Graphene Based Waveguides

Graphene, which is well known as a one-atom thick carbon allotrope, has drawn lots of attention since its first announcement due to remarkable performance in mechanical, electrical, magnetic, thermal, and optical areas. In particular, unique properties of graphene such as low net absorption in broadband optical band, notably high nonlinear optical effects, and gate-variable optical conductivity make it an excellent candidate for high speed, high performance, and broadband electronic and photonics devices. Embedding graphene into optical devices longitudinally would enhance the light-graphene interaction, which shows great potential in photonic components. Since the carrier density of graphene could be tuned by external gate voltage, chemical doping, light excitation, graphene-based waveguide modulator could be designed to have high flexibility in controlling the absorption and modulation depth. Furthermore, graphene-based waveguides could take advantages in detection, sensing, polarizer, and so on

MD-IQA: Learning Multi-scale Distributed Image Quality Assessment with Semi Supervised Learning for Low Dose CT

Image quality assessment (IQA) plays a critical role in optimizing radiation dose and developing novel medical imaging techniques in computed tomography (CT). Traditional IQA methods relying on hand-crafted features have limitations in summarizing the subjective perceptual experience of image quality. Recent deep learning-based approaches have demonstrated strong modeling capabilities and potential for medical IQA, but challenges remain regarding model generalization and perceptual accuracy. In this work, we propose a multi-scale distributions regression approach to predict quality scores by constraining the output distribution, thereby improving model generalization. Furthermore, we design a dual-branch alignment network to enhance feature extraction capabilities. Additionally, semi-supervised learning is introduced by utilizing pseudo-labels for unlabeled data to guide model training. Extensive qualitative experiments demonstrate the effectiveness of our proposed method for advancing the state-of-the-art in deep learning-based medical IQA. Code is available at: https://github.com/zunzhumu/MD-IQA

A Long-Tail Friendly Representation Framework for Artist and Music Similarity

The investigation of the similarity between artists and music is crucial in music retrieval and recommendation, and addressing the challenge of the long-tail phenomenon is increasingly important. This paper proposes a Long-Tail Friendly Representation Framework (LTFRF) that utilizes neural networks to model the similarity relationship. Our approach integrates music, user, metadata, and relationship data into a unified metric learning framework, and employs a meta-consistency relationship as a regular term to introduce the Multi-Relationship Loss. Compared to the Graph Neural Network (GNN), our proposed framework improves the representation performance in long-tail scenarios, which are characterized by sparse relationships between artists and music. We conduct experiments and analysis on the AllMusic dataset, and the results demonstrate that our framework provides a favorable generalization of artist and music representation. Specifically, on similar artist/music recommendation tasks, the LTFRF outperforms the baseline by 9.69%/19.42% in Hit Ratio@10, and in long-tail cases, the framework achieves 11.05%/14.14% higher than the baseline in Consistent@10

More on difference between angular momentum and pseudo-angular momentum

We extend the discussion on the difference between angular momentum and pseudo-angular momentum in field theory. We show that the often quoted expressions in [Phys.Rev.B 103, L100409 (2021)] only apply to a non-linear system, and derive the correct rotation symmetry and the corresponding angular momentum for a linear elastic system governed by Navier-Cauchy equation. By mapping the concepts and methods for the elastic wave into electromagnetic theory, we argue that the renowned canonical and Benlinfante angular momentum of light are actually pseudo-angular momentum. Then, we derive the ``Newtonian" momentum $\int \text{d}^3 x\boldsymbol{E}$ and angular momentum $\int \text{d}^3 x (\boldsymbol{r}\times\boldsymbol{E})$ for a free electromagnetic wave, which are conserved quantities during propagation in vacuum.Comment: 8 pages, no figure

Trajectory Tracking Control for Flexible-Joint Robot Based on Extended Kalman Filter and PD Control

The robot arm with flexible joint has good environmental adaptability and human robot interaction ability. However, the controller for such robot mostly relies on data acquisition of multiple sensors, which is greatly disturbed by external factors, resulting in a decrease in control precision. Aiming at the control problem of the robot arm with flexible joint under the condition of incomplete state feedback, this paper proposes a control method based on closed-loop PD (Proportional-Derivative) controller and EKF (Extended Kalman Filter) state observer. Firstly, the state equation of the control system is established according to the non-linear dynamic model of the robot system. Then, a state prediction observer based on EKF is designed. The state of the motor is used to estimate the output state, and this method reduces the number of sensors and external interference. The Lyapunov method is used to analyze the stability of the system. Finally, the proposed control algorithm is applied to the trajectory control of the flexible robot according to the stability conditions, and compared with the PD control algorithm based on sensor data acquisition under the same experimental conditions, and the PD controller based on sensor data acquisition under the same test conditions. The experimental data of comparison experiments show that the proposed control algorithm is effective and has excellent trajectory tracking performance

Risk factors of distant brain failure for patients with newly diagnosed brain metastases treated with stereotactic radiotherapy alone

<p>Abstract</p> <p>Objective</p> <p>To explore the risk factors of distant brain failure (DBF) for patients with brain metastasis (BM) who were treated with stereotactic radiotherapy alone and to group the patients on the basis of their risk levels.</p> <p>Methods and Materials</p> <p>We retrospectively analyzed 132 newly diagnosed BM patients who were treated with stereotactic radiotherapy alone from May 2000 to April 2010. Kaplan-Meier and Cox proportional hazards regression analyses were performed for univariate and multivariate analyses.</p> <p>Results</p> <p>The 1-year incidence rate of DBF was 44.7%, and the median DBF time (MDBFT) was 18 months. In multivariate analysis, the risk factors of DBF were the number of BMs greater than 1 (p = 0.041), uncontrolled extracranial disease (p = 0.005), interval time (IT) of less than 60 months between the diagnosis of primary tumor and BM (p = 0.024), and total volume of BM was greater than 6 cc (p = 0.049). Each risk factor was assigned 1 score. The median survival times for the patients with scores of 0-1, 2-3, and 4 were 31, 12, and 10 months, respectively, and the corresponding MDBFTs were not reached, 13, and 3 months, respectively, (p < 0.001). The crude DBF incidence rates in patients with scores of 0-1, 2-3, and 4 were 14.8%, 50.0%, and 76.9%, respectively, (p < 0.001).</p> <p>Conclusions</p> <p>The patients with scores of 0-1 had a lower risk of DBF than the patients with higher scores did, and it may be reasonable to treat these patients with SRS alone and resort to whole-brain radiation therapy only for salvage. The patients with a score of 4 had the highest risk of developing DBF after stereotactic radiotherapy alone, these patients may be candidates for initial whole-brain radiation therapy or clinical trials. The patients with a score of 2-3 had a moderate risk of developing DBF, SRT alone combined with close clinical monitoring would be the optimal treatment regimen for such patients, and for those patients with difficulties in receiving close clinical mornitoring, SRT combined with WBRT will be more suitable.</p