To further validate the reproducibility of performance, we used the model of MHRWR to verify related lncRNAs of colon cancer, colorectal cancer and lung adenocarcinoma in the case studies. this website The codes of MHRWR is available on https//github.com/yangyq505/MHRWR.Interpretation of high level cognitive behavior of human brain requires comprehensive understanding of spike transfer process at neuronal level. Synapses play major role in spike transfer process from one neuron to another. An expanded leaky integrate and fire model of a neuron in multiple input and single output configuration with threshold variability for spike transfer process is proposed in this paper. Asynchronous generation of post synaptic potential is considered. Multiple types of excitatory and inhibitory post-synaptic potentials are also included in the model. An analytical expression of membrane potential including threshold variability and activity dependant noise process has been developed. The model captures several important features of a spiking neuron through a set of well defined parameters. Simulation results are provided to explain various aspects of the proposed model. A functionally scaled version of the model has also been compared with limited experimental data, available from the Allen Institute of Brain Science.Postural sway is a product of the neuromuscular system that is commonly used in contemporary labs and clinics for the assessment of postural stability. In this study, we analyzed the transient responses of the neuromuscular system during the rise-on-toes (ROT) movement in eighteen 11 yrs old girls. Their center of pressure (COP) trajectories were recorded with standard force-platform during the transition from quiet stance to standing on toes. To assess the robustness of children’s postural stability, we compared the ROT trajectories while the movement was performed with and without vision. Our results confirmed that the dynamic characteristics of the COP step response were significantly modified by visual feedback. In particular, the ROT test performed with eyes closed (EC) was characterized by a four-fold increase of COP chaotic oscillations at the target (tiptoe) position. This resulted in a substantial increase in the movement’s index of difficulty (ID) thus to achieve adequate accuracy of the target-oriented movement the COP velocity was decreased accordingly. This inherent strategy of the brain controller allowed for precise positioning of the COP within the reduced size of the target. In conclusion, the dynamics of the ROT movement is always precisely adjusted to the stability of the upright posture, and thus, the dynamic characteristics of the COP step response are also sensitive measures of postural stability and the ROT can be recommended as a useful test for this assessment in the general population.Optimizing rendering performance is critical for a wide variety of virtual reality (VR) applications. Foveated rendering is emerging as an indispensable technique for reconciling interactive frame rates with ever-higher head-mounted display resolutions. Here, we present a simple yet effective technique for further reducing the cost of foveated rendering by leveraging ocular dominance – the tendency of the human visual system to prefer scene perception from one eye over the other. Our new approach, eye-dominance-guided foveated rendering (EFR), renders the scene at a lower foveation level (with higher detail) for the dominant eye than the non-dominant eye. Compared with traditional foveated rendering, EFR can be expected to provide superior rendering performance while preserving the same level of perceived visual quality.In this work, we tackle the problem of person search, which is a challenging task consisted of pedestrian detection and person re-identification (re-ID). Instead of sharing representations in a single joint model, we find that separating detector and re-ID feature extraction yields better performance. In order to extract more representative features for each identity, we segment out the foreground person from the original image patch. We propose a simple yet effective re-ID method, which models foreground person and original image patches individually, and obtains enriched representations from two separate CNN streams. We also propose a Confidence Weighted Stream Attention method which further re-adjusts the relative importance of the two streams by incorporating the detection confidence. Furthermore, we simplify the whole pipeline by incorporating semantic segmentation into the re-ID network, which is trained by bounding boxes as weakly-annotated masks and identification labels simultaneously. From the experiments on two standard person search benchmarks i.e. CUHK-SYSU and PRW, we achieve mAP of 83.3% and 32.8% respectively, surpassing the state of the art by a large margin. The extensive ablation study and model inspection further justifies our motivation.Region-based methods have become the state-of-art solution for monocular 6-DOF object pose tracking in recent years. However, two main challenges still remain the robustness to heterogeneous configurations (both foreground and background), and the robustness to partial occlusions. In this paper, we propose a novel region-based monocular 3D object pose tracking method to tackle these problems. Firstly, we design a new strategy to define local regions, which is simple yet efficient in constructing discriminative local color histograms. Contrary to previous methods which define multiple circular regions around the object contour, we propose to define multiple overlapped, fan-shaped regions according to polar coordinates. This local region partitioning strategy produces much less number of local regions that need to be maintained and updated, while still being temporally consistent. Secondly, we propose to detect occluded pixels using edge distance and color cues. The proposed occlusion detection strategy is seamlessly integrated into the region-based pose optimization pipeline via a pixel-wise weight function, which significantly alleviates the interferences caused by partial occlusions. We demonstrate the effectiveness of the proposed two new strategies with a careful ablation study. Furthermore, we compare the performance of our method with the most recent state-of-art region-based methods in a recently released large dataset, in which the proposed method achieves competitive results with a higher average tracking success rate. Evaluations on two real-world datasets also show that our method is capable of handling realistic tracking scenarios.