scholarly journals A pilot for implementing environmental DNA (eDNA) based methods into environmental and biomonitoring

2021 ◽  
Vol 4 ◽  
Author(s):  
Tiina Laamanen ◽  
Veera Norros ◽  
Sanna Suikkanen ◽  
Mikko Tolkkinen ◽  
Kristiina Vuorio ◽  
...  

Environmental DNA (eDNA) and other molecular based approaches are revolutionizing the field of biomonitoring. These approaches undergo rapid modifications, and it is crucial to develop the best practices by sharing the newest information and knowledge. In our ongoing project we: assess the state-of-the-art of eDNA methods at Finnish Environment Institute SYKE; identify concrete next steps towards the long-term aim of implementing eDNA methods into environmental and biomonitoring; promote information exchange on eDNA methods and advance future research efforts both within SYKE and with our national and international partners. assess the state-of-the-art of eDNA methods at Finnish Environment Institute SYKE; identify concrete next steps towards the long-term aim of implementing eDNA methods into environmental and biomonitoring; promote information exchange on eDNA methods and advance future research efforts both within SYKE and with our national and international partners. Scientific background Well-functioning and intact natural ecosystems are essential for human well-being, provide a variety of ecosystem services and contain a high diversity of organisms. However, human activities such as eutrophication, pollution, land-use or invasive species, are threatening the state and functioning of ecosystems from local to global scale (e.g. Benateau et al. 2019; Reid et al. 2018; Vörösmarty et al. 2010). New molecular techniques in the field and in the laboratory have enabled sampling and identification of much of terrestrial, marine and freshwater biodiversity. These include environmental DNA (eDNA, e.g. Valentini et al. 2016) and bulk-sample DNA metabarcoding approaches (e.g. Elbrecht et al. 2017) and targeted RNA-based methods (e.g. Mäki and Tiirola 2018). The eDNA technique uses DNA that is released from organisms into their environment, from which a signal of organisms’ presence in the system can be obtained. For example, in aquatic ecosystems, eDNA is typically extracted from sediment or filtered water samples (e.g. Deiner et al. 2016), and this approach is distinguished from bulk DNA metabarcoding, where organisms are directly identified from e.g. complete biological monitoring samples (e.g. Elbrecht et al. 2017). Despite the demonstrated potential of environmental and bulk-sample DNA metabarcoding approaches in recent years, there are still significant bottlenecks to their routine use that need to be addressed (e.g. Pawlowski et al. 2020). Methods and implementati on The project is divided into three work packages: WP1 Gathering existing knowledge, identifying knowledge gaps and proposing best practices, WP2 Roadmap to implementation and WP3 eDNA monitoring pilot. Please see more details in the Fig. 1

2021 ◽  
Vol 54 (7) ◽  
pp. 1-39
Author(s):  
Ankur Lohachab ◽  
Saurabh Garg ◽  
Byeong Kang ◽  
Muhammad Bilal Amin ◽  
Junmin Lee ◽  
...  

Unprecedented attention towards blockchain technology is serving as a game-changer in fostering the development of blockchain-enabled distinctive frameworks. However, fragmentation unleashed by its underlying concepts hinders different stakeholders from effectively utilizing blockchain-supported services, resulting in the obstruction of its wide-scale adoption. To explore synergies among the isolated frameworks requires comprehensively studying inter-blockchain communication approaches. These approaches broadly come under the umbrella of Blockchain Interoperability (BI) notion, as it can facilitate a novel paradigm of an integrated blockchain ecosystem that connects state-of-the-art disparate blockchains. Currently, there is a lack of studies that comprehensively review BI, which works as a stumbling block in its development. Therefore, this article aims to articulate potential of BI by reviewing it from diverse perspectives. Beginning with a glance of blockchain architecture fundamentals, this article discusses its associated platforms, taxonomy, and consensus mechanisms. Subsequently, it argues about BI’s requirement by exemplifying its potential opportunities and application areas. Concerning BI, an architecture seems to be a missing link. Hence, this article introduces a layered architecture for the effective development of protocols and methods for interoperable blockchains. Furthermore, this article proposes an in-depth BI research taxonomy and provides an insight into the state-of-the-art projects. Finally, it determines possible open challenges and future research in the domain.


Electrochem ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 149-184
Author(s):  
Francisco T. T. Cavalcante ◽  
Italo R. R. de A. Falcão ◽  
José E. da S. Souza ◽  
Thales G. Rocha ◽  
Isamayra G. de Sousa ◽  
...  

Among the many biological entities employed in the development of biosensors, enzymes have attracted the most attention. Nanotechnology has been fostering excellent prospects in the development of enzymatic biosensors, since enzyme immobilization onto conductive nanostructures can improve characteristics that are crucial in biosensor transduction, such as surface-to-volume ratio, signal response, selectivity, sensitivity, conductivity, and biocatalytic activity, among others. These and other advantages of nanomaterial-based enzymatic biosensors are discussed in this work via the compilation of several reports on their applications in different industrial segments. To provide detailed insights into the state of the art of this technology, all the relevant concepts around the topic are discussed, including the properties of enzymes, the mechanisms involved in their immobilization, and the application of different enzyme-derived biosensors and nanomaterials. Finally, there is a discussion around the pressing challenges in this technology, which will be useful for guiding the development of future research in the area.


Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 197 ◽  
Author(s):  
Heloise Leão ◽  
Edna Canedo

Governments at all levels have a mandate to provide services, protect society, and make the economy prosper. While this is a long-term goal, citizens are now expecting greater and faster delivery of services from government. This paper presents a systematic literature review of service digitization carried out by the governments of several countries, which was motivated by the lack of primary studies in the literature related to the identification of the processes and methodologies adopted by these governments and private companies to provide their services to the citizen. This work also contributes to the identification of best practices, technologies and tools used for the provision and evaluation of digitized services provided and how governments are evaluating the gains from digitization. These results of this systematic literature review serve as inputs to guide current and future research of the Brazilian Government in the construction of a digital platform for the provision of its services directed to the citizen, seeking to analyze their needs and improving the services currently provided.


2009 ◽  
Vol 47 (2-3) ◽  
Author(s):  
N. N. Ambraseys
Keyword(s):  

2021 ◽  
Vol 11 (23) ◽  
pp. 11344
Author(s):  
Wei Ke ◽  
Ka-Hou Chan

Paragraph-based datasets are hard to analyze by a simple RNN, because a long sequence always contains lengthy problems of long-term dependencies. In this work, we propose a Multilayer Content-Adaptive Recurrent Unit (CARU) network for paragraph information extraction. In addition, we present a type of CNN-based model as an extractor to explore and capture useful features in the hidden state, which represent the content of the entire paragraph. In particular, we introduce the Chebyshev pooling to connect to the end of the CNN-based extractor instead of using the maximum pooling. This can project the features into a probability distribution so as to provide an interpretable evaluation for the final analysis. Experimental results demonstrate the superiority of the proposed approach, being compared to the state-of-the-art models.


2020 ◽  
Vol 34 (06) ◽  
pp. 10352-10360
Author(s):  
Jing Bi ◽  
Vikas Dhiman ◽  
Tianyou Xiao ◽  
Chenliang Xu

Learning from Demonstrations (LfD) via Behavior Cloning (BC) works well on multiple complex tasks. However, a limitation of the typical LfD approach is that it requires expert demonstrations for all scenarios, including those in which the algorithm is already well-trained. The recently proposed Learning from Interventions (LfI) overcomes this limitation by using an expert overseer. The expert overseer only intervenes when it suspects that an unsafe action is about to be taken. Although LfI significantly improves over LfD, the state-of-the-art LfI fails to account for delay caused by the expert's reaction time and only learns short-term behavior. We address these limitations by 1) interpolating the expert's interventions back in time, and 2) by splitting the policy into two hierarchical levels, one that generates sub-goals for the future and another that generates actions to reach those desired sub-goals. This sub-goal prediction forces the algorithm to learn long-term behavior while also being robust to the expert's reaction time. Our experiments show that LfI using sub-goals in a hierarchical policy framework trains faster and achieves better asymptotic performance than typical LfD.


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