AquaLog : an ontology-driven question answering system for organizational semantic intranets

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

Form follows function:model-driven engineering for clinical trials

We argue that, for certain constrained domains, elaborate model transformation technologies-implemented from scratch in general-purpose programming languages-are unnecessary for model-driven engineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of software tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial protocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automatically from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conducting the trial instantiates such models in reporting observations-again by completing a form to create a conformant XML document, representing the data gathered during that observation. Simple standard form management tools are all that is needed. Our approach is applicable to a wide variety of information-modelling domains: not just clinical trials, but also electronic public sector computing, customer relationship management, document workflow, and so on. © 2012 Springer-Verlag.

Candidate knowledge? Exploring epistemic claims in scientific writing:a corpus-driven approach

In this article I argue that the study of the linguistic aspects of epistemology has become unhelpfully focused on the corpus-based study of hedging and that a corpus-driven approach can help to improve upon this. Through focusing on a corpus of texts from one discourse community (that of genetics) and identifying frequent tri-lexical clusters containing highly frequent lexical items identified as keywords, I undertake an inductive analysis identifying patterns of epistemic significance. Several of these patterns are shown to be hedging devices and the whole corpus frequencies of the most salient of these, candidate and putative, are then compared to the whole corpus frequencies for comparable wordforms and clusters of epistemic significance. Finally I interviewed a ‘friendly geneticist’ in order to check my interpretation of some of the terms used and to get an expert interpretation of the overall findings. In summary I argue that the highly unexpected patterns of hedging found in genetics demonstrate the value of adopting a corpus-driven approach and constitute an advance in our current understanding of how to approach the relationship between language and epistemology.

A case study of the development of the Argentinean community college system

In the 1980's and 1990's, Argentina was undergoing significant political, social and economic changes as a result of the change over from a military driven government to elected governments. A major aspect of the change was an increased emphasis on privatization, and promotion of foreign and domestic investment in Argentina. Higher education leaders were increasingly drawn into developing a national strategy for changing the educational structure to help facilitate changes in other aspects of the society. Preliminary reviews by the Argentinean higher education leaders indicated that adaptation of the American community college promised to help achieve the national goals. ^ The purpose of this study was to determine: if and how the community college concept, an American invention, could be adapted to function in Argentina, a nation with a significantly different history of political, social, cultural and economic development. Achieving this purpose involved: identifying the key leaders in the movement that developed to apply the community college concept in Argentina; the study of their perspectives regarding the movement as it developed; and tracking the assistance given by selected American community college leaders. ^ The case study method was employed in this research, using interview and historical data collection. Key leaders from higher education in the United States and Argentina were interviewed in-depth, to determine their views. An interview protocol with appropriate sub-questions was followed to ensure complete coverage. The interviewees identified several major areas of education in need of change including, the system, access to the system, new areas of study, integration into the hemisphere and, in general, decentralization. Historical review revealed a steady development of the community college concept in Argentina reflected in documentation of events, conceptual writings and legal structures. ^ It was concluded that there is a community college structure beginning to emerge that, so far, in broad outline, follows the structure developed in the United States. It is anticipated however, that future developments will include conceptual aspects to the model reflective of Argentina. ^

Comparative study of periphyton community structure in long and short-hydroperiod Everglades marshes

The Florida Everglades is a mosaic of short and long-hydroperiod marshes that differ in the depth, duration, and timing of inundation. Algae are important primary producers in widespread Everglades’ periphyton mats, but relationships of algal production and community structure to hydrologic variability are poorly understood. We quantified differences in algal biomass and community structure between periphyton mats in 5 short and 6 long-hydroperiod marshes in Everglades National Park (ENP) in October 2000. We related differences to water depth and total phosphorus (TP) concentration in the water, periphyton and soils. Long and short-hydroperiod marshes differed in water depth (73 cm vs. 13 cm), periphyton TP concentrations (172μg g−1 vs. 107 μg g−1, respectively) and soil TP (284 μg g−1 vs. 145 μg g−1). Periphyton was abundant in both marshes, with short-hydroperiod sites having greater biomass than long-hydroperiod sites (2936 vs. 575 grams ash-free dry mass m−2). A total of 156 algal taxa were identified and separated into diatom (68 species from 21 genera) and “soft algae” (88 non-diatom species from 47 genera) categories for further analyses. Although diatom total abundance was greater in long-hydroperiod mats, diatom species richness was significantly greater in short- hydroperiod periphyton mats (62 vs. 47 diatom taxa). Soft algal species richness was greater in long-hydroperiod sites (81 vs. 67 soft algae taxa). Relative abundances of individual taxa were significantly different among the two site types, with soft algal distributions being driven by water depth, and diatom distributions by water depth and TP concentration in the water and periphyton. Periphyton communities differ between short and long-hydroperiod marshes, but because they share many taxa, alterations in hydroperiod could rapidly

Macroinvertebrate community response to eutrophication in an oligotrophic wetland: An in situ mesocosm experiment

Eutrophication from anthropogenic nutrient enrichment is a primary threat to the oligotrophic freshwater marshes of southern Florida. Macrophyte and periphyton response to increased phosphorus (P) has been well documented in both correlative and experimental studies, but the response of consumer communities remains poorly understood, especially in southern marl prairies. We conducted a P-loading experiment in in situ mesocosms in Taylor Slough, Everglades National Park, and examined the response of macroinvertebrate communities. Mesocosms at two sites were loaded weekly with P at four levels: control (0 g P/m2/yr), low (0.2 g P/m2/yr), intermediate (0.8 g P/m2/yr), and high (3.2 g P/m2/ yr). After ∼2 yrs of P-loading, macroinvertebrates were sampled using periphyton mat and benthic floc cores. Densities of macroinvertebrate taxa (no./g AFDM) were two to 16 times higher in periphyton mats than benthic floc. Periphyton biomass decreased with enrichment at one site, and periphyton was absent from many intermediate and all high P treatments at both sites. Total macroinvertebrate density in periphyton mats increased with intermediate P loads, driven primarily by chironomids and nematodes. Conversely, total macroinvertebrate density in benthic floc decreased with enrichment, driven primarily by loss of chironomids and ceratopogonids (Dasyhelea). This study suggests that macroinvertebrate density increases with enrichment until periphyton mats are lost, after which it decreases, and mat infauna fail to move into benthic substrates in response to mat loss. These results were noted at nutrient levels too low to yield anoxia, and we believe that the decrease of macroinvertebrate density resulted from a loss of habitat. This work illustrates the importance of periphyton mats as habitat for macroinvertebrates in the Everglades. This study also indicates that in this system, macroinvertebrate sampling should be designed to target periphyton mats or conducted with special attention to inclusion of substrates relative to their coverage.

A retrospective-longitudinal examination of the relationship between apportionment of seat time in community-college algebra courses and student academic performance

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Disturbance Driven Colony Fragmentation as a Driver of a Coral Disease Outbreak

In September of 2010, Brewer's Bay reef, located in St. Thomas (U.S. Virgin Islands), was simultaneously affected by abnormally high temperatures and the passage of a hurricane that resulted in the mass bleaching and fragmentation of its coral community. An outbreak of a rapid tissue loss disease among coral colonies was associated with these two disturbances. Gross lesion signs and lesion progression rates indicated that the disease was most similar to the Caribbean coral disease white plague type 1. Experiments indicated that the disease was transmissible through direct contact between colonies, and five-meter radial transects showed a clustered spatial distribution of disease, with diseased colonies being concentrated within the first meter of other diseased colonies. Disease prevalence and the extent to which colonies were bleached were both significantly higher on unattached colony fragments than on attached colonies, and disease occurred primarily on fragments found in direct contact with sediment. In contrast to other recent studies, disease presence was not related to the extent of bleaching on colonies. The results of this study suggest that colony fragmentation and contact with sediment played primary roles in the initial appearance of disease, but that the disease was capable of spreading among colonies, which suggests secondary transmission is possible through some other, unidentified mechanism.

Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients

Chronic bronchopulmonary bacterial infections remain the most common cause of morbidity and mortality among patients with cystic fibrosis (CF). Recent community sequencing work has now shown that the bacterial community in the CF lung is polymicrobial. Identifying bacteria in the CF lung through sequencing can be costly and is not practical for many laboratories. Molecular techniques such as terminal restriction fragment length polymorphism or amplicon length heterogeneity-polymerase chain reaction (LH-PCR) can provide many laboratories with the ability to study CF bacterial communities without costly sequencing. The aim of this study was to determine if the use of LH-PCR with multiple hypervariable regions of the 16S rRNA gene could be used to identify organisms found in sputum DNA. This work also determined if LH-PCR could be used to observe the dynamics of lung infections over a period of time. Nineteen samples were analysed with the V1 and the V1_V2 region of the 16S rRNA gene. Based on the amplicon size present in the V1_V2 region, Pseudomonas aeruginosa was confirmed to be in all 19 samples obtained from the patients. The V1 region provided a higher power of discrimination between bacterial profiles of patients. Both regions were able to identify trends in the bacterial population over a period of time. LH profiles showed that the CF lung community is dynamic and that changes in the community may in part be driven by the patient's antibiotic treatment. LH-PCR is a tool that is well suited for studying bacterial communities and their dynamics.

Global Mental Health: Five Areas for Value-Driven Training Innovation.

OBJECTIVE: In the field of global mental health, there is a need for identifying core values and competencies to guide training programs in professional practice as well as in academia. This paper presents the results of interdisciplinary discussions fostered during an annual meeting of the Society for the Study of Psychiatry and Culture to develop recommendations for value-driven innovation in global mental health training. METHODS: Participants (n = 48), who registered for a dedicated workshop on global mental health training advertised in conference proceedings, included both established faculty and current students engaged in learning, practice, and research. They proffered recommendations in five areas of training curriculum: values, competencies, training experiences, resources, and evaluation. RESULTS: Priority values included humility, ethical awareness of power differentials, collaborative action, and "deep accountability" when working in low-resource settings in low- and middle-income countries and high-income countries. Competencies included flexibility and tolerating ambiguity when working across diverse settings, the ability to systematically evaluate personal biases, historical and linguistic proficiency, and evaluation skills across a range of stakeholders. Training experiences included didactics, language training, self-awareness, and supervision in immersive activities related to professional or academic work. Resources included connections with diverse faculty such as social scientists and mentors in addition to medical practitioners, institutional commitment through protected time and funding, and sustainable collaborations with partners in low resource settings. Finally, evaluation skills built upon community-based participatory methods, 360-degree feedback from partners in low-resource settings, and observed structured clinical evaluations (OSCEs) with people of different cultural backgrounds. CONCLUSIONS: Global mental health training, as envisioned in this workshop, exemplifies an ethos of working through power differentials across clinical, professional, and social contexts in order to form longstanding collaborations. If incorporated into the ACGME/ABPN Psychiatry Milestone Project, such recommendations will improve training gained through international experiences as well as the everyday training of mental health professionals, global health practitioners, and social scientists.

Climate driven regime shift of a temperate marine ecosystem

Ecosystem reconfigurations arising from climate-driven changes in species distributions are expected to have profound ecological, social, and economic implications. Here we reveal a rapid climate-driven regime shift of Australian temperate reef communities, which lost their defining kelp forests and became dominated by persistent seaweed turfs. After decades of ocean warming, extreme marine heat waves forced a 100-kilometer range contraction of extensive kelp forests and saw temperate species replaced by seaweeds, invertebrates, corals, and fishes characteristic of subtropical and tropical waters. This community-wide tropicalization fundamentally altered key ecological processes, suppressing the recovery of kelp forests.

Climate driven regime shift of a temperate marine ecosystem

Ecosystem reconfigurations arising from climate-driven changes in species distributions are expected to have profound ecological, social, and economic implications. Here we reveal a rapid climate-driven regime shift of Australian temperate reef communities, which lost their defining kelp forests and became dominated by persistent seaweed turfs. After decades of ocean warming, extreme marine heat waves forced a 100-kilometer range contraction of extensive kelp forests and saw temperate species replaced by seaweeds, invertebrates, corals, and fishes characteristic of subtropical and tropical waters. This community-wide tropicalization fundamentally altered key ecological processes, suppressing the recovery of kelp forests.

SURVEILLANCE OF, AND THE IMPACT OF COMMUNITY POLICING ON ARREST-RELATED DEATHS (ARDS): Exploring the surveillance of ARDs and the opportunities to prevent them in the United States

Thesis (Master's)--University of Washington, 2016-08

Long-term changes of the phytoplankton community and biomass in the subtropical shallow Patos Lagoon Estuary, Brazil

Seasonal and interannual changes (1993e2012) of water temperature and transparency, river discharge, salinity, water quality properties, chlorophyll a (chl-a) and the carbon biomass of the main taxonomical phytoplankton groups were evaluated at a shallow station (~2 m) in the subtropical Patos Lagoon Estuary (PLE), Brazil. Large variations in salinity (0e35), due to a complex balance between Patos Lagoon outflow and oceanic inflows, affected significantly other water quality variables and phytoplankton dynamics, masking seasonal and interannual variability. Therefore, salinity effect was filtered out by means of a Generalized Additive Model (GAM). River discharge and salinity had a significant negative relation, with river discharge being highest and salinity lowest during July to October. Diatoms comprised the dominant phytoplankton group, contributing substantially to the seasonal cycle of chl-a showing higher values in austral spring/summer (September to April) and lowest in autumn/winter (May to August). PLE is a nutrient-rich estuary and the phytoplankton seasonal cycle was largely driven by light availability, with few exceptions in winter. Most variables exhibited large interannual variability. When varying salinity effect was accounted for, chl-a concentration and diatom biomass showed less irregularity over time, and significant increasing trends emerged for dinoflagellates and cyanobacteria. Long-term changes in phytoplankton and water quality were strongly related to variations in salinity, largely driven by freshwater discharge influenced by climatic variability, most pronounced for ENSO events. However, the significant increasing trend of the N:P ratio indicates that important environmental changes related to anthropogenic effects are undergoing, in addition to the hydrology in the PLE.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.