Trade Policies and Economic Growth

This paper aims to examine the relationship between trade policies and economic growth. In order to test whether restrictive trade policies have a positive impact on economic growth, we investigate America, Australia and China, and, analyse how their economic performance varies between a free trade environment and a relatively protective trade environment. In this paper, we focus on comparative advantage and use various data such as tariff rate, GDP growth rate, unemployment rate, etc. to test the influence of trade policies on economic growth.We find some support that less restrictive trade policy leads to better economic growth; however overall tariff rates do not seem to have a strong effect on economic growth rate

SHARE: Single-view Human Adversarial REconstruction

The accuracy of 3D Human Pose and Shape reconstruction (HPS) from an image is progressively improving. Yet, no known method is robust across all image distortion. To address issues due to variations of camera poses, we introduce SHARE, a novel fine-tuning method that utilizes adversarial data augmentation to enhance the robustness of existing HPS techniques. We perform a comprehensive analysis on the impact of camera poses on HPS reconstruction outcomes. We first generated large-scale image datasets captured systematically from diverse camera perspectives. We then established a mapping between camera poses and reconstruction errors as a continuous function that characterizes the relationship between camera poses and HPS quality. Leveraging this representation, we introduce RoME (Regions of Maximal Error), a novel sampling technique for our adversarial fine-tuning method. The SHARE framework is generalizable across various single-view HPS methods and we demonstrate its performance on HMR, SPIN, PARE, CLIFF and ExPose. Our results illustrate a reduction in mean joint errors across single-view HPS techniques, for images captured from multiple camera positions without compromising their baseline performance. In many challenging cases, our method surpasses the performance of existing models, highlighting its practical significance for diverse real-world applications

Preserving the woody plant tree of life in China under future climate and land-cover changes

The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation. However, we know little about the effectiveness of existing PAs in preserving the TOL of plants and how to prioritize PA expansion for better TOL preservation under future climate and land-cover changes. Here, using high-resolution distribution maps of 8732 woody species in China and phylogeny-based Zonation, we find that current PAs perform poorly in preserving the TOL both at present and in 2070s. The geographical coverage of TOL branches by current PAs is approx. 9%, and less than 3% of the identified priority areas for preserving the TOL are currently protected. Interestingly, the geographical coverage of TOL branches by PAs will be improved from 9% to 52-79% by the identified priority areas for PA expansion. Human pressures in the identified priority areas are high, leading to high cost for future PA expansion. We thus suggest that besides nature reserves and national parks, other effective area-based conservation measures should be considered. Our study argues for the inclusion of preserving the TOL in the post-2020 conservation framework, and provides references for decision-makers to preserve the Earth's evolutionary history.Fil: Peng, Shijia. Peking University; ChinaFil: Hu, Ruocheng. Peking University; ChinaFil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Universidade Federal da Integração Latino-Americana; Brasil. University of California; Estados UnidosFil: Luo, Yuan. Peking University; ChinaFil: Lyu, Tong. Peking University; ChinaFil: Zhang, Xiaoling. Peking University; ChinaFil: Zhang, Jian. East China Normal University; ChinaFil: Wang, Zhiheng. Peking University; Chin

Exploiting Multiple Embeddings for Chinese Named Entity Recognition

Identifying the named entities mentioned in text would enrich many semantic applications at the downstream level. However, due to the predominant usage of colloquial language in microblogs, the named entity recognition (NER) in Chinese microblogs experience significant performance deterioration, compared with performing NER in formal Chinese corpus. In this paper, we propose a simple yet effective neural framework to derive the character-level embeddings for NER in Chinese text, named ME-CNER. A character embedding is derived with rich semantic information harnessed at multiple granularities, ranging from radical, character to word levels. The experimental results demonstrate that the proposed approach achieves a large performance improvement on Weibo dataset and comparable performance on MSRA news dataset with lower computational cost against the existing state-of-the-art alternatives.Comment: accepted at CIKM 201

Spatio-temporal patterns in the woodiness of flowering plants

Under embargo until: 2023-12-31Aim Woody and herbaceous habits represent one of the most distinct contrasts among angiosperms, and the proportion of woody species in floras (i.e., “woodiness” hereafter) represents a fundamental structural element of plant diversity. Despite its core influence on ecosystem processes, spatio-temporal patterns in woodiness remain poorly understood. Here, we aim to demonstrate the global spatio-temporal patterns in angiosperm woodiness and their relationship with environmental factors. Location Global. Time period Cenozoic, 66 Ma to present. Major taxa studied Angiosperms. Methods Using newly compiled data on the growth forms and distributions of c. 300,000 angiosperm species and an angiosperm phylogeny, we mapped the current global geographical patterns in angiosperm woodiness, reconstructed ancestral states of growth forms through the angiosperm phylogeny and demonstrated the Cenozoic evolutionary dynamics of woodiness. We evaluated the relationships between woodiness and current climate and palaeoclimate. Results We found that c. 42.7% of angiosperms are woody. Woodiness decreased spatially from the equator towards high latitudes, temporally since the early Cenozoic. Temperature was the best predictor of the spatio-temporal decline in woodiness and was positively correlated with woodiness. Despite the temporal decline in woodiness, macroevolutionary herbaceous-to-woody transitions increased through time and contributed to the evolution of woody floras in temperate drylands, whereas the opposite transitions decreased through time and contributed to herbaceous floras in tropical and subtropical drylands. Main conclusions Our study improves understanding of the spatio-temporal dynamics of angiosperm woodiness. Our findings suggest that temperature is likely to be a determinant of spatio-temporal variations in woodiness, highlighting the role of temperature in maintaining the growth form composition of ecosystems. Our study also calls for attention to growth form transitions (e.g., secondary woodiness) in temperate drylands that have been neglected before.acceptedVersio

Analysis of lncRNA-Associated ceRNA Network Reveals Potential lncRNA Biomarkers in Human Colon Adenocarcinoma

Background/Aims: Long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) play significant roles in the development of tumors, but the functions of specific lncRNAs and lncRNA-related ceRNA networks have not been fully elucidated for colon adenocarcinoma (COAD). In this study, we aimed to clarify the lncRNA-microRNA (miRNA)-mRNA ceRNA network and potential lncRNA biomarkers in COAD. Methods: We extracted data from The Cancer Genome Atlas (TCGA) and identified COAD-specific mRNAs, miRNAs, and lncRNAs. The biological processes in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed for COAD-specific mRNAs. We then constructed a ceRNA network of COAD-specific mRNAs, miRNAs and lncRNAs and analyzed the correlation between expression patterns and clinical features of the lncRNAs involved. After identifying potential mRNA targets of 4 lncRNAs related to overall survival (OS), we conducted stepwise analysis of these targets through GO and KEGG. Using tissue samples from our own patients, we also verified certain analytical results using quantitative real-time PCR (qRT-PCR). Results: Data from 521 samples (480 tumor tissue and 41 adjacent non-tumor tissue samples) were extracted from TCGA. A total of 258 specific lncRNAs, 206 specific miRNAs, and 1467 specific mRNAs were identified (absolute log2 [fold change] > 2, false discovery rate < 0.01). Analysis of KEGG revealed that specific mRNAs were enriched in cancer-related pathways. The ceRNA network was constructed with 64 lncRNAs, 18 miRNAs, and 42 mRNAs. Among these lncRNAs involved in the network, 3 lncRNAs (LINC00355, HULC, and IGF2-AS) were confirmed to be associated with certain clinical features and 4 lncRNAs (HOTAIR, LINC00355, KCNQ1OT1, and TSSC1-IT1) were found to be negatively linked to OS (log-rank p < 0.05). KEGG showed that the potential mRNA targets of these 4 lncRNAs may be concentrated in the MAPK pathway. Certain results were validated by qRT-PCR. Conclusion: This study providing novel insights into the lncRNA-miRNA-mRNA ceRNA network and reveals potential lncRNA biomarkers in COAD

Meta-analysis Database

All data extracted from papers used in the meta-analysis. R code for the analysis used with these data is uploaded separately

Systematic Review Database

Information from papers in the Systematic review, including grain, extent, habitat type, type of research, and lat/long