Cues and knowledge structures used by mental-health professionals when making risk assessments

Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

Finding structures in information networks using the affinity network

This thesis proposes a novel graphical model for inference called the Affinity Network,which displays the closeness between pairs of variables and is an alternative to Bayesian Networks and Dependency Networks. The Affinity Network shares some similarities with Bayesian Networks and Dependency Networks but avoids their heuristic and stochastic graph construction algorithms by using a message passing scheme. A comparison with the above two instances of graphical models is given for sparse discrete and continuous medical data and data taken from the UCI machine learning repository. The experimental study reveals that the Affinity Network graphs tend to be more accurate on the basis of an exhaustive search with the small datasets. Moreover, the graph construction algorithm is faster than the other two methods with huge datasets. The Affinity Network is also applied to data produced by a synchronised system. A detailed analysis and numerical investigation into this dynamical system is provided and it is shown that the Affinity Network can be used to characterise its emergent behaviour even in the presence of noise.

An investigation into inductive parameter learning in complex hierarchical knowledge structures representing clinical expertise

This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.

Relaxation procedures for an iterative MFS algorithm for the stable reconstruction of elastic fields from Cauchy data in two-dimensional isotropic linear elasticity

We investigate two numerical procedures for the Cauchy problem in linear elasticity, involving the relaxation of either the given boundary displacements (Dirichlet data) or the prescribed boundary tractions (Neumann data) on the over-specified boundary, in the alternating iterative algorithm of Kozlov et al. (1991). The two mixed direct (well-posed) problems associated with each iteration are solved using the method of fundamental solutions (MFS), in conjunction with the Tikhonov regularization method, while the optimal value of the regularization parameter is chosen via the generalized cross-validation (GCV) criterion. An efficient regularizing stopping criterion which ceases the iterative procedure at the point where the accumulation of noise becomes dominant and the errors in predicting the exact solutions increase, is also presented. The MFS-based iterative algorithms with relaxation are tested for Cauchy problems for isotropic linear elastic materials in various geometries to confirm the numerical convergence, stability, accuracy and computational efficiency of the proposed method.

Understanding manufacturing companies' environmental decision making structures

This paper provides an understanding of the current environmental decision structures within companies in the manufacturing sector. Through case study research, we explored the complexity, robustness and decision making processes companies were using in order to cope with ever increasing environmental pressures and choice of environmental technologies. Our research included organisations in UK, Thailand, and Germany. Our research strategy was case study composed of different research methods, namely: focus group, interviews and environmental report analysis. The research methods and their data collection instruments also varied according to the access we had. Our unity of analysis was decision making teams and the scope of our investigation included product development, environment & safety, manufacturing, and supply chain management. This study finds that environmental decision making have been gaining importance over the time as well as complexity when it is starting to move from manufacturing to non,manufacturing activities. Most companies do not have a formal structure to take environmental decisions; hence, they follow a similar path of other corporate decisions, being affected by organizational structures besides the technical competence of the teams. We believe our results will help improving structures in both beginners and leaders teams for environmental decision making across the different departments.

Copper(II) complexes with unsymmetrical pentadentate ed3a-type diamino-tricarboxylate ligands. Crystal structures, configurational analysis and DFT study of complexes

The O–O–N–N–O-type pentadentate ligands H3ed3a, H3pd3a and H3pd3p (H3ed3a stands ethylenediamine-N,N,N′-triacetic acid; H3pd3a stands 1,3-propanediamine-N,N,N′-triacetic acid and H3pd3p stands 1,3-propanediamine-N,N,N′-tri-3-propionic acid) and the corresponding novel octahedral or square-planar/trigonal-bipyramidal copper(II) complexes have been prepared and characterized. H3ed3a, H3pd3a and H3pd3p ligands coordinate to copper(II) ion via five donor atoms (three deprotonated carboxylate atoms and two amine nitrogens) affording octahedral in case of ed3a3− and intermediate square-pyramidal/trigonal-bipyramidal structure in case of pd3a3− and pd3p3−. A six coordinate, octahedral geometry has been established crystallographically for the [Mg(H2O)6][Cu(ed3a)(H2O)]2 · 2H2O complex and five coordinate square-pyramidal for the [Mg(H2O)5Cu(pd3a)][Cu(pd3a)] · 2H2O. Structural data correlating similar chelate Cu(II) complexes have been used for the better understanding the pathway: octahedral → square-pyramidal ↔ trigonal- bipyramid geometry. An extensive configuration analysis is discussed in relation to information obtained for similar complexes. The infra-red and electronic absorption spectra of the complexes are discussed in comparison with related complexes of known geometries. Molecular mechanics and density functional theory (DFT) programs have been used to model the most stable geometric isomer yielding, at the same time, significant structural data. The results from density functional studies have been compared with X-ray data.

Studies on the relative stabilities of Mn(II) and Mn(III) in complexes with N4O2 donor environments:crystal structures of [Mn(pybzhz)2] and [Mn(Ophsal)(imzH)2] ClO4 (pybzhz = N-(benzoyl)-N-(picolinylidene) hydrazine, Ophsal = N,N-o-phenylenebis(salicylideneimine), imzH = imidazole)

Five manganese complexes in an N 4O 2 donor environment have been prepared. Four of the compounds involve aroyl hydrazone as ligands and manganese is in a +2 oxidation state. The fifth compound was prepared using N,Nprime-o-phenylenebis(salicylideneimine) and imidazole as ligands where manganese is present in +3 oxidation state. X-ray crystal structure of one Mn +2 compound and the Mn +3 compound was determined. The relative stabilities of the Mn +2 and Mn +3 oxidation states were analyzed using the structural data and MO calculations. Manganese(II) complexes of four aroyl hydrazone ligands were prepared and characterized by different physicochemical techniques. The complexes are of the type Mn(L) 2, where L stands for the deprotonated hydrazone ligand. One of the compounds, Mn(pybzhz) 2, was also characterized by single crystal structure determination. In all these complexes, the Mn(II) is in an N 4O 2 donor environment and the Mn(II) center cannot be oxidized either chemically or electrochemically. However, when another ligand Ophsal is used to give the compound [Mn(Ophsal)(imzH) 2]ClO 4, which was also characterized by X-ray crystal structure determination, manganese can easily avail the +3 oxidation state. The relative stabilities of the +2 and +3 oxidation states of manganese were analyzed and it was concluded that the extent of distortion from the perfect octahedral geometry is the main controlling factor in these cases. © 2004 Elsevier B.V. All rights reserved.

Data Independence in the Multi-dimensional Numbered Information Spaces

The concept of data independence designates the techniques that allow data to be changed without affecting the applications that process it. The different structures of the information bases require corresponded tools for supporting data independence. A kind of information bases (the Multi-dimensional Numbered Information Spaces) are pointed in the paper. The data independence in such information bases is discussed.

Advances in characterisation, calibration and data processing speed of optical coherence tomography systems

This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

Algorithm BIDIMS for Automated Systematization of Data Array. Case Study: Rediscovering Mendeleev’s Periodic Table of Chemical Elements

The method (algorithm BIDIMS) of multivariate objects display to bidimensional structure in which the sum of differences of objects properties and their nearest neighbors is minimal is being described. The basic regularities on the set of objects at this ordering become evident. Besides, such structures (tables) have high inductive opportunities: many latent properties of objects may be predicted on their coordinates in this table. Opportunities of a method are illustrated on an example of bidimentional ordering of chemical elements. The table received in result practically coincides with the periodic Mendeleev table.

Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis

Renewable energy forms have been widely used in the past decades highlighting a "green" shift in energy production. An actual reason behind this turn to renewable energy production is EU directives which set the Union's targets for energy production from renewable sources, greenhouse gas emissions and increase in energy efficiency. All member countries are obligated to apply harmonized legislation and practices and restructure their energy production networks in order to meet EU targets. Towards the fulfillment of 20-20-20 EU targets, in Greece a specific strategy which promotes the construction of large scale Renewable Energy Source plants is promoted. In this paper, we present an optimal design of the Greek renewable energy production network applying a 0-1 Weighted Goal Programming model, considering social, environmental and economic criteria. In the absence of a panel of experts Data Envelopment Analysis (DEA) approach is used in order to filter the best out of the possible network structures, seeking for the maximum technical efficiency. Super-Efficiency DEA model is also used in order to reduce the solutions and find the best out of all the possible. The results showed that in order to achieve maximum efficiency, the social and environmental criteria must be weighted more than the economic ones.

Arthur Lindo Patterson, his function and element preferences in early crystal structures

In 1934, Arthur Lindo Patterson showed that a map of interatomic vectors is obtainable from measured X-ray diffraction data without phase information. Such maps were interpretable for simple crystal structures, but proliferation and overlapping of peaks caused confusion as the number of atoms increased. Since the peak height of a vector between two particular atoms is related to the product of their atomic numbers, a complicated structure could effectively be reduced to a simple one by including just a few heavy atoms (of high atomic number) since their interatomic vectors would stand out from the general clutter. Once located, these atoms provide approximate phases for Fourier syntheses that reveal the locations of additional atoms. Surveys of small-molecule structures in the Cambridge Structural Database during the periods 1936-1969, when Patterson methods were commonly used, and 1980-2013, dominated by direct methods, demonstrate large differences in the abundance of certain elements. The moderately heavy elements K, Rb, As and Br are the heaviest elements in the structure more than 3 times as often in the early period than in the recent period. Examples are given of three triumphs of the heavy atom method and two initial failures that had to be overcome. © 2014 © 2014 Taylor & Francis.

A semantic paradigm for intelligent data access

An implementation of Sem-ODB—a database management system based on the Semantic Binary Model is presented. A metaschema of Sem-ODB database as well as the top-level architecture of the database engine is defined. A new benchmarking technique is proposed which allows databases built on different database models to compete fairly. This technique is applied to show that Sem-ODB has excellent efficiency comparing to a relational database on a certain class of database applications. A new semantic benchmark is designed which allows evaluation of the performance of the features characteristic of semantic database applications. An application used in the benchmark represents a class of problems requiring databases with sparse data, complex inheritances and many-to-many relations. Such databases can be naturally accommodated by semantic model. A fixed predefined implementation is not enforced allowing the database designer to choose the most efficient structures available in the DBMS tested. The results of the benchmark are analyzed. ^ A new high-level querying model for semantic databases is defined. It is proven adequate to serve as an efficient native semantic database interface, and has several advantages over the existing interfaces. It is optimizable and parallelizable, supports the definition of semantic userviews and the interoperability of semantic databases with other data sources such as World Wide Web, relational, and object-oriented databases. The query is structured as a semantic database schema graph with interlinking conditionals. The query result is a mini-database, accessible in the same way as the original database. The paradigm supports and utilizes the rich semantics and inherent ergonomics of semantic databases. ^ The analysis and high-level design of a system that exploits the superiority of the Semantic Database Model to other data models in expressive power and ease of use to allow uniform access to heterogeneous data sources such as semantic databases, relational databases, web sites, ASCII files, and others via a common query interface is presented. The Sem-ODB engine is used to control all the data sources combined under a unified semantic schema. A particular application of the system to provide an ODBC interface to the WWW as a data source is discussed. ^

State legislative term limits and the law of unintended consequences: An examination of member behavior, power structures, and legislative organization in Florida

The implementation of term limits on state legislators has provided a wealth of data for study. Florida, the second largest state in the Union with term limits, has not been comprehensively studied. This research examines the effects of term limits on electoral competition, member composition, legislator career paths, legislative leadership, and intra- and inter-governmental influences on Florida's legislature. This study looks at the Florida legislature from 1992 when term limits were enacted through 2004, three electoral cycles in which term limits have been in effect. This study uses both quantitative and qualitative data where appropriate. Electoral data is used to assess electoral and demographic effects, as well as member career trajectories. Interview data with current and former legislators, lobbyists, and executive branch officials is used to analyze both changes in legislative organization and intra- and inter-governmental influences on the legislative process. Term limits has only created greater competition when a legislative seat opens and has actually created a greater advantage for incumbents. Women and minorities have only made minimal gains in winning seats post-term limits. Newly elected legislators are not political novices with a vast majority having previous elective experience. Leadership is more centralized under term limits and the Senate has gained an advantage over the more inexperienced House. Lastly, the influence of staff, lobbyists, and most importantly, the governor has greatly increased under term limits. This research finds that term limits have not produced the consequences that proponents had envisioned.^

Step and flash imprint lithography: Fabrication of patterned media for extremely high density magnetic data storage devices

Currently the data storage industry is facing huge challenges with respect to the conventional method of recording data known as longitudinal magnetic recording. This technology is fast approaching a fundamental physical limit, known as the superparamagnetic limit. A unique way of deferring the superparamagnetic limit incorporates the patterning of magnetic media. This method exploits the use of lithography tools to predetermine the areal density. Various nanofabrication schemes are employed to pattern the magnetic material are Focus Ion Beam (FIB), E-beam Lithography (EBL), UV-Optical Lithography (UVL), Self-assembled Media Synthesis and Nanoimprint Lithography (NIL). Although there are many challenges to manufacturing patterned media, the large potential gains offered in terms of areal density make it one of the most promising new technologies on the horizon for future hard disk drives. Thus, this dissertation contributes to the development of future alternative data storage devices and deferring the superparamagnetic limit by designing and characterizing patterned magnetic media using a novel nanoimprint replication process called "Step and Flash Imprint lithography". As opposed to hot embossing and other high temperature-low pressure processes, SFIL can be performed at low pressure and room temperature. Initial experiments carried out, consisted of process flow design for the patterned structures on sputtered Ni-Fe thin films. The main one being the defectivity analysis for the SFIL process conducted by fabricating and testing devices of varying feature sizes (50 nm to 1 μm) and inspecting them optically as well as testing them electrically. Once the SFIL process was optimized, a number of Ni-Fe coated wafers were imprinted with a template having the patterned topography. A minimum feature size of 40 nm was obtained with varying pitch (1:1, 1:1.5, 1:2, and 1:3). The Characterization steps involved extensive SEM study at each processing step as well as Atomic Force Microscopy (AFM) and Magnetic Force Microscopy (MFM) analysis.