The structure and dynamics of 2-dimensional fluids in swelling clays

The interlayer pores of swelling 2:1 clays provide an ideal 2-dimensional environment in which to study confined fluids. In this paper we discuss our understanding of the structure and dynamics of interlayer fluid species in expanded clays, based primarily on the outcome of recent molecular modelling and neutron scattering studies. Counterion solvation is compared with that measured in bulk solutions, and at a local level the cation-oxygen coordination is found to be remarkably similar in these two environments. However, for the monovalent ions the contribution to the first coordination shell from the clay surfaces increases with counterion radius. This gives rise to inner-sphere (surface) complexes in the case of potassium and caesium. In this context, the location of the negative clay surface charge (i.e. arising from octahedral or tetrahedral substitution) is also found to be of major importance. Divalent cations, such as calcium, eagerly solvate to form outer-sphere complexes. These complexes are able to pin adjacent clay layers together, and thereby prevent colloidal swelling. Confined water molecules form hydrogen bonds to each other and to the clays' surfaces. In this way their local environment relaxes to close to the bulk water structure within two molecular layers of the clay surface. Finally, we discuss the way in which the simple organic molecules methane, methanol and ethylene glycol behave in the interlayer region of hydrated clays. Quasi-elastic neutron scattering of isotopically labelled interlayer CH 3OD and (CH2OD)2 in deuterated clay allows us to measure the diffusion of the CH3- and CH2-groups in both clay and liquid environments. We find that in both the one-layer methanol solvates and the two-layer glycol solvates the diffusion of the most mobile organic molecules is close to that in the bulk solution.

Low gravity rotational culture and the integration of immunomodulatory stem cells reduce human islet allo-reactivity

Modification of human islets prior to transplantation may improve long-term clinical outcome in terms of diabetes management, by supporting graft function and reducing the potential for allo-rejection. Intragraft incorporation of stem cells secreting beta (β)-cell trophic and immunomodulatory factors represents a credible approach, but requires suitable culture methods to facilitate islet alteration without compromising integrity. This study employed a three-dimensional rotational cell culture system (RCCS) to achieve modification, preserve function, and ultimately influence immune cell responsiveness to human islets. Islets underwent intentional dispersal and rotational culture-assisted aggregation with amniotic epithelial cells (AEC) exhibiting intrinsic immunomodulatory potential. Reassembled islet constructs were assessed for functional integrity, and their ability to induce an allo-response in discrete T-cell subsets determined using mixed islet:lymphocyte reaction assays. RCCS supported the formation of islet:AEC aggregates with improved insulin secretory capacity compared to unmodified islets. Further, the allo-response of peripheral blood mononuclear cell (PBMC) and purified CD4+ and CD8+ T-cell subsets to AEC-bearing grafts was significantly (p < 0.05) attenuated. Rotational culture enables pre-transplant islet modification involving their integration with immunomodulatory stem cells capable of subduing the allo-reactivity of T cells relevant to islet rejection. The approach may play a role in achieving acute and long-term graft survival in islet transplantation.

Mixed Fractional Integration Operators in Mixed Weighted Hölder Spaces

MSC 2010: 26A33

Integrated Dimensional Variation Management in the Digital Factory

This paper describes how dimensional variation management could be integrated throughout design, manufacture and verification, to improve quality while reducing cycle times and manufacturing cost in the Digital Factory environment. Initially variation analysis is used to optimize tolerances during product and tooling design and also results in the creation of a simplified representation of product key characteristics. This simplified representation can then be used to carry out measurability analysis and process simulation. The link established between the variation analysis model and measurement processes can subsequently be used throughout the production process to automatically update the variation analysis model in real time with measurement data. This ‘live’ simulation of variation during manufacture will allow early detection of quality issues and facilitate autonomous measurement assisted processes such as predictive shimming. A study is described showing how these principles can be demonstrated using commercially available software combined with a number of prototype applications operating as discrete modules. The commercially available modules include Catia/Delmia for product and process design, 3DCS for variation analysis and Spatial Analyzer for measurement simulation. Prototype modules are used to carry out measurability analysis and instrument selection. Realizing the full potential of Metrology in the Digital Factory will require that these modules are integrated and software architecture to facilitate this is described. Crucially this integration must facilitate the use of realtime metrology data describing the emerging assembly to update the digital model.

A Note on Bayesian Estimation for the Negative-Binomial Model

2000 Mathematics Subject Classification: 62F15.

Degree of vertical integration and its buffering effects on political uncertainty

The focus of this study is on the governance decisions in a concurrent channels context, in the case of uncertainty. The study examines how a firm chooses to deploy its sales force in times of uncertainty, and the subsequent performance outcome of those deployment choices. The theoretical framework is based on multiple theories of governance, including transaction cost analysis (TCA), agency theory, and institutional economics. Three uncertainty variables are investigated in this study. The first two are demand and competitive uncertainty which are considered to be industry-level market uncertainty forms. The third uncertainty, political uncertainty, is chosen as it is an important dimension of institutional environments, capturing non-economic circumstances such as regulations and political systemic issues. The study employs longitudinal secondary data from a Thai hotel chain, comprising monthly observations from January 2007 – December 2012. This hotel chain has its operations in 4 countries, Thailand, the Philippines, United Arab Emirates – Dubai, and Egypt, all of which experienced substantial demand, competitive, and political uncertainty during the study period. This makes them ideal contexts for this study. Two econometric models, both deploying Newey-West estimations, are employed to test 13 hypotheses. The first model considers the relationship between uncertainty and governance. The second model is a version of Newey-West, using an Instrumental Variables (IV) estimator and a Two-Stage Least Squares model (2SLS), to test the direct effect of uncertainty on performance and the moderating effect of governance on the relationship between uncertainty and performance. The observed relationship between uncertainty and governance observed follows a core prediction of TCA; that vertical integration is the preferred choice of governance when uncertainty rises. As for the subsequent performance outcomes, the results corroborate that uncertainty has a negative effect on performance. Importantly, the findings show that becoming more vertically integrated cannot help moderate the effect of demand and competitive uncertainty, but can significantly moderate the effect of political uncertainty. These findings have significant theoretical and practical implications, and extend our knowledge of the impact on uncertainty significantly, as well as bringing an institutional perspective to TCA. Further, they offer managers novel insight into the nature of different types of uncertainty, their impact on performance, and how channel decisions can mitigate these impacts.

Discovering biomarkers for antidepressant response:protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.

Leader-member exchange and attitudes:a theoretical and empirical integration

The central proposition of this thesis is that there are key benefits to examining leadership perceptions as an attitude towards the leader. In particular, it is argued that doing so can provide an enhanced understanding of leadership perceptions and therefore advance theory in this area. To provide empirical support for this theoretcial integration, the current research focused on one of the most popular leadership theories, leader-member exchange (LMX), and demonstrated how the concept of attitude strength could advance understanding of how and when LMX influenced employee job performance. Although the measurement of LMX requires employees to provide a cognitive evaluation of their relationship with their leader, previous research has, to date, not considered this evaluation to be an attitude. This thesis provides a justification for doing so and develops two novel constructs: LMX importance and LMX ambivalence. Both of these variables are argued to represent previously unconsidered facets of the LMX relationship, which, according to attitude theory, provide a more multifaceted understanding of leadership perceptions than previously envisaged. Such an understanding can provide a more detailed understanding of how such perceptions influence outcomes. Two studies provided an empirical test of the above reasoning. Study 1, a longitudinal field study, demonstrated initial support for many of the hypotheses. LMX amivalence was shown to lead to poorer task performance and organisational citizenship behaviour, mediated by the experience of negative affect. Evidence was also found for the moderating effect of LMX importance, although felt obligations was not found to mediate this moderated effect. While Study 1 used project groups as its participants, Study 2 provided a first test of the construct in an organisational setting; with three companies proving data. Again, strong support was found for the negative effects of LMX ambivalence on employee outcomes, with evidence also found for the role of perceived organisational support in mitigating these negative effects. Support was also found for the moderated mediation hypothesis related to LMX importance, although this was only found in the largest organisation sample. Some of the main theoretical and methodological implications of viewing leadership perceptions as attitudes to the wider leadership area were discussed. The cross-fertilisation of research from the attitudes literature to understanding leadership perceptions provides new insights into leadership processes and potential avenues for further research.

Effective knowledge integration in emergency response organizations

Natural and man-made disasters have gained attention at all levels of policy-making in recent years. Emergency management tasks are inherently complex and unpredictable, and often require coordination among multiple organizations across different levels and locations. Effectively managing various knowledge areas and the organizations involved has become a critical emergency management success factor. However, there is a general lack of understanding about how to describe and assess the complex nature of emergency management tasks and how knowledge integration can help managers improve emergency management task performance. ^ The purpose of this exploratory research was first, to understand how emergency management operations are impacted by tasks that are complex and inter-organizational and second, to investigate how knowledge integration as a particular knowledge management strategy can improve the efficiency and effectiveness of the emergency tasks. Three types of specific knowledge were considered: context-specific, technology-specific, and context-and-technology-specific. ^ The research setting was the Miami-Dade Emergency Operations Center (EOC) and the study was based on the survey responses from the participants in past EOC activations related to their emergency tasks and knowledge areas. The data included task attributes related to complexity, knowledge area, knowledge integration, specificity of knowledge, and task performance. The data was analyzed using multiple linear regressions and path analyses, to (1) examine the relationships between task complexity, knowledge integration, and performance, (2) the moderating effects of each type of specific knowledge on the relationship between task complexity and performance, and (3) the mediating role of knowledge integration. ^ As per theory-based propositions, the results indicated that overall component complexity and interactive complexity tend to have a negative effect on task performance. But surprisingly, procedural rigidity tended to have a positive effect on performance in emergency management tasks. Also as per our expectation, knowledge integration had a positive relationship with task performance. Interestingly, the moderating effects of each type of specific knowledge on the relationship between task complexity and performance were varied and the extent of mediation of knowledge integration depended on the dimension of task complexity. ^

Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.

Effective Knowledge Integration in Emergency Response Organizations

Natural and man-made disasters have gained attention at all levels of policy-making in recent years. Emergency management tasks are inherently complex and unpredictable, and often require coordination among multiple organizations across different levels and locations. Effectively managing various knowledge areas and the organizations involved has become a critical emergency management success factor. However, there is a general lack of understanding about how to describe and assess the complex nature of emergency management tasks and how knowledge integration can help managers improve emergency management task performance. The purpose of this exploratory research was first, to understand how emergency management operations are impacted by tasks that are complex and inter-organizational and second, to investigate how knowledge integration as a particular knowledge management strategy can improve the efficiency and effectiveness of the emergency tasks. Three types of specific knowledge were considered: context-specific, technology-specific, and context-and-technology-specific. The research setting was the Miami-Dade Emergency Operations Center (EOC) and the study was based on the survey responses from the participants in past EOC activations related to their emergency tasks and knowledge areas. The data included task attributes related to complexity, knowledge area, knowledge integration, specificity of knowledge, and task performance. The data was analyzed using multiple linear regressions and path analyses, to (1) examine the relationships between task complexity, knowledge integration, and performance, (2) the moderating effects of each type of specific knowledge on the relationship between task complexity and performance, and (3) the mediating role of knowledge integration. As per theory-based propositions, the results indicated that overall component complexity and interactive complexity tend to have a negative effect on task performance. But surprisingly, procedural rigidity tended to have a positive effect on performance in emergency management tasks. Also as per our expectation, knowledge integration had a positive relationship with task performance. Interestingly, the moderating effects of each type of specific knowledge on the relationship between task complexity and performance were varied and the extent of mediation of knowledge integration depended on the dimension of task complexity.

Graphene-MoS2 Hybrid Technology for Large-Scale Two-Dimensional Electronics

Two-dimensional (2D) materials have generated great interest in the last few years as a new toolbox for electronics. This family of materials includes, among others, metallic graphene, semiconducting transition metal dichalcogenides (such as MoS2) and insulating Boron Nitride. These materials and their heterostructures offer excellent mechanical flexibility, optical transparency and favorable transport properties for realizing electronic, sensing and optical systems on arbitrary surfaces. In this work, we develop several etch stop layer technologies that allow the fabrication of complex 2D devices and present for the first time the large scale integration of graphene with molybdenum disulfide (MoS2) , both grown using the fully scalable CVD technique. Transistor devices and logic circuits with MoS2 channel and graphene as contacts and interconnects are constructed and show high performances. In addition, the graphene/MoS2 heterojunction contact has been systematically compared with MoS2-metal junctions experimentally and studied using density functional theory. The tunability of the graphene work function significantly improves the ohmic contact to MoS2. These high-performance large-scale devices and circuits based on 2D heterostructure pave the way for practical flexible transparent electronics in the future. The authors acknowledge financial support from the Office of Naval Research (ONR) Young Investigator Program, the ONR GATE MURI program, and the Army Research Laboratory. This research has made use of the MI.

The art of building trust via e-communication channels: Post-acquisition integration as a special context

This study discusses the importance of establishing trust in post-acquisition integration context and how the use of e-channels facilitates or inhibits this process. The objective of this study is to analyze how the use of electronic communication channels influences the post-acquisition integration process in terms of trust establishment and overall integration efficiency, developing a framework as a result. Three sub-objectives are introduced: to find out the building blocks of trust in M&A’s, to analyse how the use of e-channels influence the process of trust establishment in post-acquisition integration context, and to define the consequences trust and use of e-channels have for the process. The theoretical background of the study includes literature and theories relating to trust establishment in post-acquisition integration context and how the use of e-channels influences the process of trust development on a general level. The empirical research is conducted as a single case study, based on key informant interviews. The interview data was collected between October 2015 and January 2016. Altogether nine interviews were realised; six with representatives from the acquiring firm and three with target firm members. Thematic analysis was selected as the main method for analysing and processing the qualitative data. This study finds that trust has an essential role in post-acquisition integration context, facilitating the integration process in various different ways. Hence, identifying the different building blocks of trust is important in order for members of the organisations to be better able establish and maintain trust. In today’s international business, the role of electronic communication channels has also increased in importance significantly and it was confirmed that these pose both challenges and possibilities for the development of interpersonal trust. One of the most important underlying factors influencing the trust levels via e-communication channels is the level of user’s comfort in using the different e-channels. Without sufficient and meaningful training, the communication conducted via these channels in inhibited in a number of ways. Hence, understanding the defining characteristics of e-communication together with the risks and opportunities related to the use of these can have far-reaching consequences for the post-acquisition integration process as a whole. The framework based on the findings and existing theory introduces the most central factors influencing the trust establishment together with the positive and negative consequences these have for the integration process. Moreover, organizational level consistency and the existence of shared guidelines on appropriate selection of communication channels according to the nature of the task at hand are seen as important

An Investigation into the Implementation of CYP-IAPT Routine Outcome Measures in their First Year of Integration into Child Psychotherapy Practice

This thesis examines the impact on child and adolescent psychotherapists within CAMHS of the introduction of routine outcome measures (ROMs) associated with the Children and Young People’s Improving access to Psychological Therapies programme (CYP-IAPT). All CAMHS therapists working within a particular NHS mental health Trust1 were required to trial CYP-IAPT ROMs as part of their everyday clinical practice from October 2013-September 2014. During this period considerable freedom was allowed as to which of the measures each therapist used and at what frequency. In order to assess the impact of CYP-IAPT ROMs on child psychotherapy, I conducted semi-structured interviews with eight psychotherapists within a particular CAMHS partnership within one NHS Trust. Each statement was coded and grouped according to whether it related to initial (generic) assessment, goal setting / monitoring, monitoring on-going progress, therapeutic alliance, or to issues concerning how data might be used or interpreted by managers and commissioners. Analysis of interviews revealed greatest concern about session-by session ROMs, as these are felt to impact most significantly on psychotherapy; therapists felt that session-by-session ROMs do not take account of negative transference relationships, they are overly repetitive and used to reward / punish the therapist. Measures used at assessment and review were viewed as most compatible with psychotherapy, although often experienced as excessively time consuming. The Goal Based Outcome Measure was generally experienced as compatible with psychotherapy so long as goals are formed collaboratively between therapist and young person. There was considerable anxiety about how data may be (mis)used and (mis)interpreted by managers and commissioners, for example to end treatment prematurely, trigger change of therapist in the face of negative ROMs data, or to damage psychotherapy. Use of ROMs for short term and generic work was experienced as less intrusive and contentious.

On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.