Learning Features Across Tasks and Domains

The absence of in-domain labeled data hinders the applicability of powerful deep neural networks. Unsupervised Domain Adaptation (UDA) methods have emerged to exploit such models even when labeled data is not available in the target domain. All these techniques aim to reduce the distribution shift problem that afflicts these models when trained on one dataset and tested in a different one. However, most of the works, do not consider relationships among tasks to further boost performances. In this thesis, we study a recent method called AT/DT (Across Tasks Domain Transfer), that seeks to apply Domain Adaptation together with Task Adaptation, leveraging on the correlation of two popular Vision tasks such as Semantic Segmentation and Monocular Depth Estimation. Inspired by the Domain Adaptation literature, we propose many extensions to the original work and show how these enhance the framework performances. Our contributions are applied at different levels: we first study how different architectures affect the transferability of features across tasks. We further improve performances by deploying Adversarial training. Finally, we explore the possibility of replacing Depth Estimation with popular Self-supervised tasks, demonstrating that two tasks must be semantically connected to be able to transfer features among them

Risk Perception of a Major Earthquake Event at the Cascadia Subduction Plate Boundary

The Cascadia Subduction Zone (CSZ) is a tectonic plate boundary that is located about 64 to 128 kilometers off the west coast from Northern California to Vancouver Island, British Columbia (Cascadia Region Earthquake Workgroup, 2013). Subduction faults are on a cycle of a pressure build up then quick release, materializing as a megathrust earthquake. These faults have the potential to produce earthquakes of the highest magnitude. Paleoseismic studies and Native American oral history have proved that the last CSZ earthquake occurred in 1700 and likely had a magnitude of 9.0 (Finkbeiner, 2015, Nelson et al., 2006). Most probability analyses suggest that there is a 7 to 15% chance of a CSZ earthquake in the next 50 years (Lewis et al., 2007, Buylova et al., 2019). Is the Pacific Northwest prepared for a high magnitude earthquake and tsunami event? The purpose of the study is to document if and how individuals, communities, and town and state governments are preparing for the CSZ megathrust earthquake. A local seismology expert, two members of different emergency preparation and response groups, and a town official were interviewed. The interviews were recorded, transcribed, and compared. The six most commonly mentioned themes between the participants were identified and discussed. These themes include: (1) public awareness; (2) what motivates people to prepare; (3) community building; (4) cannot rely on government support; and (5) failing infrastructure and utilities. All participants believed that there is a high level of awareness of the geohazards involving the CSZ, however, awareness does not equate to taking preparation measures. Participants revealed different levels of risk perceptions and beliefs on how much individual preparation is necessary. Interpreting the interview data in our current societal context suggests that environmental justice and vulnerable populations’ needs are important issues in the context of a CSZ earthquake and tsunami event

Implementazione del modello di Biham-Middleton-Levine sulla Parallella Board

In questa tesi si descrive l’architettura hardware e software della Parallella Board, un supercomputer delle dimensioni di una carta di credito che include una cpu ARM A9 dual core e un coprocessore Epiphany con 16 o 64 core. Grazie al suo basso costo e ad un hardware particolare, si tratta di un ottimo strumento sia per il programmatore esperto sia per lo studente che vuole avvicinarsi alla programmazione parallela. Tuttavia, a causa della limitata documentazione e dei pochi e complessi esempi disponibili, programmare la Parallella potrebbe richiedere un notevole impegno; l’obbiettivo è dunque quello di fornire una panoramica dettagliata della Parallella per aiutare chiunque sia interessato nello sviluppo di algoritmi paralleli a familiarizzare velocemente con questo dispositivo. Per comprendere nel dettaglio come programmare la Parallella Board, vengono forniti una serie di esempi introduttivi prima di arrivare ad un esempio finale più complesso che consiste in un’implementazione del modello di Biham-Middleton-Levine; nonostante sia possibile utilizzare diverse estensioni per il calcolo parallelo come OpenMP e MPI, si è scelto di scrivere i programmi utilizzando il C e le librerie di supporto fornite nativamente dall’eSDK (Epiphany Software development Kit)

One-carbon (bio ?) Geochemistry in Subsurface Waters of the Serpentinizing Coast Range Ophiolite

Serpentinization - the aqueous alteration of ultramafic rocks - typically imparts a highly reducing and alkaline character to the reacting fluids. In turn, these can influence the speciation and potential for metabolism of one-carbon compounds in the system. We examined the aqueous geochemistry and assessed the biological potential of one-carbon compounds in the subsurface of the McLaughlin Natural Reserve (Coast Range Ophiolite, California, USA). Fluids from wells sunk at depths of 25-90 meters have pH values ranging from 9.7 to 11.5 and dissolved inorganic carbon (DIC concentrations) generally below 60 micromolar. Methane is present at concentrations up to 1.3 millimolar (approximately one-atmosphere saturation), and hydrogen concentrations are below 15 nanomolar, suggesting active consumption of H2 and production of CH4. However, methane production from CO2 is thermodynamically unfavorable under these conditions. Additionally, the speciation of DIC predominantly into carbonate at these high pH values creates a problem of carbon availability for any organisms that require CO2 (or bicarbonate) for catabolism or anabolism. A potential alternative is carbon monoxide, which is present in these waters at concentrations 2000-fold higher than equilibrium with atmospheric CO. CO is utilized in a variety of metabolisms, including methanogenesis, and bioavailability is not adversely affected by pH-dependent speciation (as for DIC). Methanogenesis from CO under in situ conditions is thermodynamically favorable and would satisfy biological energy requirements with respect to both Gibbs Energy yield and power

Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries

Although deep neural networks have achieved remarkable results for the task of semantic segmentation, they usually fail to generalize towards new domains, especially when performing synthetic-to-real adaptation. Such domain shift is particularly noticeable along class boundaries, invalidating one of the main goals of semantic segmentation that consists in obtaining sharp segmentation masks.In this work, we specifically address this core problem in the context of Unsupervised Domain Adaptation and present a novel low-level adaptation strategy that allows us to obtain sharp predictions. Moreover, inspired by recent self-training techniques, we introduce an effective data augmentation that alleviates the noise typically present at semantic boundaries when employing pseudo-labels for self-training. Our contributions can be easily integrated into other popular adaptation frameworks, and extensive experiments show that they effectively improve performance along class boundaries

Carbon assimilation strategies in ultrabasic groundwater: clues from the integrated study of a serpentinization-influenced aquifer

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Seyler, L. M., Brazelton, W. J., McLean, C., Putman, L. I., Hyer, A., Kubo, M. D. Y., Hoehler, T., Cardace, D., & Schrenk, M. O. . Carbon assimilation strategies in ultrabasic groundwater: clues from the integrated study of a serpentinization-influenced aquifer. mSystems, 5(2), (2020): e00607-00619, doi: 10.1128/mSystems.00607-19.Serpentinization is a low-temperature metamorphic process by which ultramafic rock chemically reacts with water. Such reactions provide energy and materials that may be harnessed by chemosynthetic microbial communities at hydrothermal springs and in the subsurface. However, the biogeochemistry mediated by microbial populations that inhabit these environments is understudied and complicated by overlapping biotic and abiotic processes. We applied metagenomics, metatranscriptomics, and untargeted metabolomics techniques to environmental samples taken from the Coast Range Ophiolite Microbial Observatory (CROMO), a subsurface observatory consisting of 12 wells drilled into the ultramafic and serpentinite mélange of the Coast Range Ophiolite in California. Using a combination of DNA and RNA sequence data and mass spectrometry data, we found evidence for several carbon fixation and assimilation strategies, including the Calvin-Benson-Bassham cycle, the reverse tricarboxylic acid cycle, the reductive acetyl coenzyme A (acetyl-CoA) pathway, and methylotrophy, in the microbial communities inhabiting the serpentinite-hosted aquifer. Our data also suggest that the microbial inhabitants of CROMO use products of the serpentinization process, including methane and formate, as carbon sources in a hyperalkaline environment where dissolved inorganic carbon is unavailable.We thank McLaughlin Reserve, in particular Paul Aigner and Cathy Koehler, for hosting sampling at CROMO and providing access to the wells, A. Daniel Jones and Anthony Schilmiller for their advice regarding metabolite extraction and mass spectrometry, Elizabeth Kujawinski for her guidance in metabolomics data analysis and interpretation, and Julia McGonigle, Christopher Thornton, and Katrina Twing for assistance with metagenomic and computational analyses

Effect of Local Materials on the Silver Sorption and Strength of Ceramic Water Filters

In this paper, we present a systematic evaluation of the effects of local clays and the manufacturing process on the performance of ceramic water filters (CWFs) impregnated with silver compounds, which are used for point-of-use water treatment in developing countries. Mineral composition, silver sorption/desorption, and strength are the important characteristics that influence effectiveness and durability of CWFs during transport and use. Laboratory tests were conducted on ceramic samples obtained from five CWF factories around the world to determine their mineral composition, silver sorption/desorption, and flexural strength. The results of this study showed that clays that contain traces of crystalline albite or crystalline pyroxene have better sorption of silver species than those that do not. The results showed that the Freundlich model provided the best fit for both ionic silver and silver nanoparticles for all of the ceramic materials that were tested. Thus, this model can be used to optimize the manufacturing process and the application of silver. Silver nanoparticles were desorbed more slowly than ionic silver, so they last longer in the ceramic material. Water that contains a high concentration of divalent ions is not recommended for preparing solutions of silver nanoparticles due to aggregation of the particles, which limits their sorption by the ceramic materials. In this study, the mineralogy of the source materials was found to have the most significant influence on the strength of ceramic filters

RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation

Unsupervised Domain Adaptation (UDA) for point cloud classification is an emerging research problem with relevant practical motivations. Reliance on multi-task learning to align features across domains has been the standard way to tackle it. In this paper, we take a different path and propose RefRec, the first approach to investigate pseudo-labels and self-training in UDA for point clouds. We present two main innovations to make self-training effective on 3D data: i) refinement of noisy pseudo-labels by matching shape descriptors that are learned by the unsupervised task of shape reconstruction on both domains; ii) a novel self-training protocol that learns domain-specific decision boundaries and reduces the negative impact of mislabelled target samples and in-domain intra-class variability. RefRec sets the new state of the art in both standard benchmarks used to test UDA for point cloud classification, showcasing the effectiveness of self-training for this important problem

Feasible Metabolisms in High pH Springs of the Philippines

A field campaign targeting high pH, H2-, and CH4-emitting serpentinite-associated springs in the Zambales and Palawan Ophiolites of the Philippines was conducted in 2012-2013, and enabled description of several springs sourced in altered pillow basalts, gabbros, and peridotites. We combine field observations of pH, temperature, conductivity, dissolved oxygen, and oxidation-reduction potential with analyses of major ions, dissolved inorganic carbon, dissolved organic carbon, and dissolved gas phases in order to model the activities of selected phases important to microbial metabolism, and to rank feasible metabolic reactions based on energy yield. We document changing geochemical inventories in these springs between sampling years, and examine how the environment supports or prevents the function of certain microbial metabolisms. In all, this geochemistry-based assessment of feasible metabolisms indicates methane cycling, hydrogen oxidation, some iron and sulfur metabolisms, and ammonia oxidation are feasible reactions in this continental site of serpentinization