Human germ line gene editing: why comparative, cross-national studies on public viewpoints are important

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Air-water exchange and distribution pattern of organochlorine pesticides in the atmosphere and surface water of the open Pacific ocean

Surface seawater and lower atmosphere gas samples were collected simultaneously between 18°N and 40°S in the open Pacific Ocean in 2006–2007. Samples were analyzed for organochlorine pesticides (OCPs) to assess their distribution patterns, the role of ocean in the long-range transport (LRT), and the air-water exchange directions in the open Pacific Ocean. Such open ocean studies can yield useful information such as establishing temporal and spatial trends and assessing primary vs secondary emissions of legacy OCPs. Target compounds included hexachlorocyclohexanes (HCHs), dichlorodiphenyltrichloroethanes (DDTs) and its derivatives, and chlordane compounds. Concentrations for α-HCH, γ-HCH, trans-chlordane (TC), and cis-chlordane (CC) were higher in the Northern Hemisphere (NH) than the Southern Hemisphere (SH) in both gaseous and dissolved phases, while the distribution patterns of DDTs and heptachlor exo-epoxide (HEPX) showed a reversed pattern. In the N Pacific, concentrations of α-HCH and γ-HCH in the present work were lower by 63 and 16 times than those observed in 1989–1990. The distribution patterns of DDT suggested there was usage in the SH around 2006. Calculated fugacity ratios suggested that γ-HCH was volatilizing from surface water to the atmosphere, and the air-water exchange fluxes were 0.3–11.1 ng m−2 day−1. This is the first field study that reported the open Pacific Ocean has become the secondary source for γ-HCH and implied that ocean could affect LRT of OCPs by supplying these compounds via air-sea exchange

Shift invariant sparse coding ensemble and its application in rolling bearing fault diagnosis

This paper proposes an automatic diagnostic scheme without manual feature extraction or signal pre-processing. It directly handles the original data from sensors and determines the condition of the rolling bearing. With proper application of the new technique of shift invariant sparse coding (SISC), it is much easier to recognize the fault. Yet, this SISC, though being a powerful machine learning algorithm to train and test the original signals, is quite demanding computationally. Therefore, this paper proposes a highly efficient SISC which has been proved by experiments to be capable of representing signals better and making converges faster. For better performance, the AdaBoost algorithm is also combined with SISC classifier. Validated by the fault diagnosis of bearings and compared with other methods, this algorithm has higher accuracy rate and is more robust to load as well as to certain variation of speed

The seasonal cycle and break-up of landfast sea ice along the northwest coast of Kotelny Island, East Siberian Sea

Arctic landfast sea ice (LFSI) represents an important quasi-stationary coastal zone. Its evolution is determined by the regional climate and bathymetry. This study investigated the seasonal cycle and interannual variations of LFSI along the northwest coast of Kotelny Island. Initial freezing, rapid ice formation, stable and decay stages were identified in the seasonal cycle based on application of the visual inspection approach (VIA) to MODIS/Envisat imagery and results from a thermodynamic snow/ice model. The modeled annual maximum ice thickness in 1995-2014 was 2.02 +/- 0.12 m showing a trend of -0.13 m decade(-1). Shortened ice season length (-22 d decade(-1)) from model results associated with substantial spring (2.3 degrees C decade(-1)) and fall (1.9 degrees C decade(-1)) warming. LFSI break-up resulted from combined fracturing and melting, and the local spatiotemporal patterns of break-up were associated with the irregular bathymetry. Melting dominated the LFSI break-up in the nearshore sheltered area, and the ice thickness decreased to an average of 0.50 m before the LFSI disappeared. For the LFSI adjacent to drift ice, fracturing was the dominant process and the average ice thickness was 1.56 m at the occurrence of the fracturing. The LFSI stages detected by VIA were supported by the model results.Peer reviewe

Resolving Fine-Scale Surface Features on Polar Sea Ice: A First Assessment of UAS Photogrammetry Without Ground Control

Mapping landfast sea ice at a fine spatial scale is not only meaningful for geophysical study, but is also of benefit for providing information about human activities upon it. The combination of unmanned aerial systems (UAS) with structure from motion (SfM) methods have already revolutionized the current close-range Earth observation paradigm. To test their feasibility in characterizing the properties and dynamics of fast ice, three flights were carried out in the 2016–2017 austral summer during the 33rd Chinese National Antarctic Expedition (CHINARE), focusing on the area of the Prydz Bay in East Antarctica. Three-dimensional models and orthomosaics from three sorties were constructed from a total of 205 photos using Agisoft PhotoScan software. Logistical challenges presented by the terrain precluded the deployment of a dedicated ground control network; however, it was still possible to indirectly assess the performance of the photogrammetric products through an analysis of the statistics of the matching network, bundle adjustment, and Monte-Carlo simulation. Our results show that the matching networks are quite strong, given a sufficient number of feature points (mostly > 20,000) or valid matches (mostly > 1000). The largest contribution to the total error using our direct georeferencing approach is attributed to inaccuracies in the onboard position and orientation system (POS) records, especially in the vehicle height and yaw angle. On one hand, the 3D precision map reveals that planimetric precision is usually about one-third of the vertical estimate (typically 20 cm in the network centre). On the other hand, shape-only errors account for less than 5% for the X and Y dimensions and 20% for the Z dimension. To further illustrate the UAS’s capability, six representative surface features are selected and interpreted by sea ice experts. Finally, we offer pragmatic suggestions and guidelines for planning future UAS-SfM surveys without the use of ground control. The work represents a pioneering attempt to comprehensively assess UAS-SfM survey capability in fast ice environments, and could serve as a reference for future improvements

Effective microorganisms input efficiently improves the vegetation and microbial community of degraded alpine grassland

Soil beneficial microorganism deficiency in the degraded grasslands have emerged as the major factors negatively impacting soil quality and vegetation productivity. EM (effective microorganisms) has been regarded as a good ameliorant in improving microbial communities and restoring degraded soil of agricultural systems. However, knowledge was inadequate regarding the effects of adding EM on the degraded alpine grassland. Four levels of EM addition (0, 150, 200, 250 mL m–2) were conducted to investigate the effects of EM addition on soil properties and microorganisms of degraded alpine grassland. The addition of EM increased aboveground biomass, soil organic carbon, total nitrogen, available phosphorus, and microbial biomass, but decreased soil electric conductivity. Meanwhile, the relative biomasses of gram-negative bacteria decreased, while the ectomycorrhizal fungi and arbuscular mycorrhizal fungi increased after EM addition. The relationship between microbial communities and environmental factors has been changed. The restore effect of EM increased with the increase of addition time. These results indicated that EM addition could be a good practice to restore the health of the degraded alpine grassland ecosystem