Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill sampling criteria balancing exploitation and exploration such as the Expected Hypervolume Improvement. Here we consider Kriging metamodels not only for selecting new points, but as a tool for estimating the whole Pareto front and quantifying how much uncertainty remains on it at any stage of Kriging-based multi-objective optimization algorithms. Our approach relies on the Gaussian process interpretation of Kriging, and bases upon conditional simulations. Using concepts from random set theory, we propose to adapt the Vorob’ev expectation and deviation to capture the variability of the set of non-dominated points. Numerical experiments illustrate the potential of the proposed workflow, and it is shown on examples how Gaussian process simulations and the estimated Vorob’ev deviation can be used to monitor the ability of Kriging-based multi-objective optimization algorithms to accurately learn the Pareto front.

SOMS: SurrOgate MultiStart algorithm for use with nonlinear programming for global optimization

SOMS is a general surrogate-based multistart algorithm, which is used in combination with any local optimizer to find global optima for computationally expensive functions with multiple local minima. SOMS differs from previous multistart methods in that a surrogate approximation is used by the multistart algorithm to help reduce the number of function evaluations necessary to identify the most promising points from which to start each nonlinear programming local search. SOMS’s numerical results are compared with four well-known methods, namely, Multi-Level Single Linkage (MLSL), MATLAB’s MultiStart, MATLAB’s GlobalSearch, and GLOBAL. In addition, we propose a class of wavy test functions that mimic the wavy nature of objective functions arising in many black-box simulations. Extensive comparisons of algorithms on the wavy testfunctions and on earlier standard global-optimization test functions are done for a total of 19 different test problems. The numerical results indicate that SOMS performs favorably in comparison to alternative methods and does especially well on wavy functions when the number of function evaluations allowed is limited.

Reliability of operational data from pig herds and performance ratings by veterinarians and pig farmers collected during telephone interviews for the evaluation of a PCV2 piglet vaccination

BackgroundThe aim of the present study was to evaluate the feasibility of using a telephone survey in gaining an understanding of the possible herd and management factors influencing the performance (i.e. safety and efficacy) of a vaccine against porcine circovirus type 2 (PCV2) in a large number of herds and to estimate customers¿ satisfaction.ResultsDatasets from 227 pig herds that currently applied or have applied a PCV2 vaccine were analysed. Since 1-, 2- and 3-site production systems were surveyed, the herds were allocated in one of two subsets, where only applicable variables out of 180 were analysed. Group 1 was comprised of herds with sows, suckling pigs and nursery pigs, whereas herds in Group 2 in all cases kept fattening pigs. Overall 14 variables evaluating the subjective satisfaction with one particular PCV2 vaccine were comingled to an abstract dependent variable for further models, which was characterized by a binary outcome from a cluster analysis: good/excellent satisfaction (green cluster) and moderate satisfaction (red cluster). The other 166 variables comprised information about diagnostics, vaccination, housing, management, were considered as independent variables. In Group 1, herds using the vaccine due to recognised PCV2 related health problems (wasting, mortality or porcine dermatitis and nephropathy syndrome) had a 2.4-fold increased chance (1/OR) of belonging to the green cluster. In the final model for Group 1, the diagnosis of diseases other than PCV2, the reason for vaccine administration being other than PCV2-associated diseases and using a single injection of iron had significant influence on allocating into the green cluster (P¿<¿0.05). In Group 2, only unchanged time or delay of time of vaccination influenced the satisfaction (P¿<¿0.05).ConclusionThe methodology and statistical approach used in this study were feasible to scientifically assess ¿satisfaction¿, and to determine factors influencing farmers¿ and vets¿ opinion about the safety and efficacy of a new vaccine.

Ethics in science: enhancing the democratisation of knowledge production in transdisciplinary research partnerships for sustainable development

Better access to knowledge and knowledge production has to be reconsidered as key to successful individual and social mitigation and adaptation strategies for global change. Indeed, concepts of sustainable development imply a transformation of science towards fostering democratisation of knowledge production and the development of knowledge societies as a strategic goal. This means to open the process of scientific knowledge production while simultaneously empowering people to implement their own visions for sustainable development. Advocates of sustainability science support this transformation. In transdisciplinary practice, they advance equity and accountability in the access to and production of knowledge at the science–society interface. UNESCO points to advancements, yet Northern dominance persists in knowledge production as well as in technology design and transfer. Further, transdisciplinary practice remains experimental and hampered by inadequate and asymmetrically equipped institutions in the North and South and related epistemological and operational obscurity. To help identify clear, practicable transdisciplinary approaches, I recommend examining the institutional route – i.e., the learning and adaptation process – followed in concrete cases. The transdisciplinary Eastern and Southern Africa Partnership Programme (1998–2013) is a case ripe for such examination. Understanding transdisciplinarity as an integrative approach, I highlight ESAPP’s three key principles for a more democratised knowledge production for sustainable development: (1) integration of scientific and “non-scientific” knowledge systems; (2) integration of social actors and institutions; and (3) integrative learning processes. The analysis reveals ESAPP’s achievements in contributing to more democratic knowledge production and South ownership in the realm of sustainable development.

Knowledge as a resource: enhancing the democratisation of knowledge production in transdisciplinary research partnerships for sustainable development

Better access to knowledge and knowledge production has to be reconsidered as key to successful individual and social mitigation and adaptation strategies for global change. Indeed, concepts of sustainable development imply a transformation of science (Lubchenco 1998; WBGU 2011 and 2012) towards fostering democratisation of knowledge production as a contribution to the development of knowledge societies as a strategic goal (UNESCO 2005). This means to open the process of scientific knowledge production while simultaneously empowering people to implement their own visions for sustainable development. Advocates of sustainability science support this transformation. In transdisciplinary practice, they advance equity and accountability in the access to and production of knowledge at the science–society interface (Hirsch Hadorn et al 2006; Hirsch Hadorn et al 2008; Jäger 2009; Adger and Jordan 2009; KFPE 2012). UNESCO (2010) points to advancements, yet Northern dominance persists in knowledge production as well as in technology design and transfer (Standing and Taylor 2007; Zingerli 2010). Further, transdisciplinary practice remains experimental and hampered by inadequate and asymmetrically equipped institutions in the North and South and related epistemological and operational obscurity (Wiesmann et al 2011). To help identify clear, practicable transdisciplinary approaches, I recommend examining the institutional route (Mukhopadhyay et al 2006) – i.e., the learning and adaptation process – followed in concrete cases. The transdisciplinary Eastern and Southern Africa Partnership Programme (1998–2013) is a case ripe for such examination. Understanding transdisciplinarity as an integrative approach (Pohl et al 2008; Stock and Burton 2011), I highlight ESAPP’s three key principles for a more democratised knowledge production for sustainable development: (1) integration of scientific and “non-scientific” knowledge systems; (2) integration of social actors and institutions; and (3) integrative learning processes. The analysis reveals ESAPP’s achievements in contributing to more democratic knowledge production and South ownership in the realm of sustainable development.

EARLINET: potential operationality of a research network

In the framework of ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated in the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time, the single calculus chain (SCC) – the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products – was used. All stations sent in real-time measurements of a 1 h duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC, while the optical processing was performed in near-real time after the exercise ended. 98 and 79 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on the lidar data. The paper draws present and future SCC users' attention to the most critical parameters of the SCC product configuration and their possible optimal value but also to the limitations inherent to the raw data. The continuous use of SCC direct and derived products in heterogeneous conditions is used to demonstrate two potential applications of EARLINET infrastructure: the monitoring of a Saharan dust intrusion event and the evaluation of two dust transport models. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modeling, climate research and calibration/validation activities of spaceborne observations.