Promoting cold-start items in recommender systems

As one of major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, so-called the item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. To our surprise, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs.Comment: 6 pages, 6 figure

OptSample: A Resilient Buffer Management Policy for Robotic Systems based on Optimal Message Sampling

Modern robotic systems have become an alternative to humans to perform risky or exhausting tasks. In such application scenarios, communications between robots and the control center have become one of the major problems. Buffering is a commonly used solution to relieve temporary network disruption. But the assumption that newer messages are more valuable than older ones is not true for many application scenarios such as explorations, rescue operations, and surveillance. In this paper, we proposed a novel resilient buffer management policy named OptSample. It can uniformly sampling messages and dynamically adjust the sample rate based on run-time network situation. We define an evaluation function to estimate the profit of a message sequence. Based on the function, our analysis and simulation shows that the OptSample policy can effectively prevent losing long segment of continuous messages and improve the overall profit of the received messages. We implement the proposed policy in ROS. The implementation is transparent to user and no user code need to be changed. Experimental results on several application scenarios show that the OptSample policy can help robotic systems be more resilient against network disruption

Semantic-Aware Transformation-Invariant RoI Align

Great progress has been made in learning-based object detection methods in the last decade. Two-stage detectors often have higher detection accuracy than one-stage detectors, due to the use of region of interest (RoI) feature extractors which extract transformation-invariant RoI features for different RoI proposals, making refinement of bounding boxes and prediction of object categories more robust and accurate. However, previous RoI feature extractors can only extract invariant features under limited transformations. In this paper, we propose a novel RoI feature extractor, termed Semantic RoI Align (SRA), which is capable of extracting invariant RoI features under a variety of transformations for two-stage detectors. Specifically, we propose a semantic attention module to adaptively determine different sampling areas by leveraging the global and local semantic relationship within the RoI. We also propose a Dynamic Feature Sampler which dynamically samples features based on the RoI aspect ratio to enhance the efficiency of SRA, and a new position embedding, \ie Area Embedding, to provide more accurate position information for SRA through an improved sampling area representation. Experiments show that our model significantly outperforms baseline models with slight computational overhead. In addition, it shows excellent generalization ability and can be used to improve performance with various state-of-the-art backbones and detection methods

Linking ecology to genetics to better understand adaptation and evolution: a review in marine macrophytes

Ecological processes and intra-specific genetic diversity reciprocally affect each other. While the importance of uniting ecological variables and genetic variation to understand species’ plasticity, adaptation, and evolution is increasingly recognized, only few studies have attempted to address the intersection of population ecology and genetics using marine macrophyte as models. Representative empirical case studies on genetic diversity are reviewed that explore ecological and evolutionary processes in marine macrophytes. These include studies on environment-induced phenotypic plasticity and associated ecological adaptation; population genetic variation and structuring driven by ecological variation; and ecological consequences mediated by intraspecific and interspecific diversity. Knowledge gaps are also discussed that impede the connection of ecology and genetics in macrophytes and possible approaches to address these issues. Finally, an eco-evolutionary perspective is advocated, by incorporating structural-tofunctional genomics and life cycle complexity, to increase the understanding of the adaptation and evolution of macrophytes in response to environmental heterogeneity.info:eu-repo/semantics/publishedVersio

Privacy-preserving federated deep learning for cooperative hierarchical caching in fog computing

Over the past few years, Fog Radio Access Networks (F-RANs) have become a promising paradigm to support the tremendously increasing demands of multimedia services, by pushing computation and storage functionalities towards the edge of networks, closer to users. In F-RANs, distributed edge caching among Fog Access Points (F-APs) can effectively reduce network traffic and service latency as it places popular contents at local caches of F-APs rather than the remote cloud. Due to the limited caching resources of F-APs and spatio-temporally fluctuant content demands from users, many cooperative caching schemes were designed to decide which contents are popular and how to cache them. However, these approaches often collect and analyse the data from Internet-of-Things (IoT) devices at a central server to predict the content popularity for caching, which raises serious privacy issues. To tackle this challenge, we propose a Federated Learning based Cooperative Hierarchical Caching scheme (FLCH), which keeps data locally and employs IoT devices to train a shared learning model for content popularity prediction. FLCH exploits horizontal cooperation between neighbour F-APs and vertical cooperation between the BaseBand Unit (BBU) pool and F-APs to cache contents with different degrees of popularity. Moreover, FLCH integrates a differential privacy mechanism to achieve a strict privacy guarantee. Experimental results demonstrate that FLCH outperforms five important baseline schemes in terms of the cache hit ratio, while preserving data privacy. Moreover, the results show the effectiveness of the proposed cooperative hierarchical caching mechanism for FLCH

Prevalence of non-alcoholic fatty liver disease and its relation to hypoadiponectinaemia in the middle-aged and elderly Chinese population

Introduction: Hypoadiponectinaemia is an important risk factor for non-alcoholic fatty liver disease (NAFLD). However, little is known about its role in the Chinese population. This study sought to assess the prevalence of NAFLD and its association with hypoadiponectinaemia in middle-aged and elderly Chinese. Material and methods: We conducted a population-based cross-sectional study in an urban Shanghai sample of 2201 participants age 50 years to 83 years (973 men, 1228 women). Hepatic ultrasonographic examination was performed for all participants. Serum adiponectin concentrations were measured by ELISA methods. Results: The prevalence of NAFLD was 19.8% (16.0% in men, 22.8% in women). Serum adiponectin levels were significantly higher in female than in male subjects (p < 0.001). Serum adiponectin levels were significantly lower in NAFLD subjects than those in control subjects (p < 0.001). The prevalence of NAFLD progressively increased with declining adiponectin levels (p(for) (trend) < 0.001). The participants in the lowest adiponectin quartile had a significantly increased risk for acquiring NAFLD (OR = 2.31, 95% CI 1.72-3.15) after adjustment for potential confounders. Conclusions: Population-based screening suggests that NAFLD is highly prevalent in middle-aged and elderly people in Shanghai, particularly among women. Serum adiponectin level is negatively associated with NAFLD independently of potential cofounders, indicating that hypoadiponectinaemia may contribute to the development of NAFLD

MtDNA-Based Phylogeography of the Red Alga Agarophyton vermiculophyllum (Gigartinales, Rhodophyta) in the Native Northwest Pacific

The repeated transgression and regression of coastlines mediated by the late Quaternary glacial–interglacial cycles make the northwest Pacific a hot spot to study marine speciation and population diversity. The red alga Agarophyton vermiculophyllum is an ecologically important species native to the northwest Pacific, capturing considerable research interest due to its wide-range invasiveness in Europe and North America. However, the knowledge of phylogeographic structure and intraspecific genetic diversity across the entire native range was still scarce. Here, we used 1,214-bp of mitochondrial cytochrome c oxidase subunit 1 (cox1) to explore phylogeographic patterns, lineage structure, and population genetic differentiation of 48 A. vermiculophyllum populations in the northwest Pacific. Our DNA data revealed overall high haplotype diversity and low nucleotide diversity and five phylogeographically structured genetic lineages that diverged significantly from each other. S-DIVA analysis showed the ancestors of A. vermiculophyllum originating from multiple areas encompassing the Japan–Pacific coast, East and South China Seas. This combined evidence indicates that A. vermiculophyllum might have survived in multiple scattered glacial refugia during the late Quaternary climate oscillations in the northwest Pacific. Such knowledge may help to better understand how palaeoclimate interacted with contemporary environments to contribute to intraspecific genetic variation and provide a new perspective for conserving natural resource of A. vermiculophyllum in the northwest Pacific

Timing Is Critical for an Effective Anti-Metastatic Immunotherapy: The Decisive Role of IFNγ/STAT1-Mediated Activation of Autophagy

BACKGROUND: Immunotherapy is often recommended as an adjuvant treatment to reduce the chance of cancer recurrence or metastasis. Interestingly, timing is very important for a successful immunotherapy against metastasis, although the precise mechanism is still unknown. METHODS AND FINDINGS: Using a mouse model of melanoma metastasis induced by intravenous injection of B16-F10 cells, we investigated the mechanism responsible for the diverse efficacy of the prophylactic or therapeutic TLR4 and TLR9 agonist complex against metastasis. We found that the activation of TLR4 and TLR9 prevented, but did not reverse, metastasis because the potency of this combination was neither sufficient to overcome the tumor cell-educated immune tolerance nor to induce efficacious autophagy in tumor cells. The prophylactic application of the complex promoted antimetastatic immunity, leading to the autophagy-associated death of melanoma cells via IFNγ/STAT1 activation and attenuated tumor metastasis. IFNγ neutralization reversed the prophylactic benefit induced by the complex by suppressing STAT1 activation and attenuating autophagy in mice. However, the therapeutic application of the complex did not suppress metastasis because the complex could not reverse tumor cell-induced STAT3 activation and neither activate IFNγ/STAT1 signaling and autophagy. Suppressing STAT3 activation with the JAK/STAT antagonist AG490 restored the antimetastatic effect of the TLR4/9 agonist complex. Activation of autophagy after tumor inoculation by using rapamycin, with or without the TLR4/9 agonist complex, could suppress metastasis. CONCLUSION AND SIGNIFICANCE: Our studies suggest that activation of IFNγ/STAT1 signaling and induction of autophagy are critical for an efficacious anti-metastatic immunotherapy and that autophagy activators may overcome the timing barrier for immunotherapy against metastasis

The Positive Effect of Moderate-Intensity Exercise on the Mirror Neuron System: An fNIRS Study

A growing number of studies have reported the beneficial effect of exercise on human social behavior. The mirror neuron system (MNS) plays a critical role in a variety of social behaviors from imitation to empathy. However, neuroimaging investigations into the effects of exercise on the MNS remain unexplored. To address this question, our study determined the effect of moderate-intensity exercise on the MNS using functional near-infrared spectroscopy (fNIRS). Specifically, 23 right-handed young individuals were asked to perform a table-setting task that included action execution and action observation before and after a 25-min exercise session on a cycle ergometer at moderate intensity (65% VO2peak). The control condition was the same task performed without exercise. Cortical hemodynamic changes in the four primary brain regions of the MNS were monitored with fNIRS, using a modified probe configuration that covered all four MNS regions in the left hemisphere. We used a region of interest (ROI)-based group analysis to determine which regions were activated during action execution and action observation. Following a session of moderate-intensity exercise, we found a significant increase in activation in all four MNS regions, namely the inferior frontal gyrus (IFG), premotor cortex (PMC), superior parietal lobule (SPL), and rostral inferior parietal lobule (IPL). This result indicated a positive effect of exercise on the MNS, specifically that moderate-intensity exercise could activate the MNS

Adaptation of temperate seagrass to Arctic light relies on seasonal acclimatization of carbon capture and metabolism

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