Mobile-to-mobile MIMO transmit-receive diversity systems: analysis and performance in three-dimensional double-correlated channels

Mobile-to-mobile (M-to-M) communications are expected to play a crucial role in future wireless systems and networks. In this paper, we consider M-to-M multiple-input multiple-output (MIMO) maximal ratio combining system and assess its performance in spatially correlated channels. The analysis assumes double-correlated Rayleigh-and-Lognormal fading channels and is performed in terms of average symbol error probability, outage probability, and ergodic capacity. To obtain the receive and transmit spatial correlation functions needed for the performance analysis, we used a three-dimensional (3D) M-to-M MIMO channel model, which takes into account the effects of fast fading and shadowing. The expressions for the considered metrics are derived as a function of the average signal-to-noise ratio per receive antenna in closed-form and are further approximated using the recursive adaptive Simpson quadrature method. Numerical results are provided to show the effects of system parameters, such as distance between antenna elements, maximum elevation angle of scatterers, orientation angle of antenna array in the x–y plane, angle between the x–y plane and the antenna array orientation, and degree of scattering in the x–y plane, on the system performance. Copyright © 2011 John Wiley & Sons, Ltd.

Performance analysis of AF cooperative systems with HPA nonlinearity in semi-blind relays

In this paper, dual-hop amplify-and-forward (AF) cooperative systems in the presence of high-power amplifier (HPA) nonlinearity at semi-blind relays, are investigated. Based on the modified AF cooperative system model taking into account the HPA nonlinearity, the expression for the output signal-to-noise ratio (SNR) at the destination node is derived, where the interference due to both the AF relaying mechanism and the HPA nonlinearity is characterized. The performance of the AF cooperative system under study is evaluated in terms of average symbol error probability (SEP), which is derived using the moment-generating function (MGF) approach, considering transmissions over Nakagami-m fading channels. Numerical results are provided and show the effects of some system parameters, such as the HPA parameters, numbers of relays, quadrature amplitude modulation (QAM) order, Nakagami parameters, on performance.

Complex-valued b-spline neural networks for modelling and inverse of wiener systems

Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV

Local and average structure in zinc cyanide: towards an understanding of the atomistic origin of negative thermal expansion

Neutron diffraction at 11.4 and 295 K and solid-state 67Zn NMR are used to determine both the local and average structures in the disordered, negative thermal expansion (NTE) material, Zn(CN)2. Solid-state NMR not only confirms that there is head-to-tail disorder of the C≡N groups present in the solid, but yields information about the relative abundances of the different Zn(CN)4-n(NC)n tetrahedral species, which do not follow a simple binomial distribution. The Zn(CN)4 and Zn(NC)4 species occur with much lower probabilities than are predicted by binomial theory, supporting the conclusion that they are of higher energy than the other local arrangements. The lowest energy arrangement is Zn(CN)2(NC)2. The use of total neutron diffraction at 11.4 K, with analysis of both the Bragg diffraction and the derived total correlation function, yields the first experimental determination of the individual Zn−N and Zn−C bond lengths as 1.969(2) and 2.030(2) Å, respectively. The very small difference in bond lengths, of ~0.06 Å, means that it is impossible to obtain these bond lengths using Bragg diffraction in isolation. Total neutron diffraction also provides information on both the average and local atomic displacements responsible for NTE in Zn(CN)2. The principal motions giving rise to NTE are shown to be those in which the carbon and nitrogen atoms within individual Zn−C≡N−Zn linkages are displaced to the same side of the Zn···Zn axis. Displacements of the carbon and nitrogen atoms to opposite sides of the Zn···Zn axis, suggested previously in X-ray studies as being responsible for NTE behavior, in fact make negligible contribution at temperatures up to 295 K.

The importance of moisture distribution for the growth and energetics of mid-latitude systems

A primitive equation model is used to study the sensitivity of baroclinic wave life cycles to the initial latitude-height distribution of humidity. Diabatic heating is parametrized only as a consequence of condensation in regions of large-scale ascent. Experiments are performed in which the initial relative humidity is a simple function of model level, and in some cases latitude bands are specified which are initially relatively dry. It is found that the presence of moisture can either increase or decrease the peak eddy kinetic energy of the developing wave, depending on the initial moisture distribution. A relative abundance of moisture at mid-latitudes tends to weaken the wave, while a relative abundance at low latitudes tends to strengthen it. This sensitivity exists because competing processes are at work. These processes are described in terms of energy box diagnostics. The most realistic case lies on the cusp of this sensitivity. Further physical parametrizations are then added, including surface fluxes and upright moist convection. These have the effect of increasing wave amplitude, but the sensitivity to initial conditions of relative humidity remains. Finally, 'control' and 'doubled CO2' life cycles are performed, with initial conditions taken from the time-mean zonal-mean output of equilibrium GCM experiments. The attenuation of the wave resulting from reduced baroclinicity is more pronounced than any effect due to changes in initial moisture.

Participatory research approaches in the development of improved management practices in indigenous chickens production systems with smallholder farmers in Kenya

This thesis is concerned with development of improved management practices in indigenous chicken production systems in a research process that includes participatory approaches with smallholder farmers and other stakeholders in Kenya. The research process involved a wide range of activities that included on-station experiments, field surveys, stakeholder consultations in workshops, seminars and visits, and on-farm farmer participatory research to evaluate the effect of some improved management interventions on production performance of indigenous chickens. The participatory research was greatly informed from collective experiences and lessons of the previous activities. The on-station studies focused on hatching, growth and nutritional characteristics of the indigenous chickens. Four research publications from these studies are included in this thesis. Quantitative statistical analyses were applied and they involved use of growth models estimated with non-linear regressions for the growth characteristics, chi-square determinations to investigate differences among different reciprocal crosses of indigenous chickens and general linear models and covariance determination for the nutrition study. The on-station studies brought greater understanding of performance and production characteristics of indigenous chickens and the influence of management practices on these characteristics. The field surveys and stakeholder consultations helped in understanding the overarching issues affecting the productivity of the indigenous chickens systems and their place in the livelihoods of smallholder farmers. These activities created strong networking opportunities with stakeholders from a wide spectrum. The on-farm farmer participatory research involved selection of 200 farmers in five regions followed by training and introduction of interventions on improved management practices which included housing, vaccination, deworming and feed supplementation. Implementation and monitoring was mainly done by individual farmers continuously for close to one and half years. Six quarterly visits to the farms were made by the research team to monitor and provide support for on-going project activities. The data collected has been analysed for 5 consecutive 3-monthly periods. Descriptive and inferential statistics were applied to analyse the data collected involving treatment applications, production characteristics and flock demography characteristics. Out of the 200 farmers initially selected, 173 had records on treatment applications and flock demography characteristics while 127 farmers had records on production characteristics. The demographic analysis with a dissimilarity index of flock size produced 7 distinct farm groups from among the 173 farms. Two of these farm groups were represented in similar numbers in each of the five regions. The research process also involved a number of dissemination and communication strategies that have brought the process and project outcomes into the domain of accessibility by wider readership locally and globally. These include workshops, seminars, field visits and consultations, local and international conferences, electronic conferencing, publications and personal communication via emailing and conventional posting. A number of research and development proposals were also developed based on the knowledge and experiences gained from the research process. The thesis captures the research process activities and outcomes in 8 chapters which include in ascending order – introduction, theoretical concepts underpinning FPR, research methodology and process, on-station research output, FPR descriptive statistical analysis, FPR inferential statistical analysis on production characteristics, FPR demographic analysis and conclusions. Various research approaches both quantitative and qualitative have been applied in the research process indicating the possibilities and importance of combining both systems for greater understanding of issues being studied. In our case, participatory studies of the improved management of indigenous chickens indicates their potential importance as livelihood assets for poor people.

The outsourcing strategy of local and multinational firms: A supply base perspective

Firms outsource through connecting to local and global supply bases and making such connections produces costs of search and evaluation, which are a function of transaction characteristics and firm capabilities. We argue that firms outsource more when those costs are low. Hence, domestic subsidiaries of multinational firms, with low cost access to both local and global supply bases, outsource more than either domestic firms or foreign subsidiaries, as confirmed by evidence from a large data panel. We also propose that among foreign subsidiaries, distance from the home country co-determines search and evaluation costs such that subsidiaries from more distant countries outsource less. This is confirmed for geographic distance, but a positive effect is found for political distance and a mixed effect for cultural distance.

Flavonoid inhibitory pharmacodynamics on platelet function in physiological environments

The complex relationship between flavonoid-based nutrition and cardiovascular disease may be dissected by understanding the activities of these compounds in biological systems. The aim of the present study was to explore a hierarchy for the importance of dietary flavonoids on cardiovascular health by examining the structural basis for inhibitory effects of common, dietary flavonoids (quercetin, apigenin, and naringenin) and the plasma metabolite, tamarixetin. Understanding flavonoid effects on platelets in vivo can be informed by investigations of the ability of these compounds to attenuate the function of these cells. Inhibition of platelet function in whole blood and plasma was structure-dependent. The order of potency was apigenin > tamarixetin > quercetin = naringenin indicating that in vivo, important functional groups are potentially a methylated B ring, and a non-hydroxylated, planar C ring. Apigenin and the methylated metabolite of quercetin, tamarixetin significantly reduced thrombus volume at concentrations (5 μM) that suggested their reported physiological levels (0.1-1 μM) may exert low levels of inhibition. Flavonoid interactions with erythrocytes, leukocytes and human serum albumin in whole blood reduce their inhibitory activities against platelet function. The diminished inhibitory activity of flavonoids that we observed in whole blood and plasma indicated that these interactions do not overcome the attenuating effects of these compounds. Furthermore, inhibition of platelet aggregation by flavonoids was enhanced with increases in exposure time, indicating the potential for measurable inhibitory effects during resident plasma times. We conclude that flavonoid structures may be a major influence of their activities in vivo with methylated metabolites and those of flavones being more potent than those of flavonols and flavanones.

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

Pragmatic oriented data interoperability for smart healthcare information systems

Smart healthcare is a complex domain for systems integration due to human and technical factors and heterogeneous data sources involved. As a part of smart city, it is such a complex area where clinical functions require smartness of multi-systems collaborations for effective communications among departments, and radiology is one of the areas highly relies on intelligent information integration and communication. Therefore, it faces many challenges regarding integration and its interoperability such as information collision, heterogeneous data sources, policy obstacles, and procedure mismanagement. The purpose of this study is to conduct an analysis of data, semantic, and pragmatic interoperability of systems integration in radiology department, and to develop a pragmatic interoperability framework for guiding the integration. We select an on-going project at a local hospital for undertaking our case study. The project is to achieve data sharing and interoperability among Radiology Information Systems (RIS), Electronic Patient Record (EPR), and Picture Archiving and Communication Systems (PACS). Qualitative data collection and analysis methods are used. The data sources consisted of documentation including publications and internal working papers, one year of non-participant observations and 37 interviews with radiologists, clinicians, directors of IT services, referring clinicians, radiographers, receptionists and secretary. We identified four primary phases of data analysis process for the case study: requirements and barriers identification, integration approach, interoperability measurements, and knowledge foundations. Each phase is discussed and supported by qualitative data. Through the analysis we also develop a pragmatic interoperability framework that summaries the empirical findings and proposes recommendations for guiding the integration in the radiology context.

Cost function for sub-agent elements in multi-agent energy management system

Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

Changing HRM systems in two Russian oil companies: Western hegemony or Russian spetsifika?

We contrast attempts to introduce what were seen as sophisticated Western-style human resource management (HRM) systems into two Russian oil companies – a joint venture with a Western multinational corporation (TNK-BP) and a wholly Russian-owned company (Yukos). The drivers for Western hegemony within the joint venture, heavily influenced by expatriates and the established HRM processes introduced by the Western parent, were counteracted to a significant degree by the Russian spetsifika – the peculiarly Russian way of thinking and doing things. In contrast, developments were absorbed faster in the more authoritarian Russian-owned company. The research adds to the theoretical debate about international knowledge transfer and provides detailed empirical data to support our understanding of the effect of both organizational and cultural context on the knowledge-transfer mechanisms of local and multinational companies. As the analysis is based on the perspective of senior local nationals, we also address a relatively under-researched area in the international HRM literature which mostly relies on empirical data collected from expatriates and those based solely in multinational headquarters.

A radial basis function network classifier to maximise leave-one-out mutual information

tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.

A role for hippocampal PSA-NCAM and NMDA-NR2B receptor function in flavonoid-induced spatial memory improvements in young rats

The increase in incidence and prevalence of neurodegenerative diseases highlights the need for a more comprehensive understanding of how food components may affect neural systems. In particular, flavonoids have been recognized as promising agents capable of influencing different aspects of synaptic plasticity resulting in improvements in memory and learning in both animals and humans. Our previous studies highlight the efficacy of flavonoids in reversing memory impairments in aged rats, yet little is known about the effects of these compounds in healthy animals, particularly with respect to the molecular mechanisms by which flavonoids might alter the underlying synaptic modifications responsible for behavioral changes. We demonstrate that a 3-week intervention with two dietary doses of flavonoids (Dose I: 8.7 mg/day and Dose II: 17.4 mg/day) facilitates spatial memory acquisition and consolidation (24 recall) (p < 0.05) in young healthy rats. We show for the first time that these behavioral improvements are linked to increased levels in the polysialylated form of the neural adhesion molecule (PSA-NCAM) in the dentate gyrus (DG) of the hippocampus, which is known to be required for the establishment of durable memories. We observed parallel increases in hippocampal NMDA receptors containing the NR2B subunit for both 8.7 mg/day (p < 0.05) and 17.4 mg/day (p < 0.001) doses, suggesting an enhancement of glutamate signaling following flavonoid intervention. This is further strengthened by the simultaneous modulation of hippocampal ERK/CREB/BDNF signaling and the activation of the Akt/mTOR/Arc pathway, which are crucial in inducing changes in the strength of hippocampal synaptic connections that underlie learning. Collectively, the present data supports a new role for PSA-NCAM and NMDA-NR2B receptor on flavonoid-induced improvements in learning and memory, contributing further to the growing body of evidence suggesting beneficial effects of flavonoids in cognition and brain health.

Lattice Boltzmann simulation of viscous fluid systems with elastic boundaries

A lattice Boltzmann model able to simulate viscous fluid systems with elastic and movable boundaries is proposed. By introducing the virtual distribution function at the boundary, the Galilean invariance is recovered for the full system. As examples of application, the how in elastic vessels is simulated with the pressure-radius relationship similar to that of the pulmonary blood vessels. The numerical results for steady how are in good agreement with the analytical prediction, while the simulation results for pulsative how agree with the experimental observation of the aortic flows qualitatively. The approach has potential application in the study of the complex fluid systems such as the suspension system as well as the arterial blood flow.