Automatic Hierarchical Classification of Kelps utilizing Deep Residual Feature

Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes for experts to identify organisms found in these images. With this limitation in mind, a large effort has been made globally to introduce automation and machine learning algorithms to accelerate both classification and assessment of marine benthic biota. One major issue lies with organisms that move with swell and currents, like kelps. This paper presents an automatic hierarchical classification method (local binary classification as opposed to the conventional flat classification) to classify kelps in images collected by autonomous underwater vehicles. The proposed kelp classification approach exploits learned feature representations extracted from deep residual networks. We show that these generic features outperform the traditional off-the-shelf CNN features and the conventional hand-crafted features. Experiments also demonstrate that the hierarchical classification method outperforms the traditional parallel multi-class classifications by a significant margin (90.0% vs 57.6% and 77.2% vs 59.0%) on Benthoz15 and Rottnest datasets respectively. Furthermore, we compare different hierarchical classification approaches and experimentally show that the sibling hierarchical training approach outperforms the inclusive hierarchical approach by a significant margin. We also report an application of our proposed method to study the change in kelp cover over time for annually repeated AUV surveys.Comment: MDPI Sensor

Deep transfer learning-based gaze tracking for behavioral activity recognition

Computational Ethology studies focused on human beings is usually referred as Human Activity Recognition (HAR). Specifically, this paper belongs to a line of work on the identification of broad cognitive activities that users carry out with computers. The keystone of this kind of systems is the noninvasive detection of the subject's gaze fixations in selected display areas. Noninvasiveness is ensured by using the conventional laptop cameras without additional illumination or tracking devices. The gaze ethograms, composed as sequences of gaze fixations, are the basis to identify the user activities. To determine the gaze fixation display areas with the highest accuracy, this paper explores the use of a transfer learning approach applied to several well-known deep learning network (DLN) architectures whose input is the eye area extracted from the face image,and output is the identification of the gaze fixation area in the computer screen. Two different datasets are created and used in the validation experiments. We report encouraging results that may allow the general use of the system.This work has been supported by FEDER funds through MINECO project TIN2017-85827-P. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 777720. XinZhe Jin contributed some early computational experiences

A Review on Deep Learning in UAV Remote Sensing

Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, surveys and literature revisions specifically involving DNNs algorithms' applications have been conducted in an attempt to summarize the amount of information produced in its subfields. Recently, Unmanned Aerial Vehicles (UAV) based applications have dominated aerial sensing research. However, a literature revision that combines both "deep learning" and "UAV remote sensing" thematics has not yet been conducted. The motivation for our work was to present a comprehensive review of the fundamentals of Deep Learning (DL) applied in UAV-based imagery. We focused mainly on describing classification and regression techniques used in recent applications with UAV-acquired data. For that, a total of 232 papers published in international scientific journal databases was examined. We gathered the published material and evaluated their characteristics regarding application, sensor, and technique used. We relate how DL presents promising results and has the potential for processing tasks associated with UAV-based image data. Lastly, we project future perspectives, commentating on prominent DL paths to be explored in the UAV remote sensing field. Our revision consists of a friendly-approach to introduce, commentate, and summarize the state-of-the-art in UAV-based image applications with DNNs algorithms in diverse subfields of remote sensing, grouping it in the environmental, urban, and agricultural contexts.Comment: 38 pages, 10 figure

Molecular support for temporal dynamics of induced anti-herbivory defenses in the brown seaweed Fucus Vesiculosus

Grazing by the isopod Idotea baltica induces chemical defenses in the brown seaweed Fucus vesiculosus. A combination of a 33 day induction experiment, feeding choice assays and functional genomic analyses was used to investigate temporal defense patterns and to correlate changes in palatability to changes in gene expression. Despite permanent grazing, seaweed palatability varied over time. Controls were significantly more consumed than grazed pieces only after 18 and 27 days of grazing. Relative to controls, 562/402 genes were up-/down-regulated in seaweed pieces that were grazed for 18 days, i.e. when defense induction was detected. Reprogramming of the regulative expression orchestra (translation, transcription), up-regulation of genes involved in lipid and carbohydrate metabolism, intracellular trafficking, defense and stress response, as well as downregulation of photosynthesis was found in grazed seaweed. These findings indicate short-term temporal variation in defenses and that modified gene expression patterns arise at the same time when grazed seaweed pieces show reduced palatability. Several genes with putative defensive functions and cellular processes potentially involved in defence, such as reallocation of resources from primary to secondary metabolism, were reveale

Successful invaders are better defended: The example of Gracilaria vermiculophylla

To evaluate the importance of anti-herbivore resistance for algal invasion success we compared resistance traits among specimens of the red macroalga Gracilaria vermiculophylla from six native populations in Korea and China and eight invasive populations in Europe and Mexico that were maintained under identical conditions in the laboratory. Herbivorous snails both from the native range (Littorina brevicula) and from the invaded range (Littorina littorea) consumed significantly less of seaweed specimens originating from non-native populations. Metabolome profiling revealed that this preference was correlated with an increased woundactivated production of deterring prostaglandins and hydroxyeicosatetraenoic acids. Thus, invasive populations of G. vermiculophylla are more strongly defended against challenge by herbivores and other biological enemies that cause local tissue or cell disruption and activate oxylipin production. Anthropogenic distribution of genotypes adapted to resist elevated feeding pressure probably contributed to the invasion success of this species

Current marine pressures and mechanisms driving changes in marine habitats

Human activities and the resultant pressures they place on the marine environment have been widely demonstrated to contribute to habitat degradation, therefore, their identification and quantification is an essential step towards any meaningful restoration effort. The overall scope of MERCES Deliverable 1.2 is to review current knowledge regarding the major marine pressures placed upon marine ecosystems in EU waters and the mechanisms by which they impact habitats in order to determine potential restoration pathways. An understanding of their geographical distribution is critical for any local assessment of degradation, as well as for planning conservation and restoration actions. This information would ideally be in the form of maps, which: (a) compile single or multiple activities and pressures over broad scales, integrating and visualizing available data and allowing direct identification of aggregations as well as gaps and (b) may be overlaid with habitat maps (or any other map layer containing additional information), thus combining different data levels and producing new information to be used for example when implementing EU policies. The deliverable also documents typical example habitat case studies, the prominent impacts and consequences of activities and pressures towards the identification of possible restoration or mitigation actions. Finally the deliverable discusses pressures, assessments, marine spatial planning and blue growth potential. Activities and pressures are used in a strict sense, where marine activities are undertaken to satisfy the needs of societal drivers (e.g. aquaculture or tourism) and pressures are considered to be the mechanism through which an activity has an actual or potential effect on any part of the ecosystem (e.g. for demersal trawling activity, one pressure would be abrasion of the seabed). Habitats are addressed using a nested approach from large-scale geological features (e.g. shallow soft bottoms) to species-characterised habitats (e.g. Posidonia meadows) because of the way they are referred to in current policy documents which lack standard and precise definitions

Dense 3D Reconstruction in Dynamic Environments

3D reconstruction/dense mapping can be used in many applications such as medical imaging, virtual reality, navigations, etc. In this dissertation, we discussed the different state-of-the-art approaches for 3D reconstruction using visual sensors. Current dense space reconstruction representation can be point cloud, octomap, voxel, surfel, etc. The system generally requires the scan of the environment along with the tracking estimation of the moving sensors. This dissertation provides solutions to the dense 3D reconstruction with visual/visual-inertial sensors in a dynamic environment and tests it both on the CPU and GPU. We decouple the sensor tracking and dense reconstruction. Additionally, we develop a learning-based segmentation technique to detect possible dynamic objects and use the static objects for robust sensor tracking. Then we apply the tracking result to the reconstruction system. We modulize our system so each part (tracking, segmentation, reconstruction) can be replaced in the future by a more advanced tracking/mapping system for better performance. The source code is shared for the benefit of the community1 .</p

Science-based restoration monitoring of coastal habitats, Volume Two: Tools for monitoring coastal habitats

Healthy coastal habitats are not only important ecologically; they also support healthy coastal communities and improve the quality of people’s lives. Despite their many benefits and values, coastal habitats have been systematically modified, degraded, and destroyed throughout the United States and its protectorates beginning with European colonization in the 1600’s (Dahl 1990). As a result, many coastal habitats around the United States are in desperate need of restoration. The monitoring of restoration projects, the focus of this document, is necessary to ensure that restoration efforts are successful, to further the science, and to increase the efficiency of future restoration efforts

Comparación de transcriptoma global de Macrocystis pyrifera (Laminariales) en la zona intermareal y submareal, San Juan de Marcona. Ica. Perú

Universidad Nacional Agraria La Molina. Escuela de Posgrado. Doctorado en Ciencias e Ingeniería BiológicasLa transcriptómica de macroalgas pardas para el estudio comparativo de los genes involucrados en su regulación bajo condiciones naturales de inmersión y emersión por efecto de las mareas, ha sido escasamente investigada. Debido a la importancia económica de Macrocystis pyrifera se caracterizó su transcriptoma global, mediante tecnología RNA seq (Illumina NextSeq 500), e identificó los genes que se expresan durante el estrés abiótico en condiciones intermareal y submareal para el análisis del mapa transcriptómico y las respuestas adaptativas frente a cambios tan variables de su entorno natural. Al mismo tiempo, para relacionar las variables ambientales, se realizó el análisis químico de las muestras de agua de mar colectadas en el área de estudio a 0 m (T2A) y 10 m de profundidad (T2B) o condición control. Se realizó análisis químicos proximales, como el rendimiento de la biomasa y gel de alginato de sodio extraído de plantas enteras de Macrocystis pyrifera, colectadas en San Juan de Marcona, centro de Perú; así como también se realizó pruebas de viscosidad para ambas profundidades. Además se realizaron análisis en Microcopia Electrónica de Barrido MEB en las muestras de las frondas colectadas para los estudios transcriptómicos y microanálisis de dispersión de energía EDX. El análisis de RNA-seq produjo 101,468 unigenes no redundantes con un promedio de 827pb. Se identificaron 30,559 transcriptos funcionales con regiones codificantes (30.1%). Los transcriptos fueron anotados usando la base de datos de NCBI y el programa BLAST 2.2.31, mediante la comparación con las secuencias de proteínas conocidas del alga parda Ectocarpus siliculosus con un E value <10-5 se obtuvo 96,997 unigenes. Se identificaron 34 unigenes para la síntesis de polisacáridos de pared. El análisis de ontología de genes identificó 9,331 genes y 8,429 unigenes involucrados en 50 vías metabólicas conocidas. Basado en los valores obtenidos de la lectura por kilobase por millón (RPKM), se determinaron 9,519 (9.4%) unigenes expresados diferencialmente entre los tratamientos de 0 metros y 10 metros de profundidad; estos incluían 4,556 unigenes inducidos y 4,963 unigenes reprimidos, sugiriendo que existe expresión diferencial de genes asociados a condiciones de desecación. Al realizar la caracterización del perfil transcriptómico de M. pyrifera la respuesta, durante la desecación, consistió en la activación de las proteínas de tolerancia al estrés térmico; por ejemplo Heat shock protein (Hsp 70) y la represión de las vías de síntesis de acuaporinas. Al mismo tiempo, indujo una respuesta diferencial en los procesos de biosíntesis de polisacáridos de pared como el alginato; activó los sistemas de desintoxicación ROS como el Vanadio dependiente bromoperoxidasa y procesos metabólicos primarios como la producción de Piruvato fotosintético. Finalmente, observamos la presencia de importantes vías como L-ascorbato (Smirnoff-Wheeler pathway), síntesis de Aprataxina, fitohormonas y la represión de genes implicados en la asimilación de nitrógeno. Los análisis de la calidad de agua de mar coincidieron con los resultados obtenidos a nivel molecular y permitieron comparar información importante para comprender mejor la respuesta de M. pyrifera frente a condiciones de estrés. Los análisis químicos proximales, reportó mayor rendimiento del gel de alginato de sodio en el tratamiento T2B, esto concuerda con el perfil transcripcional de M. pyrifera en la condición de 10 metros de profundidad (T2B) en donde se halla una sobre expresión de los genes para la síntesis de alginatos. Al comparar la viscosidad de una muestra comercial de alginato de sodio marca Sigma-AldrichR con el tratamiento T2B, los resultados del alginato de sodio del Perú tienen una calidad equivalente al 50% en relación al alginato comercial, a una concentración del 70%. En los análisis de Microscopia Electrónica de Barrido (MEB) de las muestras colectadas a 10 metros (T2B) se observó la presencia de polisacáridos en las paredes celulares, a manera de estructuras esponjosas. Los análisis de EDX, indican mayor porcentaje en la composición atómica y peso de elementos como carbono (C) en la pared celular, en relación al parénquima, en la condición T2B. El mapa transcriptómico de novo de M. pyrifera evidenció una amplia respuesta adaptativa frente a cambios tan variables a su entorno natural. Consecuentemente, M. pyrifera, presentó una gran capacidad de tolerancia a los efectos del estrés abiótico. La presencia de polisacáridos de pared, como el alginato de sodio, presentó un rol importante en la regulación iónica para la adaptación de Macrocystis al estrés por efecto de la desecación y en la respuesta al estrés en generalThe transcriptomics of brown macroalgae for the comparative study of the genes involved in their regulation under natural conditions of immersion and emersion by the effect of the tides has been scarcely investigated. Due to the economic importance of Macrocystis pyrifera, its global transcriptome was characterized, using RNA seq technology (Illumina NextSeq 500), and identified the genes that are expressed during abiotic stress in intertidal and subtidal conditions for transcriptomic map analysis and adaptive responses in the face of such variable changes in its natural environment. At the same time, to relate the environmental variables, the chemical analysis of the seawater samples collected in the study area was carried out at 0 m (T2A) and 10 m deep (T2B) or control condition. Proximal chemical analyzes were carried out, such as biomass yield and sodium alginate gel extracted from whole plants of Macrocystis pyrifera, collected in San Juan de Marcona, central Peru; as well as viscosity tests were carried out for both depths. In addition, scanning electron microbial MEB analyzes were performed on the samples of the fronds collected for transcriptomic studies and EDX energy dispersion microanalysis. The analysis of RNA-seq produced 101,468 non-redundant unigenes with an average of 827 bp. 30,559 functional transcripts with coding regions (30.1%) were identified. The transcripts were annotated using the NCBI database and the BLAST program 2.2.31, by comparing with the known protein sequences of the brown algae Ectocarpus siliculosus with an E value <10-5, 96,997 unigenes were obtained. We identified 34 unigenes for the synthesis of wall polysaccharides. The gene ontology analysis identified 9,331 genes and 8,429 unigenes involved in 50 known metabolic pathways. Based on the values obtained from the reading per kilobase per million (RPKM), 9,519 (9.4%) unigenes differentially expressed between the treatments of 0 meters and 10 meters deep were determined; these included 4,556 induced unigenes and 4,963 repressed unigenes, suggesting that there is differential expression of genes associated with dry conditions. When carrying out the characterization of the transcriptomic profile of M. pyrifera, the response, during the desiccation, consisted in the activation of the thermal stress tolerance proteins; for example Heat shock protein (Hsp 90) and repression of aquaporin synthesis pathways. At the same time, it induced a differential response in the biosynthesis processes of wall polysaccharides such as alginate; Actactivized ROS detoxification systems such as the Vanadium-dependent bromoperoxidase and primary metabolic processes such as the production of photosynthetic pyruvate. Finally, we observed the presence of important pathways such as L-ascorbate (Smirnoff-Wheeler pathway), synthesis of Aprataxin, phytohormones and the repression of genes involved in the assimilation of nitrogen. Seawater quality analyzes coincided with the results obtained at the molecular level and allowed comparing important information to better understand the response of M. pyrifera to stress conditions. The proximal chemical analyzes reported higher performance of the sodium alginate gel in the T2B treatment, this agrees with the transcriptional profile of M. pyrifera in the condition of 10 meters of depth (T2B) where there is an over expression of the genes for the synthesis of alginates. When comparing the viscosity of a commercial sample of Sigma-Aldrich® brand sodium alginate with the T2B treatment, the results of the Peruvian alginate have a quality equivalent to 50% in relation to the commercial alginate, at a concentration of 70%. In the Scanning Electron Microscopy (SEM) analyzes of the samples collected at 10 meters (T2B), the presence of polysaccharides was observed in the cell walls, in the form of spongy structures. The EDX analyzes indicate a higher percentage of the atomic composition and weight of elements such as carbon (C) in the cell wall, in relation to the parenchyma, in the T2B condition. The de novo transcriptomic map of M. pyrifera showed a wide adaptive response to changes so variable in its natural environment. Consequently, M. pyrifera presented a great capacity for tolerance to the effects of abiotic stress. The presence of wall polysaccharides, such as sodium alginate, presented an important role in the ionic regulation for the adaptation of Macrocystis to stress due to the effect of drying and in the response to stress in generalTesi