State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning

Pessimism is of great importance in offline reinforcement learning (RL). One broad category of offline RL algorithms fulfills pessimism by explicit or implicit behavior regularization. However, most of them only consider policy divergence as behavior regularization, ignoring the effect of how the offline state distribution differs with that of the learning policy, which may lead to under-pessimism for some states and over-pessimism for others. Taking account of this problem, we propose a principled algorithmic framework for offline RL, called \emph{State-Aware Proximal Pessimism} (SA-PP). The key idea of SA-PP is leveraging discounted stationary state distribution ratios between the learning policy and the offline dataset to modulate the degree of behavior regularization in a state-wise manner, so that pessimism can be implemented in a more appropriate way. We first provide theoretical justifications on the superiority of SA-PP over previous algorithms, demonstrating that SA-PP produces a lower suboptimality upper bound in a broad range of settings. Furthermore, we propose a new algorithm named \emph{State-Aware Conservative Q-Learning} (SA-CQL), by building SA-PP upon representative CQL algorithm with the help of DualDICE for estimating discounted stationary state distribution ratios. Extensive experiments on standard offline RL benchmark show that SA-CQL outperforms the popular baselines on a large portion of benchmarks and attains the highest average return

Genomic mosaicism due to homoeologous exchange generates extensive phenotypic diversity in nascent allopolyploids

Allopolyploidy is an important process in plant speciation, yet newly formed allopolyploid species typically suffer from extreme genetic bottlenecks. One escape from this impasse might be homoeologous meiotic pairing, during which homoeologous exchanges (HEs) generate phenotypically variable progeny. However, the immediate genome-wide patterns and resulting phenotypic diversity generated by HEs remain largely unknown. Here, we analyzed the genome composition of 202 phenotyped euploid segmental allopolyploid individuals from the 4th selfed generation following chromosomal doubling of reciprocal F1 hybrids of crosses between rice subspecies, using whole genome sequencing. We describe rampant occurrence of HEs that, by overcoming incompatibility or conferring superiority of hetero-cytonuclear interactions, generate extensive and individualized genomic mosaicism across the analyzed tetraploids. We show that the resulting homoeolog copy number alteration in tetraploids affects known-function genes and their complex genetic interactions, in the process creating extraordinary phenotypic diversity at the population level following a single initial hybridization. Our results illuminate the immediate genomic landscapes possible in a tetraploid genomic environment, and underscore HE as an important mechanism that fuels rapid phenotypic diversification accompanying the initial stages of allopolyploid evolution

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Study on the Impact of Supply Chain Dynamic Capabilities on Long-Term Performance of Enterprises

The risk of frequent disasters is becoming a huge challenge for enterprises and their supply chains. In particular, sudden global public health events have brought a great test to the supply chain. How to make sustainable planning and preparedness and smoothly carry out supply chain operations and obtain sustainable firm performance in the complex market environment requires urgent attention from industries and academia. The different effects of supply chain operational capability and dynamic capability on the long-term performance and short-term performance of enterprises are still unclear; therefore, a model was established to discuss this. Based on the theory of dynamic capability, a relational model between supply chain dynamic capability, supply chain operational capability, and firm performance was constructed, a hypothesis testing method and Amos software were used to verify the set model, and the mechanisms of supply chain dynamic capability and supply chain operational capability on firm performance were discussed. The empirical results show that supply chain operational capability has a mediating effect on supply chain dynamic capability and firm performance, and supply chain dynamic capability has a moderating impact on supply chain operational capability and firm performance. The supply chain and its enterprises should cultivate and continuously improve the supply chain dynamic capability as soon as possible, so that in the face of emergencies, the supply chain operation capability can be reasonably configured to avoid damage, improve firm performance, and gain competitive advantages

The impact of different pollution sources on modern dinoflagellate cysts in Sishili Bay, Yellow Sea, China

The spatial distribution of dinoflagellate cysts in the surface sediment of Sishili Bay, Yellow Sea, China, was studied, with the purpose of understanding the impact from nutrient enrichment and industrial pollution. Thirty-five dinoflagellate cyst taxa belonging to 15 genera and 3 unknown cysts were identified and quantified at 22 sampling sites. Autotrophic cysts (e.g., Spiniferites bentori var. truncata) and heterotrophic cysts (Brigantedinium sp.1 and Quinquecuspis concreta) dominated the sediment samples. The spatial distribution of cyst abundance showed a significant positive correlation with increased nutrients, but was negative to heavy metal pollution. The highest cyst abundance (with an average of 539 cysts g–1 DW) occurred in Zone A, corresponding to nutrient enrichment caused by domestic sewage discharge. In contrast, the lowest cyst abundance (with an average of 131 cysts g–1 DW) occurred in Zone E, impacted heavily by the industrial pollution. The abundance of autotrophic cysts decreased dramatically in Zone E compared with heterotrophic cysts and showed asensitivity to industrial pollution. How heavy metals affect physiological mechanisms in autotrophic and heterotrophic cysts differentially is in need of in-depth study.The spatial distribution of dinoflagellate cysts in the surface sediment of Sishili Bay, Yellow Sea, China, was studied, with the purpose of understanding the impact from nutrient enrichment and industrial pollution. Thirty-five dinoflagellate cyst taxa belonging to 15 genera and 3 unknown cysts were identified and quantified at 22 sampling sites. Autotrophic cysts (e.g., Spiniferites bentori var. truncata) and heterotrophic cysts (Brigantedinium sp.1 and Quinquecuspis concreta) dominated the sediment samples. The spatial distribution of cyst abundance showed a significant positive correlation with increased nutrients, but was negative to heavy metal pollution. The highest cyst abundance (with an average of 539 cysts g(-1) DW) occurred in Zone A, corresponding to nutrient enrichment caused by domestic sewage discharge. In contrast, the lowest cyst abundance (with an average of 131 cysts g-1 DW) occurred in Zone E. impacted heavily by the industrial pollution. The abundance of autotrophic cysts decreased dramatically in Zone E compared with heterotrophic cysts and showed a sensitivity to industrial pollution. How heavy metals affect physiological mechanisms in autotrophic and heterotrophic cysts differentially is in need of in-depth study. (C) 2011 Elsevier B.V. All rights reserved

A Two-Staged SEM-Artificial Neural Network Approach to Analyze the Impact of FinTech Adoption on the Sustainability Performance of Banking Firms: The Mediating Effect of Green Finance and Innovation

This study aims to examine the effect of FinTech adoption on the sustainability performance of banking institutions in an emerging economy such as Bangladesh. Besides, this study also investigates the mediating role of green finance and green innovation in the relationship between FinTech adoption and sustainability performance. To examine the relationship among the study variables, this study used data from 351 employees of banking institutions operating in Bangladesh during the period January to March 2021 using a convenience sampling method. Furthermore, the study utilized a two-staged structural equation modeling and an artificial neural network (SEM-ANN) approach to analyze the data. The findings show that FinTech adoption significantly influences green finance, green innovation, and sustainability performance. Similarly, the results indicate that green finance and green innovation have a significant positive influence on sustainability performance. Furthermore, the results reveal that green finance and green innovation fully mediate the relationship between FinTech adoption and the sustainability performance of banking institutions. Moreover, the present study contributes to the existing literature on technological innovation, green finance, and sustainability performance greatly as it is the first study to examine both linear and non-linear relationships among these variables using the SEM-ANN approach. As a result, the study highlights the importance of FinTech adoption, green finance, and innovation in the attainment of sustainability performance, as well as the urgent need to incorporate new technologies, green initiatives, and financing into banking strategies to help achieve the country’s sustainable economic development

Evolution of Homeologous Gene Expression in Polyploid Wheat

Polyploidization has played a prominent role in the evolutionary history of plants. Two recent and sequential allopolyploidization events have resulted in the formation of wheat species with different ploidies, and which provide a model to study the effects of polyploidization on the evolution of gene expression. In this study, we identified differentially expressed genes (DEGs) between four BBAA tetraploid wheats of three different ploidy backgrounds. DEGs were found to be unevenly distributed among functional categories and duplication modes. We observed more DEGs in the extracted tetraploid wheat (ETW) than in natural tetraploid wheats (TD and TTR13) as compared to a synthetic tetraploid (AT2). Furthermore, DEGs showed higher Ka/Ks ratios than those that did not show expression changes (non-DEGs) between genotypes, indicating DEGs and non-DEGs experienced different selection pressures. For A-B homeolog pairs with DEGs, most of them had only one differentially expressed copy, however, when both copies of a homeolog pair were DEGs, the A and B copies were more likely to be regulated to the same direction. Our results suggest that both cis- and inter-subgenome trans-regulatory changes are important drivers in the evolution of homeologous gene expression in polyploid wheat, with ploidy playing a significant role in the process

Cytonuclear Variation of Rubisco in Synthesized Rice Hybrids and Allotetraploids

The allopolyploid speciation process faces the genomic challenge of stoichiometric disruption caused by merging biparental nuclear genomes with only one (usually maternal) of the two sets of progenitor cytoplasmic genomes. The photosynthetic protein 1,5-bisphosphate carboxylase/oxygenase (Rubisco) is composed of nuclear-encoded small subunits (SSUs) and plastome-encoded large subunits (LSUs), making it an ideal enzyme to explore the evolution process of cytonuclear accommodation. We investigated the variation of SSUs and their encoding genes in synthetic nascent rice ( L.) allotetraploid lineages, formed from the parental subspecies and of Asian rice. The evolution of genes in rice subspecies involves both mutation and concerted homogenization. Within reciprocal rice hybrids and allopolyploids, there was no consistent pattern of biased expression of alleles or homeologs, nor was there biased gene conversion favoring the maternal gene copies. Instead, we observed an apparently stochastic pattern of intergenomic gene conversions and biased expression of homeologs. We conclude that in young rice allopolyploids, cytonuclear coordination either is not selectively favored because of high parental sequence similarity or because there has been insufficient time for subtle selective effects to become observable