Mosaics For Nephrops Detection in Underwater Survey Videos

Harvesting the commercially significant lobster, Nephrops norvegicus, is a multimillion dollar industry in Europe. Stock assessment is essential for maintaining this activity but it is conducted by manually inspecting hours of underwater surveillance videos. To improve this tedious process, we propose an automated procedure. This procedure uses mosaics for detecting the Nephrops, which improves visibility and reduces the tedious video inspection process to the browsing of a single image. In addition to this novel application approach, key contributions are made for handling the difficult lighting conditions in these kinds of videos. Mosaics are build using 1-10 minutes of footage and candidate Nephrops regions are selected using image segmentation based on local image contrast and colour features. A K-Nearest Neighbour classifier is then used to select the respective Nephrops from these candidate regions. Our final decision accuracy at 87.5% recall and precision shows a corresponding 31.5% and 79.4% improvement compared with previous work

A Low-Complexity Mosaicing Algorithm for Stock Assessment of Seabed-Burrowing Species

Peer-reviewed This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. Manuscript received January 27, 2017; revised August 17, 2017 and December 27, 2017; accepted February 16, 2018. Published in: IEEE Journal of Oceanic Engineering ( Early Access ) DOI: 10.1109/JOE.2018.2808973This paper proposes an algorithm for mosaicing videos generated during stock assessment of seabed-burrowing species. In these surveys, video transects of the seabed are captured and the population is estimated by counting the number of burrows in the video. The mosaicing algorithm is designed to process a large amount of video data and summarize the relevant features for the survey in a single image. Hence, the algorithm is designed to be computationally inexpensive while maintaining a high degree of robustness. We adopt a registration algorithm that employs a simple translational motion model and generates a mapping to the mosaic coordinate system using a concatenation of frame-by-frame homographies. A temporal smoothness prior is used in a maximum a posteriori homography estimation algorithm to reduce noise in the motion parameters in images with small amounts of texture detail. A multiband blending scheme renders the mosaic and is optimized for the application requirements. Tests on a large data set show that the algorithm is robust enough to allow the use of mosaics as a medium for burrow counting. This will increase the verifiability of the stock assessments as well as generate a ground truth data set for the learning of an automated burrow counting algorithm.This work was supported by the Science Foundation Ireland under Award SFI-PI 08/IN.1/I2112

Mosaics For Burrow Detection in Underwater Surveillance Video

Harvesting the commercially significant lobster,Nephrops norvegicus, is a multimillion dollar industry in Europe. Stock assessment is essential for maintaining this activity but it is conducted by manually inspecting hours of underwater surveillance videos. To improve this tedious process, we propose the use of mosaics for the automated detection of burrows on the seabed. We present novel approaches for handling the difficult lighting conditions that cause poor video quality in this kind of video material. Mosaics are built using 1-10 minutes of footage and candidate burrows are selected using image segmentation based on local image contrast. A K-Nearest Neighbour classifier is then used to select burrows from these candidate regions. Our final decision accuracy at 93.6% recall and 86.6% precision shows a corresponding 18% and 14.2% improvement compared with previous work.Funder: Science Foundation Ireland PI Programme: SFI-PI 08/IN.1/I211

Epidemiology of Untreated Psychoses in 3 Diverse Settings in the Global South: The International Research Program on Psychotic Disorders in Diverse Settings (INTREPID II).

IMPORTANCE: Less than 10% of research on psychotic disorders has been conducted in settings in the Global South, which refers broadly to the regions of Latin America, Asia, Africa, and Oceania. There is a lack of basic epidemiological data on the distribution of and risks for psychoses that can inform the development of services in many parts of the world. OBJECTIVE: To compare demographic and clinical profiles of cohorts of cases and rates of untreated psychoses (proxy for incidence) across and within 3 economically and socially diverse settings in the Global South. Two hypotheses were tested: (1) demographic and clinical profiles of cases with an untreated psychotic disorder vary across setting and (2) rates of untreated psychotic disorders vary across and within setting by clinical and demographic group. DESIGN, SETTING, AND PARTICIPANTS: The International Research Program on Psychotic Disorders in Diverse Settings (INTREPID II) comprises incidence, case-control, and cohort studies of untreated psychoses in catchment areas in 3 countries in the Global South: Kancheepuram District, India; Ibadan, Nigeria; and northern Trinidad. Participants were individuals with an untreated psychotic disorder. This incidence study was conducted from May 1, 2018, to July 31, 2020. In each setting, comprehensive systems were implemented to identify and assess all individuals with an untreated psychosis during a 2-year period. Data were analyzed from January 1 to May 1, 2022. MAIN OUTCOMES AND MEASURES: The presence of an untreated psychotic disorder, assessed using the Schedules for Clinical Assessment in Neuropsychiatry, which incorporate the Present State Examination. RESULTS: Identified were a total of 1038 cases, including 64 through leakage studies (Kancheepuram: 268; median [IQR] age, 42 [33-50] years; 154 women [57.5%]; 114 men [42.5%]; Ibadan: 196; median [IQR] age, 34 [26-41] years; 93 women [47.4%]; 103 men [52.6%]; Trinidad: 574; median [IQR] age, 30 [23-40] years; 235 women [40.9%]; 339 men [59.1%]). Marked variations were found across and within settings in the sex, age, and clinical profiles of cases (eg, lower percentage of men, older age at onset, longer duration of psychosis, and lower percentage of affective psychosis in Kancheepuram compared with Ibadan and Trinidad) and in rates of untreated psychosis. Age- and sex-standardized rates of untreated psychoses were approximately 3 times higher in Trinidad (59.1/100 000 person-years; 95% CI, 54.2-64.0) compared with Kancheepuram (20.7/100 000 person-years; 95% CI, 18.2-23.2) and Ibadan (14.4/100 000 person-years; 95% CI, 12.3-16.5). In Trinidad, rates were approximately 2 times higher in the African Trinidadian population (85.4/100 000 person-years; 95% CI, 76.0-94.9) compared with the Indian Trinidadian (43.9/100 000 person-years; 95% CI, 35.7-52.2) and mixed populations (50.7/100 000 person-years; 95% CI, 42.0-59.5). CONCLUSIONS AND RELEVANCE: This analysis adds to research that suggests that core aspects of psychosis vary by historic, economic, and social context, with far-reaching implications for understanding and treatment of psychoses globally

Highly Parallel Genome-Wide Expression Analysis of Single Mammalian Cells

We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology

Within-individual phenotypic plasticity in flowers fosters pollination niche shift

Authors thank Raquel Sánchez, Angel Caravante, Isabel Sánchez Almazo, Tatiana López Pérez, Samuel Cantarero, María José Jorquera and Germán Fernández for helping us during several phases of the study and Iván Rodríguez Arós for drawing the insect silhouettes. This research is supported by grants from the Spanish Ministry of Science, Innovation and Universities (CGL2015-71634-P, CGL2015-63827-P, CGL2017-86626-C2-1-P, CGL2017- 86626-C2-2-P, UNGR15-CE-3315, including EU FEDER funds), Junta de Andalucía (P18- FR-3641), Xunta de Galicia (CITACA), BBVA Foundation (PR17_ECO_0021), and a contract grant to C.A. from the former Spanish Ministry of Economy and Competitiveness (RYC-2012-12277). This is a contribution to the Research Unit Modeling Nature, funded by the Consejería de Economía, Conocimiento, Empresas y Universidad, and European Regional Development Fund (ERDF), reference SOMM17/6109/UGR.Phenotypic plasticity, the ability of a genotype of producing different phenotypes when exposed to different environments, may impact ecological interactions. We study here how within-individual plasticity in Moricandia arvensis flowers modifies its pollination niche. During spring, this plant produces large, cross-shaped, UV-reflecting lilac flowers attracting mostly long-tongued large bees. However, unlike most co-occurring species, M. arvensis keeps flowering during the hot, dry summer due to its plasticity in key vegetative traits. Changes in temperature and photoperiod in summer trigger changes in gene expression and the production of small, rounded, UV-absorbing white flowers that attract a different assemblage of generalist pollinators. This shift in pollination niche potentially allows successful reproduction in harsh conditions, facilitating M. arvensis to face anthropogenic perturbations and climate change. Floral phenotypes impact interactions between plants and pollinators. Here, the authors show that Moricandia arvensis displays discrete seasonal plasticity in floral phenotype, with large, lilac flowers attracting long-tongued bees in spring and small, rounded, white flowers attracting generalist pollinators in summer.Spanish Ministry of Science, Innovation and Universities (EU FEDER funds) CGL2015-71634-P CGL2015-63827-P CGL2017-86626-C2-1-P CGL2017-86626-C2-2-P UNGR15-CE-3315Junta de Andalucia P18-FR-3641Xunta de GaliciaBBVA Foundation PR17_ECO_0021Spanish Ministry of Economy and Competitiveness RYC-2012-12277Consejeria de Economia, Conocimiento, Empresas y Universidad SOMM17/6109/UGREuropean Union (EU) SOMM17/6109/UG

Indexing and selection of well-lit details in underwater video using vignetting estimation

Video is an important tool in underwater surveys today, yet its useful field of view is restricted to image details within well lit regions on the seafloor. In this paper we present a novel vignetting-based weighting scheme for selecting these well lit details for use in the creation of a wide area view (mosaic) of the surveyed seafloor. Apart from this detail selection novelity,two other contributions are made. Firstly, because some of these scenes contain very little image texture, we introduce a hybrid homography estimation procedure that uses both feature-based and exhaustive searching techniques. Secondly, to facilitate cross referencing with the video, sections of the mosaic were indexed with the frame number in which the respective image details was selected from. We test our algorithm with real seabed survey video, whose scientific mission was population census of the particular species of lobster, Nephrops norvegicus. High quality mosaics were obtained that captured image details from well lit regions of the scene, which expert marine biologists agreed was a useful analysis tool. This work was supported by the Science Foundation Ireland PI Programme: SFI-PI 08/IN.1/I2112, and was done in collaboration with the Marine Institute Galway.Funder: Science Foundation Ireland PI Programme: SFI-PI 08/IN.1/I211

Improving Underwater Visibility Using Vignetting Correction

Underwater survey videos of the seafloor are usually plagued with heavy vignetting (radial falloff) outside of the light source beam footprint on the seabed. In this paper we propose a novel multi-frame approach for removing this vignetting phenomenon which involves estimating the light source footprint on the seafloor, and the parameters for our proposed vignetting model. This estimation is accomplished in a bayesian framework with an iterative SVD-based optimization. Within the footprint, we leave the image contents as is, whereas outside this region, we perform vignetting correction. Our approach does not require images with different exposure values or recovery of the camera response function, and is entirely based on the attenuation experienced by point correspondences accross multiple frames. We verify our algorithm with both synthetic and real data, and then compare it with an existing technique. Results obtained show significant improvement in the fidelity of the restored images. 1