Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA40

Reanalysis data obtained from data assimilation are increasingly used for diagnostic studies of the general circulation of the atmosphere, for the validation of modelling experiments and for estimating energy and water fluxes between the Earth surface and the atmosphere. Because fluxes are not specifically observed, but determined by the data assimilation system, they are not only influenced by the utilized observations but also by model physics and dynamics and by the assimilation method. In order to better understand the relative importance of humidity observations for the determination of the hydrological cycle, in this paper we describe an assimilation experiment using the ERA40 reanalysis system where all humidity data have been excluded from the observational data base. The surprising result is that the model, driven by the time evolution of wind, temperature and surface pressure, is able to almost completely reconstitute the large-scale hydrological cycle of the control assimilation without the use of any humidity data. In addition, analysis of the individual weather systems in the extratropics and tropics using an objective feature tracking analysis indicates that the humidity data have very little impact on these systems. We include a discussion of these results and possible consequences for the way moisture information is assimilated, as well as the potential consequences for the design of observing systems for climate monitoring. It is further suggested, with support from a simple assimilation study with another model, that model physics and dynamics play a decisive role for the hydrological cycle, stressing the need to better understand these aspects of model parametrization. .

Modelling impacts of pollution in river systems: a new dispersion model and a case study of mine discharges in the Abrud, Aries and Mures river system in Transylvania, Romania

A new model of dispersion has been developed to simulate the impact of pollutant discharges on river systems. The model accounts for the main dispersion processes operating in rivers as well as the dilution from incoming tributaries and first-order kinetic decay processes. The model is dynamic and simulates the hourly behaviour of river flow and pollutants along river systems. The model has been applied to the Aries and Mures River System in Romania and has been used to assess the impacts of potential dam releases from the Roia Montan Mine in Transylvania, Romania. The question of mine water release is investigated under a range of scenarios. The impacts on pollution levels downstream at key sites and at the border with Hungary are investigated.

Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments

During the past 15 years, a number of initiatives have been undertaken at national level to develop ocean forecasting systems operating at regional and/or global scales. The co-ordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants in GODAE. The MERCATOR systems routinely assimilate a variety of observations such as multi-satellite altimeter data, sea-surface temperature and in situ temperature and salinity profiles, focusing on high-resolution scales of the ocean dynamics. The assimilation strategy in MERCATOR is based on a hierarchy of methods of increasing sophistication including optimal interpolation, Kalman filtering and variational methods, which are progressively deployed through the Syst`eme d’Assimilation MERCATOR (SAM) series. SAM-1 is based on a reduced-order optimal interpolation which can be operated using ‘altimetry-only’ or ‘multi-data’ set-ups; it relies on the concept of separability, assuming that the correlations can be separated into a product of horizontal and vertical contributions. The second release, SAM-2, is being developed to include new features from the singular evolutive extended Kalman (SEEK) filter, such as three-dimensional, multivariate error modes and adaptivity schemes. The third one, SAM-3, considers variational methods such as the incremental four-dimensional variational algorithm. Most operational forecasting systems evaluated during GODAE are based on least-squares statistical estimation assuming Gaussian errors. In the framework of the EU MERSEA (Marine EnviRonment and Security for the European Area) project, research is being conducted to prepare the next-generation operational ocean monitoring and forecasting systems. The research effort will explore nonlinear assimilation formulations to overcome limitations of the current systems. This paper provides an overview of the developments conducted in MERSEA with the SEEK filter, the Ensemble Kalman filter and the sequential importance re-sampling filter.

Puroindoline-b mutations control the lipid binding interactions in mixed puroindoline-a: puroindoline-b systems

The interactions have been investigated of puroindoline-a (Pin-a) and mixed protein systems of Pin-a and wild-type puroindoline-b (Pin-b+) or puroindoline-b mutants (G46S mutation (Pin bH) or W44R mutation (Pin-bS)) with condensed phase monolayers of an anionic phospholipid (L-α-dipalmitoylphosphatidyl-dl-glycerol (DPPG)) at the air/water interface. The interactions of the mixed systems were studied at three different concentration ratios of Pin-a:Pin-b, namely 3:1, 1:1 and 1:3 in order to establish any synergism in relation to lipid binding properties. Surface pressure measurements revealed that Pin-a interaction with DPPG monolayers led to an equilibrium surface pressure increase of 8.7 ± 0.6 mN m-1. This was less than was measured for Pin-a:Pin-b+ (9.6 to 13.4 mN m-1), but was significantly more than was measured for Pin-a:Pin-bH (4.0 to 6.2 mN m-1) or Pin-a:Pin-bS (3.8 to 6.3 mN m-1) over the complete range of concentration ratio. Consequently, surface pressure increases were shown to correlate to endosperm hardness phenotype, with puroindolines present in hard-textured wheat varieties yielding lower equilibrium surface pressure changes. Integrated amide I peak areas from corresponding external reflectance Fourier-transform infrared (ER-FTIR) spectra, used to indicate levels of protein adsorption to the lipid monolayers, showed that differences in adsorbed amount were less significant. The data therefore suggest that Pin-b mutants having single residue substitutions within their tryptophan-rich loop that are expressed in some hard-textured wheat varieties influence the degree of penetration of Pin-a and Pin-b into anionic phospholipid films. These findings highlight the key role of the tryptophan-rich loop in puroindoline-lipid interactions.

Autopoiesis vs. social autopoiesis: critical evaluation and implications for understanding firms as autopoietic social systems

The main objective of this study is to revisit the fundamental postulations of autopoietic self-production wrapped within the autopoietic six-point key and to investigate whether or not firms as specific social systems can be treated as autopoietic unities. In order to do so firms have to be defined as simple and composite unities whereupon their boundaries have to be clearly identifiable. The test of social autopoiesis reveals that firms can be viewed as autopoietic social systems that exist in the communicative space with employees' firm-specific communicative sub-domains as their components. Furthermore, it is argued that the social reification of autopoiesis (autokoinopoiesis) in firms is quintessentially interconnected with physical autopoiesis of their employees (autophysiopoiesis). Discontiguous focus on productivity as firms' obvious physical implication may thus be upgraded by a very social nature of ideactivity, firms' only real survival force.

Farming systems methodology for efficient resource management at the farm level: a review from an Indian perspective

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.

Nitrogen budgets for three cropping systems fertilised with cattle manure

A field plot experiment was set up on a sandy loam soil of SW England in order to determine the efficiency of nitrogen use from different cattle manures. The manure treatments were low and high dry matter cattle slurries and one farmyard manure applied at a target rate of 200 kg total Nha(-1) year(-1), and an untreated control. There were three different cropping systems: ryegrass/clover mixture, maize/rye and maize/bare soil, which were evaluated during 1998/99 and 1999/00. Measurements were made of N losses, N uptake and herbage DM yields. Result showed that manure type had a significant effect on N utilisation only for maize. N balances were negative in maize (approximately -247 to -10 kg N) compared to grass (approximately 5-158 kg N). Agronomic management was more important than manure type in influencing N losses, where soil cultivation appeared to be a key factor when comparing maize and grass systems. (C) 2004 Elsevier Ltd. All rights reserved.

Analysis of the calving pattern of herds in small-scale dairy systems in central Mexico

This study sets out to find the best calving pattern for small-scale dairy systems in Michoacan State, central Mexico. Two models were built. First, a linear programming model was constructed to optimize calving pattern and herd structure according to metabolizable energy availability. Second, a Markov chain model was built to investigate three reproductive scenarios (good, average and poor) in order to suggest factors that maintain the calving pattern given by the linear programming model. Though it was not possible to maintain the optimal linear programming pattern, the Markov chain model suggested adopting different reproduction strategies according to period of the year that the cow is expected to calve. Comparing different scenarios, the Markov model indicated the effect of calving interval on calving pattern and herd structure.

A rheological and SAXS study of the lamellar order in a side-on liquid crystalline block copolymer

We study the structure and shear flow behavior of a side-on liquid crystalline triblock copolymer, named PBA-b-PA444-b-PBA (PBA is poly(butyl acrylate) and PA444 is a poly(acrylate) with a nematic liquid crystal side-on mesogen), in the self-assembled lamellar phase and in the disordered phase. Simultaneous oscillatory shear and small-angle X-ray scattering experiments show that shearing PBA-b-PA444-b-PBA at high frequency and strain amplitudes leads to the alignment of the lamellae with normals perpendicular to the shear direction and to the velocity gradient direction, i.e., in the perpendicular orientation. The order-to-disorder transition temperature (T-ODT) is independent of the applied strain, in contrast to results reported in the literature for coil-coil diblock copolymers, which show an increase in T-ODT with shear rate. It is possible that in our system, T-ODT does not depend on the applied strain because the fluctuations are weaker than those present in coil-coil diblock copolymer systems.

The air distribution index as an indicator for energy consumption and performance of ventilation systems

This paper deals with the energy consumption and the evaluation of the performance of air supply systems for a ventilated room involving high- and low-level supplies. The energy performance assessment is based on the airflow rate, which is related to the fan power consumption by achieving the same environmental quality performance for each case. Four different ventilation systems are considered: wall displacement ventilation, confluent jets ventilation, impinging jet ventilation and a high level mixing ventilation system. The ventilation performance of these systems will be examined by means of achieving the same Air Distribution Index (ADI) for different cases. The widely used high-level supplies require much more fan power than those for low-level supplies for achieving the same value of ADI. In addition, the supply velocity, hence the supply dynamic pressure, for a high-level supply is much larger than for low-level supplies. This further increases the power consumption for high-level supply systems. The paper considers these factors and attempts to provide some guidelines on the difference in the energy consumption associated with high and low level air supply systems. This will be useful information for designers and to the authors' knowledge there is a lack of information available in the literature on this area of room air distribution. The energy performance of the above-mentioned ventilation systems has been evaluated on the basis of the fan power consumed which is related to the airflow rate required to provide equivalent indoor environment. The Air Distribution Index (ADI) is used to evaluate the indoor environment produced in the room by the ventilation strategy being used. The results reveal that mixing ventilation requires the highest fan power and the confluent jets ventilation needs the lowest fan power in order to achieve nearly the same value of ADI.

Towards a unifying framework for pattern transformation in swarm systems

This paper identifies the major challenges in the area of pattern formation. The work is also motivated by the need for development of a single framework to surmount these challenges. A framework based on the control of macroscopic parameters is proposed. The issue of transformation of patterns is specifically considered. A definition for transformation and four special cases, namely elementary and geometrical transformations by repositioning all or some robots in the pattern are provided. Two feasible tools for pattern transformation namely, a macroscopic parameter method and a mathematical tool - Moebius transformation also known as the linear fractional transformation are introduced. The realization of the unifying framework considering planning and communication is reported.

Closely coupled behaviour in networked robot systems

Multiple cooperating robot systems may be required to take up a closely coupled configuration in order to perform a task. An example is extended baseline stereo (EBS), requiring that two robots must establish and maintain for a certain period of time a constrained kinematic relationship to each other. In this paper we report on the development of a networked robotics framework for modular, distributed robot systems that supports the creation of such configurations. The framework incorporates a query mechanism to locate modules distributed across the two robot systems. The work presented in this paper introduces special mechanisms to model the kinematic constraint and its instantiation. The EBS configuration is used as a case study and experimental implementation to demonstrate the approach.