16,750 research outputs found

    Évaluation de l'impact du changement climatique sur la défoliation de l'épinette noire par la tordeuse des bourgeons de l'épinette

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    Les modèles écologiques actuels prévoient de profonds effets des changements climatiques sur les régimes de perturbations naturelles des forêts. La tordeuse des bourgeons de l'épinette (Choristoneura fumiferana) (TBE) est le principal insecte défoliateur dans l'est de l'Amérique du Nord. Les épidémies de TBE ont un impact majeur sur la structure et la fonction de la forêt boréale canadienne puisque la défoliation entraîne une diminution de la croissance des arbres, une augmentation de la mortalité et une baisse de la productivité forestière. Les épidémies de TBE sont devenues plus sévères au cours du dernier siècle à cause des changements climatiques; cependant, nous savons peu de choses sur la manière dont l'effet intégré du climat et du TBE modifie la croissance des espèces hôtes. Nous évaluons ici comment l’interaction entre le climat et la gravité de l'épidémie affecte la croissance de l'épinette noire (Picea mariana) pendant l'épidémie de TBE qui a eu lieu entre 1968-1988 et 2006-2017. Nous avons compilé des séries dendrochronologiques (2271 arbres), des données de sévérité de l'épidémie (estimée par la défoliation aérienne observée) et des données climatiques pour 164 sites au Québec, Canada. Nous avons utilisé un modèle linéaire à effets mixtes pour déterminer l'impact des paramètres climatiques, de la défoliation cumulative (des cinq années précédentes) et de leur effet couplé sur la croissance en surface terrière. À la gravité maximale de l'épidémie, la croissance en surface terrière de l'épinette noire a été réduite de 14 à 18 % sur les cinq années en raison de l'effet TBE. Cette croissance a été affectée par le climat : des températures minimales estivales précédentes plus élevées et un indice d'humidité climatique estival plus élevé ont réduit la croissance de 11 % et 4 % respectivement. En revanche, l'effet négatif de la défoliation a été atténué de 9% pour une température minimale plus élevée au printemps précédent et de 7% pour une température maximale plus élevée l'été précédent. Cette étude améliore notre compréhension des effets combinés de la TBE et du climat et aide à prévoir les dommages futurs causés par cet insecte dans les peuplements forestiers afin de soutenir la gestion durable des forêts. Nous recommandons également que les projections des écosystèmes dans la forêt boréale incluent plusieurs classes de défoliation de la TBE et plusieurs scénarios climatiques

    Pollution-induced community tolerance in freshwater biofilms – from molecular mechanisms to loss of community functions

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    Exposure to herbicides poses a threat to aquatic biofilms by affecting their community structure, physiology and function. These changes render biofilms to become more tolerant, but on the downside community tolerance has ecologic costs. A concept that addresses induced community tolerance to a pollutant (PICT) was introduced by Blanck and Wängberg (1988). The basic principle of the concept is that microbial communities undergo pollution-induced succession when exposed to a pollutant over a long period of time, which changes communities structurally and functionally and enhancing tolerance to the pollutant exposure. However, the mechanisms of tolerance and the ecologic consequences were hardly studied up to date. This thesis addresses the structural and functional changes in biofilm communities and applies modern molecular methods to unravel molecular tolerance mechanisms. Two different freshwater biofilm communities were cultivated for a period of five weeks, with one of the communities being contaminated with 4 μg L-1 diuron. Subsequently, the communities were characterized for structural and functional differences, especially focusing on their crucial role of photosynthesis. The community structure of the autotrophs was assessed using HPLC-based pigment analysis and their functional alterations were investigated using Imaging-PAM fluorometry to study photosynthesis and community oxygen profiling to determine net primary production. Then, the molecular fingerprints of the communities were measured with meta-transcriptomics (RNA-Seq) and GC-based community metabolomics approaches and analyzed with respect to changes in their molecular functions. The communities were acute exposed to diuron for one hour in a dose-response design, to reveal a potential PICT and uncover related adaptation to diuron exposure. The combination of apical and molecular methods in a dose-response design enabled the linkage of functional effects of diuron exposure and underlying molecular mechanisms based on a sensitivity analysis. Chronic exposure to diuron impaired freshwater biofilms in their biomass accrual. The contaminated communities particularly lost autotrophic biomass, reflected by the decrease in specific chlorophyll a content. This loss was associated with a change in the molecular fingerprint of the communities, which substantiates structural and physiological changes. The decline in autotrophic biomass could be due to a primary loss of sensitive autotrophic organisms caused by the selection of better adapted species in the course of chronic exposure. Related to this hypothesis, an increase in diuron tolerance has been detected in the contaminated communities and molecular mechanisms facilitating tolerance have been found. It was shown that genes of the photosystem, reductive-pentose phosphate cycle and arginine metabolism were differentially expressed among the communities and that an increased amount of potential antioxidant degradation products was found in the contaminated communities. This led to the hypothesis that contaminated communities may have adapted to oxidative stress, making them less sensitive to diuron exposure. Moreover, the photosynthetic light harvesting complex was altered and the photoprotective xanthophyll cycle was increased in the contaminated communities. Despite these adaptation strategies, the loss of autotrophic biomass has been shown to impair primary production. This impairment persisted even under repeated short-term exposure, so that the tolerance mechanisms cannot safeguard primary production as a key function in aquatic systems.:1. The effect of chemicals on organisms and their functions .............................. 1 1.1 Welcome to the anthropocene .......................................................................... 1 1.2 From cellular stress responses to ecosystem resilience ................................... 3 1.2.1 The individual pursuit for homeostasis ....................................................... 3 1.2.2 Stability from diversity ................................................................................. 5 1.3 Community ecotoxicology - a step forward in monitoring the effects of chemical pollution? ................................................................................................................. 6 1.4 Functional ecotoxicological assessment of microbial communities ................... 9 1.5 Molecular tools – the key to a mechanistic understanding of stressor effects from a functional perspective in microbial communities? ...................................... 12 2. Aims and Hypothesis ......................................................................................... 14 2.1 Research question .......................................................................................... 14 2.2 Hypothesis and outline .................................................................................... 15 2.3 Experimental approach & concept .................................................................. 16 2.3.1 Aquatic freshwater biofilms as model community ..................................... 16 2.3.2 Diuron as model herbicide ........................................................................ 17 2.3.3 Experimental design ................................................................................. 18 3. Structural and physiological changes in microbial communities after chronic exposure - PICT and altered functional capacity ................................................. 21 3.1 Introduction ..................................................................................................... 21 3.2 Methods .......................................................................................................... 23 3.2.1 Biofilm cultivation ...................................................................................... 23 3.2.2 Dry weight and autotrophic index ............................................................. 23 3.2.4 Pigment analysis of periphyton ................................................................. 23 3.2.4.1 In-vivo pigment analysis for community characterization ....................... 24 3.2.4.2 In-vivo pigment analysis based on Imaging-PAM fluorometry ............... 24 3.2.4.3 In-vivo pigment fluorescence for tolerance detection ............................. 26 3.2.4.4 Ex-vivo pigment analysis by high-pressure liquid-chromatography ....... 27 3.2.5 Community oxygen metabolism measurements ....................................... 28 3.3 Results and discussion ................................................................................... 29 3.3.1 Comparison of the structural community parameters ............................... 29 3.3.2 Photosynthetic activity and primary production of the communities after selection phase ................................................................................................. 33 3.3.3 Acquisition of photosynthetic tolerance .................................................... 34 3.3.4 Primary production at exposure conditions ............................................... 36 3.3.5 Tolerance detection in primary production ................................................ 37 3.4 Summary and Conclusion ........................................................................... 40 4. Community gene expression analysis by meta-transcriptomics ................... 41 4.1 Introduction to meta-transcriptomics ............................................................... 41 4.2. Methods ......................................................................................................... 43 4.2.1 Sampling and RNA extraction................................................................... 43 4.2.2 RNA sequencing analysis ......................................................................... 44 4.2.3 Data assembly and processing................................................................. 45 4.2.4 Prioritization of contigs and annotation ..................................................... 47 4.2.5 Sensitivity analysis of biological processes .............................................. 48 4.3 Results and discussion ................................................................................... 48 4.3.1 Characterization of the meta-transcriptomic fingerprints .......................... 49 4.3.2 Insights into community stress response mechanisms using trend analysis (DRomic’s) ......................................................................................................... 51 4.3.3 Response pattern in the isoform PS genes .............................................. 63 4.5 Summary and conclusion ................................................................................ 65 5. Community metabolome analysis ..................................................................... 66 5.1 Introduction to community metabolomics ........................................................ 66 5.2 Methods .......................................................................................................... 68 5.2.1 Sampling, metabolite extraction and derivatisation................................... 68 5.2.2 GC-TOF-MS analysis ............................................................................... 69 5.2.3 Data processing and statistical analysis ................................................... 69 5.3 Results and discussion ................................................................................... 70 5.3.1 Characterization of the metabolic fingerprints .......................................... 70 5.3.2 Difference in the metabolic fingerprints .................................................... 71 5.3.3 Differential metabolic responses of the communities to short-term exposure of diuron ............................................................................................................ 73 5.4 Summary and conclusion ................................................................................ 78 6. Synthesis ............................................................................................................. 79 6.1 Approaches and challenges for linking molecular data to functional measurements ...................................................................................................... 79 6.2 Methods .......................................................................................................... 83 6.2.1 Summary on the data ............................................................................... 83 6.2.2 Aggregation of molecular data to index values (TELI and MELI) .............. 83 6.2.3 Functional annotation of contigs and metabolites using KEGG ................ 83 6.3 Results and discussion ................................................................................... 85 6.3.1 Results of aggregation techniques ........................................................... 85 6.3.2 Sensitivity analysis of the different molecular approaches and endpoints 86 6.3.3 Mechanistic view of the molecular stress responses based on KEGG functions ............................................................................................................ 89 6.4 Consolidation of the results – holistic interpretation and discussion ............... 93 6.4.1 Adaptation to chronic diuron exposure - from molecular changes to community effects.............................................................................................. 93 6.4.2 Assessment of the ecological costs of Pollution-induced community tolerance based on primary production ............................................................. 94 6.5 Outlook ............................................................................................................ 9

    Neural Architecture Search: Insights from 1000 Papers

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    In the past decade, advances in deep learning have resulted in breakthroughs in a variety of areas, including computer vision, natural language understanding, speech recognition, and reinforcement learning. Specialized, high-performing neural architectures are crucial to the success of deep learning in these areas. Neural architecture search (NAS), the process of automating the design of neural architectures for a given task, is an inevitable next step in automating machine learning and has already outpaced the best human-designed architectures on many tasks. In the past few years, research in NAS has been progressing rapidly, with over 1000 papers released since 2020 (Deng and Lindauer, 2021). In this survey, we provide an organized and comprehensive guide to neural architecture search. We give a taxonomy of search spaces, algorithms, and speedup techniques, and we discuss resources such as benchmarks, best practices, other surveys, and open-source libraries

    Qluster: An easy-to-implement generic workflow for robust clustering of health data

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    The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, contrary to the so-called conventional biostatistical methods where numerous guidelines exist, the standardization of data science approaches in clinical research remains a little discussed subject. This results in a significant variability in the execution of data science projects, whether in terms of algorithms used, reliability and credibility of the designed approach. Taking the path of parsimonious and judicious choice of both algorithms and implementations at each stage, this article proposes Qluster, a practical workflow for performing clustering tasks. Indeed, this workflow makes a compromise between (1) genericity of applications (e.g. usable on small or big data, on continuous, categorical or mixed variables, on database of high-dimensionality or not), (2) ease of implementation (need for few packages, few algorithms, few parameters, ...), and (3) robustness (e.g. use of proven algorithms and robust packages, evaluation of the stability of clusters, management of noise and multicollinearity). This workflow can be easily automated and/or routinely applied on a wide range of clustering projects. It can be useful both for data scientists with little experience in the field to make data clustering easier and more robust, and for more experienced data scientists who are looking for a straightforward and reliable solution to routinely perform preliminary data mining. A synthesis of the literature on data clustering as well as the scientific rationale supporting the proposed workflow is also provided. Finally, a detailed application of the workflow on a concrete use case is provided, along with a practical discussion for data scientists. An implementation on the Dataiku platform is available upon request to the authors

    Countermeasures for the majority attack in blockchain distributed systems

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    La tecnología Blockchain es considerada como uno de los paradigmas informáticos más importantes posterior al Internet; en función a sus características únicas que la hacen ideal para registrar, verificar y administrar información de diferentes transacciones. A pesar de esto, Blockchain se enfrenta a diferentes problemas de seguridad, siendo el ataque del 51% o ataque mayoritario uno de los más importantes. Este consiste en que uno o más mineros tomen el control de al menos el 51% del Hash extraído o del cómputo en una red; de modo que un minero puede manipular y modificar arbitrariamente la información registrada en esta tecnología. Este trabajo se enfocó en diseñar e implementar estrategias de detección y mitigación de ataques mayoritarios (51% de ataque) en un sistema distribuido Blockchain, a partir de la caracterización del comportamiento de los mineros. Para lograr esto, se analizó y evaluó el Hash Rate / Share de los mineros de Bitcoin y Crypto Ethereum, seguido del diseño e implementación de un protocolo de consenso para controlar el poder de cómputo de los mineros. Posteriormente, se realizó la exploración y evaluación de modelos de Machine Learning para detectar software malicioso de tipo Cryptojacking.DoctoradoDoctor en Ingeniería de Sistemas y Computació

    Lift EVERY Voice and Sing: An Intersectional Qualitative Study Examining the Experiences of Lesbian, Gay, Bisexual, and Queer Faculty and Administrators at Historically Black Colleges and Universities

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    While there is minimal literature that address the experiences of lesbian, gay, bisexual, and trans* identified students at Historically Black Colleges and Universities (HBCUs), the experiences of Black, queer faculty and administrators at HBCUs has not been studied. This intersectional qualitative research study focused on the experiences of lesbian, gay, bisexual, and queer identified faculty and administrators who work at HBCUs. By investigating the intersections of religion, race, gender, and sexuality within a predominantly Black institution, this study aims to enhance diversity, equity, and inclusion efforts at HBCUs by sharing the experiences of the LGBQ faculty and administrators that previously or currently work at an HBCU as a full-time employee. The research questions that guided this study were 1) How have LGBQ faculty and staff negotiated/navigated their careers at HBCUs? and 2) How do LGBQ faculty and staff at HBCUs influence cultural (relating to LGBQ inclusion) change at the organizational level? The main theoretical framework used was intersectionality and it shaped the chosen methodology and methods. The Politics of Respectability was the second theoretical framework used to describe the intra-racial tensions within the Black/African American community. The study included 60-120 minute interviews with 12 participants. Using intersectionality as a guide, the data were coded and utilized for thematic analysis. Then, an ethnodramatic performance engages readers. The goals of this study were to encourage policy changes, promote inclusivity for LGBQ employees at HBCUs, and provide an expansion to the body of literature in the field pertaining to the experiences of LGBQ faculty and administrators in higher education

    Message Journal, Issue 5: COVID-19 SPECIAL ISSUE Capturing visual insights, thoughts and reflections on 2020/21 and beyond...

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    If there is a theme running through the Message Covid-19 special issue, it is one of caring. Of our own and others’ resilience and wellbeing, of friendship and community, of students, practitioners and their futures, of social justice, equality and of doing the right thing. The veins of designing with care run through the edition, wide and deep. It captures, not designers as heroes, but those with humble views, exposing the need to understand a diversity of perspectives when trying to comprehend the complexity that Covid-19 continues to generate. As graphic designers, illustrators and visual communicators, contributors have created, documented, written, visualised, reflected, shared, connected and co-created, designed for good causes and re-defined what it is to be a student, an academic and a designer during the pandemic. This poignant period in time has driven us, through isolation, towards new rules of living, and new ways of working; to see and map the world in a different light. A light that is uncertain, disjointed, and constantly being redefined. This Message issue captures responses from the graphic communication design community in their raw state, to allow contributors to communicate their experiences through both their written and visual voice. Thus, the reader can discern as much from the words as the design and visualisations. Through this issue a substantial number of contributions have focused on personal reflection, isolation, fear, anxiety and wellbeing, as well as reaching out to community, making connections and collaborating. This was not surprising in a world in which connection with others has often been remote, and where ‘normal’ social structures of support and care have been broken down. We also gain insight into those who are using graphic communication design to inspire and capture new ways of teaching and learning, developing themselves as designers, educators, and activists, responding to social justice and to do good; gaining greater insight into society, government actions and conspiracy. Introduction: Victoria Squire - Coping with Covid: Community, connection and collaboration: James Alexander & Carole Evans, Meg Davies, Matthew Frame, Chae Ho Lee, Alma Hoffmann, Holly K. Kaufman-Hill, Joshua Korenblat, Warren Lehrer, Christine Lhowe, Sara Nesteruk, Cat Normoyle & Jessica Teague, Kyuha Shim. - Coping with Covid: Isolation, wellbeing and hope: Sadia Abdisalam, Tom Ayling, Jessica Barness, Megan Culliford, Stephanie Cunningham, Sofija Gvozdeva, Hedzlynn Kamaruzzaman, Merle Karp, Erica V. P. Lewis, Kelly Salchow Macarthur, Steven McCarthy, Shelly Mayers, Elizabeth Shefrin, Angelica Sibrian, David Smart, Ane Thon Knutsen, Isobel Thomas, Darryl Westley. - Coping with Covid: Pedagogy, teaching and learning: Bernard J Canniffe, Subir Dey, Aaron Ganci, Elizabeth Herrmann, John Kilburn, Paul Nini, Emily Osborne, Gianni Sinni & Irene Sgarro, Dave Wood, Helena Gregory, Colin Raeburn & Jackie Malcolm. - Coping with Covid: Social justice, activism and doing good: Class Action Collective, Xinyi Li, Matt Soar, Junie Tang, Lisa Winstanley. - Coping with Covid: Society, control and conspiracy: Diana Bîrhală, Maria Borțoi, Patti Capaldi, Tânia A. Cardoso, Peter Gibbons, Bianca Milea, Rebecca Tegtmeyer, Danne Wo

    Image classification over unknown and anomalous domains

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    A longstanding goal in computer vision research is to develop methods that are simultaneously applicable to a broad range of prediction problems. In contrast to this, models often perform best when they are specialized to some task or data type. This thesis investigates the challenges of learning models that generalize well over multiple unknown or anomalous modes and domains in data, and presents new solutions for learning robustly in this setting. Initial investigations focus on normalization for distributions that contain multiple sources (e.g. images in different styles like cartoons or photos). Experiments demonstrate the extent to which existing modules, batch normalization in particular, struggle with such heterogeneous data, and a new solution is proposed that can better handle data from multiple visual modes, using differing sample statistics for each. While ideas to counter the overspecialization of models have been formulated in sub-disciplines of transfer learning, e.g. multi-domain and multi-task learning, these usually rely on the existence of meta information, such as task or domain labels. Relaxing this assumption gives rise to a new transfer learning setting, called latent domain learning in this thesis, in which training and inference are carried out over data from multiple visual domains, without domain-level annotations. Customized solutions are required for this, as the performance of standard models degrades: a new data augmentation technique that interpolates between latent domains in an unsupervised way is presented, alongside a dedicated module that sparsely accounts for hidden domains in data, without requiring domain labels to do so. In addition, the thesis studies the problem of classifying previously unseen or anomalous modes in data, a fundamental problem in one-class learning, and anomaly detection in particular. While recent ideas have been focused on developing self-supervised solutions for the one-class setting, in this thesis new methods based on transfer learning are formulated. Extensive experimental evidence demonstrates that a transfer-based perspective benefits new problems that have recently been proposed in anomaly detection literature, in particular challenging semantic detection tasks

    Entities and their genera: Slicing up the world the medieval way--and does it matter to formal ontology?

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    Genera, typically hand-in-hand with their branching species, are essential elements of vocabulary-based information constructs, in particular scientific taxonomies. Should they also feature in formal ontologies, the highest of such constructs? I argue in this article that the answer is “Yes” and that the question posed in its title also has a Yes-answer: The way medieval ontologists sliced up the world into genera does matter to formal ontology. More specifically, the way Dietrich of Freiberg, a Latin scholastic, conceived and applied strictly generic criteria to slice up the world into its entities can provide some guidelines to the field of formal ontology with respect to not only its contents, but also its scope. In particular, Dietrich's information criterion plays here a central role
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