How good are Bayesian belief networks for environmental management? A test with data from an agricultural river catchment

1. The ecological health of rivers worldwide continues to decline despite increasing effort and investment in river science and management. Bayesian belief networks (BBNs) are increasingly being used as a mechanism for decision-making in river management because they provide a simple visual framework to explore different management scenarios for the multiple stressors that impact rivers. However, most applications of BBN modelling to resource management use expert knowledge and/or limited real data, and fail to accurately assess the ability of the model to make predictions. 2. We developed a BBN to model ecological condition in a New Zealand river using field/GIS data (from multiple rivers), rather than expert opinion, and assessed its predictive ability on an independent dataset. The developed BBN performed moderately better than a number of other modelling techniques (e.g., artificial neural networks, classification trees, random forest, logistic regression), although model construction was more time3consuming. Thus the predictive ability of BBNs is (in this case at least) on a par with other modelling methods but the approach is distinctly better for its ability to visually present the data linkages, issues and potential outcomes of management options in real time. 3. The BBN suggested management of habitat quality, su ch as riparian planting, along with the current management focus on limiting nutrient leaching from agricultural land may be most effective in improving ecological condition. 4. BBNs can be a powerful and accurate method of effectively portraying the multiple interacting drivers of environmental condition in an easily understood manner. However, most BBN applications fail to appropriately test the model fit prior to use. We believe this lack of testing may seriously undermine their long-term effectiveness in resource management, and recommend that BBNs should be used in conjunction with some measure of uncertainty about model predictions. We have demonstrated this for a BBN of ecological condition in a New Zealand river, shown that model fit is better than that for other modelling techniques, and that improving habitat would be equally effective to reducing nutrients to improve ecological condition

Patterns and correlates of claims for brown bear damage on a continental scale

Wildlife damage to human property threatens human-wildlife coexistence. Conflicts arising from wildlife damage in intensively managed landscapes often undermine conservation efforts, making damage mitigation and compensation of special concern for wildlife conservation. However, the mechanisms underlying the occurrence of damage and claims at large scales are still poorly understood. Here, we investigated the patterns of damage caused by brown bears Ursus arctos and its ecological and socio-economic correlates at a continental scale. We compiled information about compensation schemes across 26 countries in Europe in 2005-2012 and analysed the variation in the number of compensated claims in relation to (i) bear abundance, (ii) forest availability, (iii) human land use, (iv) management practices and (v) indicators of economic wealth. Most European countries have a posteriori compensation schemes based on damage verification, which, in many cases, have operated for more than 30 years. On average, over 3200 claims of bear damage were compensated annually in Europe. The majority of claims were for damage to livestock (59%), distributed throughout the bear range, followed by damage to apiaries (21%) and agriculture (17%), mainly in Mediterranean and eastern European countries. The mean number of compensated claims per bear and year ranged from 0·1 in Estonia to 8·5 in Norway. This variation was not only due to the differences in compensation schemes; damage claims were less numerous in areas with supplementary feeding and with a high proportion of agricultural land. However, observed variation in compensated damage was not related to bear abundance. Synthesis and applications. Compensation schemes, management practices and human land use influence the number of claims for brown bear damage, while bear abundance does not. Policies that ignore this complexity and focus on a single factor, such as bear population size, may not be effective in reducing claims. To be effective, policies should be based on integrative schemes that prioritize damage prevention and make it a condition of payment of compensation that preventive measures are applied. Such integrative schemes should focus mitigation efforts in areas or populations where damage claims are more likely to occur. Similar studies using different species and continents might further improve our understanding of conflicts arising from wildlife damage

Single-pass Nystr\"{o}m approximation in mixed precision

Low rank matrix approximations appear in a number of scientific computing applications. We consider the Nystr\"{o}m method for approximating a positive semidefinite matrix $A$. The computational cost of its single-pass version can be decreased by running it in mixed precision, where the expensive products with $A$ are computed in a precision lower than the working precision. We bound the extra finite precision error which is compared to the error of the Nystr\"{o}m approximation in exact arithmetic and develop a heuristic to identify when the approximation quality is not affected by the low precision computation. Further, the mixed precision Nystr\"{o}m method can be used to inexpensively construct a limited memory preconditioner for the conjugate gradient method. We bound the condition number of the resulting preconditioned coefficient matrix, and experimentally show that such a preconditioner can be effective

Monitoring Gearbox Using a Wireless Temperature Node Powered by Thermal Energy Harvesting Module

Condition monitoring (CM) of gearbox is a crucial activity due to its importance in power transmission for many industrial applications. Monitoring temperature is an effective mean to collect useful information about the healthy conditions of the gearbox. This study investigates the use of a novel wireless temperature node to monitor and diagnose different faults on a gearbox transmission system under different conditions. The wireless temperature node was fabricated with a novel feature that it is supplied by a thermoelectric generator module mounted on the gearbox house to be monitored so that the measurement system avoids the shortage of using a wired power sources or the requirement for recharging or changing batteries. Moreover, the temperatures from lubricating oils and housing are modelled empirically to implement a model based detection. The results show that this monitoring approach allows a number of common faults: tooth breakage, oil shortage, and shaft misalignment to be separated under different loads, which demonstrates the outstanding performance of the proposed system and thus suitable for online and automated condition monitoring

Extension of Intersection Method for Multi-Objective Optimization in Case of Interval Number and its Application

This paper aims to develop the extension of intersection method for multi-objective optimization under condition of interval number. Based on the linear correlation of partial favourable probability and the corresponding performance indicator, and the assumption of uniform distribution of the actual value of performance indicator within the range of its lower and upper limits in case of interval number, it derives that the actual partial favourable probability of a performance indicator is the arithmetic mean value of the partial favourable probabilities of the arithmetic mean value and the variation value of the interval index of the corresponding performance indicator for each candidate, or their desired sum. Furthermore, according to the rule of algorithm for the total favourable probability quantitatively, all candidates are ranked according to their total favourable probabilities to complete the multi- objective optimization in case of interval number. As applications, the quantitative assessments of multi-criteria selections for effective dwelling house walls, project managers and contractor for construction works are given in detail, satisfied results are obtained

Optical self-cooling of a membrane oscillator in a cavity optomechanical experiment at room temperature

Thermal noise is a major obstacle to observing quantum behavior in macroscopic systems. To mitigate its effect, quantum optomechanical experiments are typically performed in a cryogenic environment. However, this condition represents a considerable complication in the transition from fundamental research to quantum technology applications. It is therefore interesting to explore the possibility of achieving the quantum regime in room temperature experiments. In this work we test the limits of sideband cooling vibration modes of a SiN membrane in a cavity optomechanical experiment. We obtain an effective temperature of a few mK, corresponding to a phononic occupation number of around 100. We show that further cooling is prevented by the excess classical noise of our laser source, and we outline the road toward the achievement of ground state coolin

A theory and model for the evolution of software services

Software services are subject to constant change and variation. To control service development, a service developer needs to know why a change was made, what are its implications and whether the change is complete. Typically, service clients do not perceive the upgraded service immediately. As a consequence, service-based applications may fail on the service client side due to changes carried out during a provider service upgrade. In order to manage changes in a meaningful and effective manner service clients must therefore be considered when service changes are introduced at the service provider's side. Otherwise such changes will most certainly result in severe application disruption. Eliminating spurious results and inconsistencies that may occur due to uncontrolled changes is therefore a necessary condition for the ability of services to evolve gracefully, ensure service stability, and handle variability in their behavior. Towards this goal, this work presents a model and a theoretical framework for the compatible evolution of services based on well-founded theories and techniques from a number of disparate fields.