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The coarseModerate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product (spatial resolution: 3 km) retrieved by the dark-target algorithm always generates the missing values when being adopted to estimate the ground-level PM2.5 concentrations. In this study, we developed a two-stage random forest using MODIS 3-km AOD to obtain the PM2.5 concentrations with full coverage in a contiguous coastal developed region, i.e., Yangtze River delta--Fujian--Pearl River delta (YRD--FJ--PRD) region of China. A first-stage random forest--integrated six meteorological fields was employed to predict the missing values of AOD product, and the combined AOD (i.e., random forest--derived AOD and MODIS 3-km AOD) incorporated with other ancillary variables were developed for predicting PM2.5 concentrations within a second-stage random forest model. The results showed that the first-stage random forest could explain 94% of the AOD variability over YRD--FJ--PRD region, and we achieved a site-based cross validation (CV) R² of 0.87 and a time-based CV R² of 0.85. The full-coverage PM2.5 concentrations illustrated a spatial pattern with annual-mean PM2.5 of 46, 40, and 35 µg m-3 in YRD, PRD, and FJ, respectively, sharing the same trend with previous studies. Our results indicated that the proposed two-stage random forest model could be effectively used for PM2.5 estimation in different areas. [ABSTRACT FROM AUTHOR]

A study on the use of a machine learning algorithm for the level 1 trigger decision in the Jiangmen Underground Neutrino Observatory (JUNO) experiment is presented. JUNO is a medium baseline neutrino experiment under construction in China, with the main goal of determining the neutrino mass hierarchy. A large liquid scintillator (LS) volume will detect the electron antineutrinos issued from nuclear reactors. The LS detector is instrumented by around 20 000 large photomultiplier tubes (PMTs). The hit information from each PMT will be collected into a central trigger unit for the level 1 trigger decision. The current trigger algorithm used to select a neutrino signal event is based on a fast vertex reconstruction. We propose to study an alternative level 1 (L1) trigger in order to achieve a similar performance as the vertex fitting trigger but with fewer logic resources by using a firmware implemented machine learning model at the L1 trigger level. We treat the trigger decision as a classification problem and train a multilayer perceptron (MLP) model to distinguish the signal events with energy higher than a certain threshold from noise events. We use JUNO software to generate datasets that include 100k physics events with noise and 100k pure noise events coming from PMT dark noise. For events with energy higher than 100 keV, the L1 trigger based on the converged MLP model can achieve an efficiency of higher than 99%. After the training performed on simulations, we successfully implemented the trained model into a Kintex 7 field-programmable gate array (FPGA). We present the technical details of the neural network development and training, as well as its implementation in the hardware with the FPGA programming. Finally, the performance of the L1 trigger MLP implementation is discussed. [ABSTRACT FROM AUTHOR]

Except for its known aspects of positioning, navigation, and timing (PNT), the Global Navigation Satellite System (GNSS) has extended its application to the rainfall forecasting. GNSS-derived zenith total delay (ZTD) or precipitable water vapor (PWV) has been used as a single factor to predict the occurrence of rainfall; however, the rainfall is highly correlated with myriad atmospheric parameters, which cannot be perfectly reflected by a single predictor. In this article, an improved rainfall forecasting model (IRFM) is proposed to forecast the rainfall. The IRFM considers five predictors: monthly PWV value, seasonal PWV/ZTD variations, and their first derivatives: it can forecast rainfall using a single predicator or an arbitrary combination of those predicators. The merit of IRFM is reducing the false forecasted rainfall (FFR) events and missed detected rainfall (MDR) events as much as possible while guaranteeing the true detected rainfall (TDR) events. An optimized selecting principle of predictors’ threshold has been determined using the percentile method. The test experiment has been performed using five GNSS stations derived from continuously operating reference system (CORS) network of Zhejiang province, China. The analysis reveals that the IRFM considering five predictors provides a better performance than that only using a single predictor or a combination of arbitrary predictors. The statistical result shows the average TDR value of more than 95%, FFR value of less than 30%, and MDR of less than 5%, respectively. Compared to the existing rainfall forecasting methods using ZTD or PWV, the IRFM reduces the FFR and MDR, respectively, with the lowest values, while the TDR value is the highest. [ABSTRACT FROM AUTHOR]

Objectives: The continuous emergence of ceftriaxone-resistant Neisseria gonorrhoeae strains threatens the effectiveness of current treatment regimens for gonorrhoea. The objective of the present study was to characterize three ceftriaxone-resistant N. gonorrhoeae strains with a novel mosaic penA allele isolated in China.Methods: Three ceftriaxone-resistant Neisseria gonorrhoeae strains (GC150, GC161 and GC208) isolated in 2017 were characterized by N. gonorrhoeae multiantigen sequence typing (NG-MAST), MLST and N. gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR). Recombination analyses were performed using the SimPlot software.Results: Three strains had the same antibiotic resistance profiles, with resistance to ceftriaxone (MIC 0.5 mg/L), ciprofloxacin (MIC 8.0 mg/L), penicillin (MIC 2.0 mg/L) and tetracycline (MIC 2.0-8.0 mg/L). STs were assigned as MLST7360, NG-MAST14292 and NG-STAR1611/NG-STAR1612. The penA gene of these three strains differed from previous ceftriaxone-resistant gonococcal strains and harboured a novel mosaic allele (penA-121.001). Like N. gonorrhoeae FC428, a widely disseminated ceftriaxone-resistant strain that was initially described in Japan in 2015, all strains also possessed substitutions A311V and T483S in PBP2, which are associated with resistance to ceftriaxone. Potential recombination events were detected in penA between N. gonorrhoeae strain FC428 and commensal Neisseria species. Our results provide further evidence that the commensal Neisseria species (Neisseria cinerea and Neisseria perflava) can serve as a reservoir of ceftriaxone resistance-mediating penA sequences in clinical gonococcal strains.Conclusions: The emergence of such strains may be the result of the interspecies recombination of penA genes between N. gonorrhoeae strain FC428 and commensal Neisseria species. [ABSTRACT FROM AUTHOR]

The emergence of Lethal Autonomous Weapon Systems (LAWS) offers a comparatively low adoption-cost strategy to emerging great powers that would allow them to offset the conventional military advantage enjoyed by their rivals, which threatens the established global balance of power. This article critically analyses the role of China and the United States in the development of the "hardware" and "software" components of LAWS, concluding that, while the demonstration point has not yet been reached, the incubation of this emerging revolution in military affairs has already begun to have a geopolitical impact. [ABSTRACT FROM AUTHOR]

This article examines the current trend toward solving issues of procurement and processing of publicly disclosed pollution source data in China, where this data is characterized by heterogeneity and lack of standardization. Through ethnography and software analysis, the article examines the hidden labor entailed in automation using the case study of a Chinese e-NGO. We identify the bulk of this labor in "datascape navigation", or the practices needed to locate, acquire and process the desired information within the infrastructure enabling the circulation of the data. The aspects of this labor are examined in relation to two data flows: enterprise environmental supervision records and information about real-time emissions. We identify several forms of unpredicted human and non-human labor entailed by both unsuccessful and successful automation attempts. We conclude that the labor involved by software automation of environmental data procurement and processing can critically impact environmental disclosure timing and quality. [ABSTRACT FROM AUTHOR]

Examining the territorial and logistical factors surrounding the leasing of the Greek port of Piraeus to a subsidiary of the Chinese state-owned enterprise COSCO, this paper responds to calls to investigate variations in experiences of precarity. The article is based on research conducted in 2014 when the container processing area at Piraeus was divided between two terminals: the first run by the Piraeus Port Authority (OLP) and the second run by COSCO's subsidiary Piraeus Container Terminals (PCT). By contrasting the threatened unionized labour regime at OLP with the highly precarious labour conditions at PCT, the paper asks how the operative dimensions of capital condition precarity's intensification and spread. In this light, precarity emerges not simply as a form of labour insecurity or an unevenly shared condition of human vulnerability but as a relational nexus that links questions of political economy to matters of subjectivity, space, power, and governance. [ABSTRACT FROM AUTHOR]

Significant efforts towards environmental transparency have been made by the Chinese government since 2008. This paper focuses on the technical decisions shaping a database of official pollution information built and operated by a Chinese NGO known as the Institute of Public and Environmental Affairs (IPE). Issues of standardization, power distribution and institutional fragmentation are discussed. The paper illustrates a case of NGOs integrating enforcement capabilities as data centres amidst the growing reliance on processes of informational governance of environmental issues. [ABSTRACT FROM PUBLISHER]

Seafloor observatories enable long-term, continuous, real-time, weather-independent, and multidisciplinary scientific observation and research that will promise major breakthroughs in ocean sciences. China has started to establish a seafloor observation system in the East China Sea (ECSSOS), and the purpose of this paper is to describe the remote control for ECSSOS. Technological development in system architecture and remote communication was first performed in this paper. Based on this work, an overall framework for the remote control solution for ECSSOS was developed, adopting a client-server architecture containing three components, that is, a control center, a shore station, and observatory facilities, as well as two strands of information flow, that is, flow of observation data and flow of control commands. To implement the present solution, operational data flow and the core module were further designed and the corresponding remote control subsystem for ECSSOS was developed against all design specifications. This backbone system has been put into operation in China's first seafloor observatory in 2009, and in this paper the practical performance is evaluated addressing both the general descriptions and results from case studies. Given the successful trial in the Xiaoqushan seafloor observatory, the remote control solution proposed in this paper could be a useful reference implementation to the following construction phases of ECSSOS. [ABSTRACT FROM AUTHOR]

To assess the prevalence of plagiarism in manuscripts submitted for publication in the Croatian Medical Journal (CMJ). All manuscripts submitted in 2009-2010 were analyzed using plagiarism detection software: eTBLAST, CrossCheck, and WCopyfind. Plagiarism was suspected in manuscripts with more than 10% of the text derived from other sources. These manuscripts were checked against the Déjà vu database and manually verified by investigators. Of 754 submitted manuscripts, 105 (14%) were identified by the software as suspicious of plagiarism. Manual verification confirmed that 85 (11%) manuscripts were plagiarized: 63 (8%) were true plagiarism and 22 (3%) were self-plagiarism. Plagiarized manuscripts were mostly submitted from China (21%), Croatia (14%), and Turkey (19%). There was no significant difference in the text similarity rate between plagiarized and self-plagiarized manuscripts (25% [95% CI 22-27%] vs. 28% [95% CI 20-33%]; U = 645.50; P = 0.634). Differences in text similarity rate were found between various sections of self-plagiarized manuscripts (H = 12.65, P = 0.013). The plagiarism rate in the Materials and Methods (61% (95% CI 41-68%) was higher than in the Results (23% [95% CI 17-36%], U = 33.50; P = 0.009) or Discussion (25.5 [95% CI 15-35%]; U = 57.50; P < 0.001) sections. Three authors were identified in the Déjà vu database. Plagiarism detection software combined with manual verification may be used to detect plagiarized manuscripts and prevent their publication. The prevalence of plagiarized manuscripts submitted to the CMJ, a journal dedicated to promoting research integrity, was 11% in the 2-year period 2009-2010. [ABSTRACT FROM AUTHOR]

Background Metabolic rearrangement has been shown to be an important characteristic for stomach adenocarcinomas. Here we aimed to improve our understanding of the tumorigenesis of gastric cancer by means of gene and protein expression profile analysis with a focus on metabolic genes and pathways. Methods Array-based gene expression profiling of fresh frozen cancer tissues and adjacent normal tissues were obtained from 8 patients with gastric cancer at early stage by using Affymetrix oligonucleotide microarray. Assays targeted 179 unique genes related to cancer metabolism. The raw expression data were normalized using nSolver Analysis Software 3.0 and a dataset of gene expression ratios for GC vs. controls was generated. The p values were calculated using a paired t-test, and the threshold for up- and down-regulated genes was set at p value < 0.05. The protein expression of the dysregualted genes were detected by immunohistochemistry (IHC) in the formalin fixed paraffin embedded tissue blocks. The signal was quantified by the Allred score system which represented the estimated intensity and proportion of positive-staining cells. Results Our microarray results showed increased expression of 20 metabolic genes and decreased expression of 6 metabolic genes in all cases of gastric cancer at early stage. Besides of the undetected NOX4, the protein levels of all the others dysregualted genes, detected by IHC, showed consistently results. Half of all dysregulated genes (AKT2, EGLN3, G6PD, GLS, HIF1A, HK2, HRAS, MAP2K1, NTRK3, PGK1, PLCG1, RET and RPS6KB1) are implicated in Carbon Metabolism, a pivotal metabolic approach involving in nucleic acid biosynthesis. Five genes (ARNT, EGLN1, EGLN3, HIF1A and NOX4) are molecules implicated in hypoxia signaling. Besides, the upregulated HIF1A is a cancer metabolism driver, which means that HIF1A may induce the oncogenesis of gastric cancer. Conclusions The gastric mucosa in gastric cancer at early stage is characterized by dysregulated expression of a limited repertoire of metabolic genes. The nature of the corresponding metabolic rearrangement and pathways may help guide further investigations into its etiology. Legal entity responsible for the study Fudan University Shanghai Cancer Center. Funding National Human Genetic Resources Sharing Service Platform (2005DKA21300), National Natural Science Foundation of China (81602078),. Disclosure All authors have declared no conflicts of interest. [ABSTRACT FROM AUTHOR]

During the 1970s and early 1980s China tried to develop a full line of computer hardware and software incorporating indigenous technology. [ABSTRACT FROM PUBLISHER]