Global properties of the spectrum of the Haldane-Shastry spin chain

We derive an exact expression for the partition function of the su(m) Haldane-Shastry spin chain, which we use to study the density of levels and the distribution of the spacing between consecutive levels. Our computations show that when the number of sites N is large enough the level density is Gaussian to a very high degree of approximation. More surprisingly, we also find that the nearest-neighbor spacing distribution is not Poissonian, so that this model departs from the typical behavior for an integrable system. We show that the cumulative spacing distribution of the model can be well approximated by a simple functional law involving only three parameters.Comment: RevTeX 4, 7 pages, 4 figures. To appear in Phys. Rev.

Study of growth-environment relationships and optimisation of management including climatic uncertainty of radiata pine stands in Galicia

Climate change is intended to impact forest dynamics significantly inthe following decades. To proactively adapt forest management to these expected alterations, new methodologies for handling the uncertain-ties regarding forest growth under varying environmental conditions become necessary. The purpose of this thesis was to forecast the impact of climate change on radiata pine plantations in the northwest of Spain in terms of productivity, profitability, and silvicultural treatments. In Study I, several statistical techniques were used for predicting thesite index (SI) of radiata pine stands using environmental predictors extracted from available raster maps. A non-linear technique, Multivariate Adaptive Regression Splines (MARS), was suggested as the best modelling alternative, explaining up to 52% of the SI variability. In Study II, the Support Vector Regression technique was used to predict SI and delimit the validity area of predictions based on the radial basis kernel. The resulting model had high predictive performance, provided robust predictions under varied climatic conditions, and included a relatively small number of predictors. Moreover, the model was able to identify areas where climatic conditions were very different from the observed and consequently regularised predictions for those areas. In Study III, silviculture under climate change was optimised for maximising the soil expectation value of a set of radiata pine plantations. The future forest productivity projections, produced by the model developed in Study II, forecasted an overall reduction in SI under climate change, mainly driven by increased temperatures and continentality. Consequently, the economic simulations forecasted a drop in profitability under climate change that was more intense for more pessimistic scenarios (RCP 6.0). However, the climatic projections were very varied over the set of used climate models, which led to a great dispersion in productivity and profitability predictions. From the perspective of silviculture, the most notable forecasted variation is the expected increase in optimum rotation lengths

Daylighting Performance of Solar Control Films for Hospital Buildings in a Mediterranean Climate

One of the main retrofitting strategies in warm climates is the reduction of the effects of solar radiation. Cooling loads, and in turn, cooling consumption, can be reduced through the implementation of reflective materials such as solar control films. However, these devices may also negatively affect daylight illuminance conditions and the electric consumption of artificial lighting systems. In a hospital building, it is crucial to meet daylighting requirements as well as indoor illuminance levels and visibility from the inside, as these have a significant impact on health outcomes. The aim of this paper is to evaluate the influence on natural illuminance conditions of a solar control film installed on the windows of a public hospital building in a Mediterranean climate. To this end, a hospital room, with and without solar film, was monitored for a whole year. A descriptive statistical analysis was conducted on the use of artificial lighting, illuminance levels and rolling shutter aperture levels, as well as an analysis of natural illuminance and electric consumption of the artificial lighting system. The addition of a solar control film to the external surface of the window, in combination with the user-controlled rolling shutter aperture levels, has reduced the electric consumption of the artificial lighting system by 12.2%. Likewise, the solar control film has increased the percentage of annual hours with natural illuminance levels by 100–300 lux

CMOS design of adaptive fuzzy ASICs using mixed-signal circuits

Analog circuits are natural candidates to design fuzzy chips with optimum speed/power figures for precision up to about 1%. This paper presents a methodology and circuit blocks to realize fuzzy controllers in the form of analog CMOS chips. These chips can be made to adapt their function through electrical control. The proposed design methodology emphasizes modularity and simplicity at the circuit level - prerequisites to increasing processor complexity and operation speed. The paper include measurements from a silicon prototype of a fuzzy controller chip in CMOS 1.5 /spl mu/m single-poly technology

A modular CMOS analog fuzzy controller

The low/medium precision required for many fuzzy applications makes analog circuits natural candidates to design fuzzy chips with optimum speed/power figures. This paper presents a sixteen rules-two inputs analog fuzzy controller in a CMOS 1 /spl mu/m single-poly technology based on building blocks implementations previously proposed by the authors (1995). However, such building blocks are rearranged here to get a highly modular architecture organized from two high level blocks: the label block and the rule block. In addition, sharing of membership function circuits allows a compact design with low area and power consumption and its highly modular architecture will permit to increase the number of inputs and rules in future chips with hardly design effort. The paper includes measurements from a silicon prototype of the controller

Multiplexing architecture for mixed-signal CMOS fuzzy controllers

Limited precision imposes limits on the complexity of analogue circuits, and hence fuzzy analogue controllers are usually oriented to fast low-power systems with low-medium complexity. A strategy to preserve most of the advantages of an analogue implementation, while allowing a marked increment in system complexity, is presented.Comisión Interministerial de Ciencia y Tecnología TIC96-1392-C02-0

Neuro-fuzzy chip to handle complex tasks with analog performance

This Paper presents a mixed-signal neuro-fuzzy controller chip which, in terms of power consumption, input-output delay and precision performs as a fully analog implementation. However, it has much larger complexity than its purely analog counterparts. This combination of performance and complexity is achieved through the use of a mixed-signal architecture consisting of a programmable analog core of reduced complexity, and a strategy, and the associated mixed-signal circuitry, to cover the whole input space through the dynamic programming of this core [1]. Since errors and delays are proportional to the reduced number of fuzzy rules included in the analog core, they are much smaller than in the case where the whole rule set is implemented by analog circuitry. Also, the area and the power consumption of the new architecture are smaller than those of its purely analog counterparts simply because most rules are implemented through programming. The Paper presents a set of building blocks associated to this architecture, and gives results for an exemplary prototype. This prototype, called MFCON, has been realized in a CMOS 0.7μm standard technology. It has two inputs, implements 64 rules and features 500ns of input to output delay with 16mW of power consumption. Results from the chip in a control application with a DC motor are also provided

A multiplexed mixed-signal fuzzy architecture

Analog circuits provide better area/power efficiency than their digital counterparts for low-medium precision requirements. This limit in precision as well as the lack of design tools when compared to the digital approach, imposes a limit of complexity, hence fuzzy analog controllers are usually oriented to fast low-power systems with low-medium complexity. The paper presents a strategy to preserve most of the advantages of an analog implementation, while allowing a notorious increment of the system complexity. Such strategy consists in implementing a reduced number of rules, those that really determine the output in a lattice controller, which we call analog core, then this core is dynamically programmed to perform the computation related to a specific rule set. The data to program the analog core are stored in a memory, and constitutes the whole knowledge base in a kind of virtual rule set. HSPICE simulations from an exemplary controller are shown to illustrate the viability of the proposal

Indoor Air Quality Assessment: Comparison of Ventilation Scenarios for Retrofitting Classrooms in a Hot Climate

Current energy e ciency policies in buildings foster the promotion of energy retrofitting of the existing stock. In southern Spain, the most extensive public sector is that of educational buildings, which is especially subject to significant internal loads due to high occupancy. A large fraction of the energy retrofit strategies conducted to date have focused on energy aspects and indoor thermal comfort, repeatedly disregarding indoor air quality criteria. This research assesses indoor air quality in a school located in the Mediterranean area, with the objective of promoting di erent ventilation scenarios, based on occupancy patterns and carbon dioxide levels monitored on site. Results show that manual ventilation cannot guarantee minimum indoor quality levels following current standards. A constant ventilation based on CO2 levels allows 15% more thermal comfort hours a year to be reached, compared to CO2-based optimized demand-controlled ventilation. Nevertheless, the latter ensures 35% annual energy savings, compared to a constant CO2-based ventilation, and 37% more annual energy savings over that of a constant ventilation rate of outdoor air per person

A mixed-signal fuzzy controller and its application to soft start of DC motors

Presents a mixed-signal fuzzy controller chip and its application to control of DC motors. The controller is based on a multiplexed architecture presented by the authors (1998), where building blocks are also described. We focus here on showing experimental results from an example implementation of this architecture as well as on illustrating its performance in an application that has been proposed and developed. The presented chip implements 64 rules, much more than the reported pure analog monolithic fuzzy controllers, while preserving most of their advantages. Specifically, the measured input-output delay is around 500 ns for a power consumption of 16 mW and the chip area (without pads) is 2.65 mm/sup 2/. In the presented application, sensed motor speed and current are the controller input, while it determines the proper duty cycle to a PWM control circuit for the DC-DC converter that powers the motor drive. Experimental results of this application are also presented.Comisión Interministerial de Ciencia y Tecnología TIC99-082