497 research outputs found
Author Correction: Deficiency of TET3 leads to a genome-wide DNA hypermethylation episignature in human whole blood (npj Genomic Medicine, (2021), 6, 1, (92), 10.1038/s41525-021-00256-y):Deficiency of TET3 leads to a genome-wide DNA hypermethylation episignature in human whole blood (npj Genomic Medicine, (2021), 6, 1, (92), 10.1038/s41525-021-00256-y)
Full text linkIn this article the author name Siddharth Banka was incorrectly written as Sidharth Banka. The original article has been corrected.</p
Towards autonomic virtual machine management
No full textVirtual machine technologies are gaining wide acceptance in today’s era due to invaluable services in system management, server consolidation, and secure resource containment along with providing requisite application execution environment. Every virtual machine platform reduces dependence on hardware by fully or partially abstracting operating systems enabling flexible control of manipulation or migration of guest machines by manual system administration or reactive/proactive approaches to management. This dissertation focuses on resolving the resource reservation problem to help define a mathematical model and study interference within multiple virtual machines while trying to achieve load balancing and improve performance efficiency. Our goal is three-pronged. Firstly, we aim to understand the underlying support available for virtual machine migration and pursue new technologies or abstractions to improve efficiency and speed of the data transfer. Secondly, we carefully evaluate all the resources used by VMs for proper functioning and study the synchronization and multiplexing processes underneath which delineate when and where to migrate a virtual machine. Finally, we attempt to deduce the action to perform on running VMs (manipulation or resource configuration) so as to resolve the issue at hand. To achieve these goals, we follow a step-by-step procedure limiting the number of variable parameters and analyze the outcome of focal experiments. The results show that, using RDMA (Remote Direct Memory Access) to perform virtual machine migration can be used only in scenarios where the underlying hardware offers support for such transactions (eg. InfiniBand architecture) and such an abstraction over TCP/IP does not ameliorate efficiency of VM transfers. Further, a utility based function designed to analyze environment and application metrics and project an area of good/bad states on a map would require a plethora of parameters increasing its complexity. Considering VM re-distribution, one can predict the ideal number and time of migration of guest virtual machines on any configuration by gathering statistics from parallel migration for graphical analysis. Parallel VM migration gives us shorter average transfer time and higher latencies per VM. Pinning of virtual CPUs to VMs improves the performance efficiency of applications compared to sharing of CPUs.M.S.Includes bibliographical referencesby Siddharth Wag
Special Session: STT-MRAMs: Technology, Design and Test
Full text linkSTT-MRAM has long been a promising non-volatile memory solution for the embedded application space owing to its attractive characteristics such as non-volatility, low leakage, high endurance, and scalability. However, the operating requirements for high-performance computing (HPC) and low power (LP) applications involve different challenges. This paper addresses different aspects of STT-MRAM; it will cover state-of-the-art, some new results and future challenges related to technology, design and test. While STT-MRAM devices have shown encouraging performance metrics at device-level, a key challenge has been achieving backend-of-line (BEOL) CMOS compatibility, while retaining the benefits of low power operation. Scaling demands to improve data densities have placed additional challenges in terms of addressing the impact of process-induced damage on device performance at CD < 100 nm. In addition, the paper discusses the design of reliable read mechanism considering the variability effects. Moreover, the failure of traditional fault modeling and test approaches in model STT-MRAM unique defects for appropriate test solutions is demonstrated in this paper based on silicon data. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Computer EngineeringQuantum & Computer Engineerin
A new microdeletion syndrome involving TBC1D24, ATP6V0C, and PDPK1 causes epilepsy, microcephaly, and developmental delay
No full textCorrected by: Correction: A new microdeletion syndrome involving TBC1D24, ATP6V0C, and PDPK1 causes epilepsy, microcephaly, and developmental delay, in Volume 21, Issue 9, September 2019, Pages 2159-2160. The original version of this Article contained an error in the spelling of the author Siddharth Banka, which was incorrectly given as Siddhart Banka. This has now been corrected in both the PDF and HTML versions of the Article.PURPOSE:Contiguous gene deletions are known to cause several neurodevelopmental syndromes, many of which are caused by recurrent events on chromosome 16. However, chromosomal microarray studies (CMA) still yield copy-number variants (CNVs) of unknown clinical significance. We sought to characterize eight individuals with overlapping 205-kb to 504-kb 16p13.3 microdeletions that are distinct from previously published deletion syndromes. METHODS:Clinical information on the patients and bioinformatic scores for the deleted genes were analyzed. RESULTS:All individuals in our cohort displayed developmental delay, intellectual disability, and various forms of seizures. Six individuals were microcephalic and two had strabismus. The deletion was absent in all 13 parents who were available for testing. The area of overlap encompasses seven genes including TBC1D24, ATP6V0C, and PDPK1 (also known as PDK1). Bi-allelic TBC1D24 pathogenic variants are known to cause nonsyndromic deafness, epileptic disorders, or DOORS syndrome (deafness, onychodystrophy, osteodystrophy, mental retardation, seizures). Sanger sequencing of the nondeleted TBC1D24 allele did not yield any additional pathogenic variants. CONCLUSIONS:We propose that 16p13.3 microdeletions resulting in simultaneous haploinsufficiencies of TBC1D24, ATP6V0C, and PDPK1 cause a novel rare contiguous gene deletion syndrome of microcephaly, developmental delay, intellectual disability, and epilepsy.Bettina E. Mucha, Siddharth Banka, Norbert Fonya Ajeawung, Sirinart Molidperee, Gary G. Chen, Mary Kay Koenig, Rhamat B. Adejumo, Marianne Till, Michael Harbord, Renee Perrier, Emmanuelle Lemyre, Renee-Myriam Boucher, Brian G. Skotko, Jessica L. Waxler, Mary Ann Thomas, Jennelle C. Hodge, Jozef Gecz, Jillian Nicholl, Lesley McGregor, Tobias Linden, Sanjay M. Sisodiya, Damien Sanlaville, Sau W. Cheung, Carl Ernst, and Philippe M. Campea
Computer vision methods for large-scale online clustering and quantitative dermatology
No full textIn modern computer vision applications where datasets are large and updates with new data may be ongoing, methods of online clustering are extremely important. Online clustering algorithms incrementally cluster the data points, use a fraction of the dataset memory, and update the clustering decisions when new data comes in. In this thesis we adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) to incrementally cluster large datasets of features commonly used in computer vision, e.g., 840K color SIFT descriptors, 1.09 million color patches, 60K outlier corrupted grayscale patches, and 700K grayscale SIFT descriptors. We use the algorithm to cluster datasets consisting of non-convex clusters, e.g., Hopkins 155 3-D motion segmentation dataset. We call the adapted version modified-BIRCH (m-BIRCH). BIRCH was originally developed by the database management community. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in the data summarization. Our implementation of the algorithm provides a useful clustering tool and is made publicly available. In the second part of the thesis, we present a micro-level feature based approach to register time-lapse skin images acquired over an extended period of time and multimodal skin images acquired in quick succession. Misregistration between the images makes it difficult to perform quantitative analysis and track the progression of skin disease. We demonstrate the utility of both types of registration, by employing the results for two quantitative dermatology tasks: 1) automatic detection of acne-like regions, and 2) separation of surface and subsurface reflection. Additionally, we have created a time-lapse video showing the registered time-lapse images, which clearly brings out the evolution of acne lesions with time.Ph. D.Includes bibliographical referencesby Siddharth K. Mada
MFA-MTJ Model: Magnetic-Field-Aware Compact Model of pMTJ for Robust STT-MRAM Design
Full text linkThe popularity of perpendicular magnetic tunnel junction (pMTJ)-based spin-transfer torque magnetic random access memories (STT-MRAMs) is growing very fast. The performance of such memories is very sensitive to magnetic fields, including both internal and external ones. This article presents a magnetic-field-aware compact model of pMTJ, named the MFA-magnetic tunnel junction (MTJ) model, for magnetic/electrical co-simulation of MTJ/CMOS circuits. Magnetic measurement data of MTJ devices, with diameters ranging from 35 to 175 nm, are used to calibrate an in-house magnetic coupling model. This model is subsequently integrated into our developed compact pMTJ model, which is implemented in Verilog-A. The superiority of the proposed MFA-MTJ model for device/circuit co-design of STT-MRAM is demonstrated by simulating a single pMTJ as well as STT-MRAM full circuits. The design space is explored under PVT variations and various configurations of magnetic fields.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Computer EngineeringQuantum & Computer Engineerin
Germline intergenic duplications at Xq26.1 underlie Bazex‐Dupré‐Christol basal cell carcinoma susceptibility syndrome
No full textIn this paper we show that Bazex‐Dupré‐Christol syndrome (BDCS), an X‐linked disorder of susceptibility to basal cell carcinomas, is caused by non‐coding Xq26.1 duplications that likely result in dysregulation of ARHGAP36, encoded by a flanking gene
Budhan Stories S2E8: We wanted to go back
No full textEpisode 8 of Season 2 - In this episode we spoke with migrant workers who walked thousands of kilometers to reach their homes in different part of India. We also spoke with labourers who travelled by train and faced hardships. When there was no livelihood options open due to lockdown, millions of labourers walked to their homes. This episode is an effort to capture the gist of their huge suffering on the way and in their hometowns. Created (Author) by: Siddharth Garange. Participants: Budhan Theatre, Dakxin Chhara, Atish Indrekar, Ruchika Kodekar, Chetna Rathod, Kushal Batunge, Keyur Bajrange, Anish Garange, Siddharth Garange, Alice Tilche, Akshay Khanna, Yashodara Udupa, Labour exodus, Labour on foot, Harsh Shodhan, Machan Theatre company, Nasim Akhtar.Supplementary materials include short clips, poster and subtitles.</p
Applications of U-net to diffuse optical tomography data: Image reconstruction and superresolution
Full text linkDi use optical tomography (DOT) is being investigated for effective functional brain imaging. It serves as a cheaper, less bulky and safer alternative to fMRI imaging which is the current gold standard. However, due to the complicated nature of the system, analytical reconstruction approaches begin to fail. Currently functional signal activations are reconstructed using an analytical approach but the quality of the image, especially in terms of resolution, is low. This is one of the primary barriers to making DOT the gold standard for functional brain imaging. This thesis presents the theory behind the inverse problem and discusses possible solutions to image reconstruction and superresolution problems in the DOT brain imaging space. With the growth in deep learning and its applications in medical imaging, a U-net based architecture is proposed to learn the mapping and estimate a higher resolution image. This work shows that the proposed deep learning model trained on simulated images from real-world fMRI images of the human brain can reconstruct higher resolution images while reducing the number of hallucinations.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-05-01The student, Siddharth Muralidaran, accepted the attached license on 2021-04-28 at 13:55.The student, Siddharth Muralidaran, submitted this Thesis for approval on 2021-04-28 at 14:03.This Thesis was approved for publication on 2021-04-28 at 14:12.DSpace SAF Submission Ingestion Package generated from Vireo submission #16605 on 2021-09-16 at 17:06:40Made available in DSpace on 2021-09-17T02:34:50Z (GMT). No. of bitstreams: 2
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Clinical, genetic, epidemiologic, evolutionary, and functional delineation of TSPEAR-related autosomal recessive ectodermal dysplasia 14
Full text linkTSPEAR variants cause autosomal recessive ectodermal dysplasia (ARED) 14. The function of TSPEAR is unknown. The clinical features, the mutation spectrum, and the underlying mechanisms of ARED14 are poorly understood. Combining data from new and previously published individuals established that ARED14 is primarily characterized by dental anomalies such as conical tooth cusps and hypodontia, like those seen in individuals with WNT10A-related odontoonychodermal dysplasia. AlphaFold-predicted structure-based analysis showed that most of the pathogenic TSPEAR missense variants likely destabilize the β-propeller of the protein. Analysis of 100000 Genomes Project (100KGP) data revealed multiple founder TSPEAR variants across different populations. Mutational and recombination clock analyses demonstrated that non-Finnish European founder variants likely originated around the end of the last ice age, a period of major climatic transition. Analysis of gnomAD data showed that the non-Finnish European population TSPEAR gene-carrier rate is ∼1/140, making it one of the commonest AREDs. Phylogenetic and AlphaFold structural analyses showed that TSPEAR is an ortholog of drosophila Closca, an extracellular matrix-dependent signaling regulator. We, therefore, hypothesized that TSPEAR could have a role in enamel knot, a structure that coordinates patterning of developing tooth cusps. Analysis of mouse single-cell RNA sequencing (scRNA-seq) data revealed highly restricted expression of Tspear in clusters representing enamel knots. A tspeara−/−;tspearb−/− double-knockout zebrafish model recapitulated the clinical features of ARED14 and fin regeneration abnormalities of wnt10a knockout fish, thus suggesting interaction between tspear and wnt10a. In summary, we provide insights into the role of TSPEAR in ectodermal development and the evolutionary history, epidemiology, mechanisms, and consequences of its loss of function variants.</p
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