An Internet for Water: Connecting Texas Water Data

The Connecting Texas Water Data Workshop brought together experts representative of Texas’ water sectors to engage in the identification of critical water data needs and to discuss the design of a data system that facilitates access to and the use of public water data in Texas. Workshop participants identified “use cases” that list data gaps, needs, and uses for water data and answered questions on who needs data, what data do they need, in what form do they need the data, and what decisions need to be made about water in Texas. They described desires for future water data management and access practices and articulated key attributes of a comprehensive, open access, public water data information system. Next, steps were described to include a subset of workshop participants meeting regularly to further define the goals of a Texas public water data hub, develop a strawman of the hub’s structure, characterize several use cases, and facilitate development of pilot projects that demonstrate the value of connected public water data for improved decision making

LEAF: Logger for ecological and atmospheric factors

The fields of meteorology, surface- and groundwater hydrology, and forestry are often decoupled despite the fact that they occur simultaneously at the intersection of living systems and the physical environment. In this work, we describe a system that allows concurrent measurement of canopy throughfall, transpiration, air temperature, pressure, and humidity at multiple heights, in addition to soil moisture and several surface water parameters. LEAF is designed to be generalizable to many other hydrology and meteorology applications, and is modular such that it is easily adaptable for use with additional, diverse environmental monitoring sensors. This low-cost, light-weight, solar-powered system is capable of simultaneous streaming telemetry as well as local data logging via SD card.Office of the VP for Researc

Merging spatially variant physical process models under an optimized systems dynamics framework.

The complexity of water resource issues, its interconnectedness to other systems, and the involvement of competing stakeholders often overwhelm decision-makers and inhibit the creation of clear management strategies. While a range of modeling tools and procedures exist to address these problems, they tend to be case specific and generally emphasize either a quantitative and overly analytic approach or present a qualitative dialogue-based approach lacking the ability to fully explore consequences of different policy decisions. The integration of these two approaches is needed to drive toward final decisions and engender effective outcomes. Given these limitations, the Computer Assisted Dispute Resolution system (CADRe) was developed to aid in stakeholder inclusive resource planning. This modeling and negotiation system uniquely addresses resource concerns by developing a spatially varying system dynamics model as well as innovative global optimization search techniques to maximize outcomes from participatory dialogues. Ultimately, the core system architecture of CADRe also serves as the cornerstone upon which key scientific innovation and challenges can be addressed

A framework for characterising and evaluating the effectiveness of environmental modelling

Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures

Effective modeling for integrated water resource management: a guide to contextual practices by phases and steps and future opportunities

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management. © 2019 Elsevier Lt

An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models

Understanding the interactions between natural processes and human activities poses major challenges as it requires the integration of models and data across disparate disciplines. It typically takes many months and even years to create valid end-to-end simulations as different models need to be configured in consistent ways and generate data that is usable by other models. MINT is a novel framework for model integration that captures extensive knowledge about models and data and aims to automatically compose them together. MINT guides a user to pose a well-formed modeling question, select and configure appropriate models, find and prepare appropriate datasets, compose data and models into end-to-end workflows, run the simulations, and visualize the results. MINT currently includes hydrology, agriculture, and socioeconomic models.Office of the VP for Researc

Better Palliative Care for people with a Dementia: Summary of InterdisciplinaryWorkshop Highlighting Current Gaps and Recommendations for Future Research

Background: Dementia is the most common neurological disorder worldwide and is a life-limiting condition, but very often is not recognised as such. People with dementia, and their carers, have been shown to have palliative care needs equal in extent to those of cancer patients. However, many people with advanced dementia are not routinely being assessed to determine their palliative care needs, and it is not clear why this is so. Main body: An interdisciplinary workshop on "Palliative Care in Neurodegeneration, with a focus on Dementia", was held in Cork, Ireland, in May 2016. The key aim of this workshop was to discuss the evidence base for palliative care for people with dementia, to identify 'gaps' for clinical research, and to make recommendations for interdisciplinary research practice. To lead the discussion throughout the day a multidisciplinary panel of expert speakers were brought together, including both researchers and clinicians from across Ireland and the UK. Targeted invitations were sent to attendees ensuring all key stakeholders were present to contribute to discussions. In total, 49 experts representing 17 different academic and practice settings, attended. Key topics for discussion were pre-selected based on previously identified research priorities (e.g. James Lind Alliance) and stakeholder input. Key discussion topics included: i. Advance Care Planning for people with Dementia; ii. Personhood in End-of-life Dementia care; iii. Topics in the care of advanced dementia at home. These topics were used as a starting point, and the ethos of the workshop was that the attendees could stimulate discussion and debate in any relevant area, not just the key topics, summarised under iv. Other priorities. Conclusions: The care experienced by people with dementia and their families has the potential to be improved; palliative care frameworks may have much to offer in this endeavour. However, a solid evidence base is required to translate palliative care into practice in the context of dementia. This paper presents suggested research priorities as a starting point to build this evidence base. An interdisciplinary approach to research and priority setting is essential to develop actionable knowledge in this area

Intelligent Systems for Geosciences: An Essential Research Agenda

A research agenda for intelligent systems that will result in fundamental new capabilities for understanding the Earth system. Many aspects of geosciences pose novel problems for intelligent systems research. Geoscience data is challenging because it tends to be uncertain, intermittent, sparse, multiresolution, and multiscale. Geosciences processes and objects often have amorphous spatiotemporal boundaries. The lack of ground truth makes model evaluation, testing, and comparison difficult. Overcoming these challenges requires breakthroughs that would significantly transform intelligent systems, while greatly benefitting the geosciences in turn

Engaging in Health Behaviors to Lower Risk for Breast Cancer Recurrence

Purpose While post-treatment breast cancer survivors face up to twice the cancer risk of the general population, modifiable health behaviors may somewhat reduce this risk. We sought to better understand health behaviors that early stage breast cancer survivors engage in to reduce recurrence risk. Methods Data came from a cross-sectional multi-site survey of 186 early-stage breast cancer survivors who received genomic testing for breast cancer recurrence risk (Oncotype DX) during their clinical care. Study outcomes were meeting health behavior recommendations (daily fruit and vegetable intake, regular physical activity, and having a healthy body mass index (BMI)). Results Approximately three-quarters of survivors we surveyed believed the 3 behaviors might reduce their cancer risk but many did not engage in these behaviors for this purpose: 62% for BMI, 36% for fruit and vegetable consumption, and 37% for physical activity. Survivors with higher recurrence risk, as indicated by their genomic test results, were no more likely to meet any of the three health behavior recommendations. Adherence to health behavior recommendations was higher for women who were white, college-educated, and had higher incomes. Conclusions Many nonadherent breast cancer survivors wish to use these behavioral strategies to reduce their risk for recurrence, suggesting an important opportunity for intervention. Improving BMI, which has the largest association with cancer risk, is an especially promising target

A Phase 1 Trial of MSP2-C1, a Blood-Stage Malaria Vaccine Containing 2 Isoforms of MSP2 Formulated with Montanide® ISA 720

Background: In a previous Phase 1/2b malaria vaccine trial testing the 3D7 isoform of the malaria vaccine candidate Merozoite surface protein 2 (MSP2), parasite densities in children were reduced by 62%. However, breakthrough parasitemias were disproportionately of the alternate dimorphic form of MSP2, the FC27 genotype. We therefore undertook a dose-escalating, double-blinded, placebo-controlled Phase 1 trial in healthy, malaria-naïve adults of MSP2-C1, a vaccine containing recombinant forms of the two families of msp2 alleles, 3D7 and FC27 (EcMSP2-3D7 and EcMSP2-FC27), formulated in equal amounts with Montanide® ISA 720 as a water-in-oil emulsion. Methodology/Principal Findings: The trial was designed to include three dose cohorts (10, 40, and 80 μg), each with twelve subjects receiving the vaccine and three control subjects receiving Montanide® ISA 720 adjuvant emulsion alone, in a schedule of three doses at 12-week intervals. Due to unexpected local reactogenicity and concern regarding vaccine stability, the trial was terminated after the second immunisation of the cohort receiving the 40 μg dose; no subjects received the 80 μg dose. Immunization induced significant IgG responses to both isoforms of MSP2 in the 10 μg and 40 μg dose cohorts, with antibody levels by ELISA higher in the 40 μg cohort. Vaccine-induced antibodies recognised native protein by Western blots of parasite protein extracts and by immunofluorescence microscopy. Although the induced anti-MSP2 antibodies did not directly inhibit parasite growth in vitro, IgG from the majority of individuals tested caused significant antibody-dependent cellular inhibition (ADCI) of parasite growth. Conclusions/Significance: As the majority of subjects vaccinated with MSP2-C1 developed an antibody responses to both forms of MSP2, and that these antibodies mediated ADCI provide further support for MSP2 as a malaria vaccine candidate. However, in view of the reactogenicity of this formulation, further clinical development of MSP2-C1 will require formulation of MSP2 in an alternative adjuvant. Trial Registration: Australian New Zealand Clinical Trials Registry 12607000552482