One dimensional terpyridine-based metal organic framework for stable supercapacitor

In summary, a novel structure of MOF based on 1,4–di ([2,2':6',2''terpyridin] -4'-yl)benzene and 1,4-naphthalenedicarboxylic acid has been constructed through hydrothermal reaction. The Ni-MOF displays one dimensional zigzag chain, which connect each other by hydrogen bonding to form three dimensional supramolecule with large channels. The conjugated systems of the terpyridin and benzene ligands enhance the chain rigidity, accelerate the electron transport. The massive channels provides electrolyte rapid transfer. By the structural feature aforementioned, the Ni-MOF demonstrates stable electrochemical performance as suprocapacitor

Interpretable Math Word Problem Solution Generation Via Step-by-step Planning

Solutions to math word problems (MWPs) with step-by-step explanations are valuable, especially in education, to help students better comprehend problem-solving strategies. Most existing approaches only focus on obtaining the final correct answer. A few recent approaches leverage intermediate solution steps to improve final answer correctness but often cannot generate coherent steps with a clear solution strategy. Contrary to existing work, we focus on improving the correctness and coherence of the intermediate solutions steps. We propose a step-by-step planning approach for intermediate solution generation, which strategically plans the generation of the next solution step based on the MWP and the previous solution steps. Our approach first plans the next step by predicting the necessary math operation needed to proceed, given history steps, then generates the next step, token-by-token, by prompting a language model with the predicted math operation. Experiments on the GSM8K dataset demonstrate that our approach improves the accuracy and interpretability of the solution on both automatic metrics and human evaluation.Comment: Accepted to The 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023

Doping-free complementary WSe2 circuit via van der Waals metal integration.

Two-dimensional (2D) semiconductors have attracted considerable attention for the development of ultra-thin body transistors. However, the polarity control of 2D transistors and the achievement of complementary logic functions remain critical challenges. Here, we report a doping-free strategy to modulate the polarity of WSe2 transistors using same contact metal but different integration methods. By applying low-energy van der Waals integration of Au electrodes, we observed robust and optimized p-type transistor behavior, which is in great contrast to the transistors fabricated on the same WSe2 flake using conventional deposited Au contacts with pronounced n-type characteristics. With the ability to switch majority carrier type and to achieve optimized contact for both electrons and holes, a doping-free logic inverter is demonstrated with higher voltage gain of 340, at the bias voltage of 5.5 V. Furthermore, the simple polarity control strategy is extended for realizing more complex logic functions such as NAND and NOR

Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting

Traffic forecasting is of great importance to transportation management and public safety, and very challenging due to the complicated spatial-temporal dependency and essential uncertainty brought about by the road network and traffic conditions. Latest studies mainly focus on modeling the spatial dependency by utilizing graph convolutional networks (GCNs) throughout a fixed weighted graph. However, edges, i.e., the correlations between pair-wise nodes, are much more complicated and interact with each other. In this paper, we propose the Multi-Range Attentive Bicomponent GCN (MRA-BGCN), a novel deep learning model for traffic forecasting. We first build the node-wise graph according to the road network distance and the edge-wise graph according to various edge interaction patterns. Then, we implement the interactions of both nodes and edges using bicomponent graph convolution. The multi-range attention mechanism is introduced to aggregate information in different neighborhood ranges and automatically learn the importance of different ranges. Extensive experiments on two real-world road network traffic datasets, METR-LA and PEMS-BAY, show that our MRA-BGCN achieves the state-of-the-art results.Comment: Accepted by AAAI 202

Comparative Analysis of Complete Chloroplast Genomes of Nine Species of Litsea (Lauraceae): Hypervariable Regions, Positive Selection, and Phylogenetic Relationships

Litsea is a group of evergreen trees or shrubs in the laurel family, Lauraceae. Species of the genus are widely used for a wide range of medicinal and industrial aspects. At present, most studies related to the gene resources of Litsea are restricted to morphological analyses or features of individual genomes, and currently available studies of select molecular markers are insufficient. In this study, we assembled and annotated the complete chloroplast genomes of nine species in Litsea, carried out a series of comparative analyses, and reconstructed phylogenetic relationships within the genus. The genome length ranged from 152,051 to 152,747 bp and a total of 128 genes were identified. High consistency patterns of codon bias, repeats, divergent analysis, single nucleotide polymorphisms (SNP) and insertions and deletions (InDels) were discovered across the genus. Variations in gene length and the presence of the pseudogene ycf1Ψ, resulting from IR contraction and expansion, are reported. The hyper-variable gene rpl16 was identified for its exceptionally high Ka/Ks and Pi values, implying that those frequent mutations occurred as a result of positive selection. Phylogenetic relationships were recovered for the genus based on analyses of full chloroplast genomes and protein-coding genes. Overall, both genome sequences and potential molecular markers provided in this study enrich the available genomic resources for species of Litsea. Valuable genomic resources and divergent analysis are also provided for further research of the evolutionary patterns, molecular markers, and deeper phylogenetic relationships of Litsea

Effect of potential pathogenic gene PDX1 variants of total anomalous pulmonary venous connection on its gene function

Objective·To explore the possible pathogenic gene of total anomalous pulmonary venous connection (TAPVC) by whole exon sequencing and verify its function.Methods·One hundred TAPVC children (case group) and one hundred and twenty healthy children (control group) in Xinhua Hospital and Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine from 2014 to 2019 were included. The blood samples from the two groups of children were collected, and whole blood genomic DNA was extracted for exon sequencing to screen out the potential pathogenic genes of TAPVC. Harmful mutation sites of pathogenic genes were screened through Mutation Taster, SIFT and PolyPhen-2 websites, and then conducted by Sanger sequencing. The wild-type (wild-type group) and mutant (mutant group) plasmids of PDX1 were transfected into HUVEC cells. Quantitative real-time PCR (qPCR) and Western blotting were used to detect the effects of mutations on mRNA and protein levels of PDX1, respectively. The STRING database was used to analyze the interaction between proteins, and qPCR was used to determine the expressions of downstream genes regulated by PDX1.Results·Pathogenic PDX1 was found in TAPVC children, and Sanger sequencing revealed two novel variants in the gene: c.C237A (P33T) and c. C237G (P33A). Compared with the wild-type group, there was no significant difference in PDX1 mRNA levels in the two mutant groups, but there was a significant increase in relative protein expression of the CA group and CG group, which was 2.9 and 3.4 times higher than the wild-type group, respectively (P=0.000, P=0.001). Protein interaction analysis demonstrated that PDX1 was associated with SOX17. qPCR results showed that overexpression of PDX1 could downregulate the expression of SOX17 in HUVEC.Conclusion·The two novel PDX1 missense mutations can affect the process of PDX1 post-transcriptional translation, indicating that PDX1 may participate in the occurrence and development of TAPVC by regulating SOX17

Granular risk assessment of earthquake induced landslide via latent representations of stacked autoencoder

Earthquake-induced landslides are ubiquitous on slopes in terrestrial environments, which can pose a serious threat to local communities and infrastructures. Data-driven landslide assessments play a crucial role in preventing future landslide occurrences and recurrences. We present a novel granular computing approach that assesses landslide risk by combining fuzzy information granulation and a stacked autoencoder algorithm. The stacked autoencoder is trained using an end-to-end learning strategy to obtain a central latent vector with reduced dimensionality. The multivariate landslide dataset was used as both the input and output to train the stacked autoencoder algorithm. Subsequently, in the central latent vector of the stacked autoencoder, the Fuzzy C-means clustering algorithm was applied to cluster the landslides into various groups with different risk levels, and the intervals for each group were computed using the granular computing approach. An empirical case study in Wenchuan County, Sichuan, China, was conducted. A comparative analysis with other state-of-the-art approaches including Density-based spatial clustering of applications with noise (DBSCAN), K-means clustering, and Principal Component Analysis (PCA), is provided and discussed. The experimental results demonstrate that the proposed approach using a stacked autoencoder integrated with fuzzy information granulation provides superior performance compared to those by other state-of-the-art approaches, and is capable of studying deep patterns in earthquake-induced landslide datasets and provides sufficient interpretation for field engineers

A control method for the single-phase three-leg unified power quality conditioner without a phase-locked loop

The single-phase three-leg unified power quality conditioner (UPQC) can achieve the functions of voltage compensation, reactive power compensation, and harmonic compensation. However, traditional control algorithms require a phase-locked loop to obtain the real-time phase angle of the grid voltage, which undoubtedly increases algorithm complexity. To simplify the phase-locked calculation, this paper proposes a control method without the phase-locked loop for the single-phase three-leg UPQC. In the proposed scheme, the instantaneous value of the grid voltage is employed to realize the grid integration control. Then, the load voltage reference is calculated in real time using a second-order generalized integrator. Moreover, a simple algorithm for reactive power and harmonic compensation is discussed, further simplifying the control algorithm. Finally, a small-scale experimental platform is built, and the effectiveness of the proposed method is verified by the experimental results