879 resultados para eresearch and data management


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Soils of the tropics are prone to a decrease in quality after conversion from native forest (FO) to a conventional tillage system (CT). However, the adoption of no-tillage (NT) and complex crop rotations may improve soil structural quality. Thus, the aim of this study was to evaluate the physical properties of an Oxisol under FO, CT, and three summer crop sequences in NT: continuous corn (NTcc), continuous soybean (NTcs), and a soybean/corn rotation (NTscr). Both NT and CT decreased soil organic carbon (SOC) content, SOC stock, water stable aggregates (WSA), geometric mean diameter (GMD), soil total porosity (TP), macroporosity (MA), and the least limiting water range (LLWR). However they increased soil bulk density (BD) and tensile strength (TS) of the aggregates when compared to soil under FO. Soil under NT had higher WSA, GMD, BD, TS and microporosty, but lower TP and MA than soil under CT. Soil under FO did not attain critical values for the LLWR, but the lower limit of the LLWR in soils under CT and NT was resistance to penetration (RP) for all values of BD, while the upper limit of field capacity was air-filled porosity for BD values greater than 1.46 (CT), 1.40 (NTscr), 1.42 (NTcc), and 1.41 (NTcs) kg dm-3. Soil under NTcc and NTcs decreased RP even with the increase in BD because of the formation of biopores. Furthermore, higher critical BD was verified under NTcc (1.62 kg dm-3) and NTcs (1.57 kg dm-3) compared to NTscr and CT (1.53 kg dm-3).

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We study theoretical and empirical aspects of the mean exit time (MET) of financial time series. The theoretical modeling is done within the framework of continuous time random walk. We empirically verify that the mean exit time follows a quadratic scaling law and it has associated a prefactor which is specific to the analyzed stock. We perform a series of statistical tests to determine which kind of correlation are responsible for this specificity. The main contribution is associated with the autocorrelation property of stock returns. We introduce and solve analytically both two-state and three-state Markov chain models. The analytical results obtained with the two-state Markov chain model allows us to obtain a data collapse of the 20 measured MET profiles in a single master curve.

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Soils constructed after mining often have low carbon (C) stocks and low quality of organic matter (OM). Cover crops are decisive for the recovery process of these stocks, improving the quality of constructed soils. Therefore, the goal of this study was to evaluate the effect of cover crops on total organic C (TOC) stocks, C distribution in physical fractions of OM and the C management index (CMI) of a soil constructed after coal mining. The experiment was initiated in 2003 with six treatments: Hemarthria altissima (T1), Paspalum notatum (T2), Cynodon dactylon (T3), Urochloa brizantha (T4), bare constructed soil (T5), and natural soil (T6). Soil samples were collected in 2009 from the 0.00-0.03 m layer, and the TOC and C stocks in the physical particle size fractions (carbon in the coarse fraction - CCF, and mineral-associated carbon - MAC) and density fractions (free light fraction - FLF; occluded light fraction - OLF, and heavy fraction - HF) of OM were determined. The CMI components: carbon pool index (CPI), lability (L) and lability index (LI) were estimated by both fractionation methods. No differences were observed between TOC, CCF and MAC stocks. The lowest C stocks in FLF and OLF fractions were presented by T2, 0.86 and 0.61 Mg ha-1, respectively. The values of TOC stock, C stock in physical fractions and CMI were intermediate, greater than T5 and lower than T6 in all treatments, indicating the partial recovery of soil quality. As a result of the better adaptation of the species Hemarthria and Brizantha, resulting in greater accumulation of labile organic material, the CPI, L, LI and CMI values were higher in these treatments, suggesting a greater potential of these species for recovery of constructed soils.

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In response to the mandate on Load and Resistance Factor Design (LRFD) implementations by the Federal Highway Administration (FHWA) on all new bridge projects initiated after October 1, 2007, the Iowa Highway Research Board (IHRB) sponsored these research projects to develop regional LRFD recommendations. The LRFD development was performed using the Iowa Department of Transportation (DOT) Pile Load Test database (PILOT). To increase the data points for LRFD development, develop LRFD recommendations for dynamic methods, and validate the results ofLRFD calibration, 10 full-scale field tests on the most commonly used steel H-piles (e.g., HP 10 x 42) were conducted throughout Iowa. Detailed in situ soil investigations were carried out, push-in pressure cells were installed, and laboratory soil tests were performed. Pile responses during driving, at the end of driving (EOD), and at re-strikes were monitored using the Pile Driving Analyzer (PDA), following with the CAse Pile Wave Analysis Program (CAPWAP) analysis. The hammer blow counts were recorded for Wave Equation Analysis Program (WEAP) and dynamic formulas. Static load tests (SLTs) were performed and the pile capacities were determined based on the Davisson’s criteria. The extensive experimental research studies generated important data for analytical and computational investigations. The SLT measured loaddisplacements were compared with the simulated results obtained using a model of the TZPILE program and using the modified borehole shear test method. Two analytical pile setup quantification methods, in terms of soil properties, were developed and validated. A new calibration procedure was developed to incorporate pile setup into LRFD.

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Audit report on the Wireless E911 Emergency Communications Fund of the Iowa Homeland Security and Emergency Management Division of the Iowa Department of Public Defense for the year ended June 30, 2011

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Audit report on the Wireless E911 Emergency Communications Fund of the Iowa Homeland Security and Emergency Management Division of the Iowa Department of Public Defense for the year ended June 30, 2012

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This paper presents a process of mining research & development abstract databases to profile current status and to project potential developments for target technologies, The process is called "technology opportunities analysis." This article steps through the process using a sample data set of abstracts from the INSPEC database on the topic o "knowledge discovery and data mining." The paper offers a set of specific indicators suitable for mining such databases to understand innovation prospects. In illustrating the uses of such indicators, it offers some insights into the status of knowledge discovery research*.

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Agency Performance Report

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Agency Performance Report

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Agency Performance Report

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Agency Performance Report

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Agency Performance Report

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Agency Performance Report