TEACHING OLD CALIPERS NEW TRICKS: USING CRANIOMETRICS FOR ANCESTRY ADMIXTURE ESTIMATION VIA FUZZY MATH

Cranial measurements have been a cornerstone of physical anthropology since its formation as a discipline in the early 1900s. However, most other ancestry determination methods come with a significant epistemological issue: they differentiate individuals into discrete categories without accounting for the issue of admixture. Advances in data mining and analysis techniques can now be used to help resolve this issue through soft computing, also known as “fuzzy math”. This type of advanced computational math requires specialized knowledge in computer programming, statistics, and data analysis techniques unless one is using computer programs specially designed to run these analyses. This project compiled a database from multiple open-source craniometrics data and utilized prepared packages within the R statistical environment to find a valid soft computing method for fuzzy ancestry determination that does not require extensive knowledge in computer programming or data mining. Exploration of database demographics notes an excess of White-identified individuals, and when tested, this demographic skew impacts the ability of the given package to return valid results. The package chosen was valid using the compiled database. Exploration of causes for the invalid results, including a significant White skew in the underlying database due to accessibility of metric databases, overfitting, and the inherent issues of admixture on craniometric research, are explored, and future directions discussed

APPLICATIONS OF MACHINE LEARNING IN MICROBIAL FORENSICS

Microbial ecosystems are complex, with hundreds of members interacting with each other and the environment. The intricate and hidden behaviors underlying these interactions make research questions challenging – but can be better understood through machine learning. However, most machine learning that is used in microbiome work is a black box form of investigation, where accurate predictions can be made, but the inner logic behind what is driving prediction is hidden behind nontransparent layers of complexity. Accordingly, the goal of this dissertation is to provide an interpretable and in-depth machine learning approach to investigate microbial biogeography and to use micro-organisms as novel tools to detect geospatial location and object provenance (previous known origin). These contributions follow with a framework that allows extraction of interpretable metrics and actionable insights from microbiome-based machine learning models. The first part of this work provides an overview of machine learning in the context of microbial ecology, human microbiome studies and environmental monitoring – outlining common practice and shortcomings. The second part of this work demonstrates a field study to demonstrate how machine learning can be used to characterize patterns in microbial biogeography globally – using microbes from ports located around the world. The third part of this work studies the persistence and stability of natural microbial communities from the environment that have colonized objects (vessels) and stay attached as they travel through the water. Finally, the last part of this dissertation provides a robust framework for investigating the microbiome. This framework provides a reasonable understanding of the data being used in microbiome-based machine learning and allows researchers to better apprehend and interpret results. Together, these extensive experiments assist an understanding of how to carry an in-silico design that characterizes candidate microbial biomarkers from real world settings to a rapid, field deployable diagnostic assay. The work presented here provides evidence for the use of microbial forensics as a toolkit to expand our basic understanding of microbial biogeography, microbial community stability and persistence in complex systems, and the ability of machine learning to be applied to downstream molecular detection platforms for rapid and accurate detection

Addressing the high adverse pregnancy outcomes through the incorporation of preconception care (PCC) in the health system of Ethiopia

Background: Preconception care (PCC) is highly recommended evidence-based intervention to optimize women’s health in particular and in so doing reduce the incidences of adverse pregnancy outcomes (APO). PCC targets modification of risk factors to APO occurring before and just at early weeks of conception. Nevertheless, in Ethiopia, the need to implement PCC as part of the continuums of the comprehensive Maternal, Neonatal and Child Health Care services is not yet studied. Purpose/Aim of the study: This study aimed to develop a guideline to assist the incorporation of PCC in Ethiopian health system thereby reduce the highly incident APOs in the country, which is the purpose of the study. Methodology: This study applied the explanatory sequential mixed method to determine the determinants to the non-implementation PCC in Ethiopia. In addition, a policy document analysis was conducted to identify the existence of policy guiding the implementation of PCC in Ethiopia. Finally, the study applied a Delphi technique to increase the utility and acceptance of the guideline developed. The study was guided by a theory based framework called a Framework for Determinants of Innovation Processes (FDOIP). RESULT: Nearly all (84.7%) of the healthcare providers (HCPs) never ever practiced PCC. Even among those who ever practiced, the majority (74%), practiced it poorly. More than two third (68.6%) had poor PCC knowledge. HCP’s with good PCC knowledge had likely hood of practicing PCC by four times greater than those with poor PCC knowledge (AOR=4.4, 95% CI: 2.5-7.6). The policy document analysis identified the absence of policy guiding the practice of PCC in Ethiopia. The HCP’s curriculums also didn’t include PCC. The determinants to non-implementation of PCC, as perceived by the qualitative study participants include absence of national PCC policy , absence of PCC guideline, lack of institutional PCC plan, presence of other competing demand, lack of laboratory facilities and setup, lack of accountable body, absence of Individual or organization introduced PCC to the country, absence of trained manpower on PCC, absence of known expert in PCC, Poor public awareness about preconception health and PCC, Unplanned Pregnancy and poor health seeking behaviour. CONCLUSION The study revealed the absence of a standard and complete PCC practices by the HCPs. Nearly all HCPs never ever implement PCC. Even those very few practitioners were found practicing PCC poorly that is in a substandard, incidental, and in an inconsistent way. There is no formal policy document guiding the implementation of in Ethiopia. The HCPs training curriculum didn’t include PCC. The guideline developed base on the study findings of the study recommended to incorporating PCC in Ethiopia health system.Health StudiesD. Litt. et Phil. (Health Studies

Diverse Contributions to Implicit Human-Computer Interaction

Cuando las personas interactúan con los ordenadores, hay mucha información que no se proporciona a propósito. Mediante el estudio de estas interacciones implícitas es posible entender qué características de la interfaz de usuario son beneficiosas (o no), derivando así en implicaciones para el diseño de futuros sistemas interactivos. La principal ventaja de aprovechar datos implícitos del usuario en aplicaciones informáticas es que cualquier interacción con el sistema puede contribuir a mejorar su utilidad. Además, dichos datos eliminan el coste de tener que interrumpir al usuario para que envíe información explícitamente sobre un tema que en principio no tiene por qué guardar relación con la intención de utilizar el sistema. Por el contrario, en ocasiones las interacciones implícitas no proporcionan datos claros y concretos. Por ello, hay que prestar especial atención a la manera de gestionar esta fuente de información. El propósito de esta investigación es doble: 1) aplicar una nueva visión tanto al diseño como al desarrollo de aplicaciones que puedan reaccionar consecuentemente a las interacciones implícitas del usuario, y 2) proporcionar una serie de metodologías para la evaluación de dichos sistemas interactivos. Cinco escenarios sirven para ilustrar la viabilidad y la adecuación del marco de trabajo de la tesis. Resultados empíricos con usuarios reales demuestran que aprovechar la interacción implícita es un medio tanto adecuado como conveniente para mejorar de múltiples maneras los sistemas interactivos.Leiva Torres, LA. (2012). Diverse Contributions to Implicit Human-Computer Interaction [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17803Palanci

Genetic mapping of metabolic biomarkers of cardiometabolic diseases

Cardiometabolic disorders (CMDs) are a major public health problem worldwide. The main goal of this thesis is to characterize the genetic architecture of CMD-related metabolites in a Lebanese cohort. In order to maximise the extraction of meaningful biological information from this dataset, an important part of this thesis focuses on the evaluation and subsequent improvement of the standard methods currently used for molecular epidemiology studies. First, I describe MetaboSignal, a novel network-based approach to explore the genetic regulation of the metabolome. Second, I comprehensively compare the recovery of metabolic information in the different 1H NMR strategies routinely used for metabolic profiling of plasma (standard 1D, spin-echo and JRES). Third, I describe a new method for dimensionality reduction of 1H NMR datasets prior to statistical modelling. Finally, I use all this methodological knowledge to search for molecular biomarkers of CMDs in a Lebanese population. Metabolome-wide association analyses identified a number of metabolites associated with CMDs, as well as several associations involving N-glycan units from acute-phase glycoproteins. Genetic mapping of these metabolites validated previously reported gene-metabolite associations, and revealed two novel loci associated with CMD-related metabolites. Collectively, this work contributes to the ongoing efforts to characterize the molecular mechanisms underlying complex human diseases.Open Acces

Improving evolutionary algorithms by MEANS of an adaptive parameter control approach

Evolutionary algorithms (EA) constitute a class of optimization methods that is widely used to solve complex scientific problems. However, EA often converge prematurely over suboptimal solutions, the evolution process is computational expensive, and setting the required EA parameters is quite difficult. We believe that the best way to address these problems is to begin by improving the parameter setting strategy, which will in turn improve the search path of the optimizer, and, we hope, ultimately help prevent premature convergence and relieve the computational burden. The strategy that will achieve this outcome, and the one we adopt in this research, is to ensure that the parameter setting approach takes into account the search path and attempts to drive it in the most advantageous direction. Our objective is therefore to develop an adaptive parameter setting approach capable of controlling all the EA parameters at once. To interpret the search path, we propose to incorporate the concept of exploration and exploitation into the feedback indicator. The first step is to review and study the available genotypic diversity measurements used to characterize the exploration of the optimizer over the search space. We do this by implementing a specifically designed benchmark, and propose three diversity requirements for evaluating the meaningfulness of those measures as population diversity estimators. Results show that none of the published formulations is, in fact, a qualified diversity descriptor. To remedy this, we introduce a new genotypic formulation here, the performance analysis of which shows that it produces better results overall, notwithstanding some serious defects. We initiate a similar study aimed at describing the role of exploitation in the search process, which is to indicate promising regions. However, since exploitation is mainly driven by the individuals’ fitness, we turn our attention toward phenotypic convergence measures. Again, the in-depth analysis reveals that none of the published phenotypic descriptors is capable of portraying the fitness distribution of a population. Consequently, a new phenotypic formulation is developed here, which shows perfect agreement with the expected population behavior. On the strength of these achievements, we devise an optimizer diagnostic tool based on the new genotypic and phenotypic formulations, and illustrate its value by comparing the impacts of various EA parameters. Although the main purpose of this development is to explore the relevance of using both a genotypic and a phenotypic measure to characterize the search process, our diagnostic tool proves to be one of the few tools available to practitioners for interpreting and customizing the way in which optimizers work over real-world problems. With the knowledge gained in our research, the objective of this thesis is finally met, with the proposal of a new adaptive parameter control approach. The system is based on a Bayesian network that enables all the EA parameters to be considered at once. To the authors’ knowledge, this is the first parameter setting proposal devised to do so. The genotypic and phenotypic measures developed are combined in the form of a credit assignment scheme for rewarding parameters by, among other things, promoting maximization of both exploration and exploitation. The proposed adaptive system is evaluated over a recognized benchmark (CEC’05) through the use of a steady-state genetic algorithm (SSGA), and then compared with seven other approaches, like FAUC-RMAB and G-CMA-ES, which are state-of-the-art adaptive methods. Overall, the results demonstrate statistically that the new proposal not only performs as well as G-CMA-ES, but outperforms almost all the other adaptive systems. Nonetheless, this investigation revealed that none of the methods tested is able to locate global optimum over complex multimodal problems. This led us to conclude that synergy and complementarity among the parameters involved is probably missing. Consequently, more research on these topics is advised, with a view to devising enhanced optimizers. We provide numerous recommendations for such research at the end of this thesis

ENDOMET database – A means to identify novel diagnostic and prognostic tools for endometriosis

Endometriosis is a common benign hormone reliant inflammatory gynecological disease that affects fertile aged women and has a considerable economic impact on healthcare systems. Symptoms include intense menstrual pain, persistent pelvic pain, and infertility. It is defined by the existence of endometrium-like tissue developing in ectopic locations outside the uterine cavity and inflammation in the peritoneal cavity. Endometriosis presents with multifactorial etiology, and despite extensive research the etiology is still poorly understood. Diagnostic delay from the onset of the disease to when a conclusive diagnosis is reached is between 7–12 years. There is no known cure, although symptoms can be improved with hormonal medications (which often have multiple side effects and prevent pregnancy), or through surgery which carries its own risk. Current non-invasive tools for diagnosis are not sufficiently dependable, and a definite diagnosis is achieved through laparoscopy or laparotomy. This study was based on two prospective cohorts: The ENDOMET study, including 137 endometriosis patients scheduled for surgery and 62 healthy women, and PROENDO that included 138 endometriosis patients and 33 healthy women. Our long-term goal with the current study was to support the discovery of innovative new tools for efficient diagnosis of endometriosis as well as tools to further understand the etiology and pathogenesis of the disease. We set about achieving this goal by creating a database, EndometDB, based on a relational data model, implemented with PostgreSQL programming language. The database allows e.g., for the exploration of global genome-wide expression patterns in the peritoneum, endometrium, and in endometriosis lesions of endometriosis patients as well as in the peritoneum and endometrium of healthy control women of reproductive age. The data collected in the EndometDB was also used for the development and validation of a symptom and biomarker-based predictive model designed for risk evaluation and early prediction of endometriosis without invasive diagnostic methods. Using the data in the EndometDB we discovered that compared with the eutopic endometrium, the WNT- signaling pathway is one of the molecular pathways that undergo strong changes in endometriosis. We then evaluated the potential role for secreted frizzled-related protein 2 (SFRP-2, a WNT-signaling pathway modulator), in improving endometriosis lesion border detection. The SFRP-2 expression visualizes the lesion better than previously used markers and can be used to better define lesion size and that the surgical excision of the lesions is complete.ENDOMET tietokanta – Keino tunnistaa uusi diagnostinen ja ennustava työkalu endometrioosille Endometrioosi on yleinen hyvänlaatuinen, hormoneista riippuvainen tulehduksellinen lisääntymisikäisten naisten gynekologinen sairaus, joka kuormittaa terveydenhuoltojärjestelmää merkittävästi. Endometrioositaudin oireita ovat mm. voimakas kuukautiskipu, jatkuva lantion alueen kipu ja hedelmättömyys. Sairaus määritellään kohdun limakalvon kaltaisen kudoksen esiintymisenä kohdun ulkopuolella sekä siihen liittyvänä vatsakalvon tulehduksena. Endometrioosin etiologia on monitahoinen, ja laajasta tutkimuksesta huolimatta edelleen huonosti tunnettu. Kesto taudin puhkeamisesta lopullisen diagnoosin saamiseen on usein jopa 7–12 vuotta. Sairauteen ei tunneta parannuskeinoa, mutta oireita voidaan lievittää esimerkiksi hormonaalisilla lääkkeillä (joilla on usein monia sivuvaikutuksia ja jotka estävät raskauden) tai leikkauksella, johon liittyy omat tunnetut riskit. Nykyiset ei-invasiiviset diagnoosityökalut eivät ole riittävän luotettavia sairauden tunnistamiseen, ja varma endometrioosin diagnoosi saavutetaan laparoskopian tai laparotomian avulla. Tämä tutkimus perustui kahteen prospektiiviseen kohorttiin: ENDOMET-tutkimuk-seen, johon osallistui 137 endometrioosipotilasta ja 62 terveellistä naista, sekä PROENDO-tutkimukseen, johon osallistui 138 endometrioosipotilasta ja 33 terveellistä naista. Tässä tutkimuksessa pitkän aikavälin tavoitteemme oli löytää uusia työkalujen endometrioosin diagnosointiin, sekä ymmärtää endometrioosin etiologiaa ja patogeneesiä. Ensimmäisessä vaiheessa loimme EndometDB –tietokannan PostgreSQL-ohjelmointi-kielellä. Tämän osittain avoimeen käyttöön vapautetun tietokannan avulla voidaan tutkia genomin, esimerkiksi kaikkien tunnettujen geenien ilmentymistä peritoneumissa, endo-metriumissa ja endometrioosipotilaiden endometrioosileesioissa EndometDB-tietokantaan kerättyjä tietoja käytettiin oireiden ja biomarkkeripohjaisen ennustemallin kehittämiseen ja validointiin. Malli tuottaa riskinarvioinnin endometrioositaudin varhaiseen ennustamiseen ilman laparoskopiaa. Käyttäen EndometDB-tietokannan tietoja havaitsimme, että endo-metrioositautikudoksessa tapahtui voimakkaita geeni-ilmentymisen muutoksia erityisesti geeneissä, jotka liittyvät WNT-signalointireitin säätelyyn. Keskeisin löydös oli, että SFRP-2 proteiinin ilmentyminen oli huomattavasti koholla endometrioosikudoksessa ja SFRP-2 proteiinin immunohistokemiallinen värjäys erottaa endometrioosin tautikudoksen terveestä kudoksesta aiempia merkkiaineita paremmin. Löydetyllä menetelmällä voidaan siten selvittää tautikudoksen laajuus ja tarvittaessa osoittaa, että leikkauksella on kyetty poistamaan koko sairas kudos

시각화 초심자에게 시각적 비교를 돕는 정보 시각화 기술의 디자인

학위논문(박사)--서울대학교 대학원 :공과대학 컴퓨터공학부,2020. 2. 서진욱.The visual comparison is one of the fundamental tasks in information visualization (InfoVis) that enables people to organize, evaluate, and combine information fragmented in visualizations. For example, people perform visual comparison tasks to compare data over time, from different sources, or with different analytic models. While the InfoVis community has focused on understanding the effectiveness of different visualization designs for supporting visual comparison tasks, it is still unclear how to design effective comparative visualizations due to several limitations: (1) Empirical findings and practical implications from those studies are fragmented, and (2) we lack user studies that directly investigated the effectiveness of different visualization designs for visual comparison. In this dissertation, we present the results of three studies to build our knowledge on how to support effective visual comparison to InfoVis novices⁠—general people who are not familiar with visual representations and visual data exploration process. Identifying the major stages in the visualization construction process where novices confront challenges with visual comparison tasks, we explored two high-level comparison tasks with actual users: comparing visual mapping (encoding barrier) and comparing information (interpretation barrier) in visualizations. First, we conducted a systematical literature review on research papers (N = 104) that focused on supporting visual comparison tasks to gather and organize the practical insights that researchers gained in the wild. From this study, we offered implications for designing comparative visualizations, such as actionable guidelines, as well as the lucid categorization of comparative designs which can help researchers explore the design space. In the second study, we performed a qualitative user study (N = 24) to investigate how novices compare and understand visual mapping suggested in a visual-encoding recommendation interface. Based on the study, we present novices' main challenges in using visual encoding recommendations and design implications as remedies. In the third study, we conducted a design study in the area on bioinformatics to design and implement a visual analytics tool, XCluSim, that helps users to compare multiple clustering results. Case studies with a bioinformatician showed that our system enables analysts to easily evaluate the quality of a large number of clustering results. Based on the results of three studies in this dissertation, we suggest a future research agenda, such as designing recommendations for visual comparison and distinguishing InfoVis novices from experts.시각적 비교는 정보 시각화를 이용한 핵심적인 데이터 분석 과정 중 하나로써, 분산되어 있는 정보들을 사람들이 서로 정리, 평가, 병합할 수 있도록 돕는다. 예를 들어, 사람들은 시간의 흐름에 따른 데이터의 변화를 보거나, 서로 다른 출처의 데이터를 비교하거나, 같은 데이터를 여러 분석 모델들을 이용해 평가하기 위해 시각적 비교 과업을 흔히 수행하게 된다. 효과적인 시각화 디자인을 위한 여러 연구가 정보 시각화 분야에서 이루어지고 있는 반면, 어떤 디자인을 통해 효과적으로 시각적 비교를 지원할 수 있는지에 대한 이해는 다음의 제약들로 인해 아직까지 불분명하다. (1) 경험적 통찰들과 실용적 설계 지침들이 파편화되어 있으며 (2) 비교 시각화를 지원하는 방법을 이해하기 위한 사용자 실험의 수가 여전히 제한적이다. 본 논문에서는 시각화 초심자들에게 효과적으로 시각적 비교를 지원하기 위한 정보 시각화 디자인 방법을 더 깊이 이해하기 위해서 일련의 세 연구를 진행하고 이에 대한 결과를 제시한다. 특별히, 시각화 초심자들이 시각적 비교를 할 때 어려움을 경험할 수 있는 두 주요 시각화 단계를 확인함으로써, 본 연구에서는 시각적 인코딩 비교 (인코딩 장벽) 및 정보 비교 (해석 장벽) 과업들에 초점을 맞춘다. 첫째, 비교 시각화 디자인을 제시한 문헌들(N = 104)을 체계적으로 조사 및 분석함으로써 시각화 연구자들이 사용자 실험과 시각화 설계 과정을 통해 얻은 실용적 통찰들을 정리하였다. 이 문헌조사를 기반으로 비교 시각화 설계에 대한 지침들을 정립하고, 비교 시각화를 위한 디자인 공간을 더 깊이 이해하고 탐색하는 데 도움을 줄 수 있는 시각화 분류 및 예시들을 제공한다. 둘째, 초심자들이 시각화 추천 인터페이스에서 어떻게 새로운 시각적 인코딩들을 서로 비교하고 사용하는지에 대한 이해를 돕기 위해 사용자 실험(N = 24)을 수행하였다. 이 실험의 결과를 기반으로, 초심자들의 주요 어려움들과 이들을 해결하기 위한 디자인 지침들을 제시한다. 셋째, 생명정보학자가 시각적으로 다수 개의 클러스터링 결과들을 비교 및 분석할 수 있도록 도와주는 시각화 시스템, XCluSim을 디자인하고 구현하는 디자인 스터디를 수행하였다. 사례 연구를 통해 실제로 생명정보학자가 XCluSim을 이용하여 많은 클러스터링 결과들을 쉽게 비교 및 평가할 수 있다는 것을 보였다. 마지막으로, 이 세 연구 결과들을 기반으로 비교 시각화 분야에서 유망한 향후 연구들을 제시한다.CHAPTER 1. Introduction 1 1.1 Background and Motivation 1 1.2 Research Questions and Approaches 4 1.2.1 Revisiting Comparative Layouts: Design Space, Guidelines, and Future Directions 5 1.2.2 Understanding How InfoVis Novices Compare Visual Encoding Recommendation 6 1.2.3 Designing XCluSim: a Visual Analytics System for Comparing Multiple Clustering Results 7 1.3 Dissertation Outline 8 CHAPTER 2. Related Work 9 2.1 Visual Comparison Tasks 9 2.2 Visualization Designs for Comparison 10 2.2.1 Gleicher et al.s Comparative Layout 11 2.3 Understanding InfoVis Novices 12 2.4 Visualization Recommendation Interfaces 13 2.5 Comparative Visualizations for Cluster Analysis 14 CHAPTER 3. Comparative Layouts Revisited: Design Space, Guidelines, and Future Directions 19 3.1 Introduction 19 3.2 Literature Review 21 3.2.1 Method 22 3.3 Comparative Layouts in The Wild 23 3.3.1 Classifying Comparison Tasks in User Studies 25 3.3.2 Same LayoutIs Called Differently 26 3.3.3 Lucid Classification of Comparative Layouts 28 3.3.4 Advantages and Concerns of Using Each Layout 30 3.3.5 Trade-offs between Comparative Layouts 36 3.3.6 Approaches to Overcome the Concerns 38 3.3.7 Comparative Layout Explorer 42 3.4 Discussion 42 3.4.1 Guidelines for Comparative Layouts 44 3.4.2 Promising Directions for Future Research 48 3.5 Summary 49 CHAPTER 4. Understanding How InfoVis Novices Compare Visual Encoding Recommendation 51 4.1 Motivation 51 4.2 Interface 53 4.2.1 Visualization Goals 53 4.2.2 Recommendations 54 4.2.3 Representation Methods for Recommendations 54 4.2.4 Interface 58 4.2.5 Pilot Study 61 4.3 User Study 62 4.3.1 Participants 62 4.3.2 Interface 62 4.3.3 Tasks and Datasets 65 4.3.4 Procedure. 65 4.4 Findings 68 4.4.1 Poor Design Decisions 68 4.4.2 Role of Preview, Animated Transition, and Text 69 4.4.3 Challenges For Understanding Recommendations 70 4.4.4 Learning By Doing 71 4.4.5 Effects of Recommendation Order 71 4.4.6 Personal Criteria for Selecting Recommendations 72 4.5 Discussion 73 4.5.1 Design Implications 73 4.5.2 Limitations and FutureWork 75 4.6 Summary 77 CHAPTER 5. Designing XCluSim: a Visual Analytics System for Comparing Multiple Clustering Results 78 5.1 Motivation 78 5.2 Task Analysis and Design Goals 79 5.3 XCluSim 80 5.3.1 Color Encoding of Clusters Using Tree Colors 82 5.3.2 Overview of All Clustering Results 83 5.3.3 Visualization for Comparing Selected Clustering Results 86 5.3.4 Visualization for Individual Clustering Results 92 5.3.5 Implementation 100 5.4 CaseStudy 100 5.4.1 Elucidating the Role of Ferroxidase in Cryptococcus Neoformans Var. Grubii H99 (CaseStudy 1) 100 5.4.2 Finding a Clustering Result that Clearly Represents Biological Relations (CaseStudy 2) 103 5.5 Discussion 106 5.5.1 Limitations and FutureWork 108 5.6 Summary 108 CHAPTER 6. Future Research Agenda 110 6.0.1 Recommendation for Visual Comparison 110 6.0.2 Understanding the Perception of Subtle Difference 111 6.0.3 Distinguishing InfoVis Novices from Experts 112 CHAPTER 7. Conclusion. 113 Abstract (Korean) 129 Acknowledgments (Korean) 131Docto

EXPERIENCE OF MANAGING ESRD DIETARY MODIFICATIONS

Aims: The purpose of this mixed-methods study is to explore the impact of participant characteristics on dietary patterns, adherence, perceived problems, and self-efficacy; identify characteristics of hemodialysis patients most likely to experience difficulty adhering to restrictions; and to explore perceived dietary related barriers experienced in this patient population. Methods: A secondary analysis using data of 122 participants from an ongoing randomized clinical trial examining the effects of a technology supported behavioral intervention on dietary sodium intake in hemodialysis patients was performed. Semi-structured interviews were conducted on a subset of 30 participants to complete the qualitative analysis. Results: Younger participants were more likely to report problems managing the hemodialysis diet and low self-efficacy for restricting sodium intake. Consistent with these findings, younger participants had a higher median sodium intake and average daily weight gain. Females reported more problems managing the diet. Race and perceived income adequacy did not appear to influence outcome measures. Barriers included time and convenience, cost, and content of nutritional counseling. Participants were satisfied with efforts made by dialysis center staff to disseminate information. Conclusions: Our findings suggest that there may not be a need to customize interventions in regard to race or income adequacy. There may, however, be a need to customize counseling and interventions for younger adults and females. Further investigation is needed to understand the independent effects of age and gender on variations in hemodialysis dietary recommendations and problems and self-efficacy. Additionally, while participants were satisfied with nutritional counseling efforts, interventions which improve food choices and decision making in real time would be helpful

Numerical Simulation in Biomechanics and Biomedical Engineering

In the first contribution, Morbiducci and co-workers discuss the theoretical and methodological bases supporting the Lagrangian- and Euler-based methods, highlighting their application to cardiovascular flows. The second contribution, by the Ansón and van Lenthe groups, proposes an automated virtual bench test for evaluating the stability of custom shoulder implants without the necessity of mechanical testing. Urdeitx and Doweidar, in the third paper, also adopt the finite element method for developing a computational model aim to study cardiac cell behavior under mechano-electric stimulation. In the fourth contribution, Ayensa-Jiménez et al. develop a methodology to approximate the multidimensional probability density function of the parametric analysis obtained developing a mathematical model of the cancer evolution. The fifth paper is oriented to the topological data analysis; the group of Cueto and Chinesta designs a predictive model capable of estimating the state of drivers using the data collected from motion sensors. In the sixth contribution, the Ohayon and Finet group uses wall shear stress-derived descriptors to study the role of recirculation in the arterial restenosis due to different malapposed and overlapping stent conditions. In the seventh contribution, the research group of Antón demonstrates that the simulation time can be reduced for cardiovascular numerical analysis considering an adequate geometry-reduction strategy applicable to truncated patient specific artery. In the eighth paper, Grasa and Calvo present a numerical model based on the finite element method for simulating extraocular muscle dynamics. The ninth paper, authored by Kahla et al., presents a mathematical mechano-pharmaco-biological model for bone remodeling. Martínez, Peña, and co-workers propose in the tenth paper a methodology to calibrate the dissection properties of aorta layer, with the aim of providing useful information for reliable numerical tools. In the eleventh contribution, Martínez-Bocanegra et al. present the structural behavior of a foot model using a detailed finite element model. The twelfth contribution is centered on the methodology to perform a finite, element-based, numerical model of a hydroxyapatite 3D printed bone scaffold. In the thirteenth paper, Talygin and Gorodkov present analytical expressions describing swirling jets for cardiovascular applications. In the fourteenth contribution, Schenkel and Halliday propose a novel non-Newtonian particle transport model for red blood cells. Finally, Zurita et al. propose a parametric numerical tool for analyzing a silicone customized 3D printable trachea-bronchial prosthesis