Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Reporting of methodologic information on trial registries for quality assessment: a study of trial records retrieved from the WHO search portal

Background: Although randomized clinical trials (RCTs) are considered the gold standard of evidence, their reporting is often suboptimal. Trial registries have the potential to contribute important methodologic information for critical appraisal of study results. Methods and Findings: The objective of the study was to evaluate the reporting of key methodologic study characteristics in trial registries. We identified a random sample (n = 265) of actively recruiting RCTs using the World Health Organization International Clinical Trials Registry Platform (ICTRP) search portal in 2008. We assessed the reporting of relevant domains from the Cochrane Collaboration’s ‘Risk of bias’ tool and other key methodological aspects. Our primary outcomes were the proportion of registry records with adequate reporting of random sequence generation, allocation concealment, blinding, and trial outcomes. Two reviewers independently assessed each record. Weighted overall proportions in the ICTRP search portal for adequate reporting of sequence generation, allocation concealment, blinding (including and excluding open label RCT) and primary outcomes were 5.7% (95% CI 3.0–8.4%), 1.4% (0–2.8%), 41% (35–47%), 8.4% (4.1–13%), and 66% (60–72%), respectively. The proportion of adequately reported RCTs was higher for registries that used specific methodological fields for describing methods of randomization and allocation concealment compared to registries that did not. Concerning other key methodological aspects, weighted overall proportions of RCTs with adequately reported items were as follows: eligibility criteria (81%), secondary outcomes (46%), harm (5%) follow-up duration (62%), description of the interventions (53%) and sample size calculation (1%). Conclusions: Trial registries currently contain limited methodologic information about registered RCTs. In order to permit adequate critical appraisal of trial results reported in journals and registries, trial registries should consider requesting details on key RCT methods to complement journal publications. Full protocols remain the most comprehensive source of methodologic information and should be made publicly available.

Technical Note: Dissolved organic matter fluorescence a finite mixture approach to deconvolve excitation-emission matrices

The analysis of the shape of excitation-emission matrices (EEMs) is a relevant tool for exploring the origin, transport and fate of dissolved organic matter (DOM) in aquatic ecosystems. Within this context, the decomposition of EEMs is acquiring a notable relevance. A simple mathematical algorithm that automatically deconvolves individual EEMs is described, creating new possibilities for the comparison of DOM fluorescence properties and EEMs that are very different from each other. A mixture model approach is adopted to decompose complex surfaces into sub-peaks. The laplacian operator and the Nelder-Mead optimisation algorithm are implemented to individuate and automatically locate potential peaks in the EEM landscape. The EEMs of a simple artificial mixture of fluorophores and DOM samples collected in a Mediterranean river are used to describe the model application and to illustrate a strategy that optimises the search for the optimal output.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

Search and Discovery : OER's Open Loop

Open educational resources (OER) promise increased access, participation, quality, and relevance, in addition to cost reduction. These seemingly fantastic promises are based on the supposition that educators and learners will discover existing resources, improve them, and share the results, resulting in a virtuous cycle of improvement and re-use. By anecdotal metrics, existing web scale search is not working for OER. This situation impairs the cycle underlying the promise of OER, endangering long term growth and sustainability. While the scope of the problem is vast, targeted improvements in areas of curation, indexing, and data exchange can improve the situation, and create opportunities for further scale. I explore the way the system is currently inadequate, discuss areas for targeted improvement, and describe a prototype system built to test these ideas. I conclude with suggestions for further exploration and development.

The unfathomable secret remains: a reverse engineering study of SEO factors on Google's search engine

The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Shout and Act: an Algorithm for Digital Objects Preservation Inspired from Rescue Robots

We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several experiments to show that this system works very scalably, showing that heterogeneous teams of agents outperform homogeneous ones over a wide range of tasks complexity. The target at-risk documents are MS Office documents (including an RTF file) with Excel content or in Excel format. Thus, an interesting conclusion from the experiments is that fewer heterogeneous (varying skills) agents can equal the performance of many homogeneous (combined super-skilled) agents, implying significant performance increases with lower overall cost growth. Our results impact the design of Digital Objects Preservation teams: a properly designed combination of heterogeneous teams is cheaper and more scalable when confronted with uncertain maps of digital objects that need to be preserved. A cost pyramid is proposed for engineers to use for modeling the most effective agent combinations

An energy efficient vertical handover decision algorithm

As wireless communications evolve towards heterogeneousnetworks, mobile terminals have been enabled tohandover seamlessly from one network to another. At the sametime, the continuous increase in the terminal power consumptionhas resulted in an ever-decreasing battery lifetime. To that end,the network selection is expected to play a key role on howto minimize the energy consumption, and thus to extend theterminal lifetime. Hitherto, terminals select the network thatprovides the highest received power. However, it has been provedthat this solution does not provide the highest energy efficiency.Thus, this paper proposes an energy efficient vertical handoveralgorithm that selects the most energy efficient network thatminimizes the uplink power consumption. The performance of theproposed algorithm is evaluated through extensive simulationsand it is shown to achieve high energy efficiency gains comparedto the conventional approach.

Escacs, un sistema intel·ligent

Des dels inicis dels ordinadors com a màquines programables, l’home ha intentat dotar-los de certa intel•ligència per tal de pensar o raonar el més semblant possible als humans. Un d’aquests intents ha sigut fer que la màquina sigui capaç de pensar de tal manera que estudiï jugades i guanyi partides d’escacs. En l’actualitat amb els actuals sistemes multi tasca, orientat a objectes i accés a memòria i gràcies al potent hardware del que disposem, comptem amb una gran varietat de programes que es dediquen a jugar a escacs. Però no hi ha només programes petits, hi ha fins i tot màquines senceres dedicades a calcular i estudiar jugades per tal de guanyar als millors jugadors del món. L’objectiu del meu treball és dur a terme un estudi i implementació d’un d’aquests programes, per això es divideix en dues parts. La part teòrica o de l’estudi, consta d’un estudi dels sistemes d’intel•ligència artificial que es dediquen a jugar a escacs, estudi i cerca d’una funció d’avaluació vàlida i estudi dels algorismes de cerca. La part pràctica del treball es basa en la implementació d’un sistema intel•ligent capaç de jugar a escacs amb certa lògica. Aquesta implementació es porta a terme amb l’ajuda de les llibreries SDL, utilitzant l’algorisme minimax amb poda alfa-beta i codi c++. Com a conclusió del projecte m’agradaria remarcar que l’estudi realitzat m’ha deixat veure que crear un joc d’escacs no era tan fàcil com jo pensava però m’ha aportat la satisfacció d’aplicar tot el que he après durant la carrera i de descobrir moltes altres coses noves.