Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems

Designing an e-commerce recommender system that serves hundreds of millions of active users is a daunting challenge. From a human vision perspective, there're two key factors that affect users' behaviors: items' attractiveness and their matching degree with users' interests. This paper proposes Telepath, a vision-based bionic recommender system model, which understands users from such perspective. Telepath is a combination of a convolutional neural network (CNN), a recurrent neural network (RNN) and deep neural networks (DNNs). Its CNN subnetwork simulates the human vision system to extract key visual signals of items' attractiveness and generate corresponding activations. Its RNN and DNN subnetworks simulate cerebral cortex to understand users' interest based on the activations generated from browsed items. In practice, the Telepath model has been launched to JD's recommender system and advertising system. For one of the major item recommendation blocks on the JD app, click-through rate (CTR), gross merchandise value (GMV) and orders have increased 1.59%, 8.16% and 8.71% respectively. For several major ads publishers of JD demand-side platform, CTR, GMV and return on investment have increased 6.58%, 61.72% and 65.57% respectively by the first launch, and further increased 2.95%, 41.75% and 41.37% respectively by the second launch.Comment: 8 pages, 11 figures, 1 tabl

System Design of a Cheetah Robot Toward Ultra-high Speed

High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system

Social Burden, Social Venture or Social Responsibility? A Reflection on CSR in China and CSR Strategy Suggestions for Multinational Companies in China

Thirty years into its reform and opening, the People’s Republic of China (referred to as China) has become aware of many international practices, including corporate social responsibility (CSR). Yet FOR Chinese enterprises, CSR seems similar to the heavy social burdens of THE state-owned enterprises (SOEs). The “cradle-to-grave” welfare system, notorious but standard in THE planned economy, played a role in the failure of most SOEs to compete with the new, burgeoning private sector. Although laws were promulgated to free the SOEs from their “social burdens,” the new township enterprises set a different example. Some of the latter even profited from their “social ventures.” A comparison of the approach of the state sector and that of township enterprises sheds light on how MNCs can best tailor their CSR strategies to the Chinese situation

Regulation of circular RNAs and micro RNAs in hippocampal neurons

Synaptic plasticity is the activity dependent alteration of the composition, form and strength of synapses and believed to be the underlying mechanism of learning and memory formation. While initial changes in synaptic transmission are caused by second messenger signaling pathways and rapid modifications in the cytoskeleton, to achieve stable and persistent changes at individual synapses, the expression of new mRNAs and proteins is required. The central dogma postulated that the cell body is the only source of newly synthesized proteins. For neurons, with their unique morphology, this meant that proteins would need be transported long distances, often hundreds of microns, to reach their destined locations in dendrites and at spines. To overcome this limitation, neurons have developed a strategy to regulate protein synthesis locally by distributing thousands of mRNAs into neuronal processes and use them for local protein synthesis. Ample research has demonstrated the importance of local protein synthesis to many forms of long-term synaptic plasticity. One potential regulator of mRNA localization and local translation in neurons are non-coding RNAs. Intensive work over the past decades has highlighted the importance of non-coding RNAs in many aspects of brain function. The aim of this thesis is to obtain a better understanding of the role of non-coding RNAs in synaptic function and plasticity in the murine hippocampus. For this, we focused our studies on two classes of non-coding RNAs. In the first part of my thesis, I describe our efforts on characterizing circular RNAs, a novel and peculiar family of non-coding RNAs, in the murine hippocampus by combining high throughput RNA-Sequencing with fluorescence in situ hybridization. Furthermore, we investigated the mechanisms of circular RNA biogenesis in hippocampal neurons by temporarily inhibiting spliceosome activity and analyzing the differentially regulated circular RNAs

Effect of fruit juice on glucose control and insulin sensitivity in adults: a meta-analysis of 12 randomized controlled trials.

BACKGROUND: Diabetes mellitus has become a worldwide health problem. Whether fruit juice is beneficial in glycemic control is still inconclusive. This study aimed to synthesize evidence from randomized controlled trials on fruit juice in relationship to glucose control and insulin sensitivity. METHODS: A strategic literature search of PubMed, EMBASE, and the Cochrane Library (updated to March, 2014) was performed to retrieve the randomized controlled trials that evaluated the effects of fruit juice on glucose control and insulin sensitivity. Study quality was assessed using the Jadad scale. Weighted mean differences were calculated for net changes in the levels of fasting glucose, fasting insulin, hemoglobin A1c (HbA1c), and homeostatic model assessment of insulin resistance (HOMA-IR) using fixed- or random-effects model. Prespecified subgroup and sensitivity analyses were performed to explore the potential heterogeneity. RESULTS: Twelve trials comprising a total of 412 subjects were included in the current meta-analysis. The numbers of these studies that reported the data on fasting glucose, fasting insulin, HbA1c and HOMA-IR were 12, 5, 3 and 3, respectively. Fruit juice consumption did not show a significant effect on fasting glucose and insulin concentrations. The net change was 0.79 mg/dL (95% CI: -1.44, 3.02 mg/dL; P = 0.49) for fasting glucose concentrations and -0.74 µIU/ml (95% CI: -2.62, 1.14 µIU/ml; P = 0.44) for fasting insulin concentrations in the fixed-effects model. Subgroup analyses further suggested that the effect of fruit juice on fasting glucose concentrations was not influenced by population region, baseline glucose concentration, duration, type of fruit juice, glycemic index of fruit juice, fruit juice nutrient constitution, total polyphenols dose and Jadad score. CONCLUSION: This meta-analysis showed that fruit juice may have no overall effect on fasting glucose and insulin concentrations. More RCTs are warranted to further clarify the association between fruit juice and glycemic control

Research on the Obstacle Negotiation Strategy for the Heavy-duty Six-legged Robot based on Force Control

To make heavy-duty six-legged robots without environment reconstruction system negotiate obstacles after the earthquake successfully, an obstacle negotiation strategy is described in this paper. The reflection strategy is generated by the information of plantar force sensors and Bezier Curve is used to plan trajectory. As the heavy-duty six-legged robot has a large inertia, force controller is necessary to ensure the robot not to lose stability while negotiating obstacles. Impedance control is applied to reduce the impact of collision and active force control is applied to adjust the pose of the robot. The robot can walk through zones that are filled with obstacles automatically because of force control. Finally, the algorithm is verified in a simulation environment

Research on the Obstacle Negotiation Strategy for the Heavy-duty Six-legged Robot based on Force Control

To make heavy-duty six-legged robots without environment reconstruction system negotiate obstacles after the earthquake successfully, an obstacle negotiation strategy is described in this paper. The reflection strategy is generated by the information of plantar force sensors and Bezier Curve is used to plan trajectory. As the heavy-duty six-legged robot has a large inertia, force controller is necessary to ensure the robot not to lose stability while negotiating obstacles. Impedance control is applied to reduce the impact of collision and active force control is applied to adjust the pose of the robot. The robot can walk through zones that are filled with obstacles automatically because of force control. Finally, the algorithm is verified in a simulation environment