On the Origin of Frictional Adhesion in Geckos: Small Morphological Changes Lead to a Major Biomechanical Transition in the Genus \u3cem\u3eGonatodes\u3c/em\u3e

The evolutionary history of vertebrate locomotion is punctuated by innovations that have permitted expansion into novel ecological niches. Frictional adhesion of geckos is an innovation renowned for enabling locomotion on vertical and inverted smooth surfaces. Much is known about the microstructure and function of the fully-expressed gekkotan adhesive apparatus, although how it originated is poorly understood. Therefore, identifying species that exhibit the earliest stages of expression of frictional adhesion will provide significant insights into the evolution of this trait. Our previous investigation of digital proportions, shape, scalation, skeletal form, and subdigital epidermal micro-ornamentation in the genus Gonatodes led us to hypothesize that Gonatodes humeralisexpresses incipient frictional adhesion. To test this, we first conducted a phylogenetic analysis of Gonatodes and related sphaerodactyl genera to clarify the historical context of the evolution of frictional adhesive capability in the genus. We then measured the ability of G. humeralis and its close relatives to generate frictional adhesive force, examined their locomotor capabilities on low-friction surfaces, and observed animals in their natural habitat. After accounting for body mass and phylogenetic relationships, we found that G. humeralis generates frictional adhesive force essentially equivalent to that of Anolis, and can scale vertical smooth surfaces. Gonatodes vittatus, a species that lacks elaborated epidermal setae, generates negligible frictional adhesive force and can only ascend smooth inclined surfaces with a pitch of ≤ 40°. We conclude that the ostensibly padless G. humeralis, with feet lacking the musculoskeletal, tendinous, and vascular modifications typical of pad-bearing geckos, nevertheless can employ frictional adhesive contact to assist locomotion. As in Anolis, the release of frictional adhesive contact occurs when the foot is plantar flexed after the heel has lifted from the surface. Our findings indicate that the origin of frictional adhesion was likely gradual but that, ultimately, this led to major shifts in ecology and function

Beirut’s Civil War Hotel District: Preserving the World’s First High-Rise Urban Battlefield

My thesis aims at preserving a historic event in Beirut through the proposal of a historic district. The event in question is the Battle of the Hotels, a 5-month urban battle that took place within and around the historic luxury hotel district in the Minet El Husn neighborhood of Beirut at the beginning of the 15-year Lebanese Civil War (1975-1990). The battle opposed the left-wing pro-Palestinian Lebanese National Movement against the right-wing Christian-nationalist Phalanges Party. The battle is worth commemorating, and therefore preserving, for its instrumental role in shaping the urban rift that divided the city of Beirut during the Lebanese civil war, violently affecting the lives of all Lebanese citizens for a period of 13 years. Lebanese society shares a violent history that could, if considered a common heritage, be part of its postwar nation-building identity and inspire socio-political reform. The Battle of the Hotels’ significance also lies in its status as the first high-rise urban battle in the world. As a global historic event, the battle deserves to be commemorated as a peace-building historic district, protesting urban warfare and civil war as the current most common methods for conducting war. The American practice of mapping Civil War battlefields as part of preserving national military parks was relevant to me for its potential efficacy in representing battles to fellow citizens without the vilification of a particular faction, and the use of similar symbols to qualify military events, movements and positions related to both factions. Mapping is also interesting for its spatial visualization qualities, as it offers the option to compare historic and current urban configurations. In order to determine the boundaries of a potential Battle of the Hotels Historic District, I gathered and listed the chronological events of the battle from several sources and positioned them on a map of Beirut. The urban battlefield map I created contains new kinds of symbols specifically related to urban battlefields. Beyond its symbolic meanings, the battle of the hotels was first and foremost an architectural and geographical phenomenon, fueled by the spatial qualities the buildings in Beirut offered and the military strategies envisioned within and around them. The transformation of urban areas into historic objects requires new experimental preservation methodologies in Lebanon, not only because the country lacks traditional historic districting laws, but also because the current "postmemory" generation, which has been de-schooled in the history of the civil war, does not yet recognize its possible historical significance. They do not know that the Battle of the Hotels is the first high-rise urban battlefield in the world or the event that directly led to the East-West division of Beirut during the civil war. I therefore propose a new method for setting into motion the creation of a historic district by drawing and carving the map of the district directly on the places from which the militias fought and the public spaces in the city that witnessed the events. The balconies of the Holiday Inn, once sandbagged for sniper posts, now become viewing posts for a generation to confront and historically contextualize its "postmemory" condition

Computer generated 3D animated holographic stereograms

This thesis describes the process of creating and displaying a computer generated 3D animated holographic stereogram. The objective of the project was to create a computer generated 3-dimensional model and animate it to perform some action using an animation program. This animated object would then be transferred to holographic film in the form of incremental component views of that object, resulting in a holographic stereogram that displays both parallax as well as animation

A digital open source investigation of how war begins: Ukraine’s Donbas in 2014

This dissertation demonstrates the usefulness of digital open source information (DOSI) for academic research on the causes of war through an in-depth case study of the conflict in eastern Ukraine’s Donets Basin (Donbas). It argues that the current social science literature is in need of theoretical and methodological innovation to operate in the abundant but murky information environment that surrounds the Donbas war and other conflicts of the social media age. The result is a deep divide in the academic literature between scholars who emphasize domestic causes of the Donbas war and those who emphasize Russian involvement. To address this shortcoming, my dissertation develops new theoretical and methodological frameworks. My theoretical framework combines conflict escalation theory with the historical institutionalist concept of critical junctures. Based on this framework, I develop an escalation sequence model of the Donbas conflict which divides the formative phase of the war into six critical junctures. Moreover, my theoretical framework draws attention to intervention and delegation as two distinct modes of external actor involvement in these critical junctures. My methodological framework combines process tracing with the journalistic practice of DOSI analysis to shift the methodological focus towards source criticism and probabilistic reasoning. I argue that this shift towards digital forensic process tracing is essential to make social science methodology fit for the social media age. The six empirical chapters of my dissertation apply digital forensic process tracing to the six critical junctures of the Donbas war’s escalation sequence. For each critical juncture, they assess the available open source evidence of domestic causes and Russian interference. I argue that there is convincing evidence that Russian involvement was the primary cause of four of the six critical junctures. For this reason, my dissertation concludes that the Donbas war is primarily an interstate war between Russia and Ukraine

Adversarial content manipulation for analyzing and improving model robustness

The recent rapid progress in machine learning systems has opened up many real-world applications --- from recommendation engines on web platforms to safety critical systems like autonomous vehicles. A model deployed in the real-world will often encounter inputs far from its training distribution. For example, a self-driving car might come across a black stop sign in the wild. To ensure safe operation, it is vital to quantify the robustness of machine learning models to such out-of-distribution data before releasing them into the real-world. However, the standard paradigm of benchmarking machine learning models with fixed size test sets drawn from the same distribution as the training data is insufficient to identify these corner cases efficiently. In principle, if we could generate all valid variations of an input and measure the model response, we could quantify and guarantee model robustness locally. Yet, doing this with real world data is not scalable. In this thesis, we propose an alternative, using generative models to create synthetic data variations at scale and test robustness of target models to these variations. We explore methods to generate semantic data variations in a controlled fashion across visual and text modalities. We build generative models capable of performing controlled manipulation of data like changing visual context, editing appearance of an object in images or changing writing style of text. Leveraging these generative models we propose tools to study robustness of computer vision systems to input variations and systematically identify failure modes. In the text domain, we deploy these generative models to improve diversity of image captioning systems and perform writing style manipulation to obfuscate private attributes of the user. Our studies quantifying model robustness explore two kinds of input manipulations, model-agnostic and model-targeted. The model-agnostic manipulations leverage human knowledge to choose the kinds of changes without considering the target model being tested. This includes automatically editing images to remove objects not directly relevant to the task and create variations in visual context. Alternatively, in the model-targeted approach the input variations performed are directly adversarially guided by the target model. For example, we adversarially manipulate the appearance of an object in the image to fool an object detector, guided by the gradients of the detector. Using these methods, we measure and improve the robustness of various computer vision systems -- specifically image classification, segmentation, object detection and visual question answering systems -- to semantic input variations.Der schnelle Fortschritt von Methoden des maschinellen Lernens hat viele neue Anwendungen ermöglicht – von Recommender-Systemen bis hin zu sicherheitskritischen Systemen wie autonomen Fahrzeugen. In der realen Welt werden diese Systeme oft mit Eingaben außerhalb der Verteilung der Trainingsdaten konfrontiert. Zum Beispiel könnte ein autonomes Fahrzeug einem schwarzen Stoppschild begegnen. Um sicheren Betrieb zu gewährleisten, ist es entscheidend, die Robustheit dieser Systeme zu quantifizieren, bevor sie in der Praxis eingesetzt werden. Aktuell werden diese Modelle auf festen Eingaben von derselben Verteilung wie die Trainingsdaten evaluiert. Allerdings ist diese Strategie unzureichend, um solche Ausnahmefälle zu identifizieren. Prinzipiell könnte die Robustheit “lokal” bestimmt werden, indem wir alle zulässigen Variationen einer Eingabe generieren und die Ausgabe des Systems überprüfen. Jedoch skaliert dieser Ansatz schlecht zu echten Daten. In dieser Arbeit benutzen wir generative Modelle, um synthetische Variationen von Eingaben zu erstellen und so die Robustheit eines Modells zu überprüfen. Wir erforschen Methoden, die es uns erlauben, kontrolliert semantische Änderungen an Bild- und Textdaten vorzunehmen. Wir lernen generative Modelle, die kontrollierte Manipulation von Daten ermöglichen, zum Beispiel den visuellen Kontext zu ändern, die Erscheinung eines Objekts zu bearbeiten oder den Schreibstil von Text zu ändern. Basierend auf diesen Modellen entwickeln wir neue Methoden, um die Robustheit von Bilderkennungssystemen bezüglich Variationen in den Eingaben zu untersuchen und Fehlverhalten zu identifizieren. Im Gebiet von Textdaten verwenden wir diese Modelle, um die Diversität von sogenannten Automatische Bildbeschriftung-Modellen zu verbessern und Schreibtstil-Manipulation zu erlauben, um private Attribute des Benutzers zu verschleiern. Um die Robustheit von Modellen zu quantifizieren, werden zwei Arten von Eingabemanipulationen untersucht: Modell-agnostische und Modell-spezifische Manipulationen. Modell-agnostische Manipulationen basieren auf menschlichem Wissen, um bestimmte Änderungen auszuwählen, ohne das entsprechende Modell miteinzubeziehen. Dies beinhaltet das Entfernen von für die Aufgabe irrelevanten Objekten aus Bildern oder Variationen des visuellen Kontextes. In dem alternativen Modell-spezifischen Ansatz werden Änderungen vorgenommen, die für das Modell möglichst ungünstig sind. Zum Beispiel ändern wir die Erscheinung eines Objekts um ein Modell der Objekterkennung täuschen. Dies ist durch den Gradienten des Modells möglich. Mithilfe dieser Werkzeuge können wir die Robustheit von Systemen zur Bildklassifizierung oder -segmentierung, Objekterkennung und Visuelle Fragenbeantwortung quantifizieren und verbessern

Automatic Image Captioning with Style

This thesis connects two core topics in machine learning, vision and language. The problem of choice is image caption generation: automatically constructing natural language descriptions of image content. Previous research into image caption generation has focused on generating purely descriptive captions; I focus on generating visually relevant captions with a distinct linguistic style. Captions with style have the potential to ease communication and add a new layer of personalisation. First, I consider naming variations in image captions, and propose a method for predicting context-dependent names that takes into account visual and linguistic information. This method makes use of a large-scale image caption dataset, which I also use to explore naming conventions and report naming conventions for hundreds of animal classes. Next I propose the SentiCap model, which relies on recent advances in artificial neural networks to generate visually relevant image captions with positive or negative sentiment. To balance descriptiveness and sentiment, the SentiCap model dynamically switches between two recurrent neural networks, one tuned for descriptive words and one for sentiment words. As the first published model for generating captions with sentiment, SentiCap has influenced a number of subsequent works. I then investigate the sub-task of modelling styled sentences without images. The specific task chosen is sentence simplification: rewriting news article sentences to make them easier to understand. For this task I design a neural sequence-to-sequence model that can work with limited training data, using novel adaptations for word copying and sharing word embeddings. Finally, I present SemStyle, a system for generating visually relevant image captions in the style of an arbitrary text corpus. A shared term space allows a neural network for vision and content planning to communicate with a network for styled language generation. SemStyle achieves competitive results in human and automatic evaluations of descriptiveness and style. As a whole, this thesis presents two complete systems for styled caption generation that are first of their kind and demonstrate, for the first time, that automatic style transfer for image captions is achievable. Contributions also include novel ideas for object naming and sentence simplification. This thesis opens up inquiries into highly personalised image captions; large scale visually grounded concept naming; and more generally, styled text generation with content control

Pattern Formation and Organization of Epithelial Tissues

Developmental biology is a study of how elaborate patterns, shapes, and functions emerge as an organism grows and develops its body plan. From the physics point of view this is very much a self-organization process. The genetic blueprint contained in the DNA does not explicitly encode shapes and patterns an animal ought to make as it develops from an embryo. Instead, the DNA encodes various proteins which, among other roles, specify how different cells function and interact with each other. Epithelial tissues, from which many organs are sculpted, serve as experimentally- and analytically-tractable systems to study patterning mechanisms in animal development. Despite extensive studies in the past decade, the mechanisms that shape epithelial tissues into functioning organs remain incompletely understood. This thesis summarizes various studies we have done on epithelial organization and patterning, both in abstract theory and in close contact with experiments. A novel mechanism to establish cellular left-right asymmetry based on planar polarity instabilities is discussed. Tissue chirality is often assumed to originate from handedness of biological molecules. Here we propose an alternative where it results from spontaneous symmetry breaking of planar polarity mechanisms. We show that planar cell polarity (PCP), a class of well-studied mechanisms that allows epithelia to spontaneously break rotational symmetry, is also generically capable of spontaneously breaking reflection symmetry. Our results provide a clear interpretation of many mutant phenotypes, especially those that result in incomplete inversion. To bridge theory and experiments, we develop quantitative methods to analyze fluorescence microscopy images. Included in this thesis are algorithms to selectively project intensities from a surface in z-stack images, analysis of cells forming short chain fragments, analysis of thick fluorescent bands using steerable ridge detector, and analysis of cell recoil in laser ablation experiments. These techniques, though developed in the context of zebrafish retina mosaic, are general and can be adapted to other systems. Finally we explore correlated noise in morphogenesis of fly pupa notum. Here we report unexpected correlation of noise in cell movements between left and right halves of developing notum, suggesting that feedback or other mechanisms might be present to counteract stochastic noise and maintain left-right symmetry.PHDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138800/1/hjeremy_1.pd

TB146: The Eccentric Bogs of Maine: A Rare Wetland Type in the United States

The specific objectives of this project were to (1) map the distribution in Maine of eccentric bogs; (2) map the surface physical features and vegetation of a large sample of Maine\u27s eccentric bogs; (3) determine for these bogs the vascular plant, bryophyte, and lichen flora; types and structure of vegetation; peat interstitial water chemistry; relationships between vegetation-flora and water chemistry; subsurface features relating to origins and development; and (4) evaluate the bogs for their unique and exemplary characteristics an d recommend certain of them to the Maine Critica l Areas Program for designation as Critical Areas.https://digitalcommons.library.umaine.edu/aes_techbulletin/1203/thumbnail.jp

Intermedia strategies of narrative resistance: Cartucho, La noche de Tlatelolco, and representations of Ayotzinapa

This dissertation examines the use of visual media as a means of resistance to oppressive political narratives in five Mexican works from the twentieth and twenty-first centuries. Included are two novels: Nellie Campobello’s Cartucho: Relatos de la lucha en el Norte de México (1931), on the Mexican Revolution, and Elena Poniatowska’s La noche de Tlatelolco (1971), about the 1968 Mexican student movement and the October 2 massacre. I also analyze three projects, both visual and discursive, related to the 2014 forced disappearance of 43 students of the Ayotzinapa Teacher’s College in Guerrero, Mexico. The three historical moments the five texts explore are marked by particular trends in visual representation as well as by official narratives that manipulate or misrepresent history for political purposes. I analyze Cartucho and La noche de Tlatelolco with regard to their distinctive structures using theories on photography and cinematography, which help to describe the narrative dimensions of the works. The photography theory is primarily drawn from the work of Walter Benjamin, Susan Sontag, and Roland Barthes, while the cinematographic theory is drawn from Sergei Eisenstein’s work on intellectual montage. I argue that Cartucho functions as a textual “album,” in which each brief text (relato) presents a snapshot of a participant or moment during the Mexican Revolution related to the Villista forces. Campobello’s work responds to the commercial and political uses of photographic images of the time (1916-1920) and was written with the goal of refuting the “black legend,” which characterized the Villistas as criminals. Concerning La noche de Tlatelolco, I analyze the way in which early editions of the book incorporated images of 1968, and argue that the text is best understood as an intellectual montage, which communicates through interactions between the fragmentary and contradictory texts that comprise the book. I analyze the three Ayotzinapa projects, a museum exhibit, an online platform, and the Antimonumento +43, by considering how an audience must interact with each; my goal is to understand the discourse these works generate regarding the Ayotzinapa case, and I explore the problems of historicization and memorialization in relation to ongoing Ayotzinapa activism