Decision Making on Government Subsidy for Highway Public-Private Partnership Projects in China Using an Iteration Game Model

Government subsidy is an important responsibility of fiscal expenditure in public-private partnership (PPP) projects. However, an improper subsidy strategy may cause over-compensation or under-compensation. In this research, an iteration game model combining game theory and real option is established to describe the periodic decision-making process. The strategy game model is applied to characterize the behavioral interactions between stakeholders, and the real option theory is used to predict the project performance under the influence of their decisions. Besides, two new indicators, the efficiency of fund (SE) and the total extra cost paid by the private sector (ME), are proposed to evaluate the extra project revenue caused by each unit of the subsidy and the incentive effects of the subsidy. Consequently, the preliminary results indicate that a periodic and iterative negotiations regarding the subsidy will effectively improve the efficiency of fund compared to the traditional way. The results also show that it is important for the public sector to give incentives, encouraging the private sector to make more efforts on the project, rather than merely providing fund support. Further study will focus on more detailed and complicated behaviors of stakeholders based on the model proposed in this paper

Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes

Despite the recent successes of vanilla Graph Neural Networks (GNNs) on many tasks, their foundation on pairwise interaction networks inherently limits their capacity to discern latent higher-order interactions in complex systems. To bridge this capability gap, we propose a novel approach exploiting the rich mathematical theory of simplicial complexes (SCs) - a robust tool for modeling higher-order interactions. Current SC-based GNNs are burdened by high complexity and rigidity, and quantifying higher-order interaction strengths remains challenging. Innovatively, we present a higher-order Flower-Petals (FP) model, incorporating FP Laplacians into SCs. Further, we introduce a Higher-order Graph Convolutional Network (HiGCN) grounded in FP Laplacians, capable of discerning intrinsic features across varying topological scales. By employing learnable graph filters, a parameter group within each FP Laplacian domain, we can identify diverse patterns where the filters' weights serve as a quantifiable measure of higher-order interaction strengths. The theoretical underpinnings of HiGCN's advanced expressiveness are rigorously demonstrated. Additionally, our empirical investigations reveal that the proposed model accomplishes state-of-the-art (SOTA) performance on a range of graph tasks and provides a scalable and flexible solution to explore higher-order interactions in graphs

Unchain the Search Space with Hierarchical Differentiable Architecture Search

Differentiable architecture search (DAS) has made great progress in searching for high-performance architectures with reduced computational cost. However, DAS-based methods mainly focus on searching for a repeatable cell structure, which is then stacked sequentially in multiple stages to form the networks. This configuration significantly reduces the search space, and ignores the importance of connections between the cells. To overcome this limitation, in this paper, we propose a Hierarchical Differentiable Architecture Search (H-DAS) that performs architecture search both at the cell level and at the stage level. Specifically, the cell-level search space is relaxed so that the networks can learn stage-specific cell structures. For the stage-level search, we systematically study the architectures of stages, including the number of cells in each stage and the connections between the cells. Based on insightful observations, we design several search rules and losses, and mange to search for better stage-level architectures. Such hierarchical search space greatly improves the performance of the networks without introducing expensive search cost. Extensive experiments on CIFAR10 and ImageNet demonstrate the effectiveness of the proposed H-DAS. Moreover, the searched stage-level architectures can be combined with the cell structures searched by existing DAS methods to further boost the performance. Code is available at: https://github.com/MalongTech/research-HDASComment: To appear in AAAI2021. Code is availabl

Weed genomics : yielding insights into the genetics of weedy traits for crop improvement

Weeds cause tremendous economic and ecological damage worldwide. The number of genomes established for weed species has sharply increased during the recent decade, with some 26 weed species having been sequenced and de novo genomes assembled. These genomes range from 270 Mb (Barbarea vulgaris) to almost 4.4 Gb (Aegilops tauschii). Importantly, chromosome-level assemblies are now available for 17 of these 26 species, and genomic investigations on weed populations have been conducted in at least 12 species. The resulting genomic data have greatly facilitated studies of weed management and biology, especially origin and evolution. Available weed genomes have indeed revealed valuable weed-derived genetic materials for crop improvement. In this review, we summarize the recent progress made in weed genomics and provide a perspective for further exploitation in this emerging field

Analgesic effect of ropivacaine combined with dexmedetomidine in the postoperative period in children undergoing ultrasound-guided single-shot sacral epidural block: A systematic review and meta-analysis

ObjectiveThis study aims to evaluate the efficacy of dexmedetomidine as an adjuvant to ropivacaine in prolonging postoperative analgesia and reducing pain scores in children undergoing surgery.MethodsFive online databases were searched for RCTs on postoperative analgesia of pediatric patients undergoing ultrasound-guided single-shot sacral epidural block with dexmedetomidine as an adjuvant to ropivacaine up to January 2, 2023. Pain score and sedation score at 2, 4, 8, 12, and 24 h after the operation, the time of first receiving additional analgesic drugs, and the number of postoperative adverse effects were selected to compare the efficacy and safety of combined treatment with ropivacaine alone for pediatrics. The standard mean difference (SMD) or odds ratio (OR) and the corresponding 95% confidence interval (95%CI) were calculated by using a random-effects model.ResultsA total of 295 articles were retrieved, but only 20 records were included in this meta-analysis. The results showed that dexmedetomidine combined with ropivacaine for sacral epidural block in children undergoing ultrasound-guided single-shot sacral epidural block had a more prolonged analgesia effect (SMD = 3.47, 95%CI: 2.80, 4.14). There were lower analgesia scores at 2 h(T1), 4 h(T2), 8 h(T3), 12 h(T4), and 24 h(T5) in postoperative period (T1: SMD = −1.02, 95%CI: −1.31, −0.72; T2: SMD = −1.02, 95%CI: −1.32, −0.72; T3: SMD = −0.84, 95%CI: −1.12, −0.56; T4: SMD = −0.61, 95%CI: −1.03, −0.20; T5: SMD = −1.03, 95%CI: −1.28, −0.78). And the incidence of adverse effects was similar between the two groups (OR = 0.84, 95%CI: 0.59, 1.18).ConclusionsThe results of this review and meta-analysis support that dexmedetomidine, as an adjuvant to ropivacaine, can improve postoperative analgesia of surgery and significantly prolong the analgesic time in children, with a similar incidence rate of adverse symptoms when compared with ropivacaine alone

Three complete chloroplast genomes from two north American Rhus species and phylogenomics of Anacardiaceae

Background: The suamc genus Rhus (sensu stricto) includes two subgenera, Lobadium (ca. 25 spp.) and Rhus (ca. 10 spp.). Their members, R. glabra and R. typhina (Rosanae: Sapindales: Anacardiaceae), are two economic important species. Chloroplast genome information is of great significance for the study of plant phylogeny and taxonomy. Results: The three complete chloroplast genomes from two Rhus glabra and one R. typhina accessions were obtained with a total of each about 159k bp in length including a large single-copy region (LSC, about 88k bp), a small single-copy regions (SSC, about 19k bp) and a pair of inverted repeats regions (IRa/IRb, about 26k bp), to form a canonical quadripartite structure. Each genome contained 88 protein-coding genes, 37 transfer RNA genes, eight ribosomal RNA genes and two pseudogenes. The overall GC content of the three genomes all were same (37.8%), and RSCU values showed that they all had the same codon prefers, i.e., to use codon ended with A/U (93%) except termination codon. Three variable hotspots, i.e., ycf4-cemA, ndhF-rpl32-trnL and ccsA-ndhD, and a total of 152–156 simple sequence repeats (SSR) were identified. The nonsynonymous (Ka)/synonymous (Ks) ratio was calculated, and cemA and ycf2 genes are important indicators of gene evolution. The phylogenetic analyses of the family Anacardiaceae showed that the eight genera were grouped into three clusters, and supported the monophyly of the subfamilies and all the genera. The accessions of five Rhus species formed four clusters, while, one individual of R. typhina grouped with the R. glabra accessions instead of clustering into the two other individuals of R. typhina in the subgenus Rhus, which showed a paraphyletic relationship. Conclusions: Comparing the complete chloroplast genomes of the Rhus species, it was found that most SSRs were A/T rich and located in the intergenic spacer, and the nucleotide divergence exhibited higher levels in the non-coding region than in the coding region. The Ka/Ks ratio of cemA gene was > 1 for species collected in America, while it was < 1 for other species in China, which dedicated that the Rhus species from North America and East Asia have different evolutionary pressure. The phylogenetic analysis of the complete chloroplast genome clarified the Rhus placement and relationship. The results obtained in this study are expected to provide valuable genetic resources to perform species identification, molecular breeding, and intraspecific diversity of the Rhus speciesThis work was supported by the National Natural Science Foundation of China (31870366), Shanxi International Science and Technology Cooperation Project (201803D421051), Research Project Supported by Shanxi Scholarship Council of China (2020-018), the National High Technology Research and Development “863” Program (2014AA021802