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In recent years, China's advanced light sources have entered a period of rapid construction and development. As modern X-ray detectors and data acquisition technologies advance, these facilities are expected to generate massive volumes of data annually, presenting significant challenges in data management and utilization. These challenges encompass data storage, metadata handling, data transfer and user data access. In response, the Data Organization Management Access Software (DOMAS) has been designed as a framework to address these issues. DOMAS encapsulates four fundamental modules of data management software, including metadata catalogue, metadata acquisition, data transfer and data service. For light source facilities, building a data management system only requires parameter configuration and minimal code development within DOMAS. This paper firstly discusses the development of advanced light sources in China and the associated demands and challenges in data management, prompting a reconsideration of data management software framework design. It then outlines the architecture of the framework, detailing its components and functions. Lastly, it highlights the application progress and effectiveness of DOMAS when deployed for the High Energy Photon Source (HEPS) and Beijing Synchrotron Radiation Facility (BSRF). [ABSTRACT FROM AUTHOR]

Background and Aims: The Rome Foundation Global Epidemiology Study (RFGES) assessed the prevalence, burden, and associated factors of Disorders of Gut–Brain Interaction (DGBI) in 33 countries around the world. Achieving worldwide sampling necessitated use of two different surveying methods: In‐person household interviews (9 countries) and Internet surveys (26 countries). Two countries, China and Turkey, were surveyed with both methods. This paper examines the differences in the survey results with the two methods, as well as likely reasons for those differences. Methods: The two RFGES survey methods are described in detail, and differences in DGBI findings summarized for household versus Internet surveys globally, and in more detail for China and Turkey. Logistic regression analysis was used to elucidate factors contributing to these differences. Results: Overall, DGBI were only half as prevalent when assessed with household vs Internet surveys. Similar patterns of methodology‐related DGBI differences were seen within both China and Turkey, but prevalence differences between the survey methods were dramatically larger in Turkey. No clear reasons for outcome differences by survey method were identified, although greater relative reduction in bowel and anorectal versus upper gastrointestinal disorders when household versus Internet surveying was used suggests an inhibiting influence of social sensitivity. Conclusions: The findings strongly indicate that besides affecting data quality, manpower needs and data collection time and costs, the choice of survey method is a substantial determinant of symptom reporting and DGBI prevalence outcomes. This has important implications for future DGBI research and epidemiological research more broadly. [ABSTRACT FROM AUTHOR]

Drawing on my accompanied returning‐home fieldwork in China with a dear friend, Yun, this paper critically reflects on the ideas of friendship in fieldwork and its enabling and enhancing role in managing safety concerns and negotiating data collection. The contribution is two‐fold. First, it advances current fieldwork scholarship in Humanities and Social Sciences that predominantly focuses on the researcher–informant friendship formed in the field by engaging with the companionship of pre‐existing friends. This diversifies our understandings of fieldwork friendship in individually, socially and culturally unsettling ways. Second, this study furthers ongoing conversations calling for greater visibility and support of different forms of accompanied fieldwork by focusing on the accompaniment of pre‐existing friends. Three potential directions are outlined to normalise the model of accompanied fieldwork in efforts to promote equality, diversity and inclusion (EDI) in geography fieldwork. [ABSTRACT FROM AUTHOR]

Understanding the contribution of aboveground dry matter (DM) production and harvest index (HI) to maize grain yield is essential to further improve grain yield to ensure future food growing requirements. In this study, we collected 548 sets of data of DM, HI, and grain yield from a multisite (40 sites) and multiyear (2009–2016) experiment conducted in major maize‐growing regions across China and 615 sets of data from 40 published papers distributed from 1988 to 2018 to assess the performance of DM, HI, and their contributions to grain yield. It was found that the average contribution rate of DM was 73.71%, which was much higher than those of HI (26.28%) across China. For the five different modern hybrids, the contribution rates of DM to grain yield (ranged from 71.36% to 89.10%) were also significantly higher than those of HI (ranged from 10.79% to 28.64%) on a large spatial scale. The significant differences in grain yields between cultivars were mainly due to the differences in HI. Among the four maize‐growing regions, the contribution rates of DM in both NW (57.34%) and NM (64.46%) were higher than those of HI (42.66% and 35.54%, respectively). In contrast, the contribution rates of HI in HM (52.67%) and SW (50.92%) were slightly higher than those of DM (47.33% and 49.08%, respectively). The interregional differences in grain yield were mainly attributed to the differences in DM between regions. Additionally, combining the data of this study and data collected from previous studies, we found that the increase in maize grain yield under lower yield levels (<15 Mg/ha) was mainly attributed to the increase in both DM and HI, while that under higher yield levels (>15 Mg/ha) was mainly dependent on the increase in DM. [ABSTRACT FROM AUTHOR]

A software maintenance process is important for reducing maintenance effort and for improving software quality. In recent years, the Lean-Kanban approach has been widely applied in software practice including software maintenance. This approach minimizes Work-in-Progress (WIP), which is the number of items that are worked on by the team at any given time, thus improving the maintenance process. In this paper, we describe our simulation studies, which show that the Lean-Kanban approach can indeed help reduce the average time needed to complete maintenance requests. We develop a process simulator that can simulate both existing maintenance processes that do not use a WIP limit and that adopt it. We perform two case studies using real maintenance data collected from a Microsoft project and from a Chinese software firm. The main results of our study are twofold. First, we demonstrate that it is possible to effectively model and simulate, using actors and events, a maintenance process where a flow of issues is processed through a sequence of activities, correctly reproducing key statistics of real data. Second, our results confirm that the WIP-limited process could be useful to increase the efficiency of software maintenance, as reported in previous industrial practices. [ABSTRACT FROM AUTHOR]

Please cite this paper as: Pepin et al. (2012) Multiannual patterns of influenza A transmission in Chinese live bird market systems. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750-2659.2012.00354.x. Background Avian influenza viruses (AIV) cause huge economic losses in poultry industries and pose a substantial threat to human health. However, predicting AIV epizootics and emergence in humans is confounded by insufficient empirical data on the ecology and dynamics of AIV in poultry systems. To address this gap, we quantified incidence patterns for 13 hemagglutinin subtypes of AIV using 6 years of surveillance data that were collected from ten different species of poultry and three different types of poultry holdings (contexts) - retail, wholesale, or farms. Methods We collected 42 646 samples in Shantou, China between 2000 and 2006. We screened samples for hemagglutinin subtypes 1-13 of AIV and Avian Paramyxovirus-type-1 (APMV-1) using monospecific antisera in hemagglutination inhibition tests. We analyzed the data to determine seasonality patterns, subtype-host, and subtype-subtype interactions as well as subtype bias in incidence in different contexts. Results H3, H6, H9, and APMV-1 were the most prevalent. No significant seasonality was found when all subtypes were considered together. For most AIV subtypes and APMV-1, there was subtype specificity for host, context, and coinfection partner. H5 showed the most generalized host usage pattern, followed by H9 and H6. Conclusion Subtype-specific patterns because of host, context, and other subtypes suggest that risk assessments that exclude these details are likely inaccurate. Surveillance should include longitudinal sampling of multiple host species in multiple contexts. Quantitative models of control strategies must consider multiple subtypes, hosts, and source contexts to assess the effectiveness of interventions. [ABSTRACT FROM AUTHOR]