GATOR: Requirements capturing of telephony features

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues

Can Blood Flow Restriction En hance the Effectiveness of Electrical Stimulations for Treating Muscle Damage?

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Blood Flow Restricted Electrical Stimulations to Prevent Symptoms of Muscle Damage

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A Knowledge-based Clinical Toxicology Consultant for Diagnosing Multiple Exposures

Objective: This paper presents continued research toward the development of a knowledge-based system for the diagnosis of human toxic exposures. In particular, this research focuses on the challenging task of diagnosing exposures to multiple toxins. Although only 10% of toxic exposures in the United States involve multiple toxins, multiple exposures account for more than half of all toxin-related fatalities. Using simple medical mathematics, we seek to produce a practical decision support system capable of supplying useful information to aid in the diagnosis of complex cases involving multiple unknown substances. Methods: The system is automatically trained using data mining techniques to extract prior probabilities and likelihood ratios from a database managed by the Florida Poison Information Center (FPIC). When supplied with observed clinical effects, the system produces a ranked list of the most plausible toxic exposures. During testing, the system diagnosed toxins at three levels: identifying the substance, identifying the toxin’s major and minor categories, and identifying the toxin’s major category alone. To enable comparison between these three levels, accuracy was calculated as the percentage of exposures correctly identified in top 10% of trained diagnoses. Results: System evaluation utilized a dataset of 8,901 multiple exposure cases and 37,617 single exposure cases. Initial system testing using only multiple exposure cases yielded poor results, with diagnosis accuracies ranging from 18.5-50.1%. Further investigation revealed that the system’s inability to diagnose multiple disorders resulted from insufficient data and that the clinical effects observed in multiple exposures are dominated by a single substance. Including single exposures when training, the system achieved accuracies as high as 83.5% when 2 diagnosing the primary contributors in multiple exposure cases by substance, 86.9% when diagnosing by major and minor categories, and 79.9% when diagnosing by major category alone. Conclusions: Although the system failed to completely diagnose exposures to multiple toxins, the ability to identify the primary contributor in such cases may prove valuable in aiding medical personnel as they seek to diagnose and treat patients. As time passes and more cases are added to the FPIC database, we believe system accuracy will continue to improve, producing a viable decision support system for clinical toxicology

A Knowledge-based Clinical Toxicology Consultant for Diagnosing Single Exposures

Objective: Every year, toxic exposures kill twelve hundred Americans. To aid in the timely diagnosis and treatment of such exposures, this research investigates the feasibility of a knowledge-based system capable of generating differential diagnoses for human exposures involving unknown toxins. Methods: Data mining techniques automatically extract prior probabilities and likelihood ratios from a database managed by the Florida Poison Information Center. Using observed clinical effects, the trained system produces a ranked list of plausible toxic exposures. The resulting system was evaluated using 30,152 single exposure cases. In addition, the effects of two filters for refining diagnosis based on a minimum number of exposure cases and a minimum number of clinical effects were also explored. Results: The system achieved accuracies (calculated as the percentage of exposures correctly identified in top 10% of trained diagnoses) as high as 79.8% when diagnosing by substance and 78.9% when diagnosing by the major and minor categories of toxins. Conclusions: The results of this research are modest, yet promising. At this time, no similar systems are currently in use in the United States and it is hoped that these studies will yield an effective medical decision support system for clinical toxicology

Insect feeds in salmon aquaculture : sociotechnical imagination and responsible story-telling

Unidad de excelencia María de Maeztu CEX2019-000940-MSalmon aquaculture is a growing industry with increasing challenges of feed sustainability and availability. This global sustainability issue has led to calls for novel feeds. Aquafly, a Norwegian research project, has performed small-scale tests using the black soldier fly as an ingredient in salmon diet. However, in order for insect feeds to become a reality on the industrial scale, workable scientific, technical and political solutions have to be envisioned in tandem. In this study, we studied, elicited and assessed sociotechnical imaginaries in the Aquafly research consortium, using the approaches of concomitant ELSA research, the Ethical Matrix and Quantitative Story-Telling. We show how the sociotechnical imaginaries develop together with the scientific trajectory of the project, and how this also affects the assessment of the ethical and environmental impacts of the technology, including issues of food and feed safety and security, fish health and welfare, pollution and efficient use of waste streams. We show how there are intrinsic challenges when dealing with global sustainability issues in the research project. For instance, overcoming the problem of salmon feed scarcity may aggravate the challenges caused by intensive aquaculture. We report the results of a Quantitative Story-Telling exercise that indicates that Aquafly can be seen as part of a larger economy of technological promise, and discuss if and how this critique can be employed and integrated into scientific and technical imagination in a research project, contributing to Responsible Research and Innovation

The effect of monitoring complexity on stakeholder acceptance of CO2 geological storage projects in the US gulf coast region

Environmental monitoring at geologic CO2 storage sites is required by regulations for the purposes of environmental protection and emissions accounting in the case of leakage to surface. However, another very important goal of environmental monitoring is to assure stakeholders that the project is monitored for safety and effectiveness. With current efforts to optimize monitoring for cost-effectiveness, the question remains: will optimization of monitoring approaches degrade stakeholder assurance, or do heavily-instrumented sites communicate higher risk to a stakeholder? We report the results of a stakeholder survey in Gulf Coast states of the US where carbon capture and storage (CCS) is developing quickly. We rely on a 2 by 2 factorial experiment in which we manipulate message complexity (complex v. simple) and social norm (support from scientists v. support from community members). Subjects were randomly assigned to one of four conditions: 1) complex message with scientist support; 2) complex message with community member support; 3) simple message with scientist support; or 4) simple message with community member support. In addition to the experimental stimuli, subjects were also asked about their need for cognition, attitudes toward science and scientists, attitudes about climate change and support for carbon capture and storage (CCS). Our sample is drawn from residents in states bordering the western Gulf of Mexico (Texas, Louisiana, Florida) where CO2 geologic storage is being planned both onshore and offshore. The results offer important implications for public outreach efforts to key stakeholders

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). while the number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently in fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behavior, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause fisheries-induced evolution with effects accumulating over time. Consequently, FIE may alter then utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons, An important reason this is not happening is the lack of an appropriate assessment framework. We therefor describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary outcomes of alternative management options. EvoIA can contribute to the ecosystem approach to fisheries management by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries

Can fisheries-induced evolution shift reference points for fisheries management?

Heino, M., Baulier, L., Boukal, D. S., Ernande, B., Johnston, F. D., Mollet, F. M., Pardoe, H., Therkildsen, N. O., Uusi-Heikkilä, S., Vainikka, A., Arlinghaus, R., Dankel, D. J., Dunlop, E. S., Eikeset, A. M., Enberg, K., Engelhard G. H., Jørgensen, C., Laugen, A. T., Matsumura, S., Nusslé, S., Urbach, D., Whitlock, R., Rijnsdorp, A. D., and Dieckmann, U. 2013. Can fisheries-induced evolution shift reference points for fisheries management? - ICES Journal of Marine Science, 70: 707-721. Biological reference points are important tools for fisheries management. Reference points are not static, but may change when a population's environment or the population itself changes. Fisheries-induced evolution is one mechanism that can alter population characteristics, leading to "shifting” reference points by modifying the underlying biological processes or by changing the perception of a fishery system. The former causes changes in "true” reference points, whereas the latter is caused by changes in the yardsticks used to quantify a system's status. Unaccounted shifts of either kind imply that reference points gradually lose their intended meaning. This can lead to increased precaution, which is safe, but potentially costly. Shifts can also occur in more perilous directions, such that actual risks are greater than anticipated. Our qualitative analysis suggests that all commonly used reference points are susceptible to shifting through fisheries-induced evolution, including the limit and "precautionary” reference points for spawning-stock biomass, Blim and Bpa, and the target reference point for fishing mortality, F0.1. Our findings call for increased awareness of fisheries-induced changes and highlight the value of always basing reference points on adequately updated information, to capture all changes in the biological processes that drive fish population dynamic