The Thinking of “Negative List” Management Mode Implemented by Administrative Approval System

“Negative list” management as a key point in the economic system reform will be of great reference to deepen the reform of administrative approval system which can be regarded as a sally port to promote the transformation of government functions. This paper tries to analyses feasibility of the mode to promote administrative system reform and its key points and difficulties in the operation process by drawing lessons from “negative list” management in free trade area and the development of foreign experience as well as combining the characteristics of “negative list” management mode.

A personalized hybrid music recommender based on empirical estimation of user-timbre preference

Automatic recommendation system as a subject of machine learning has been undergoing a rapid development in the recent decade along with the trend of big data. Particularly, music recommendation is a highlighted topic because of its commercial value coming from the large music industry. Popular online music recommendation services, including Spotify, Pandora and Last.FM use similarity-based approaches to generate recommendations. In this thesis work, I propose a personalized music recommendation approach that is based on probability estimation without any similarity calculation involved. In my system, each user gets a score for every piece of music. The score is obtained by combining two estimated probabilities of an acceptance. One estimated probability is based on the user’s preferences on timbres. Another estimated probability is the empirical acceptance rate of a music piece. The weighted arithmetic mean is evaluated to be the best performing combination function. An online demonstration of my system is available at www.shuyang.eu/plg/. Demonstrating recommendation results show that the system works effectively. Through the algorithm analysis on my system, we can see that my system has good reactivity and scalability without suffering cold start problem. The accuracy of my recommendation approach is evaluated with Million Song Dataset. My system achieves a pairwise ranking accuracy of 0.592, which outperforms random ranking (0.5) and ranking by popularity (0.557). Unfortunately, I have not found any other music recommendation method evaluated with ranking accuracy yet. As a comparison, Page Rank algorithm (for web page ranking) has a pairwise ranking accuracy of 0.567

Engineering high-emissive silicon-doped carbon nanodots towards efficient large-area luminescent solar concentrators

Luminescent solar concentrators (LSCs) are devices that can collect sunlight from a large area, concentrating it at the borders of the slab, to achieve efficient photovoltaic conversion when small area solar cells are placed at their edges, realizing building-integrated photovoltaics. Efficient luminophores in terms of high luminescence quantum yield are needed to obtain high-performance LSCs. A key point is the ability to engineer the Stokes shift (i.e. the difference between the maximum of the absorption and emission spectra), to minimize reabsorption processes. In this work, we report novel silicon-doped carbon nanodots (Si-CDs) with an ultrahigh quantum yield (QY) up to 92.3% by a simple hydrothermal method. Thin-film structured LSCs (5 × 5 × 0.2 cm3) with different concentrations of Si-CDs are prepared by dispersing the Si-CDs into polyvinyl pyrrolidone (PVP) matrix, and the optimal power conversion efficiency (PCE) of LSCs can be as high as 4.36%, which is nearly 2.5 times higher than that prepared with silicon-undoped CDs. This Si-CDs/PVP film LSC has a high QY of 80.5%. A large-area LSC (15 × 15 cm2) is also successfully fabricated, which possesses a PCE of 2.06% under natural sunlight irradiation (35 mW·cm−2), one of the best reported values for similar size LSCs. The efficient Si-CDs as luminescent substances for high-efficiency large-area LSCs will further give an impetus to the practical exploitation of LSCs

Network-based stratification analysis of 13 major cancer types using mutations in panels of cancer genes.

BACKGROUND: Cancers are complex diseases with heterogeneous genetic causes and clinical outcomes. It is critical to classify patients into subtypes and associate the subtypes with clinical outcomes for better prognosis and treatment. Large-scale studies have comprehensively identified somatic mutations across multiple tumor types, providing rich datasets for classifying patients based on genomic mutations. One challenge associated with this task is that mutations are rarely shared across patients. Network-based stratification (NBS) approaches have been proposed to overcome this challenge and used to classify tumors based on exome-level mutations. In routine research and clinical applications, however, usually only a small panel of pre-selected genes is screened for mutations. It is unknown whether such small panels are effective in classifying patients into clinically meaningful subtypes. RESULTS: In this study, we applied NBS to 13 major cancer types with exome-level mutation data and compared the classification based on the full exome data with those focusing only on small sets of genes. Specifically, we investigated three panels, FoundationOne (240 genes), PanCan (127 genes) and TruSeq (48 genes). We showed that small panels not only are effective in clustering tumors but also often outperform full exome data for most cancer types. We further associated subtypes with clinical data and identified 5 tumor types (CRC-Colorectal carcinoma, HNSC-Head and neck squamous cell carcinoma, KIRC-Kidney renal clear cell carcinoma, LUAD-Lung adenocarcinoma and UCEC-Uterine corpus endometrial carcinoma) whose subtypes are significantly associated with overall survival, all based on small panels. CONCLUSION: Our analyses indicate that effective patient subtyping can be carried out using mutations detected in smaller gene panels, probably due to the enrichment of clinically important genes in such panels

Establishment of Tumor Treating Fields Combined With Mild Hyperthermia as Novel Supporting Therapy for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with poor prognosis and limited therapeutic options. Alternating electrical fields with low intensity called “Tumor Treating Fields” (TTFields) are a new, non-invasive approach with almost no side effects and phase 3 trials are ongoing in advanced PDAC. We evaluated TTFields in combination with mild hyperthermia. Three established human PDAC cell lines and an immortalized pancreatic duct cell line were treated with TTFields and hyperthermia at 38.5°C, followed by microscopy, assays for MTT, migration, colony and sphere formation, RT-qPCR, FACS, Western blot, microarray and bioinformatics, and in silico analysis using the online databases GSEA, KEGG, Cytoscape-String, and Kaplan-Meier Plotter. Whereas TTFields and hyperthermia alone had weak effects, their combination strongly inhibited the viability of malignant, but not those of nonmalignant cells. Progression features and the cell cycle were impaired, and autophagy was induced. The identified target genes were key players in autophagy, the cell cycle and DNA repair. The expression profiles of part of these target genes were significantly involved in the survival of PDAC patients. In conclusion, the combination of TTFields with mild hyperthermia results in greater efficacy without increased toxicity and could be easily clinically approved as supporting therapy

Epoxy as Filler or Matrix for Polymer Composites

Epoxy is a widely used polymer because of its ease of processing, high adhesiveness, and high chemical resistance. Epoxy-based composites are commonly used in aerospace, automotive, and marine applications. The epoxy type, function, curing agent, and curing process are discussed in this chapter. Epoxy is used as either a filler or polymer matrix in composite applications. As a filler, the epoxy modification on the fiber is discussed. As a polymer matrix, the epoxy is reinforced by natural and synthetic fibers. The manufacturing process and the fabricated epoxy-based composites’ performance (e.g., mechanical and thermal properties) are investigated. The advantages and disadvantages of epoxy’s function are discussed and summarized. Epoxy modification is an effective approach to improve the composites’ performance