BAKTRAK: Backtracking drifting objects using an iterative algorithm with a forward trajectory model

The task of determining the origin of a drifting object after it has been located is highly complex due to the uncertainties in drift properties and environmental forcing (wind, waves and surface currents). Usually the origin is inferred by running a trajectory model (stochastic or deterministic) in reverse. However, this approach has some severe drawbacks, most notably the fact that many drifting objects go through nonlinear state changes underway (e.g., evaporating oil or a capsizing lifeboat). This makes it difficult to naively construct a reverse-time trajectory model which realistically predicts the earliest possible time the object may have started drifting. We propose instead a different approach where the original (forward) trajectory model is kept unaltered while an iterative seeding and selection process allows us to retain only those particles that end up within a certain time-space radius of the observation. An iterative refinement process named BAKTRAK is employed where those trajectories that do not make it to the goal are rejected and new trajectories are spawned from successful trajectories. This allows the model to be run in the forward direction to determine the point of origin of a drifting object. The method is demonstrated using the Leeway stochastic trajectory model for drifting objects due to its relative simplicity and the practical importance of being able to identify the origin of drifting objects. However, the methodology is general and even more applicable to oil drift trajectories, drifting ships and hazardous material that exhibit non-linear state changes such as evaporation, chemical weathering, capsizing or swamping. The backtracking method is tested against the drift trajectory of a life raft and is shown to predict closely the initial release position of the raft and its subsequent trajectory.Comment: 28 pages, 8 figures, 2 table

Pre-Stressor Interference Control and Intrusive Memories

Although intrusive imagery is a common response in the aftermath of a stressful or traumatic event, only a minority of trauma victims show persistent re-experiencing and related psychopathology. Individual differences in pre-trauma executive control possibly play a critical role. Therefore, this study investigated whether a relatively poor pre-stressor ability to resist proactive interference in working memory might increase risk for experiencing undesirable intrusive memories after being exposed to a stressful event. Non-clinical participants (N = 85) completed a modified version of a widely used test of interference control in working memory (CVLT; Kramer and Delis 1991) and subsequently watched an emotional film fragment. Following presentation of the fragment, intrusive memories were recorded in a 1-week diary and at a follow up session 7 days later. A relatively poor ability to resist proactive interference was related to a relatively high frequency of film-related intrusive memories. This relationship was independent of neuroticism and gender. These findings are consistent with the idea that a pre-morbid deficit in the ability to resist proactive interference reflects a vulnerability factor for experiencing intrusive memories after trauma exposure

Discovering joint associations between disease and gene pairs with a novel similarity test

Genes in a functional pathway can have complex interactions. A gene might activate or suppress another gene, so it is of interest to test joint associations of gene pairs. To simultaneously detect the joint association between disease and two genes (or two chromosomal regions), we propose a new test with the use of genomic similarities. Our test is designed to detect epistasis in the absence of main effects, main effects in the absence of epistasis, or the presence of both main effects and epistasis. Results: The simulation results show that our similarity test with the matching measure is more powerful than the Pearson's chi(2) test when the disease mutants were introduced at common haplotypes, but is less powerful when the disease mutants were introduced at rare haplotypes. Our similarity tests with the counting measures are more sensitive to marker informativity and linkage disequilibrium patterns, and thus are often inferior to the similarity test with the matching measure and the Pearson 's chi(2) test. Conclusions: In detecting joint associations between disease and gene pairs, our similarity test is a complementary method to the Pearson's chi(2) test

Deformation-related volcanism in the Pacific Ocean linked to the Hawaiian-Emperor bend

Ocean islands, seamounts and volcanic ridges are thought to form above mantle plumes. Yet, this mechanism cannot explain many volcanic features on the Pacific Ocean floor and some might instead be caused by cracks in the oceanic crust linked to the reorganization of plate motions. A distinctive bend in the Hawaiian–Emperor volcanic chain has been linked to changes in the direction of motion of the Pacific Plate, movement of the Hawaiian plume, or a combination of both. However, these links are uncertain because there is no independent record that precisely dates tectonic events that affected the Pacific Plate. Here we analyse the geochemical characteristics of lava samples collected from the Musicians Ridges, lines of volcanic seamounts formed close to the Hawaiian–Emperor bend. We find that the geochemical signature of these lavas is unlike typical ocean island basalts and instead resembles mid-ocean ridge basalts. We infer that the seamounts are unrelated to mantle plume activity and instead formed in an extensional setting, due to deformation of the Pacific Plate. 40Ar/39Ar dating reveals that the Musicians Ridges formed during two time windows that bracket the time of formation of the Hawaiian–Emperor bend, 53–52 and 48–47 million years ago. We conclude that the Hawaiian–Emperor bend was formed by plate–mantle reorganization, potentially triggered by a series of subduction events at the Pacific Plate margins

Is There a Seamount Effect on Microbial Community Structure and Biomass? The Case Study of Seine and Sedlo Seamounts (Northeast Atlantic)

Seamounts are considered to be “hotspots” of marine life but, their role in oceans primary productivity is still under discussion. We have studied the microbial community structure and biomass of the epipelagic zone (0–150 m) at two northeast Atlantic seamounts (Seine and Sedlo) and compared those with the surrounding ocean. Results from two cruises to Sedlo and three to Seine are presented. Main results show large temporal and spatial microbial community variability on both seamounts. Both Seine and Sedlo heterotrophic community (abundance and biomass) dominate during winter and summer months, representing 75% (Sedlo, July) to 86% (Seine, November) of the total plankton biomass. In Seine, during springtime the contribution to total plankton biomass is similar (47% autotrophic and 53% heterotrophic). Both seamounts present an autotrophic community structure dominated by small cells (nano and picophytoplankton). It is also during spring that a relatively important contribution (26%) of large cells to total autotrophic biomass is found. In some cases, a “seamount effect” is observed on Seine and Sedlo microbial community structure and biomass. In Seine this is only observed during spring through enhancement of large autotrophic cells at the summit and seamount stations. In Sedlo, and despite the observed low biomasses, some clear peaks of picoplankton at the summit or at stations within the seamount area are also observed during summer. Our results suggest that the dominance of heterotrophs is presumably related to the trapping effect of organic matter by seamounts. Nevertheless, the complex circulation around both seamounts with the presence of different sources of mesoscale variability (e.g. presence of meddies, intrusion of African upwelling water) may have contributed to the different patterns of distribution, abundances and also changes observed in the microbial community

Absence of Membrane Phosphatidylcholine Does Not Affect Virulence and Stress Tolerance Phenotypes in the Opportunistic Pathogen Pseudomonas aeruginosa

During growth in presence of choline, both laboratory and clinical Pseudomonas aeruginosa strains synthesize phosphatidylcholine (PC), and PC makes up ∼4% of the total membrane phospholipid content. In all the strains tested, PC synthesis occurred only when choline is provided exogenously. Mutants defective in synthesis of PC were generated in the strain backgrounds PAO1 and PA14. Minimum inhibitory concentration studies testing sensitivity of PC-deficient strains towards various antibiotics and cationic antimicrobial peptides revealed no differences as compared to wild-type strains. Mutants incapable of synthesizing PC were also found to be unaffected in motility and biofilm formation on abiotic surfaces, colonization of biotic surfaces and virulence in a mouse infection model. A global phenotypic microarray was further used to identify conditions wherein membrane PC may play a role of in P. aeruginosa. No culture conditions were identified wherein wild-type and PC-deficient mutants showed phenotypic differences. Membrane PC may serve a highly specific role during P. aeruginosa interactions with its eukaryotic hosts based on all the clinical strains tested retaining the ability to synthesize it during availability of choline

Statistical Coding and Decoding of Heartbeat Intervals

The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems

Computational approaches for modeling human intestinal absorption and permeability

Human intestinal absorption (HIA) is an important roadblock in the formulation of new drug substances. Computational models are needed for the rapid estimation of this property. The measurements are determined via in vivo experiments or in vitro permeability studies. We present several computational models that are able to predict the absorption of drugs by the human intestine and the permeability through human Caco-2 cells. The training and prediction sets were derived from literature sources and carefully examined to eliminate compounds that are actively transported. We compare our results to models derived by other methods and find that the statistical quality is similar. We believe that models derived from both sources of experimental data would provide greater consistency in predictions. The performance of several QSPR models that we investigated to predict outside the training set for either experimental property clearly indicates that caution should be exercised while applying any of the models for quantitative predictions. However, we are able to show that the qualitative predictions can be obtained with close to a 70% success rate