Evidence-Based Detection of Pancreatic Canc

This study is an effort to develop a tool for early detection of pancreatic cancer using evidential reasoning. An evidential reasoning model predicts the likelihood of an individual developing pancreatic cancer by processing the outputs of a Support Vector Classifier, and other input factors such as smoking history, drinking history, sequencing reads, biopsy location, family and personal health history. Certain features of the genomic data along with the mutated gene sequence of pancreatic cancer patients was obtained from the National Cancer Institute (NIH) Genomic Data Commons (GDC). This data was used to train the SVC. A prediction accuracy of ~85% with a ROC AUC of 83.4% was achieved. Synthetic data was assembled in different combinations to evaluate the working of evidential reasoning model. Using this, variations in the belief interval of developing pancreatic cancer are observed. When the model is provided with an input of high smoking history and family history of cancer, an increase in the evidential reasoning interval in belief of pancreatic cancer and support in the machine learning model prediction is observed. Likewise, decrease in the quantity of genetic material and an irregularity in the cellular structure near the pancreas increases support in the machine learning classifier’s prediction of having pancreatic cancer. This evidence-based approach is an attempt to diagnose the pancreatic cancer at a premalignant stage. Future work includes using the real sequencing reads as well as accurate habits and real medical and family history of individuals to increase the efficiency of the evidential reasoning model. Next steps also involve trying out different machine learning models to observe their performance on the dataset considered in this study

On the Conditional Distribution of a Multivariate Normal given a Transformation - the Linear Case

We show that the orthogonal projection operator onto the range of the adjoint of a linear operator $T$ can be represented as $UT,$ where $U$ is an invertible linear operator. Using this representation we obtain a decomposition of a Normal random vector $Y$ as the sum of a linear transformation of $Y$ that is independent of $TY$ and an affine transformation of $TY$. We then use this decomposition to prove that the conditional distribution of a Normal random vector $Y$ given a linear transformation $\mathcal{T}Y$ is again a multivariate Normal distribution. This result is equivalent to the well-known result that given a $k$-dimensional component of a $n$-dimensional Normal random vector, where $k<n$, the conditional distribution of the remaining $\left(n-k\right)$-dimensional component is a $\left(n-k\right)$-dimensional multivariate Normal distribution, and sets the stage for approximating the conditional distribution of $Y$ given $g\left(Y\right)$, where $g$ is a continuously differentiable vector field.Comment: 2/6/18: Updated the proof of Theorem 4 & added a corollary. arXiv admin note: text overlap with arXiv:1612.0121

Cell-Mediated Immunity in Porcine Reproductive and Respiratory Syndrome Virus

Porcine reproductive and respiratory syndrome virus is a significant swine pathogen which exhibits considerable sequence diversity. In an attempt to identify highly conserved T-cell epitopes contained in proteins of this virus, we examined heptadecamer peptides spanning the sequence of the PRRSV nonstructural proteins 9, 10 and 11, all of them are highly conserved, for their ability to elicit a recall proliferative and interferon-gamma response in peripheral blood mononuclear cells obtained from pigs immunized against the type-II PRRSV strain FL-12. These studies led to the identification of seven peptides, two from each NSP 9 and NSP 10 and, three from NSP 11 that appear to contain T-cell epitopes. Comparison of the amino acid sequence of these seven peptide sequences to the analogous sequences from a diverse sample of type-II PRRSV strains indicated that these sequences are highly conserved and thus contain highly conserved T-cell epitopes. The identified epitopes may be important in the formulation of immunogens to provide broad cross-protection against diverse PRRSV strains. Advisor: Fernando A. Osori

FORMALISATION OF LABOUR: THE ECONOMICS OF PROSTITUTION IN INDIA

Prostitution is one of the oldest professions of the world and has been practiced since the birth of the Indian society. The moral ambiguity that engulfs this practice is increasingly bringing out the question of its formalization. This paper assesses the technical shortcomings in India that go unnoticed in the midst of the social debate of a formal industry for prostitution and objectively lays out a steady path for a better socio-economic development. A historical analogy was employed in the prediction of the outcomes of the policy models of the Dutch and Bangladesh in the Indian context by employing economic theories. This application places the questions asked in the context of the current stage of development of India. Along with Growth Indices, Human Trafficking Statistics and trends on HIV/AIDS are superimposed into this because of the direct impact it has on the Prostitution industry and to examine how the legalization affects these statistics. With reference to the analytical insights studied, the paper arrives at a conclusive inference that India is, as yet, not economically equipped to undergo formalization of prostitution. The developing nation does not have the preconditions for ensuring the upward trajectory in the standard of living. This underlines the ever asserted disparity between Growth and Development and the fact that one does not necessitate the other. The findings are backed by statistical data from surveys from national registries, research and reports.&nbsp

Generalization of Pascal\u27s Rule and Leibniz\u27s Rule for Differentiation

We generalize the combinatorial identity for binomial coefficients underlying the construction of Pascal\u27s Triangle to multinomial coefficients underlying the construction of Pascal\u27s Simplex. Using this identity, we present a new proof of the formula for calculating the nth derivative of the product of k functions, a generalization of Leibniz\u27s Rule for differentiation

Cell-Mediated Immunity in Porcine Reproductive and Respiratory Syndrome Virus

Porcine reproductive and respiratory syndrome virus is a significant swine pathogen which exhibits considerable sequence diversity. In an attempt to identify highly conserved T-cell epitopes contained in proteins of this virus, we examined heptadecamer peptides spanning the sequence of the PRRSV nonstructural proteins 9, 10 and 11, all of them are highly conserved, for their ability to elicit a recall proliferative and interferon-gamma response in peripheral blood mononuclear cells obtained from pigs immunized against the type-II PRRSV strain FL-12. These studies led to the identification of seven peptides, two from each NSP 9 and NSP 10 and, three from NSP 11 that appear to contain T-cell epitopes. Comparison of the amino acid sequence of these seven peptide sequences to the analogous sequences from a diverse sample of type-II PRRSV strains indicated that these sequences are highly conserved and thus contain highly conserved T-cell epitopes. The identified epitopes may be important in the formulation of immunogens to provide broad cross-protection against diverse PRRSV strains. Advisor: Fernando A. Osori