MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed

Nowadays, the mainstream approach in position allocation system is to utilize a reinforcement learning model to allocate appropriate locations for items in various channels and then mix them into the feed. There are two types of data employed to train reinforcement learning (RL) model for position allocation, named strategy data and random data. Strategy data is collected from the current online model, it suffers from an imbalanced distribution of state-action pairs, resulting in severe overestimation problems during training. On the other hand, random data offers a more uniform distribution of state-action pairs, but is challenging to obtain in industrial scenarios as it could negatively impact platform revenue and user experience due to random exploration. As the two types of data have different distributions, designing an effective strategy to leverage both types of data to enhance the efficacy of the RL model training has become a highly challenging problem. In this study, we propose a framework named Multi-Distribution Data Learning (MDDL) to address the challenge of effectively utilizing both strategy and random data for training RL models on mixed multi-distribution data. Specifically, MDDL incorporates a novel imitation learning signal to mitigate overestimation problems in strategy data and maximizes the RL signal for random data to facilitate effective learning. In our experiments, we evaluated the proposed MDDL framework in a real-world position allocation system and demonstrated its superior performance compared to the previous baseline. MDDL has been fully deployed on the Meituan food delivery platform and currently serves over 300 million users.Comment: 4 pages, 2 figures, accepted by SIGIR 202

Rethink Baseline of Integrated Gradients from the Perspective of Shapley Value

Numerous approaches have attempted to interpret deep neural networks (DNNs) by attributing the prediction of DNN to its input features. One of the well-studied attribution methods is Integrated Gradients (IG). Specifically, the choice of baselines for IG is a critical consideration for generating meaningful and unbiased explanations for model predictions in different scenarios. However, current practice of exploiting a single baseline fails to fulfill this ambition, thus demanding multiple baselines. Fortunately, the inherent connection between IG and Aumann-Shapley Value forms a unique perspective to rethink the design of baselines. Under certain hypothesis, we theoretically analyse that a set of baseline aligns with the coalitions in Shapley Value. Thus, we propose a novel baseline construction method called Shapley Integrated Gradients (SIG) that searches for a set of baselines by proportional sampling to partly simulate the computation path of Shapley Value. Simulations on GridWorld show that SIG approximates the proportion of Shapley Values. Furthermore, experiments conducted on various image tasks demonstrate that compared to IG using other baseline methods, SIG exhibits an improved estimation of feature's contribution, offers more consistent explanations across diverse applications, and is generic to distinct data types or instances with insignificant computational overhead.Comment: 12 page

The GATA factor HANABA TARANU promotes runner formation by regulating axillary bud initiation and outgrowth in cultivated strawberry

A runner, as an elongated branch, develops from the axillary bud (AXB) in the leaf axil and is crucial for the clonal propagation of cultivated strawberry (Fragaria x ananassa Duch.). Runner formation occurs in at least two steps: AXB initiation and AXB outgrowth. HANABA TARANU (HAN ) encodes a GATA transcription factor that affects AXB initiation in Arabidopsis and promotes branching in grass species, but the underlying mechanism is largely unknown. Here, the function of a strawberry HAN homolog FaHAN in runner formation was characterized. FaHAN transcripts can be detected in the leaf axils. Overexpression (OE) of FaHAN increased the number of runners, mainly by enhancing AXB outgrowth, in strawberry. The expression of the strawberry homolog of BRANCHED1 , a key inhibitor of AXB outgrowth in many plant species, was significantly downregulated in the AXBs of FaHAN -OE lines, whereas the expression of the strawberry homolog of SHOOT MERISTEMLESS, a marker gene for AXB initiation in Arabidopsis, was upregulated. Moreover, several genes of gibberellin biosynthesis and cytokinin signaling pathways were activated, whereas the auxin response pathway genes were repressed. Further assays indicated that FaHAN could be directly activated by FaNAC2, the overexpression of which in strawberry also increased the number of runners. The silencing of FaNAC2 or FaHAN inhibited AXB initiation and led to a higher proportion of dormant AXBs, confirming their roles in the control of runner formation. Taken together, our results revealed a FaNAC2-FaHAN pathway in the control of runner formation and have provided a means to enhance the vegetative propagation of cultivated strawberry.Peer reviewe

Evaluation of Alpha-Ketoglutarate Supplementation on the Improvement of Intestinal Antioxidant Capacity and Immune Response in Songpu Mirror Carp (Cyprinus carpio) After Infection With Aeromonas hydrophila

As an intermediate substance of the tricarboxylic acid cycle and a precursor substance of glutamic acid synthesis, the effect of alpha-ketoglutarate on growth and protein synthesis has been extensively studied. However, its prevention and treatment of pathogenic bacteria and its mechanism have not yet been noticed. To evaluate the effects of alpha-ketoglutarate on intestinal antioxidant capacity and immune response of Songpu mirror carp, a total of 360 fish with an average initial weight of 6.54 ± 0.08 g were fed diets containing alpha-ketoglutarate with 1% for 8 weeks. At the end of the feeding trial, the fish were challenged with Aeromonas hydrophila for 2 weeks. The results indicated that alpha-ketoglutarate supplementation significantly increased the survival rate of carp after infection with Aeromonas hydrophila (P < 0.05), and the contents of immune digestion enzymes including lysozyme, alkaline phosphatase and the concentration of complement C4 were markedly enhanced after alpha-ketoglutarate supplementation (P < 0.05). Also, appropriate alpha-ketoglutarate increased the activities of total antioxidant capacity and catalase and prevented the up-regulation in the mRNA expression levels of pro-inflammatory cytokines including tumor necrosis factor-α, interleukin-1β, interleukin-6, and interleukin-8 (P < 0.05). Furthermore, the mRNA expression levels of toll-like receptor 4 (TLR4), and nuclear factor kappa-B (NF-κB) were strikingly increased after infection with Aeromonas hydrophila (P < 0.05), while the TLR4 was strikingly decreased with alpha-ketoglutarate supplementation (P < 0.05). Moreover, the mRNA expression levels of tight junctions including claudin-1, claudin-3, claudin-7, claudin-11 and myosin light chain kinases (MLCK) were upregulated after alpha-ketoglutarate supplementation (P < 0.05). In summary, the appropriate alpha-ketoglutarate supplementation could increase survival rate, strengthen the intestinal enzyme immunosuppressive activities, antioxidant capacities and alleviate the intestinal inflammation, thereby promoting the intestinal immune responses and barrier functions of Songpu mirror carp via activating TLR4/MyD88/NF-κB and MLCK signaling pathways after infection with Aeromonas hydrophila

Searching for Black Hole Candidates by LAMOST and ASAS-SN

Most dynamically confirmed stellar-mass black holes (BHs) and their candidates were originally selected from X-ray outbursts. In the present work, we search for BH candidates in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey using the spectra along with photometry from the All Sky Automated Survey for SuperNovae (ASAS-SN), where the orbital period of the binary may be revealed by the periodic light curve, such as the ellipsoidal modulation type. Our sample consists of nine binaries, where each source contains a giant star with large radial velocity variation (ΔV_R ≳ 70 km s^(-1)) and periods known from light curves. We focus on the nine sources with long periods (T_(ph) > 5 days) and evaluate the mass M_2 of the optically invisible companion. Since the observed ΔV_R from only a few repeating spectroscopic observations is a lower limit of the real amplitude, the real mass M_2 can be significantly higher than the current evaluation. It is likely an efficient method to place constraints on M 2 by combining ΔV_R from LAMOST and T_(ph) from ASAS-SN, particularly by the ongoing LAMOST Medium Resolution Survey

Transcriptomic analyses of regenerating adult feathers in chicken

Transcriptome Expression Data. Table of mapped reads to Galgal4 transcripts for all 15 data sets. FPKM (Fragments per kilobase of exon per million fragments mapped): normalized transcript abundance values for each gene in the indicated tissues. (CSV 1314 kb

In situ interface engineering for probing the limit of quantum dot photovoltaic devices.

Quantum dot (QD) photovoltaic devices are attractive for their low-cost synthesis, tunable band gap and potentially high power conversion efficiency (PCE). However, the experimentally achieved efficiency to date remains far from ideal. Here, we report an in-situ fabrication and investigation of single TiO2-nanowire/CdSe-QD heterojunction solar cell (QDHSC) using a custom-designed photoelectric transmission electron microscope (TEM) holder. A mobile counter electrode is used to precisely tune the interface area for in situ photoelectrical measurements, which reveals a strong interface area dependent PCE. Theoretical simulations show that the simplified single nanowire solar cell structure can minimize the interface area and associated charge scattering to enable an efficient charge collection. Additionally, the optical antenna effect of nanowire-based QDHSCs can further enhance the absorption and boost the PCE. This study establishes a robust 'nanolab' platform in a TEM for in situ photoelectrical studies and provides valuable insight into the interfacial effects in nanoscale solar cells

Searching for Black Hole Candidates by LAMOST and ASAS-SN

Most dynamically confirmed stellar-mass black holes (BHs) and their candidates were originally selected from X-ray outbursts. In the present work, we search for BH candidates in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey using the spectra along with photometry from the All Sky Automated Survey for SuperNovae (ASAS-SN), where the orbital period of the binary may be revealed by the periodic light curve, such as the ellipsoidal modulation type. Our sample consists of nine binaries, where each source contains a giant star with large radial velocity variation (ΔV_R ≳ 70 km s^(-1)) and periods known from light curves. We focus on the nine sources with long periods (T_(ph) > 5 days) and evaluate the mass M_2 of the optically invisible companion. Since the observed ΔV_R from only a few repeating spectroscopic observations is a lower limit of the real amplitude, the real mass M_2 can be significantly higher than the current evaluation. It is likely an efficient method to place constraints on M 2 by combining ΔV_R from LAMOST and T_(ph) from ASAS-SN, particularly by the ongoing LAMOST Medium Resolution Survey