A hierarchical distributed approach for mining molecular fragments

Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.

Autopoietic organization of firm: an illustration for the construction industry

Generally poor productivity, delays, low profitability and exceeded budgets are Common problems in modern construction management, however it seems that a basic obstacle lies far deeper in the understanding of a firm's fundamental mission, its existence. The main objective of this paper therefore is to examine the operational living of a construction firm and by doing that to reveal the key problem or the solution for a construction firm - its organization. A firm as a social system in which interactions between its constitutive components (employees) are surordinated to its maintenance (keeping a system alive) is an autopoietic social system. Two domains of external perturbations are uncovered to which a construction firm has to adapt (market driven and project driven perturbations). Constructed conceptual model of an autopoietic organization is based upon two necessary and sufficient operational domains that a firm has to create in order to become an autopoietic, adaptive social system. The first one is a domain of interactions between employees and other operationally external systems, which is representing an idea-generating domain of interactions. The second is employee's autonomous operational domain, which embodies employee's autonomy and individuality and represents a necessary condition for the establishment of an idea-generating domain. Finally, it is recognized that interactions within these four domains keep a construction firm alive.

World Health Organization dietary norms: a quantitative evaluation of potential consumption impacts in the United States, United Kingdom, and France

The member countries of the World Health Organization have endorsed its Global Strategy on Diet, Physical Activity, and Health. We assess the potential consumption impacts of these norms in the United States, France, and the United Kingdom using a mathematical programming approach. We find that adherence would involve large reductions in the consumption of fats and oils accompanying large rises in the consumption of fruits, vegetables, and cereal. Further, in the United Kingdom and the United States, but not France, sugar intakes would have to shrink considerably. Focusing on sub-populations within each country, we find that the least educated, not necessarily the poorest, would have to bear the highest burden of adjustment.

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Heat shock protein 27 is the major differentially phosphorylated protein involved in renal epithelial cellular stress response and controls focal adhesion organization and apoptosis

We used two-dimensional difference gel electrophoresis to determine early changes in the stress-response pathways that precede focal adhesion disorganization linked to the onset of apoptosis of renal epithelial cells. Treatment of LLC-PK1 cells with the model nephrotoxicant 1,2-(dichlorovinyl)-L-cysteine (DCVC) resulted in a >1.5-fold up- and down-regulation of 14 and 9 proteins, respectively, preceding the onset of apoptosis. Proteins included those involved in metabolism, i.e. aconitase and pyruvate dehydrogenase, and those related to stress responses and cytoskeletal reorganization, i.e. cofilin, Hsp27, and alpha-b-crystallin. The most prominent changes were found for Hsp27, which was related to a pI shift in association with an altered phosphorylation status of serine residue 82. Although both p38 and JNK were activated by DCVC, only inhibition of p38 with SB203580 reduced Hsp27 phosphorylation, which was associated with accelerated reorganization of focal adhesions, cell detachment, and apoptosis. In contrast, inhibition of JNK with SP600125 maintained cell adhesion as well as protection against apoptosis. Active JNK co-localized at focal adhesions after DCVC treatment in a FAK-dependent manner. Inhibition of active JNK localization at focal adhesions did not prevent DCVC-induced phosphorylation of Hsp27. Overexpression of a phosphorylation-defective mutant Hsp27 acted as a dominant negative and accelerated the DCVC-induced changes in the focal adhesions as well as the onset of apoptosis. Our data fit a model whereby early p38 activation results in a rapid phosphorylation of Hsp27, a requirement for proper maintenance of cell adhesion, thus suppressing renal epithelial cell apoptosis.

Heat shock protein 27 is the major differentially phosphorylated protein involved in renal epithelial cellular stress response and controls focal adhesion organization and apoptosis

We used two-dimensional difference gel electrophoresis to determine early changes in the stress-response pathways that precede focal adhesion disorganization linked to the onset of apoptosis of renal epithelial cells. Treatment of LLC-PK1 cells with the model nephrotoxicant 1,2-(dichlorovinyl)-L-cysteine ( DCVC) resulted in a > 1.5-fold up- and down-regulation of 14 and 9 proteins, respectively, preceding the onset of apoptosis. Proteins included those involved in metabolism, i.e. aconitase and pyruvate dehydrogenase, and those related to stress responses and cytoskeletal reorganization, i.e. cofilin, Hsp27, and alpha-b-crystallin. The most prominent changes were found for Hsp27, which was related to a pI shift in association with an altered phosphorylation status of serine residue 82. Although both p38 and JNK were activated by DCVC, only inhibition of p38 with SB203580 reduced Hsp27 phosphorylation, which was associated with accelerated reorganization of focal adhesions, cell detachment, and apoptosis. In contrast, inhibition of JNK with SP600125 maintained cell adhesion as well as protection against apoptosis. Active JNK co-localized at focal adhesions after DCVC treatment in a FAK-dependent manner. Inhibition of active JNK localization at focal adhesions did not prevent DCVC-induced phosphorylation of Hsp27. Overexpression of a phosphorylation-defective mutant Hsp27 acted as a dominant negative and accelerated the DCVC-induced changes in the focal adhesions as well as the onset of apoptosis. Our data fit a model whereby early p38 activation results in a rapid phosphorylation of Hsp27, a requirement for proper maintenance of cell adhesion, thus suppressing renal epithelial cell apoptosis.

A new organization for a perceptron-based branch predictor and its FPGA implementation

An unaltered rearrangement of the original computation of a neural based predictor at the algorithmic level is introduced as a new organization. Its FPGA implementation generates circuits that are 1.7 faster than a direct implementation of the original algorithm. This faster clock rate allows to implement predictors with longer history lengths using the nearly the same hardware budget.

FPGA organization for the fast path-based neural branch predictor

This paper develops cycle-level FPGA circuits of an organization for a fast path-based neural branch predictor Our results suggest that practical sizes of prediction tables are limited to around 32 KB to 64 KB in current FPGA technology due mainly to FPGA area of logic resources to maintain the tables. However the predictor scales well in terms of prediction speed. Table sizes alone should not be used as the only metric for hardware budget when comparing neural-based predictor to predictors of totally different organizations. This paper also gives early evidence to shift the attention on to the recovery from mis-prediction latency rather than on prediction latency as the most critical factor impacting accuracy of predictions for this class of branch predictors.

Semantic organization to enhance active learning based on distributed multimedia educational resources

In order to organize distributed educational resources efficiently, to provide active learners an integrated, extendible and cohesive interface to share the dynamically growing multimedia learning materials on the Internet, this paper proposes a generic resource organization model with semantic structures to improve expressiveness, scalability and cohesiveness. We developed an active learning system with semantic support for learners to access and navigate through efficient and flexible manner. We learning resources in an efficient and flexible manner. We provide facilities for instructors to manipulate the structured educational resources via a convenient visual interface. We also developed a resource discovering and gathering engine based on complex semantic associations for several specific topics.

Hierarchical composite regular parallel architecture

The design space of emerging heterogenous multi-core architectures with re-configurability element makes it feasible to design mixed fine-grained and coarse-grained parallel architectures. This paper presents a hierarchical composite array design which extends the curret design space of regular array design by combining a sequence of transformations. This technique is applied to derive a new design of a pipelined parallel regular array with different dataflow between phases of computation.