scholarly journals Documentary data and the study of the past droughts: an overview of the state of the art worldwide

2018 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
The State ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including: general annals, chronicles, and memoirs, diaries kept by missionaries, travellers and those specifically interested in the weather, the records kept by administrators tasked with keeping accounts and other financial and economic records, legal-administrative evidence, religious sources, letters, marketplace and shopkeepers' songs, newspapers and journals, pictographic evidence, chronograms, epigraphic evidence, early instrumental observations, society commentaries, compilations and books, and historical-climatological databases. These come from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also discussed from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree-rings) is discussed. Finally, conclusions are drawn and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

Etude de l'aménagement d'une forêt classée au Mali avec la participation des populations riveraines - Données du problème et éléments de méthodologie | A Study of the Management of a State-Owned Forest in Mali with the Participation of the Population Living nearby - Issue under Investigation and Elements of Methodology

2000 ◽  
Vol 151 (3) ◽  
pp. 80-83
Author(s):  
Pascal Schneider ◽  
Jean-Pierre Sorg
Keyword(s):  
Natural Resources ◽  
Research Methodology ◽  
Large Scale ◽  
Environmental Context ◽  
Forest Resources ◽  
The State ◽  
Commercial Use ◽  
Economic Context ◽  
The People

In and around the state-owned forest of Farako in the region of Sikasso, Mali, a large-scale study focused on finding a compromise allowing the existential and legitimate needs of the population to be met and at the same time conserving the forest resources in the long term. The first step in research was to sketch out the rural socio-economic context and determine the needs for natural resources for autoconsumption and commercial use as well as the demand for non-material forest services. Simultaneously, the environmental context of the forest and the resources available were evaluated by means of inventories with regard to quality and quantity. According to an in-depth comparison between demand and potential, there is a differentiated view of the suitability of the forest to meet the needs of the people living nearby. Propositions for a multipurpose management of the forest were drawn up. This contribution deals with some basic elements of research methodology as well as with results of the study.

scholarly journals Large-scale Semantic Parsing without Question-Answer Pairs

2014 ◽  
Vol 2 ◽  
pp. 377-392 ◽  
Author(s):  
Siva Reddy ◽  
Mirella Lapata ◽  
Mark Steedman
Keyword(s):  
Natural Language ◽  
Large Scale ◽  
Graph Matching ◽  
State Of The Art ◽  
The State ◽  
Semantic Parsing ◽  
Matching Problem ◽  
Weak Supervision ◽  
Benchmark Datasets

In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a graph matching problem. Our model converts sentences to semantic graphs using CCG and subsequently grounds them to Freebase guided by denotations as a form of weak supervision. Evaluation experiments on a subset of the Free917 and WebQuestions benchmark datasets show our semantic parser improves over the state of the art.

Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration

2021 ◽  
Vol 376 (1821) ◽  
pp. 20190765 ◽  
Author(s):  
Giovanni Pezzulo ◽  
Joshua LaPalme ◽  
Fallon Durant ◽  
Michael Levin
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
State Of The Art ◽  
Memory Representation ◽  
Theme Issue ◽  
Evolutionary Innovation ◽  
New Interpretation ◽  
The Brain

Nervous systems’ computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states—in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo . This article is part of the theme issue ‘Basal cognition: multicellularity, neurons and the cognitive lens’.

scholarly journals A Multilayer CARU Framework to Obtain Probability Distribution for Paragraph-Based Sentiment Analysis

2021 ◽  
Vol 11 (23) ◽  
pp. 11344
Author(s):  
Wei Ke ◽  
Ka-Hou Chan
Keyword(s):  
Probability Distribution ◽  
Information Extraction ◽  
Sentiment Analysis ◽  
State Of The Art ◽  
Final Analysis ◽  
The State ◽  
Experimental Results ◽  
Content Adaptive

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.

scholarly journals Learning from Interventions Using Hierarchical Policies for Safe Learning

2020 ◽  
Vol 34 (06) ◽  
pp. 10352-10360
Author(s):  
Jing Bi ◽  
Vikas Dhiman ◽  
Tianyou Xiao ◽  
Chenliang Xu
Keyword(s):  
Reaction Time ◽  
State Of The Art ◽  
The State ◽  
Policy Framework ◽  
Asymptotic Performance ◽  
Short Term ◽  
Learning From Demonstrations ◽  
Hierarchical Levels ◽  
Long Term Behavior

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.

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 ◽  
...  
Keyword(s):  
Best Practices ◽  
Information Exchange ◽  
State Of The Art ◽  
Environmental Dna ◽  
Bulk Sample ◽  
The State ◽  
Molecular Techniques ◽  
Future Research ◽  
Dna Metabarcoding

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

Self-healing organic coatings based on microcapsules – A patent-based review

2021 ◽  
Vol 04 ◽  
Author(s):  
Diego Moreira Schlemper ◽  
Sérgio Henrique Pezzin
Keyword(s):  
Corrosion Protection ◽  
State Of The Art ◽  
Review Article ◽  
The State ◽  
Organic Coatings ◽  
Self Healing ◽  
Future Challenges ◽  
The Matrix ◽  
Healing Agent

: Self-healing coatings are intended to increase long-term durability and reliability and can be enabled by the presence of microcapsules containing a self-healing agent capable of interacting with the matrix and regenerating the system. This review article provides an overview of the state-of-the-art, focusing on the patents published in the field of microcapsule-based self-healing organic coatings, since the early 2000’s. A discussion about coatings for corrosion protection and the different self-healing approaches and mechanisms are also addressed, as well as future challenges and expectations for this kind of coatings.

A Comprehensive Taxonomy of Dynamic Texture Representation

2023 ◽  
Vol 55 (1) ◽  
pp. 1-39
Author(s):  
Thanh Tuan Nguyen ◽  
Thanh Phuong Nguyen
Keyword(s):  
Large Scale ◽  
Environmental Changes ◽  
State Of The Art ◽  
The State ◽  
Future Research ◽  
Research Activities ◽  
Potential Applications ◽  
Benchmark Datasets ◽  
Negative Impacts ◽  
Made In

Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental changes, noise, illumination, etc.), efficiently analyzing DTs has raised considerable challenges for the state-of-the-art approaches. For 20 years, many different techniques have been introduced to handle the above well-known issues for enhancing the performance. Those methods have shown valuable contributions, but the problems have been incompletely dealt with, particularly recognizing DTs on large-scale datasets. In this article, we present a comprehensive taxonomy of DT representation in order to purposefully give a thorough overview of the existing methods along with overall evaluations of their obtained performances. Accordingly, we arrange the methods into six canonical categories. Each of them is then taken in a brief presentation of its principal methodology stream and various related variants. The effectiveness levels of the state-of-the-art methods are then investigated and thoroughly discussed with respect to quantitative and qualitative evaluations in classifying DTs on benchmark datasets. Finally, we point out several potential applications and the remaining challenges that should be addressed in further directions. In comparison with two existing shallow DT surveys (i.e., the first one is out of date as it was made in 2005, while the newer one (published in 2016) is an inadequate overview), we believe that our proposed comprehensive taxonomy not only provides a better view of DT representation for the target readers but also stimulates future research activities.

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