Eight Dimensions for the Emotions

The author proposes a dimensional model of our emotion concepts that is intended to be largely independent of one’s theory of emotions and applicable to the different ways in which emotions are measured. He outlines some conditions for selecting the dimensions based on these motivations and general conceptual grounds. Given these conditions he then advances an 8-dimensional model that is shown to effectively differentiate emotion labels both within and across cultures, as well as more obscure expressive language. The 8 dimensions are: (1) attracted—repulsed, (2) powerful—weak, (3) free—constrained, (4) certain—uncertain, (5) generalized—focused, (6) future directed—past directed, (7) enduring—sudden, (8) socially connected—disconnected

Climate change adaptation and vulnerability assessment of water resources systems in developing countries: a generalized framework and a feasibility study in Bangladesh

Water is the primary medium through which climate change influences the Earth’s ecosystems and therefore people’s livelihoods and wellbeing. Besides climatic change, current demographic trends, economic development and related land use changes have direct impact on increasing demand for freshwater resources. Taken together, the net effect of these supply and demand changes is affecting the vulnerability of water resources. The concept of ‘vulnerability’ is not straightforward as there is no universally accepted approach for assessing vulnerability. In this study, we review the evolution of approaches to vulnerability assessment related to water resources. From the current practices, we identify research gaps, and approaches to overcome these gaps a generalized assessment framework is developed. A feasibility study is then presented in the context of the Lower Brahmaputra River Basin (LBRB). The results of the feasibility study identify the current main constraints (e.g., lack of institutional coordination) and opportunities (e.g., adaptation) of LBRB. The results of this study can be helpful for innovative research and management initiatives and the described framework can be widely used as a guideline for the vulnerability assessment of water resources systems, particularly in developing countries

A Generic Conceptual Model for Risk Analysis in a Multi-agent Based Collaborative Design Environment

Organised by: Cranfield UniversityThis paper presents a generic conceptual model of risk evaluation in order to manage the risk through related constraints and variables under a multi-agent collaborative design environment. Initially, a hierarchy constraint network is developed to mapping constraints and variables. Then, an effective approximation technique named Risk Assessment Matrix is adopted to evaluate risk level and rank priority after probability quantification and consequence validation. Additionally, an Intelligent Data based Reasoning Methodology is expanded to deal with risk mitigation by combining inductive learning methods and reasoning consistency algorithms with feasible solution strategies. Finally, two empirical studies were conducted to validate the effectiveness and feasibility of the conceptual model.Mori Seiki – The Machine Tool Compan

Natural selection as coarsening

Analogies between evolutionary dynamics and statistical mechanics, such as Fisher's second-law-like "fundamental theorem of natural selection" and Wright's "fitness landscapes", have had a deep and fruitful influence on the development of evolutionary theory. Here I discuss a new conceptual link between evolution and statistical physics. I argue that natural selection can be viewed as a coarsening phenomenon, similar to the growth of domain size in quenched magnets or to Ostwald ripening in alloys and emulsions. In particular, I show that the most remarkable features of coarsening---scaling and self-similarity---have strict equivalents in evolutionary dynamics. This analogy has three main virtues: it brings a set of well-developed mathematical tools to bear on evolutionary dynamics; it suggests new problems in theoretical evolution; and it provides coarsening physics with a new exactly soluble model.Comment: Submitted to J. Stat. Phys. for special issue on evolutionary dynamic

Development of an automated aircraft subsystem architecture generation and analysis tool

Purpose – The purpose of this paper is to present a new computational framework to address future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimization. Main focus lies with a demonstration of the frameworks workings, as well as the optimizers performance with a typical form of application problem. Design/methodology/approach – The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture and component levels. This may be followed by a complete enumeration of architectures, combined with a user defined technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The optimizer is tested on a generic architecture design problem combined with modified Griewank and parabolic functions for the continuous space. Findings – Insights from the generalized application problem show consistent rediscovery of the optimal architectures with the optimizer, as compared to a full problem enumeration. In addition multi-objective optimization reveals a Pareto front with differences in component composition as well as continuous parameters. Research limitations/implications – This paper demonstrates the frameworks application on a generalized test problem only. Further publication will consider real engineering design problems. Originality/value – The paper addresses the need for future conceptual design methods of complex systems to consider a mixed concept space of both discrete and continuous nature via automated methods

A review of applied methods in Europe for flood-frequency analysis in a changing environment

The report presents a review of methods used in Europe for trend analysis, climate change projections and non-stationary analysis of extreme precipitation and flood frequency. In addition, main findings of the analyses are presented, including a comparison of trend analysis results and climate change projections. Existing guidelines in Europe on design flood and design rainfall estimation that incorporate climate change are reviewed. The report concludes with a discussion of research needs on non-stationary frequency analysis for considering the effects of climate change and inclusion in design guidelines. Trend analyses are reported for 21 countries in Europe with results for extreme precipitation, extreme streamflow or both. A large number of national and regional trend studies have been carried out. Most studies are based on statistical methods applied to individual time series of extreme precipitation or extreme streamflow using the non-parametric Mann-Kendall trend test or regression analysis. Some studies have been reported that use field significance or regional consistency tests to analyse trends over larger areas. Some of the studies also include analysis of trend attribution. The studies reviewed indicate that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant increasing trends at regional or national level of extreme streamflow. For some smaller regions increases in extreme streamflow are reported. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows. Climate change projections have been reported for 14 countries in Europe with results for extreme precipitation, extreme streamflow or both. The review shows various approaches for producing climate projections of extreme precipitation and flood frequency based on alternative climate forcing scenarios, climate projections from available global and regional climate models, methods for statistical downscaling and bias correction, and alternative hydrological models. A large number of the reported studies are based on an ensemble modelling approach that use several climate forcing scenarios and climate model projections in order to address the uncertainty on the projections of extreme precipitation and flood frequency. Some studies also include alternative statistical downscaling and bias correction methods and hydrological modelling approaches. Most studies reviewed indicate an increase in extreme precipitation under a future climate, which is consistent with the observed trend of extreme precipitation. Hydrological projections of peak flows and flood frequency show both positive and negative changes. Large increases in peak flows are reported for some catchments with rainfall-dominated peak flows, whereas a general decrease in flood magnitude and earlier spring floods are reported for catchments with snowmelt-dominated peak flows. The latter is consistent with the observed trends. The review of existing guidelines in Europe on design floods and design rainfalls shows that only few countries explicitly address climate change. These design guidelines are based on climate change adjustment factors to be applied to current design estimates and may depend on design return period and projection horizon. The review indicates a gap between the need for considering climate change impacts in design and actual published guidelines that incorporate climate change in extreme precipitation and flood frequency. Most of the studies reported are based on frequency analysis assuming stationary conditions in a certain time window (typically 30 years) representing current and future climate. There is a need for developing more consistent non-stationary frequency analysis methods that can account for the transient nature of a changing climate

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error