Forensic facial reconstruction may be the final option available to draw the public attention in cases where the identity of an individual cannot be established by standard identification methods. Two fundamental components of all forensic facial reconstruction techniques are cranial morphology and soft tissue depths databases. The purpose of this study was to extend such databases by providing a complete set of accurate facial soft tissue thickness measurements, acquired from a contemporary adult population from Germany, for use in forensic facial reconstruction. The aims were to measure the distance between well-defined landmarks on the skull and reference points on the face in a standardised manner, to analyse how sex, age and body mass index (BMI) influence facial soft tissue depths, to identify patterns of facial asymmetry, and to conduct a comparative analysis with other populations. The material for this study consisted of 320 (160 male, 160 female) anonymised multi-slice computerised tomography (MSCT) scans of individuals drawn from a German population. Individuals between the ages of 18 and 84 years were analysed. Their statures varied between 1.50 m and 1.96 m; their weights ranged between 40 kg and 145 kg. The BMI fluctuated between 16.6 kg/m2 and 45.8 kg/m2. Patients with severe trauma or pathologies that may compromise facial soft tissue depth were excluded from the study as were patients known to have been treated with specific medication (e.g. cortisone). In Amira®, 3D models of the surfaces of the skull and the facial skin were semi-automatically segmented using previously calculated thresholds and surface extraction algorithms. The parameters were adjusted to permit semi-transparent visualisation and examination of the structures of both the 3D skull and facial skin surface models simultaneously. Facial soft tissue depth was measured at 10 midline and 28 bilateral anatomical landmarks, according to the main orientations of the skull. Statistical analyses and tests were performed with SPSS® Version 22 and TDStats Version v2015.1. The analysis of facial soft tissue thickness versus BMI, sex and age, for each landmark separately, indicated that, at a number of the landmarks, facial soft tissue depth is significantly (p < 0.05) influenced by all three biometric variables. Facial soft tissue thickness increased with increasing BMI, but the correlations with age were insignificant. The differences between males and females were statistically significant (p < 0.05) for almost all anatomical landmarks with the exception of a few in the region of the nasal root and orbitals. Asymmetry was noted at over half of the bilateral landmarks. The differences between the results from this sample and those obtained from comparable databases contradict the hypothesis that population-specificity significantly influences facial soft tissue thickness. Nevertheless, this and future studies of craniofacial soft tissues will improve our knowledge of the complexity of the human face. The information gathered will be invaluable when considering forensic facial reconstruction methods for neighbouring populations.

JavaScript Object Notation (JSON) is a format for representing data. In this thesis we show how to capture the history of changes to a JSON document. Capturing the history is important in many applications, where not only the current version of a document is required, but all the previous versions. Conceptually the history can be thought of as a sequence of non-temporal JSON documents, one for each instant of time. Each document in the sequence is called a snapshot. Since changes to a document are few and infrequent, the sequence of snapshots largely duplicates a document across many time instants, so the snapshot model is (wildly) inefficient in terms of space needed to represent the history and time taken to navigate within it. A more efficient representation can be achieved by “gluing" the snapshots together to form a temporal model. Data that remains unchanged across snapshots is represented only once in a temporal model. But we show that the temporal model is not a JSON document, and it is important to represent a history as JSON to ensure compatibility with web services and scripting languages that use JSON. So we describe a representational model that captures the information in a temporal model. We implement the representational model in Python and extensively experiment with the model. Our experiments show that the model is efficient.

Cordova (Curated Online Reference Database Of Variation Annotations) is an out-of-the-box solution for building and maintaining an online database of genetic variations integrated with population study information and pathogenicity prediction results from popular algorithms. Our primary motivation for developing this system is to aid researchers and clinician-scientists in determining the clinical significance of genetic variations. To achieve this goal, Cordova provides an interface to review and manually or computationally curate genetic variation data as well as share it for clinical diagnostics and the advancement of research.

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Magnet Recognition, a nurse-driven certification, is an acknowledgement of nursing excellence within a hospital. Magnetic Recognition supports the highest quality of patient outcomes and is the standard for nursing care and professionalism in nursing practice. The site for this project has engaged in the process of seeking Magnet Recognition but lacked a method of communicating their progress to staff, prompting the need for the institutional intranet Magnet webpage. Guided by Roger's diffusion of innovation theory and Lewin's change management model, the purpose of this quality improvement project was to develop an evaluation plan for this webpage on the institutional intranet. Specific stakeholders within the institution were targeted to answer open-ended questions about the Magnet webpage. Their feedback was summarized and used to guide the development of the evaluation plan. Feedback revealed a need to change areas of the webpage related to navigating back to the homepage, reporting outcome data for the shared-decision councils' projects, and improving the resolution of the professional practice model. A toolkit was then developed, consisting of a checklist and a questionnaire using questions about the design and content of the Magnet webpage, which could be implemented immediately and then completed annually for continuous quality improvement. The results of this project are consistent with the literature, illustrating the importance of developing a plan for evaluating the implementation process. This project was socially significant because an effective evaluation plan could be used by other institutions seeking Magnet Recognition who develop a webpage as a strategy to engage staff and communicate their Magnet Recognition journey.

Elasticsearch and Cassandra are two of the widely used databases today withElasticsearch showing a more recent resurgence due to its unique full text searchfeature, akin to that of a search engine, contrasting with the conventional querylanguage-based methods used to perform data searching and retrieval operations. The demand for more powerful and better performing yet more feature rich andflexible databases has ever been growing. This project attempts to study how the twodatabases perform under a specific workload of 2,000,000 fixed sized logs and underan environment where the two can be compared while maintaining the results of theexperiment meaningful for the production environment which they are intended for. A total of three benchmarks were carried, an Elasticsearch deployment using defaultconfiguration and two Cassandra deployments, a default configuration a long with amodified one which reflects a currently running configuration in production for thetask at hand. The benchmarks showed very interesting performance differences in terms of CPU,memory and disk space usage. Elasticsearch showed the best performance overallusing significantly less memory and disk space as well as CPU to some degree. However, the benchmarks were done in a very specific set of configurations and a veryspecific data set and workload. Those differences should be considered whencomparing the benchmark results.

L’efficacité d’une thérapeutique repose, en grande partie, sur la bonne observance de la prescription. Une mauvaise observance est susceptible de provoquer un échec thérapeutique et une escalade dans les traitements. Elle est également génératrice de surcoûts pour le système de protection sociale. La base de données Erasme, base de remboursement du régime général de l’assurance maladie (Cnam-TS), constitue une source d’information importante pour la mesure de l’utilisation des médicaments et donc, possiblement, de l’observance. Hors, depuis de nombreuses années, il a été proposé des descripteurs de l’observance calculable à partir des remboursements de différents systèmes d’assurance maladie dans le monde. Le but de ce travail était de : - recenser ces indicateurs et les appliquer à la base Erasme ; - proposer de nouveaux indicateurs ; - catégoriser ces indicateurs. Dans une première partie nous faisons l’état des lieux de la notion et du concept d’observance médicamenteuse et de sa mesure à partir des bases de données de remboursement. Dans une deuxième partie, nous présentons la base Erasme et proposons des nouveaux indicateurs. Afin d’illustrer nos propos, nous présentons les études que nous avons réalisé à partir de l’étude de médicaments ayant des profils de consommation différents : traitement au long cours d’une affection symptomatique (asthme), traitement au long cours d’une affection asymptomatique (hypercholestérolémie), traitement au long cours d’une affection grave (diabète), traitement « minute » (infection urinaire) et un traitement de durée moyenne (contraception orale). / The efficacy of a therapeutic response depends largely on good adherence to the prescription. Poor adherence may lead to therapeutic failure and an escalation of treatment. Furthermore, this generates excess cost for the health insurance system. The Erasme reimbursement database of the largest health insurance system in France (régime général de l'assurance maladie, Cnam-TS), represents an important source of information on the use of medicines, and, therefore, possibly adherence. This is particularly the case as several indicators have been proposed to describe adherence from reimbursements in the different health insurance systems around the world. The objective of the current work was to: - identify the indicators and to apply these to the Erasme database; - propose new indicators; - categorise these indicators. The first part introduces the notion and concept of medication adherence and its measurement from reimbursement databases. The second part describes the Erasme database and the propositions for new indicators. This will then be illustrated by the studies that we have performed on medicines that have different profiles of use: long-term treatment of symptomatic disease (asthma), long-term treatment of asymptomatic disease (hypercholesterolaemia), long-term treatment of serious disease (diabetes), short-term treatment (urinary infection), and medium-term treatment (oral contraceptives).

By the end of 2015, Medicare-eligible physicians at primary care practices (PCP) who do not use an electronic health record (EHR) system will incur stiff penalties if they fail to meet the deadline for using EHRs. Yet, less than 30% of rural primary clinics have fully functional EHR systems. The purpose of this phenomenology study was to explore rural primary care physicians and physician assistants' experiences regarding overcoming barriers to implementing EHRs. Complex adaptive systems formed the conceptual framework for this study. Data were collected through face-to-face interviews with a purposeful sample of 21 physicians and physician assistants across 2 rural PCPs in the southeastern region of Missouri. Participant perceptions were elicited regarding overcoming barriers to implementing EHRs under the American Recovery and Reinvestment Act, Health Information Technology for Economic and Clinical Health, and the Patient Protection and Affordable Care Act legislation. Interview questions were transcribed and processed through qualitative software to discern themes of how rural PCP physicians and physician assistants might overcome barriers to implementing electronic health records. Through the exploration of the narrative segments, 4 emergent themes were common among the participants: (a) limited finances to support EHRs, (b) health information exchange issues, (c) lack of business education, and (d) lack of transformation at rural medical practices. The implications for positive social change include the potential implementation of EHRs particularly in physician practices in rural communities, which could provide cost-efficient health care services for those communities and a more sustainable future at primary care practices.

Strategies for enterprise resource planning (ERP) system implementation success have been a focus of scholars since the 1990s. Researchers have demonstrated that ERP system implementation could cause both system failures and organization failures, affecting both operations and stakeholders. The theory of constraints was the conceptual framework for this single qualitative case study that explored ERP system critical success factors (CSFs) and strategies U.S. city governments use to successfully implement ERP systems. One city government in New Mexico with a successful ERP system served as the case study's population. Data were collected from semistructured interviews and relevant documents and then open coded and thematically analyzed. Triangulation was employed to increase the trustworthiness of interpretations. The primary themes that emerged from the analysis of this single case study revealed the importance of the city government adequately resourcing and staffing the organization, providing top management support, continuously communicating to clarify motivations for implementations, gaining concurrence, and maintaining a change management asset. Other city government end-users, managers, leaders, and vendors could benefit from results of this study by identifying and addressing the relevant principal CSFs, and then developing and deploying strategies for the implementation, control, and remediation phases to increase ERP systems' utility. City governments seeking to implement ERPs could effect social change by demonstrating fiscal stewardship of resources, adding fiscally efficient and efficacious operations directly supporting constituents, and increasing public confidence.

This mixed-methods study focused on the internal human factors responsible for data breaches that could cause adverse impacts on organizations. Based on the Swiss cheese theory, the study was designed to examine preventative measures that managers could implement to minimize potential data breaches resulting from internal employees' behaviors. The purpose of this study was to provide insight to managers about developing strategies that could prevent data breaches from cyber-threats by focusing on the specific internal human factors responsible for data breaches, the root causes, and the preventive measures that could minimize threats from internal employees. Data were collected from 10 managers and 12 employees from the business sector, and 5 government managers in Ivory Coast, Africa. The mixed methodology focused on the why and who using the phenomenological approach, consisting of a survey, face-to-face interviews using open-ended questions, and a questionnaire to extract the experiences and perceptions of the participants about preventing the adverse consequences from cyber-threats. The results indicated the importance of top managers to be committed to a coordinated, continuous effort throughout the organization to ensure cyber security awareness, training, and compliance of security policies and procedures, as well as implementing and upgrading software designed to detect and prevent data breaches both internally and externally. The findings of this study could contribute to social change by educating managers about preventing data breaches who in turn may implement information accessibility without retribution. Protecting confidential data is a major concern because one data breach could impact many people as well as jeopardize the viability of the entire organization.