Nitrate reduction in the vicinity of tile drains

The fate of nitrates as they travel through a long porous column at a slow rate was observed in this study with temperature and substrate materials variable. During a one month period of flow with pore velocities averaging up to 21 centimeters per day, losses as high as 89 percent were found for a methanol treatment at 24˚ while for 13˚ losses were reduced to 46 percent. A sawdust substrate material resulted in very little reduction of nitrate concentrations at 24˚ and actual increases (presumably from mineralization) at 13˚. Since methanol was found to be an effective means of removing nitrate from a slowly moving stream of water at 0 temperatures as low as 13 C, it will be used as a standard in future field studies to evaluate less expensive substrate materials.U.S. Geological SurveyU.S. Department of the InteriorOpe

Practical Performance Measurements of LTE Broadcast (eMBMS) for TV Applications

The 3GPP Release-14 specification has enhanced LTE eMBMS to enable the provision of television services according to some of the requirements of the broadcasting industry. These improvements include radio interface enhancements such as support for larger inter-site distances in Single Frequency Network deployments and the introduction of more flexibility including a dedicated eMBMS carrier with 100% broadcast resource allocation. Although the performance of LTE eMBMS has been extensively evaluated by numerical computations, it is crucial to perform laboratory measurements that provide insights into the operation of the system in a practical setup. This paper describes the construction of eMBMS chains within the laboratory to carry out physical-layer measurements within a controlled environment and presents a methodology to measure the signal-to-noise-ratio (SNR) of eMBMS signals (that can time multiplex both unicast and broadcast parts). The SNR thresholds at different modulation and coding schemes are measured independently in the laboratories of BBC R&D and IRT and the results are compared with the results obtained with numerical evaluations

Bearing Diagnosis Using Fault Signal Enhancing Teqniques and Data-driven Classification

Rolling element bearings are a vital part in many rotating machinery, including vehicles. A defective bearing can be a symptom of other problems in the machinery and is due to a high failure rate. Early detection of bearing defects can therefore help to prevent malfunction which ultimately could lead to a total collapse. The thesis is done in collaboration with Scania that wants a better understanding of how external sensors such as accelerometers, can be used for condition monitoring in their gearboxes. Defective bearings creates vibrations with specific frequencies, known as Bearing Characteristic Frequencies, BCF [23]. A key component in the proposed method is based on identification and extraction of these frequencies from vibration signals from accelerometers mounted near the monitored bearing. Three solutions are proposed for automatic bearing fault detection. Two are based on data-driven classification using a set of machine learning methods called Support Vector Machines and one method using only the computed characteristic frequencies from the considered bearing faults. Two types of features are developed as inputs to the data-driven classifiers. One is based on the extracted amplitudes of the BCF and the other on statistical properties from Intrinsic Mode Functions generated by an improved Empirical Mode Decomposition algorithm. In order to enhance the diagnostic information in the vibration signals two pre-processing steps are proposed. Separation of the bearing signal from masking noise are done with the Cepstral Editing Procedure, which removes discrete frequencies from the raw vibration signal. Enhancement of the bearing signal is achieved by band pass filtering and amplitude demodulation. The frequency band is produced by the band selection algorithms Kurtogram and Autogram. The proposed methods are evaluated on two large public data sets considering bearing fault classification using accelerometer data, and a smaller data set collected from a Scania gearbox. The produced features achieved significant separation on the public and collected data. Manual detection of the induced defect on the outer race on the bearing from the gearbox was achieved. Due to the small amount of training data the automatic solutions were only tested on the public data sets. Isolation performance of correct bearing and fault mode among multiplebearings were investigated. One of the best trade offs achieved was 76.39 % fault detection rate with 8.33 % false alarm rate. Another was 54.86 % fault detection rate with 0 % false alarm rate

Oceanic surface water isotopic compositions calibrated data from POLARSTERN cruise PS97 (ANT-XXXI/3)

Isotopic measurements of seawater sampled on-board Polarstern research vesse

Biogeochemical proxies and diatoms in surface sediments across the Drake Passage reflect oceanic domains and frontal systems in the region

The Antarctic Circumpolar Current is the world's largest current system connecting all major ocean basins of the global ocean. Its flow, driven by strong westerly winds, is constricted to its narrowest extent in the Drake Passage, located between South America and the Antarctic Peninsula. Due to the remoteness of the area, harsh weather conditions and strong bottom currents, sediment recovery is difficult and data coverage is still inadequate. Here, we report on the composition of 51 surface sediments collected during the R/V Polarstern PS97 expedition (Februaryâ-April 2016) across the western and central Drake Passage, from the Chilean/Argentinian continental margin to the South Shetland Islands and the Bransfield Strait (water depth: ∼100–4000 m). We studied microfossils (diatoms), bulk sediment composition and geochemical proxies (biogenic opal, organic carbon, calcium carbonate, carbon and nitrogen stable isotopes, sterols and photosynthetic pigments), and evaluated how they respond to, and reflect oceanic domains and polar to subpolar frontal systems in this region. Our multi-proxy approach shows a strong relationship between the composition of surface sediments and ocean productivity, terrigenous input, intensity of ocean currents, and ice proximity, clearly differentiating among 4 biogeographical zones. The Subantarctic Zone was characterized by warmer-water diatoms, high carbonate (>45) and low organic carbon contents (avg. 0.26), as well as low concentrations of pigments (avg. 1.75 μg/g) and sterols (avg. 0.90 μg/g). A general N-S transition from carbonate-rich to opal-rich sediment was observed at Drake Passage sites of the Polar Front and Permanently Open Ocean Zone. These sites were characterized by low organic carbon content (0.22), high relative abundances of heavily silicified diatoms (≥60% Fragilariopsis kerguelensis), and abundant foraminifera at shallower stations. Approaching the Antarctic Peninsula in the Transitional Zone, an increase in the concentrations of pigments and sterols (avg. 2.57 μg/g and 1.44 μg/g, respectively) and a strong decrease in carbonate content was observed. The seasonal Sea-Ice Zone in the southern section of the study area, had the highest contents of biogenic opal (avg. 14.6) and organic carbon (avg. 0.7), low carbonate contents (avg. 2.4), with the occurrence of sea-ice-related diatoms and sterols. In all zones, terrigenous input was detected, although carbon/nitrogen ratios and δ13Corg suggest a predominance of marine-derived organic matter; lower values of δ13Corg occurred south of the Polar Front. The new results presented here constitute a highly valuable reference dataset for the calibration of microfossil and geochemical proxies against observational data and provide a useful regional baseline for future paleo-research