831 resultados para Harness making and trade.
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These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.
More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.
The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.
Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.
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The following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?
In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.
Evaluation of the contribution of fisheries and aquaculture to food security in developing countries
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Fish contain important nutrients such as essential fatty acids, iron, zinc, calcium, vitamin A and vitamin C. Production of freshwater fish depends on the strategic application of various management techniques. The demand for fish products has increased beyond the natural supply, resulting in a high pressure on fisheries. Development of aquaculture is necessary for a rapid growth in fish production. A number of constraints hamper the development of aquaculture. Introduction of polyculture technologies in some countries is a way of maximizing production from different levels of the food chain. The roles of women in making fish products available to consumers is frequently over-looked by policy makers. Gender equity in policy-making and management of fisheries and in capacity building is an important issue. Fish production from inland waters and coastal areas can be increased by adopting cage and pen culture systems. Input subsidies and loans to resource poor farmers can boost fish production.
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As part of the Australian Government’s International Climate Change Adaptation Initiative (ICCAI), the Pacific Adaptation Strategy Assistance Program (PASAP) aims to enhance the capacity of partner countries to assess key vulnerabilities and risks, formulate adaptation strategies and plans, mainstream adaptation into decision-making, and inform robust longterm national planning and decision-making in partner countries. The Department of Climate Change and Energy Efficiency contracted University of Queensland (UQ) and University of California, Santa Barbara (UCSB) to lead the project: “Building social and ecological resilience to climate change in Roviana, Solomon Islands” (2010-2012). Under this project The WorldFish Center was subcontracted to undertake outputs 5 and 6 of Objective three: (5) Review of climate change evidence and projections for the study area and (6) Vulnerability and adaptation assessment for the study area. This report addresses the first of these and comprises a desktop review of climate change evidence and projections for the study area.
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For more than 25 years all sea turtle products have been prohibited from international commerce by the 170-member nations of the Convention on International Trade in Endangered Species (CITES). Sea turtles continue to be threatened by direct take (including poaching) and illegal trade despite multi-national protection efforts. Although take may contribute significantly to sea turtle decline, illegal take is difficult to measure since there are few quantified records associated with legal fisheries and fewer still for illegal take (poaching). We can, however, quantify one portion of the illegal sea turtle trade by determining how many illegal products were seized at United States ports of entry over a recent 10-year period. The United States Fish and Wildlife Service (USFWS) oversees the import and export of wildlife and wildlife products, ensuring that wildlife trade complies with United States laws and international treaties. Additionally, the USFWS has legal authority to target suspected illegal wildlife activity through undercover and field investigations. In an effort to assess the scale of illegal sea turtle take and trade, we have conducted a 10-year (1994 – 2003) review of the law enforcement database maintained by the USFWS. This database tracks the number and type of wildlife cases, the quantity of seized products, and the penalties assessed against violators. These data are minimum estimates of the sea turtle products passing through the United States borders, as smuggled wildlife is oftentimes not detected.
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The demand for brooders of Penaeus monodon by the hatcheries, which are solely dependant on wild brooders for their seed production, has resulted in a vigorous fishery and trade for this species, especially along the Visakhapatnam coast. More than three hundred brooders are brought in per day for trading during the peak landing season from December to March every year. The price of gravid brooders has been declining over the years but on an average is about Rs. 30,000 per brooder. The total length of male brooders ranged from 190 to 246 mm during the three years under study and for females it varied between 210 and 330 mm. A specialized methodology for transportation, storage and trade of P. monodon brooders has been evolved over the years at Visakhapatnam Fishing Harbour. Concentrated exploitation of brooders from the wild and presence of pathogens in them makes a strong case for development of specific pathogen free brooders and conservation of wild stock.
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The priorities for the revised National Plan of Action include: strengthening current regulations; improved data collection of landings; identifying breeding and nursery grounds; study of ecology and biology of sharks; improved data acquisition of shark products and trade; and active enforcement at sea, landing sites and markets.
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A large database of 115 triaxial, direct simple shear, and cyclic tests on 19 clays and silts is presented and analysed to develop an empirical framework for the prediction of the mobilization of the undrained shear strength, cu, of natural clays tested from an initially isotropic state of stress. The strain at half the peak undrained strength (γM=2) is used to normalize the shear strain data between mobilized strengths of 0.2cu and 0.8cu. A power law with an exponent of 0.6 is found to describe all the normalized data within a strain factor of 1.75 when a representative sample provides a value for γM=2. Multi-linear regression analysis shows that γM=2 is a function of cu, plasticity index Ip, and initial mean effective stress p′0. Of the 97 stress-strain curves for which cu, Ip, and p′0 were available, the observed values of γM=2 fell within a factor of three of the regression; this additional uncertainty should be acknowledged if a designer wished to limit immediate foundation settlements on the basis of an undrained strength profile and the plasticity index of the clay. The influence of stress history is also discussed. The application of these stress-strain relations to serviceability design calculations is portrayed through a worked example. The implications for geotechnical decision-making and codes of practice are considered.
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Purpose: The paper examines how a number of key themes are introduced in the Masters programme in Engineering for Sustainable Development at Cambridge University through student centred activities. These themes include dealing with complexity, uncertainty, change, other disciplines, people, environmental limits, whole life costs, and trade-offs. Design/methodology/approach: The range of exercises and assignments designed to encourage students to test their own assumptions and abilities to develop competencies in these areas are analysed by mapping the key themes onto the formal activities which all students undertake throughout the core MPhil programme. The paper reviews the range of these activities that are designed to help support the formal delivery of the taught programme. These include residential field courses, role plays, change challenges, games, systems thinking, multi criteria decision making, awareness of literature from other disciplines and consultancy projects. An axial coding approach to the analysis of routine feedback questionnaires drawn from recent years has been used to identify how student’s own awareness develops. Also results of two surveys are presented which tests the students’ perceptions about whether or not the course is providing learning environments to develop awareness and skills in these areas. Findings: Students generally perform well against these tasks with a significant feature being the mutual support they give to each other in their learning. The paper concludes that for students from an engineering background it is an holistic approach to delivering a new way of thinking through a combination of lectures, class activities, assignments, interactions between class members, and access to material elsewhere in the University that enables participants to develop their skills in each of the key themes. Originality /value: The paper provides a reflection on different pedagogical approaches to exploring key sustainable themes and reports students own perceptions of the value of these kinds of activities. Experiences are shared of running a range of diverse learning activities within a professional practice Masters programme.
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Large concrete structures need to be inspected in order to assess their current physical and functional state, to predict future conditions, to support investment planning and decision making, and to allocate limited maintenance and rehabilitation resources. Current procedures in condition and safety assessment of large concrete structures are performed manually leading to subjective and unreliable results, costly and time-consuming data collection, and safety issues. To address these limitations, automated machine vision-based inspection procedures have increasingly been proposed by the research community. This paper presents current achievements and open challenges in vision-based inspection of large concrete structures. First, the general concept of Building Information Modeling is introduced. Then, vision-based 3D reconstruction and as-built spatial modeling of concrete civil infrastructure are presented. Following that, the focus is set on structural member recognition as well as on concrete damage detection and assessment exemplified for concrete columns. Although some challenges are still under investigation, it can be concluded that vision-based inspection methods have significantly improved over the last 10 years, and now, as-built spatial modeling as well as damage detection and assessment of large concrete structures have the potential to be fully automated.
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The large uncertainties in estimates of cropland area in China may have significant implications for major cross-cutting themes of global environmental change-food production and trade, water resources, and the carbon and nitrogen cycles. Many earlier studies have indicated significant under-reporting of cropland area in China from official agricultural census statistics datasets. Space-borne remote sensing analyses provide an alternative and independent approach for estimating cropland area in China. In this study, we report estimates of cropland area from the National Land Cover Dataset (NLCD-96) at the 1:100,000 scale, which was generated by a multi-year National Land Cover Project in China through visual interpretation and digitization of Landsat TM images acquired mostly in 1995 and 1996. We compared the NLCD-96 dataset to another land cover dataset at I-km spatial resolution (the IGBP DIScover dataset version 2.0), which was generated from monthly Advanced Very High Resolution Radiometer (AVHRR)-derived Normalized Difference Vegetation Index (NDVI) from April, 1992 to March, 1993. The data comparison highlighted the limitation and uncertainty of cropland area estimates from the DIScover dataset. (C) 2003 Elsevier Science B.V. All rights reserved.
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Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.
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Grattan, J. Pollution and paradigms: Lessons from Icelandic volcanism for continental flood basalt studies. Lithos. 2005. 79 pp 343-353
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A neural model is presented that explains how outcome-specific learning modulates affect, decision-making and Pavlovian conditioned approach responses. The model addresses how brain regions responsible for affective learning and habit learning interact, and answers a central question: What are the relative contributions of the amygdala and orbitofrontal cortex to emotion and behavior? In the model, the amygdala calculates outcome value while the orbitofrontal cortex influences attention and conditioned responding by assigning value information to stimuli. Model simulations replicate autonomic, electrophysiological, and behavioral data associated with three tasks commonly used to assay these phenomena: Food consumption, Pavlovian conditioning, and visual discrimination. Interactions of the basal ganglia and amygdala with sensory and orbitofrontal cortices enable the model to replicate the complex pattern of spared and impaired behavioral and emotional capacities seen following lesions of the amygdala and orbitofrontal cortex.