scholarly journals A Data-intensive Approach for Evaluating Water-Energy-Land-Food Nexus at Multiple Scales

2021 ◽  
Author(s):  
Gaddam Sai Jagadeesh ◽  
Prasanna Venkatesh Sampath
Keyword(s):  
Multiple Scales ◽  
Data Intensive ◽  
Intensive Approach

scholarly journals A DATA-INTENSIVE APPROACH TO EXPLOIT NEW GNSS SCIENCE OPPORTUNITIES

2021 ◽  
Author(s):  
Vicente Navarro ◽  
Javier Ventura-Traveset
Keyword(s):  
Dual Band ◽  
Smart Devices ◽  
Data Repository ◽  
Infrastructure Development ◽  
Data Intensive ◽  
Development Plans ◽  
Intensive Approach ◽  
New Generation ◽  
Gnss Data ◽  
Interactive Algorithms

With the current GNSS infrastructure development plans, over 120 GNSS satellites (including European Galileo satellites)will provide, already this decade, continuous data, in several frequencies, without interruption and on a permanent basis.This global and permanent GNSS infrastructure constitutes a major opportunity for GNSS science applications. In themeantime, recent advances in technology have contributed "de-facto" to the deployment of a large GNSS receiver arraybased on Internet of Things (IoT), affordable smart devices easy to find in everybody’s pockets. These devices – evolvingfast at each new generation – feature an increasing number of capabilities and sensors able to collect a variety ofmeasurements, improving GNSS performance. Among these capabilities, Galileo dual band smartphones receivers andAndroid’s support for raw GNSS data recording represent major steps forward for Positioning, Navigation and Timing (PNT)data processing improvements. Information gathering from these devices, commonly referred as crowdsourcing, opensthe door to new data-intensive analysis techniques in many science domains. At this point, collaboration between variousresearch groups is essential to harness the potential hidden behind the large volumes of data generated by thiscyberinfrastructure. Cloud Computing technologies extend traditional computational boundaries, enabling execution ofprocessing components close to the data. This paradigm shift offers seamless execution of interactive algorithms andanalytics, skipping lengthy downloads and setups. The resulting scenario, defined by a GNSS Big Data repository with colocatedprocessing capabilities, sets an excellent basis for the application of Artificial Intelligence / Machine Learning (ML)technologies in the context of GNSS. This unique opportunity for science has been recognized by the European SpaceAgency (ESA) with the creation of the Navigation Scientific Office, which leverages on GNSS infrastructure to deliverinnovative solutions across multiple scientific domains.

A Data-Intensive Approach to Studying Climate and Climate Change in Africa

2000 ◽  
Vol 48 (4) ◽  
pp. 464-468 ◽  
Author(s):  
Tanya Furman ◽  
Eileen Merritt
Keyword(s):  
Climate Change ◽  
Data Intensive ◽  
Intensive Approach

scholarly journals No general relationship between mass and temperature in endothermic species

2017 ◽  
Author(s):  
Kristina Riemer ◽  
Robert P Guralnick ◽  
Ethan White
Keyword(s):  
Global Warming ◽  
Size Variation ◽  
Single Species ◽  
Bergmann’S Rule ◽  
Bergmann's Rule ◽  
Mammal Species ◽  
Data Intensive ◽  
Multiple Processes ◽  
Intensive Approach ◽  
Individual Mass

Bergmann’s rule is a widely-accepted biogeographic rule stating that individuals within a species are smaller in warmer environments. While there are many single-species studies and integrative reviews documenting this pattern, a data-intensive approach has not been used yet to determine the generality of this pattern. We assessed the strength and direction of the intraspecific relationship between temperature and individual mass for 952 bird and mammal species. For eighty-seven percent of species, temperature explained less than 10% of variation in mass, and for 79% of species the correlation was not statistically significant. These results suggest that Bergmann’s rule is not general and temperature is not a dominant driver of biogeographic variation in mass. Further understanding of size variation will require integrating multiple processes that influence size. The lack of dominant temperature forcing weakens the justification for the hypothesis that global warming could result in widespread decreases in body size.

Are multiscale Water-Energy-Land-Food nexus studies effective in assessing agricultural sustainability?

2021 ◽  
Author(s):  
Sai Jagadeesh Gaddam ◽  
Prasanna Venkatesh Sampath
Keyword(s):  
Energy Consumption ◽  
Energy Security ◽  
Multiple Scales ◽  
Spatial Scales ◽  
Critical Role ◽  
Vulnerability Index ◽  
Sustainable Food ◽  
Data Intensive ◽  
Agricultural Efficiency ◽  
Requirement Model

Abstract Several studies have highlighted the need for multiscale Water-Energy-Land-Food (WELF) nexus studies to ensure sustainable food production without endangering water and energy security. However, a systematic attempt to evaluate the efficiency of such multiscale studies has not yet been made. In this study, we used a data-intensive crop water requirement model to study the multiscale WELF nexus in southern India. In particular, we estimated the groundwater and energy consumption for cultivating five major crops between 2017 and 2019 at three distinct spatial scales ranging from 160,000 km2 (state) to 11,000 km2 (district) to 87 km2 (block). A two-at-one-time approach was used to develop six WELF interactions for each crop, which was used to evaluate the performance of each region. A Gross Vulnerability Index (GVI) was developed at multiple scales that integrated the WELF interactions to identify vulnerable hotspots from a nexus perspective. Results from this nexus study identified the regions that accounted for the largest groundwater and energy consumption, which were also adjudged to be vulnerable hotspots. Our results indicate that while a finer analysis may be necessary for drought-resistant crops like groundnut, a coarser scale analysis may be sufficient to evaluate the agricultural efficiency of water-intensive crops like paddy and sugarcane. We identified that vulnerable hotspots at local scales were often dependent on the crop under consideration, i.e., a hotspot for one crop may not necessarily be a hotspot for another. Clearly, policymaking decisions for improving irrigation efficiency through interventions such as crop-shifting would benefit from such insights. It is evident that such approaches will play a critical role in ensuring food-water-energy security in the coming decades.

scholarly journals A data-intensive approach to mechanistic elucidation applied to chiral anion catalysis

Science ◽  
2015 ◽  
Vol 347 (6223) ◽  
pp. 737-743 ◽  
Author(s):  
A. Milo ◽  
A. J. Neel ◽  
F. D. Toste ◽  
M. S. Sigman
Keyword(s):  
Data Intensive ◽  
Intensive Approach

scholarly journals A corpus-driven approach to discourse organisation: from cues to complex markers

2017 ◽  
Vol 8 (1) ◽  
pp. 66-105
Author(s):  
Marie-Paule Péry-Woodley ◽  
Lydia-Mai Ho-Dac ◽  
Josette Rebeyrolle ◽  
Ludovic Tanguy ◽  
C`ecile Fabre
Keyword(s):  
Large Scale ◽  
Discourse Markers ◽  
Data Intensive ◽  
Multi Level ◽  
Mining Methods ◽  
The Rich ◽  
Intensive Approach ◽  
Rich Data ◽  
Descriptive Survey ◽  
Oriented Approach

This paper reports on an experiment implementing a data-intensive approach to discourse organisation. Its focus is on enumerative structures envisaged as a type of textual pattern in a sequentiality-oriented approach to discourse. On the basis of a large-scale annotation exercise calling upon automatic feature mark-up alongside manual annotation, we explore a method to identify complex discourse markers seen as configurations of cues. The presentation of the background to what is termed "multi-level annotation" is organised around four issues: linearity, complexity of discourse markers, top-down processing, granularity and the multi-level nature of discourse structures. In this context, enumerative structures seem to deserve scrutiny for a number of reasons: they are frequent structures appearing at different granularity levels, they are signalled by a variety of devices appearing to work together in complex ways, and they combine a textual role (discourse organisation) with an ideational role (categorisation). We describe the annotation procedure and experimental framework which resulted in nearly 1,000 enumerative structures being annotated in a diversified corpus of over 600,000 words. The results of two approaches to the rich data produced are then presented: firstly, a descriptive survey highlights considerable variation in length and composition, while showing enumerative structure to be a basic strategy resorted to in all three sub-corpora, and leads to a granularity-based typology of the annotated structures; secondly, recurrent cue configurations---our "complex~ markers"---are identified by the application of data mining methods. The paper ends with perspectives for further exploitation of the data, in particular with respect to the semantic characterisation of enumerative structures.

A data-intensive approach for discovering user similarities in social behavioral interactions based on the bayesian network

2017 ◽  
Vol 219 ◽  
pp. 364-375 ◽  
Author(s):  
Kun Yue ◽  
Hao Wu ◽  
Xiaodong Fu ◽  
Juan Xu ◽  
Zidu Yin ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Behavioral Interactions ◽  
Data Intensive ◽  
Intensive Approach

Thermal boundary resistance at graphene-pentacene interface explored by a data-intensive approach

2021 ◽  
Vol 32 (21) ◽  
pp. 215404
Author(s):  
Xinyu Wang ◽  
Hongzhao Fan ◽  
Dan Han ◽  
Yang Hong ◽  
Jingchao Zhang
Keyword(s):  
Boundary Resistance ◽  
Thermal Boundary Resistance ◽  
Data Intensive ◽  
Intensive Approach

scholarly journals No general relationship between mass and temperature in endothermic species

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Kristina Riemer ◽  
Robert P Guralnick ◽  
Ethan P White
Keyword(s):  
Global Warming ◽  
Size Variation ◽  
Single Species ◽  
Bergmann’S Rule ◽  
Bergmann's Rule ◽  
Mammal Species ◽  
Data Intensive ◽  
Multiple Processes ◽  
Intensive Approach ◽  
Individual Mass

Bergmann's rule is a widely-accepted biogeographic rule stating that individuals within a species are smaller in warmer environments. While there are many single-species studies and integrative reviews documenting this pattern, a data-intensive approach has not been used yet to determine the generality of this pattern. We assessed the strength and direction of the intraspecific relationship between temperature and individual mass for 952 bird and mammal species. For eighty-seven percent of species, temperature explained less than 10% of variation in mass, and for 79% of species the correlation was not statistically significant. These results suggest that Bergmann's rule is not general and temperature is not a dominant driver of biogeographic variation in mass. Further understanding of size variation will require integrating multiple processes that influence size. The lack of dominant temperature forcing weakens the justification for the hypothesis that global warming could result in widespread decreases in body size.

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