Learning about Distributed Systems

This paper presents the "state of the art" about distributed systems and applications and it's focused on teaching about these systems. It presents different platforms where to run distributed applications and describes some development toolkits whose can be used to develop prototypes, practices and distributed applications. It also presents some existing distributed algorithms useful for class practices, and some tools to help managing distributed environments. Finally, the paper presents some teaching experiences with different approaches on how to teach about distributed systems.

Serial measurement of the circulating levels of tumour necrosis factor and its soluble receptors 1 and 2 for monitoring leprosy patients during multidrug treatment

Leprosy is an infectious and contagious spectral disease accompanied by a series of immunological events triggered by the host response to the aetiologic agent, Mycobacterium leprae . The induction and maintenance of the immune/inflammatory response in leprosy are linked to multiple cell interactions and soluble factors, primarily through the action of cytokines. The purpose of the present study was to evaluate the serum levels of tumour necrosis factor (TNF)-α and its soluble receptors (sTNF-R1 and sTNF-R2) in leprosy patients at different stages of multidrug treatment (MDT) in comparison with non-infected individuals and to determine their role as putative biomarkers of the severity of leprosy or the treatment response. ELISA was used to measure the levels of these molecules in 30 healthy controls and 37 leprosy patients at the time of diagnosis and during and after MDT. Our results showed increases in the serum levels of TNF-α and sTNF-R2 in infected individuals in comparison with controls. The levels of TNF-α, but not sTNF-R2, decreased with treatment. The current results corroborate previous reports of elevated serum levels of TNF-α in leprosy and suggest a role for sTNF-R2 in the control of this cytokine during MDT.

Evaluation of MPI collectives for HPC applications on distributed virtualized environments

Through this study, we will measure how the collective MPI operations behaves in virtual and physical clusters, and its impact on the application performance. As we stated before, we will use as a test case the Weather Research and Forecasting simulations.

Serial QuantiFERON-TB Gold In-Tube assay and tuberculin skin test to diagnose latent tuberculosis in household Mexican contacts: conversion and reversion rates and associated factors using conventional and borderline zone definitions

A cohort of 123 adult contacts was followed for 18‐24 months (86 completed the follow-up) to compare conversion and reversion rates based on two serial measures of QuantiFERON (QFT) and tuberculin skin test (TST) (PPD from TUBERSOL, Aventis Pasteur, Canada) for diagnosing latent tuberculosis (TB) in household contacts of TB patients using conventional (C) and borderline zone (BZ) definitions. Questionnaires were used to obtain information regarding TB exposure, TB risk factors and socio-demographic data. QFT (IU/mL) conversion was defined as <0.35 to ≥0.35 (C) or <0.35 to >0.70 (BZ) and reversion was defined as ≥0.35 to <0.35 (C) or ≥0.35 to <0.20 (BZ); TST (mm) conversion was defined as <5 to ≥5 (C) or <5 to >10 (BZ) and reversion was defined as ≥5 to <5 (C). The QFT conversion and reversion rates were 10.5% and 7% with C and 8.1% and 4.7% with the BZ definitions, respectively. The TST rates were higher compared with QFT, especially with the C definitions (conversion 23.3%, reversion 9.3%). The QFT conversion and reversion rates were higher for TST ≥5; for TST, both rates were lower for QFT <0.35. No risk factors were associated with the probability of converting or reverting. The inconsistency and apparent randomness of serial testing is confusing and adds to the limitations of these tests and definitions to follow-up close TB contacts.

Sensitivity and specificity of parallel or serial serological testing for detection of canine Leishmania infection

In Brazil, human and canine visceral leishmaniasis (CVL) caused byLeishmania infantum has undergone urbanisation since 1980, constituting a public health problem, and serological tests are tools of choice for identifying infected dogs. Until recently, the Brazilian zoonoses control program recommended enzyme-linked immunosorbent assays (ELISA) and indirect immunofluorescence assays (IFA) as the screening and confirmatory methods, respectively, for the detection of canine infection. The purpose of this study was to estimate the accuracy of ELISA and IFA in parallel or serial combinations. The reference standard comprised the results of direct visualisation of parasites in histological sections, immunohistochemical test, or isolation of the parasite in culture. Samples from 98 cases and 1,327 noncases were included. Individually, both tests presented sensitivity of 91.8% and 90.8%, and specificity of 83.4 and 53.4%, for the ELISA and IFA, respectively. When tests were used in parallel combination, sensitivity attained 99.2%, while specificity dropped to 44.8%. When used in serial combination (ELISA followed by IFA), decreased sensitivity (83.3%) and increased specificity (92.5%) were observed. Serial testing approach improved specificity with moderate loss in sensitivity. This strategy could partially fulfill the needs of public health and dog owners for a more accurate diagnosis of CVL.

The efficiency of antigen recognition by CD8+ CTL clones is determined by the frequency of serial TCR engagement.

Using H-2Kd-restricted CTL clones, which are specific for a photoreactive derivative of the Plasmodium berghei circumsporozoite peptide PbCS(252-260) (SYIPSAEKI) and permit assessment of TCR-ligand interactions by TCR photoaffinity labeling, we have previously identified several peptide derivative variants for which TCR-ligand binding and the efficiency of Ag recognition deviated by fivefold or more. Here we report that the functional CTL response (cytotoxicity and IFN-gamma production) correlated with the rate of TCR-ligand complex dissociation, but not the avidity of TCR-ligand binding. While peptide antagonists exhibited very rapid TCR-ligand complex dissociation, slightly slower dissociation was observed for strong agonists. Conversely and surprisingly, weak agonists typically displayed slower dissociation than the wild-type agonists. Acceleration of TCR-ligand complex dissociation by blocking CD8 participation in TCR-ligand binding increased the efficiency of Ag recognition in cases where dissociation was slow. In addition, permanent TCR engagement by TCR-ligand photocross-linking completely abolished sustained intracellular calcium mobilization, which is required for T cell activation. These results indicate that the functional CTL response depends on the frequency of serial TCR engagement, which, in turn, is determined by the rate of TCR-ligand complex dissociation.

A distributed environment for virtual and/or real experiments for underwater robots

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments

Selection on a eumelanic ornament is stronger in the tropics than in temperate zones in the worldwide-distributed barn owl.

Spatial variation in the pattern of natural selection can promote local adaptation and genetic differentiation between populations. Because heritable melanin-based ornaments can signal resistance to environmentally mediated elevation in glucocorticoids, to oxidative stress and parasites, populations may vary in the mean degree of melanic coloration if selection on these phenotypic aspects varies geographically. Within a population of Swiss barn owls (Tyto alba), the size of eumelanic spots is positively associated with survival, immunity and resistance to stress, but it is yet unknown whether Tyto species that face stressful environments evolved towards a darker eumelanic plumage. Because selection regimes vary along environmental gradients, we examined whether melanin-based traits vary clinally and are expressed to a larger extent in the tropics where parasites are more abundant than in temperate zones. To this end, we considered 39 barn owl species distributed worldwide. Barn owl species living in the tropics displayed larger eumelanic spots than those found in temperate zones. This was, however, verified in the northern hemisphere only. Parasites being particularly abundant in the tropics, they may promote the evolution of darker eumelanic ornaments.

Reliable and persistent storage for CoDeS a distributed collaborative system

This research is aimed to find a solution for a distributed storage system adapted for CoDeS. By studying how DSSs work and how they are implemented, we can conclude how we can implement a DSS compatible with CoDeS requirements.

Prognostic value of serial blood S100B determinations in stage IIB-III melanoma patients: a corollary study to EORTC trial 18952.

S100B is a prognostic factor for melanoma as elevated levels correlate with disease progression and poor outcome. We determined its prognostic value based on updated information using serial determinations in stage IIb/III melanoma patients. 211 Patients who participated in the EORTC 18952 trial, evaluating efficacy of adjuvant intermediate doses of interferon α2b (IFN) versus observation, entered a corollary study. Over a period of 36 months, 918 serum samples were collected. The Cox time-dependent model was used to assess prognostic value of the latest (most recent) S100B determination. At first measurement, 178 patients had S100B values <0.2 μg/l and 33 ≥ 0.2 μg/l. Within the first group, 61 patients had, later on, an increased value of S100B (≥ 0.2 μg/l). An initial increased value of S100B, or during follow-up, was associated with worse distant metastasis-free survival (DMFS); hazard ratio (HR) of S100B ≥ 0.2 versus S100B < 0.2 was 5.57 (95% confidence interval (CI) 3.81-8.16), P < 0.0001, after adjustment for stage, number of lymph nodes and sex. In stage IIb patients, the HR adjusted for sex was 2.14 (95% CI 0.71, 6.42), whereas in stage III, the HR adjusted for stage, number of lymph nodes and sex was 6.76 (95% CI 4.50-10.16). Similar results were observed regarding overall survival (OS). Serial determination of S100B in stage IIb-III melanoma is a strong independent prognostic marker, even stronger compared to stage and number of positive lymph nodes. The prognostic impact of S100B ≥ 0.2 μg/l is more pronounced in stage III disease compared with stage IIb.

Distributed all-atom simulations of intrinsically unstructured proteins

The Computational Biophysics Group at the Universitat Pompeu Fabra (GRIB-UPF) hosts two unique computational resources dedicated to the execution of large scale molecular dynamics (MD) simulations: (a) the ACMD molecular-dynamics software, used on standard personal computers with graphical processing units (GPUs); and (b) the GPUGRID. net computing network, supported by users distributed worldwide that volunteer GPUs for biomedical research. We leveraged these resources and developed studies, protocols and open-source software to elucidate energetics and pathways of a number of biomolecular systems, with a special focus on flexible proteins with many degrees of freedom. First, we characterized ion permeation through the bactericidal model protein Gramicidin A conducting one of the largest studies to date with the steered MD biasing methodology. Next, we addressed an open problem in structural biology, the determination of drug-protein association kinetics; we reconstructed the binding free energy, association, and dissaciociation rates of a drug like model system through a spatial decomposition and a Makov-chain analysis. The work was published in the Proceedings of the National Academy of Sciences and become one of the few landmark papers elucidating a ligand-binding pathway. Furthermore, we investigated the unstructured Kinase Inducible Domain (KID), a 28-peptide central to signalling and transcriptional response; the kinetics of this challenging system was modelled with a Markovian approach in collaboration with Frank Noe’s group at the Freie University of Berlin. The impact of the funding includes three peer-reviewed publication on high-impact journals; three more papers under review; four MD analysis components, released as open-source software; MD protocols; didactic material, and code for the hosting group.

Decoding sequence learning from single-trial intracranial EEG in humans.

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

On the computational security of a distributed key distribution scheme

In a distributed key distribution scheme, a set of servers helps a set of users in a group to securely obtain a common key. Security means that an adversary who corrupts some servers and some users has no information about the key of a noncorrupted group. In this work, we formalize the security analysis of one such scheme which was not considered in the original proposal. We prove the scheme is secure in the random oracle model, assuming that the Decisional Diffie-Hellman (DDH) problem is hard to solve. We also detail a possible modification of that scheme and the one in which allows us to prove the security of the schemes without assuming that a specific hash function behaves as a random oracle. As usual, this improvement in the security of the schemes is at the cost of an efficiency loss.

Differential Gene Expression between Fall- and Spring-Run Chinook Salmon Assessed by Long Serial Analysis of Gene Expression

Of all Pacific salmonids, Chinook salmon Oncorhynchus tshawytscha display the greatest variability in return times to freshwater. The molecular mechanisms of these differential return times have not been well described. Current methods, such as long serial analysis of gene expression (LongSAGE) and microarrays, allow gene expression to be analyzed for thousands of genes simultaneously. To investigate whether differential gene expression is observed between fall- and spring-run Chinook salmon from California's Central Valley, LongSAGE libraries were constructed. Three libraries containing between 25,512 and 29,372 sequenced tags (21 base pairs/tag) were generated using messenger RNA from the brains of adult Chinook salmon returning in fall and spring and from one ocean-caught Chinook salmon. Tags were annotated to genes using complementary DNA libraries from Atlantic salmon Salmo salar and rainbow trout O. mykiss. Differentially expressed genes, as estimated by differences in the number of sequence tags, were found in all pairwise comparisons of libraries (freshwater versus saltwater = 40 genes; fall versus spring = 11 genes: and spawning versus nonspawning = 51 genes). The gene for ependymin, an extracellular glycoprotein involved in behavioral plasticity in fish, exhibited the most differential expression among the three groupings. Reverse transcription polymerase chain reaction analysis verified the differential expression of ependymin between the fall- and spring-run samples. These LongSAGE libraries, the first reported for Chinook salmon, provide a window of the transcriptional changes during Chinook salmon return migration to freshwater and spawning and increase the amount of expressed sequence data.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.