Coupling climate and economic models in a cost-benefit framework: a convex optimization approach

In this paper we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99 we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model

Detection of Neural Activity in the Brains of Japanese Honeybee Workers during the Formation of a “Hot Defensive Bee Ball”

Anti-predator behaviors are essential to survival for most animals. The neural bases of such behaviors, however, remain largely unknown. Although honeybees commonly use their stingers to counterattack predators, the Japanese honeybee (Apis cerana japonica) uses a different strategy to fight against the giant hornet (Vespa mandarinia japonica). Instead of stinging the hornet, Japanese honeybees form a “hot defensive bee ball” by surrounding the hornet en masse, killing it with heat. The European honeybee (A. mellifera ligustica), on the other hand, does not exhibit this behavior, and their colonies are often destroyed by a hornet attack. In the present study, we attempted to analyze the neural basis of this behavior by mapping the active brain regions of Japanese honeybee workers during the formation of a hot defensive bee ball. First, we identified an A. cerana homolog (Acks = Apis cerana kakusei) of kakusei, an immediate early gene that we previously identified from A. mellifera, and showed that Acks has characteristics similar to kakusei and can be used to visualize active brain regions in A. cerana. Using Acks as a neural activity marker, we demonstrated that neural activity in the mushroom bodies, especially in Class II Kenyon cells, one subtype of mushroom body intrinsic neurons, and a restricted area between the dorsal lobes and the optic lobes was increased in the brains of Japanese honeybee workers involved in the formation of a hot defensive bee ball. In addition, workers exposed to 46°C heat also exhibited Acks expression patterns similar to those observed in the brains of workers involved in the formation of a hot defensive bee ball, suggesting that the neural activity observed in the brains of workers involved in the hot defensive bee ball mainly reflects thermal stimuli processing

A parametric design method for CFD-supported wind-driven ventilation

The negative impact of the building industry has brought a critical emphasis on the performance-related tools and processes of architectural design. The integration of design and performance simulation has the potential to extend the decision-making capabilities of the architects. Amongst a number of performance parameters, wind-related measures are generally problematic for the design phase, due to the computational cost of predicting wind behaviour, the complexity of the urban context and the constantly changing airflow patterns. In this respect, this paper proposes the preliminary exploration of a design method towards integrating Computational Fluid Dynamics (CFD) coupled with energy modelling and parametric design tools for the wind-related design acts. As building performance is regarded as a design problem that necessitates a designerly point of view as much as a technical perspective, the method aims at providing visual, generative and accurate feedback regarding its potential to facilitate the architect's designerly integration to the process and to provide a flexible design environment. The preliminary quantitative analysis conducted through a case study indicates the preliminary data flow through the design process

Reaction synthesis of Ni-Al-based particle composite coatings

Electrodeposited metal matrix/metal particle composite (EMMC) coatings were produced with a nickel matrix and aluminum particles. By optimizing the process parameters, coatings were deposited with 20 volume percent aluminum particles. Coating morphology and composition were characterized using light optical microscopy (LOM), scanning electron microscopy (SEM), and electron probe microanalysis (EPMA). Differential thermal analysis (DTA) was employed to study reactive phase formation. The effect of heat treatment on coating phase formation was studied in the temperature range 415 to 1,000 C. Long-time exposure at low temperature results in the formation of several intermetallic phases at the Ni matrix/Al particle interfaces and concentrically around the original Al particles. Upon heating to the 500--600 C range, the aluminum particles react with the nickel matrix to form NiAl islands within the Ni matrix. When exposed to higher temperatures (600--1,000 C), diffusional reaction between NiAl and nickel produces ({gamma})Ni{sub 3}Al. The final equilibrium microstructure consists of blocks of ({gamma}{prime})Ni{sub 3}Al in a {gamma}(Ni) solid solution matrix, with small pores also present. Pore formation is explained based on local density changes during intermetallic phase formation and microstructural development is discussed with reference to reaction synthesis of bulk nickel aluminides