The Management of Long-Term Sickness Absence in Large Public Sector Healthcare Organisations: A Realist Evaluation Using Mixed Methods

Purpose The success of measures to reduce long-term sickness absence (LTSA) in public sector organisations is contingent on organisational context. This realist evaluation investigates how interventions interact with context to influence successful management of LTSA. Methods Multi-method case study in three Health and Social Care Trusts in Northern Ireland comprising realist literature review, semi-structured interviews (61 participants), Process-Mapping and feedback meetings (59 participants), observation of training, analysis of documents. Results Important activities included early intervention; workplace-based occupational rehabilitation; robust sickness absence policies with clear trigger points for action. Used appropriately, in a context of good interpersonal and interdepartmental communication and shared goals, these are able to increase the motivation of staff to return to work. Line managers are encouraged to take a proactive approach when senior managers provide support and accountability. Hindering factors: delayed intervention; inconsistent implementation of policy and procedure; lack of resources; organisational complexity; stakeholders misunderstanding each other’s goals and motives. Conclusions Different mechanisms have the potential to encourage common motivations for earlier return from LTSA, such as employees feeling that they have the support of their line manager to return to work and having the confidence to do so. Line managers’ proactively engage when they have confidence in the support of seniors and in their own ability to address LTSA. Fostering these motivations calls for a thoughtful, diagnostic process, taking into account the contextual factors (and whether they can be modified) and considering how a given intervention can be used to trigger the appropriate mechanisms.

Application of connectivity mapping in predictive toxicology based on gene-expression similarity.

Connectivity mapping is the process of establishing connections between different biological states using gene-expression profiles or signatures. There are a number of applications but in toxicology the most pertinent is for understanding mechanisms of toxicity. In its essence the process involves comparing a query gene signature generated as a result of exposure of a biological system to a chemical to those in a database that have been previously derived. In the ideal situation the query gene-expression signature is characteristic of the event and will be matched to similar events in the database. Key criteria are therefore the means of choosing the signature to be matched and the means by which the match is made. In this article we explore these concepts with examples applicable to toxicology.

Identification of candidate small-molecule therapeutics to cancer by gene-signature perturbation in connectivity mapping.

Connectivity mapping is a recently developed technique for discovering the underlying connections between different biological states based on gene-expression similarities. The sscMap method has been shown to provide enhanced sensitivity in mapping meaningful connections leading to testable biological hypotheses and in identifying drug candidates with particular pharmacological and/or toxicological properties. Challenges remain, however, as to how to prioritise the large number of discovered connections in an unbiased manner such that the success rate of any following-up investigation can be maximised. We introduce a new concept, gene-signature perturbation, which aims to test whether an identified connection is stable enough against systematic minor changes (perturbation) to the gene-signature. We applied the perturbation method to three independent datasets obtained from the GEO database: acute myeloid leukemia (AML), cervical cancer, and breast cancer treated with letrozole. We demonstrate that the perturbation approach helps to identify meaningful biological connections which suggest the most relevant candidate drugs. In the case of AML, we found that the prevalent compounds were retinoic acids and PPAR activators. For cervical cancer, our results suggested that potential drugs are likely to involve the EGFR pathway; and with the breast cancer dataset, we identified candidates that are involved in prostaglandin inhibition. Thus the gene-signature perturbation approach added real values to the whole connectivity mapping process, allowing for increased specificity in the identification of possible therapeutic candidates.

Business representation and the UK regions: mapping institutional change

Political devolution in Scotland, Wales and Northern Ireland and the developing regional agenda in England are prompting changes in the organization of business interest representation within the devolved and decentralized territories. In this paper we seek to describe the realignment of business interest representation at the 'regional' scale, first through a detailed review of changes underway across specific business associations and representative fora, and secondly through an initial attempt to compare and 'map' the patterns of institutional change recorded in the various territories. In broad terms the overall scale, operation and degree of formalization of the new political arrangements for business representation tend broadly to reflect the established institutional and political contexts of the respective nations and regions and the level of devolution ceded to the territories. However, there are important variations in a complex process of uneven development. In the concluding section we present some initial thoughts on the nature of the changes observed in the institutional framework for business representation. A key argument is that to date such changes suggest a reconfiguration of business political activity rather than a step-change in the institutional foundation for sub-national business interest representation in the UK. (C) 2003 Elsevier Ltd. All rights reserved.

A Competence-Based Post-Disaster Reconstruction Process: Findings from Sri Lanka

As natural disasters continue to escalate in frequency and magnitude, NGOs are faced with numerous barriers as they attempt to implement post-disaster reconstruction (PDR) projects. In many cases, a lack of competency in key areas leads to a reduction in overall project success. This paper utilizes the competency-based framework of von Meding et al. (2010) as the starting point of its inquiry. In this context, a leading NGO responsible for the implementation of reconstruction and rehabilitation in Sri Lanka following the Asian Tsunami has been investigated in depth using a causal mapping interview procedure with key project staff. The combined barriers within this organization’s PDR operations have been identified and measured and solutions articulated. The study found that within this organization key objectives were to achieve the ‘build back better’ mantra and to effectively plan interventions in advance. The primary barriers to successful reconstruction were identified as the high turnover rate of humanitarian staff and a poor level of communication and co-operation between agencies. An essential strategy employed to combat these barriers is the consideration of staff capabilities, which links us back to competence-based theory. The results are highly valuable in the context of an ongoing wider research study on competence within humanitarian organizations.

Mapping Irreversible Electrochemical Processes on the Nanoscale: Ionic Phenomena in Li Ion Conductive Glass Ceramics

A scanning probe microscopy approach for mapping local irreversible electrochemical processes based on detection of bias-induced frequency shifts of cantilevers in contact with the electrochemically active surface is demonstrated. Using Li ion conductive glass ceramic as a model, we demonstrate near unity transference numbers for ionic transport and establish detection limits for current-based and strain-based detection. The tip-induced electrochemical process is shown to be a first-order transformation and nucleation potential is close to the Li metal reduction potential. Spatial variability of the nucleation bias is explored and linked to the local phase composition. These studies both provide insight into nanoscale ionic phenomena in practical Li-ion electrolyte and also open pathways for probing irreversible electrochemical, bias-induced, and thermal transformations in nanoscale systems.

Nanoscale mapping of oxygen vacancy kinetics in nanocrystalline Samarium doped ceria thin films

The position-dependent oxygen vacancy dynamics induced by a biased scanning probe microscopy tip in Samarium doped ceria thin films grown on MgO (100) substrates is investigated. The granularity of the samples gives rise to spatially dependent local electrochemical activity, as explored by electrochemical strain microscopy. The kinetics of the oxygen vacancy relaxation process is investigated separately for grain boundaries and grains. Higher oxygen vacancy concentration variation and slower diffusion are observed in the grain boundary regions as compared to the grains.

Evaluation of drilling process in Ti6Al4V using 3D FE simulation

Drilling of Ti6Al4V is investigated experimentally and numerically. A 3D finite element model developed based on Lagrangian approach using commercial finite element software ABAQUS/explicit. 3D complex drill geometry is included in the model. The drilling process simulations are performed at the combinations of three cutting speed and four feed rates. The effects of cutting parameters on the induced thrust force and torque are predicted by the developed model. For validation purpose, experimental trials have been performed in similar condition to the simulations. The forces and torques measured during experiment are compared to the results of the finite element analysis. The agreement of the experimental results for force and torque values with the FE results is very good. Moreover, surface roughness of the holes was measured for mapping of machining. Copyright © 2013 Inderscience Enterprises Ltd.

Data Mapping for Unreliable Memories

Future digital signal processing (DSP) systems must provide robustness on algorithm and application level to the presence of reliability issues that come along with corresponding implementations in modern semiconductor process technologies. In this paper, we address this issue by investigating the impact of unreliable memories on general DSP systems. In particular, we propose a novel framework to characterize the effects of unreliable memories, which enables us to devise novel methods to mitigate the associated performance loss. We propose to deploy specifically designed data representations, which have the capability of substantially improving the system reliability compared to that realized by conventional data representations used in digital integrated circuits, such as 2's-complement or sign-magnitude number formats. To demonstrate the efficacy of the proposed framework, we analyze the impact of unreliable memories on coded communication systems, and we show that the deployment of optimized data representations substantially improves the error-rate performance of such systems.

Optimizing the efficiency of the sub-map technique for large-scale simultaneous localization and mapping

A technique for optimizing the efficiency of the sub-map method for large-scale simultaneous localization and mapping (SLAM) is proposed. It optimizes the benefits of the sub-map technique to improve the accuracy and consistency of an extended Kalman filter (EKF)-based SLAM. Error models were developed and engaged to investigate some of the outstanding issues in employing the sub-map technique in SLAM. Such issues include the size (distance) of an optimal sub-map, the acceptable error effect caused by the process noise covariance on the predictions and estimations made within a sub-map, when to terminate an existing sub-map and start a new one and the magnitude of the process noise covariance that could produce such an effect. Numerical results obtained from the study and an error-correcting process were engaged to optimize the accuracy and convergence of the Invariant Information Local Sub-map Filter previously proposed. Applying this technique to the EKF-based SLAM algorithm (a) reduces the computational burden of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. A Monte Carlo analysis of the system is presented as a means of demonstrating the consistency and efficacy of the proposed technique.

Composing with Graphics: Revealing the Compositional Process through Performance.

The research presented here is product of a practice-based process that primarily generates knowledge through collaboration and exchange in performance situations. This collaboration and exchange with various musicians over a period of five years that constitutes a body of practice that is here reflected upon. The paper focuses on non-instructional graphic scores and presents some insights based on performances of works by the author. We address how composition processes are revealed in graphic scores by looking at the conditions of decision making at the point of preparing a performance. We argue that three key elements are at play in the interpretation of these types of graphic scores: performance practice, mapping and musical form. By reflecting particularly on the work Cipher Series (Rebelo, 2010) we offer insights into the strategies for approaching the performance of graphic scores that go beyond symbolic codification.

Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping

Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.

Free-stretch-blow Investigation of Poly(ethylene terephthalate) over a Large Process Window

This paper highlights for the first time a full comprehension of the deformation procedure during the injection stretch blow moulding (ISBM) process of poly(ethylene terephthalate) (PET) containers, namely thin-walled rigid bottles. The processes required to form PET bottles are complicated and extensive; any development in understanding the nature of material deformation can potentially improve the bottle optimisation process. Removing the bottle mould and performing free-stretch-blow (FSB) experiments revealed insight into the bottle forming characteristics at various preform temperatures and blowing rates. Process outputs cavity pressure and stretch-rod force were recorded using at instrumented stretch-rod and preform surface strain mapping was determined using a combination of a unique patterning procedure and high speed stereoscopic digital image correlation. The unprecedented experimental analysis reveals that the deformation behaviour varies considerably with contrasting process input parameters. Investigation into the effect on deformation mode, strain rate and final bottle shape provide a basis for full understanding of the process optimisation and therefore how the process inputs may aid development of the preferred optimised container.