Simplification Resilient LDPC-Coded Sparse-QIM Watermarking for 3D-Meshes

We propose a blind watermarking scheme for 3-D meshes which combines sparse quantization index modulation (QIM) with deletion correction codes. The QIM operates on the vertices in rough concave regions of the surface thus ensuring impeccability, while the deletion correction code recovers the data hidden in the vertices which is removed by mesh optimization and/or simplification. The proposed scheme offers two orders of magnitude better performance in terms of recovered watermark bit error rate compared to the existing schemes of similar payloads and fidelity constraints.Comment: Submitted, revised and Copyright transfered to IEEE Transactions on Multimedia, October 9th 201

Achievable Information Rates and Concatenated Codes for the DNA Nanopore Sequencing Channel

The errors occurring in DNA-based storage are correlated in nature, which is a direct consequence of the synthesis and sequencing processes. In this paper, we consider the memory-$k$ nanopore channel model recently introduced by Hamoum et al., which models the inherent memory of the channel. We derive the maximum a posteriori (MAP) decoder for this channel model. The derived MAP decoder allows us to compute achievable information rates for the true DNA storage channel assuming a mismatched decoder matched to the memory-$k$ nanopore channel model, and quantify the loss in performance assuming a small memory length--and hence limited decoding complexity. Furthermore, the derived MAP decoder can be used to design error-correcting codes tailored to the DNA storage channel. We show that a concatenated coding scheme with an outer low-density parity-check code and an inner convolutional code yields excellent performance.Comment: This paper has been accepted and awaiting publication in informatio theory workshop (ITW) 202

Signal Processing for Bit-Patterned Media Recording

Ph.DDOCTOR OF PHILOSOPH

A RUNLENGTH CODED ADAPTIVE QIM FOR THE CULTURAL HERITAGE 3D MODELS AUTHENTICATION

We describe a simple and effective quantization scheme for a digital 3D cultural heritage models authentication and watermarking. It is based on runlength coding which converts a class of deletion channels that have infinite memory into memoryless channels. We consider a novel application of this technique in multimedia watermarking and authentication using quantization index modulation operating on the three dimensional mesh vertices, which are invariant to geometric and topological transformation. Vector of the vertex indices is extracted from a huge digital 3D model using our powerful vertex extraction tool. The coding recovers the data hidden in the vertices removed by the process of mesh simplification

Towards long double-stranded chains and robust DNA-based data storage using the random code system

DNA has become a popular choice for next-generation storage media due to its high storage density and stability. As the storage medium of life’s information, DNA has significant storage capacity and low-cost, low-power replication and transcription capabilities. However, utilizing long double-stranded DNA for storage can introduce unstable factors that make it difficult to meet the constraints of biological systems. To address this challenge, we have designed a highly robust coding scheme called the “random code system,” inspired by the idea of fountain codes. The random code system includes the establishment of a random matrix, Gaussian preprocessing, and random equilibrium. Compared to Luby transform codes (LT codes), random code (RC) has better robustness and recovery ability of lost information. In biological experiments, we successfully stored 29,390 bits of data in 25,700 bp chains, achieving a storage density of 1.78 bits per nucleotide. These results demonstrate the potential for using long double-stranded DNA and the random code system for robust DNA-based data storage

Genomic analyses of the immune system

Project 1. Genetic variation in key immune system components Genes underpinning the diversity and plasticity of the human adaptive immune system, such as the HLA and immunoglobulins, are known for their complex structures and polymorphism. The emergence of long-read sequencing technologies has revolutionised genomics research, in particular the characterisation of segmental duplications and structural variation. Here, using long-read sequencing and additional genomics data from a healthy donor identified as HV31, I built two iterations of de novo personal genome assemblies for HV31 as a foundation to study the genetic variation of the immune system. I analysed complex structural variants found in genomic regions encoding key immune system components, and validated them against sequencing data. I also evaluated long-read sequencing accuracy and developed a tool for genomic data visualisation. Collectively, these efforts demonstrate the applications of personal genome assemblies in studying the immune system. Project 2. Effects of low-dose IL-2 immunotherapy in T and NK cells Low-dose interleukin-2 (IL-2) immunotherapy is a promising treatment for type 1 diabetes (T1D). IL-2 supresses autoimmune reactions by increasing the number of regulatory T cells (Tregs). To better understand the mechanism of action of low- dose IL-2 immunotherapy, I analysed single-cell multiomics data of T and NK cells collected from T1D patients before and after low-dose IL-2 treatment. I confirmed that low-dose IL-2 selectively expanded thymic-derived FOXP3+ HELIOS+ regulatory T cells and CD56br NK cells, and showed that the treatment reduced the frequency of IL-21-producing CD4+ T cells. In addition, I identified a long-lived gene expression signature induced by IL-2, which featured the upregulation of CISH and downregulation of AREG. Notably, I found that the signature remained detectable one month after the treatment. Further analyses of publicly available COVID-19 cohort data revealed that SARS-CoV-2 infection induced opposite changes that persisted for several months after recovery. These findings suggested potential mechanisms of long COVID and longer-term benefits of IL-2 immunotherapy

Computational Reconstruction of Enhancer-Gene Regulatory Networks Altered in Cancer

Enhancers are cis-acting non-coding regulatory elements that regulate the transcriptional output of target genes. Their dysregulation has been associated with various diseases including cancer. However, identification and characterisation of non-coding mutations that are relevant for tumorigenesis and prognosis remains a major challenge. We hypothesised that non-coding mutations in enhancers could significantly influence cancer prognosis and patient survival and thus can be exploited as novel prognostic biomarkers for better patient stratification and targeted therapy in lung cancer. Here we present the detection and characterisation of enhancer mutations in a genome-wide analysis of 159 lung cancer samples. To define enhancers across the genome we leverage the epigenomic signatures incorporating histone marks (H3K27ac) and chromatin accessibility (DNase I sensitivity or ATAC-seq) from 8 lung cell lines and primary tissue. We observe that the mutation burden at enhancers, promoters and exons is similar, whereas the mutation signature at these genomic locations varies significantly. We observe recurrent mutations in enhancers at base pair level and show their impact on target genes. We also demonstrate that genes have more than one enhancer and when they are mutated, the gene expression is altered. We also observe pathway-level aggregated enhancer mutations in cancer patients. These results contribute to a new approach towards the functional validation of non-coding mutations in cancer

Advances in Modeling and Signal Processing for Bit-Patterned Magnetic Recording Channels with Written-In Errors

In the past perpendicular magnetic recording on continuous media has served as the storage mechanism for the hard-disk drive (HDD) industry, allowing for growth in areal densities approaching 0.5 Tb/in2. Under the current system design, further increases are limited by the superparamagnetic effect where the medium's thermal energy destabilizes the individual bit domains used for storage. In order to provide for future growth in the area of magnetic recording for disk drives, a number of various technology shifts have been proposed and are currently undergoing considerable research. One promising option involves switching to a discrete medium in the form of individual bit islands, termed bit-patterned magnetic recording (BPMR).When switching from a continuous to a discrete media, the problems encountered become substantial for every aspect of the hard-disk drive design. In this dissertation the complications in modeling and signal processing for bit-patterned magnetic recording are investigated where the write and read processes along with the channel characteristics present considerable challenges. For a target areal density of 4 Tb/in2, the storage process is hindered by media noise, two-dimensional (2D) intersymbol interference (ISI), electronics noise and written-in errors introduced during the write process. Thus there is a strong possibility that BPMR may prove intractable as a future HDD technology at high areal densities because the combined negative effects of the many error sources produces an environment where current signal processing techniques cannot accurately recover the stored data. The purpose here is to exploit advanced methods of detection and error correction to show that data can be effectively recovered from a BPMR channel in the presence of multiple error sources at high areal densities.First a practical model for the readback response of an individual island is established that is capable of representing its 2D nature with a Gaussian pulse. Various characteristics of the readback pulse are shown to emerge as it is subjected to the degradation of 2D media noise. The writing of the bits within a track is also investigated with an emphasis on the write process's ability to inject written-in errors in the data stream resulting from both a loss of synchronization of the write clock and the interaction of the local-scale magnetic fields under the influence of the applied write field.To facilitate data recovery in the presence of BPMR's major degradations, various detection and error-correction methods are utilized. For single-track equalization of the channel output, noise prediction is incorporated to assist detection with increased levels of media noise. With large detrimental amounts of 2D ISI and media noise present in the channel at high areal densities, a 2D approach known as multi-track detection is investigated where multiple tracks are sensed by the read heads and then used to extract information on the target track. For BPMR the output of the detector still possesses the uncorrected written-in errors. Powerful error-correction codes based on finite geometries are employed to help recover the original data stream. Increased error-correction is sought by utilizing two-fold EG codes in combination with a form of automorphism decoding known as auto-diversity. Modifications to the parity-check matrices of the error-correction codes are also investigated for the purpose of attempting more practical applications of the decoding algorithms based on belief propagation. Under the proposed techniques it is shown that effective data recovery is possible at an areal density of 4 Tb/in2 in the presence of all significant error sources except for insertions and deletions. Data recovery from the BPMR channel with insertions and deletions remains an open problem