Towards automating underwater measurement of fish length: a comparison of semi-automatic and manual stereo–video measurements

Underwater stereo–video systems are widely used for counting and measuring fish in aquaculture, fisheries, and conservation management. Length measurements are generated from stereo–video recordings by a software operator using a mouse to locate the head and tail of a fish in synchronized pairs of images. This data can be used to compare spatial and temporal changes in the mean length and biomass or frequency distributions of populations of fishes. Since the early 1990s stereo–video has also been used for measuring the lengths of fish in aquaculture for quota and farm management. However, the costs of the equipment, software, the time, and salary costs involved in post processing imagery manually and the subsequent delays in the availability of length information inhibit the adoption of this technology. We present a semi-automatic method for capturing stereo–video measurements to estimate the lengths of fish. We compare the time taken to make measurements of the same fish measured manually from stereo–video imagery to that measured semi-automatically. Using imagery recorded during transfers of Southern Bluefin Tuna (SBT) from tow cages to grow out cages, we demonstrate that the semi-automatic algorithm developed can obtain fork length measurements with an error of less than 1% of the true length and with at least a sixfold reduction in operator time in comparison to manual measurements. Of the 22 138 SBT recorded we were able to measure 52.6% (11 647) manually and 11.8% (2614) semi-automatically. For seven of the eight cage transfers recorde,d there were no statistical differences in the mean length, weight, or length frequency between manual and semi-automatic measurements. When the data were pooled across the eight cage transfers, there was no statistical difference in mean length or weight between the stereo–video-based manual and semi-automated measurements. Hence, the presented semi-automatic system can be deployed to significantly reduce the cost involved in adoption of stereo–video technology

Reconstruction of three-dimensional porous media using generative adversarial neural networks

To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a novel method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image datasets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that GANs can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.Comment: 21 pages, 20 figure

Comparing the excessive daytime sleepiness of obese and non-obese patients

Background: Obesity, particularly morbid obesity, has various physical and mental complications. Excessive daytime somnolence (EDS) is a sleep disorder that reduces individuals� performance capability and the accuracy of their short-term memory and causes learning problems. This retrospective study aimed to document the presence of EDS in a sample of obese patients in comparison to patients with a normal weight. Objectives: This article compares the excessive daytime sleepiness of obese and non-obese patients in the minimally invasive surgery research center in Tehran, Iran. Patients and Methods: In this case-control study, we compared excessive daytime sleepiness in 55 obese patients who were candidates for laparoscopic surgery, with a body mass index (BMI) of equal to or greater than 30 kg/m2, with 55 controls with a normal BMI (19.5-24.9 kg/m2). The process of selecting the control group in our case-control study is matching in group levels, so that the controls are similar to the case group with regard to certain key characteristics, such as age, sex, and race. The sleep assessment was based on the Epworth sleepiness scale (ESS) questionnaire. Analysis of variance (ANOVA) was used to compare the means of quantitative data, such as the ESS score of groups. Results: Sleepiness was not affected by gender in cases or controls. The sleepiness prevalence was 29 (52.7) in the cases group and 17 (30.9) in the control group (OR = 2.493 (95 CI 1.144-5.435)). The mean ESS scores in cases and controls were 7.82 ± 3.86 and 10.54±6.15, respectively (P = 0.007). Moreover, the prevalence of sleepiness and the mean ESS scores in class III of obesity differed significantly from the controls (16 (57.1) vs. 17 (30.9)) (OR = 2.980 (95 CI 1.162-7.645)) and (11.04±5.93 vs. 7.82±3.86) (P = 0.013), respectively. Conclusions: Our findings suggest a strong relationship between EDS and obesity, particularly morbid obesity. Therefore, physicians must be familiar with EDS as a mixed clinical entity indicating careful assessment and specific treatment planning. © 2016, Iranian Red Crescent Medical Journal

Microplastics in the atmosphere of Ahvaz City, Iran

Airborne particulate matter (PM) with an aerodynamic size cutoff of 10 µm (PM10) has been collected using a high volume air sampler at two locations (urban and residential) in the city of Ahvaz, Iran, for sixteen 24-hour periods over four months (late summer to early winter). Microplastics (MPs) in the PM were isolated after sample digestion and were subsequently characterised by established techniques. All MPs sampled (n = 322) were of a fibrous nature, with polyethylene terephthalate, nylon and polypropylene being the dominant polymers and consistent with textiles and fabrics as the principal source. Despite a distinct seasonality (temperature and wind) over the study period, the abundance, size and colour of the fibres exhibited no clear temporal trend, and no clear differences were observed between the two sites. Concentrations of MPs ranged from none detected to about 0.017/m3 (median = 0.0065/m3) and are at the low end of ranges reported in the recent literature for various urban and remote locations. While some MPs may have a local origin, the weathering of other MPs and their acquisition of extraneous geosolids and salts suggests that long-range transport is also important. Back-trajectory calculations indicate that regional sources are mainly to the north and west of Ahvaz, but a southerly, maritime source is also possible in late autumn. Although concentrations of MPs in the atmosphere are well below those encountered in indoor air, further studies are required to elucidate their potential ecological impacts

LifeCLEF 2016: Multimedia Life Species Identification Challenges

International audienceUsing multimedia identification tools is considered as one of the most promising solutions to help bridge the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g., iSpot, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipment have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching real world requirements. The LifeCLEF lab proposes to evaluate these challenges around 3 tasks related to multimedia information retrieval and fine-grained classification problems in 3 domains. Each task is based on large volumes of real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders to reflect realistic usage scenarios. For each task, we report the methodology, the data sets as well as the results and the main outcom

LifeCLEF 2015: Multimedia Life Species Identification Challenges

International audienceUsing multimedia identification tools is considered as one of the most promising solutions to help bridging the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g. eBird, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipments have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching the real world’s requirements. The LifeCLEF lab proposes to evaluate these challenges around three tasks related to multimedia information retrieval and fine-grained classification problems in three living worlds. Each task is based on large and real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders in order to reflect realistic usage scenarios. This paper presents more particularly the 2014 edition of LifeCLEF, i.e. the pilot one. For each of the three tasks, we report the methodology and the datasets as well as the official results and the main outcomes

Radial evolution of the April 2020 stealth coronal mass ejection between 0.8 and 1 AU - Comparison of Forbush decreases at Solar Orbiter and near the Earth

Aims. We present observations of the first coronal mass ejection (CME) observed at the Solar Orbiter spacecraft on April 19, 2020, and the associated Forbush decrease (FD) measured by its High Energy Telescope (HET). This CME is a multispacecraft event also seen near Earth the next day. Methods. We highlight the capabilities of HET for observing small short-term variations of the galactic cosmic ray count rate using its single detector counters. The analytical ForbMod model is applied to the FD measurements to reproduce the Forbush decrease at both locations. Input parameters for the model are derived from both in situ and remote-sensing observations of the CME. Results. The very slow (~350 km/s) stealth CME caused a FD with an amplitude of 3 % in the low-energy cosmic ray measurements at HET and 2 % in a comparable channel of the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) on the Lunar Reconnaissance Orbiter, as well as a 1 % decrease in neutron monitor measurements. Significant differences are observed in the expansion behavior of the CME at different locations, which may be related to influence of the following high speed solar wind stream. Under certain assumptions, ForbMod is able to reproduce the observed FDs in low-energy cosmic ray measurements from HET as well as CRaTER, but with the same input parameters, the results do not agree with the FD amplitudes at higher energies measured by neutron monitors on Earth. We study these discrepancies and provide possible explanations. Conclusions. This study highlights that the novel measurements of the Solar Orbiter can be coordinated with other spacecraft to improve our understanding of space weather in the inner heliosphere. Multi-spacecraft observations combined with data-based modeling are also essential to understand the propagation and evolution of CMEs as well as their space weather impacts

First year of energetic particle measurements in the inner heliosphere with Solar Orbiter's Energetic Particle Detector

Context. Solar Orbiter strives to unveil how the Sun controls and shapes the heliosphere and fills it with energetic particle radiation. To this end, its Energetic Particle Detector (EPD) has now been in operation, providing excellent data, for just over a year. Aims. EPD measures suprathermal and energetic particles in the energy range from a few keV up to (near-) relativistic energies (few MeV for electrons and about 500 MeV nuc−1 for ions). We present an overview of the initial results from the first year of operations and we provide a first assessment of issues and limitations. In addition, we present areas where EPD excels and provides opportunities for significant scientific progress in understanding how our Sun shapes the heliosphere. Methods. We used the solar particle events observed by Solar Orbiter on 21 July and between 10 and 11 December 2020 to discuss the capabilities, along with updates and open issues related to EPD on Solar Orbiter. We also give some words of caution and caveats related to the use of EPD-derived data. Results. During this first year of operations of the Solar Orbiter mission, EPD has recorded several particle events at distances between 0.5 and 1 au from the Sun. We present dynamic and time-averaged energy spectra for ions that were measured with a combination of all four EPD sensors, namely: the SupraThermal Electron and Proton sensor (STEP), the Electron Proton Telescope (EPT), the Suprathermal Ion Spectrograph (SIS), and the High-Energy Telescope (HET) as well as the associated energy spectra for electrons measured with STEP and EPT. We illustrate the capabilities of the EPD suite using the 10 and 11 December 2020 solar particle event. This event showed an enrichment of heavy ions as well as 3He, for which we also present dynamic spectra measured with SIS. The high anisotropy of electrons at the onset of the event and its temporal evolution is also shown using data from these sensors. We discuss the ongoing in-flight calibration and a few open instrumental issues using data from the 21 July and the 10 and 11 December 2020 events and give guidelines and examples for the usage of the EPD data. We explain how spacecraft operations may affect EPD data and we present a list of such time periods in the appendix. A list of the most significant particle enhancements as observed by EPT during this first year is also provided.Ministerio de Economía y CompetitividadAgencia Estatal de Investigació

The quijote simulations

The Quijote simulations are a set of 44,100 full N-body simulations spanning more than 7000 cosmological models in the hyperplane. At a single redshift, the simulations contain more than 8.5 trillion particles over a combined volume of 44,100 each simulation follows the evolution of 2563, 5123, or 10243 particles in a box of 1 h -1 Gpc length. Billions of dark matter halos and cosmic voids have been identified in the simulations, whose runs required more than 35 million core hours. The Quijote simulations have been designed for two main purposes: (1) to quantify the information content on cosmological observables and (2) to provide enough data to train machine-learning algorithms. In this paper, we describe the simulations and show a few of their applications. We also release the petabyte of data generated, comprising hundreds of thousands of simulation snapshots at multiple redshifts; halo and void catalogs; and millions of summary statistics, such as power spectra, bispectra, correlation functions, marked power spectra, and estimated probability density functions