Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Immersive analytics for oncology patient cohorts

This thesis proposes a novel interactive immersive analytics tool and methods to interrogate the cancer patient cohort in an immersive virtual environment, namely Virtual Reality to Observe Oncology data Models (VROOM). The overall objective is to develop an immersive analytics platform, which includes a data analytics pipeline from raw gene expression data to immersive visualisation on virtual and augmented reality platforms utilising a game engine. Unity3D has been used to implement the visualisation. Work in this thesis could provide oncologists and clinicians with an interactive visualisation and visual analytics platform that helps them to drive their analysis in treatment efficacy and achieve the goal of evidence-based personalised medicine. The thesis integrates the latest discovery and development in cancer patients’ prognoses, immersive technologies, machine learning, decision support system and interactive visualisation to form an immersive analytics platform of complex genomic data. For this thesis, the experimental paradigm that will be followed is in understanding transcriptomics in cancer samples. This thesis specifically investigates gene expression data to determine the biological similarity revealed by the patient's tumour samples' transcriptomic profiles revealing the active genes in different patients. In summary, the thesis contributes to i) a novel immersive analytics platform for patient cohort data interrogation in similarity space where the similarity space is based on the patient's biological and genomic similarity; ii) an effective immersive environment optimisation design based on the usability study of exocentric and egocentric visualisation, audio and sound design optimisation; iii) an integration of trusted and familiar 2D biomedical visual analytics methods into the immersive environment; iv) novel use of the game theory as the decision-making system engine to help the analytics process, and application of the optimal transport theory in missing data imputation to ensure the preservation of data distribution; and v) case studies to showcase the real-world application of the visualisation and its effectiveness

Beyond transcription : a post-transcriptional role of 3D chromatin crosstalk in oncogene regulation

This thesis explores how stochastic chromatin fibre interactions, chromatin organization in the 3D nuclear architecture, and environmental signals collaborate to regulate MYC oncogene expression in human colon cancer cells. In Paper I, we employ the ultra-sensitive Nodewalk technique to uncover the dynamic and stochastic nature of chromatin networks impinging on MYC. The analyses revealed that the MYC interactome mainly consists of stochastic pairwise interactions between MYC and its flanking enhancers in two neighbouring topologically associated domains (TADs), which are insulated self-interacting genomic domains. The limits of Nodewalk were also pushed to enable the detection of interactions in very small cell populations, corresponding to the genomic content of ~7 cells. Comparing the frequency of interactions detected in such small input samples with ensemble interactomes of large cell populations uncovered that the enhancer hubs of the ensemble interactomes that appear to simultaneously interact with MYC likely represent virtual events, which are not present in reality at the single cell level. These data support a model where MYC interacts with its enhancers in a mutually exclusive way, with MYC screening for enhancer contacts, rather than the other way around. Paper II provides a detailed understanding of a novel post-transcriptional mechanism of enhancer action on MYC expression. We have thus uncovered that the cancer-specific recruitment of the MYC gene to nuclear pores and ensuing rapid nuclear export of MYC transcripts - a process that increases MYC expression by enabling the escape of MYC mRNAs from rapid decay in the nucleus - require a CTCF binding site positioned within the colorectal oncogenic super-enhancer. Genetic editing by CRISPR-Cas9 was thus commissioned to establish two clones of human colon cancer cells with a mutated sequence in the OSE-specific CTCFBS. Comparing the mutant cells to the parental cell line, we uncovered that the WNT-dependent increase in the nuclear export rate of MYC transcripts was abrogated in the CTCFBS mutant clones, providing the first genetic evidence of super- enhancer-mediated gene gating in human cells. In line with this finding, the OSE-specific CTCFBS thus conferred a significant growth advantage to the parental colon cancer cells, compared to the mutant clones. Moreover, we found that WNT-dependent CCAT1 eRNA transcription is mediated by the OSE-specific CTCFBS that is required for recruitment of AHCTF1 to the OSE to mediate the positioning of the OSE to the nuclear periphery, enabling the subsequent facilitation of MYC mRNA export. A multistep molecular process including WNT signalling and the OSE-specific CTCFBS thus underlies the gene gating of MYC in human colon cancer cells, and could potentially be targeted for diagnostic or therapeutic uses. In summary, this thesis explores the dynamics of the stochastic interactomes impinging on the MYC oncogene, and provides new insights on the role of 3D chromatin orchestration in the transcriptional regulation of MYC. Our analyses uncovered the molecular factors involved in the gene gating of MYC, and thus increase our understanding of tumour development. These findings could potentially be beneficial for future diagnostic approaches, or for targeted therapeutic strategies in the treatment of cancer

Innate Structure of DNA Foci Restricts the Mixing of DNA from Different Chromosome Territories

The distribution of chromatin within the mammalian nucleus is constrained by its organization into chromosome territories (CTs). However, recent studies have suggested that promiscuous intra- and inter-chromosomal interactions play fundamental roles in regulating chromatin function and so might define the spatial integrity of CTs. In order to test the extent of DNA mixing between CTs, DNA foci of individual CTs were labeled in living cells following incorporation of Alexa-488 and Cy-3 conjugated replication precursor analogues during consecutive cell cycles. Uniquely labeled chromatin domains, resolved following random mitotic segregation, were visualized as discrete structures with defined borders. At the level of resolution analysed, evidence for mixing of chromatin from adjacent domains was only apparent within the surface volumes where neighboring CTs touched. However, while less than 1% of the nuclear volume represented domains of inter-chromosomal mixing, the dynamic plasticity of DNA foci within individual CTs allows continual transformation of CT structure so that different domains of chromatin mixing evolve over time. Notably, chromatin mixing at the boundaries of adjacent CTs had little impact on the innate structural properties of DNA foci. However, when TSA was used to alter the extent of histone acetylation changes in chromatin correlated with increased chromatin mixing. We propose that DNA foci maintain a structural integrity that restricts widespread mixing of DNA and discuss how the potential to dynamically remodel genome organization might alter during cell differentiation

Actas do 10º Encontro Português de Computação Gráfica

Actas do 10º Encontro Portugês de Computação Gráfica, Lisboa, 1-3 de Outubro de 2001A investigação, o desenvolvimento e o ensino na área da Computação Gráfica constituem, em Portugal, uma realidade positiva e de largas tradições. O Encontro Português de Computação Gráfica (EPCG), realizado no âmbito das actividades do Grupo Português de Computação Gráfica (GPCG), tem permitido reunir regularmente, desde o 1º EPCG realizado também em Lisboa, mas no já longínquo mês de Julho de 1988, todos os que trabalham nesta área abrangente e com inúmeras aplicações. Pela primeira vez no historial destes Encontros, o 10º EPCG foi organizado em ligação estreita com as comunidades do Processamento de Imagem e da Visão por Computador, através da Associação Portuguesa de Reconhecimento de Padrões (APRP), salientando-se, assim, a acrescida colaboração, e a convergência, entre essas duas áreas e a Computação Gráfica. Este é o livro de actas deste 10º EPCG.INSATUniWebIcep PortugalMicrografAutodes

Resource optimization and dynamic state management in a collaborative virtual environment.

Yim-Pan Chui.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 126-132).Abstracts in English and Chinese.Abstract --- p.iiAcknowledgments --- p.vChapter 1 --- Introduction --- p.1Chapter 1.1 --- Introduction to Collaborative Virtual Environments --- p.1Chapter 1.2 --- Barriers to Resource Management and Optimization --- p.3Chapter 1.3 --- Thesis Contributions --- p.5Chapter 1.4 --- Application of this Research Work --- p.6Chapter 1.5 --- Thesis Organization --- p.6Chapter 2 --- Resource Optimization - Intelligent Server Partitioning --- p.9Chapter 2.1 --- Introduction --- p.9Chapter 2.2 --- Server Partitioning --- p.13Chapter 2.2.1 --- Related Works --- p.15Chapter 2.2.2 --- Global Optimization Approaches --- p.17Chapter 2.3 --- Hybrid Genetic Algorithm Paradigm --- p.17Chapter 2.3.1 --- Drawbacks of traditional GA --- p.18Chapter 2.3.2 --- Problem Modeling --- p.19Chapter 2.3.3 --- Discussion --- p.24Chapter 2.4 --- Results --- p.25Chapter 2.5 --- Concluding Remarks --- p.28Chapter 3 --- Dynamic State Management - Dead Reckoning of Attitude --- p.32Chapter 3.1 --- Introduction to Dynamic State Management --- p.32Chapter 3.2 --- The Dead Reckoning Approach --- p.35Chapter 3.3 --- Attitude Dead Reckoning by Quaternion --- p.37Chapter 3.3.1 --- Modeling of the Paradigm --- p.38Chapter 3.3.2 --- Prediction Step --- p.39Chapter 3.3.3 --- Convergence Step --- p.40Chapter 3.3.4 --- Overall Algorithm --- p.46Chapter 3.4 --- Results --- p.47Chapter 3.5 --- Conclusion --- p.51Chapter 4 --- Polynomial Attitude Extrapolation --- p.52Chapter 4.1 --- Introduction --- p.52Chapter 4.2 --- Related Works on Kalman Filtering --- p.53Chapter 4.3 --- Historical Propagation of Quaternion --- p.54Chapter 4.3.1 --- Cumulative Extrapolation --- p.54Chapter 4.3.2 --- Method I. Vandemonde Approach --- p.55Chapter 4.3.3 --- Method II. Lagrangian Approach --- p.58Chapter 4.4 --- History-Based Attitude Management --- p.60Chapter 4.4.1 --- Multi-order Prediction --- p.60Chapter 4.4.2 --- Adaptive Attitude Convergence --- p.63Chapter 4.4.3 --- Overall Algorithm --- p.67Chapter 4.5 --- Results --- p.69Chapter 4.6 --- Conclusion --- p.77Chapter 5 --- Forward Difference Approach on State Estimation --- p.78Chapter 5.1 --- Introduction --- p.78Chapter 5.2 --- Positional Forward Differencing --- p.79Chapter 5.3 --- Forward Difference on Quaternion Space --- p.80Chapter 5.3.1 --- Attitude Forward Differencing --- p.83Chapter 5.3.2 --- Trajectory Blending --- p.84Chapter 5.4 --- State Estimation --- p.86Chapter 5.5 --- Computational Efficiency --- p.87Chapter 5.6 --- Results --- p.88Chapter 5.7 --- Conclusion --- p.96Chapter 6 --- Predictive Multibody Kinematics --- p.98Chapter 6.1 --- Introduction --- p.98Chapter 6.2 --- Dynamic Management of Multibody System --- p.100Chapter 6.2.1 --- Multibody Representation --- p.100Chapter 6.2.2 --- Paradigm Overview --- p.101Chapter 6.3 --- Motion Estimation by Joint Extrapolation --- p.102Chapter 6.3.1 --- Individual Joint Extrapolation --- p.102Chapter 6.3.2 --- Forward Propagation of Joint State --- p.104Chapter 6.3.3 --- Pose Correction --- p.107Chapter 6.4 --- Limitations on Predictive Articulated State Management --- p.108Chapter 6.5 --- Implementation and Results --- p.109Chapter 6.6 --- Conclusion --- p.112Chapter 7 --- Complete System Architecture --- p.113Chapter 7.1 --- Server Cluster Model --- p.113Chapter 7.1.1 --- Peer-Server Systems --- p.114Chapter 7.1.2 --- Server Hierarchies --- p.114Chapter 7.2 --- Multi-Level Resource Management --- p.115Chapter 7.3 --- Aggregation of State Updates --- p.116Chapter 7.4 --- Implementation Issues --- p.117Chapter 7.4.1 --- Medical Visualization --- p.117Chapter 7.4.2 --- Virtual Walkthrough Application --- p.118Chapter 7.5 --- Conclusion --- p.119Chapter 8 --- Conclusions and Future directions --- p.121Chapter 8.1 --- Conclusion --- p.121Chapter 8.2 --- Future Research Directions --- p.122Chapter A --- Quaternion Basis --- p.124Chapter A.1 --- Basic Quaternion Mathematics --- p.124Chapter A.2 --- The Exponential and Logarithmic Maps --- p.125Bibliography --- p.12

Utilitarian placement of composite services

The emergence of distributed clouds opens up new research challenges for service deployment. Composite services consist of multiple components, potentially located in different geographical locations, which need to be interconnected and invoked in the correct order according to the overall service work-flow. The placement of composite services over distributed cloud node locations raises new challenges for efficient deployment and management. In this paper, we design exact models of the composite service placement problems using Mixed Integer Linear Program (MILP), and compare these to solutions based on genetic algorithms. We use a utility function, based initially on latency metrics, to evaluate the quality of service (QoS) of the deployed composite service. By maximizing the utility with respect to deployment cost, our approach can provide good QoS for users while satisfying budget constraints for service providers. Based on simulations using real data-center locations and traffic demand patterns, we show that our algorithms are scalable under a range of scenarios.This work has been supported in part by the FP7 FUSION (grant agreement 318205), in part by the U.S. Army Research Laboratory and the U.K. Ministry of Defence (agreement number W911NF-16-3-0001), in part by the H2020 5G-MEDIA (grant agreement 761699) and in part by the CHIST-ERA CONCERT (grant agreement I1402) projects.info:eu-repo/semantics/publishedVersio

First-trimester Screening for Down Syndrome and Other Aneuploidies

__Abstract__ Down syndrome, which is synonymous with trisomy 21 (47, +21), is the most common chromosomal anomaly in live born children. In 1866 John Langdon Down first described children with common phenotypically features distinct from other children with mental retardation . These children were referred by Down as ‘mongoloids’, based on the typical facial characteristics of individuals with Down syndrome. Specific characteristics of newborns with Down syndrome include a flat nasal bridge, epicanthic folds, small ears, a protruding tongue, a short neck and hypotonia . Beside the visual features, newborns with Down syndrome have an increased risk of congenital structural anomalies such as heart defects, gastrointestinal defects, hearing and ophthalmic problems, hypothyroidism and leukemia. In 1956 Joe Hin Tjio and Albert Levan reported that the total number of human chromosomes in ‘normal subject’ is 46, rather than 48 as was supposedly established some three decades earlier. The importance of this finding was not the total number of chromosomes itself, but rather the ability to distinguish the number of 46 chromosomes from numerical chromosomal abnormalities. In fact, it was three years later (1959) when Lejeune et al demonstrated that Down syndrome is associated with the presence of an additional chromosome 21. Due to this extra copy of chromosome 21, the clinical condition Down syndrome is also known as trisomy 21. As a result of the technical advances in chromosomal analysis of human amniotic-fluid cells demonstrated by Steele and Breg , the first prenatal diagnosis of Down syndrome by amniocentesis was reported in 1968. Because of the development of the new obstetric techniques together with the advances in direct analysis of spontaneous mitoses in fetal tissue it was possible from 1989 to carry out prenatal chromosome diagnosis in the first trimester of pregnancy. Chorionic villi, which typically have the same genotype as the fetus, were obtained by gentle suction under constant realtime ultrasound guidance. These techniques enabled pregnant women to choose between chorionic villus sampling (CVS) at the 9th to 11th week of gestation and amniocentesis at the 16th to 18th week of gestation. These invasive procedures are associated with an iatrogenic miscarriage rate of 0.3- 0.5% . For The Netherlands nowadays the estimated birth prevalence of Down syndrome is per 10.000 with around 322 total annual births 19,20. The relatively high prevalence of this condition and the association with perinatal morbidity and mortality has been one of the main reasons for the implementation of prenatal screening for Down syndrome