Pathologies of Neural Models Make Interpretations Difficult

One way to interpret neural model predictions is to highlight the most important input features---for example, a heatmap visualization over the words in an input sentence. In existing interpretation methods for NLP, a word's importance is determined by either input perturbation---measuring the decrease in model confidence when that word is removed---or by the gradient with respect to that word. To understand the limitations of these methods, we use input reduction, which iteratively removes the least important word from the input. This exposes pathological behaviors of neural models: the remaining words appear nonsensical to humans and are not the ones determined as important by interpretation methods. As we confirm with human experiments, the reduced examples lack information to support the prediction of any label, but models still make the same predictions with high confidence. To explain these counterintuitive results, we draw connections to adversarial examples and confidence calibration: pathological behaviors reveal difficulties in interpreting neural models trained with maximum likelihood. To mitigate their deficiencies, we fine-tune the models by encouraging high entropy outputs on reduced examples. Fine-tuned models become more interpretable under input reduction without accuracy loss on regular examples.Comment: EMNLP 2018 camera read

The Revolting Monster - A Consideration of Existentialist Themes in Mary Shelley\u27s Frankenstein Through a Comparison to Albert Camus\u27 The Stranger

This Master’s thesis is concerned with analyzing key themes and ideas in Mary Shelley’s Frankenstein through an existentialist lens which is made possible through a comparison to themes and ideas in Albert Camus’ The Stranger. I aim to make a contribution to my field by fulfilling a comparison that has long been made since the late 1960s when conversations about British Romanticism and Existentialism were still common. The purpose of my first chapter is to elucidate a new argument about the relationship between these two novels. There is a discernable element of Camusian Revolt exhibited by the Creature in some of the most riveting passages of Frankenstein; this element is all the more clearer when placed in conversation with the actions of Meursault, the protagonist of The Stranger. Through more specific examples, and a large reliance on the historical context of both novels that this project is concerned with, I am able to draw connections that go further than thematic similarities and show the relevance of these ideas to readers in our time. The second chapter consists of historical context that sets up an understanding of the reception of Frankenstein and the ensuing consequences of this novel for ruling body interested in maintaining a permanent underclass within the population. The third chapter examines the species of Revolt within Frankenstein by comparing it to The Stranger in order to reach conclusions about the significance of these themes today. The final chapter is an observation about the behavior of revolt modeled by the authors discussed in this thesis. It proposes that the act of writing and creating art is in itself an act of revolt which is the true message the authors intended to convey. It also argues that the medium of the novel is the most effective method of expression for revolt because it taps into human experience in a way no other distinct work of art can

Multi-Class Classification for Identifying JPEG Steganography Embedding Methods

Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher s discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images. Based on classifying stego images created from research and commercial JPEG steganography techniques, F5, JP Hide, JSteg, Model-based, Model-based Version 1.2, OutGuess, Steganos, StegHide and UTSA embedding methods, the performance of the system shows a statistically significant increase in classification accuracy of 5%. In addition, this system provides a solution for identifying steganographic fingerprints as well as the ability to include future multi-class classification tools

Oncogenic mutation profiling in new lung cancer and mesothelioma cell lines

published_or_final_versio

The Bolocam Galactic Plane Survey IV: 1.1 and 0.35 mm Dust Continuum Emission in the Galactic Center Region

The Bolocam Galactic Plane Survey (BGPS) data for a six square degree region of the Galactic plane containing the Galactic center is analyzed and compared to infrared and radio continuum data. The BGPS 1.1 mm emission consists of clumps interconnected by a network of fainter filaments surrounding cavities, a few of which are filled with diffuse near-IR emission indicating the presence of warm dust or with radio continuum characteristic of HII regions or supernova remnants. New 350 {\mu}m images of the environments of the two brightest regions, Sgr A and B, are presented. Sgr B2 is the brightest mm-emitting clump in the Central Molecular Zone and may be forming the closest analog to a super star cluster in the Galaxy. The Central Molecular Zone (CMZ) contains the highest concentration of mm and sub-mm emitting dense clumps in the Galaxy. Most 1.1 mm features at positive longitudes are seen in silhouette against the 3.6 to 24 {\mu}m background observed by the Spitzer Space Telescope. However, only a few clumps at negative longitudes are seen in absorption, confirming the hypothesis that positive longitude clumps in the CMZ tend to be on the near-side of the Galactic center, consistent with the suspected orientation of the central bar in our Galaxy. Some 1.1 mm cloud surfaces are seen in emission at 8 {\mu}m, presumably due to polycyclic aromatic hydrocarbons (PAHs). A ~0.2\degree (~30 pc) diameter cavity and infrared bubble between l \approx 0.0\degree and 0.2\degree surrounds the Arches and Quintuplet clusters and Sgr A. The bubble contains several clumpy dust filaments that point toward Sgr A\ast; its potential role in their formation is explored. [abstract truncated]Comment: 76 pages, 22 figures, published in ApJ: http://iopscience.iop.org/0004-637X/721/1/137

Wide field CO J = 3->2 mapping of the Serpens Cloud Core

Context. Outflows provide indirect means to get an insight on diverse star formation associated phenomena. On scales of individual protostellar cores, outflows combined with intrinsic core properties can be used to study the mass accretion/ejection process of heavily embedded protostellar sources. Methods. An area comprising 460"x230" of the Serpens cloud core has been mapped in 12 CO J = 3\to 2 with the HARP-B heterodyne array at the James Clerk Maxwell Telescope; J = 3\to 2 observations are more sensitive tracers of hot outflow gas than lower J CO transitions; combined with the high sensitivity of the HARP-B receptors outflows are sharply outlined, enabling their association with individual protostellar cores. Results. Most of ~20 observed outflows are found to be associated with known protostellar sources in bipolar or unipolar configurations. All but two outflow/core pairs in our sample tend to have a projected orientation spanning roughly NW-SE. The overall momentum driven by outflows in Serpens lies between 3.2 and 5.1 x 10^(-1) M\odot km s^(-1), the kinetic energy from 4.3 to 6.7 x 10^(43) erg and momentum flux is between 2.8 and 4.4 x 10^(-4) M\odot km s^(-1) yr^(-1). Bolometric luminosities of protostellar cores based on Spitzer photometry are found up to an order of magnitude lower than previous estimations derived with IRAS/ISO data. Conclusions. We confirm the validity of the existing correlations between the momentum flux and bolometric luminosity of Class I sources for the homogenous sample of Serpens, though we suggest that they should be revised by a shift to lower luminosities. All protostars classified as Class 0 sources stand well above the known Class I correlations, indicating a decline in momentum flux between the two classes.Comment: 15 pages, 10 figures, accepted for publication in A&

Magnetism and its microscopic origin in iron-based high-temperature superconductors

High-temperature superconductivity in the iron-based materials emerges from, or sometimes coexists with, their metallic or insulating parent compound states. This is surprising since these undoped states display dramatically different antiferromagnetic (AF) spin arrangements and N$\rm \acute{e}$el temperatures. Although there is general consensus that magnetic interactions are important for superconductivity, much is still unknown concerning the microscopic origin of the magnetic states. In this review, progress in this area is summarized, focusing on recent experimental and theoretical results and discussing their microscopic implications. It is concluded that the parent compounds are in a state that is more complex than implied by a simple Fermi surface nesting scenario, and a dual description including both itinerant and localized degrees of freedom is needed to properly describe these fascinating materials.Comment: 14 pages, 4 figures, Review article, accepted for publication in Nature Physic

Wnt5a induces ROR1 to complex with HS1 to enhance migration of chronic lymphocytic leukemia cells.

ROR1 (receptor tyrosine kinase-like orphan receptor 1) is a conserved, oncoembryonic surface antigen expressed in chronic lymphocytic leukemia (CLL). We found that ROR1 associates with hematopoietic-lineage-cell-specific protein 1 (HS1) in freshly isolated CLL cells or in CLL cells cultured with exogenous Wnt5a. Wnt5a also induced HS1 tyrosine phosphorylation, recruitment of ARHGEF1, activation of RhoA and enhanced chemokine-directed migration; such effects could be inhibited by cirmtuzumab, a humanized anti-ROR1 mAb. We generated truncated forms of ROR1 and found its extracellular cysteine-rich domain or kringle domain was necessary for Wnt5a-induced HS1 phosphorylation. Moreover, the cytoplamic, and more specifically the proline-rich domain (PRD), of ROR1 was required for it to associate with HS1 and allow for F-actin polymerization in response to Wnt5a. Accordingly, we introduced single amino acid substitutions of proline (P) to alanine (A) in the ROR1 PRD at positions 784, 808, 826, 841 or 850 in potential SH3-binding motifs. In contrast to wild-type ROR1, or other ROR1P→︀A mutants, ROR1P(841)A had impaired capacity to recruit HS1 and ARHGEF1 to ROR1 in response to Wnt5a. Moreover, Wnt5a could not induce cells expressing ROR1P(841)A to phosphorylate HS1 or activate ARHGEF1, and was unable to enhance CLL-cell motility. Collectively, these studies indicate HS1 plays an important role in ROR1-dependent Wnt5a-enhanced chemokine-directed leukemia-cell migration

A specific case in the classification of woods by FTIR and chemometric: discrimination of Fagales from Malpighiales

Fourier transform infrared (FTIR) spectroscopic data was used to classify wood samples from nine species within the Fagales and Malpighiales using a range of multivariate statistical methods. Taxonomic classification of the family Fagaceae and Betulaceae from Angiosperm Phylogenetic System Classification (APG II System) was successfully performed using supervised pattern recognition techniques. A methodology for wood sample discrimination was developed using both sapwood and heartwood samples. Ten and eight biomarkers emerged from the dataset to discriminate order and family, respectively. In the species studied FTIR in combination with multivariate analysis highlighted significant chemical differences in hemicelluloses, cellulose and guaiacyl (lignin) and shows promise as a suitable approach for wood sample classification