235 research outputs found
Degradation of Cry1Ac Protein Within Transgenic Bacillus thuringiensis Rice Tissues Under Field and Laboratory Conditions
To clarify the environmental fate of the Cry1Ac protein from Bacillus thuringiensis subsp. kurstaki (Bt) contained in transgenic rice plant stubble after harvest, degradation was monitored under field conditions using an enzyme-linked immunosorbent assay. In stalks, Cry1Ac protein concentration decreased rapidly to 50% of the initial amount during the first month after harvest; subsequently, the degradation decreased gradually reaching 21.3% when the experiment was terminated after 7 mo. A similar degradation pattern of the Cry1Ac protein was observed in rice roots. However, when the temperature increased in April of the following spring, protein degradation resumed, and no protein could be detected by the end of the experiment. In addition, a laboratory experiment was conducted to study the persistence of Cry1Ac protein released from rice tissue in water and paddy soil. The protein released from leaves degraded rapidly in paddy soil under flooded conditions during the first 20 d and plateaued until the termination of this trial at 135 d, when 15.3% of the initial amount was still detectable. In water, the Cry1Ac protein degraded more slowly than in soil but never entered a relatively stable phase as in soil. The degradation rate of Cry1Ac protein was significantly faster in nonsterile water than in sterile water. These results indicate that the soil environment can increase the degradation of Bt protein contained in plant residues. Therefore, plowing a field immediately after harvest could be an effective method for decreasing the persistence of Bt protein in transgenic rice field
Detrital zircon geochronology and related evidence from clastic sediments in the Kyrenia Range, N Cyprus: Implications for the Mesozoic-Cenozoic erosional history and tectonics of southern Anatolia
Bis[μ-1,2-bisÂ(1H-imidazol-1-ylmethÂyl)benzene-κ2 N 3:N 3′]disilver(I) bisÂ(4-carbÂoxyÂnaphthalene-1-carboxylÂate) tetraÂhydrate
In the title compound, [Ag2(C14H14N4)2](C12H7O4)2·4H2O, the dinuclear dication has crystallographically imposed inversion symmetry. Each AgI ion is bicoordinated in a slightly distorted linear coordination geometry by the N atoms of two ligands, resulting in the formation of a 22-membered metallamacrocycle. In the dication, π–π interÂactions are observed between the imidazole rings, with centroid–centroid distances of 3.528 (3) Å and dihedral angles of 9.92 (9)°. The crystal structure is stabilized by interÂmolecular O—H⋯O hydrogen bonds and π–π interÂactions involving the benzene rings of adjacent dications, with centroid–centroid distances of 3.651 (2) Å
Neutron Energy Spectrum Measurements with a Compact Liquid Scintillation Detector on EAST
A neutron detector based on EJ301 liquid scintillator has been employed at
EAST to measure the neutron energy spectrum for D-D fusion plasma. The detector
was carefully characterized in different quasi-monoenergetic neutron fields
generated by a 4.5 MV Van de Graaff accelerator. In recent experimental
campaigns, due to the low neutron yield at EAST, a new shielding device was
designed and located as close as possible to the tokamak to enhance the count
rate of the spectrometer. The fluence of neutrons and gamma-rays was measured
with the liquid neutron spectrometer and was consistent with 3He proportional
counter and NaI (Tl) gamma-ray spectrometer measurements. Plasma ion
temperature values were deduced from the neutron spectrum in discharges with
lower hybrid wave injection and ion cyclotron resonance heating. Scattered
neutron spectra were simulated by the Monte Carlo transport Code, and they were
well verified by the pulse height measurements at low energies.Comment: 19 pages,10 figures, 1 tabl
A combined methodology for reconstructing source-to-sink basin evolution, exemplified by the Triassic Songpan–Ganzi basin, central China
Source-to-sink evolution of a basin is a key to understand sedimentary processes, especially in a complex regional orogenic setting. Detrital zircon populations can be traced from their primary sources to their depositional settings. The resulting interpretations are enhanced by calculation of the adjacent orogen's paleoaltimetry, which provides additional insights into paleogeography. In this study, we present a combined methodology which aims to reconstruct source-to-sink evolution by the analysis of detrital zircon age distribution in sandstones, together with the calculation of paleo-elevation of surrounding orogens based on the chemical compositions of coeval magmatic rocks. We test the method using detrital zircon U–Pb geochronological data sets from the Triassic Songpan–Ganzi basin in central China, combined with whole-rock geochemical data from intermediate-composition magmatic rocks in adjacent crustal blocks. Application of the combined methodology supports a syn-collisional basin model for the formation of the Triassic Songpan-Ganzi basin in preference to a continental back-arc basin. The clastic sediments, mainly deep-marine turbidites, accumulated in a remnant Paleotethyan Ocean that was surrounded by the converging North China Block, South China Block, East Kunlun Orogenic Belt and the Qiangtang Block. The North China Block and the North Qaidam Block were major proto-sources of detrital zircons to the basin, contributing on average 12 % and 15 %, respectively. Triassic magmatic rocks in the East Kunlun and Qiangtang regions were major sources of igneous zircons, up to 68 % for the former and up to 56 % for the latter. Despite being located at a calculated elevation of ca. 4000 m, the Qinling Orogenic Belt contributed only ca. <10 % of the zircons, mostly restricted to the eastern depocenter of the basin. In contrast, supply from the North Qiangtang Block, despite its calculated lower elevation (1000–3000 m), accounts for 2–10 % of the detrital zircons in the basin, suggesting high erosion rates of this block. The minimal supply of zircons from the South China Block, restricted to 3–6 % in the central and western depocenters, is inconsistent with the zircon abundances predicted in the alternative back-arc basin model of the Songpan–Ganzi basin
Cell Pluripotency Levels Associated with Imprinted Genes in Human
Pluripotent stem cells are exhibited similarly in the morphology, gene expression, growth properties, and epigenetic modification with embryonic stem cells (ESCs). However, it is still controversial that the pluripotency of induced pluripotent stem cell (iPSC) is much inferior to ESC, and the differentiation capacity of iPSC and ESC can also be separated by transcriptome and epigenetics. miRNAs, which act in posttranscriptional regulation of gene expression and are involved in many basic cellular processes, may reveal the answer. In this paper, we focused on identifying the hidden relationship between miRNAs and imprinted genes in cell pluripotency. Total miRNA expression patterns in iPSC and ES cells were comprehensively analysed and linked with human imprinted genes, which show a global picture of their potential function in pluripotent level. A new CPA4-KLF14 region which locates in chromosomal homologous segments (CHSs) within mammals and include both imprinted genes and significantly expressed miRNAs was first identified. Molecular network analysis showed genes interacted with imprinted genes closely and enriched in modules such as cancer, cell death and survival, and tumor morphology. This imprinted region may provide a new look for those who are interested in cell pluripotency of hiPSCs and hESCs
Drone-based Computer Vision-Enabled Vehicle Dynamic Mobility and Safety Performance Monitoring
This report documents the research activities to develop a drone-based computer vision-enabled vehicle dynamic safety performance monitoring in Rural, Isolated, Tribal, or Indigenous (RITI) communities. The acquisition of traffic system information, especially the vehicle speed and trajectory information, is of great significance to the study of the characteristics and management of the traffic system in RITI communities. The traditional method of relying on video analysis to obtain vehicle number and trajectory information has its application scenarios, but the common video source is often a camera fixed on a roadside device. In the videos obtained in this way, vehicles are likely to occlude each other, which seriously affects the accuracy of vehicle detection and the estimation of speed. Although there are methods to obtain high-view road video by means of aircraft and satellites, the corresponding cost will be high. Therefore, considering that drones can obtain high-definition video at a higher viewing angle, and the cost is relatively low, we decided to use drones to obtain road videos to complete vehicle detection. In order to overcome the shortcomings of traditional object detection methods when facing a large number of targets and complex scenes of RITI communities, our proposed method uses convolutional neural network (CNN) technology. We modified the YOLO v3 network structure and used a vehicle data set captured by drones for transfer learning, and finally trained a network that can detect and classify vehicles in videos captured by drones. A self-calibrated road boundary extraction method based on image sequences was used to extract road boundaries and filter vehicles to improve the detection accuracy of cars on the road. Using the results of neural network detection as input, we use video-based object tracking to complete the extraction of vehicle trajectory information for traffic safety improvements. Finally, the number of vehicles, speed and trajectory information of vehicles were calculated, and the average speed and density of the traffic flow were estimated on this basis. By analyzing the acquiesced data, we can estimate the traffic condition of the monitored area to predict possible crashes on the highways
Extracting Rural Crash Injury and Fatality Patterns Due to Changing Climates in RITI Communities Based on Enhanced Data Analysis and Visualization Tools (Phase I)
Traffic crashes cause considerable incapacitating injuries and losses in Rural, Isolated, Tribal, or Indigenous (RITI) communities. Compared to urban traffic crashes, those rural crashes, especially for those occurred in RITI communities, are heavily associated with factors such as speeding, low safety devices application (for instance, seatbelt), adverse weather conditions and lacking maintenance and repairers for road conditions, inferior lighting conditions, and so on. Therefore, there exists an urgent need to investigate the unique attributes associated with the RITI traffic crashes based on numerous approaches, such as statistical methods, and data-driven approaches. This project focused on extracting rural crash injury and fatality patterns due to changing climates in RITI communities based on enhanced data analysis and visualization tools. Three new interactive graphic tools were added to the Rural Crash Visualization Tool System (RCVTS), to enhance the visualization approach. A Bayesian vector auto-regression based data analysis approach was proposed to enable irregularly-spaced mixture-frequency traffic collision data interpretation with missing values. Moreover, a finite mixture random parameters model was formulated to explore driver injury severity patterns and causes in low visibility related single-vehicle crashes. The research findings are helpful for transportation agencies to develop cost-effective countermeasures to mitigate rural crash severities under extreme climate and weather conditions and minimize the rural crash risks and severities in the States of Alaska, Washington, Idaho, and Hawaii
Developing an Interactive Baseline Data Platform for Visualizing and Analyzing Rural Crash Characteristics in RITI Communities
This project focused on developing an interactive baseline crash data platform, termed as Rural Crash Visualization Tool System (RCVTS), to visualize and analyze rural crash characteristics in RITI communities. More than 975 thousand crash records were collected in the state of Alaska, Idaho, and Washington, from 2010 to 2016. Data fusion is applied to unify the collected data. In the proposed RCVTS platform, three main functions are defined: crash data visualization, data analysis, and data retrieval. Crash data visualization includes an on-street map based crash location tool and a graphic query tool. Data analysis involves a number of visualization approaches, including static charts— i.e., the scatter chart—the line chart, the area chart, the bar chart, and interactive graph— i.e., the sunburst chart. Users are allowed to generate customized analytical graphs by specifying the parameters and scale. The three types of authorized users are defined to download crash information in the data retrieval section following corresponding limitations. The proposed RCVTS was illustrated using a sample case with crash records of the State of Alaska. It showed that the proposed RCVTS functions well. Recommendations on future research are provided as well
- …