Risk Communication Mechanisms in China Coping with the Risk of Digital Transformation of Society

In the process of promoting the digital transformation of the society, digital platform companies will transform the previously uncontrollable uncertain damage into controllable uncertain damage by reasonable risk decisions. but at the same time, unreasonable risk decisions will cause new uncertain damage and it is the main source of risk in the digital society. How to motivate multiple risk stakeholders such as government, digital platform companies and the public to jointly make reasonable risk decisions and practices is the dilemma of risk management in digital society. China has opened up the governance of digital platform companies to the government and the public through a dual cycle system of risk decision-making. These Institutional innovations are aimed at transforming in-company business decisions into public decisions negotiated by multiple risk stakeholders through constructing risk communication mechanisms, thereby enhancing the transparency, democracy and accountability of risk decisions. However, there are many problems in the construction of specific communication mechanisms, which hinder the regional development of digital economy in Asia. China should learn from other’s experience and promote the convergence of risk communication mechanisms by more concrete measures

Metrology of Quantum Control and Measurement in Superconducting Qubits

Quantum computers have the potential to solve problems which are classically intractable. Superconducting qubits present a promising path to building such a computer. Recent experiments with these qubits have demonstrated the principles of quantum error correction, quantum simulation, quantum annealing, and more. Current research with superconducting qubits is focused on two primary goals: creating a fully fault tolerant logical qubit out of many physical qubits using surface code error correction, and demonstrating an exponential speedup over any classical computer for a well-defined computational problem. To achieve either of these goals requires high precision control of three components: single qubit gates, two qubit gates, and qubit measurement. In this thesis, we use randomized benchmarking to characterize single qubit gates with 99.95\% fidelity and two qubit gates wiht 99.5\% fidelity in superconducting transmon qubits. In addition, we use standard decoherence measurements as well as newly developed extensions of randomized benchmarking to determine the limiting sources of error. Finally, we explore the surprisingly complicated dynamics of measuring the transmon state through a coupled resonator, and show that fully understanding this process requires breaking a few "standard" assumptions

Effects of species mixtures on fine root production in a young boreal forest

1. Fine roots (< 2 mm) play a key role in terrestrial ecosystem processes. Species diversity loss has been recognized as one of the primary global change drivers that can have profound negative effects on ecosystem functionality and services to humanity. However, our understanding of the effects of plant diversity on fine root production remains limited. 2. We investigated the effects of species diversity on fine root production in a boreal forest that had grown naturally for eight years, following stand-replacing fire, by comparing the generation of fine-roots in single-species stands (Populus tremuloides Michx. (Populus) and Pinus banksiana Lamb. (Pinus)], and their mixtures (Populus+Pinus). 3. We hypothesized that: (i) fine root production is higher in mixed stands, (ii) across a given growing season, the effects of diversity on fine root production would be the greatest in August in a boreal forest, and (iii) fine root production in a mixed stand is strongly influenced by the dominant species. 4. We found no evidence of positive diversity effects on fine root production in a young natural boreal forest. Moreover, fine root production was not altered during sampling dates between May to October; however, the effects of tree species diversity on fine root production was positive in August. Rather, fine root production differed significantly with the composition of overstory tree species, with Populus stands having the highest root production. 5. Our results suggested that mixtures of two shade-tolerant tree species at an early stage of development did not benefit fine root production, except during the mid-growth season. Further, our results supported the mass ratio hypothesis for species compositional effects on the belowground processes that we investigated

FX Resilience around the World: Fighting Volatile Cross-Border Capital Flows

We show that capital flow (CF) volatility exerts an adverse effect on exchange rate (FX) volatility, regardless of whether capital controls have been put in place. However, this effect can be significantly moderated by certain macroeconomic fundamentals that reflect trade openness, foreign assets holdings, monetary policy easing, fiscal sustainability, and financial development. Passing the threshold levels of these macroeconomic fundamentals, the adverse effect of CF volatility may be negligible. We further construct an intuitive FX resilience measure, which provides an assessment of the strength of a country's exchange rates

How complex is the microarray dataset? A novel data complexity metric for biological high-dimensional microarray data

Data complexity analysis quantifies the hardness of constructing a predictive model on a given dataset. However, the effectiveness of existing data complexity measures can be challenged by the existence of irrelevant features and feature interactions in biological micro-array data. We propose a novel data complexity measure, depth, that leverages an evolutionary inspired feature selection algorithm to quantify the complexity of micro-array data. By examining feature subsets of varying sizes, the approach offers a novel perspective on data complexity analysis. Unlike traditional metrics, depth is robust to irrelevant features and effectively captures complexity stemming from feature interactions. On synthetic micro-array data, depth outperforms existing methods in robustness to irrelevant features and identifying complexity from feature interactions. Applied to case-control genotype and gene-expression micro-array datasets, the results reveal that a single feature of gene-expression data can account for over 90% of the performance of multi-feature model, confirming the adequacy of the commonly used differentially expressed gene (DEG) feature selection method for the gene expression data. Our study also demonstrates that constructing predictive models for genotype data is harder than gene expression data. The results in this paper provide evidence for the use of interpretable machine learning algorithms on microarray data

Localization of Fusobacterium nucleatum in oral squamous cell carcinoma and its possible directly interacting protein molecules: A case series

Introduction. While 15 to 20% of cancers are associated with microbial infection, the relationship between oral microorganisms and oral squamous cell carcinoma (OSCC) remains unclear. The location of bacteria in a tumor is closely related to its carcinogenic mechanism. The aim of this study was to analyse bacterial diversity in clinical OSCC tissue samples and tumor distant normal tissues, locate target bacteria, and search for proteins that may interact with target bacteria. Materials and Methods. The 16S rDNA method was used to analyse bacterial diversity in clinical OSCC tissue samples and tumor distant normal tissues. Correlations between Fusobacterium abundance and clinicopathological characteristics were analysed using the χ2 test. The position of target bacteria was analysed by fluorescence in situ hybridization (FISH), and the expression of CK, CD31, CD45, CD68, cyclin D1, βcatenin, E-cadherin, NF-κB, and HIF-1α was analysed by immunohistochemistry (IHC) in OSCC tumor tissues and tumor distant normal tissues. Results. The 16S rDNA results showed that the detected amount of Fusobacterium in OSCC tumor tissues was significantly larger than that in tumor distant normal tissues. High expression of Fusobacterium was significantly correlated with the lifestyle-related oral risk habits, including smoking (p=0.036) and alcohol consumption (p=0.022), but did not correlate with patient sex, age, tumor laterality, tumor size, grade or TNM stage. Fusobacterium nucleatum was enriched in tumor stroma, where CD31+ blood vessels and inflammatory cells (including CD45+ leukocytes and CD68+ macrophages) were densely distributed. Cyclin D1 was mainly expressed in the nucleus of tumor cells. β-catenin was expressed in the tumor cell membrane and was positively expressed in tumor interstitial vascular endothelial cells. E-cadherin was mainly expressed in tumor cell membranes. NF-κB was positively expressed in the cytoplasm of tumor cells, tumor interstitial cells and myo-fibrocytes. HIF-1α was mainly expressed in the cytoplasm of tumor interstitial cells. HIF-1α was highly expressed where Fusobacterium nucleatum was densely distributed. Conclusion. According to our study, the detected amount of Fusobacterium in OSCC tumor tissues was significantly larger than that in tumor distant normal tissues, and Fusobacterium nucleatum might aggravate inflammation and hypoxia by interacting with NF-κB and HIF-1α in OSCC