Neural Network Model for Classifying the Economic Recession and Construction of Financial Stress Index

In this paper, a C5.0 decision tree and neural network models are proposed to classify recessions in the US with 12 common financial indices and new financial stress indices inferred from the neural network models are created. A detailed experiment is presented and demonstrates that the neural network models with proper regularization and dropout achieve 98% accuracy in the training set, 97% accuracy in validation set and 100% accuracy in test accuracy. The financial stress indices outperform other existing financial stress indices in many scenes and can accurately locate crisis events even the most recent 2018 US Bear Market. With these models and new indices, contraction can be detected before NBER’s announcement and action could be taken as early as the situation get worse.

Population genomic analysis reveals domestication of cultivated rye from weedy rye

Rye(Secale cereale)is an important crop with multiple uses and a valuable genetic resource for wheat breeding.However,due to its complex genome and outcrossing nature,the origin of cultivated rye remains elusive.The geneticist N.I.Vavilov proposed that cultivated rye had been domesticated from weedy rye,rather than directly from wild species like other crops.Unraveling the domestication history of rye will extend our understanding of crop evolution and upend our inherent understanding of agricultural weeds.To this end,in this study we generated the 8.5 Tb of whole-genome resequencing data from 116 worldwide accessions of wild,weedy,and cultivated rye,and demonstrated that cultivated rye was domesticated directly from weedy relatives with a similar but enhanced genomic selection by humans.We found that a repertoire of genes that experienced artificial selection is associated with important agronomic traits,including shattering,grain yield,and disease resistance.Furthermore,we identified a composite introgression in cultivated rye from the wild perennial Secale strictum and detected a 2-Mb introgressed fragment containing a candidate ammonium transporter gene with potential effect on the grain yield and plant growth of rye.Taken together,our findings unravel the domestication history of cultivated rye,suggest that interspecific introgression serves as one of the likely causes of obscure species taxonomy of the genus Secale,and provide an important resource for future rye and wheat breeding.

Rapid and multimodal in vivo bioimaging of cancer cells through in situ biosynthesis of Zn＆Fe nanoclusters

Early diagnosis remains highly important for efficient cancer treatment, and hence, there is significant interest in the development of effective imaging strategies. This work reports a new multimodal bioimaging method for accurate and rapid diagnosis of cancer cells by introducing aqueous Fe^2＋ and Zn^2＋ ions into cancer cells （i.e., HeLa, U87, and HepG2 cancer cells）. We found that the biocompatible metal ions Fe^2＋ and Zn^2＋ forced the cancer cells to spontaneously synthesize fluorescent ZnO nanoclusters and magnetic Fe3O4 nanoclusters. These clusters could then be used for multimodal cancer imaging by combining fluorescence imaging with magnetic resonance imaging and computed tomography imaging. Meanwhile, for normal cells （i.e., L02） and tissues, neither fluorescence nor any other obvious difference could be detected between pre- and post-injection. This multimodal bioimaging strategy based on the in situ biosynthesized Zn＆Fe oxide nanoclusters might therefore be useful for early cancer diagnosis and therapy.

Spreading Social Influence with both Positive and Negative Opinions in Online Networks

Social networks are important media for spreading information, ideas, and influence among individuals.Most existing research focuses on understanding the characteristics of social networks, investigating how information is spread through the "word-of-mouth" effect of social networks, or exploring social influences among individuals and groups. However, most studies ignore negative influences among individuals and groups. Motivated by the goal of alleviating social problems, such as drinking, smoking, and gambling, and influence-spreading problems, such as promoting new products, we consider positive and negative influences, and propose a new optimization problem called the Minimum-sized Positive Influential Node Set(MPINS) selection problem to identify the minimum set of influential nodes such that every node in the network can be positively influenced by these selected nodes with no less than a threshold of ?. Our contributions are threefold. First, we prove that, under the independent cascade model considering positive and negative influences, MPINS is APX-hard. Subsequently, we present a greedy approximation algorithm to address the MPINS selection problem. Finally, to validate the proposed greedy algorithm, we conduct extensive simulations and experiments on random graphs and seven different realworld data sets that represent small-, medium-, and large-scale networks.

Constructing data literacy evaluation system for social science scholars

To establish a data literacy evaluation system for social science scholars is a part of transformation to data-intensive scientific research paradigm in social science.Based on the literature review of data literacy and survey of social science data management features,this paper analyzed the elements of data literacy of social science scholars.The data literacy of social science scholars ma inly consists of data awareness level,data discovery and access ability,data management and organization ability,data processing and analysis ability,data utilization and preservation ability,and data ethics level.Each of these primary indexes has several secondary indexes.It constructed the evaluation system of social science scholars data literacy.The weights of the primary and secondary indexes in the system were calculated by applying AHP.The data literacy evaluation system for social science scholars can provide a reference for assessing and promoting social science scholars'data literacy ability in China.

PlantcircBase 7.0:Full-length transcripts and conservation of plant circRNAs

Circular RNA(circRNA)is a special type of non-coding RNA that participates in diverse biological processes in both animals and plants.Five years ago,we developed a comprehensive plant circRNA database(PlantcircBase),which has attracted much attention from the plant circRNA community.Here,we report an updated PlantcircBase(v.7.0),which contains 171,118 circRNAs from 21 plant species.Over 31,000 of the circRNAs have full-length sequences constructed based on analysis of 749 bulk RNA sequencing(RNAseq)datasets downloaded from the public domain and Nanopore long-read sequencing results of rice RNAs newly generated in this study.A plant multiple conservation score(PMCS),based on the conservation of both sequence and expression profiles,was calculated for each circRNA to quantify and compare the conservation of all circRNAs.A new parameter,plant circRNA confidence level(PCCL),is introduced to measure the identity reliability of each circRNA based on experimental validation results and the number of references that support the circRNA.All this information and other details of circRNAs can be browsed,searched,and downloaded from PlantcircBase 7.0,which also provides online bioinformatics tools for visualization and sequence alignment.PlantcircBase 7.0 is publicly and freely accessible at http://ibi.zju.edu.cn/plantcircbase/.