Label-free 3D visualization of cellular and tissue structures in intact muscle with second and third harmonic generation microscopy.

Second and Third Harmonic Generation (SHG and THG) microscopy is based on optical effects which are induced by specific inherent physical properties of a specimen. As a multi-photon laser scanning approach which is not based on fluorescence it combines the advantages of a label-free technique with restriction of signal generation to the focal plane, thus allowing high resolution 3D reconstruction of image volumes without out-of-focus background several hundred micrometers deep into the tissue. While in mammalian soft tissues SHG is mostly restricted to collagen fibers and striated muscle myosin, THG is induced at a large variety of structures, since it is generated at interfaces such as refraction index changes within the focal volume of the excitation laser. Besides, colorants such as hemoglobin can cause resonance enhancement, leading to intense THG signals. We applied SHG and THG microscopy to murine (Mus musculus) muscles, an established model system for physiological research, to investigate their potential for label-free tissue imaging. In addition to collagen fibers and muscle fiber substructure, THG allowed us to visualize blood vessel walls and erythrocytes as well as white blood cells adhering to vessel walls, residing in or moving through the extravascular tissue. Moreover peripheral nerve fibers could be clearly identified. Structure down to the nuclear chromatin distribution was visualized in 3D and with more detail than obtainable by bright field microscopy. To our knowledge, most of these objects have not been visualized previously by THG or any label-free 3D approach. THG allows label-free microscopy with inherent optical sectioning and therefore may offer similar improvements compared to bright field microscopy as does confocal laser scanning microscopy compared to conventional fluorescence microscopy

Late Pleistocene fans and terraces in the Majes valley, southern Peru, and their relation to climatic variations

This study investigates the connection between sediment aggradation, erosion and climate in a desert environment of the Majes valley, southern Peru. Luminescence dating of terraces and fans shows that sediment aggradation correlates with wet time intervals on the Altiplano, suggesting a climatic influence on the aggradation-degradation cycles. Major periods of aggradation occurred between ~110-100, ~60-50 and 12-8ka. More precipitation in the Majes catchment resulted in increased erosion and transportation of sediment from the hillslopes into the trunk river. As a result, the sediment loads exceeded the transport capacity of the Majes River and aggradation started in the lower reaches where the river gradient is less. Depletion of the hillslope sediment reservoirs caused a relative increase in the capacity of the trunk river to entrain and transport sediment, resulting in erosion of the previously deposited sediment. Consequently, although climate change may initiate a phase of sediment accumulation, degradation can be triggered by an autocyclic negative feedback and does not have to be driven by climatic chang

A comparison and evaluation of performances among crop yield forecasting models based on remote sensing: Results from the GEOLAND Observatory of Food Monitoring

In the context of the GEOLAND EC FP6 project the comparison of different remote sensing based approaches for yield forecasting over large areas in Europe are tested and results inter-compared. In particular the methods tested include the ones in use within the MARS-Crop Yield Forecasting System as the results from a Crop Growth Monitoring model (Alterra) and vegetation indicators derived from Low Resolution VGT and NOAA Images (VITO, IGiK), METEOSAT based yield forecasting (EARS) and ERS-Scatterometer Crop Performance Index (TPF and NEO). Performances of the different models were tested in Spain, Belgium and Poland. The inter-comparison of the crop yield forecasts were mainly based on the forecasting error obtained from the different approaches based on the Root Mean Square Forecast Error (RMSFE). This error was derived by comparing the predicted yields of the different models with the official yield from EUROSTAT. The comparison of the RMSFE was used to verify the convergence of results from the different models, the reliability of the information, i.e. precision and bias, and its precocity compared to the crop cycle. The results showed that the indicators are able to give reliable information with some differences: remote sensing indicators are more precise and accurate in southern areas (less cloud cover) while in northern areas good results are obtained under the use of better local calibrations of traditional crop yield forecasting systems, the use of additional information or the additional use of remote sensing data as inputs into advanced crop modelling systems. Furthermore, in order to take care of the different time series length available, a qualitative indicator called Performance Score (Ps) was introduced. The analysis of the Ps showed that when a long time series of observation is available greater advantages are obtained from RS rather than from more advanced crop models.JRC.DG.G.3-Monitoring agricultural resource

What do we know about poverty in North Korea?

Reliable quantitative information on the North Korean economy is extremely scarce. In particular, reliable income per capita and poverty figures for the country are not available. In this contribution, we provide for the first time estimates of absolute poverty rates in North Korean subnational regions based on the combination of innovative remote-sensednight-time light intensity data (monthly information for built areas) with estimated income distributions. Our results, which are robust to the use of different methods to approximatethe income distribution in the country, indicate that the share of persons living in extreme poverty in North Korea may be larger than previously thought. We estimate a poverty rate for the country of around 60% in 2018 and a high volatility in the dynamics of income at the national level in North Korea for the period 2012–2018. Income per capita estimates tend to decline significantly from 2012 to 2015 and present a recovery since 2016. The subnational estimates of income and poverty reveal a change in relative dynamics since the second half of the 2012–2018 period. The first part of the period is dominated by divergent dynamics inincome across regions, while the second half reveals convergence in regional income

Ice wedge polygon stability on steep slopes in West Greenland related to temperature and moisture dynamics of the active layer

Ice wedge polygons on steep slopes have generally been described as being covered by periglacial sediments and, typically, the active layer on slopes becomes mobile during thaw periods, which can lead to solifluction. In West Greenland close to the ice margin, however, the active layer and ice wedge polygons are stable despite their occurrence on steep slopes with inclinations of ≥30°. We conducted a soil survey (including sampling for soil analyses and radiocarbon dating) in the Umimmalissuaq valley and installed a field station ~4 km east of the current ice margin to monitor soil temperature and water tension at depths of 10, 20 and 35 cm of the active layer on a steep, north-facing slope in the middle of an ice wedge polygon from 2009 to 2015. Thawing and freezing periods lasted between 2 and 3 months and the active layer was usually completely frozen from November to April. We observed simultaneous and complete water saturation at all three depths of the active layer in one summer for 1 day. The amount of water in the active layer apparently was not enough to trigger solifluction during the summer thaw, even at slope inclinations above 30°. In addition, the dense shrub tundra absorbs most of the water during periods between thawing and freezing, which further stabilizes the slope. This process, together with the dry and continental climate caused by katabatic winds combined with no or limited frost heave, plays a crucial role in determining the stability of these slopes and can explain the presence of large-scale stable ice wedge polygon networks in organic matter-rich permafrost, which is about 5,000 years old. This study underlines the importance of soil hydrodynamics and local climate regime for landscape stability and differing intensities of solifluction processes in areas with strong geomorphological gradients and rising air temperatures

Best practices for crop area estimation with Remote Sensing

This document gives recommendations on different ways to use Earth Observation as a tool for crop area estimation highlighting strengths and limitations. The document was discussed in a workshop hosted by the Joint Research Centre (JRC) of the European Commission in June 2008 and attended by 40 remote sensing practitioners and users.JRC.DG.G.3-Monitoring agricultural resource

Enantioselektive Synthese von (1S,4R)-4-Hydroxycyclopent-2-enyl-acetat durch enzym-katalysierte Veresterung von cis-Cyclopent-2-en-1,4-diol mit Acetanhydrid. Gaschromatographische Untersuchungen zum Reaktionsmechanismus

(1S,4R)-4-Hydroxycyclopent-2-enyl-acetate (1), an attractive starting material for the synthesis of prostaglandins, was readily prepared by an enzyme-catalyzed interesterification procedure using acetic anhydride as acylation agent. As the chemical yield of the chiral monoacylation product is rather low (45%), we investigated the acylation mechanism of this reaction to optimize the product output. Kinetic measurements were carried out by means of gas chromatography on a chiral stationary phase, synthesized by methylation of β-cyclodextrin

How many people need to classify the same image? A method for optimizing volunteer contributions in binary geographical classifications

Involving members of the public in image classification tasks that can be tricky to automate is increasingly recognized as a way to complete large amounts of these tasks and promote citizen involvement in science. While this labor is usually provided for free, it is still limited, making it important for researchers to use volunteer contributions as efficiently as possible. Using volunteer labor efficiently becomes complicated when individual tasks are assigned to multiple volunteers to increase confidence that the correct classification has been reached. In this paper, we develop a system to decide when enough information has been accumulated to confidently declare an image to be classified and remove it from circulation. We use a Bayesian approach to estimate the posterior distribution of the mean rating in a binary image classification task. Tasks are removed from circulation when user-defined certainty thresholds are reached. We demonstrate this process using a set of over 4.5 million unique classifications by 2783 volunteers of over 190,000 images assessed for the presence/absence of cropland. If the system outlined here had been implemented in the original data collection campaign, it would have eliminated the need for 59.4% of volunteer ratings. Had this effort been applied to new tasks, it would have allowed an estimated 2.46 times as many images to have been classified with the same amount of labor, demonstrating the power of this method to make more efficient use of limited volunteer contributions. To simplify implementation of this method by other investigators, we provide cutoff value combinations for one set of confidence levels

Harmonizing and combining existing land cover and land use datasets for cropland area monitoring at the African continental scale

Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this study were to (i) consolidate the best existing land cover/land use datasets, (ii) adopt the Land Cover Classification System (LCCS) for harmonization and (iii) assess the final product. Ten datasets were compared and combined through an expert-based approach to create the derived map of cropland areas at 250m covering the whole of Africa. The resulting cropland mask was compared with two recent cropland extent maps at 1km: one derived from MODIS and one derived from five existing products. The accuracy of the three products was assessed against a validation sample of 3591 pixels of 1km² regularly distributed over Africa and interpreted using high resolution images, which were collected using the agriculture.geo.wiki.org tool. The comparison of the resulting crop mask with existing products shows that it has a greater agreement with the expert validation dataset, in particular for cropland above 30%.JRC.H.4-Monitoring Agricultural Resource