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.

Improving co-development through process alignment

There has been a recent surge of enthusiasm icithin tlie automotive industry to build closer supplier relationships idthin the area of product development. One concept deemed central to these relationships is the alignment of development processes between the collaborating organizations, an area that is expanded upon idthin this paper. We suggest that synchronization can be achieved through the four key steps of process standardization, knowledge sliaring, alignment of existing practices, and continuous elimination oftcaste idthin the joint development cycles. A methodology for implementing these stages is presented along idth the underlying prindples on which it is based - the importance of joint teamworking and multi-company involvement idthin the alignment process is higlilighted. © MCB University Press.

An analysis of factors improving technology roadmap credibility: A communications theory assessment of roadmapping processes

In recent years, many industrial firms have been able to use roadmapping as an effective process methodology for projecting future technology and for coordinating technology planning and strategy. Firms potentially realize a number of benefits in deploying technology roadmapping (TRM) processes. Roadmaps provide information identifying which new technologies will meet firms' future product demands, allowing companies to leverage R&D investments through choosing appropriately out of a range of alternative technologies. Moreover, the roadmapping process serves an important communication tool helping to bring about consensus among roadmap developers, as well as between participants brought in during the development process, who may communicate their understanding of shared corporate goals through the roadmap. However, there are few conceptual accounts or case studies have made the argument that roadmapping processes may be used effectively as communication tools. This paper, therefore, seeks to elaborate a theoretical foundation for identifying the factors that must be considered in setting up a roadmap and for analyzing the effect of these factors on technology roadmap credibility as perceived by its users. Based on the survey results of 120 different R&D units, this empirical study found that firms need to explore further how they can enable frequent interactions between the TRM development team and TRM participants. A high level of interaction will improve the credibility of a TRM, with communication channels selected by the organization also positively affecting TRM credibility. © 2011 Elsevier Inc.

Improving effects of huperzine A on spatial working memory in aged monkeys and young adult monkeys with experimental cognitive impairment

Our previous studies demonstrated that huperzine A, a reversible and selective acetylcholinesterase inhibitor, exerts beneficial effects on memory deficits in various rodent models of amnesia. To extend the antiamnesic action of huperzine A to nonhuman primates, huperzine A was evaluated for its ability to reverse the deficits in spatial memory produced by scopolamine in young adult monkeys or those that are naturally occurring in aged monkeys using a delayed-response task. Scopolamine, a muscarinic receptor antagonist, dose dependently impaired performance with the highest dose (0.03 mg/kg, i.m.) producing a significant reduction in choice accuracy in young adult monkeys. The delayed performance changed from an average of 26.8/30 trials correct on saline control to an average of 20.2/30 trials correct after scopolamine administration. Huperzine A (0.01-0.1 mg/kg, i.m.) significantly reversed deficits induced by scopolamine in young adult monkeys on a delayed-response task; performance after an optimal dose (0.1 mg/kg) averaged 25.0/30 correct. In four aged monkeys, huperzine A (0.001-0.01 mg/kg, i.m.) significantly increased choice accuracy from 20.5/30 on saline control to 25.2/30 at the optimal dose (0.001 mg/kg for two monkeys and 0.01 mg/kg for the other two monkeys). The beneficial effects of huperzine A on delayed-response performance were long lasting; monkeys remained improved for about 24 h after a single injection of huperzine A. This study extended the findings that huperzine A improves the mnemonic performance requiring working memory in monkeys, and suggests that huperzine A may be a promising agent for clinical therapy of cognitive impairments in patients with Alzheimer's disease.

Improving data quality in DSM modelling: A structural comparison approach

The Dependency Structure Matrix (DSM) has proved to be a useful tool for system structure elicitation and analysis. However, as with any modelling approach, the insights gained from analysis are limited by the quality and correctness of input information. This paper explores how the quality of data in a DSM can be enhanced by elicitation methods which include comparison of information acquired from different perspectives and levels of abstraction. The approach is based on comparison of dependencies according to their structural importance. It is illustrated through two case studies: creation of a DSM showing the spatial connections between elements in a product, and a DSM capturing information flows in an organisation. We conclude that considering structural criteria can lead to improved data quality in DSM models, although further research is required to fully explore the benefits and limitations of our proposed approach.

Improving communication in design: Recommendations from the literature

Communication permeates every aspect of an engineer's work-from clarifying product specifications to shaping social ties. This paper offers an overview of recommendations from literature to improve communication within and among engineering teams. We assume communication problems are often the outcome of underlying factors and that it is fruitful to study and improve these influences. Having been empirically elicited in prior research, 24 factors considered in this paper include, e.g., availability of information about product specifications, roles and responsibilities, and overview of sequence of tasks. To improve these factors in order to enable effective communication, this paper collates more than hundred recommendations from journal articles and textbooks published in the fields of engineering design, management science, sociology, and psychology. Recommendations include, for example, identify priorities through risk and bottleneck analysis, give clear descriptions and role expectations, and employ effective process modeling tools. Contributions of this paper are a list of recommendations for industry practitioners and an effort-benefit evaluation of individual recommendations. Copyright © 2002-2012 The Design Society. All rights reserved.

Improving reverberant VTS for hands-free robust speech recognition

Model-based approaches to handling additive background noise and channel distortion, such as Vector Taylor Series (VTS), have been intensively studied and extended in a number of ways. In previous work, VTS has been extended to handle both reverberant and background noise, yielding the Reverberant VTS (RVTS) scheme. In this work, rather than assuming the observation vector is generated by the reverberation of a sequence of background noise corrupted speech vectors, as in RVTS, the observation vector is modelled as a superposition of the background noise and the reverberation of clean speech. This yields a new compensation scheme RVTS Joint (RVTSJ), which allows an easy formulation for joint estimation of both additive and reverberation noise parameters. These two compensation schemes were evaluated and compared on a simulated reverberant noise corrupted AURORA4 task. Both yielded large gains over VTS baseline system, with RVTSJ outperforming the previous RVTS scheme. © 2011 IEEE.

Improving model quality through computer controlled saturation

In dynamic centrifuge modelling, fluids with enhanced viscosity are often used to correct for the discrepancy in time scaling. However, great care must be taken when using a high viscosity fluid that hydraulic gradients during saturation do not become high enough to cause excessive model disturbance. This paper introduces the CAM-Sat system which aims to improve the saturation process by continually controlling the fluid flow into the model, limiting it to rates low enough to avoid model disturbance. A new method for measuring the fluid flow rate is then described, and its implementation & improvement to the system is discussed. © 2010 Taylor & Francis Group, London.

Improving statistical machine translation by classifying and generalizing inflected verb forms

This paper introduces a rule-based classification of single-word and compound verbs into a statistical machine translation approach. By substituting verb forms by the lemma of their head verb, the data sparseness problem caused by highly-inflected languages can be successfully addressed. On the other hand, the information of seen verb forms can be used to generate new translations for unseen verb forms. Translation results for an English to Spanish task are reported, producing a significant performance improvement.

Phrase linguistic classification and generalization for improving statistical machine translation

In this paper a method to incorporate linguistic information regarding single-word and compound verbs is proposed, as a first step towards an SMT model based on linguistically-classified phrases. By substituting these verb structures by the base form of the head verb, we achieve a better statistical word alignment performance, and are able to better estimate the translation model and generalize to unseen verb forms during translation. Preliminary experiments for the English - Spanish language pair are performed, and future research lines are detailed. © 2005 Association for Computational Linguistics.

Improving Pothole Recognition through Vision Tracking for Automated Pavement Assessment

Pavement condition assessment is essential when developing road network maintenance programs. In practice, pavement sensing is to a large extent automated when regarding highway networks. Municipal roads, however, are predominantly surveyed manually due to the limited amount of expensive inspection vehicles. As part of a research project that proposes an omnipresent passenger vehicle network for comprehensive and cheap condition surveying of municipal road networks this paper deals with pothole recognition. Existing methods either rely on expensive and high-maintenance range sensors, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In our previous work we created a pothole detection method for pavement images. In this paper we present an improved recognition method for pavement videos that incrementally updates the texture signature for intact pavement regions and uses vision tracking to track detected potholes. The method is tested and results demonstrate its reasonable efficiency.

Improving LVCSR system combination using neural network language model cross adaptation

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. The standard approach involves only cross adapting acoustic models. To fully exploit the complimentary features among sub-systems, language model (LM) cross adaptation techniques can be used. Previous research on multi-level n-gram LM cross adaptation is extended to further include the cross adaptation of neural network LMs in this paper. Using this improved LM cross adaptation framework, significant error rate gains of 4.0%-7.1% relative were obtained over acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. Copyright © 2011 ISCA.

The role of infrastructure in improving human settlements

This paper considers how the provision of integrated household-level infrastructure – particularly water and environmental sanitation (including water supply, sewerage, roads, storm drainage and solid waste management) –can play a leading role in improving the conditions in slum settlements. Around 700 socio-economic interviews were carried out in India and South Africa to investigate an innovative approach called slum networking, which sees the strong correlation between slum locations and drainage paths as an opportunity for improving the wider urban environment. This recognition allows resources to be mobilised locally, thereby removing the need for external aid funding. The evidence from the 700 families shows that communities perceive water and sanitation inputs to be their top priority and are willing to contribute to the costs. If slum upgrading is led with access to integrated water and environmental sanitation at household level with community contributions to the cost of infrastructure, then slum communities subsequently invest considerably greater sums in improved housing and education, with longer term contributions to poverty alleviation, improvements in health and literacy and an increase in disposable incomes.