The potential of community fish refuges (CFRs) in rice field agro-ecosystems for improving food and nutrition security in the Tonle Sap region

The fisheries sector in Cambodia contributes 8%–12% to national GDP and 25% - 30% to agricultural GDP, with an estimated 4.5 million people involved in fishing and associated trades. Fish and other aquatic animals are important food sources, contributing an estimated national average of 60% - 70% of total animal protein intake. Of the 2013 total fish production, 550,000 metric tons were harvested from freshwater habitats, of which rice field fisheries and small-scale family fisheries contributed approximately 20%. The productivity and value of rice field fisheries to households in rural Cambodia has been highlighted in a number of previous studies. The Fisheries Administration of the Ministry of Agriculture, Forestry and Fisheries plans to increase productivity from rice field fisheries and aquaculture at an annual rate of 15% to maintain supply for a growing population. This report draws mainly on the baseline and monitoring data from the Rice Field Fisheries Enhancement Project (RFFEP) during its implementation between 2012 and 2014. Reference is also made to the Fish on Farms project to highlight the relative contribution of fish from small-scale aquaculture compared to wild-caught fish.

Building more sustainable solutions in production-consumption systems: the case of food for people with reduced access

In new product development, the ability to integrate different dimensions of sustainability at a value chain level is still a complex, problematic goal. As product-service approaches are increasingly enabling the introduction of more sustainable paths, this paper describes the authors' experience thus far when building insights into conditions for the implementation of integrated solutions in a process of co-development and testing in real life conditions, which are driven by a social need focusing on food for people with reduced access. Throughout this process, which brought together producers, consumers and other stakeholders to design and test industrialised, sustainable solutions, empirical evidence demonstrates feasibility and usefulness of the approach and insight into the conditions for implementing interactive, comprehensive multi-stakeholder processes in real life situations. In addition, results show that the delivery of innovative solutions enabled to offer social added value, economic profits and environmental improvements under specific experimental conditions. © 2006 Elsevier Ltd. All rights reserved.

Responses to seasonal changes in nutrient quality and patchiness of food in a multigroup community of Tibetan macaques at Mt. Emei

Provisioning along pedestrian trails by tourists much increased the nutrient quality and patchiness of food (NqPF)for Tibetan macaques (Macaca thibetana) at Mt Emei in spring and summer. In the habitat at a temperate-subtropical transition zone, the mncaque's NqPF could be ordered in a decreasing rank from spring summer to autumn to winter With the aid of a radio-tracking system, I collected ranging data on a multigroup community in three 70-day periods representing the different seasons in 1991-92, Rank-order correlation on the data show that with the decline of NqPF; the groups tended to increase days away from the trail, their effective range size (ERS) their exclusive area (EA) and the number of days spent in the EA, and reduced their group/community density and the ratio of the overlapped range to the seasonal range (ROR). In icy/snowy winter; the macaques searched for mature leaves slowly and carefully in the largest seasonal range with a considerable portion that was nor used in other seasons. Of the responses, the ROR decreased with the reduction in group/community density; and the ERS was the function of both group size (+) and intergroup rank (-) when favorite food was highly clumped. All above responses were clearly bound to maximize foraging effectiveness and minimize energy expenditure, and their integration in term of changes in time and space leads to better understanding macaque ecological adaptability. Based on this study and previous work on behavioral and physiological factors, I suggest a unifying theory of intergroup interactions. Ir! addition, as the rate of behavioral interactions,was also related to the group density, I Waser's (1976) gas model probably applies to behavioral, as well as spatial, data on intergroup interactions.

I did that! Measuring users' experience of agency in their own actions

Cognitive neuroscience defines the sense of agency as the experience of controlling one's own actions and, through this control, affecting the external world. We believe that the sense of personal agency is a key factor in how people experience interactions with technology. This paper draws on theoretical perspectives in cognitive neuroscience and describes two implicit methods through which personal agency can be empirically investigated. We report two experiments applying these methods to HCI problems. One shows that a new input modality - skin-based interaction - can substantially increase users' sense of agency. The second demonstrates that variations in the parameters of assistance techniques such as predictive mouse acceleration can have a significant impact on users' sense of agency. The methods presented provide designers with new ways of evaluating and refining empowering interaction techniques and interfaces, in which users experience an instinctive sense of control and ownership over their actions. Copyright 2012 ACM.

Detection of large-scale concrete columns for automated bridge inspection

There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.

Large Scale Column Detection for Bridge Inspection

Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

Machine Vision Enhanced Post-Earthquake Inspection and Rapid Loss Estimation

Manual inspection is required to determine the condition of damaged buildings after an earthquake. The lack of available inspectors, when combined with the large volume of inspection work, makes such inspection subjective and time-consuming. Completing the required inspection takes weeks to complete, which has adverse economic and societal impacts on the affected population. This paper proposes an automated framework for rapid post-earthquake building evaluation. Under the framework, the visible damage (cracks and buckling) inflicted on concrete columns is first detected. The damage properties are then measured in relation to the column's dimensions and orientation, so that the column's load bearing capacity can be approximated as a damage index. The column damage index supplemented with other building information (e.g. structural type and columns arrangement) is then used to query fragility curves of similar buildings, constructed from the analyses of existing and on-going experimental data. The query estimates the probability of the building being in different damage states. The framework is expected to automate the collection of building damage data, to provide a quantitative assessment of the building damage state, and to estimate the vulnerability of the building to collapse in the event of an aftershock. Videos and manual assessments of structures after the 2009 earthquake in Haiti are used to test the parts of the framework.

Machine Vision Enhanced Post-earthquake Inspection

Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

An analytical model for guided wave inspection optimization for prismatic structures of any cross section.

This paper presents an analytical modeling technique for the simulation of long-range ultrasonic guided waves in structures. The model may be used to predict the displacement field in a prismatic structure arising from any excitation arrangement and may therefore be used as a tool to design new inspection systems. It is computationally efficient and relatively simple to implement, yet gives accuracy similar to finite element analysis and semi-analytical finite element analysis methods. The model has many potential applications; one example is the optimization of part-circumferential arrays where access to the full circumference of the pipe is restricted. The model has been successfully validated by comparison with finite element solutions. Experimental validation has also been carried out using an array of piezoelectric transducer elements to measure the displacement field arising from a single transducer element in an 88.9-mm-diameter pipe. Good agreement has been obtained between the two models and the experimental data.