Museum in the Age of Digital Transformation

Transformational technologies have arrived to the traditional institutions accompanied with new promises and challenges. Nevertheless, little research exists to inform our understanding on the transformation undergoing in our aged old institutions. This short paper presents an in- depth case study at a world-renowned museum in China to develop understanding on the digital transformation of a traditional institution. Our preliminary analysis sheds light on the duality of digital transformation through the theoretical lens of technology affordances. On one hand, digital transformation affords unprecedented possibilities for the revitalization of an aged old institution. On the other hand, digital transformation also generates uncertainties and tensions. Our analysis suggests that most traditional institutions are not well-endowed to quickly adapt to the changing needs in the digital environment. These preliminary findings unveil the intricacies of digital transformation in traditional institutions and serve to inform further theorizing around this underresearched phenomenon

The ‘responsibility’ factor in imagining the future of education in China

Design and creativity have been a considerable force for improving life conditions. A lot of effort has been invested in explaining the design process and creativity mainly through the design thinking methodology, but design accountability and responsible actions in the design process are, yet, to be fully explored. The concept of design ethics is now increasingly scrutinized on both the level of business organization and of the individual designer. A 4-day design workshop that involved creativity techniques provided the base to explore responsibility in the fuzzy front end of the design process. The future of education in 2030 was defined as the workshop's theme and fifty-six students from China were asked to create detailed alternative scenarios. A number of imagination exercises, implementation of technological innovations and macro-environment evolutions employed in the workshop are discussed. The aim was to incite moral and responsible actions among students less familiar with creative educational contexts of student-led discovery and collaborative learning. This paper reflects on the use of creativity methods to stimulate anticipation in (non)design students

Prediction of World Crude Oil Price with the Method of Missing Data

As the fluctuation of oil price plays an important role in global political and economic situation, forecasting the price of oil is significant. In this paper, we analyze the data of the world crude oil price using ideas of treating with the missing data, i.e. we take the predictor as missing data and use the EM algorithm to establish time series model. We give the predictive values of weekly world crude oil price of January and February in 2011 using the data of 2009 and 2010. Meanwhile, we found that the method based on missing data is more effective than normal time series method by comparing the predictive value with reality data. In addition, this method is also applicable to the case that historical observations have missing data. Key words: World Crude Oil Price; Forecast; Missing Data; EM Algorithm; Time Serie

Parameter identification approach using improved teaching and learning based optimization for hub motor considering temperature rise

Temperature rise of the hub motor in distributed drive electric vehicles (DDEVs) under long-time and overload operating conditions brings parameter drift and degrades the performance of the motor. A novel online parameter identification method based on improved teaching-learning-based optimization (ITLBO) is proposed to estimate the stator resistance, ��-axis inductance, ��-axis inductance, and flux linkage of the hub motor with respect to temperature rise. The effect of temperature rise on the stator resistance, ��-axis inductance, ��-axis inductance, and magnetic flux linkage is analysed. The hub motor parameters are identified offline. The proposed ITLBO algorithm is introduced to estimate the parameters online. The Gaussian perturbation function is employed to optimize the TLBO algorithm and improve the identification speed and accuracy. The mechanisms of group learning and low-ranking elimination are established. After that, the proposed ITLBO algorithm for parameter identification is employed to identify the hub motor parameters online on the test bench. Compared with other parameter identification algorithms, both simulation and experimental results show the proposed ITLBO algorithm has rapid convergence and a higher convergence precision, by which the robustness of the algorithm is effectively verified. Keywords: parameters identification, teaching–learning-based optimization, hub motor, temperature rise

Controlling factors and physical property cutoffs of the tight reservoir in the Liuhe Basin

Tight gas sandstone reservoirs of the Lower Cretaceous Xiahuapidianzi Formation are the main exploration target in the Liuhe Basin in China. Petrology characteristics, reservoir space (pore space), controlling factors and physical property cutoffs of the tight sandstone reservoir in the Liuhe Basin were determined through the integrated analysis of several methods including: casting thin section, field emission scanning electron microscopy (FE-SEM), X-ray diffraction, mercury intrusion porosimetry, nuclear magnetic resonance and nitrogen gas adsorption. The sandstones dominated by lithic arkoses and feldspathic litharenites are characterized by low porosity, low permeability and strong microscopic heterogeneity. The porosity has a range between 0.48% and 4.80%, with an average of 2.26%. Intercrystalline pores, intergranular pores, dissolved pores and microfractures can be observed through the casting thin section and FE-SEM images. Compaction and carbonate cementation are the two primary mechanisms resulting in the low porosity of the Liuhe sandstones. Microfractures improve the permeability of the tight sandstones and provide pathways for fluid migration and the storage of hydrocarbon accumulations. Moreover, the theoretical cutoff of the porosity in the Xiahuapidianzi Formation tight sandstones is 3.3%.Cited as: Tan, Z., Wang, W., Li, W., et al. Controlling factors and physical property cutoffs of the tight reservoir in the Liuhe Basin. Advances in Geo-Energy Research, 2017, 1(3): 190-202, doi: 10.26804/ager.2017.03.0

Xin-Li-Fang efficacy and safety for patients with chronic heart failure: A study protocol for a randomized, double-blind, and placebo-controlled trial

IntroductionXin-Li-Fang (XLF), a representative Chinese patent medicine, was derived from years of clinical experience by academician Chen Keji, and is widely used to treat chronic heart failure (CHF). However, there remains a lack of high-quality evidence to support clinical decision-making. Therefore, we designed a randomized controlled trial (RCT) to evaluate the efficacy and safety of XLF for CHF.Methods and designThis multicenter, double-blinded RCT will be conducted in China. 300 eligible participants will be randomly assigned to either an XLF group or a control group at a 1:1 ratio. Participants in the XLF group will receive XLF granules plus routine care, while those in the control group will receive placebo granules plus routine care. The study period is 26 weeks, including a 2-week run-in period, a 12-week treatment period, and a 12-week follow-up. The primary outcome is the proportion of patients whose serum NT-proBNP decreased by more than 30%. The secondary outcomes include quality of life, the NYHA classification evaluation, 6-min walking test, TCM symptom evaluations, echocardiography parameters, and clinical events (including hospitalization for worsening heart failure, all-cause death, and other major cardiovascular events).DiscussionThe results of the study are expected to provide evidence of high methodological and reporting quality on the efficacy and safety of XLF for CHF.Clinical trial registrationChinese Clinical Trial Registration Center (www.chictr.org.cn). The trial was registered on 13 April 2022 (ChiCTR2200058649)

Autophagy-related IFNG is a prognostic and immunochemotherapeutic biomarker of COAD patients

BackgroundNumerous studies have shown autophagy affects cellular immune responses. This study aims to explore prognosis and immunotherapeutic biomarkers related to autophagy in colon adenocarcinoma (COAD).MethodsBased on R software, we performed the ssGSEA, differential expression analysis, Kaplan-Meier survival analysis, correlation analysis, and enrichment analysis. For wet experiment, we did qRT-PCR, immunohistochemistry and CCK-8 experiments.ResultsUsing autophagy-related genes (ARGs) and the ssGSEA, COAD patients were divided into low and high autophagy groups. For immune score, stromal score, tumor purity, tumor infiltrating immune cells, co-signaling molecules, tumor mutational burden, microsatellite instability, mismatch repair, immune-related pathways, immune signatures, somatic mutations and subtype analysis, high autophagy group might benefit more from immunotherapy. Among 232 ARGs, IFNG was generally significantly correlated with tumor immunotherapy biomarkers (PD-L1, CD8A and cytotoxic T lymphocytes (CTL)). The disease-free survival of high IFNG group was significantly longer than that of low group. On above-mentioned immune-related research, the high IFNG group reached the same conclusion. The qRT-PCR and IHC analysis confirmed that IFNG was significantly higher expressed in dMMR samples compared to pMMR samples. For chemotherapy, the autophagy and IFNG were significantly negatively related to the chemosensitivity to cisplatin; IFNG inhibitor glucosamine increased cisplatin chemoresistance while IFNG increased cisplatin chemosensitivity; IFNG could reverse glucosamine induced chemoresistance. The functional enrichment analysis of IFNG, PD-L1, CD8A and 20 similar proteins were related to the activation of the immune system. The GSEA and ceRNA network partly described interaction mechanisms of IFNG with PD-L1 and CD8A.ConclusionAutophagy score and IFNG expression were novel immunotherapy predictive biomarkers, which might play predictive effects through the JAK-STAT signaling pathway. IFNG might be a potential targeted therapy for cisplatin resistant colon cancer. Besides, IFNG was also a prognostic indicator

Global analysis of the rat and human platelet proteome - the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution

Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome

A Fast Implicit Finite Difference Method for Fractional Advection-Dispersion Equations with Fractional Derivative Boundary Conditions

Fractional advection-dispersion equations, as generalizations of classical integer-order advection-dispersion equations, are used to model the transport of passive tracers carried by fluid flow in a porous medium. In this paper, we develop an implicit finite difference method for fractional advection-dispersion equations with fractional derivative boundary conditions. First-order consistency, solvability, unconditional stability, and first-order convergence of the method are proven. Then, we present a fast iterative method for the implicit finite difference scheme, which only requires storage of O(K) and computational cost of O(Klog⁡K). Traditionally, the Gaussian elimination method requires storage of O(K2) and computational cost of O(K3). Finally, the accuracy and efficiency of the method are checked with a numerical example