THE FLUVIAL ACTION OF THE KARLA BASIN STREAMS IN A NATURAL AND MAN – MADE ENVIRONMENT

This study investigates the fluvial action of streams draining the Lake Karla basin, located in the plain of Thessaly, in Central Greece. Until a few decades ago, a large part of this area had been occupied by a lake. In order to find out the relation between the channel bed morphology and the oscillations of the local base level due to variations in water level and human intervention in the lake, the following streams were investigated: the flumes of Mpegiatiko, Bagiorema, Bathurema, Xerias and Maurorema. The width and the length of all channels were measured with a laser range finder while the incision and the erosive events were recorded by GPS with sub-meter accuracy. Furthermore, an integrated GIS analysis was undertaken in order to illustrate the changes in the water level of Lake Karla coupled with historical data and data from previous studies. It will be shown that there were two main evolutionary stages which controlled the local base level changes of the studied area. The first one is connected to the continuous changes in the lake’s water level and its reduction from 64m to 45m a.s.l. This resulted in the incision of the channels and the creation of characteristic knick points upstream. The second stage is associated with the draining of Lake Karla in 1962. This intervention mostly altered the streams that developed into fine-grained material channel beds.

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Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽

10.3390/w12010219 ◽

2020 ◽

Vol 12 (1) ◽

pp. 219 ◽

Cited By ~ 2

Author(s):

Antonio-Juan Collados-Lara ◽

David Pulido-Velazquez ◽

Rosa María Mateos ◽

Pablo Ezquerro

Keyword(s):

Climate Change ◽

Land Subsidence ◽

Ground Subsidence ◽

Lower Percentage ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Fine Grained ◽

Fine Grained Material ◽

The Impact

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.

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Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i05.6383 ◽

2020 ◽

Vol 34 (05) ◽

pp. 8600-8607

Author(s):

Haiyun Peng ◽

Lu Xu ◽

Lidong Bing ◽

Fei Huang ◽

Wei Lu ◽

...

Keyword(s):

Sentiment Analysis ◽

State Of The Art ◽

Complete Solution ◽

Unified Model ◽

Two Stage ◽

Fine Grained ◽

Aspect Extraction ◽

Second Stage ◽

Opinion Extraction ◽

Complete Story

Target-based sentiment analysis or aspect-based sentiment analysis (ABSA) refers to addressing various sentiment analysis tasks at a fine-grained level, which includes but is not limited to aspect extraction, aspect sentiment classification, and opinion extraction. There exist many solvers of the above individual subtasks or a combination of two subtasks, and they can work together to tell a complete story, i.e. the discussed aspect, the sentiment on it, and the cause of the sentiment. However, no previous ABSA research tried to provide a complete solution in one shot. In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE). Particularly, a solver of this task needs to extract triplets (What, How, Why) from the inputs, which show WHAT the targeted aspects are, HOW their sentiment polarities are and WHY they have such polarities (i.e. opinion reasons). For instance, one triplet from “Waiters are very friendly and the pasta is simply average” could be (‘Waiters’, positive, ‘friendly’). We propose a two-stage framework to address this task. The first stage predicts what, how and why in a unified model, and then the second stage pairs up the predicted what (how) and why from the first stage to output triplets. In the experiments, our framework has set a benchmark performance in this novel triplet extraction task. Meanwhile, it outperforms a few strong baselines adapted from state-of-the-art related methods.

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Mineralogy and petrology of Stardust particles encased in the bulb of track 80: TEM investigation of the Wild 2 fine-grained material

Geochimica et Cosmochimica Acta ◽

10.1016/j.gca.2012.03.026 ◽

2012 ◽

Vol 87 ◽

pp. 35-50 ◽

Cited By ~ 32

Author(s):

Julien Stodolna ◽

Damien Jacob ◽

Hugues Leroux

Keyword(s):

Fine Grained ◽

Fine Grained Material

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Two-dimensional consolidation analysis of geotextile tubes filled with fine-grained material

Geotextiles and Geomembranes ◽

10.1016/j.geotexmem.2021.03.009 ◽

2021 ◽

Author(s):

H.J. Kim ◽

P.R. Dinoy

Keyword(s):

Two Dimensional ◽

Fine Grained ◽

Fine Grained Material ◽

Consolidation Analysis

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FG-LiquID

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies ◽

10.1145/3478075 ◽

2021 ◽

Vol 5 (3) ◽

pp. 1-27

Author(s):

Yumeng Liang ◽

Anfu Zhou ◽

Huanhuan Zhang ◽

Xinzhe Wen ◽

Huadong Ma

Keyword(s):

Alcohol Concentration ◽

Coarse Grained ◽

Robust Identification ◽

Fine Grained ◽

Fresh Milk ◽

Average Accuracy ◽

Coarse Grained Material ◽

Potential Applications ◽

Fine Grained Material ◽

The Difference

Contact-less liquid identification via wireless sensing has diverse potential applications in our daily life, such as identifying alcohol content in liquids, distinguishing spoiled and fresh milk, and even detecting water contamination. Recent works have verified the feasibility of utilizing mmWave radar to perform coarse-grained material identification, e.g., discriminating liquid and carpet. However, they do not fully exploit the sensing limits of mmWave in terms of fine-grained material classification. In this paper, we propose FG-LiquID, an accurate and robust system for fine-grained liquid identification. To achieve the desired fine granularity, FG-LiquID first focuses on the small but informative region of the mmWave spectrum, so as to extract the most discriminative features of liquids. Then we design a novel neural network, which uncovers and leverages the hidden signal patterns across multiple antennas on mmWave sensors. In this way, FG-LiquID learns to calibrate signals and finally eliminate the adverse effect of location interference caused by minor displacement/rotation of the liquid container, which ensures robust identification towards daily usage scenarios. Extensive experimental results using a custom-build prototype demonstrate that FG-LiquID can accurately distinguish 30 different liquids with an average accuracy of 97%, under 5 different scenarios. More importantly, it can discriminate quite similar liquids, such as liquors with the difference of only 1% alcohol concentration by volume.

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Unrestricted Bridging Resolution

Computational Linguistics ◽

10.1162/coli_a_00315 ◽

2018 ◽

Vol 44 (2) ◽

pp. 237-284 ◽

Cited By ~ 1

Author(s):

Yufang Hou ◽

Katja Markert ◽

Michael Strube

Keyword(s):

High Reliability ◽

Class Imbalance ◽

Collective Classification ◽

Fine Grained ◽

Joint Inference ◽

Second Stage ◽

Information Status ◽

Novel Method ◽

Definition Of ◽

Marginal Reliability

In contrast to identity anaphors, which indicate coreference between a noun phrase and its antecedent, bridging anaphors link to their antecedent(s) via lexico-semantic, frame, or encyclopedic relations. Bridging resolution involves recognizing bridging anaphors and finding links to antecedents. In contrast to most prior work, we tackle both problems. Our work also follows a more wide-ranging definition of bridging than most previous work and does not impose any restrictions on the type of bridging anaphora or relations between anaphor and antecedent. We create a corpus (ISNotes) annotated for information status (IS), bridging being one of the IS subcategories. The annotations reach high reliability for all categories and marginal reliability for the bridging subcategory. We use a two-stage statistical global inference method for bridging resolution. Given all mentions in a document, the first stage, bridging anaphora recognition, recognizes bridging anaphors as a subtask of learning fine-grained IS. We use a cascading collective classification method where (i) collective classification allows us to investigate relations among several mentions and autocorrelation among IS classes and (ii) cascaded classification allows us to tackle class imbalance, important for minority classes such as bridging. We show that our method outperforms current methods both for IS recognition overall as well as for bridging, specifically. The second stage, bridging antecedent selection, finds the antecedents for all predicted bridging anaphors. We investigate the phenomenon of semantically or syntactically related bridging anaphors that share the same antecedent, a phenomenon we call sibling anaphors. We show that taking sibling anaphors into account in a joint inference model improves antecedent selection performance. In addition, we develop semantic and salience features for antecedent selection and suggest a novel method to build the candidate antecedent list for an anaphor, using the discourse scope of the anaphor. Our model outperforms previous work significantly.

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Geological framework of the Laurentian trough aquifer system, southern Ontario

Canadian Journal of Earth Sciences ◽

10.1139/cjes-2017-0113 ◽

2018 ◽

Vol 55 (7) ◽

pp. 677-708 ◽

Cited By ~ 4

Author(s):

David R. Sharpe ◽

André J.-M. Pugin ◽

Hazen A.J. Russell

Keyword(s):

Lake Ontario ◽

Water Levels ◽

Coarse Grained ◽

Oak Ridges Moraine ◽

Aquifer System ◽

Fine Grained ◽

Niagara Escarpment ◽

Base Level ◽

Glacial Periods ◽

East West

The Laurentian trough (LT), a depression >100 km long, >3000 km2 in area, and 100 m deep at the base of the Niagara Escarpment, extends from within Georgian Bay to Lake Ontario. It has a complex erosional history and is filled and buried by up to 200 m of interglacial and glacial sediment. The primary depression fronts a cuesta landscape and is attributed to differential erosion by fluvial, glacial, and glaciofluvial processes, exposing Ordovician rocks along the Canadian Shield margin. The fill succession includes sediments from the last two glacial periods (Illinoian, Wisconsinan) and the intervening interglacial time (Sangamonian), a poorly dated succession with at least three regional unconformities. A subaerial (interglacial, Don Formation) unconformity relates to low base level mainly preserved in lows of the LT, succeeded by a long period of rising water levels and glaciolacustrine conditions as ice advanced into the Lake Ontario basin. A second unconformity, within the Thorncliffe Formation, is the result of rapid channel erosion to bedrock, forming an ∼north–south network filled with coarse-grained glaciofluvial, transitional to fine-grained glaciolacustrine subaqueous fan sediment. The overlying drumlinized Newmarket Till, up to 50 m thick, is a distinct regional unit with a planar to undulating base. A third unconformity event eroded Newmarket Till, locally truncating it and underlying sediment to bedrock. Three younger sediment packages, Oak Ridges Moraine (channel and ridge sediment), Halton, and glaciolacustrine overlie this erosion surface. Significant regional aquifers are hosted within the LT. Upper Thorncliffe Formation sediments, north–south glaciofluvial channel–fan aquifers, are protected by overlying mud and Newmarket Till aquitards. Similarly, Oak Ridges Moraine sediments comprise a north–south array of glaciofluvial channel–fans and east–west fan aquifers, locally covered by silt–clay rhythmite and till aquitards.

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