Diffusion Augmentation for Sequential Recommendation

Sequential recommendation (SRS) has become the technical foundation in many applications recently, which aims to recommend the next item based on the user's historical interactions. However, sequential recommendation often faces the problem of data sparsity, which widely exists in recommender systems. Besides, most users only interact with a few items, but existing SRS models often underperform these users. Such a problem, named the long-tail user problem, is still to be resolved. Data augmentation is a distinct way to alleviate these two problems, but they often need fabricated training strategies or are hindered by poor-quality generated interactions. To address these problems, we propose a Diffusion Augmentation for Sequential Recommendation (DiffuASR) for a higher quality generation. The augmented dataset by DiffuASR can be used to train the sequential recommendation models directly, free from complex training procedures. To make the best of the generation ability of the diffusion model, we first propose a diffusion-based pseudo sequence generation framework to fill the gap between image and sequence generation. Then, a sequential U-Net is designed to adapt the diffusion noise prediction model U-Net to the discrete sequence generation task. At last, we develop two guide strategies to assimilate the preference between generated and origin sequences. To validate the proposed DiffuASR, we conduct extensive experiments on three real-world datasets with three sequential recommendation models. The experimental results illustrate the effectiveness of DiffuASR. As far as we know, DiffuASR is one pioneer that introduce the diffusion model to the recommendation

RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN

The second-order training methods can converge much faster than first-order optimizers in DNN training. This is because the second-order training utilizes the inversion of the second-order information (SOI) matrix to find a more accurate descent direction and step size. However, the huge SOI matrices bring significant computational and memory overheads in the traditional architectures like GPU and CPU. On the other side, the ReRAM-based process-in-memory (PIM) technology is suitable for the second-order training because of the following three reasons: First, PIM's computation happens in memory, which reduces data movement overheads; Second, ReRAM crossbars can compute SOI's inversion in $O\left(1\right)$ time; Third, if architected properly, ReRAM crossbars can perform matrix inversion and vector-matrix multiplications which are important to the second-order training algorithms. Nevertheless, current ReRAM-based PIM techniques still face a key challenge for accelerating the second-order training. The existing ReRAM-based matrix inversion circuitry can only support 8-bit accuracy matrix inversion and the computational precision is not sufficient for the second-order training that needs at least 16-bit accurate matrix inversion. In this work, we propose a method to achieve high-precision matrix inversion based on a proven 8-bit matrix inversion (INV) circuitry and vector-matrix multiplication (VMM) circuitry. We design \archname{}, a ReRAM-based PIM accelerator architecture for the second-order training. Moreover, we propose a software mapping scheme for \archname{} to further optimize the performance by fusing VMM and INV crossbar. Experiment shows that \archname{} can achieve an average of 115.8$\times$/11.4$\times$ speedup and 41.9$\times$/12.8$\times$energy saving compared to a GPU counterpart and PipeLayer on large-scale DNNs.Comment: 13pages, 13 figure

2D materials for conducting holes from grain boundaries in perovskite solar cells

Grain boundaries in organic-inorganic halide perovskite solar cells (PSCs) have been found to be detrimental to the photovoltaic performance of devices. Here, we develop a unique approach to overcome this problem by modifying the edges of perovskite grain boundaries with flakes of high-mobility two-dimensional (2D) materials via a convenient solution process. A synergistic effect between the 2D flakes and perovskite grain boundaries is observed for the first time, which can significantly enhance the performance of PSCs. We find that the 2D flakes can conduct holes from the grain boundaries to the hole transport layers in PSCs, thereby making hole channels in the grain boundaries of the devices. Hence, 2D flakes with high carrier mobilities and short distances to grain boundaries can induce a more pronounced performance enhancement of the devices. This work presents a cost-effective strategy for improving the performance of PSCs by using high-mobility 2D materials

The water lily genome and the early evolution of flowering plants

Water lilies belong to the angiosperm order Nymphaeales. Amborellales, Nymphaeales and Austrobaileyales together form the so-called ANA-grade of angiosperms, which are extant representatives of lineages that diverged the earliest from the lineage leading to the extant mesangiosperms1–3. Here we report the 409-megabase genome sequence of the blue-petal water lily (Nymphaea colorata). Our phylogenomic analyses support Amborellales and Nymphaeales as successive sister lineages to all other extant angiosperms. The N. colorata genome and 19 other water lily transcriptomes reveal a Nymphaealean whole-genome duplication event, which is shared by Nymphaeaceae and possibly Cabombaceae. Among the genes retained from this whole-genome duplication are homologues of genes that regulate flowering transition and flower development. The broad expression of homologues of floral ABCE genes in N. colorata might support a similarly broadly active ancestral ABCE model of floral organ determination in early angiosperms. Water lilies have evolved attractive floral scents and colours, which are features shared with mesangiosperms, and we identified their putative biosynthetic genes in N. colorata. The chemical compounds and biosynthetic genes behind floral scents suggest that they have evolved in parallel to those in mesangiosperms. Because of its unique phylogenetic position, the N. colorata genome sheds light on the early evolution of angiosperms.Supplementary Tables: This file contains Supplementary Tables 1-21.National Natural Science Foundation of China, the open funds of the State Key Laboratory of Crop Genetics and Germplasm Enhancement (ZW201909) and State Key Laboratory of Tree Genetics and Breeding, the Fujian provincial government in China, the European Union Seventh Framework Programme (FP7/2007-2013) under European Research Council Advanced Grant Agreement and the Special Research Fund of Ghent University.http://www.nature.com/naturecommunicationsam2021BiochemistryGeneticsMicrobiology and Plant Patholog

Synthesis of ethyl 4-(2-fluoro-4-nitrophenoxy) picolinate

Cancer has seriously affected people's production and life. The appearance of anti-cancer drugs has brought good news to people. Ethyl 4-(2-fluoro-4-nitrophenoxy) picolinate is an important basic skeleton of a small molecule inhibitor of c-Met and a major intermediate in cancer therapy. A rapid and efficient method for the synthesis of compound 8 was established. Compound 8 was synthesized from picolinic acid by acylation and substitution. These steps were weight gain reaction. The synthesis method was optimized and the structure was confirmed by hydrogen NMR spectroscopy

Synthesis of ethyl 4-(2-fluoro-4-nitrophenoxy) picolinate

Cancer has seriously affected people's production and life. The appearance of anti-cancer drugs has brought good news to people. Ethyl 4-(2-fluoro-4-nitrophenoxy) picolinate is an important basic skeleton of a small molecule inhibitor of c-Met and a major intermediate in cancer therapy. A rapid and efficient method for the synthesis of compound 8 was established. Compound 8 was synthesized from picolinic acid by acylation and substitution. These steps were weight gain reaction. The synthesis method was optimized and the structure was confirmed by hydrogen NMR spectroscopy

Design, Synthesis, Activity and Docking Study of Sorafenib Analogs Bearing Sulfonylurea Unit

Two series of novel sorafenib analogs containing a sulfonylurea unit were synthesized and their chemical structures were confirmed by 1H-NMR, 13C-NMR, MS spectrum and elemental analysis. The synthesized compounds were evaluated for the cytotoxicity against A549, Hela, MCF-7, and PC-3 cancer cell lines. Some of the compounds showed moderate cytotoxic activity, especially compounds 1-(2,4-difluorophenylsulfonyl)-3-(4-(2-(methylcarbamoyl)pyridin-4-yloxy)phenyl)urea (6c) and 1-(4-bromophenylsulfonyl)-3-(4-(2-(methylcarbamoyl)pyridin-4-yloxy)phenyl)urea (6f) with the IC50 values against four cancer cell lines ranging from 16.54 ± 1.22 to 63.92 ± 1.81 μM, respectively. Inhibitory rates against vascular endothelial growth factor receptor-2 (VEGFR2/KDR) kinase at 10 μM of target compounds were further carried out in this paper in order to investigate the target of these compounds. Structure-activity relationships (SARs) and docking studies indicated that the sulfonylurea unit was important to these kinds of compounds. None of the substitutions in the phenoxy group and small halogen atoms such as 2,4-difluoro substitution of the aryl group contributed to the activity. The results suggested that sulfonylurea sorafenib analogs are worthy of further study