Integrating a mobile accessible electronic system into dockside monitoring: How can small-scale fisheries data collection programs transition from paper-based to digital data collection?

Thesis (Master's)--University of Washington, 2016-06

Architecture of Large-Scale Systems

In this paper various techniques in relation to large-scale systems are presented. At first, explanation of large-scale systems and differences from traditional systems are given. Next, possible specifications and requirements on hardware and software are listed. Finally, examples of large-scale systems are presented.

Detection of mesoscale thermal fronts from 4km data using smoothing techniques: Gradient-based fronts classification and basin scale application

In order to optimize frontal detection in sea surface temperature fields at 4 km resolution, a combined statistical and expert-based approach is applied to test different spatial smoothing of the data prior to the detection process. Fronts are usually detected at 1 km resolution using the histogram-based, single image edge detection (SIED) algorithm developed by Cayula and Cornillon in 1992, with a standard preliminary smoothing using a median filter and a 3 × 3 pixel kernel. Here, detections are performed in three study regions (off Morocco, the Mozambique Channel, and north-western Australia) and across the Indian Ocean basin using the combination of multiple windows (CMW) method developed by Nieto, Demarcq and McClatchie in 2012 which improves on the original Cayula and Cornillon algorithm. Detections at 4 km and 1 km of resolution are compared. Fronts are divided in two intensity classes (“weak” and “strong”) according to their thermal gradient. A preliminary smoothing is applied prior to the detection using different convolutions: three type of filters (median, average and Gaussian) combined with four kernel sizes (3 × 3, 5 × 5, 7 × 7, and 9 × 9 pixels) and three detection window sizes (16 × 16, 24 × 24 and 32 × 32 pixels) to test the effect of these smoothing combinations on reducing the background noise of the data and therefore on improving the frontal detection. The performance of the combinations on 4 km data are evaluated using two criteria: detection efficiency and front length. We find that the optimal combination of preliminary smoothing parameters in enhancing detection efficiency and preserving front length includes a median filter, a 16 × 16 pixel window size, and a 5 × 5 pixel kernel for strong fronts and a 7 × 7 pixel kernel for weak fronts. Results show an improvement in detection performance (from largest to smallest window size) of 71% for strong fronts and 120% for weak fronts. Despite the small window used (16 × 16 pixels), the length of the fronts has been preserved relative to that found with 1 km data. This optimal preliminary smoothing and the CMW detection algorithm on 4 km sea surface temperature data are then used to describe the spatial distribution of the monthly frequencies of occurrence for both strong and weak fronts across the Indian Ocean basin. In general strong fronts are observed in coastal areas whereas weak fronts, with some seasonal exceptions, are mainly located in the open ocean. This study shows that adequate noise reduction done by a preliminary smoothing of the data considerably improves the frontal detection efficiency as well as the global quality of the results. Consequently, the use of 4 km data enables frontal detections similar to 1 km data (using a standard median 3 × 3 convolution) in terms of detectability, length and location. This method, using 4 km data is easily applicable to large regions or at the global scale with far less constraints of data manipulation and processing time relative to 1 km data.

Diurnal temporal patterns of the diversity and the abundance of reef fishes in a branching coral patch in New Caledonia

Small-scale spatial and temporal variability in animal abundance is an intrinsic characteristic of marine ecosystems but remains largely unknown for most animals, including coral reef fishes. In this study, we used a remote autonomous unbaited video system and recorded reef fish assemblages during daylight hours, 10 times a day for 34 consecutive days in a branching coral patch of the lagoon of New Caledonia. In total, 50 031 fish observations belonging to 114 taxa, 66 genera and 31 families were recorded in 256 recorded videos. Carnivores and herbivore-detritus feeders dominated the trophic structure. We found significant variations in the composition of fish assemblages between times of day. Taxa richness and fish abundance were greater in the early morning and in the late afternoon than during the day. Fourteen taxa displayed well-defined temporal patterns in abundance with one taxon influenced by time of day, six influenced by tidal state and seven influenced by both time of day and tidal state. None of these 14 taxa were piscivores, 10 were herbivore-detritus feeders, three were carnivores and one was plankton feeder. Our results suggest a diel migration from feeding grounds to shelter areas and highlight the importance of taking into account small-scale temporal variability in animal diversity and abundance when studying connectivity between habitats and monitoring communities.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Optimization of the large scale synthesis of the LSF-20 cathode material for SOFCs

Póster presentado en: 21st World Hydrogen Energy Conference 2016. Zaragoza, Spain. 13-16th June, 2016

A perfect day for zebrafish : neuromodulation of sleep in a diurnal vertebrate

Every day, we shift among various states of sleep and arousal to meet the many demands of our bodies and environment. A central puzzle in neurobiology is how the brain controls these behavioral states, which are essential to an animal's well-being and survival. Mammalian models have predominated sleep and arousal research, although in the past decade, invertebrate models have made significant contributions to our understanding of the genetic underpinnings of behavioral states. More recently, the zebrafish (Danio rerio), a diurnal vertebrate, has emerged as a promising model system for sleep and arousal research.

In this thesis, I describe two studies on sleep/arousal pathways that I conducted using zebrafish, and I discuss how the findings can be combined in future projects to advance our understanding of vertebrate sleep/arousal pathways. In the first study, I discovered a neuropeptide that regulates zebrafish sleep and arousal as a result of a large-scale effort to identify molecules that regulate behavioral states. Taking advantage of facile zebrafish genetics, I constructed mutants for the three known receptors of this peptide and identified the one receptor that exclusively mediates the observed behavioral effects. I further show that the peptide exerts its behavioral effects independently of signaling at a key module of a neuroendocrine signaling pathway. This finding contradicts the hypothesis put forth in mammalian systems that the peptide acts through the classical neuroendocrine pathway; our data further generate new testable hypotheses for determining the central nervous system or alternative neuroendocrine pathways involved.

Second, I will present the development of a chemigenetic method to non-invasively manipulate neurons in the behaving zebrafish. I validated this technique by expressing and inducing the chemigenetic tool in a restricted population of sleep-regulating neurons in the zebrafish. As predicted by established models of this vertebrate sleep regulator, chemigenetic activation of these neurons induced hyperactivity, whereas chemigenetic ablation of these neurons induced increased sleep behavior. Given that light is a potent modulator of behavior in zebrafish, our proof-of-principle data provide a springboard for future studies of sleep/arousal and other light-dependent behaviors to interrogate genetically-defined populations of neurons independently of optogenetic tools.

Effect of Playing Interactive Computer Game on Distress of Insulin Injection Among Type 1 Diabetic Children

Background: Diabetic children and their families experience high level stress because of daily insulin injection. Objectives: This study was conducted to investigate the impact of an interactive computer game on behavioral distress due to insulin injection among diabetic children. Patients and Methods: In this clinical trial, thirty children (3-12 years) with type 1 diabetes who needed daily insulin injection were recruited and allocated randomly into two groups. Children in intervention groups received an interactive computer game and asked to play at home for a week. No special intervention was done for control group. The behavioral distress of groups was assessed before, during and after the intervention by Observational Scale of Behavioral Distress–Revised (OSBD-R). Results: Repeated measure ANOVA test showed no significantly difference of OSBD-R over time for control group (P = 0.08), but this changes is signification in the study group (P = 0.001). Comparison mean score of distress were significantly different between two groups (P = 0.03). Conclusions: According to the findings, playing interactive computer game can decrease behavioral distress induced by insulin injection in type 1 diabetic children. It seems this game can be beneficial to be used alongside other interventions.

Towards understanding resprouting at the global scale

Understanding and predicting plant response to disturbance is of paramount importance in our changing world. Resprouting ability is often considered a simple qualitative trait and used in many ecological studies. Our aim is to show some of the complexities of resprouting while highlighting cautions that need be taken in using resprouting ability to predict vegetation responses across disturbance types and biomes. There are marked differences in resprouting depending on the disturbance type, and fire is often the most severe disturbance because it includes both defoliation and lethal temperatures. In the Mediterranean biome, there are differences in functional strategies to cope with water deficit between resprouters (dehydration avoiders) and nonresprouters (dehydration tolerators); however, there is little research to unambiguously extrapolate these results to other biomes. Furthermore, predictions of vegetation responses to changes in disturbance regimes require consideration not only of resprouting, but also other relevant traits (e.g. seeding, bark thickness) and the different correlations among traits observed in different biomes; models lacking these details would behave poorly at the global scale. Overall, the lessons learned from a given disturbance regime and biome (e.g. crown-fire Mediterranean ecosystems) can guide research in other ecosystems but should not be extrapolated at the global scale.

Therapeutic education, the premise of adherence to the type 2 diabetes therapeutic regimen

Background: type 2 diabetes mellitus includes changes in lifestyle in its etiology of prevention, but the evidence is clear —even when people know what to do and what they want to do, they simply do not adopt adherence behaviors. Structured education will allow improving not only metabolic control, but also the adjustment process to a new situation of disease, as well as to develop the patient’s skills in order to make him the key manager of his illness. Objectives: To determine patients’ adherence to prescribed therapeutic regimens. Material and methods: Quantitative, cross-sectional, non-experimental, descriptive, correlational study, with a sample of 102 people with type 2 diabetes, aged between 40 and 85 years old, mostly male (51.96%). The evaluation protocol included social-demographic and clinical questionnaire, Diabetes Self-care Scale and a questionnaire on Diabetes’ knowledge. We also used HbA1c in order to directly assess adherence. Results: It appears that there is no statistically signiicant correlation between socio-demographic variables such as gender and age and adherence. Variables, such as blood glucose monitoring, speciic diet compliance and knowledge, reveal a statistically signiicant effect on adherence (P < .05). Conclusion: The evidence is clear on the urgent need to recognize the importance of measuring patient adherence to a diabetes treatment plan for the maintenance of glycaemic control. We suggest the reinforcement of educational programs in people with type 2 diabetes so as to improve adherence to self-care.

Adherence to therapeuthic regimen and metabolic control of type 1 diabetes

Abstract Objectives: To assess the adherence to therapeutic regimen; to determine the Hemoglobin Glycation Index (HbA1c); to analyse the relationship that exists between the adherence to therapeutic regimen and metabolic control. Design: correlational analytical study, carried out according to a cross-sectional perspective. Participants: A non-probabilistic sample of 266 people with type 1 diabetes aged between 18 and 78 years old (mean M = 51.02 ± SD = 18.710), attending follow-up diabetes consultations. Mostly male individuals (51.88%), with low schooling level (50.75% had only inished elementar school). Measuring Instruments: We used the following data collection tools: a questionnaire on clinical and socio-demographic data, blood analysis of venous blood to determine the glycated hemoglobin level (HbA1c).Three self-report scales were used: Accession to Diabetes Treatment (Matos, 1999), Self-perception Scale (Vaz Serra, 1986) and Social Support Scale (Matos & Rodrigues, 2000). Results: In a sample in which the mean disease duration is 12.75 years, 69.17% of the sample run glycemic control tests between once a day and four times a year and 42.86% of them undergo insulin treatment. In the last 3 weeks, 26.32% of these people have experienced an average of 4.22 to 44.36%, hypoglycemic crises and experienced an average of 6.18 hyperglycemic crises. 57% of the individuals have showed a poor metabolic control (mean HbA1c higher than 7.5% (HbA1c mean M ≥ 7.50%). The mean psychosocial proile revealed individuals who show a decent self-esteem (M = 70.81) and acceptable social support (M = 58.89). Conclusions: The results suggest we should develop a kind of investigation that could be used to monitor the strenght of the mediation effect effect of the psychosocial predictive dimension of the adherence, since it has become essential to support a multidisciplinary approach which center lays in the promotion of a co-responsible self-management from the person who suffers from diabetes. This will enable a better quality of life; fewer years of people’s lives lost prematurely and a better health with less economical costs for citizens and healthcare systems.

Trophic signatures of small-scale fishing gears: implications for conservation and management

We quantified the ecosystem effects of small-scale gears operating in southern European waters (Portugal, Spain, Greece), based on a widely accepted ecosystem measure and indicator, the trophic level (TL). We used data from experimental fishing trials during 1997 to 2000. We studied a wide range of gear types and sizes: (1) gill nets of 8 mesh sizes, ranging from 44 to 80 mm; (2) trammel nets of 9 inner panel mesh sizes, ranging from 40 to 140 mm; and (3) longlines of 8 hook sizes, ranging from Nos. 15 (small) to 5 (large). We used the number of species caught per TL class for constructing trophic signatures (i.e. cumulative TL distributions), and estimated the TL at 25, 50 and 75% cumulative frequency (TL25, TL50, TL75) and the slopes using the logistic function. We also estimated the mean weighted TL of the catches (TLW). Our analyses showed that the TL characteristics of longlines varied much more than those of gill and trammel nets. The longlines of large hooks (Nos. 10, 9, 7, 5) were very TL selective, and their trophic signatures had very steep slopes, the highest mean TL50 values, very narrow mean TL25 to TL75 ranges and mean TLW > 4. In addition, the mean number of TL classes exploited was smaller and the mean TL50 and TLW were larger for the longlines of small hooks (Nos. 15, 13, 12, 11) in Greek than in Portuguese waters. Trammel and gill nets caught more TL classes, and the mean slopes of their trophic signatures were significantly smaller than those of longlines as a group. In addition, the mean number of TL classes exploited, the mean TL50 and the TLW of gill nets were significantly smaller than those of trammel nets. We attribute the differences between longlines of small hooks to bait type, and the differences between all gear types to their characteristic species and size-selectivity patterns. Finally, we showed how the slope and the TL50 Of the trophic signatures can be used to characterise different gears along the ecologically 'unsustainable-sustainable' continuum.

Broad-scale mapping of seafloor habitats in the north-east Atlantic using existing environmental data

If marine management policies and actions are to achieve long-term sustainable use and management of the marine environment and its resources, they need to be informed by data giving the spatial distribution of seafloor habitats over large areas. Broad-scale seafloor habitat mapping is an approachwhich has the benefit of producing maps covering large extents at a reasonable cost. This approach was first investigated by Roff et al. (2003), who, acknowledging that benthic communities are strongly influenced by the physical characteristics of the seafloor, proposed overlaying mapped physical variables using a geographic information system (GIS) to produce an integrated map of the physical characteristics of the seafloor. In Europe the method was adapted to the marine section of the EUNIS (European Nature Information System) classification of habitat types under the MESH project, andwas applied at an operational level in 2011 under the EUSeaMap project. The present study compiled GIS layers for fundamental physical parameters in the northeast Atlantic, including (i) bathymetry, (ii) substrate type, (iii) light penetration depth and (iv) exposure to near-seafloor currents andwave action. Based on analyses of biological occurrences, significant thresholds were fine-tuned for each of the abiotic layers and later used in multi-criteria raster algebra for the integration of the layers into a seafloor habitat map. The final result was a harmonised broad-scale seafloor habitat map with a 250 m pixel size covering four extensive areas, i.e. Ireland, the Bay of Biscay, the Iberian Peninsula and the Azores. The map provided the first comprehensive perception of habitat spatial distribution for the Iberian Peninsula and the Azores, and fed into the initiative for a pan- European map initiated by the EUSeaMap project for Baltic, North, Celtic and Mediterranean seas.

Validity and reliability of the international fItness scale (IFIS) in a population-based sample of schoolchildren in Bogota, Colombia: The FUPRECOL study

The International FItness Scale (IFIS) is a self-reported measure of physical fitness that could easily. This scale has been validated in children, adolescents, and young adults; however, it is unknown whether the IFIS represents a valid and reliable estimate of physical fitness in Latino-American youth population. In the present study we aimed to examine the validity and reliability of the IFIS on a population-based sample of schoolchildren in Bogota, Colombia. Participants were 1,875 Colombian youth (56.2% girls) aged 9 to 17.9 years old. We measured adiposity markers (body fat, waist-to-height ratio, skinfold thicknesses and BMI), blood pressure, lipids profile, fasting glucose, and physical fitness level (self reported and measured). Also, a validated cardiometabolic risk index was used. An age- and sex-matched sample of 229 Schoolchildren originally not included in the study sample fulfilled IFIS twice for reliability purposes. Our data suggest that both measured and self-reported overall fitness were associated inversely with adiposity indicators and a cardiometabolic risk score. Overall, schoolchildren who self-reported “good” and “very good” fitness had better measured fitness than those who reported “very poor” and “poor” fitness (all p<0.001). Test–retest reliability of IFIS items was also good, with an average weighted Kappa of 0.811. Therefore, our findings suggest that self-reported fitness, as assessed by IFIS, is a valid, reliable, and health-related measure, and it can be a good alternative for future use in large studies with Latin-schoolchildren from Colombia.

Mucopolysaccharidosis Type Ii: Identification Of 30 Novel Mutations Among Latin American Patients.

In this study, 103 unrelated South-American patients with mucopolysaccharidosis type II (MPS II) were investigated aiming at the identification of iduronate-2-sulfatase (IDS) disease causing mutations and the possibility of some insights on the genotype-phenotype correlation The strategy used for genotyping involved the identification of the previously reported inversion/disruption of the IDS gene by PCR and screening for other mutations by PCR/SSCP. The exons with altered mobility on SSCP were sequenced, as well as all the exons of patients with no SSCP alteration. By using this strategy, we were able to find the pathogenic mutation in all patients. Alterations such as inversion/disruption and partial/total deletions of the IDS gene were found in 20/103 (19%) patients. Small insertions/deletions/indels (<22 bp) and point mutations were identified in 83/103 (88%) patients, including 30 novel mutations; except for a higher frequency of small duplications in relation to small deletions, the frequencies of major and minor alterations found in our sample are in accordance with those described in the literature.