Fast Automatic Bayesian Cubature Using Matching Kernels and Designs

Automatic cubatures approximate integrals to user-specified error tolerances. For high dimensional problems, it is difficult to adaptively change the sampling pattern to focus on peaks because peaks can hide more easily in high dimensional space. But, one can automatically determine the sample size, $n$, given a reasonable, fixed sampling pattern. This approach is pursued in Jagadeeswaran and Hickernell, Stat.\ Comput., 29:1214-1229, 2019, where a Bayesian perspective is used to construct a credible interval for the integral, and the computation is terminated when the half-width of the interval is no greater than the required error tolerance. Our earlier work employs integration lattice sampling, and the computations are expedited by the fast Fourier transform because the covariance kernels for the Gaussian process prior on the integrand are chosen to be shift-invariant. In this chapter, we extend our fast automatic Bayesian cubature to digital net sampling via \emph{digitally} shift-invariant covariance kernels and fast Walsh transforms. Our algorithm is implemented in the MATLAB Guaranteed Automatic Integration Library (GAIL) and the QMCPy Python library.Comment: PhD thesi

A Systematic Review of Formative Assessment to Support Students Learning Computer Programming

Formative assessment aims to increase student understanding, instructor instruction, and learning by providing feedback on students\u27 progress. The goal of this systematic review is to discover trends on formative assessment techniques used to support computer programming learners by synthesizing literature published between 2013 and 2023. 17 articles that were peer-reviewed and published in journals were examined from the initial search of 197 studies. According to the findings, all the studies were conducted at the higher education level and only a small number at the secondary school level. Overall, most studies found that motivation, scaffolding, and engagement were the three main goals of feedback, with less research finding that metacognitive goals were the intended outcomes. The two techniques for facilitating formative feedback that were used most frequently were compiler or testing based error messages and customised error messages. The importance of formative feedback is highlighted in the reviewed articles, supporting the contention that assessments used in programming courses should place a heavy emphasis on motivating students to increase their level of proficiency. This study also suggests a formative assessment that employs an adaptive strategy to evaluate the ability level of the novice students and motivate them to learn programming to acquire the necessary knowledge

In silico identification of conserved microRNAs in large number of diverse plant species

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are recently discovered small non-coding RNAs that play pivotal roles in gene expression, specifically at the post-transcriptional level in plants and animals. Identification of miRNAs in large number of diverse plant species is important to understand the evolution of miRNAs and miRNA-targeted gene regulations. Now-a-days, publicly available databases play a central role in the in-silico biology. Because, at least ~21 miRNA families are conserved in higher plants, a homology based search using these databases can help identify orthologs or paralogs in plants.</p> <p>Results</p> <p>We searched all publicly available nucleotide databases of genome survey sequences (GSS), high-throughput genomics sequences (HTGS), expressed sequenced tags (ESTs) and nonredundant (NR) nucleotides and identified 682 miRNAs in 155 diverse plant species. We found more than 15 conserved miRNA families in 11 plant species, 10 to14 families in 10 plant species and 5 to 9 families in 29 plant species. Nineteen conserved miRNA families were identified in important model legumes such as <it>Medicago</it>, <it>Lotus </it>and soybean. Five miRNA families – miR319, miR156/157, miR169, miR165/166 and miR394 – were found in 51, 45, 41, 40 and 40 diverse plant species, respectively. miR403 homologs were found in 16 dicots, whereas miR437 and miR444 homologs, as well as the miR396d/e variant of the miR396 family, were found only in monocots, thus providing large-scale authenticity for the dicot- and monocot-specific miRNAs. Furthermore, we provide computational and/or experimental evidence for the conservation of 6 newly found Arabidopsis miRNA homologs (miR158, miR391, miR824, miR825, miR827 and miR840) and 2 small RNAs (small-85 and small-87) in <it>Brassica spp</it>.</p> <p>Conclusion</p> <p>Using all publicly available nucleotide databases, 682 miRNAs were identified in 155 diverse plant species. By combining the expression analysis with the computational approach, we found that 6 miRNAs and 2 small RNAs that have been identified only in Arabidopsis thus far, are also conserved in <it>Brassica spp</it>. These findings will be useful for tracing the evolution of small RNAs by examining their expression in common ancestors of the <it>Arabidopsis</it>-<it>Brassica </it>lineage.</p

On Bounding and Approximating Functions of Multiple Expectations using Quasi-Monte Carlo

Monte Carlo and Quasi-Monte Carlo methods present a convenient approach for approximating the expected value of a random variable. Algorithms exist to adaptively sample the random variable until a user defined absolute error tolerance is satisfied with high probability. This work describes an extension of such methods which supports adaptive sampling to satisfy general error criteria for functions of a common array of expectations. Although several functions involving multiple expectations are being evaluated, only one random sequence is required, albeit sometimes of larger dimension than the underlying randomness. These enhanced Monte Carlo and Quasi-Monte Carlo algorithms are implemented in the QMCPy Python package with support for economic and parallel function evaluation. We exemplify these capabilities on problems from machine learning and global sensitivity analysis

Radiographic analysis of zebrafish skeletal defects

AbstractSystematic identification of skeletal dysplasias in model vertebrates provides insight into the pathogenesis of human skeletal disorders and can aid in the identification of orthologous human genes. We are undertaking a mutagenesis screen for skeletal dysplasias in adult zebrafish, using radiography to detect abnormalities in skeletal anatomy and bone morphology. We have isolated chihuahua, a dominant mutation causing a general defect in bone growth. Heterozygous chihuahua fish have phenotypic similarities to human osteogenesis imperfecta, a skeletal dysplasia caused by mutations in the type I collagen genes. Mapping and molecular characterization of the chihuahua mutation indicates that the defect resides in the gene encoding the collagen I(α1) chain. Thus, chihuahua accurately models osteogenesis imperfecta at the biologic and molecular levels, and will prove an important resource for studies on the disease pathophysiology. Radiography is a practical screening tool to detect subtle skeletal abnormalities in the adult zebrafish. The identification of chihuahua demonstrates that mutant phenotypes analogous to human skeletal dysplasias will be discovered

Generating cadastral base for Kolathupalayam village in Tamil Nadu from high resolution LISS IV sensor data

In the present study an attempt was made to generate cadastral base from high resolution satellite image (LISS IV) and to integrate with land use land cover information. The digital cadastral map with survey number for Kolathupalayam village in Erode district of Tamil Nadu was scanned, digitized and parcels were extracted. Similarly parcels or field boundaries were digitized and extracted from satellite image and were statistically compared by area. The area obtained from both the source through digitization correlated well with a pearson correlation of 0.87 and it was significant at 5 per cent. Thus, the area comparisons from both methods are significant indicating boundaries of individual fields generated from satellite image matched well with the one generated from cadastral map. The cadastral base generated from satellite image was overlaid on the classified image (level III output) to identify and generate land cover information against each survey number. Thus, the LISS IV data can be used for the identification and extraction of cadastral boundaries with good accuracy

Enhancing Self-Security in Wireless Adhoc Networks Using Multi-hop Authentication

Department of Computer Scienc

DNA catalysts as phosphatases and as phosphoserine lyases

Proteins and RNA are the only known biopolymers that have catalytic roles in nature, whereas DNA is primarily considered to store and transfer genetic information. However, artificial single-stranded DNA has been identified by in vitro selection to catalyze several chemical reactions and several of those are of biological relevance. For in vitro selection or directed evolution of proteins, direct amplification is not possible, and it essential to attach the genotype to the phenotype. For nucleic acids however, the functional biopolymer can be readily amplified. DNA has the advantage of being directly amplified by polymerases, whereas RNA requires an additional reverse transcription step. Moreover, DNA catalysts identified by in vitro selection processes have shown similar catalytic proficiency as RNA. DNA has added advantages of low cost of chemical synthesis and higher stability. Considering these factors combined, identification of artificial DNA catalysts (deoxyribozymes) for chemical reactions is a valuable endeavor with long-term implications. Protein post-translational modifications (PTMs) are highly important in biological processes involving cellular regulation. Additionally, PTMs serve as important intermediates or key motifs on natural products and bioactive peptides. The natural protein enzymes carrying out the essential modifications may have several shortcomings for biotechnological use. Identification of artificial DNA catalysts with ability to perform chemoselective post-translation chemical reaction would be highly useful in studying biological regulatory processes, performing synthesis and late-stage diversification of post-translationally modified peptides, as well as carrying out other important functions that natural proteins may not readily solve. My first effort was to identify DNA enzymes with peptide/protein phosphatase activity, more specifically dephosphorylation of peptide side chains. Without a catalyst, phosphomonoester hydrolysis reactions have exceedingly low spontaneous reaction rates. Nature utilizes proficient protein enzymes to perform this challenging reaction with great efficiency. Using a known DNA catalyst for the in vitro selection process, new DNA catalysts were identified with phosphatase activity. The phosphatase DNA catalysts exhibited multiple-turnover activity with phosphotyrosine-containing free peptides and were active even in the presence of externally added cell lysate or bovine serum albumin (BSA). Furthermore, the best DNA phosphatase functioned with a larger protein substrate. This established the fundamental ability of DNA to catalyze dephosphorylation of amino acid side chain residues. The study also suggested that phosphatase DNA catalysts could perform intracellular phosphatase activity. Hence, these deoxyribozymes were functionalized on gold nanoparticles and delivered inside live mammalian cells to investigate if they behave as functional protein analogues (or mimics) of recombinantly expressed Protein Tyrosine Phosphatase (PTP1B). Separately, efforts were directed towards the important goal of identifying sequence-selective phosphatase deoxyribozymes. Although three separate efforts were directed towards identifying sequence-selective phosphatases deoxyribozymes, we were unsuccessful in accomplishing this specific goal of selectivity in the context of peptide sequence discrimination. Dehydroalanine (Dha) is a non-proteinogenic electrophilic amino acid that serves as a synthetic intermediate or product in the biosynthesis of several bioactive cyclic peptides such as lantibiotics, thiopeptides and microcystins. DNA enzymes were identified to establish the fundamental catalytic ability to eliminate phosphate from phosphoserine (pSer) to form Dha, namely phosphoserine lyase activity. Furthermore, DhaDz1 was utilized to achieve chemo-enzymatic synthesis of a cyclic cystathionine-containing peptide. Based on this initial success, future efforts will be directed to achieve sequence-general phosphoserine and phosphotyrosine lyase activity. Separately, application of sequence-general lyases in the synthesis of complex lanthipeptides and enrichment of phosphopeptides/proteins in phosphoproteomics will be explored