Long-term biogenic particle fluxes in the Bering Sea and the central subarctic Pacific Ocean

Time-series sediment traps were deployed for five consecutive years in two distinctively different subarctic marine environments. The centrally located subarctic pelagic Station SA (49°N, 174°W; water depth 5406 m) was simultaneously studied along with the marginal sea Station AB (53.5°N, 177°W; water depth 3788 m) in the Aleutian Basin of the Bering Sea. A mooring system was tethered to the sea-floor with a PARFLUX type trap with 13 sample bottles, which was placed at 600 m above the sea-floor at each of the two stations. Sampling intervals were synchronized at the stations, and they were generally set for 20 days during highly productive seasons, spring through fall, and 56 days during winter months of low productivity. Total mass fluxes, which consisted of mainly biogenic phases, were significantly greater at the marginal sea Station AB than at the pelagic Station SA for the first four years and moderately greater for the last year of the observations. This reflects the generally recognized higher productivity in the Bering Sea. Temporal excursion patterns of the mass fluxes at the two stations generally were in parallel, implying that temporal changes in their biological productivity are strongly governed by a large-scale seasonal climatic variability over the region rather than local phenomena. The primary reason for the difference in total mass flux at the two stations stems mainly from varying contributions of siliceous and calcareous planktonic assemblages. A significantly higher opal contribution at Station AB than at Station SA was mainly due to diatoms. Diatom fluxes at the marginal sea station were about twice those observed at the pelagic station, resulting in a very high opal contribution at Station AB. In contrast to the opal fluxes, CaCO3 fluxes at Station AB were slightly lower than at Station SA. The ratios of Corg/Cinorg were usually significantly greater than one in both regions, suggesting that preferentially greater organic carbon from cytoplasm than skeletal inorganic carbon was exported from the surface layers. Such a process, known as the biological pump, leads to a carbon sink which effectively lowers p CO2 in the surface layers and then allows a net flux of atmospheric CO2 into the surface layer. The efficiency of the biological pump is greater in the Bering Sea than at the open-ocean station.

Physical properties of sediment cores from the Iberian Continental Slope

Climatic changes cause alterations in circulation patterns of the world oceans. The highly saline Mediterranean Outflow Water (MOW), built within the Mediterranean Sea crosses the Strait of Gibraltar in westerly directions, turning north-westward to stick to the Iberian Slope within 600-1500m water depths. Circulation pattern and current speed of the MOW are strongly influenced by climatically induced variations and thus control sedimentation processes along the South- and West - Iberian Continental Slope. Sedimentation characteristics of the investigated area are therefore suitable to reconstruct temporal hydrodynamic changes of the MOW. Detailed investigations on the silt-sized grain distribution, physical properties and hydroacoustic data were performed to recalculate paleo-current-velocities and to understand the sedimentation history in the Golf of Cadiz and the Portuguese Continental Slope. A time model based on d18Odata and 14C-datings of planktic foraminifera allowed the stratigraphical classification of the core material and thus the dating of the current induced sediment layers showing the variations of paleo-current intensities. The evaluation and interpretation of the gathered data sets enabled us to reconstruct lateral and temporal sedimentation patterns of the MOW for the Holocene and the late Pleistocene, back to the Last Glacial Maximum (LGM).

Benthic nematode assemblage composition and diversity during a natural recovery process of Zostera noltii seagrass beds,

In 2008, the stable seagrass beds of the Mira estuary (SW Portugal) disappeared completely; however, during 2009, they have begun to present early symptoms of natural recovery, characterised by a strongly heterogeneous distribution. This study was designed to investigate the spatial and temporal variability patterns of species composition, densities and trophic composition of the benthic nematode assemblages in this early recovery process, at two sampling sites with three stations each and at five sampling occasions. Because of the erratic and highly patchy seagrass recovery and the high environmental similarity of the two sampling sites, we expected within-site variability in nematode assemblages to exceed between-site variability. However, contrary to that expectation, whilst nematode genus composition was broadly similar between sites, nematode densities differed significantly between sites, and this between-site variability exceeded within-site variability. This may be linked to differences in the Zostera recovery patterns between both sites. In addition, no clear temporal patterns of nematode density, trophic composition and diversity were evident.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns

This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.

Patterns Of Seizure Control In Patients With Mesial Temporal Lobe Epilepsy With And Without Hippocampus Sclerosis.

Objective Patients with mesial temporal lobe epilepsy (MTLE) may present unstable pattern of seizures. We aimed to evaluate the occurrence of relapse-remitting seizures in MTLE with (MTLE-HS) and without (MTLE-NL) hippocampal sclerosis. Method We evaluated 172 patients with MTLE-HS (122) or MTLE-NL (50). Relapse-remitting pattern was defined as periods longer than two years of seizure-freedom intercalated with seizure recurrence. Infrequent seizures was considered as up to three seizures per year and frequent seizures as any period of seizures higher than that. Results Thirty-seven (30%) MTLE-HS and 18 (36%) MTLE-NL patients had relapse-remitting pattern (X2, p = 0.470). This was more common in those with infrequent seizures (X2, p < 0.001). Twelve MTLE-HS and one MTLE-NL patients had prolonged seizure remission between the first and second decade of life (X2, p = 0.06). Conclusion Similar proportion of MTLE-HS or MTLE-NL patients present relapse-remitting seizures and this occurs more often in those with infrequent seizures.

Spatio-temporal patterns of throughfall and solute deposition in an open tropical rain forest

The brief interaction of precipitation with a forest canopy can create a high spatial variability of both throughfall and solute deposition. We hypothesized that (i) the variability in natural forest systems is high but depends on system-inherent stability, (ii) the spatial variability of solute deposition shows seasonal dynamics depending on the increase in rainfall frequency, and (iii) spatial patterns persist only in the short-term. The study area in the north-western Brazilian state of Rondonia is subject to a climate with a distinct wet and dry season. We collected rain and throughfall on an event basis during the early wet season (n = 14) and peak of the wet season (n = 14) and analyzed the samples for pH and concentrations of NH4+, Na+, K+, Ca2+ Mg2+,, Cl-, NO3-, SO42- and DOC. The coefficient 3 4 cient of variation for throughfall based on both sampling intervals was 29%, which is at the lower end of values reported from other tropical forest sites, but which is higher than in most temperate forests. Coefficients of variation of solute deposition ranged from 29% to 52%. This heterogeneity of solute deposition is neither particularly high nor particularly tow compared with a range of tropical and temperate forest ecosystems. We observed an increase in solute deposition variability with the progressing wet season, which was explained by a negative correlation between heterogeneity of solute deposition and antecedent dry period. The temporal stability of throughfall. patterns was Low during the early wet season, but gained in stability as the wet season progressed. We suggest that rapid plant growth at the beginning of the rainy season is responsible for the lower stability, whereas less vegetative activity during the later rainy season might favor the higher persistence of ""hot"" and ""cold"" spots of throughfall. quantities. The relatively high stability of throughfall patterns during later stages of the wet season may influence processes at the forest floor and in the soil. Solute deposition patterns showed less clear trends but all patterns displayed a short-term stability only. The weak stability of those patterns is apt to impede the formation of solute deposition -induced biochemical microhabitats in the soil. (C) 2008 Elsevier B.V. All rights reserved.

Serological patterns and temporal trends of HTLV-1/2 infection in high-risk populations attending public health units in Sao Paulo, Brazil

Background: HTLV-1/2 diagnosis in high-risk populations from Sao Paulo, Brazil has been problematic due a high proportion of seroindeterminate results. Objectives: To confirm and extend previous findings regarding HTLV-1/2 diagnosis in this geographic area. Study design: Sera from 2312 patients were tested for HTLV-1/2 antibodies using enzyme immunoassay (EIA) and Western blot (WB) analysis. Patients were from AIDS Reference Centers (Group 1; 1393 patients) and HTLV out-patient clinics (Group 11; 919 patients). Results were analyzed according to patients` age, gender, and clinic type. Results: HTLV-1 and HTLV-2 were detected in both groups. Among seropositive females, HTLV-2 was slightly more common in Group 1 (54.5%), while HTLV-1 prevailed in Group II (73.9%). Males from Group II had a higher percentage of HTLV-seroindeterminate results. No correlation between HTLV serological results and age was detected. Temporal analyses disclosed a high number of HTLV-seroindeterminate samples, and a large spectrum of indeterminate WB profiles. GD21 and/or rgp46-II bands were detected in 34.6% of sera from Group 1, and a p24 or p19 band was detected in 35.3% of sera from Group II. Conclusions: High rates of HTLV-indeterminate serological patterns during temporal analyses were confirmed in high-risk populations from Sao Paulo, Brazil. (c) 2008 Elsevier B.V. All rights reserved.

Spatial and temporal patterns in Australian wheat yield and their relationship with ENSO

Spatial and temporal variability in wheat production in Australia is dominated by rainfall occurrence. The length of historical production records is inadequate, however, to analyse spatial and temporal patterns conclusively. In this study we used modelling and simulation to identify key spatial patterns in Australian wheat yield, identify groups of years in the historical record in which spatial patterns were similar, and examine association of those wheat yield year groups with indicators of the El Nino Southern Oscillation (ENSO). A simple stress index model was trained on 19 years of Australian Bureau of Statistics shire yield data (1975-93). The model was then used to simulate shire yield from 1901 to 1999 for all wheat-producing shires. Principal components analysis was used to determine the dominating spatial relationships in wheat yield among shires. Six major components of spatial variability were found. Five of these represented near spatially independent zones across the Australian wheatbelt that demonstrated coherent temporal (annual) variability in wheat yield. A second orthogonal component was required to explain the temporal variation in New South Wales. The principal component scores were used to identify high- and low-yielding years in each zone. Year type groupings identified in this way were tested for association with indicators of ENSO. Significant associations were found for all zones in the Australian wheatbelt. Associations were as strong or stronger when ENSO indicators preceding the wheat season (April-May phases of the Southern Oscillation Index) were used rather than indicators based on classification during the wheat season. Although this association suggests an obvious role for seasonal climate forecasting in national wheat crop forecasting, the discriminatory power of the ENSO indicators, although significant, was not strong. By examining the historical years forming the wheat yield analog sets within each zone, it may be possible to identify novel climate system or ocean-atmosphere features that may be causal and, hence, most useful in improving seasonal forecasting schemes.

Engineering Temporal and Spatial Aspects in OWL using Patterns

WWW is a huge, open, heterogeneous system, however its contents data is mainly human oriented. The Semantic Web needs to assure that data is readable and “understandable” to intelligent software agents, though the use of explicit and formal semantics. Ontologies constitute a privileged artifact for capturing the semantic of the WWW data. Temporal and spatial dimensions are transversal to the generality of knowledge domains and therefore are fundamental for the reasoning process of software agents. Representing temporal/spatial evolution of concepts and their relations in OWL (W3C standard for ontologies) it is not straightforward. Although proposed several strategies to tackle this problem but there is still no formal and standard approach. This work main goal consists of development of methods/tools to support the engineering of temporal and spatial aspects in intelligent systems through the use of OWL ontologies. An existing method for ontology engineering, Fonte was used as framework for the development of this work. As main contributions of this work Fonte was re-engineered in order to: i) support the spatial dimension; ii) work with OWL Ontologies; iii) and support the application of Ontology Design Patterns. Finally, the capabilities of the proposed approach were demonstrated by engineering time and space in a demo ontology about football.

Modelling and Forecasting Mortality Patterns

Thesis submitted in partial fulfillment of the requirements for the Degree of Doctor of Statistics and Information Management

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Discovery and visualization of interesting patterns

Die Preise für Speicherplatz fallen stetig, da verwundert es nicht, dass Unternehmen riesige Datenmengen anhäufen und sammeln. Diese immensen Datenmengen müssen jedoch mit geeigneten Methoden analysiert werden, um für das Unternehmen überlebensnotwendige Muster zu identifizieren. Solche Muster können Probleme aber auch Chancen darstellen. In jedem Fall ist es von größter Bedeutung, rechtzeitig diese Muster zu entdecken, um zeitnah reagieren zu können. Um breite Nutzerschichten anzusprechen, müssen Analysemethoden ferner einfach zu bedienen sein, sofort Rückmeldungen liefern und intuitive Visualisierungen anbieten. Ich schlage in der vorliegenden Arbeit Methoden zur Visualisierung und Filterung von Assoziationsregeln basierend auf ihren zeitlichen Änderungen vor. Ich werde lingustische Terme (die durch Fuzzymengen modelliert werden) verwenden, um die Historien von Regelbewertungsmaßen zu charakterisieren und so eine Ordnung von relevanten Regeln zu generieren. Weiterhin werde ich die vorgeschlagenen Methoden auf weitereModellarten übertragen, die Software-Plattformvorstellen, die die Analysemethoden dem Nutzer zugänglich macht und schließlich empirische Auswertungen auf Echtdaten aus Unternehmenskooperationen vorstellen, die die Wirksamkeit meiner Vorschläge belegen.