Intensive case management for severe psychotic illness: is there a general benefit for patients with complex needs? A secondary analysis of the UK700 trial data

The UK700 trial failed to demonstrate an overall benefit of intensive case management (ICM) in patients with severe psychotic illness. This does not discount a benefit for particular subgroups, and evidence of a benefit of ICM for patients of borderline intelligence has been presented. The aim of this study is to investigate whether this effect is part of a general benefit for patients with severe psychosis complicated by additional needs. In the UK700 trial patients with severe psychosis were randomly allocated to ICM or standard case management. For each patient group with complex needs the effect of ICM is compared with that in the rest of the study cohort. Outcome measures are days spent in psychiatric hospital and the admission and discharge rates. ICM may be of benefit to patients with severe psychosis complicated by borderline intelligence or depression, but may cause patients using illicit drugs to spend more time in hospital. There was no convincing evidence of an effect of ICM in a further seven patient groups. ICM is not of general benefit to patients with severe psychosis complicated by additional needs. The benefit of ICM for patients with borderline intelligence is an isolated effect which should be interpreted cautiously until further data are available.

Enterprise intelligence: searching for a single version of the truth

Multiple versions of information and associated problems are well documented in both academic research and industry best practices. Many solutions have proposed a single version of the truth, with Business intelligence being adopted by many organizations. Business Intelligence (BI), however, is largely based on the collection of data, processing and presentation of information to meet different stakeholders’ requirement. This paper reviews the promise of Enterprise Intelligence, which promises to support decision-making based on a defined strategic understanding of the organizations goals and a unified version of the truth.

Economic transformation in Ghana: where will the path lead?

In the context of the Ghanaian government’s objective of structural transformation with an emphasis on manufacturing, this paper provides a case study of economic transformation in Ghana, exploring patterns of growth, sectoral transformation, and agglomeration. We document and examine why, despite impressive growth and poverty reduction figures, Ghana’s economy has exhibited less transformation than might be expected for a country that has recently achieved middle-income status. Ghana’s reduced share of agriculture in the economy, unlike many successfully transformed countries in Asia and Latin America, has been filled by services, while manufacturing has stagnated and even declined. Likely causes include weak transformation of the agricultural sector and therefore little development of agroprocessing, the emergence of consumption cities and consumption-driven growth, upward pressure on the exchange rate, weak production linkages, and a poor environment for private-sector-led manufacturing.

Societal transformation in response to global environmental change: a review of emerging concepts

The study of societal transformation in response to environmental change has become established, yet little consensus exists regarding the conceptual basis of transformation. This paper aims to provide structure to the dialog on transformation, and to reflect on the challenges of social research in this area. Concepts of transformation are identified through a literature review, and examined using four analytical criteria. It is found that the term ‘transformation’ is frequently used merely as a metaphor. When transformation is not used as a metaphor, eight concepts are most frequently employed. They differ with respect to (i) system conceptualization, (ii) notions of social consciousness (deliberate/emergent), and (iii) outcome (prescriptive/descriptive). Problem-based research tends to adopt concepts of deliberate transformation with prescriptive outcome, while concepts of emergent transformation with no prescriptive outcome tend to inform descriptive-analytical research. Dialog around the complementarities of different concepts and their empirical testing are priorities for future research.

Economic Transformation in Ghana: Where Will the Path Lead?

In the context of the Ghanaian government’s objective of structural transformation with an emphasis on manufacturing, this paper provides a case study of economic transformation in Ghana, exploring patterns of growth, sector transformation, and agglomeration. We document and examine why, despite impressive growth and poverty reduction figures, Ghana’s economy has exhibited less transformation than might be expected for a country that has recently achieved middle-income status. Ghana’s reduced share of agriculture in the economy, unlike many successfully transformed countries in Asia and Latin America, has been filled by services, while manufacturing has stagnated and even declined. Likely causes include weak transformation of the agricultural sector and therefore little development of agro-processing, the emergence of “consumption cities” and consumption-driven growth, upward pressure on the exchange rate, weak production linkages, and a poor environment for private-sector-led manufacturing.

Pocket data mining: towards collaborative data mining in mobile computing environments

Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.

Behavioral and spatial analysis of extraterritorial movements in red foxes (Vulpes vulpes)

Abstract: Movements away from the natal or home territory are important to many ecological processes, including gene flow, population regulation, and disease epidemiology, yet quantitative data on these behaviors are lacking. Red foxes exhibit 2 periods of extraterritorial movements: when an individual disperses and when males search neighboring territories for extrapair copulations during the breeding season. Using radiotracking data collected at 5-min interfix intervals, we compared movement parameters, including distance moved, speed of movement, and turning angles, of dispersal and reproductive movements to those made during normal territorial movements; the instantaneous separation distances of dispersing and extraterritorial movements to the movements of resident adults; and the frequency of locations of 95%, 60%, and 30% harmonic mean isopleths of adult fox home territories to randomly generated fox movements. Foxes making reproductive movements traveled farther than when undertaking other types of movement, and dispersal movements were straighter. Reproductive and dispersal movements were faster than territorial movements and also differed in intensity of search and thoroughness. Foxes making dispersal movements avoided direct contact with territorial adults and moved through peripheral areas of territories. The converse was true for reproductive movements. Although similar in some basic characteristics, dispersal and reproductive movements are fundamentally different both behaviorally and spatially and are likely to have different ultimate purposes and contrasting effects on spatial processes such as disease transmission

Changes in gene expression in Arabidopsis shoots during phosphate starvation and the potential for developing smart plants

Our aim was to generate and prove the concept of "smart" plants to monitor plant phosphorus (P) status in Arabidopsis. Smart plants can be genetically engineered by transformation with a construct containing the promoter of a gene up-regulated specifically by P starvation in an accessible tissue upstream of a marker gene such as beta-glucuronidase (GUS). First, using microarrays, we identified genes whose expression changed more than 2.5-fold in shoots of plants growing hydroponically when P, but not N or K, was withheld from the nutrient solution. The transient changes in gene expression occurring immediately (4 h) after P withdrawal were highly variable, and many nonspecific, shock-induced genes were up-regulated during this period. However, two common putative cis-regulatory elements (a PHO-like element and a TATA box-like element) were present significantly more often in the promoters of genes whose expression increased 4 h after the withdrawal of P compared with their general occurrence in the promoters of all genes represented on the microarray. Surprisingly, the expression of only four genes differed between shoots of P-starved and -replete plants 28 h after P was withdrawn. This lull in differential gene expression preceded the differential expression of a new group of 61 genes 100 h after withdrawing P. A literature survey indicated that the expression of many of these "late" genes responded specifically to P starvation. Shoots had reduced P after 100 h, but growth was unaffected. The expression of SQD1, a gene involved in the synthesis of sulfolipids, responded specifically to P starvation and was increased 100 h after withdrawing P. Leaves of Arabidopsis bearing a SQD1::GUS construct showed increased GUS activity after P withdrawal, which was detectable before P starvation limited growth. Hence, smart plants can monitor plant P status. Transferring this technology to crops would allow precision management of P fertilization, thereby maintaining yields while reducing costs, conserving natural resources, and preventing pollution.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

The engagement of territorial knowledge communities with European spatial planning and the territorial cohesion debate: a Baltic perspective

Recent, dramatic spatial development trends have contributed to the consolidation of a unique territorial governance landscape in the Baltic States. The paper examines the transformation of this evolving institutional landscape for planning practice and knowledge, which has been marked by the disintegration of Soviet institutions and networks, the transition to a market-based economy and the process of accession to the EU. It explores the evolution of territorial knowledge channels in the Baltic States, and the extent and nature of the engagement of actors' communities with the main knowledge arenas and resources of European spatial planning (ESP). The paper concludes that recent shifts in the evolution of these channels suggest the engagement of ESP has concentrated among epistemic communities at State and trans-national levels of territorial governance. The limited policy coordination across a broader spectrum of diverse actors is compounded by institutionally weak and fragmented professional communities of practice, fragmented government structures and marginalized advocacy coalitions.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

BSkyB transformation from a new loss-making venture to a successful organisation: case study and interview with Jeremy Darroch, Chief Executive of British Sky Broadcasting Group Plc

Purpose – This paper aims to articulate strategic dilemmas faced by a Chief Executive of a highly successful company and how such dilemmas were resolved. Design/methodology/approach – The case is based on a semi-structured interview with Mr Jeremy Darroch – Chief Executive of BSkyB – and analysis of documentary evidence. Findings – It is often difficult to implement strategies that simultaneously yield high organic growth rate, innovation, and a healthy balance-sheet. The paper sheds light on how Sky has met this challenge. Research limitations/implications – The research offers a unique insight into the views of a principal strategist and articulates the background to offer context, however, because of its design the findings are not generalisable. Originality/value – Very few articles offer insight into the thinking of those with principal responsibility for design and delivery of strategy. This paper offers such an insight based on a detailed interview with a highly successful Chief Executive.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.