Chemical composition of manganese micronodules from expedition VA-05/1 in the Pacific Ocean

A radioisotope energy-dispersive X-ray (EDX) system has been used on board the German research vessel "Valdivia" during an exploration expedition in the northern equatorial Pacific in 1973. The instrumentation used consisted of an X-ray detection system incorporating a 30 mm2 effective-area Si (Li) detector with a measured energy resolution of 195 eV for Mn K alpha X-rays, standard nuclear electronics, a 1024-channel analyser and a data read-out unit. The X-ray spectra in the manganese-nodule samples were excited by a 30-mCi 238Pu source. The six elements Mn, Fe, Co, Ni, Cu and Zn were analysed on board. Precision values for the analyses were less than 3% for Mn, Fe, Ni, Cu and Zn and about 5% for Co. A total amount of 350 analyses was carried out during a one-month cruise. Average contents of 190 analysed whole manganese-nodule samples from all the sampling sites of the covered area were 23.3% Mn, 6.7% Fe, 0.23% Co, 1.16% Ni, 0.94% Cu and 0.10% Zn. The average content of the base metals expressed as the sum of the Co, Ni, Cu and Zn contents was 2.48%. A linear relationship between Mn and Ni in all analysed samples, including whole manganese-nodule samples, zones of manganese nodules and manganese crusts, was observed. The Mn/Ni ratio calculated by regression analysis was 23.0. Zonal variations of the chemical contents of the six elements in the manganese nodules were found. A size classification of the manganese nodules has been suggested. Geochemical correlations of Cu and Ni versus Mn/Fe in the investigated samples are given.

Mercury content and isotopic composition of frost flower, surface snow and brine samples near Barrow, Alaska

Frost flowers are ice crystals that grow on refreezing sea ice leads in Polar Regions by wicking brine from the sea ice surface and accumulating vapor phase condensate. These crystals contain high concentrations of mercury (Hg) and are believed to be a source of reactive halogens, but their role in Hg cycling and impact on the fate of Hg deposited during atmospheric mercury depletion events (AMDEs) are not well understood. We collected frost flowers growing on refreezing sea ice near Barrow, Alaska (U.S.A.) during an AMDE in March 2009 and measured Hg concentrations and Hg stable isotope ratios in these samples to determine the origin of Hg associated with the crystals. We observed decreasing Delta199Hg values in the crystals as they grew from new wet frost flowers (mean Delta199Hg = 0.77 ± 0.13 per mil, 1 s.d.) to older dry frost flowers (mean Delta199Hg = 0.10 ± 0.05 per mil, 1 s.d.). Over the same time period, mean Hg concentrations in these samples increased from 131 ± 6 ng/L (1 s.d.) to 180 ± 28 ng/L (1 s.d.). Coupled with a previous study of Hg isotopic fractionation during AMDEs, these results suggest that Hg initially deposited to the local snowpack was subsequently reemitted during photochemical reduction reactions and ultimately accumulated on the frost flowers. As a result of this process, frost flowers may lead to enhanced local retention of Hg deposited during AMDEs and may increase Hg loading to the Arctic Ocean.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

A high-flux BEC source for mobile atom interferometers

Quantum sensors based on coherent matter-waves are precise measurement devices whose ultimate accuracy is achieved with Bose-Einstein condensates (BECs) in extended free fall. This is ideally realized in microgravity environments such as drop towers, ballistic rockets and space platforms. However, the transition from lab-based BEC machines to robust and mobile sources with comparable performance is a challenging endeavor. Here we report on the realization of a miniaturized setup, generating a flux of 4x10(5) quantum degenerate Rb-87 atoms every 1.6 s. Ensembles of 1 x 10(5) atoms can be produced at a 1 Hz rate. This is achieved by loading a cold atomic beam directly into a multi-layer atom chip that is designed for efficient transfer from laser-cooled to magnetically trapped clouds. The attained flux of degenerate atoms is on par with current lab-based BEC experiments while offering significantly higher repetition rates. Additionally, the flux is approaching those of current interferometers employing Raman-type velocity selection of laser-cooled atoms. The compact and robust design allows for mobile operation in a variety of demanding environments and paves the way for transportable high-precision quantum sensors.

Avaliação do potencial da macrófita Pistia stratiotes na exposição de íon cromo (VI): biossorção e tolerância

The environmental pollution caused by industries has increased the concentration of pollutants in the environment, especially in water. Among the most diverse contaminants, there is the metals, who may or may not to be heavy/toxic, causing effluent of difficult treatment when in low concentrations. The search for alternative measures of wastewater effluent treatment has led to studies using phytoremediation technique through the various matrices (plant, fungi, bacteria) as means of polishing treatment to remove contaminants by means of biosorption/bioaccumulation. In order to use the phytoremediation technique for removing metals of the environmental, it have been performed bioassay with the macrophyte Pistia stratiotes. The bioassays were realized with healthy plants of P. stratiotes acclimatized in a greenhouse, at room temperature and lighting conditions during 28 days of cultivate. The cultivations were performed in glass vessels containing 1 L of the hydroponic solution with chromium (VI) in the potassium dichromate form with concentration range 0.10 to 4.90 mg L-1. The experiments were performed by Outlining Central Composite Rotational (OCCR), where the kinetics of bioaccumulation and chlorophyll a fluorescence were monitored in plants of P. stratiotes during cultivation. The collections of the samples and cultive solution were performed according to the OCCR. The chromium levels were measured in samples of P. stratiotes and the remaining solutions by the methodology of atomic absorption spectrometry by flame. The tolerance of P. stratiotes in relation to exposure to chromium (VI) was analyzed by parameters of physiological activity by means of chlorophyll a fluorescence, using the portable fluorometer PAM (Pulse Amplitude Modulation). The development of P. stratiots and their biomass were related to the time factor, while bioaccumulation capacities were strongly influenced by factors of time and chromium concentration (VI). The chlorophyll fluorescence parameters were affected by chromium and the exposure time at the bioassays. It was obtained an higher metal removal from the root in relation to the sheet, reaching a high rate of metal removal in solution. The experimental data removal kinetics were represented by kinetic models Irreversibly Langmuir, Reversible Langmuir, Pseudo-first Order and Pseudo-second Order, and the best fit for the culture solution was the Reversible Langmuir model with R² 0.993 and for the plant the best model was Pseudo-second order with R² 0.760.

Climate variability of the last 1000 years in the NW Pacific: high resolution, multi-biomarker records from Lake Toyoni

The East Asian Monsoon (EAM) is an active component of the global climate system and has a profound social and economic impact in East Asia and its surrounding countries. Its impact on regional hydrological processes may influence society through industrial water supplies, food productivity and energy use. In order to predict future rates of climate change, reliable and accurate reconstructions of regional temperature and rainfall are required from all over the world to test climate models and better predict future climate variability. Hokkaido is a region which has limited palaeo-climate data and is sensitive to climate change. Instrumental data show that the climate in Hokkaido is influenced by the East Asian Monsoon (EAM), however, instrumental data is limited to the past ~150 years. Therefore down-core climate reconstructions, prior to instrumental records, are required to provide a better understanding of the long-term behaviour of the climate drivers (e.g. the EAM, Westerlies, and teleconnections) in this region. The present study develops multi-proxy reconstructions to determine past climatic and hydrologic variability in Japan over the past 1000 years and aid in understanding the effects of the EAM and the Westerlies independently and interactively. A 250-cm long sediment core from Lake Toyoni, Hokkaido was retrieved to investigate terrestrial and aquatic input, lake temperature and hydrological changes over the past 1000-years within Lake Toyoni and its catchment using X-Ray Fluorescence (XRF) data, alkenone palaeothermometry, the molecular and hydrogen isotopic composition of higher plant waxes (δD(HPW)). Here, we conducted the first survey for alkenone biomarkers in eight lakes in the Hokkaido, Japan. We detected the occurrence of alkenones within the sediments of Lake Toyoni. We present the first lacustrine alkenone record from Japan, including genetic analysis of the alkenone producer. C37 alkenone concentrations in surface sediments are 18µg C37 g−1 of dry sediment and the dominant alkenone is C37:4. 18S rDNA analysis revealed the presence of a single alkenone producer in Lake Toyoni and thus a single calibration is used for reconstructing lake temperature based on alkenone unsaturation patterns. Temperature reconstructions over the past 1000 years suggest that lake water temperatures varies between 8 and 19°C which is in line with water temperature changes observed in the modern Lake Toyoni. The alkenone-based temperature reconstruction provides evidence for the variability of the EAM over the past 1000 years. The δD(HPW) suggest that the large fluctuations (∼40‰) represent changes in temperature and source precipitation in this region, which is ultimately controlled by the EAM system and therefore a proxy for the EAM system. In order to complement the biomarker reconstructions, the XRF data strengthen the lake temperature and hydrological reconstructions by providing information on past productivity, which is controlled by the East Asian Summer monsoon (EASM) and wind input into Lake Toyoni, which is controlled by the East Asian Winter Monsoon (EAWM) and the Westerlies. By combining the data generated from XRF, alkenone palaeothermometry and the δD(HPW) reconstructions, we provide valuable information on the EAM and the Westerlies, including; the timing of intensification and weakening, the teleconnections influencing them and the relationship between them. During the Medieval Warm Period (MWP), we find that the EASM dominated and the EAWM was suppressed, whereas, during the Little Ice Age (LIA), the influence of the EAWM dominated with time periods of increased EASM and Westerlies intensification. The El Niño Southern Oscillation (ENSO) significantly influenced the EAM; a strong EASM occurred during El Niño conditions and a strong EAWM occurred during La Niña. The North Atlantic Oscillation, on the other hand, was a key driver of the Westerlies intensification; strengthening of the Westerlies during a positive NAO phase and weakening of the Westerlies during a negative NAO phase. A key finding from this study is that our data support an anti-phase relationship between the EASM and the EAWM (e.g. the intensification of the EASM and weakening of the EAWM and vice versa) and that the EAWM and the Westerlies vary independently from each other, rather than coincide as previously suggested in other studies.

The'cave' mineral oxammite: a high resolution thermogravimetry and Raman spectroscopic study

The thermal decomposition of natural ammonium oxalate known as oxammite has been studied using a combination of high resolution thermogravimetry coupled to an evolved gas mass spectrometer and Raman spectroscopy coupled to a thermal stage. Three mass loss steps were found at 57, 175 and 188°C attributed to dehydration, ammonia evolution and carbon dioxide evolution respectively. Raman spectroscopy shows two bands at 3235 and 3030 cm-1 attributed to the OH stretching vibrations and three bands at 2995, 2900 and 2879 cm-1, attributed to the NH vibrational modes. The thermal degradation of oxammite may be followed by the loss of intensity of these bands. No intensity remains in the OH stretching bands at 100°C and the NH stretching bands show no intensity at 200°C. Multiple CO symmetric stretching bands are observed at 1473, 1454, 1447 and 1431cm-1, suggesting that the mineral oxammite is composed of a mixture of chemicals including ammonium oxalate dihydrate, ammonium oxalate monohydrate and anhydrous ammonium oxalate.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Road network extraction with new vectorization and pruning from high-resolution RS images

With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Campylobacter jejuni and campylobacter coli genotyping by high-resolution melting analysis of a flaA fragment

The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP. flaAHRManalysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.