990 resultados para Algorithmic skeleton


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Analyzing statistical dependencies is a fundamental problem in all empirical science. Dependencies help us understand causes and effects, create new scientific theories, and invent cures to problems. Nowadays, large amounts of data is available, but efficient computational tools for analyzing the data are missing. In this research, we develop efficient algorithms for a commonly occurring search problem - searching for the statistically most significant dependency rules in binary data. We consider dependency rules of the form X->A or X->not A, where X is a set of positive-valued attributes and A is a single attribute. Such rules describe which factors either increase or decrease the probability of the consequent A. A classical example are genetic and environmental factors, which can either cause or prevent a disease. The emphasis in this research is that the discovered dependencies should be genuine - i.e. they should also hold in future data. This is an important distinction from the traditional association rules, which - in spite of their name and a similar appearance to dependency rules - do not necessarily represent statistical dependencies at all or represent only spurious connections, which occur by chance. Therefore, the principal objective is to search for the rules with statistical significance measures. Another important objective is to search for only non-redundant rules, which express the real causes of dependence, without any occasional extra factors. The extra factors do not add any new information on the dependence, but can only blur it and make it less accurate in future data. The problem is computationally very demanding, because the number of all possible rules increases exponentially with the number of attributes. In addition, neither the statistical dependency nor the statistical significance are monotonic properties, which means that the traditional pruning techniques do not work. As a solution, we first derive the mathematical basis for pruning the search space with any well-behaving statistical significance measures. The mathematical theory is complemented by a new algorithmic invention, which enables an efficient search without any heuristic restrictions. The resulting algorithm can be used to search for both positive and negative dependencies with any commonly used statistical measures, like Fisher's exact test, the chi-squared measure, mutual information, and z scores. According to our experiments, the algorithm is well-scalable, especially with Fisher's exact test. It can easily handle even the densest data sets with 10000-20000 attributes. Still, the results are globally optimal, which is a remarkable improvement over the existing solutions. In practice, this means that the user does not have to worry whether the dependencies hold in future data or if the data still contains better, but undiscovered dependencies.

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We discuss three approaches to the use of technology as a teaching and learning tool that we are currently implementing for a target group of about one hundred second level engineering mathematics students. Central to these approaches is the underlying theme of motivating relatively poorly motivated students to learn, with the aim of improving learning outcomes. The approaches to be discussed have been used to replace, in part, more traditional mathematics tutorial sessions and lecture presentations. In brief, the first approach involves the application of constructivist thinking in the tertiary education arena, using technology as a computational and visual tool to create motivational knowledge conflicts or crises. The central idea is to model a realistic process of how scientific theory is actually developed, as proposed by Kuhn (1962), in contrast to more standard lecture and tutorial presentations. The second approach involves replacing procedural or algorithmic pencil-and-paper skills-consolidation exercises by software based tasks. Finally, the third approach aims at creating opportunities for higher order thinking via "on-line" exploratory or discovery mode tasks. The latter incorporates the incubation period method, as originally discussed by Rubinstein (1975) and others.

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Achieving stabilization of telomeric DNA in G-quadruplex conformation by Various organic compounds has been an important goal for the medicinal chemists seeking to develop new anticancer agents. Several compounds are known to stabilize G-quadruplexes. However, relatively few are known to induce their formation and/or alter the topology, of the preformed quadruplex DNA. Herein, four compounds having the 1,3-phenylene-bis(piperazinyl benzimidazole) unit as a basic skeleton have been synthesized, and their interactions with the 24-mer telomeric DNA sequences from Tetrahymena thermophilia d(T(2)G(4))(4) have been investigated using high-resolution techniques Such as circular dichroism (CD) spectropolarimetry, CD melting, emission spectroscopy, and polyacrylamide gel electrophoresis. The data obtained, in the presence of one of three ions (Li+, Na+, or K+), indicate that all the new compounds have a high affinity for G-quadruplex DNA, and the strength of the binding with G-quadruplex depends on (1) phenyl ring substitution, (ii) the piperazinyl side chain, and (iii) the type of monovalent cation present in the buffer. Results further Suggest that these compounds are able to abet the conversion of the Intramolecular quadruplex into parallel stranded intermolecular G-quadruplex DNA. Notably, these compounds are also capable of inducing and stabilizing the parallel stranded quadruplex from randomly structured DNA in the absence of any stabilizing cation. The kinetics of the structural changes Induced by these compounds could be followed by recording the changes in the CD signal as a function of time. The implications of the findings mentioned above are discussed in this paper.

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MicroRNAs (miRNAs) are critical post-transcriptional regulators. Based on a previous genome-wide association (GWA) scan, we conducted a polymorphism in microRNAs' Target Sites (poly-miRTS)-centric multistage meta-analysis for lumbar spine (LS)-, total hip (HIP)-, and femoral neck (FN)-bone mineral density (BMD). In stage I, 41,102 poly-miRTSs were meta-analyzed in 7 cohorts with a genome-wide significance (GWS) α=0.05/41,102=1.22×10-6. By applying α=5×10-5 (suggestive significance), 11 poly-miRTSs were selected, with FGFRL1 rs4647940 and PRR5 rs3213550 as top signals for FN-BMD (P-value=7.67×10-6 and 1.58×10-5) in gender-combined sample. In stage II in silico replication (two cohorts), FGFRL1 rs4647940 was the only signal marginally replicated for FN-BMD (P-value=5.08×10-3) at α=0.10/11=9.09×10-3. PRR5 rs3213550 was also selected based on biological significance. In stage III de novo genotyping replication (two cohorts), FGFRL1 rs4647940 was the only signal significantly replicated for FN-BMD (P-value=7.55×10-6) at α=0.05/2=0.025 in gender-combined sample. Aggregating three stages, FGFRL1 rs4647940 was the single stage I-discovered and stages II- and III-replicated signal attaining GWS for FN-BMD (P-value=8.87×10-12). Dual-luciferase reporter assays demonstrated that FGFRL1 3' untranslated region harboring rs4647940 appears to be hsa-miR-140-5p's target site. In a zebrafish microinjection experiment, dre-miR-140-5p is shown to exert a dramatic impact on craniofacial skeleton formation. Taken together, we provided functional evidence for a novel FGFRL1 poly-miRTS rs4647940 in a previously known 4p16.3 locus, and experimental and clinical genetics studies have shown both FGFRL1 and hsa-miR-140-5p are important for bone formation. © The Author 2015. Published by Oxford University Press. All rights reserved.

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Bone is a mineralized tissue that enables multiple mechanical and metabolic functions to be carried out in the skeleton. Bone contains distinct cell types: osteoblasts (bone-forming cells), osteocytes (mature osteoblast that embedded in mineralized bone matrix) and the osteoclasts (bone-resorbing cells). Remodelling of bone begins early in foetal life, and once the skeleton is fully formed in young adults, almost all of the metabolic activity is in this form. Bone is constantly destroyed or resorbed by osteoclasts and then replaced by osteoblasts. Many bone diseases, i.e. osteoporosis, also known as bone loss, typically reflect an imbalance in skeletal turnover. The cyclic adenosine monophosphate (cAMP) and the cyclic guanosine monophosphate (cGMP) are second messengers involved in a variety of cellular responses to such extracellular agents as hormones and neurotransmitters. In the hormonal regulation of bone metabolism, i.e. via parathyroid hormone (PTH), parathyroid hormone-related peptide (PTHrp) and prostaglandin E2 signal via cAMP. cAMP and cGMP are formed by adenylate and guanylate cyclases and are degraded by phosphodiesterases (PDEs). PDEs determine the amplitudes of cyclic nucleotide-mediated hormonal responses and modulate the duration of the signal. The activities of the PDEs are regulated by multiple inputs from other signalling systems and are crucial points of cross-talk between the pathways. Food-derived bioactive peptides are reported to express a variety of functions in vivo. The angiotensin-converting enzymes (ACEs) are involved in the regulation of the specific maturation or degradation of a number of mammalian bioactive peptides. The bioactive peptides offer also a nutriceutical and a nutrigenomic aspect to bone cell biology. The aim of this study was to investigate the influence of PDEs and bioactive peptides on the activation and the differentiation of human osteoblast cells. The profile of PDEs in human osteoblast-like cells and the effect of glucocorticoids on the function of cAMP PDEs, were investigated at the mRNA and enzyme levels. The effects of PDEs on bone formation and osteoblast gene expression were determined with chemical inhibitors and siRNAs (short interfering RNAs). The influence of bioactive peptides on osteoblast gene expression and proliferation was studied at the mRNA and cellular levels. This work provides information on how PDEs are involved in the function and the differentiation of osteoblasts. The findings illustrate that gene-specific silencing with an RNA interference (RNAi) method is useful in inhibiting, the gene expression of specific PDEs and further, PDE7 inhibition upregulates several osteogenic genes and increases bALP activity and mineralization in human mesenchymal stem cells-derived osteoblasts. PDEs appear to be involved in a mechanism by which glucocorticoids affect cAMP signaling. This may provide a potential route in the formation of glucocorticoid-induced bone loss, involving the down-regulation of cAMP-PDE. PDEs may play an important role in the regulation of osteoblastic differentiation. Isoleucine-proline-proline (IPP), a bioactive peptide, possesses the potential to increase osteoblast proliferation, differentiation and signalling.

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A promotional brochure celebrating the completion of the Seagram Building in spring 1957 features on its cover intense portraits of seven men bisected by a single line of bold text that asks, “Who are these Men?” The answer appears on the next page: “They Dreamed of a Tower of Light” (Figures 1, 2). Each photograph is reproduced with the respective man’s name and project credit: architects, Mies van der Rohe and Philip Johnson; associate architect, Eli Jacques Kahn; electrical contractor, Harry F. Fischbach; lighting consultant, Richard Kelly; and electrical engineer, Clifton E. Smith. To the right, a rendering of the new Seagram Tower anchors the composition, standing luminous against a star-speckled night sky; its glass walls and bronze mullions are transformed into a gossamer skin that reveals the tower’s structural skeleton. Lightolier, the contract lighting manufacturer, produced the brochure to promote its role in the lighting of the Seagram Building, but Lightolier’s promotional copy was not far from the truth.

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Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

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Social media platforms risk polarising public opinions by employing proprietary algorithms that produce filter bubbles and echo chambers. As a result, the ability of citizens and communities to engage in robust debate in the public sphere is diminished. In response, this paper highlights the capacity of urban interfaces, such as pervasive displays, to counteract this trend by exposing citizens to the socio-cultural diversity of the city. Engagement with different ideas, networks and communities is crucial to both innovation and the functioning of democracy. We discuss examples of urban interfaces designed to play a key role in fostering this engagement. Based on an analysis of works empirically-grounded in field observations and design research, we call for a theoretical framework that positions pervasive displays and other urban interfaces as civic media. We argue that when designed for more than wayfinding, advertisement or television broadcasts, urban screens as civic media can rectify some of the pitfalls of social media by allowing the polarised user to break out of their filter bubble and embrace the cultural diversity and richness of the city.

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We find sandwiched metal dimers CB5H6M–MCB5H6 (M = Si, Ge, Sn) which are minima in the potential energy surface with a characteristic M–M single bond. The NBO analysis and the M–M distances (Å) (2.3, 2.44 and 2.81 for M = Si, Ge, Sn) indicate substantial M–M bonding. Formal generation of CB5H6M–MCB5H6 has been studied theoretically. Consecutive substitution of two boron atoms in B7H−27 by M (Si, Ge, Sn) and carbon, respectively followed by dehydrogenation may lead to our desired CB5H6M–MCB5H6. We find that the slip distorted geometry is preferred for MCB5H7 and its dehydrogenated dimer CB5H6M–MCB5H6. The slip-distortion of M–M bond in CB5H6M–MCB5H6 is more than the slip distortion of M–H bond in MCB5H7. Molecular orbital analysis has been done to understand the slip distortion. Larger M–M bending (CB5H6M–MCB5H6) in comparison with M–H bending (MCB5H7) is suspected to be encouraged by stabilization of one of the M–M π bonding MO’s. Preference of M to occupy the apex of pentagonal skeleton of MCB5H7 over its icosahedral analogue MCB10H11 has been observed.

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Modern database systems incorporate a query optimizer to identify the most efficient "query execution plan" for executing the declarative SQL queries submitted by users. A dynamic-programming-based approach is used to exhaustively enumerate the combinatorially large search space of plan alternatives and, using a cost model, to identify the optimal choice. While dynamic programming (DP) works very well for moderately complex queries with up to around a dozen base relations, it usually fails to scale beyond this stage due to its inherent exponential space and time complexity. Therefore, DP becomes practically infeasible for complex queries with a large number of base relations, such as those found in current decision-support and enterprise management applications. To address the above problem, a variety of approaches have been proposed in the literature. Some completely jettison the DP approach and resort to alternative techniques such as randomized algorithms, whereas others have retained DP by using heuristics to prune the search space to computationally manageable levels. In the latter class, a well-known strategy is "iterative dynamic programming" (IDP) wherein DP is employed bottom-up until it hits its feasibility limit, and then iteratively restarted with a significantly reduced subset of the execution plans currently under consideration. The experimental evaluation of IDP indicated that by appropriate choice of algorithmic parameters, it was possible to almost always obtain "good" (within a factor of twice of the optimal) plans, and in the few remaining cases, mostly "acceptable" (within an order of magnitude of the optimal) plans, and rarely, a "bad" plan. While IDP is certainly an innovative and powerful approach, we have found that there are a variety of common query frameworks wherein it can fail to consistently produce good plans, let alone the optimal choice. This is especially so when star or clique components are present, increasing the complexity of th- e join graphs. Worse, this shortcoming is exacerbated when the number of relations participating in the query is scaled upwards.

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This paper gives a new iterative algorithm for kernel logistic regression. It is based on the solution of a dual problem using ideas similar to those of the Sequential Minimal Optimization algorithm for Support Vector Machines. Asymptotic convergence of the algorithm is proved. Computational experiments show that the algorithm is robust and fast. The algorithmic ideas can also be used to give a fast dual algorithm for solving the optimization problem arising in the inner loop of Gaussian Process classifiers.

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By a series of reactions the Diels-Alder adduct IV of maleic anhydride and β-trans-Ocimene gave 1-hydroxy-1,4-dimethyl-7-hydroxymethyloctahydroindane (XII). Its further synthetic elaboration furnished 1,4-dimethyl-7-(2-ethoxycarbonyl-1-propenyl)-Δ1-octahydroindane of the valerenic acid skeleton.

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Infrared and Raman spectra of N,N-dimethylacetamide (DMA) are recorded and the normal vibrational analysis of the DMA skeleton as well as the entire molecule carried out employing the Urey-Bradley and modified Urey-Bradley force fields. Vibrational frequencies are assigned on the basis of the normal coordinate calculations and are compared with those of related molecules. Infrared spectra of metal complexes are examined to substantiate the band assignments.

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This contribution focuses on the accelerated loss of traditional sound patterning in music, parallel to the exponential loss of linguistic and cultural variety in a world increasingly 'globalized' by market policies and economic liberalization, in which scientific or technical justification plays a crucial role. As a suggestion to an alternative trend, composers and music theorists are invited to explore the world of design and patterning by grammar rules from non-dominant cultures, and to make an effort to understand their contextual usage and its transformation, in order to appreciate their symbolism and aesthetic depth. Practical examples are provided.

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Infrared and Raman spectra of N,N-dimethylacetamide (DMA) are recorded and the normal vibrational analysis of the DMA skeleton as well as the entire molecule carried out employing the Urey-Bradley and modified Urey-Bradley force fields. Vibrational frequencies are assigned on the basis of the normal coordinate calculations and are compared with those of related molecules. Infrared spectra of metal complexes are examined to substantiate the band assignments.