Description: Networks of eddy-covariance (EC) towers such as AmeriFlux, ICOS and NEON are vital for providing the necessary distributed observations to address grand challenges in earth system and carbon cycle science. NEON, once fully operational with 47 tower sites, will represent the largest single-provider EC network globally. Its standardized observation and data processing suite is designed specifically for inter-site comparability and analysis of continental-scale ecological change, including rich contextual data such as airborne remote sensing and in-situ sampling bouts. First carbon cycle products become available in 2017, including data and software. These products strive to incorporate lessons-learned through collaborations with AmeriFlux, ICOS, LTER and others, to suggest novel systemic solutions, and to synergize ongoing research efforts across science communities. Here, we present an overview of the ongoing product release, alongside efforts to integrate and synergize with existing infrastructures, networks and communities. Near-real-time carbon cycle observations in “basic” and “expanded”, self-describing HDF5 formats become accessible from the NEON Data Portal, including an Application Program Interface. A pilot project is underway to investigate their subsequent ingest into the AmeriFlux processing pipeline, together with inclusion in FLUXNET globally harmonized data releases. Software for reproducible, extensible and portable data analysis and science operations management also becomes available. This includes the eddy4R family of R-packages underlying the carbon cycle data product generation, together with the ability to directly participate in open development via GitHub version control and Dockerhub image hosting. In addition, templates for science operations management include a web-based field maintenance application and a graphical user interface to simplify problem tracking and resolution along the entire data chain. We hope that this first release of NEON carbon cycle products can initiate further collaboration and synergies in challenge areas, and would appreciate input and discussion on continued development.

Description: Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2  =  1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time.

Description: Networks of eddy-covariance (EC) towers such as AmeriFlux, ICOS and NEON are vital for providing the necessary distributed observations to address interactions at the soil-vegetation-atmosphere interface. NEON, close to full operation with 47 tower sites, will represent the largest single-provider EC network globally. Its standardized observation and data processing suite is designed specifically for inter-site comparability and analysis of feedbacks across multiple spatial and temporal scales. Furthermore, NEON coordinates EC with rich contextual observations such as airborne remote sensing and in-situ sampling bouts. In January 2018 NEON enters its operational phase, and EC data products, software and services become fully available to the science community at large. These resources strive to incorporate lessons-learned through collaborations with AmeriFlux, ICOS, LTER and others, to suggest novel systemic solutions, and to synergize ongoing research efforts across science communities. Here, we present an overview of the ongoing product release, alongside efforts to integrate and collaborate with existing infrastructures, networks and communities. Near-real-time heat, water and carbon cycle observations in “basic” and “expanded”, self-describing HDF5 formats become accessible from the NEON Data Portal, including an Application Program Interface. Subsequently, they are ingested into the AmeriFlux processing pipeline, together with inclusion in FLUXNET globally harmonized data releases. Software for reproducible, extensible and portable data analysis and science operations management also becomes available. This includes the eddy4R family of R-packages underlying the data product generation, together with the ability to directly participate in open development via GitHub version control and DockerHub image hosting. In addition, templates for science operations management include a web-based field maintenance application and a graphical user interface to simplify problem tracking and resolution along the entire data chain. We hope that this presentation can initiate further collaboration and synergies in challenge areas, and would appreciate input and discussion on continued development. Plain Language Summary For a sustained period of time the eddy-covariance and boundary layer communities have invested technical and scientific expertise into the construction of the National Ecological Observatory Network (NEON). In January 2018 NEON enters its operational phase, and the time has come for our communities to reap the first fruits of their efforts! This presentation intends to create awareness of the resources that become available to our communities: interoperable flux data products, software and assignable asset services. We focus on how these resources will permit to elucidate interactions at the soil-vegetation-atmosphere interface for decades to come: continuous eddy-covariance observations of the surface-atmosphere exchange are tightly coordinated with rich contextual data such as airborne remote sensing and in-situ sampling bouts. In this way new investigative dimensions are provided to capture land-atmosphere feedbacks across multiple spatial and temporal scales.

Description: Water, Vol. 10, Pages 40: Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai Water doi: 10.3390/w10010040 Authors: Qin Jiang Weiyue Li Jiahong Wen Can Qiu Weiwei Sun Qilin Fang Ming Xu Jianguo Tan Satellite-based rainfall products have extensive applications in global change studies, but they are known to contain deviations that require comprehensive verification at different scales. In this paper, we evaluated the accuracies of two high-resolution satellite-based rainfall products: the Tropical Rainfall Measurement Mission (TRMM) rainfall product 3B42V7 and the Climate Prediction Center morphing (CMORPH) technique from January 2010 to December 2011 in Shanghai, by using categorical metrics (Probability of Detection, False Alarm Ratio, and Critical Success Index) and statistical indicators (Mean Absolute Error, Root Mean Square Error, Relative Bias, and Correlation Coefficient). Our findings show that, firstly, CMORPH data has a higher accuracy than 3B42V7 at the daily scale, but it underestimates the occurrence frequency of daily rainfall for some intensity ranges. Most errors of the two products are distributed between −10 and 10 mm/day. Second, at the monthly scale, the total accuracy of 3B42V7 is higher than CMORPH in terms of the value of the Correlation Coefficient (CC) and Relative Bias (RB). Finally, CMORPH brings about daily rainfall detection results from categorical metrics computation better than 3B42V7. Generally, the two satellite-based rainfall products show a high correlation with rain gauge data in Shanghai, particularly in spring and winter. Unfortunately, in summer, both of them do not perform well in detecting the short-duration heavy rainfall events. Overall, the relatively poor data accuracy has limited their further applications in Shanghai and similar urban areas.

Description: PARK2 inhibits osteosarcoma cell growth through the JAK2/STAT3/VEGF signaling pathway 〈i〉PARK2〈/i〉 inhibits osteosarcoma cell growth through the JAK2/STAT3/VEGF signaling pathway, Published online: 07 March 2018; doi:10.1038/s41419-018-0401-8 PARK2 inhibits osteosarcoma cell growth through the JAK2/STAT3/VEGF signaling pathway

Description: Shanxi province of China is threatened by the water shortage crisis. It is an important means to solve the water shortage problem by rationally water utilization planning and controlling. Using the structural decomposition analysis based on input-output table, the driving factors and driving forces of water consumption in Shanxi is researched, especially the effect of economic structure optimization. On the basis of the input-output table of Shanxi in 2002, 2007 and 2012, a comparable price water input-output model was established in combination with the water use data. According to the study, the improvement of water use efficiency has been the main driving force for reducing water consumption. The change in gross final demand has always been the main driving force for increasing water consumption. The adjustment of manufacturing industry structure, the secondary industry structure, the three industrial structure and the final demand structure have different impacts on water co...

Description: Deletion of TMEM268 inhibits growth of gastric cancer cells by downregulating the ITGB4 signaling pathway Deletion of 〈i〉TMEM268〈/i〉 inhibits growth of gastric cancer cells by downregulating the ITGB4 signaling pathway, Published online: 25 October 2018; doi:10.1038/s41418-018-0223-3 Deletion of TMEM268 inhibits growth of gastric cancer cells by downregulating the ITGB4 signaling pathway