Examining the Effects of Feedback Type and Goal Orientation on User Participation Performance in Citizen Science Projects

How to enhance user performance becomes a key issue in citizen science research. Providing feedback is regarded as an effective design principle to promote user experience and performance in many contexts. Yet, there is a lack of study on how to design feedback to improve user experience and performance in citizen science projects. Based on feedback intervention theory and achievement goal theory, we propose a research model to depict the influenceof feedback types(task, self-referential, social feedback)on user experiences (perceived enjoyment, perceived meaning, and self-expansion), which then impact participation performance. Wealsoinvestigate whether auser\u27s dispositionalgoalorientation(mastery or performance) moderates the effects offeedback typeson user experiences. We will conduct an online experiment to validate our research model.The findings will provide the groundwork for guidelines and strategies to enhance useperformancein citizen science projects

A scientometric analysis of e-participation research

Purpose - Due to the increasing demand for public services, as a new form of public governance, e-participation has emerged. Scholars from various disciplines have published plenty of research results on e-participation. This paper aims to reveal the research status frontiers directly by mapping knowledge domains. Design/methodology/approach - The authors take 1,322 articles on e-participation published in Web of Science from 2001 to 2017 as research object. They then run the information visualization software CiteSpace to drill deeper into the literature data. Findings - The study found that e-participation research has the obvious interdisciplinary feature; the author and institution cooperation networks with less internal cooperation are relatively sparse; the USA ranks first in the field of e-participation research, followed by the UK, with the other countries lagged behind; and e-participation through social media is gradually becoming the new research focus. Originality/value - Based on the objective data and information visualization technology, the research intuitively reveals the research status and development trend of e-participation

IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images

While numerous 3D reconstruction and novel-view synthesis methods allow for photorealistic rendering of a scene from multi-view images easily captured with consumer cameras, they bake illumination in their representations and fall short of supporting advanced applications like material editing, relighting, and virtual object insertion. The reconstruction of physically based material properties and lighting via inverse rendering promises to enable such applications. However, most inverse rendering techniques require high dynamic range (HDR) images as input, a setting that is inaccessible to most users. We present a method that recovers the physically based material properties and spatially-varying HDR lighting of a scene from multi-view, low-dynamic-range (LDR) images. We model the LDR image formation process in our inverse rendering pipeline and propose a novel optimization strategy for material, lighting, and a camera response model. We evaluate our approach with synthetic and real scenes compared to the state-of-the-art inverse rendering methods that take either LDR or HDR input. Our method outperforms existing methods taking LDR images as input, and allows for highly realistic relighting and object insertion.Comment: Project Website: https://irisldr.github.io

High mobility group box 1 promotes radioresistance in esophageal squamous cell carcinoma cell lines by modulating autophagy

Resistance to radiotherapy results in relapse and treatment failure in locally advanced esophageal squamous cell carcinoma (ESCC). High mobility group box 1 (HMGB1) is reported to be associated with the radioresistance in bladder and breast cancer. However, the role of HMGB1 in the radiotherapy response in ESCC has not been fully elucidated. Here, we investigated the role of HMGB1 to radioresistance in ESCC clinical samples and cell lines. We found that HMGB1 expression was associated with tumor recurrence after postoperative radiotherapy in locally advanced ESCC patients. HMGB1 knockdown in ESCC cells resulted in increased radiosensitivity both in vitro and in vivo. Autophagy level was found depressed in HMGB1 inhibition cells and activation of autophagy brought back cell's radioresistance. Our results demonstrate that HMGB1 activate autophagy and consequently promote radioresistance. HMGB1 may be used as a predictor of poor response to radiotherapy in ESCC patients. Our finding also highlights the importance of the utility of HMGB1 in ESCC radiosensitization.Peer reviewe

Productivity Growth in Chinese Medical Institutions during 2009–2018

China is the most populous nation and considerations of economic efficiency in the social sectors is important for maintaining the wellbeing of such a large population. This is especially true when gauging the performance of the healthcare sector treating the population. In this paper, we examine the total factor productivity (TFP) growth in Chinese medical institutions during the period 2009–2018, which experienced a systemic healthcare reform. In order to identify the contribution from each component of TFP indicators and from each provincial or regional medical institutions, a generalized decomposition of productivity gains is applied to analyze hospital operations based on an aggregate directional distance function (DDF). The results show that the annual average TFP growth rate in Chinese medical institutions is 1.87% that is mainly driven by technological progress (0.75%, per annum), while less contributed by technical efficiency change (0.65%, p.a.) and scale efficiency change (0.47%, p.a.). Disparities of provincial hospital performances are observed that may provide policy implications for decision makers

Examining the Effect of Interaction Content and Interaction Style on Volunteers’ Research Competence in Citizen Science Projects

Citizen science involves ordinary volunteers and uses their contributions to support scientific investigations. Besides its value for science, citizen science also has educational potential for volunteers. Interactions among involved parties (i.e., scientists and volunteers) are key to generating educational values for volunteers. We investigate how interaction characteristics, which are interaction content and interaction style, influence volunteers’ co-creation experiences and then af ect their research competence. We conduct a survey to collect data from volunteers in a continued citizen science project named the “China Health and Retirement Longitudinal Study.” Volunteers are recruited and trained to perform field data collection. The findings help guide the design and implementation of citizen science projects to generate more profound implications for improving public understanding of science

Survival benefit evaluation of radiotherapy in esophageal cancer patients aged 80 and older

Peer reviewe

Bioinformatic exploration of OLFML2B overexpression in gastric cancer base on multiple analyzing tools

Abstract Background Gastric cancer (GC) is one of the most commonly occuring gastrointestinal tumor types, and early diagnosis and operation have a notable effect on the prognosis of patients. Although certain markers, including HER2, VEGER-2, ERCC1 and Bcl-2, have been utilized in clinical practise to screen out new patients with GC, the results of using these markers remains poor. The role of olfactomedin-like 2B (OLFML2B) in GC, as a member of the olfactomedin domain-containing proteins family, is remain unclear. Methods In the present study, we assessed the expression of OLFML2B, including mRNA and protein level, by using The Cancer Genome Atlas (TCGA) database and 13 pairs of clinical samples between GC and NG tissues. The correlation between expression of OLFML2B and prognosis of GC was evaculated by the Kaplan-Meier plotter and OncoLnc online tools. In addition, mechanism analysis of OLFML2B in GC was explored thought bioinformatic tools, including cBioPortal and FunRich software. Results In our study, the mRNA expression of OLFML2B in GC both TCGA database and clinical samples was consistently revealed to be significantly higher compared with that in NG tissues (P < 0.0001 for TCGA database and P = 0.0034 for clinical samples), and high OLFML2B expression was found in 9 (69.23%) of 13 clinical GC by immunohistochemistry and was positively correlated with the depth of tumor invasion and clinical stage (TNM). In addition, the AUC for a ROC of 0.867 indicated a moderate diagnostic ability of OLFML2B for GC. Survival analysis from the Kaplan-Meier plotter (P = 2.6 × 10− 6) and OncoLnc (P = 0.00276) revealed that the high expression of OLFML2B was associated with a short overall survival. Futhermore, 5% (24/478) alterations of OLFML2B were identified from cBioPortal, and among them, missense mutation (14/478) was the primary type. The results from FunRich revealed that OLFML2B participated in mediating multiple biological processes including cell growth and maintenance, regulation of the cell cycle, apoptosis and cell communication through multiple signaling pathways including the M/G1 transition pathway, post-translational protein modification and DNA replication pre-initiation. Conclusions Taken together, it could be deduced that OLFML2B may act as an oncogene in the development of GC and the overexpression of OLFML2B in GC may be used as a novel diagnostic and prognostic target for GC