The effectiveness of non-executive directors in Chinese state-owned enterprises

Purpose – The primary aim of this paper is to examine whether boards of directors with independent members function as effective corporate governance mechanisms in Chinese State-Owned Enterprises(SOEs), by analysing four characteristics of non-executive directors (NEDs) that impact on their effectiveness, namely their degree of independence, information, incentive, and competence. Design/methodology/approach – Being exploratory in nature, the research uses qualitative methods for data collection. It is based on an interpretivist perspective of social sciences, analysing and explaining the factors that influence the effectiveness of NEDs. Findings – The findings indicate that the NED system is weak in China as a result of the concentrated ownership structure, unique business culture, intervention of controlling shareholders and the lack of understanding of the benefits brought by NEDs. Research limitations/implications – The paper examines the salient features of and challenges to the system of NEDs of SOEs in present-day China. It provides an understanding of how the various perceptions of the board, gathered from in-depth interviews of corporate directors, leads to new interpretations of board effectiveness. The research, however, is limited owing to a relatively small sample size and the sensitive nature of the information collected. Originality/value – The study aims to fill gaps in the literature and contribute to it by assessing the “real” views and perceptions of NEDs in China in an institutional environment significantly different from that of the USA, the UK and other western economies.

The state estimation of flow demands in gas networks from sparse pressure telemetry

This paper presents novel observer-based techniques for the estimation of flow demands in gas networks, from sparse pressure telemetry. A completely observable model is explored, constructed by incorporating difference equations that assume the flow demands are steady. Since the flow demands usually vary slowly with time, this is a reasonable approximation. Two techniques for constructing robust observers are employed: robust eigenstructure assignment and singular value assignment. These techniques help to reduce the effects of the system approximation. Modelling error may be further reduced by making use of known profiles for the flow demands. The theory is extended to deal successfully with the problem of measurement bias. The pressure measurements available are subject to constant biases which degrade the flow demand estimates, and such biases need to be estimated. This is achieved by constructing a further model variation that incorporates the biases into an augmented state vector, but now includes information about the flow demand profiles in a new form.

Vertical propagation of information in a middle atmosphere data assimilation system by gravity-wave drag feedbacks

The mesospheric response to the 2002 Antarctic Stratospheric Sudden Warming (SSW) is analysed using the Canadian Middle Atmosphere Model Data Assimilation System (CMAM-DAS), where it represents a vertical propagation of information from the observations into the data-free mesosphere. The CMAM-DAS simulates a cooling in the lowest part of the mesosphere which is accomplished by resolved motions, but which is extended to the mid- to upper mesosphere by the response of the model's non-orographic gravity-wave drag parameterization to the change in zonal winds. The basic mechanism is that elucidated by Holton consisting of a net eastward wave-drag anomaly in the mesosphere during the SSW, although in this case there is a net upwelling in the polar mesosphere. Since the zonal-mean mesospheric response is shown to be predictable, this demonstrates that variations in the mesospheric state can be slaved to the lower atmosphere through gravity-wave drag.

Conflict resolution in overlapping information fields for context-based activity design

Norms are a set of rules that govern the behaviour of human agent, and how human agent behaves in response to the given certain conditions. This paper investigates the overlapping of information fields (set of shared norms) in the Context State Transition Model, and how these overlapping fields may affect the choices and actions of human agent. This paper also includes discussion on the implementation of new conflict resolution strategies based on the situation specification. The reasoning about conflicting norms in multiple information fields is discussed in detail.)

Information communication technologies and distance education in Sri Lanka: a case study of two universities

Sri Lanka's participation rates in higher education are low and have risen only slightly in the last few decades; the number of places for higher education in the state university system only caters for around 3% of the university entrant age cohort. The literature reveals that the highly competitive global knowledge economy increasingly favours workers with high levels of education who are also lifelong learners. This lack of access to higher education for a sizable proportion of the labour force is identified as a severe impediment to Sri Lanka‟s competitiveness in the global knowledge economy. The literature also suggests that Information and Communication Technologies are increasingly relied upon in many contexts in order to deliver flexible learning, to cater especially for the needs of lifelong learners in today‟s higher educational landscape. The government of Sri Lanka invested heavily in ICTs for distance education during the period 2003-2009 in a bid to increase access to higher education; but there has been little research into the impact of this. To address this lack, this study investigated the impact of ICTs on distance education in Sri Lanka with respect to increasing access to higher education. In order to achieve this aim, the research focused on Sri Lanka‟s effort from three perspectives: policy perspective, implementation perspective and user perspective. A multiple case study research using an ethnographic approach was conducted to observe Orange Valley University‟s and Yellow Fields University‟s (pseudonymous) implementation of distance education programmes using questionnaires, qualitative interviewing and document analysis. In total, data for the analysis was collected from 129 questionnaires, 33 individual interviews and 2 group interviews. The research revealed that ICTs have indeed increased opportunities for higher education; but mainly for people of affluent families from the Western Province. Issues identified were categorized under the themes: quality assurance, location, language, digital literacies and access to resources. Recommendations were offered to tackle the identified issues in accordance with the study findings. The study also revealed the strong presence of a multifaceted digital divide in the country. In conclusion, this research has shown that iii although ICT-enabled distance education has the potential to increase access to higher education the present implementation of the system in Sri Lanka has been less than successful.

Information-based data selection for ensemble data assimilation

Ensemble-based data assimilation is rapidly proving itself as a computationally-efficient and skilful assimilation method for numerical weather prediction, which can provide a viable alternative to more established variational assimilation techniques. However, a fundamental shortcoming of ensemble techniques is that the resulting analysis increments can only span a limited subspace of the state space, whose dimension is less than the ensemble size. This limits the amount of observational information that can effectively constrain the analysis. In this paper, a data selection strategy that aims to assimilate only the observational components that matter most and that can be used with both stochastic and deterministic ensemble filters is presented. This avoids unnecessary computations, reduces round-off errors and minimizes the risk of importing observation bias in the analysis. When an ensemble-based assimilation technique is used to assimilate high-density observations, the data-selection procedure allows the use of larger localization domains that may lead to a more balanced analysis. Results from the use of this data selection technique with a two-dimensional linear and a nonlinear advection model using both in situ and remote sounding observations are discussed.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Accounting information systems as institutional carriers: a case study of regulatory compliance in UK asset management houses

Previously, governments have responded to the impacts of economic failures and consequently have developed more regulations to protect employees, customers, shareholders and the economic wellbeing of the state. Our research addresses how Accounting Information Systems (AIS) may act as carriers for institutionalised practices associated with maintaining regulatory compliance within the context of UK Asset Management Houses. The AIS was found to be a strong conduit for institutionalized compliance related practices, utilising symbolic systems, relational systems, routines and artefacts to carry approaches relating to regulative, normative and cultural-cognitive strands of institutionalism. Thus, AIS are integral to the development and dissipation of best practice for the management of regulatory compliance. As institutional elements are clearly present we argue that AIS and regulatory compliance provide a rich context to further institutionalism. Since AIS may act as conduits for regulatory approaches, both systems adopters and clients may benefit from actively seeking to codify and abstract best practices into AIS. However, the application of generic institutionalized approaches, which may be applied across similar organizations, must be tempered with each firm’s business environment and associated regulatory exposure. A balance should be sought between approaches specific enough to be useful but generic enough to be universally applied.

NK1 receptor antagonism and the neural processing of emotional information in healthy volunteers

The neuropeptide substance P and its receptor NK1 have been implicated in emotion, anxiety and stress in preclinical studies. However, the role of NK1 receptors in human brain function is less clear and there have been inconsistent reports of the value of NK1 receptor antagonists in the treatment of clinical depression. The present study therefore aimed to investigate effects of NK1 antagonism on the neural processing of emotional information in healthy volunteers. Twenty-four participants were randomized to receive a single dose of aprepitant (125 mg) or placebo. Approximately 4 h later, neural responses during facial expression processing and an emotional counting Stroop word task were assessed using fMRI. Mood and subjective experience were also measured using self-report scales. As expected a single dose of aprepitant did not affect mood and subjective state in the healthy volunteers. However, NK1 antagonism increased responses specifically during the presentation of happy facial expressions in both the rostral anterior cingulate and the right amygdala. In the emotional counting Stroop task the aprepitant group had increased activation in both the medial orbitofrontal cortex and the precuneus cortex to positive vs. neutral words. These results suggest consistent effects of NK1 antagonism on neural responses to positive affective information in two different paradigms. Such findings confirm animal studies which support a role for NK1 receptors in emotion. Such an approach may be useful in understanding the effects of novel drug treatments prior to full-scale clinical trials.

An evaluation of decadal probability forecasts from state-of-the-art climate models

While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 years, nontrivial structural flaws still hinder their ability to forecast the decadal dynamics of the Earth system realistically. Contrasting the skill of these models not only with each other but also with empirical models can reveal the space and time scales on which simulation models exploit their physical basis effectively and quantify their ability to add information to operational forecasts. The skill of decadal probabilistic hindcasts for annual global-mean and regional-mean temperatures from the EU Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project is contrasted with several empirical models. Both the ENSEMBLES models and a “dynamic climatology” empirical model show probabilistic skill above that of a static climatology for global-mean temperature. The dynamic climatology model, however, often outperforms the ENSEMBLES models. The fact that empirical models display skill similar to that of today's state-of-the-art simulation models suggests that empirical forecasts can improve decadal forecasts for climate services, just as in weather, medium-range, and seasonal forecasting. It is suggested that the direct comparison of simulation models with empirical models becomes a regular component of large model forecast evaluations. Doing so would clarify the extent to which state-of-the-art simulation models provide information beyond that available from simpler empirical models and clarify current limitations in using simulation forecasting for decision support. Ultimately, the skill of simulation models based on physical principles is expected to surpass that of empirical models in a changing climate; their direct comparison provides information on progress toward that goal, which is not available in model–model intercomparisons.

State of the art of learning styles-based adaptive educational hypermedia systems (Ls-Baehss)

The notion that learning can be enhanced when a teaching approach matches a learner’s learning style has been widely accepted in classroom settings since the latter represents a predictor of student’s attitude and preferences. As such, the traditional approach of ‘one-size-fits-all’ as may be applied to teaching delivery in Educational Hypermedia Systems (EHSs) has to be changed with an approach that responds to users’ needs by exploiting their individual differences. However, establishing and implementing reliable approaches for matching the teaching delivery and modalities to learning styles still represents an innovation challenge which has to be tackled. In this paper, seventy six studies are objectively analysed for several goals. In order to reveal the value of integrating learning styles in EHSs, different perspectives in this context are discussed. Identifying the most effective learning style models as incorporated within AEHSs. Investigating the effectiveness of different approaches for modelling students’ individual learning traits is another goal of this study. Thus, the paper highlights a number of theoretical and technical issues of LS-BAEHSs to serve as a comprehensive guidance for researchers who interest in this area.

Conditioning and preconditioning of the optimal state estimation problem

Optimal state estimation is a method that requires minimising a weighted, nonlinear, least-squares objective function in order to obtain the best estimate of the current state of a dynamical system. Often the minimisation is non-trivial due to the large scale of the problem, the relative sparsity of the observations and the nonlinearity of the objective function. To simplify the problem the solution is often found via a sequence of linearised objective functions. The condition number of the Hessian of the linearised problem is an important indicator of the convergence rate of the minimisation and the expected accuracy of the solution. In the standard formulation the convergence is slow, indicating an ill-conditioned objective function. A transformation to different variables is often used to ameliorate the conditioning of the Hessian by changing, or preconditioning, the Hessian. There is only sparse information in the literature for describing the causes of ill-conditioning of the optimal state estimation problem and explaining the effect of preconditioning on the condition number. This paper derives descriptive theoretical bounds on the condition number of both the unpreconditioned and preconditioned system in order to better understand the conditioning of the problem. We use these bounds to explain why the standard objective function is often ill-conditioned and why a standard preconditioning reduces the condition number. We also use the bounds on the preconditioned Hessian to understand the main factors that affect the conditioning of the system. We illustrate the results with simple numerical experiments.

Geographical distribution of American cutaneous leishmaniasis and its phlebotomine vectors (Diptera: Psychodidae) in the state of Sao Paulo, Brazil

Background: American cutaneous leishmaniasis (ACL) is a re-emerging disease in the state of Sao Paulo, Brazil. It is important to understand both the vector and disease distribution to help design control strategies. As an initial step in applying geographic information systems (GIS) and remote sensing (RS) tools to map disease-risk, the objectives of the present work were to: (i) produce a single database of species distributions of the sand fly vectors in the state of Sao Paulo, (ii) create combined distributional maps of both the incidence of ACL and its sand fly vectors, and (iii) thereby provide individual municipalities with a source of reference material for work carried out in their area. Results: A database containing 910 individual records of sand fly occurrence in the state of Sao Paulo, from 37 different sources, was compiled. These records date from between 1943 to 2009, and describe the presence of at least one of the six incriminated or suspected sand fly vector species in 183/645 (28.4%) municipalities. For the remaining 462 (71.6%) municipalities, we were unable to locate records of any of the six incriminated or suspected sand fly vector species (Nyssomyia intermedia, N. neivai, N. whitmani, Pintomyia fischeri, P. pessoai and Migonemyia migonei). The distribution of each of the six incriminated or suspected vector species of ACL in the state of Sao Paulo were individually mapped and overlaid on the incidence of ACL for the period 1993 to 1995 and 1998 to 2007. Overall, the maps reveal that the six sand fly vector species analyzed have unique and heterogeneous, although often overlapping, distributions. Several sand fly species - Nyssomyia intermedia and N. neivai - are highly localized, while the other sand fly species - N. whitmani, M. migonei, P. fischeri and P. pessoai - are much more broadly distributed. ACL has been reported in 160/183 (87.4%) of the municipalities with records for at least one of the six incriminated or suspected sand fly vector species, while there are no records of any of these sand fly species in 318/478 (66.5%) municipalities with ACL. Conclusions: The maps produced in this work provide basic data on the distribution of the six incriminated or suspected sand fly vectors of ACL in the state of Sao Paulo, and highlight the complex and geographically heterogeneous pattern of ACL transmission in the region. Further studies are required to clarify the role of each of the six suspected sand fly vector species in different regions of the state of Sao Paulo, especially in the majority of municipalities where ACL is present but sand fly vectors have not yet been identified.

Detection of a new mumps virus genotype during parotitis epidemic of 2006-2007 in the state of Sao Paulo, Brazil

Nucleoticle sequence analyses of the SH gene of 18 mumps virus isolates collected in the 2006-2007 parotitis epidemic in the state of Sao Paulo identified a new genotype, designated genotype M. This new designation fulfills all the parameters required to define a new mumps virus genotype. The parameters were established by an expert panel in collaboration with the World Health Organization (WHO) in 2005. This information will enhance the mumps virus surveillance program both at the national and global levels.

Prevalence of untreated caries in deciduous teeth in urban and rural areas in the state of Sao Paulo, Brazil

Objectives. To describe the prevalence of dental caries in children with deciduous teeth in urban and rural areas in the state of Sao Paulo, Brazil, and to identify associated factors. Methods. The study included 24 744 children ( 5 - 7 years of age) examined as part of an epidemiological survey on oral health carried out in the state of Sao Paulo ( Levan-tamento Epidemiologico de Sa de Bucal do Estado de Sao Paulo). Multilevel analysis was used to investigate whether the prevalence of untreated caries was associated with the sociodemographic characteristics of the children examined or with the socioeconomic aspects of the participating cities. Results. Being black or brown ( adjusted odds ratio ( OR) = 1.27), attending school in rural areas ( adjusted OR = 1.88), and attending public school ( adjusted OR = 3.41) were identified as determinants for an increased probability of presenting deciduous teeth with untreated caries. Being a female ( adjusted OR = 0.83) was identified as a protective factor. The negative coefficients obtained for second- level independent variables indicate that the oral health profile of the cities included in the study were positively impacted by a higher municipal human development index ( beta = - 0.47) and fluoridated drinking water ( beta = - 0.32). Conclusions. The prevalence of untreated caries is influenced by individual and sociodemographic factors. The present study provides epidemiological information concerning the rural areas in the state of Sao Paulo. This information is useful for strategic planning and for establishing guidelines for oral health actions in local health systems, thereby contributing to oral health equity.