Kumar's algorithm for solving Toeplitz systems of equations over finite fields

Adaptació de l'algorisme de Kumar per resoldre sistemes d'equacions amb matrius de Toeplitz sobre els reals a cossos finits en un temps 0 (n log n).

Implementation of the Rijndael-AES algorithm on a Sage-Math worksheet

La principal motivació d'aquest treball ha estat implementar l'algoritme Rijndael-AES en un full Sage-math, paquet de software matemàtic de lliure distribució i en actual desenvolupament, aprofitant les seves eines i funcionalitats integrades.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Enrichment cultures should be performed in the detection of bacterial oral human pathogens in DUWLs

Water delivered by dental units during routine dental practice is densely contaminated by bacteria. The aim of this study was to determine actual isolation of the microorganisms sprayed from Dental Unit Water Lines (DUWLs) when enrichment cultures are performed and to compare frequencies with those obtained without enrichment cultures. Moreover, the antimicrobial susceptibilities of the microorganisms isolated were also studied. Water samples were collected from one hundred dental equipments in use at Dental Hospital of our University in order to evaluate the presence/absence of microorganisms and to perform their presumptive identification. Aliquots from all of the samples were inoculated in eight different media including both enrichment and selective media. Minimal inhibitory concentrations (MIC) were determined by the broth dilution method. The results herein reported demonstrate that most of the DUWLs were colonized by bacteria from human oral cavity; when enrichment procedures were applied the percentage of DUWLs with detectable human bacteria was one hundred percent. The results showed that in order to evaluate the actual risk of infections spread by DUWLs the inclusion of a step of pre-enrichment should be performed. The need for devices preventing bacterial contamination of DUWLs is a goal to be achieved in the near future that would contribute to maintain safety in dental medical assistance

Generalist hydrocarbon-degrading bacterial communities in the oil-polluted water column of the North Sea.

The aim of this work was to determine the effect of light crude oil on bacterial communities during an experimental oil spill in the North Sea and in mesocosms (simulating a heavy, enclosed oil spill), and to isolate and characterize hydrocarbon-degrading bacteria from the water column. No oil-induced changes in bacterial community (3 m below the sea surface) were observed 32 h after the experimental spill at sea. In contrast, there was a decrease in the dominant SAR11 phylotype and an increase in Pseudoalteromonas spp. in the oiled mesocosms (investigated by 16S rRNA gene analysis using denaturing gradient gel electrophoresis), as a consequence of the longer incubation, closer proximity of the samples to oil, and the lack of replenishment with seawater. A total of 216 strains were isolated from hydrocarbon enrichment cultures, predominantly belonging to the genus Pseudoaltero monas; most strains grew on PAHs, branched and straight-chain alkanes, as well as many other carbon sources. No obligate hydrocarbonoclastic bacteria were isolated or detected, highlighting the potential importance of cosmopolitan marine generalists like Pseudoalteromonas spp. in degrading hydrocarbons in the water column beneath an oil slick, and revealing the susceptibility to oil pollution of SAR11, the most abundant bacterial clade in the surface ocean.

Activity patterns and foraging behaviour of Audouin's gulls at the Ebro Delta, NW Mediterranean.

Twenty Audouin´s gulls, Larus audouinii, breeding in the Ebro Delta (NW Mediterranean) were radio-tracked in 1998 to study their foraging behaviour and activity patterns. Some detrimental effects of tagging on the breeding success of the birds were detected, especially when both members of the pair were tagged. The results were actually constrained by the low number of locations due to natural breeding failure and failure in tag emission, as well as the adverse effect of tagging. However, through a combination of aircraft surveys at sea and a fixed station for automatic tracking of the presence of the birds at the colony, novel individual-based information of home ranges and activity patterns was obtained. Trawler fishing activity seemed to influence both the foraging range and habitat use: while trawlers operated, gulls overlapped their fishing grounds with vessels, probably to scavenge on discards. Very few locations were obtained during a trawling moratorium period, although they were all recorded in coastal bays and terrestrial habitats. During the trawling activity period, gulls ranged over a minimum convex polygon area of 2900 km2. Gulls were tracked up to 40 km from the colony, but some individuals were observed beyond 150 km while still breeding. Arrivals and departures from the colony were in accordance with the trawling timetable. However, most birds also showed some nocturnal foraging activity, probably linked to active fishing of clupeoids (following diel migrations) or to the exploitation of purse-seine fishing activity. Foraging trips lasted on average 15 hours: males performed significantly shorter trips than females, which spent more time outside the colony. The proportion of nocturnal time involved in the foraging trips was the same for males and females, but whilst all males initiated their trips both during the day and at night, some females only initiated their trips during the day. Hatching success was found to be related to foraging effort by males. Gulls spent on average ca. 38% of their time budget outside the nesting territory, representing the time devoted mainly to flying, foraging and other activities.

Bacterial adhesion efficiency on implant abutments: a comparative study

The attachment of Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 28213 onto six different materials used to manufacture dental implant abutments was quantitatively determined after 2 and 24 h of contact between the materials and the bacterial cultures. The materials were topographically characterized and their wettability determined, with both parameters subsequently related to bacterial adhesion. Atomic force microscopy, interferometry, and contact angle measurement were used to characterize the materials" surfaces. The results showed that neither roughness nor nano-roughness greatly influenced bacterial attachment whereas wettability strongly correlated with adhesion. After 2 h the degree of E. coli attachment markedly differed depending on the material whereas similar differences were not observed for S. aureus, which yielded consistently higher counts of adhered cells. Nevertheless, after 24 h the adhesion of the two species to the different test materials no longer significantly differed, although on all surfaces the numbers of finally adhered E. coli were higher than those of S. aureus

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.

Genomic Adaptations to the Loss of a Conserved Bacterial DNA Methyltransferase.

UNLABELLED: CcrM is an orphan DNA methyltransferase nearly universally conserved in a vast group of Alphaproteobacteria. In Caulobacter crescentus, it controls the expression of key genes involved in the regulation of the cell cycle and cell division. Here, we demonstrate, using an experimental evolution approach, that C. crescentus can significantly compensate, through easily accessible genetic changes like point mutations, the severe loss in fitness due to the absence of CcrM, quickly improving its growth rate and cell morphology in rich medium. By analyzing the compensatory mutations genome-wide in 12 clones sampled from independent ΔccrM populations evolved for ~300 generations, we demonstrated that each of the twelve clones carried at least one mutation that potentially stimulated ftsZ expression, suggesting that the low intracellular levels of FtsZ are the major burden of ΔccrM mutants. In addition, we demonstrate that the phosphoenolpyruvate-carbohydrate phosphotransfer system (PTS) actually modulates ftsZ and mipZ transcription, uncovering a previously unsuspected link between metabolic regulation and cell division in Alphaproteobacteria. We present evidence that point mutations found in genes encoding proteins of the PTS provide the strongest fitness advantage to ΔccrM cells cultivated in rich medium despite being disadvantageous in minimal medium. This environmental sign epistasis might prevent such mutations from getting fixed under changing natural conditions, adding a plausible explanation for the broad conservation of CcrM. IMPORTANCE: In bacteria, DNA methylation has a variety of functions, including the control of DNA replication and/or gene expression. The cell cycle-regulated DNA methyltransferase CcrM modulates the transcription of many genes and is critical for fitness in Caulobacter crescentus. Here, we used an original experimental evolution approach to determine which of its many targets make CcrM so important physiologically. We show that populations lacking CcrM evolve quickly, accumulating an excess of mutations affecting, directly or indirectly, the expression of the ftsZ cell division gene. This finding suggests that the most critical function of CcrM in C. crescentus is to promote cell division by enhancing FtsZ intracellular levels. During this work, we also discovered an unexpected link between metabolic regulation and cell division that might extend to other Alphaproteobacteria.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.