19 research outputs found
Interpretable Decision Trees Through MaxSAT
We present an approach to improve the accuracy-interpretability trade-off of
Machine Learning (ML) Decision Trees (DTs). In particular, we apply Maximum
Satisfiability technology to compute Minimum Pure DTs (MPDTs). We improve the
runtime of previous approaches and, show that these MPDTs can outperform the
accuracy of DTs generated with the ML framework sklearn
ETN Valued Species and Sites Report
Provide operations and maintenance support to scientific teams initiating studies of valued species, such as Bluefin tuna, European eel, sea bass, sea trout. To achieve this deliverable a workshop will be hold focussing on launching and networking activities
Positioning aquatic animals with acoustic transmitters
Geolocating aquatic animals with acoustic tags has been ongoing for decades, relying on the detection of acoustic signals at multiple receivers with known positions to calculate a 2D or 3D position, and ultimately recreate the path of an aquatic animal from detections at fixed stations.This method of underwater geolocation is evolving with new software and hardware options available to help investigators design studies and calculate positions using solvers based predominantly on time-difference-of-arrival and time-of-arrival.We provide an overview of the considerations necessary to implement positioning in aquatic acoustic telemetry studies, including how to design arrays of receivers, test performance, synchronize receiver clocks and calculate positions from the detection data. We additionally present some common positioning algorithms, including both the free open-source solvers and the 'black-box' methods provided by some manufacturers for calculating positions.This paper is the first to provide a comprehensive overview of methods and considerations for designing and implementing better positioning studies that will support users, and encourage further knowledge advances in aquatic systems
Home range and residency of Scorpaena porcus and Scorpaena scrofa in artificial reefs revealed by fine-scale acoustic tracking
WOS: 000451934800003Artificial reefs (ARs) are defined as any structures that are placed on the seafloor to protect sensitive ecosystems, enhance biodiversity, and support small-scale fisheries or diving tourism. With the recent development of fine-scale acoustic tracking, ecologists and fishery managers have gained a powerful tool to explore how exploited species behave in newly created artificial habitats. Here, we report for the first time the space used by the black scorpionfish (Scorpaena porcus) and red scorpionfish (Scorpaena scrofa), two highly important exploited species in the Mediterranean Sea that are often managed with ARs. The Vemco VR2W positioning system (VPS) was used to examine the fine-scale movement patterns (home range) and residency time of these species. S. porcus (182-271 mm total length; n = 14) and S. scrofa (252-445 mm total length; n = 7) were tracked for up to 91 d in ARs located in Edremit Bay, northern Aegean Sea, Turkey. The results revealed high site fidelity during the tracking period and high variability (among individuals) in their home range areas, which ranged from 933 m(2) to 28,674 m(2) (Kernel Utilization Distribution 95%) for S. porcus and from 1895 m(2) to 17,487 m(2) for S. scrofa, with a mean and s.d. of 9591 +/- 8998 m(2) and 8104 +/- 6113 m(2), respectively. The variability in the home range areas was explained neither by the fish length nor diel phase (day vs. night), although residency indexes suggested stronger site fidelity in large S. scrofa. While the lack of size-dependent home range behavior could be explained by the limited size of the range (imposed by the telemetry system), the lack of diel differences in their home range sizes could be explained by the ambush predatory behavior of both species. Our findings suggested that ARs may facilitate the profitability of fisheries in both species by retaining adults and enhancing recruitment of newly settled fish, as suggested by the movement patterns and habitat utilization indexes considered in this study.Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [TOVAG-1120383]; JdC postdoc grant - Spanish Ministry of Economy, Industry, and Competitiveness [IJCI-2016-27681]We would like to thank Vemco, Ltd. for providing the technical support and software to render the positions from the VPS system. This work was funded by Scientific and Technological Research Council of Turkey (TUBITAK) (TOVAG-1120383). JA was supported by a JdC postdoc grant funded by the Spanish Ministry of Economy, Industry, and Competitiveness (ref. IJCI-2016-27681). We thank Ali Ulas, Ozan Duzbastilar, our students and also fishermen in Altmoluk for their help during the sea trials
Toward a decade of ocean science for sustainable development through acoustic animal tracking
The ocean is a key component of the Earth's dynamics, providing a great variety of ecosystem services to humans. Yet, human activities are globally changing its structure and major components, including marine biodiversity. In this context, the United Nations has proclaimed a Decade of Ocean Science for Sustainable Development to tackle the scientific challenges necessary for a sustainable use of the ocean by means of the Sustainable Development Goal 14 (SDG14). Here, we review how Acoustic animal Tracking, a widely distributed methodology of tracking marine biodiversity with electronic devices, can provide a roadmap for implementing the major Actions to achieve the SDG14. We show that acoustic tracking can be used to reduce and monitor the effects of marine pollution including noise, light, and plastic pollution. Acoustic tracking can be effectively used to monitor the responses of marine biodiversity to human-made infrastructures and habitat restoration, as well as to determine the effects of hypoxia, ocean warming, and acidification. Acoustic tracking has been historically used to inform fisheries management, the design of marine protected areas, and the detection of essential habitats, rendering this technique particularly attractive to achieve the sustainable fishing and spatial protection target goals of the SDG14. Finally, acoustic tracking can contribute to end illegal, unreported, and unregulated fishing by providing tools to monitor marine biodiversity against poachers and promote the development of Small Islands Developing States and developing countries. To fully benefit from acoustic tracking supporting the SDG14 Targets, trans-boundary collaborative efforts through tracking networks are required to promote ocean information sharing and ocean literacy. We therefore propose acoustic tracking and tracking networks as relevant contributors to tackle the scientific challenges that are necessary for a sustainable use of the ocean promoted by the United Nations.Agencia Estatal Investigacion, Espana [PID2019-104940GA-I00]; Consejo Superior de Investigaciones Cientificas [PIE202030E002]; Fundacao para a Ciencia e a Tecnologia [DL57/2016/CP1361/ CT0036, BECORV PTDC/BIABMA/30278, UID/Multi/04326/2020]; European Regional Development Fund: Interreg, MarGen II Project [175806]; H2020 Marie Sklodowska-Curie Actions [793627, 891404]; Juan de la Cierva, Ministerio Ciencia e Innovacion, Espana [IJC2019-038852-I]; Norwegian Research Council; European Cooperation in Science and Technology [CA18102]Agencia Estatal Investigacion, Espana, Grant/ Award Number: PID2019-104940GA-I00; Consejo Superior de Investigaciones Cientificas, Grant/Award Number: PIE202030E002; Fundacao para a Ciencia e a Tecnologia, Grant/Award Number: DL57/2016/CP1361/ CT0036, BECORV PTDC/BIABMA/30278 and UID/Multi/04326/2020; European Regional Development Fund: Interreg, MarGen II Project, Grant/Award Number: 175806; H2020 Marie Sklodowska-Curie Actions, Grant/Award Number: 793627 and 891404; Juan de la Cierva, Ministerio Ciencia e Innovacion, Espana, Grant/ Award Number: IJC2019-038852-I; Norwegian Research Council, Grant/Award Number: LOST; European Cooperation in Science and Technology, Grant/Award Number: CA18102 COS
Reflectance Confocal Microscopy and Electrical Impedance Spectroscopy in the Early Detection of Melanoma in Changing Lesions during Long-term Follow-up of Very High-risk Patients
Electrical impedance spectroscopy has clinical relevance in diagnosing malignancy in melanocytic lesions. Sixty-eight lesions with changes during digital follow-up of patients at very high risk of developing melanoma were prospectively included in this study from February to December 2016. Electrical impedance spectroscopy and reflectance confocal microscopy were performed to evaluate their performance in this subset of difficult lesions. Forty-six lesions were considered suspicious on reflectance confocal microscopy and were excised, of these, 19 were diagnosed as melanoma. Fifteen melanomas were detected by electrical impedance spectroscopy, while 4 received a score lower than 4, which suggested no malignancy. The addition of reflectance confocal microscopy improves accuracy while maintaining the same sensitivity. In the case of electrical impedance spectroscopy scores <4, lesions exhibiting changes in follow-up may need short-term monitoring or excision if dermoscopy shows criteria for melanoma. Results of electrical impedance spectroscopy in this subset of very early lesions should be carefully considered due to the risk of false negatives
Digitally stained confocal microscopy through deep learning
Specialists have used confocal microscopy in the ex-vivo modality to identify Basal Cell Carcinoma tumors with an overall sensitivity of 96.6% and specificity of 89.2% (Chung et al., 2004). However, this technology hasnât established yet in the standard clinical practice because most pathologists lack the knowledge to interpret its output. In this paper we propose a combination of deep learning and computer vision techniques to digitally stain confocal microscopy images into H&E-like slides, enabling pathologists to interpret these images without specific training. We use a fully convolutional neural network with a multiplicative residual connection to denoise the confocal microscopy images, and then stain them using a Cycle Consistency Generative Adversarial NetworkPeer Reviewe
Digitally stained confocal microscopy through deep learning
Specialists have used confocal microscopy in the ex-vivo modality to identify Basal Cell Carcinoma tumors with an overall sensitivity of 96.6% and specificity of 89.2% (Chung et al., 2004). However, this technology hasnât established yet in the standard clinical practice because most pathologists lack the knowledge to interpret its output. In this paper we propose a combination of deep learning and computer vision techniques to digitally stain confocal microscopy images into H&E-like slides, enabling pathologists to interpret these images without specific training. We use a fully convolutional neural network with a multiplicative residual connection to denoise the confocal microscopy images, and then stain them using a Cycle Consistency Generative Adversarial NetworkPeer Reviewe
Morphological evaluation of melanocytic lesions with three-dimensional line-field confocal optical coherence tomography: correlation with histopathology and reflectance confocal microscopy. A pilot study
Background. Line-field confocal optical coherence tomography (LC-OCT) is a new in vivo emerging technique that provides cellular resolution, allows deep imaging (400 mu m) and produces real-time images in both the horizontal and vertical plane and in three dimensions. No previous description of different subtypes of melanocytic lesions and their correlation with histopathology and reflectance confocal microscopy has been reported.Aim. To describe the features of melanocytic lesions by LC-OCT and their correlation with histopathology and reflectance confocal microscopy (RCM) findings.Methods. Selected melanocytic benign lesions and melanomas were imaged in vivo with RCM and LC-OCT at the Fundacion Hospital Clinic (Barcelona, Spain). A minimum area of 4 x 4 mm (block image) at four depths (stratum granulosum, suprabasal, layer dermoepidermal junction and upper dermis) were acquired with RCM and a minimum of three cubes with LC-OCT. Horizontal, vertical sections and three-dimensional (3D) cubes of LC-OCT were matched with RCM (Vivablock two-dimensional composite mosaic) and histopathology, with similar to 5 mu m lateral resolution accuracy (the same cell nuclei were measured in X, Y and Z) and evaluated by three observers experienced in using RCM and histopathology.Results. In total, 12 melanocytic tumours (2 in situ melanomas, 2 invasive melanomas, 4 atypical naevi, 2 intradermal naevi, 1 compound naevus and 1 junctional naevus) were included. High correlation with 5 mu m accuracy between RCM and LC-OCT was observed for each tumour. The 3D images of melanocytic lesions were obtained with cellular resolution and correlated with both RCM and histopathology, allowing an understanding of the architecture and precise correlation at the cellular level with RCM. Similarities between LC-OCT and RCM for the described diagnostic features and architecture (nests of melanocytic cells, ringed and meshwork pattern, and cellular details of tumour cells as dendritic and pagetoid cells) were confirmed. The main advantage of diagnosis by RCM fixed probe was the ability to produce larger scans of the lesion using mosaicing compared with an LC-OCT handheld probe.Conclusion. LC-OCT allows the architectural and cellular description of different types of melanocytic lesions. LC-OCT showed high correlation with histopathology (vertical sections) and RCM (horizontal sections) in melanocytic lesions. Diagnostic criteria for RCM were similar to those for LC-OCT