Fish demand and supply projections

It has been predicted that the global demand for fish for human consumption will increase by more than 50% over the next 15 years. The FAO has projected that the increase in supply will originate primarily from marine fisheries, aquaculture and to a lesser extent from inland fisheries, but with a commensurate price increase. However, there are constraints to increased production in both marine and inland fisheries, such as overfishing, overexploitation limited potential increase and environmental degradation due to industrialization. The author sees aquaculture as having the greatest potential for future expansion. Aquaculture practices vary depending on culture, environment, society amd sources of fish. Inputs are generally low-cost, ecologically efficient and the majority of aquaculture ventures are small-scale and family operated. In the future, advances in technology, genetic improvement of cultured species, improvement in nutrition, disease management, reproduction control and environmental management are expected along with opportunities for complimentary activities with agriculture, industrial and wastewater linkages. The main constraints to aquaculture are from reduced access to suitable land and good quality water due to pollution and habitat degradation. Aquaculture itself carries minimal potential for aquatic pollution. State participation in fisheries production has not proven to be the best way to promote the fisheries sector. The role of governments is increasingly seen as creating an environment for economic sectors to make an optimum contribution, through support in areas such as infrastructure, research, training and extension and a legal framework. The author feels that a holistic approach integrating the natural and social sciences is called for when fisheries policy is being examined.

Mapping reef fish and the seascape: using acoustics and spatial modeling to guide coastal management

Reef fish distributions are patchy in time and space with some coral reef habitats supporting higher densities (i.e., aggregations) of fish than others. Identifying and quantifying fish aggregations (particularly during spawning events) are often top priorities for coastal managers. However, the rapid mapping of these aggregations using conventional survey methods (e.g., non-technical SCUBA diving and remotely operated cameras) are limited by depth, visibility and time. Acoustic sensors (i.e., splitbeam and multibeam echosounders) are not constrained by these same limitations, and were used to concurrently map and quantify the location, density and size of reef fish along with seafloor structure in two, separate locations in the U.S. Virgin Islands. Reef fish aggregations were documented along the shelf edge, an ecologically important ecotone in the region. Fish were grouped into three classes according to body size, and relationships with the benthic seascape were modeled in one area using Boosted Regression Trees. These models were validated in a second area to test their predictive performance in locations where fish have not been mapped. Models predicting the density of large fish (≥29 cm) performed well (i.e., AUC = 0.77). Water depth and standard deviation of depth were the most influential predictors at two spatial scales (100 and 300 m). Models of small (≤11 cm) and medium (12–28 cm) fish performed poorly (i.e., AUC = 0.49 to 0.68) due to the high prevalence (45–79%) of smaller fish in both locations, and the unequal prevalence of smaller fish in the training and validation areas. Integrating acoustic sensors with spatial modeling offers a new and reliable approach to rapidly identify fish aggregations and to predict the density large fish in un-surveyed locations. This integrative approach will help coastal managers to prioritize sites, and focus their limited resources on areas that may be of higher conservation value.

The use of agreement measures and latent class models to assess the reliability of classifying thermally marked otoliths

Otolith thermal marking is an efficient method for mass marking hatchery-reared salmon and can be used to estimate the proportion of hatchery fish captured in a mixed-stock fishery. Accuracy of the thermal pattern classification depends on the prominence of the pattern, the methods used to prepare and view the patterns, and the training and experience of the personnel who determine the presence or absence of a particular pattern. Estimating accuracy rates is problematic when no secondary marking is available and no error-free standards exist. Agreement measures, such as kappa (κ), provide a relative measure of the reliability of the determinations when independent readings by two readers are available, but the magnitude of κ can be influenced by the proportion of marked fish. If a third reader is used or if two or more groups of paired readings are examined, latent class models can provide estimates of the error rates of each reader. Applications of κ and latent class models are illustrated by a program providing contribution estimates of hatchery-reared chum and sockeye salmon in Southeast Alaska.

MMI training for continuous phoneme recognition on the TIMIT database

This paper reports our experiences with a phoneme recognition system for the TIMIT database which uses multiple mixture continuous density monophone HMMs trained using MMI. A comprehensive set of results are presented comparing the ML and MMI training criteria for both diagonal and full covariance models. These results using simple monophone HMMs show clear performance gains achieved by MMI training, and are comparable to the best reported by others including those which use context-dependent models. In addition, the paper discusses a number of performance and implementation issues which are crucial to successful MMI training.

Factor analysis based VTS and JUD noise estimation and compensation

Model based compensation schemes are a powerful approach for noise robust speech recognition. Recently there have been a number of investigations into adaptive training, and estimating the noise models used for model adaptation. This paper examines the use of EM-based schemes for both canonical models and noise estimation, including discriminative adaptive training. One issue that arises when estimating the noise model is a mismatch between the noise estimation approximation and final model compensation scheme. This paper proposes FA-style compensation where this mismatch is eliminated, though at the expense of a sensitivity to the initial noise estimates. EM-based discriminative adaptive training is evaluated on in-car and Aurora4 tasks. FA-style compensation is then evaluated in an incremental mode on the in-car task. © 2011 IEEE.

Rapid joint speaker and noise compensation for robust speech recognition

For speech recognition, mismatches between training and testing for speaker and noise are normally handled separately. The work presented in this paper aims at jointly applying speaker adaptation and model-based noise compensation by embedding speaker adaptation as part of the noise mismatch function. The proposed method gives a faster and more optimum adaptation compared to compensating for these two factors separately. It is also more consistent with respect to the basic assumptions of speaker and noise adaptation. Experimental results show significant and consistent gains from the proposed method. © 2011 IEEE.

Facilitation of learning induced by both random and gradual visuomotor task variation.

Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between -60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→-30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes.

Perceptual learning, roving and the unsupervised bias

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when . certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervised neural network models can cope easily with roving conditions. What makes humans so inferior compared to these models? As experimental and conceptual work has shown, human perceptual learning is neither supervised nor unsupervised but reward-based learning. Reward-based learning suffers from the so-called unsupervised bias, i.e., to prevent synaptic " drift" , the . average reward has to be exactly estimated. However, this is impossible when two or more stimulus types with different rewards are presented during training (and the reward is estimated by a running average). For this reason, we propose no learning occurs in roving conditions. However, roving hinders perceptual learning only for combinations of similar stimulus types but not for dissimilar ones. In this latter case, we propose that a critic can estimate the reward for each stimulus type separately. One implication of our analysis is that the critic cannot be located in the visual system. © 2011 Elsevier Ltd.

Achieving robust face recognition from video by combining a weak photometric model and a learnt generic face invariant

In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applications. The objective of this work is to recognize faces using video sequences both for training and recognition input, in a realistic, unconstrained setup in which lighting, pose and user motion pattern have a wide variability and face images are of low resolution. The central contribution is an illumination invariant, which we show to be suitable for recognition from video of loosely constrained head motion. In particular there are three contributions: (i) we show how a photometric model of image formation can be combined with a statistical model of generic face appearance variation to exploit the proposed invariant and generalize in the presence of extreme illumination changes; (ii) we introduce a video sequence re-illumination algorithm to achieve fine alignment of two video sequences; and (iii) we use the smoothness of geodesically local appearance manifold structure and a robust same-identity likelihood to achieve robustness to unseen head poses. We describe a fully automatic recognition system based on the proposed method and an extensive evaluation on 323 individuals and 1474 video sequences with extreme illumination, pose and head motion variation. Our system consistently achieved a nearly perfect recognition rate (over 99.7% on all four databases). © 2012 Elsevier Ltd All rights reserved.

Evidence-informed development of engineering practical work: Effecting change through staff and student engagement

This paper discusses innovations in curriculum development in the Department of Engineering at the University of Cambridge as a participant in the Teaching for Learning Network (TFLN), a teaching and learning development initiative funded by the Cambridge-MIT Institute a pedagogic collaboration and brokerage network. A year-long research and development project investigated the practical experiences through which students traditionally explore engineering disciplines, apply and extend the knowledge gained in lectures and other settings, and begin to develop their professional expertise. The research project evaluated current practice in these sessions and developed an evidence-base to identify requirements for new activities, student support and staff development. The evidence collected included a novel student 'practice-value' survey highlighting effective practice and areas of concern, classroom observation of practicals, semi-structured interviews with staff, a student focus group and informal discussions with staff. Analysis of the data identified three potentially 'high-leverage' strategies for improvement: development of a more integrated teaching framework, within which practical work could be contextualised in relation to other learning; a more transparent and integrated conceptual framework where theory and practice were more closely linked; development of practical work more reflective of the complex problems facing professional engineers. This paper sets out key elements of the evidence collected and the changes that have been informed by this evidence and analysis, leading to the creation of a suite of integrated practical sessions carefully linked to other course elements and reinforcing central concepts in engineering, accompanied by a training and support programme for teaching staff.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

Spatial-temporal characteristics of siping urban expansion based on remote sensing and GIS

Based on the RS and GIS methods, Siping city is selected as a study case with four remote sensing images in 25 years. Indices of urban morphology such as fractal dimension and compactness are employed to research the characteristics of urban expansion. Through digital processing and interpreting of the images, the process and characteristics of urban expansion are analysed using urban area change, fractal dimension and compactness. The results showed that there are three terms in this period. It expended fastest in the period of 1979~1991, and in the period of 1992~2001, the emphases on urban redevelopment made it expended slower. And this is in agreement with the Siping Statistical Yearbook. This indicates that the united of metrics of urban morphology and statistical data can be used to satisfactorily describe the process and characteristics of urban expansion. © 2008 IEEE.

Program, abstracts and related documents.

The context: Soil biodiversity and sustainable agriculture; Abstracts - Theme 1: Monitoring and assessment: Bioindicators of soil health: assessment and monitoring for sustainable agriculture; Practical tools to measure soil health and their use by farmers; Biological soil quality from biomass to biodiversity - importance and resilience to management stress and disturbance; Integrated management of plant-parasitic nematodes in maize-bean cropping systems; Microbial quantitative and qualitative changes in soils under different crops and tillage management systems in Brazil; Diversity in the rhizobia associated with Phaseolus vulgaris L: in Ecuador and comparisons with Mexican bean rhizobia; Sistemas integrados ganadería-agricultura en Cuba; Soil macrofauna as bioindicator of soil quality; Biological functioning of cerrado soils; Hydrolysis of fluorescein diacetate as a soil quality indicator in different pasture systems; Soil management and soil macrofauna communities at Embrapa Soybean, Londrina, Brazil; Soil macrofauna in a 24 - year old no-tillage system in Paraná, Brazil; Invertebrate macrofauna of soils inpastures under different forms of management in the cerrado (Brazil); Soil tillage modifies the invertebrate soil macrofauna community; Soil macrofauna in various tillage and land use systems on an oxisols near Londrina, Paraná, Brazil; Interference of agricultural systems on soil macrofauna; Scarab beetle-grub holes in various tillage and crop management systems at Embrapa Soybean, Londrina, Brazil; Biological management of agroecosystems; Soil biota and nutrient dynamics through litterfall in agroforestry system in Rondônia, Amazônia, Brazil; Soil-C stocks and earthworm diversity of native and introduced pastures in Veracruz, Mexico; Theme 2 : Adaptive management: Some thoughts on the effects and implications of the transition from weedy multi-crop to wead-free mono-crop systems in Africa; Towards sustainable agriculture with no-tillage and crop rotation systems in South Brazil; Effect of termites on crusted soil rehabilitation in the Sahel; Management of macrofauna in traditional and conventional agroforestry systems from India with special reference to termites and earthworms; Adaptive management for redeveloping traditional agroecosystems; Conservation and sustainable use of soil biodiversity: learning with master nature!; Convergence of sciences: inclusive technology innovation processes for better integrated crop/vegetation, soil and biodiversity management; Potential for increasing soil biodiversity in agroecosystems; Biological nitrogen fixation and sustainability in the tropics; Theme 3: Research and innovation: Plant flavonoids and cluster roots as modifiers of soil biodiversity; The significance of biological diversity in agricultural soil for disease suppressiveness and nutrient retention; Linking above - and belowground biodiversity: a comparison of agricultural systems; Insect-pests in biologically managed oil and crops: the experience at ICRISAT; Sistemas agricolas micorrizados en Cuba; The effect of velvetbean (Mucuna pruriens) on the tropical earthworm Balanteodrilus pearsei: a management option for maize crops in the Mexican humid tropics; The potential of earthworms and organic matter quality in the rehabilitation of tropical soils; Research and innovation in biological management of soil ecosystems; Application of biodynamic methods in the Egyptian cotton sector; Theme 4: Capacity building and mainstreaming: Soil ecology and biodiversity: a quick scan of its importance for government policy in The Netherlands; Agrotechnological transfer of legume inoculants in Eastern and Southern Africa; Agricultura urbana en Cuba; Soil carbon sequestration for sustaining agricultural production and improving the environment; Conservation and sustainable management of below-ground biodiversity: the TSBF-BGBD network project; The tropical soil biology and fertility institute of CIAT (TSBF); South-South initiative for training and capacity building for the management of soil biology/biodiversity; Strategies to facilititate development and adoption of integrated resource management for sustainable production and productivity improvement; The challenge program on biological nitrogen fixation (CPBNF); Living soil training for farmers: improving knowledge and skills in soil nutrition management; Do we need an inter-governmental panel on land and soil (IPLS)? Protection and sustainable use of biodiversity of soils; Cases Studies -- Plant parasitic nematodes associated with common bean (Phaseolus vulgaris L.) and integrated management approaches; Agrotechnological transfer of legume inoculants in Eastern and Southern Africa; Restoring soil fertility and enhancing productivity in Indian tea plantations with earthworms and organic fertilizers; Managing termites and organic resources to improve soil productivity in the Sahel; Overview and case studies on biological nitrogen fixation: perspectives and limitations; Soil biodiversity and sustainable agriculture: an overview.

Orthodontic and orthopaedic treatment for anterior open bite in children

BackgroundAnterior open bite occurs when there is a lack of vertical overlap of the upper and lower incisors. the aetiology is multifactorial including: oral habits, unfavourable growth patterns, enlarged lymphatic tissue with mouth breathing. Several treatments have been proposed to correct this malocclusion, but interventions are not supported by strong scientific evidence.ObjectivesThe aim of this systematic review was to evaluate orthodontic and orthopaedic treatments to correct anterior open bite in children.Search methodsThe following databases were searched: the Cochrane Oral Health Group's Trials Register (to 14 February 2014); the Cochrane Central Register of Controlled Trials (CENTRAL)(The Cochrane Library 2014, Issue 1); MEDLINE via OVID (1946 to 14 February 2014); EMBASE via OVID (1980 to 14 February 2014); LILACS via BIREME Virtual Health Library (1982 to 14 February 2014); BBO via BIREME Virtual Health Library (1980 to 14 February 2014); and SciELO (1997 to 14 February 2014). We searched for ongoing trials via ClinicalTrials.gov (to 14 February 2014). Chinese journals were handsearched and the bibliographies of papers were retrieved.Selection criteriaAll randomised or quasi-randomised controlled trials of orthodontic or orthopaedic treatments or both to correct anterior open bite in children.Data collection and analysisTwo review authors independently assessed the eligibility of all reports identified.Risk ratios (RRs) and corresponding 95% confidence intervals (CIs) were calculated for dichotomous data. the continuous data were expressed as described by the author.Main resultsThree randomised controlled trials were included comparing: effects of Frankel's function regulator-4 (FR-4) with lip-seal training versus no treatment; repelling-magnet splints versus bite-blocks; and palatal crib associated with high-pull chincup versus no treatment.The study comparing repelling-magnet splints versus bite-blocks could not be analysed because the authors interrupted the treatment earlier than planned due to side effects in four of ten patients.FR-4 associated with lip-seal training (RR = 0.02 (95% CI 0.00 to 0.38)) and removable palatal crib associated with high-pull chincup (RR = 0.23 (95% CI 0.11 to 0.48)) were able to correct anterior open bite.No study described: randomisation process, sample size calculation, there was not blinding in the cephalometric analysis and the two studies evaluated two interventions at the same time. These results should be therefore viewed with caution.Authors' conclusionsThere is weak evidence that the interventions FR-4 with lip-seal training and palatal crib associated with high-pull chincup are able to correct anterior open bite. Given that the trials included have potential bias, these results must be viewed with caution. Recommendations for clinical practice cannot be made based only on the results of these trials. More randomised controlled trials are needed to elucidate the interventions for treating anterior open bite.