquake Prediction (United States)

    Feng, Yangde; Chi, Xuebin; Wang, Wu; Chen, Jiang; Yin, Xiangchu


    The LURR theory is a new approach for earthquake prediction, which achieves good results in earthquake prediction within the China mainland and regions in America, Japan and Australia. However, the expansion of the prediction region leads to the refinement of its longitude and latitude, and the increase of the time period. This requires increasingly more computations, and the volume of data reaches the order of GB, which will be very difficult for a single CPU. In this paper, a new method was introduced to solve this problem. Adopting the technology of domain decomposition and parallelizing using MPI, we developed a new parallel tempo-spatial scanning program.

  12. Generalised empirical method for predicting surface subsidence

    International Nuclear Information System (INIS)

    Zhang, M.; Bhattacharyya, A.K.


    Based on a simplified strata parameter, i.e. the ratio of total thickness of the strong rock beds in an overburden to the overall thickness of the overburden, a Generalised Empirical Method (GEM) is described for predicting the maximum subsidence and the shape of a complete transverse subsidence profile due to a single completely extracted longwall panel. In the method, a nomogram for predicting the maximum surface subsidence is first developed from the data collected from subsidence measurements worldwide. Then, a method is developed for predicting the shapes of complete transfer subsidence profiles for a horizontal seam and ground surface and is verified by case studies. 13 refs., 9 figs., 2 tabs

  13. BDDCS Class Prediction for New Molecular Entities (United States)

    Broccatelli, Fabio; Cruciani, Gabriele; Benet, Leslie Z.; Oprea, Tudor I.


    The Biopharmaceutics Drug Disposition Classification System (BDDCS) was successfully employed for predicting drug-drug interactions (DDIs) with respect to drug metabolizing enzymes (DMEs), drug transporters and their interplay. The major assumption of BDDCS is that the extent of metabolism (EoM) predicts high versus low intestinal permeability rate, and vice versa, at least when uptake transporters or paracellular transport are not involved. We recently published a collection of over 900 marketed drugs classified for BDDCS. We suggest that a reliable model for predicting BDDCS class, integrated with in vitro assays, could anticipate disposition and potential DDIs of new molecular entities (NMEs). Here we describe a computational procedure for predicting BDDCS class from molecular structures. The model was trained on a set of 300 oral drugs, and validated on an external set of 379 oral drugs, using 17 descriptors calculated or derived from the VolSurf+ software. For each molecule, a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction the accuracy was 82% in training and 79% in external validation. The actual BDDCS class corresponded to the highest ranked calculated class for 55% of the validation molecules, and it was within the top two ranked more than 92% of the times. The unbalanced stratification of the dataset didn’t affect the prediction, which showed highest accuracy in predicting classes 2 and 3 with respect to the most populated class 1. For class 4 drugs a general lack of predictability was observed. A linear discriminant analysis (LDA) confirmed the degree of accuracy for the prediction of the different BDDCS classes is tied to the structure of the dataset. This model could routinely be used in early drug discovery to prioritize in vitro tests for NMEs (e.g., affinity to transporters

  14. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  15. Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation. (United States)

    McDonagh, J L; van Mourik, T; Mitchell, J B O


    In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions: 1) Can we apply efficient machine learning techniques, using inexpensive descriptors, to predict melting points to a reasonable level of accuracy? 2) Can values of this level of accuracy be usefully applied to predicting aqueous solubility? We present predictions of melting points made by several novel machine learning models, previously applied to solubility prediction. Additionally, we make predictions of solubility via the General Solubility Equation (GSE) and monitor the impact of varying the logP prediction model (AlogP and XlogP) on the GSE. We note that the machine learning models presented, using a modest number of 2D descriptors, can make melting point predictions in line with the current state of the art prediction methods (RMSE≥40 °C). We also find that predicted melting points, with an RMSE of tens of degrees Celsius, can be usefully applied to the GSE to yield accurate solubility predictions (log10 S RMSE<1) over a small dataset of drug-like molecules. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Strong ground motion prediction using virtual earthquakes. (United States)

    Denolle, M A; Dunham, E M; Prieto, G A; Beroza, G C


    Sedimentary basins increase the damaging effects of earthquakes by trapping and amplifying seismic waves. Simulations of seismic wave propagation in sedimentary basins capture this effect; however, there exists no method to validate these results for earthquakes that have not yet occurred. We present a new approach for ground motion prediction that uses the ambient seismic field. We apply our method to a suite of magnitude 7 scenario earthquakes on the southern San Andreas fault and compare our ground motion predictions with simulations. Both methods find strong amplification and coupling of source and structure effects, but they predict substantially different shaking patterns across the Los Angeles Basin. The virtual earthquake approach provides a new approach for predicting long-period strong ground motion.

  17. Predicting Performance Ratings Using Motivational Antecedents

    National Research Council Canada - National Science Library

    Zazania, Michelle


    This research examined the role of motivation in predicting peer and trainer ratings of student performance and contrasted the relative importance of various antecedents for peer and trainer ratings...

  18. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.


    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  19. Prediction Methods for Blood Glucose Concentration

    DEFF Research Database (Denmark)

    , but the insulin amount is chosen using factors that account for this expectation. The increasing availability of more accurate continuous blood glucose measurement (CGM) systems is attracting much interest to the possibilities of explicit prediction of future BG values. Against this background, in 2014 a two...... by the authors at the workshop but were written afterward which allowed to include the findings and conclusions of the various discussions and of course updates. The chapter "Alternative Frameworks for Personalized Insulin-Glucose Models" by Harald Kirchsteiger et al. asks the question whether more and more...... that focus not on the prediction of exact future blood glucose values, but rather on the prediction of changes in the patients’ blood glucose range. The chapter “Accuracy of BG Meters and CGM Systems: Possible Influence Factors for the Glucose Prediction Based on Tissue Glucose Concentrations” by Guido...

  20. Calibration of PMIS pavement performance prediction models. (United States)


    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  1. Predictive Model Assessment for Count Data

    National Research Council Canada - National Science Library

    Czado, Claudia; Gneiting, Tilmann; Held, Leonhard


    .... In case studies, we critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. Key words: Calibration...

  2. Predicting incident size from limited information

    International Nuclear Information System (INIS)

    Englehardt, J.D.


    Predicting the size of low-probability, high-consequence natural disasters, industrial accidents, and pollutant releases is often difficult due to limitations in the availability of data on rare events and future circumstances. When incident data are available, they may be difficult to fit with a lognormal distribution. Two Bayesian probability distributions for inferring future incident-size probabilities from limited, indirect, and subjective information are proposed in this paper. The distributions are derived from Pareto distributions that are shown to fit data on different incident types and are justified theoretically. The derived distributions incorporate both inherent variability and uncertainty due to information limitations. Results were analyzed to determine the amount of data needed to predict incident-size probabilities in various situations. Information requirements for incident-size prediction using the methods were low, particularly when the population distribution had a thick tail. Use of the distributions to predict accumulated oil-spill consequences was demonstrated

  3. Developments in Property Predictions for Weld Metal

    National Research Council Canada - National Science Library

    Olson, D


    With the introduction of higher strength low-carbon steels, which have properties that are based on strengthening mechanisms other than the austenitic decomposition, new predictive expressions are required...

  4. Chemical Function Predictions for Tox21 Chemicals (United States)

    U.S. Environmental Protection Agency — Random forest chemical function predictions for Tox21 chemicals in personal care products uses and "other" uses. This dataset is associated with the following...

  5. On the predictability of ice avalanches

    Directory of Open Access Journals (Sweden)

    A. Pralong


    Full Text Available The velocity of unstable large ice masses from hanging glaciers increases as a power-law function of time prior to failure. This characteristic acceleration presents a finite-time singularity at the theoretical time of failure and can be used to forecast the time of glacier collapse. However, the non-linearity of the power-law function makes the prediction difficult. The effects of the non-linearity on the predictability of a failure are analyzed using a non-linear regression method. Predictability strongly depends on the time window when the measurements are performed. Log-periodic oscillations have been observed to be superimposed on the motion of large unstable ice masses. The value of their amplitude, frequency and phase are observed to be spatially homogeneous over the whole unstable ice mass. Inclusion of a respective term in the function describing the acceleration of unstable ice masses greatly increases the accuracy of the prediction.

  6. Vitamin D Levels Predict Multiple Sclerosis Progression (United States)

    ... Research Matters NIH Research Matters February 3, 2014 Vitamin D Levels Predict Multiple Sclerosis Progression Among people with ... sclerosis (MS), those with higher blood levels of vitamin D had better outcomes during 5 years of follow- ...

  7. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra


    ). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. oBjectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project......) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. Methods: CERAPP combined multiple models developed in collaboration with 17 groups in the United......: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. conclusion: This project demonstrated...

  8. Are animal models predictive for humans?

    Directory of Open Access Journals (Sweden)

    Greek Ray


    Full Text Available Abstract It is one of the central aims of the philosophy of science to elucidate the meanings of scientific terms and also to think critically about their application. The focus of this essay is the scientific term predict and whether there is credible evidence that animal models, especially in toxicology and pathophysiology, can be used to predict human outcomes. Whether animals can be used to predict human response to drugs and other chemicals is apparently a contentious issue. However, when one empirically analyzes animal models using scientific tools they fall far short of being able to predict human responses. This is not surprising considering what we have learned from fields such evolutionary and developmental biology, gene regulation and expression, epigenetics, complexity theory, and comparative genomics.

  9. Programming Useful Life Prediction (PULP), Phase I (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements. Relying on...

  10. Traffic Predictive Control: Case Study and Evaluation (United States)


    This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...

  11. Predicting visual acuity from detection thresholds. (United States)

    Newacheck, J S; Haegerstrom-Portnoy, G; Adams, A J


    Visual performance based exclusively on high luminance and high contrast letter acuity measures often fails to predict individual performance at low contrast and low luminance. Here we measured visual acuity over a wide range of contrasts and luminances (low mesopic to photopic) for 17 young normal observers. Acuity vs. contrast functions appear to fit a single template which can be displaced laterally along the log contrast axis. The magnitude of this lateral displacement for different luminances was well predicted by the contrast threshold difference for a 4 min arc spot. The acuity vs. contrast template, taken from the mean of all 17 subjects, was used in conjunction with individual spot contrast threshold measures to predict an individual's visual acuity over a wide range of luminance and contrast levels. The accuracy of the visual acuity predictions from this simple procedure closely approximates test-retest accuracy for both positive (projected Landolt rings) and negative contrast (Bailey-Lovie charts).

  12. Improving predictions by cross pollination in time (United States)

    Schevenhoven, Francine; Selten, Frank


    Given a set of imperfect weather models, one could ask how these models can be combined in order to improve weather predictions produced with these models. In this study we explore a technique called cross-pollination in time (CPT, Smith 2001). In the CPT approach the models exchange states during the prediction. The number of possible predictions grows quickly with time and a strategy to retain only a small number of predictions, called pruning, needs to be developed. In the learning phase a pruning strategy is proposed based on retaining those solutions that remain closest to the truth. From the learning phase probabilities are derived that determine weights to be applied to the imperfect models in the forecast phase. The CPT technique is explored using low-order dynamical systems and applied to a global atmospheric model. First results indicate that the CPT approach improves the forecast quality over the individual models.

  13. Regression models for predicting anthropometric measurements of ...

    African Journals Online (AJOL)

    measure anthropometric dimensions to predict difficult-to-measure dimensions required for ergonomic design of school furniture. A total of 143 students aged between 16 and 18 years from eight public secondary schools in Ogbomoso, Nigeria ...

  14. Enhanced Ocean Predictability Through Optimal Observing Strategies

    National Research Council Canada - National Science Library

    Kirwan, A


    The long term goal of this research is to develop the requisite technology to design effective observation strategies that will maximize the capacity to predict mesoscale and submesoscale conditions...

  15. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp


    deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs......) for modeling and forecasting. It is argued that this gives models and predictions which better reflect reality. The SDE approach also offers a more adequate framework for modeling and a number of efficient tools for model building. A software package (CTSM-R) for SDE-based modeling is briefly described....... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...

  16. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.


    a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting......This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...

  17. Diffusion changes predict cognitive and functional outcome

    DEFF Research Database (Denmark)

    Jokinen, Hanna; Schmidt, Reinhold; Ropele, Stefan


    A study was undertaken to determine whether diffusion-weighted imaging (DWI) abnormalities in normal-appearing brain tissue (NABT) and in white matter hyperintensities (WMH) predict longitudinal cognitive decline and disability in older individuals independently of the concomitant magnetic...

  18. Prediction of deformity in spinal tuberculosis

    NARCIS (Netherlands)

    Jutte, Paul; Wuite, Sander; The, Bertram; van Altena, Richard; Veldhuizen, Albert

    Tuberculosis of the spine may cause kyphosis, which may in turn cause late paraplegia, respiratory compromise, and unsightly deformity. Surgical correction therefore may be considered for large or progressive deformities. We retrospectively analyzed clinical and radiographic parameters to predict

  19. Predicting Engine Parameters using the Optical Spectrum (United States)

    National Aeronautics and Space Administration — The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME)....

  20. Neural net prediction of tokamak plasma disruptions

    International Nuclear Information System (INIS)

    Hernandez, J.V.; Lin, Z.; Horton, W.; McCool, S.C.


    The computation based on neural net algorithms in predicting minor and major disruptions in TEXT tokamak discharges has been performed. Future values of the fluctuating magnetic signal are predicted based on L past values of the magnetic fluctuation signal, measured by a single Mirnov coil. The time step used (= 0.04ms) corresponds to the experimental data sampling rate. Two kinds of approaches are adopted for the task, the contiguous future prediction and the multi-timescale prediction. Results are shown for comparison. Both networks are trained through the back-propagation algorithm with inertial terms. The degree of this success indicates that the magnetic fluctuations associated with tokamak disruptions may be characterized by a relatively low-dimensional dynamical system

  1. Earthquake Prediction Techniques: Their Application in Japan (United States)

    Kisslinger, Carl

    Japan is serious about solving the earthquake prediction problem. A well-organized and well-funded program of research has been under way for almost 20 years in pursuit of the national goal of protecting the dense population of this earthquake-prone country through reliable predictions.This rather amazing book, edited by Toshi Asada, retired director of the Geophysical Institute of the University of Tokyo, has been written by 10 scientists, each of whom has made important contributions to earthquake science, but who have not been known in the past as principal spokesmen for the Japanese earthquake prediction program. The result is a combination of a very readable tutorial presentation of basic earthquake science that will make the book understandable to the nonspecialist, a good summary of Japanese data and research conclusions, and a bare-knuckles appraisal of current philosophy and strategy for prediction in Japan.

  2. Short-term wind power prediction

    DEFF Research Database (Denmark)

    Joensen, Alfred K.


    The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity, and to imple......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity......, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant...

  3. Predicting Employer's Benefits from Cooperative Education. (United States)

    Wiseman, Richard L.; Page, Norman R.


    Attempts to predict employer benefits resulting from their involvement in cooperative education programs. Benefits include a good source of quality employees, increased worker motivation, and increased respect between students and employers. (JOW)

  4. Predictive Analytics with Big Social Data

    DEFF Research Database (Denmark)

    Buus Lassen, Niels; Madsen, René; Vatrapu, Ravi

    Recent research in the field of computational social science have shown how data resulting from the widespread adoption and use of social media channels such as twitter can be used to predict outcomes such as movie revenues, election winners, localized moods, and epidemic outbreaks. Underlying......, we demonstrate how social media data from twitter and facebook can be used to predict the quarterly sales of iPhones and revenues of H&M respectively. Based on a conceptual model of social data consisting of social graph (actors, actions, activities, and artefacts) and social text (topics, keywords......, pronouns, and sentiments), we develop and evaluate linear regression models that transform (a) iPhone tweets into a prediction of the quarterly iPhone sales with an average error close to the established prediction models from investment banks (Lassen, Madsen, & Vatrapu, 2014)and (b) facebook likes...

  5. Asthma Medication Ratio Predicts Emergency Depart... (United States)

    U.S. Department of Health & Human Services — According to findings reported in Asthma Medication Ratio Predicts Emergency Department Visits and Hospitalizations in Children with Asthma, published in Volume 3,...

  6. Prediction methods and databases within chemoinformatics

    DEFF Research Database (Denmark)

    Jónsdóttir, Svava Osk; Jørgensen, Flemming Steen; Brunak, Søren


    MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information...... about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability...... of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described....

  7. Numerical prediction of shoreline adjacent to breakwater

    Digital Repository Service at National Institute of Oceanography (India)

    Mahadevan, R.; Chandramohan, P.; Nayak, B.U.

    Existing mathematical models for prediction of shoreline changes in the vicinity of a breakwater were reviewed The analytical and numerical results obtained from these models have been compared Under the numerical approach, two different implicit...

  8. Predicting the future of sports organizations

    Directory of Open Access Journals (Sweden)

    Jugoslav Vojinovic


    Full Text Available The current crisis of sport in Serbia justifies its prediction of real potential future of sport organizations. Sample of respondents (N=277 was divided in two subsamples: 113 professional persons involved in the management of sports clubs ("experimental" sample and 164 individuals ("control" sample. The results of structural analysis showed that experimental sample based its vision on the staff as a determinant of the system, which is providing creativity as a characteristic of the organizational culture of the club. Control subsample of respondents could indicate some characteristic variables to predict the future of clubs, but can't say a clear prediction system based on a long sequence of reasoning. We can conclude that the mentioned two sub-samples are differerent in terms of the ability to orient to predict the future of their clubs on the basis of assessment of the key variables that shape the future scenarios.

  9. Hybrid approaches to physiologic modeling and prediction (United States)

    Olengü, Nicholas O.; Reifman, Jaques


    This paper explores how the accuracy of a first-principles physiological model can be enhanced by integrating data-driven, "black-box" models with the original model to form a "hybrid" model system. Both linear (autoregressive) and nonlinear (neural network) data-driven techniques are separately combined with a first-principles model to predict human body core temperature. Rectal core temperature data from nine volunteers, subject to four 30/10-minute cycles of moderate exercise/rest regimen in both CONTROL and HUMID environmental conditions, are used to develop and test the approach. The results show significant improvements in prediction accuracy, with average improvements of up to 30% for prediction horizons of 20 minutes. The models developed from one subject's data are also used in the prediction of another subject's core temperature. Initial results for this approach for a 20-minute horizon show no significant improvement over the first-principles model by itself.

  10. Financial distress prediction and operating leases

    NARCIS (Netherlands)

    Lückerath – Rovers, M.


    This study investigates whether including operating lease commitments in financial distress prediction models would increase the classification accuracy of these models. Classification accuracy measures the percentages of correctly classified companies in either of the two categories (healthy or

  11. Predictive Values of Electroencephalography (EEG) in Epilepsy ...

    African Journals Online (AJOL)

    Predictive Values of Electroencephalography (EEG) in Epilepsy Patients with Abnormal Behavioural Symptoms. OR Obiako, SO Adeyemi, TL Sheikh, LF Owolabi, MA Majebi, MO Gomina, F Adebayo, EU Iwuozo ...


    African Journals Online (AJOL)

    direction (σx) had a maximum value of 375MPa (tensile) and minimum value of ... These results shows that the residual stresses obtained by prediction from the finite element method are in fair agreement with the experimental results.

  13. Prediction Methods for Blood Glucose Concentration

    DEFF Research Database (Denmark)

    “Recent Results on Glucose–Insulin Predictions by Means of a State Observer for Time-Delay Systems” by Pasquale Palumbo et al. introduces a prediction model which in real time predicts the insulin concentration in blood which in turn is used in a control system. The method is tested in simulation......Standard diabetes insulin therapy for type 1 diabetes and late stages of type 2 is based on the expected development of blood glucose (BG) both as a consequence of the metabolic glucose consumption as well as of meals and exogenous insulin intake. Traditionally, this is not done explicitly......, but the insulin amount is chosen using factors that account for this expectation. The increasing availability of more accurate continuous blood glucose measurement (CGM) systems is attracting much interest to the possibilities of explicit prediction of future BG values. Against this background, in 2014 a two...

  14. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara


    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...... visualization to improve our understanding of the different attained performances, effectively compiling all the conducted experiments in a meaningful way. We complete our study with an entropy-based analysis that highlights the uncertainty handling properties provided by the GP, crucial for prediction tasks...

  15. A Global Model for Bankruptcy Prediction. (United States)

    Alaminos, David; Del Castillo, Agustín; Fernández, Manuel Ángel


    The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy.

  16. A method for predicting monthly rainfall patterns

    International Nuclear Information System (INIS)

    Njau, E.C.


    A brief survey is made of previous methods that have been used to predict rainfall trends or drought spells in different parts of the earth. The basic methodologies or theoretical strategies used in these methods are compared with contents of a recent theory of Sun-Weather/Climate links (Njau, 1985a; 1985b; 1986; 1987a; 1987b; 1987c) which point towards the possibility of practical climatic predictions. It is shown that not only is the theoretical basis of each of these methodologies or strategies fully incorporated into the above-named theory, but also this theory may be used to develop a technique by which future monthly rainfall patterns can be predicted in further and finer details. We describe the latter technique and then illustrate its workability by means of predictions made on monthly rainfall patterns in some East African meteorological stations. (author). 43 refs, 11 figs, 2 tabs

  17. Genomic Prediction of Gene Bank Wheat Landraces

    Directory of Open Access Journals (Sweden)

    José Crossa


    Full Text Available This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H for the highly heritable traits, days to heading (DTH, and days to maturity (DTM. Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E. Two alternative prediction strategies were studied: (1 random cross-validation of the data in 20% training (TRN and 80% testing (TST (TRN20-TST80 sets, and (2 two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm

  18. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.


    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  19. Transistor Aging Prediction in Nanometer Digital Circuits


    Kyung Ki Kim


    In nanometer technology, accurate aging prediction of MOSFET digital circuits is one of the most critical issues for more reliable adaptive system design. This paper proposes a new on-chip aging prediction circuit to monitor BTI and HCI aging effects on digital circuits. The proposed circuit deploys a flip-flop based delay detector for monitoring a guardband violation of sequential logics. The outputs of the proposed circuit can be used as a control signal in reliable self-adaptive systems. A...

  20. A Kernel for Protein Secondary Structure Prediction


    Guermeur , Yann; Lifchitz , Alain; Vert , Régis

    2004-01-01; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...