The Static Failure of Adhesively Bonded Metal Laminate Structures: A Cohesive Zone Approach

Data on distribution, ecology, biomass, recruitment, growth, mortality and productivity of the West African bloody cockle Anadara senilis were collected at the Banc d'Aguuin, Mauritania, in early 1985 and 1986. Ash-free dry weight appeared to be correlated best with shell height. A. senilis was abundant on the tidal flats of landlocked coastal bays, but nearly absent on the tidal flats bordering the open sea. The average biomass for the entire area of tidal flats was estimated at 5.5 g·m−2 ash-free dry weight. The A. senilis population appeared to consist mainly of 10 to 20-year-old individuals, showing a very slow growth and a production: biomass ratio of about 0.02 y−1. Recruitment appeared negligible and mortality was estimated to be about 10% per year. Oystercatchers (Haematopus ostralegus), the gastropod Cymbium cymbium and unknown fish species were responsible for a large share of this. The distinction of annual growth marks permitted the assessment of year-class strength, which appeared to be correlated with the average discharge of the river Senegal. This may be explained by assuming that year-class strength and river discharge both are correlated with rainfall at the Banc d'Arguin.

DETECTION OF CLOUDS IN MEDIUM-RESOLUTION SATELLITE IMAGERY USING DEEP CONVOLUTIONAL NEURAL NETS

Cloud detection is an inextricable pre-processing step in remote sensing image analysis workflows. Most of the traditional rule-based and machine-learning-based algorithms utilize low-level features of the clouds and classify individual cloud pixels based on their spectral signatures. Cloud detection using such approaches can be challenging due to a multitude of factors including harsh lighting conditions, the presence of thin clouds, the context of surrounding pixels, and complex spatial patterns. In recent studies, deep convolutional neural networks (CNNs) have shown outstanding results in the computer vision domain. These methods are practiced for better capturing the texture, shape as well as context of images. In this study, we propose a deep learning CNN approach to detect cloud pixels from medium-resolution satellite imagery. The proposed CNN accounts for both the low-level features, such as color and texture information as well as high-level features extracted from successive convolutions of the input image. We prepared a cloud-pixel dataset of approximately 7273 randomly sampled 320 by 320 pixels image patches taken from a total of 121 Landsat-8 (30m) and Sentinel-2 (20m) image scenes. These satellite images come with cloud masks. From the available data channels, only blue, green, red, and NIR bands are fed into the model. The CNN model was trained on 5300 image patches and validated on 1973 independent image patches. As the final output from our model, we extract a binary mask of cloud pixels and non-cloud pixels. The results are benchmarked against established cloud detection methods using standard accuracy metrics

Large CO\u3csub\u3e2\u3c/sub\u3e and CH\u3csub\u3e4\u3c/sub\u3e emissions from polygonal tundra during spring thaw in northern Alaska

The few prethaw observations of tundra carbon fluxes suggest that there may be large spring releases, but little is known about the scale and underlying mechanisms of this phenomenon. To address these questions, we combined ecosystem eddy flux measurements from two towers near Barrow, Alaska, with mechanistic soil-core thawing experiment. During a 2 week period prior to snowmelt in 2014, large fluxes were measured, reducing net summer uptake of CO2 by 46% and adding 6% to cumulative CH4 emissions. Emission pulses were linked to unique rain-on-snow events enhancing soil cracking. Controlled laboratory experiment revealed that as surface ice thaws, an immediate, large pulse of trapped gases is emitted. These results suggest that the Arctic CO2 and CH4 spring pulse is a delayed release of biogenic gas production from the previous fall and that the pulse can be large enough to offset a significant fraction of the moderate Arctic tundra carbon sink

The role of defects in fluorescent silicon carbide layers grown by sublimation epitaxy

Donor-acceptor co-doped SiC is a promising light converter for novel monolithic all-semiconductor white LEDs due to its broad-band donor-acceptor pair luminescence and potentially high internal quantum efficiency. Besides sufficiently high doping concentrations in an appropriate ratio yielding short radiative lifetimes, long nonradiative lifetimes are crucial for efficient light conversion. The impact of different types of defects is studied by characterizing fluorescent silicon carbide layers with regard to photoluminescence intensity, homogeneity and efficiency taking into account dislocation density and distribution. Different doping concentrations and variations in gas phase composition and pressure are investigated

Affect in mathematics education

There are two different uses for the word “affect” in behavioral sciences. Often it is used as an overarching umbrella concept that covers attitudes, beliefs, motivation, emotions, and all other noncognitive aspects of human mind. In this article, however, the word affect is used in a more narrow sense, referring to emotional states and traits. A more technical definition of emotions, states, and traits will follow later.Peer reviewe

Decadal-scale hotspot methane ebullition within lakes following abrupt permafrost thaw

Thermokarst lakes accelerate deep permafrost thaw and the mobilization of previously frozen soil organic carbon. This leads to microbial decomposition and large releases of carbon dioxide (CO2) and methane (CH4) that enhance climate warming. However, the time scale of permafrost-carbon emissions following thaw is not well known but is important for understanding how abrupt permafrost thaw impacts climate feedback. We combined field measurements and radiocarbon dating of CH4 ebullition with (a) an assessment of lake area changes delineated from high-resolution (1–2.5 m) optical imagery and (b) geophysical measurements of thaw bulbs (taliks) to determine the spatiotemporal dynamics of hotspot-seep CH4 ebullition in interior Alaska thermokarst lakes. Hotspot seeps are characterized as point-sources of high ebullition that release 14C-depleted CH4 from deep (up to tens of meters) within lake thaw bulbs year-round. Thermokarst lakes, initiated by a variety of factors, doubled in number and increased 37.5% in area from 1949 to 2009 as climate warmed. Approximately 80% of contemporary CH4 hotspot seeps were associated with this recent thermokarst activity, occurring where 60 years of abrupt thaw took place as a result of new and expanded lake areas. Hotspot occurrence diminished with distance from thermokarst lake margins. We attribute older 14C ages of CH4 released from hotspot seeps in older, expanding thermokarst lakes (14CCH4 20 079 ± 1227 years BP, mean ± standard error (s.e.m.) years) to deeper taliks (thaw bulbs) compared to younger 14CCH4 in new lakes (14CCH4 8526 ± 741 years BP) with shallower taliks. We find that smaller, non-hotspot ebullition seeps have younger 14C ages (expanding lakes 7473 ± 1762 years; new lakes 4742 ± 803 years) and that their emissions span a larger historic range. These observations provide a first-order constraint on the magnitude and decadal-scale duration of CH4-hotspot seep emissions following formation of thermokarst lakes as climate warms

Mathematical talent in Braille code pattern finding and invention

The recognition of patterns and creativity are two characteristics associated with mathematical talent. In this study, we analyzed these characteristics in a group of 37 mathematically talented students. The students were asked to find the pattern the Braille code had been built upon and reinvent it with the aim of making its mathematical language become more functional. Initially, the students were unable to identify the formation pattern of Braille, but after experiencing the difficulties that blind people face when reading it, they recognized the generating element and the regularity. The results were in contrast with those of a control group, and it is noted that the students with mathematical talent were more effective in using visualization to identify the regularity of the pattern and their invention proposals were more sophisticated and used less conventional mathematical content.This research is part of the R+D+I project EDU2015- 69,731-R (Spanish Government/MinEco and ERDF)