K-means clustering of zebrafish embryos images acquired with AOTF-based hyperspectral microscope

Model organism studies are widely implemented in biomedical research fields. Zebrafish is a common and convenient model organism. To provide in vivo investigation of living zebrafish the non-invasive imaging methods are implemented. Hyperspectral imaging utilizing acousto-optic tunable filters is a perspective modality for zebrafish embryos and larvae automated observation. In this paper, the hyperspectral microscope based on the acousto-optical tunable filter is described. Using the hyperspectral image arrays obtained with the described setup, the K-means clustering algorithm is tested. The results obtained for different number of clusters are presented and discussed.

Vision-based monitoring and measurement of bottlenose dolphins' daily habitat use and kinematics

This research presents a framework to enable computer-automated observation and monitoring of bottlenose dolphins (Tursiops truncatus) in a professionally managed environment. Results from this work provide insight into the dolphins' movement patterns, kinematic diversity, and how changes in the environment affect their dynamics. Fixed overhead cameras were used to collect ~100 hours of observations, recorded over multiple days including time both during and outside of formal training sessions. Animal locations were estimated using convolutional neural network (CNN) object detectors and Kalman filter post-processing. The resulting animal tracks were used to quantify habitat use and animal dynamics. Additionally, Kolmogorov-Smirnov analyses of the swimming kinematics were used for high-level behavioral mode classification. The detectors achieved a minimum Average Precision of 0.76. Performing detections and post-processing yielded 1.24x10^7 estimated dolphin locations. Animal kinematic diversity was found to be lowest in the morning and peaked immediately before noon. Regions of the habitat displaying the highest activity levels correlated to locations associated with animal care specialists, conspecifics, or enrichment. The work presented here demonstrates that CNN object detection is not only viable for large-scale marine mammal tracking, it also enables automated analyses of dynamics that provide new insight into animal movement and behavior.

Multi-platform volcanological imaging: Two decades of thermal infrared data from the ASTER and MODIS sensors

<p>For the past 20 years, the ASTER and MODIS instruments on Terra have acquired thermal infrared (TIR) data of the world’s volcanoes. These observations have improved our knowledge of long-term volcanic behavior, eruption monitoring, and post-eruption change. MODIS acquires images twice per day (later doubling this after the launch of Aqua) with 1 km TIR and mid-IR resolution. The volcano data from MODIS were later organized into global automated observation programs such as MODVOLC (USA) and later MIROVA (IT). These systems continually detect and track the amount of emitted energy at each active volcano, resulting in vast databases over time that are critically important for ongoing eruptions. Unlike MODIS, ASTER is scheduled and acquires TIR data at 90 m spatial resolution nominally every 5 – 16 days depending on the latitude. This can be improved to hours with proper scheduling and orbital dependencies using its expedited data system. For the past 15 years, an ASTER program called the Urgent Request Protocol (URP) has combined the rapid detection capability of MODIS with the high resolution expedited observations of ASTER in a sensor-web approach. The URP is operated by the University of Pittsburgh in conjunction with (and the support of) the Universities of Alaska, Hawaii, Turin (IT), Clermont Auvergne (FR), and Bristol (UK) as well as the USGS, the LP DAAC and the ASTER science team. The data are used for: operational response to new eruptions; determining thermal trends months prior to an eruption; inferring the emplacement of new lava lobes; and mapping the constituents of volcanic plumes, to name a few. This ASTER TIR archive of volcanic data is now being mined to provide statistics for future TIR orbital concepts being considered by NASA. As TIR instruments get smaller and more numerous with the use of uncooled detectors, they will become CubeSat compatible and could operate in a multi-platform, sensor-web architecture. This would improve response times to volcanic crises and enable new measurements such as the global inventory of volcanic degassing, thermal precursory trends at every volcano, and active flow temperatures at the minute timescale required for predictive flow and hazard assessment models. The combined spatial, spectral and temporal resolutions of ASTER and MODIS enabled a new multi-platform, multi-scale approach to volcanic remote sensing, a model which could be greatly improved depending on future instrument/mission selections.</p>

Computational observation : Challenges and opportunities of automated observation within algorithmically curated media environments using a browser plug-in

A lot of modern media use is guided by algorithmic curation, a phenomenon that is in desperate need of empirical observation, but for which adequate methodological tools are largely missing. To fill this gap, computational observation offers a novel approach—the unobtrusive and automated collection of information encountered within algorithmically curated media environments by means of a browser plug-in. In contrast to prior methodological approaches, browser plug-ins allow for reliable capture and repetitive analysis of both content and context at the point of the actual user encounter. After discussing the technological, ethical, and practical considerations relevant to this automated solution, we present our open-source browser plug-in as an element in an adequate multi-method design, along with potential links to panel surveys and content analysis. Ultimately, we present a proof-of-concept study in the realm of news exposure on Facebook; we successfully deployed the plug-in to Chrome and Firefox, and we combined the computational observation with a two-wave panel survey. Although this study suffered from severe recruitment difficulties, the results indicate that the methodological setup is reliable and ready to implement for data collection within a variety of studies on media use and media effects.

Computational observation: Challenges and opportunities of automated observation within algorithmically curated media environments using a browser plug-in

A lot of modern media use is guided by algorithmic curation, a phenomenon that is in desperate need of empirical observation, but for which adequate methodological tools are largely missing. To fill this gap, computational observation offers a novel approach—the unobtrusive and automated collection of information encountered within algorithmically curated media environments by means of a browser plug-in. In contrast to prior methodological approaches, browser plug-ins allow for reliable capture and repetitive analysis of both content and context at the point of the actual user encounter. After discussing the technological, ethical, and practical considerations relevant to this automated solution, we present our open-source browser plug-in as an element in an adequate multi-method design, along with potential links to panel surveys and content analysis. Ultimately, we present a proof-of-concept study in the realm of news exposure on Facebook; we successfully deployed the plug-in to Chrome and Firefox, and we combined the computational observation with a two-wave panel survey. Although this study suffered from severe recruitment difficulties, the results indicate that the methodological setup is reliable and ready to implement for data collection within a variety of studies on media use and media effects.

Hydrogeoseismological Research in Kamchatka: 1977–2017

This paper is concerned with the main stages in the setting-up and technical development of a system specializing in physical and chemical parameters of groundwater at a network of wells and springs in the Petropavlovsk Geodynamic Test Area, Kamchatka. The focus is on a description of hydrogeochemical and hydrogeodynamic precursors to Kamchatka earthquakes (Мw = 6.6‒7.8) that occur a few weeks to a few months before a seismic event, manifesting themselves in anomalous changes in chemical composition and groundwater level. The precursors are discussed in application to their use at specialized councils on earthquake prediction. It is shown that the system of automated observation of groundwater parameters at wells as developed at the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences (KB GS RAS) is capable of identifying hydrogeodynamic precursors of water-level in near real time and of providing, in some particular cases, quantitative estimates of pre-seismic and coseismic deformation of water-saturated rocks. This can be useful in geophysical monitoring and intermediate-term prediction of strong earthquakes for the Kamchatka region.

Hydrogeoseismological Research in Kamchatka: 1977–2017

This paper is concerned with the main stages in the setting-up and technical development of a system specializing in physical and chemical parameters of groundwater at a network of wells and springs in the Petropavlovsk Geodynamic Test Area, Kamchatka. The focus is on a description of hydrogeochemical and hydrogeodynamic precursors to Kamchatka earthquakes (Мw = 6.6‒7.8) that occur a few weeks to a few months before a seismic event, manifesting themselves in anomalous changes in chemical composition and groundwater level. The precursors are discussed in application to their use at specialized councils on earthquake prediction. It is shown that the system of automated observation of groundwater parameters at wells as developed at the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences (KB GS RAS) is capable of identifying hydrogeodynamic precursors of water-level in near real time and of providing, in some particular cases, quantitative estimates of pre-seismic and coseismic deformation of water-saturated rocks. This can be useful in geophysical monitoring and intermediate-term prediction of strong earthquakes for the Kamchatka region.