Complex Network Analysis of Crypto Currencies

Analysis of the traditional currencies is not easy as the transactions are not centralized but rather take place over a large number of banks and commercial entities. Digital crypto currencies, however, require a public ledger to work. A crypto currency is a medium of exchange using cryptography to secure the trans- actions and to control the creation of new units. In this thesis, we analyze some of the popular crypto currencies. As the transaction data of crypto currencies are publicly available, we construct a network of transactions and extract the time and date of each payment for the analyzed crypto currencies. We investigate the structure of transaction network by measuring the network characteristics. In par- ticular, we compare the evolution of Bitcoin and Litecoin currency systems, two of the currently most popular systems; analyze the wealth correlation with degree distribution for Bitcoin and litecoin; and investigate the transactions by the top 100 richest people in Bitcoin, Litecoin, Dash, Dogecoin, Peercoin, and Namecoin crypto currencies. Additionally, as the price of digital currencies are highly volatile, we perform a regression analysis on factors that affect the price of the Bitcoin currency in USD and derive a model with the factors that affects Bitcoin price

HYDRODYNAMIC AND HEAT TRANSFER STUDIES IN RISER SYSTEM FOR WASTE HEAT RECOVERY USING LIMESTONE

Suspension pre-heater (SP) system has been a unique development in the field of cement manufacture. A modern dry process cement plant vitally constitutes, the suspension pre-heater and the pre-calcinator, which together account for a drastic reduction in the specific energy consumption in the klin, to as low as800 kcal/kg clinker. Experimental investigations were carried out using limestone particles in a metallic fluid particle heat exchanger. Acceleration length is determined by plotting pressure gradient versus riser height. From the model, experimental gas and solid temperatures were measured at different heights of the riser. Exhaustive heat transfer studies were made in hot model by varying particle size, solid flow rate and gas velocities. An empirical correlation is developed for the Nusselt number using regression analysis

To Learn or Not to Learn Features for Deformable Registration?

Feature-based registration has been popular with a variety of features ranging from voxel intensity to Self-Similarity Context (SSC). In this paper, we examine the question on how features learnt using various Deep Learning (DL) frameworks can be used for deformable registration and whether this feature learning is necessary or not. We investigate the use of features learned by different DL methods in the current state-of-the-art discrete registration framework and analyze its performance on 2 publicly available datasets. We draw insights into the type of DL framework useful for feature learning and the impact, if any, of the complexity of different DL models and brain parcellation methods on the performance of discrete registration. Our results indicate that the registration performance with DL features and SSC are comparable and stable across datasets whereas this does not hold for low level features.Comment: 9 pages, 4 figure

The human RecQ helicases BLM and RECQL4 cooperate to preserve genome stability

Bacteria and yeast possess one RecQ helicase homolog whereas humans contain five RecQ helicases, all of which are important in preserving genome stability. Three of these, BLM, WRN and RECQL4, are mutated in human diseases manifesting in premature aging and cancer. We are interested in determining to which extent these RecQ helicases function cooperatively. Here, we report a novel physical and functional interaction between BLM and RECQL4. Both BLM and RECQL4 interact in vivo and in vitro. We have mapped the BLM interacting site to the N-terminus of RECQL4, comprising amino acids 361-478, and the region of BLM encompassing amino acids 1-902 interacts with RECQL4. RECQL4 specifically stimulates BLM helicase activity on DNA fork substrates in vitro. The in vivo interaction between RECQL4 and BLM is enhanced during the S-phase of the cell cycle, and after treatment with ionizing radiation. The retention of RECQL4 at DNA double-strand breaks is shortened in BLM-deficient cells. Further, depletion of RECQL4 in BLM-deficient cells leads to reduced proliferative capacity and an increased frequency of sister chromatid exchanges. Together, our results suggest that BLM and RECQL4 have coordinated activities that promote genome stabilit

A Selective Small Molecule DNA2 Inhibitor for Sensitization of Human Cancer Cells to Chemotherapy

Cancer cells frequently up-regulate DNA replication and repair proteins such as the multifunctional DNA2 nuclease/helicase, counteracting DNA damage due to replication stress and promoting survival. Therefore, we hypothesized that blocking both DNA replication and repair by inhibiting the bifunctional DNA2 could be a potent strategy to sensitize cancer cells to stresses from radiation or chemotherapeutic agents. We show that homozygous deletion of DNA2 sensitizes cells to ionizing radiation and camptothecin (CPT). Using a virtual high throughput screen, we identify 4-hydroxy-8-nitroquinoline-3-carboxylic acid (C5) as an effective and selective inhibitor of DNA2. Mutagenesis and biochemical analysis define the C5 binding pocket at a DNA-binding motif that is shared by the nuclease and helicase activities, consistent with structural studies that suggest that DNA binding to the helicase domain is necessary for nuclease activity. C5 targets the known functions of DNA2 in vivo: C5 inhibits resection at stalled forks as well as reducing recombination. C5 is an even more potent inhibitor of restart of stalled DNA replication forks and over-resection of nascent DNA in cells defective in replication fork protection, including BRCA2 and BOD1L. C5 sensitizes cells to CPT and synergizes with PARP inhibitors

Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellum of the Tc1 mouse model of Down Syndrome - a comprehensive morphometric analysis with active staining contrast-enhanced MRI

Down Syndrome is a chromosomal disorder that affects the development of cerebellar cortical lobules. Impaired neurogenesis in the cerebellum varies among different types of neuronal cells and neuronal layers. In this study, we developed an imaging analysis framework that utilizes gadolinium-enhanced ex vivo mouse brain MRI. We extracted the middle Purkinje layer of the mouse cerebellar cortex, enabling the estimation of the volume, thickness, and surface area of the entire cerebellar cortex, the internal granular layer, and the molecular layer in the Tc1 mouse model of Down Syndrome. The morphometric analysis of our method revealed that a larger proportion of the cerebellar thinning in this model of Down Syndrome resided in the inner granule cell layer, while a larger proportion of the surface area shrinkage was in the molecular layer

Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation

Brain volume measurements extracted from structural MRI data sets are a widely accepted neuroimaging biomarker to study mouse models of neurodegeneration. Whether to acquire and analyze data in vivo or ex vivo is a crucial decision during the phase of experimental designs, as well as data analysis. In this work, we extracted the brain structures for both longitudinal in vivo and single-time-point ex vivo MRI acquired from the same animals using accurate automatic multi-atlas structural parcellation, and compared the corresponding statistical and classification analysis. We found that most gray matter structures volumes decrease from in vivo to ex vivo, while most white matter structures volume increase. The level of structural volume change also varies between different genetic strains and treatment. In addition, we showed superior statistical and classification power of ex vivo data compared to the in vivo data, even after resampled to the same level of resolution. We further demonstrated that the classification power of the in vivo data can be improved by incorporating longitudinal information, which is not possible for ex vivo data. In conclusion, this paper demonstrates the tissue-specific changes, as well as the difference in statistical and classification power, between the volumetric analysis based on the in vivo and ex vivo structural MRI data. Our results emphasize the importance of longitudinal analysis for in vivo data analysis

G-Quadruplex DNA Sequences Are Evolutionarily Conserved and Associated with Distinct Genomic Features in Saccharomyces cerevisiae

G-quadruplex DNA is a four-stranded DNA structure formed by non-Watson-Crick base pairing between stacked sets of four guanines. Many possible functions have been proposed for this structure, but its in vivo role in the cell is still largely unresolved. We carried out a genome-wide survey of the evolutionary conservation of regions with the potential to form G-quadruplex DNA structures (G4 DNA motifs) across seven yeast species. We found that G4 DNA motifs were significantly more conserved than expected by chance, and the nucleotide-level conservation patterns suggested that the motif conservation was the result of the formation of G4 DNA structures. We characterized the association of conserved and non-conserved G4 DNA motifs in Saccharomyces cerevisiae with more than 40 known genome features and gene classes. Our comprehensive, integrated evolutionary and functional analysis confirmed the previously observed associations of G4 DNA motifs with promoter regions and the rDNA, and it identified several previously unrecognized associations of G4 DNA motifs with genomic features, such as mitotic and meiotic double-strand break sites (DSBs). Conserved G4 DNA motifs maintained strong associations with promoters and the rDNA, but not with DSBs. We also performed the first analysis of G4 DNA motifs in the mitochondria, and surprisingly found a tenfold higher concentration of the motifs in the AT-rich yeast mitochondrial DNA than in nuclear DNA. The evolutionary conservation of the G4 DNA motif and its association with specific genome features supports the hypothesis that G4 DNA has in vivo functions that are under evolutionary constraint