Negative affective environments improve complex solving performance

Based on recent affect-cognition theories (Bless et al., 1996; Fiedler, 2001; Sinclair, 1988), the present study predicted and showed a differentiated influence of nice and nasty environments on complex problem solving (CPS). Environments were constructed by manipulating the target value ‘capital’ of a complex scenario: Participants in the nice environment (N=42) easily raised the capital and received positive feedback, whereas those in the nasty environment (N=42) hardly enhanced the capital and got negative feedback. The results showed that nasty environments increased negative and decreased positive affect. The reverse was true for nice environments. Furthermore, nasty environments influenced CPS by leading to a higher information retrieval and a better CPS performance. Surprisingly, the influence of environment on CPS was not mediated through affect (cf. Soldat & Sinclair, 2001), as recent affect-cognition theories suggest. The missing influence of affect and the strong impact of environment are discussed

Structured learning of assignment models for neuron reconstruction to minimize topological errors

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Structured learning provides a powerful framework for empirical risk minimization on the predictions of structured models. It allows end-to-end learning of model parameters to minimize an application specific loss function. This framework is particularly well suited for discrete optimization models that are used for neuron reconstruction from anisotropic electron microscopy (EM) volumes. However, current methods are still learning unary potentials by training a classifier that is agnostic about the model it is used in. We believe the reason for that lies in the difficulties of (1) finding a representative training sample, and (2) designing an application specific loss function that captures the quality of a proposed solution. In this paper, we show how to find a representative training sample from human generated ground truth, and propose a loss function that is suitable to minimize topological errors in the reconstruction. We compare different training methods on two challenging EM-datasets. Our structured learning approach shows consistently higher reconstruction accuracy than other current learning methods.Peer ReviewedPostprint (author's final draft

Optimization as an analysis tool for human complex decision making

We present a problem class of mixed-integer nonlinear programs (MINLPs) with nonconvex continuous relaxations which stem from economic test scenarios that are used in the analysis of human complex problem solving. In a round-based scenario participants hold an executive function. A posteriori a performance indicator is calculated and correlated to personal measures such as intelligence, working memory, or emotion regulation. Altogether, we investigate 2088 optimization problems that differ in size and initial conditions, based on real-world experimental data from 12 rounds of 174 participants. The goals are twofold. First, from the optimal solutions we gain additional insight into a complex system, which facilitates the analysis of a participant’s performance in the test. Second, we propose a methodology to automatize this process by providing a new criterion based on the solution of a series of optimization problems. By providing a mathematical optimization model and this methodology, we disprove the assumption that the “fruit fly of complex problem solving,” the Tailorshop scenario that has been used for dozens of published studies, is not mathematically accessible—although it turns out to be extremely challenging even for advanced state-of-the-art global optimization algorithms and we were not able to solve all instances to global optimality in reasonable time in this study. The publicly available computational tool Tobago [TOBAGO web site https://sourceforge.net/projects/tobago] can be used to automatically generate problem instances of various complexity, contains interfaces to AMPL and GAMS, and is hence ideally suited as a testbed for different kinds of algorithms and solvers. Computational practice is reported with respect to the influence of integer variables, problem dimension, and local versus global optimization with different optimization codes

Determinants of food choices of adolescents in south-western Nigeria

Food choices of adolescents have become increasingly unhealthy, putting them at increased risk of malnutrition, as they grow older. The study investigated the  determinants of food choices of adolescents in order to assess their nutritional knowledge and implication. World Health Organisation (WHO) describes children aged 10-19 years as adolescents. Four hundred and one adolescents who were in secondary schools were interviewed from six of the thirty local government areas of Osun State, which is a south-western state of Nigeria. Based on the population of secondary schools in the local government areas, thirty-two schools were sampled. Pre tested structured questionnaires using a set of high quality colour photographs of foods and drinks that would typically be offered to adolescents were used. The photographs, showing one item each, included foods such as biscuits, buns, meat pie that were classified as “snacks” and those, such as rice and beans garnished  with vegetable and either fish/meat stew, stewed beans, pounded yam that formed  part of a conventional meal. In the same manner, photographs showing a bottle of  coke, milk, chocolate drink and home made non-alcoholic drinks were presented. This was used to elicit information from the respondents. Descriptive statistical  techniques such as frequency counts, percentage, mean and standard deviation,  likewise inferential tools, such as, correlation analysis and analysis of variance  (ANOVA) were used in data analysis. The study showed positive and significant correlation between the preference and nutritional contents of foods (r = 0.514,  p<0.05) and drinks (r = 0.346, p<0.05). There was no significant difference in the  preference and perceived nutritional contents of the foods (F = 3.072), while there  was a difference in the choice and perceived nutritional contents of drinks (F =  0.217) among the urban and rural adolescents. It is concluded that, the food choice of the adolescents in the study area was based more on taste preference than the nutritional contents. The nutritional knowledge of the adolescents in the study area is high but the knowledge on home made non alcoholic drinks is low. Nutrition  education should be intensified especially on traditional foods and home made non-alcoholic drinks that are nutritious.Keywords: Adolescents, Food choices, Nutritional knowledge

Invest in fast-charging infrastructure or in longer battery ranges? A cost-efficiency comparison for Germany

To reach ambitious CO₂ mitigation targets, the transport sector has to become nearly emission-free and the most promising option for passenger cars are battery electric vehicles (BEV) powered using renewable energy. Despite their important benefits, BEV still face technological barriers, mainly their limited battery range and the limited availability of public fast-charging infrastructure. These factors are hindering the diffusion of electric vehicles (EV). The question of how to address these technical barriers has been widely analyzed in the literature, but so far there has been no cost-efficiency comparison of longer battery ranges and more widespread fast-charging infrastructure that evaluates them both technically and economically. This paper aims to find cost-efficient ways to address limited battery ranges and availability of public fast-charging infrastructure. We focus on German passenger cars that are licensed to commercial owners, since these are an important first market for EV. Our results indicate that fast-charging infrastructure is very cost-efficient as it enables significant proportions of BEV in the fleet at low infrastructure density. The technically feasible maximum BEV shares in the commercial sector can only be achieved with longer battery ranges. However, longer battery ranges are currently associated with comparatively high additional costs

Scenarios for the South African Water Sector in 2025

In 2008 the Water Research Commission initiated a project to develop ‘Water Sector Institutional Landscape in 2025 Scenarios’. The aim was to build knowledge about key drivers and uncertainties related to the future of the South African water sector. A diverse group of stakeholders contributed to the development of the drivers, which translated into different scenarios and associated stories that have potential implications for social and economic development, as well as for the management of water resources and water services. The four scenarios were derived from a matrix with two axes that represent the ability of the decision-making paradigm of water institutions to deal with complexity, and the reconciliation of environmental, social and economic demands of present and future generations (sustainability). The Wise Tortoise scenario describes a sector which deals with complexity and is sensitive to sustainability issues, whereas the Ignorant Ostrich scenario describes the opposite conditions. The Greedy Jackal and Busy Bee scenarios describe the other combinations of the key drivers. The scenarios provide stakeholders and policy-makers in South Africa’s water sector with insights to strengthen decision-making and to counter undesirable trajectories of change. The knowledge will empower role players in the water sector to engage in participative governance by equipping them with insights into potential futures that the South African water sector may face. This paper reports on the process to develop these scenarios for the South African water sector institutional landscape in 2025, presents the key forces, introduces the stories, and reflects on the use of scenarios in the water sector.Keywords: Scenarios, water sector, South Africa, water institutions, water future

Mesoscopic non-equilibrium thermodynamics approach to non-Debye dielectric relaxation

Mesoscopic non-equilibrium thermodynamics is used to formulate a model describing non-homogeneous and non-Debye dielectric relaxation. The model is presented in terms of a Fokker-Planck equation for the probability distribution of non-interacting polar molecules in contact with a heat bath and in the presence of an external time-dependent electric field. Memory effects are introduced in the Fokker-Planck description through integral relations containing memory kernels, which in turn are used to establish a connection with fractional Fokker-Planck descriptions. The model is developed in terms of the evolution equations for the first two moments of the distribution function. These equations are solved by following a perturbative method from which the expressions for the complex susceptibilities are obtained as a functions of the frequency and the wave number. Different memory kernels are considered and used to compare with experiments of dielectric relaxation in glassy systems. For the case of Cole-Cole relaxation, we infer the distribution of relaxation times and its relation with an effective distribution of dipolar moments that can be attributed to different segmental motions of the polymer chains in a melt.Comment: 33 pages, 6 figure

Contributions to the mixed-alkali effect in molecular dynamics simulations of alkali silicate glasses

The mixed-alkali effect on the cation dynamics in silicate glasses is analyzed via molecular dynamics simulations. Observations suggest a description of the dynamics in terms of stable sites mostly specific to one ionic species. As main contributions to the mixed--alkali slowdown longer residence times and an increased probability of correlated backjumps are identified. The slowdown is related to the limited accessibility of foreign sites. The mismatch experienced in a foreign site is stronger and more retarding for the larger ions, the smaller ions can be temporarily accommodated. Also correlations between unlike as well as like cations are demonstrated that support cooperative behavior.Comment: 10 pages, 12 figures, 1 table, revtex4, submitted to Phys. Rev.

Routing of airplanes to two runways: monotonicity of optimal controls

We consider the problem of routing incoming airplanes to two runways of an airport. Due to air turbulence, the necessary separation time between two successive landing operations depends on the types of the airplanes. When viewed as a queueing problem, this means that we have dependent service times. The aim is to minimise waiting times of aircrafts. We consider here a model where arrivals form a stochastic process and where the decision maker does not know anything about future arrivals. We formulate this as a problem of stochastic dynamic programming and investigate monotonicity of optimal routing strategies with respect e.g. to the workload of the runways. We show that an optimal strategy is monotone (i.e. of switching type) only in a restricted case where decisions depend on the state of the runways only and not on the type of the arriving aircraft. Surprisingly, in the more realistic case where this type is also known to the decision maker, monotonicity need not hold