Research of the Current Situation and Future Trend of Internet Small-Credit Companies in China—Take Chongqing as a Case Study

In recent years, Internet finance has developed rapidly in China, benefiting from China's political, economic, social and technological environment. Taking Chongqing as an example, this paper analyses the current situation and the reasons behind the development of Chongqing Internet Microfinance Company, combining with the existing literature at home and abroad, as well as many excellent and enterprise cases such as Alibaba, Suning, Xiaomi, Jingdong, Baidu and so on. At the same time, it puts forward some thoughts on the future development of Internet microfinance companies

Using improved support vector regression to predict the transmitted energy consumption data by distributed wireless sensor network

AbstractMassive energy consumption data of buildings was generated with the development of information technology, and the real-time energy consumption data was transmitted to energy consumption monitoring system by the distributed wireless sensor network (WSN). Accurately predicting the energy consumption is of importance for energy manager to make advisable decision and achieve the energy conservation. In recent years, considerable attention has been gained on predicting energy use of buildings in China. More and more predictive models appeared in recent years, but it is still a hard work to construct an accurate model to predict the energy consumption due to the complexity of the influencing factors. In this paper, 40 weather factors were considered into the research as input variables, and the electricity of supermarket which was acquired by the energy monitoring system was taken as the target variable. With the aim to seek the optimal subset, three feature selection (FS) algorithms were involved in the study, respectively: stepwise, least angle regression (Lars), and Boruta algorithms. In addition, three machine learning methods that include random forest (RF) regression, gradient boosting regression (GBR), and support vector regression (SVR) algorithms were utilized in this paper and combined with three feature selection (FS) algorithms, totally are nine hybrid models aimed to explore an improved model to get a higher prediction performance. The results indicate that the FS algorithm Boruta has relatively better performance because it could work well both on RF and SVR algorithms, the machine learning method SVR could get higher accuracy on small dataset compared with the RF and GBR algorithms, and the hybrid model called SVR-Boruta was chosen to be the proposed model in this paper. What is more, four evaluate indicators were selected to verify the model performance respectively are the mean absolute error (MAE), the mean squared error(MSE), the root mean squared error (RMSE), and the R-squared (R2), and the experiment results further verified the superiority of the recommended methodology

The expression and antigenicity of a truncated spike-nucleocapsid fusion protein of severe acute respiratory syndrome-associated coronavirus

<p>Abstract</p> <p>Background</p> <p>In the absence of effective drugs, controlling SARS relies on the rapid identification of cases and appropriate management of the close contacts, or effective vaccines for SARS. Therefore, developing specific and sensitive laboratory tests for SARS as well as effective vaccines are necessary for national authorities.</p> <p>Results</p> <p>Genes encoding truncated nucleocapsid (N) and spike (S) proteins of <it>SARSCoV </it>were cloned into the expression vector <it>pQE30 </it>and fusionally expressed in <it>Escherichia coli </it>M15. The fusion protein was analyzed for reactivity with SARS patients' sera and with anti-sera against the two human coronaviruses <it>HCoV </it>229E and <it>HCoV </it>OC43 by ELISA, IFA and immunoblot assays. Furthermore, to evaluate the antigen-specific humoral antibody and T-cell responses in mice, the fusion protein was injected into 6-week-old BALB/c mice and a neutralization test as well as a T-cell analysis was performed. To evaluate the antiviral efficacy of immunization, BALB/c mice were challenged intranasally with <it>SARSCoV </it>at day 33 post injection and viral loads were determined by fluorescent quantitative RT-PCR. Serological results showed that the diagnostic sensitivity and specificity of the truncated S-N fusion protein derived the SARS virus were > 99% (457/460) and 100.00% (650/650), respectively. Furthermore there was no cross-reactivity with other two human coronaviruses. High titers of antibodies to <it>SRASCoV </it>appeared in the immunized mice and the neutralization test showed that antibodies to the fusion protein could inhibit <it>SARSCoV</it>. The T cell proliferation showed that the fusion protein could induce an antigen-specific T-cell response. Fluorescent quantitative RT-PCR showed that BALB/c mice challenged intranasally with <it>SARSCoV </it>at day 33 post injection were completely protected from virus replication.</p> <p>Conclusion</p> <p>The truncated S-N fusion protein is a suitable immunodiagnostic antigen and vaccine candidate.</p

Last deglaciation in the Okinawa Trough : subtropical northwest Pacific link to Northern Hemisphere and tropical climate

Author Posting. © American Geophysical Union, 2005. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Paleoceanography 20 (2005): PA4005, doi:10.1029/2004PA001061.Detailed deglacial and Holocene records of planktonic δ18O and Mg/Ca–based sea surface temperature (SST) from the Okinawa Trough suggest that at ∼18 to 17 thousand years before present (kyr B.P.), late spring/early summer SSTs were approximately 3°C cooler than today, while surface waters were up to 1 practical salinity unit saltier. These conditions are consistent with a weaker influence of the summer East Asian Monsoon (EAM) than today. The timing of suborbital SST oscillations suggests a close link with abrupt changes in the EAM and North Atlantic climate. A tropical influence, however, may have resulted in subtle decoupling between the North Atlantic and the Okinawa Trough/EAM during the deglaciation. Okinawa Trough surface water trends in the Holocene are consistent with model simulations of an inland shift of intense EAM precipitation during the middle Holocene. Millennial-scale alternations between relatively warm, salty conditions and relatively cold, fresh conditions suggest varying influence of the Kuroshio during the Holocene.Funding for this research was provided by NSFC (grants 40106006 and 40206007), SKLLQG (grant LLQG0204), and the NSF (OCE-020776 to DWO). Y.S.'s visit to WHOI was supported via a NSF START Fellowship

Methodology and experiences of rapid advice guideline development for children with COVID-19: responding to the COVID-19 outbreak quickly and efficiently

BACKGROUND: Rapid Advice Guidelines (RAG) provide decision makers with guidance to respond to public health emergencies by developing evidence-based recommendations in a short period of time with a scientific and standardized approach. However, the experience from the development process of a RAG has so far not been systematically summarized. Therefore, our working group will take the experience of the development of the RAG for children with COVID-19 as an example to systematically explore the methodology, advantages, and challenges in the development of the RAG. We shall propose suggestions and reflections for future research, in order to provide a more detailed reference for future development of RAGs. RESULT: The development of the RAG by a group of 67 researchers from 11 countries took 50 days from the official commencement of the work (January 28, 2020) to submission (March 17, 2020). A total of 21 meetings were held with a total duration of 48 h (average 2.3 h per meeting) and an average of 16.5 participants attending. Only two of the ten recommendations were fully supported by direct evidence for COVID-19, three recommendations were supported by indirect evidence only, and the proportion of COVID-19 studies among the body of evidence in the remaining five recommendations ranged between 10 and 83%. Six of the ten recommendations used COVID-19 preprints as evidence support, and up to 50% of the studies with direct evidence on COVID-19 were preprints. CONCLUSIONS: In order to respond to public health emergencies, the development of RAG also requires a clear and transparent formulation process, usually using a large amount of indirect and non-peer-reviewed evidence to support the formation of recommendations. Strict following of the WHO RAG handbook does not only enhance the transparency and clarity of the guideline, but also can speed up the guideline development process, thereby saving time and labor costs

Methodology and experiences of rapid advice guideline development for children with COVID-19: responding to the COVID-19 outbreak quickly and efficiently.

BACKGROUND Rapid Advice Guidelines (RAG) provide decision makers with guidance to respond to public health emergencies by developing evidence-based recommendations in a short period of time with a scientific and standardized approach. However, the experience from the development process of a RAG has so far not been systematically summarized. Therefore, our working group will take the experience of the development of the RAG for children with COVID-19 as an example to systematically explore the methodology, advantages, and challenges in the development of the RAG. We shall propose suggestions and reflections for future research, in order to provide a more detailed reference for future development of RAGs. RESULT The development of the RAG by a group of 67 researchers from 11 countries took 50 days from the official commencement of the work (January 28, 2020) to submission (March 17, 2020). A total of 21 meetings were held with a total duration of 48 h (average 2.3 h per meeting) and an average of 16.5 participants attending. Only two of the ten recommendations were fully supported by direct evidence for COVID-19, three recommendations were supported by indirect evidence only, and the proportion of COVID-19 studies among the body of evidence in the remaining five recommendations ranged between 10 and 83%. Six of the ten recommendations used COVID-19 preprints as evidence support, and up to 50% of the studies with direct evidence on COVID-19 were preprints. CONCLUSIONS In order to respond to public health emergencies, the development of RAG also requires a clear and transparent formulation process, usually using a large amount of indirect and non-peer-reviewed evidence to support the formation of recommendations. Strict following of the WHO RAG handbook does not only enhance the transparency and clarity of the guideline, but also can speed up the guideline development process, thereby saving time and labor costs

Régularisation spatiale de représentations distribuées de mots

Stimulée par l’usage intensif des téléphones mobiles, l’exploitation conjointe des don-nées textuelles et des données spatiales présentes dans les objets spatio-textuels (p. ex. tweets)est devenue la pierre angulaire à de nombreuses applications comme la recherche de lieux d’attraction. Du point de vue scientifique, ces tâches reposent de façon critique sur la représentation d’objets spatiaux et la définition de fonctions d’appariement entre ces objets. Dans cet article,nous nous intéressons au problème de représentation de ces objets. Plus spécifiquement, confortés par le succès des représentations distribuées basées sur les approches neuronales, nous proposons de régulariser les représentations distribuées de mots (c.-à-d. plongements lexicaux ou word embeddings), pouvant être combinées pour construire des représentations d’objets,grâce à leurs répartitions spatiales. L’objectif sous-jacent est de révéler d’éventuelles relations sémantiques locales entre mots ainsi que la multiplicité des sens d’un même mot. Les expérimentations basées sur une tâche de recherche d’information qui consiste à retourner le lieu physique faisant l’objet (sujet) d’un géo-texte montrent que l’intégration notre méthode de régularisation spatiale de représentations distribuées de mots dans un modèle d’appariement de base permet d’obtenir des améliorations significatives par rapport aux modèles de référence