As a key technology of future communication systems, reconfigurable intelligent surfaces (RISs) can intelligently control wireless signal reflections, thereby optimizing propagation channels and enhancing communication performance. However, the indoor channel characteristics and communication performance of RISs in real-world deployment environments remain insufficiently studied. In this paper, we develop a RIS-based measurement platform for simultaneous channel measurement and link-level performance analysis, followed by verification and validation in a laboratory environment. Utilizing this platform, we conduct wideband channel measurement and performance analysis work in indoor scenarios at 2.6 GHz band. Multiple RIS phase shift codebooks are employed, including the 1-bit discrete Fourier transform (DFT) codebook, the Ring-type codebook, and the conditional sample mean (CSM) codebook. Based on these measurements, two empirical path loss (PL) models, namely the floating-intercept (FI) model and the close-in (CI) model, are fitted to the measured data. Furthermore, we comprehensively analyze and compare the channel characteristics of RIS-assisted communications, including shadow fading (SF), multipath components (MPCs) statistics, the Rician K-factor (KF), and root mean square (RMS) delay spread. Finally, we evaluate and compare the wireless coverage and link-level performance of various RIS reflection schemes. The findings on propagation characteristics and communication performance provide essential insights that can support the future application and deployment of RIS-assisted communication systems.

Reconfigurable intelligent surface (RIS) has emerged as a promising key technology for sixth-generation (6G) wireless communication systems, primarily due to its capability to intelligently manipulate the propagation environment. In this paper, we conduct comprehensive measurements of the wireless channel and link-level performance of an RIS-assisted communication system in indoor corridor scenarios. We analyze the time dispersion characteristics and channel capacity under both RIS intelligent reflection (RIS-IR) and without RIS (WR) cases for comparative evaluation. The results demonstrate that wideband channel characteristics have a notable impact on the performance of RIS-assisted communications. Specifically, we model the fading distribution of the visual-line-of-sight (VLoS) path introduced by the RIS and establish a corresponding tapped-delay-line (TDL) channel model. The insights derived from this study offer theoretical foundations and practical guidelines for the deployment and performance evaluation of RIS-assisted communication systems.

Whole slide image (WSI) analysis is gaining prominence within the medical imaging field. However, previous methods often fall short of efficiently processing entire WSIs due to their gigapixel size. Inspired by recent developments in state space models, this paper introduces a new Pathology Mamba (PAM) for more accurate and robust WSI analysis. PAM includes three carefully designed components to tackle the challenges of enormous image size, the utilization of local and hierarchical information, and the mismatch between the feature distributions of training and testing during WSI analysis. Specifically, we design a Bi-directional Mamba Encoder to process the extensive patches present in WSIs effectively and efficiently, which can handle large-scale pathological images while achieving high performance and accuracy. To further harness the local information and inherent hierarchical structure of WSI, we introduce a novel Local-aware Scanning module, which employs a local-aware mechanism alongside hierarchical scanning to adeptly capture both the local information and the overarching structure within WSIs. Moreover, to alleviate the patch feature distribution misalignment between training and testing, we propose a Test-time Importance Resampling module to conduct testing patch resampling to ensure consistency of feature distribution between the training and testing phases, and thus enhance model prediction. Extensive evaluation on nine WSI datasets with cancer subtyping and survival prediction tasks demonstrates that PAM outperforms current state-of-the-art methods and also its enhanced capability in modeling discriminative areas within WSIs. The source code is available at https://github.com/HKU-MedAI/PAM.

Whole slide image (WSI) analysis is gaining prominence within the medical imaging field. Recent advances in pathology foundation models have shown the potential to extract powerful feature representations from WSIs for downstream tasks. However, these foundation models are usually designed for general-purpose pathology image analysis and may not be optimal for specific downstream tasks or cancer types. In this work, we present Concept Anchor-guided Task-specific Feature Enhancement (CATE), an adaptable paradigm that can boost the expressivity and discriminativeness of pathology foundation models for specific downstream tasks. Based on a set of task-specific concepts derived from the pathology vision-language model with expert-designed prompts, we introduce two interconnected modules to dynamically calibrate the generic image features extracted by foundation models for certain tasks or cancer types. Specifically, we design a Concept-guided Information Bottleneck module to enhance task-relevant characteristics by maximizing the mutual information between image features and concept anchors while suppressing superfluous information. Moreover, a Concept-Feature Interference module is proposed to utilize the similarity between calibrated features and concept anchors to further generate discriminative task-specific features. The extensive experiments on public WSI datasets demonstrate that CATE significantly enhances the performance and generalizability of MIL models. Additionally, heatmap and umap visualization results also reveal the effectiveness and interpretability of CATE.

Gait recognition is widely used in diversified practical applications. Currently, the most prevalent approach is to recognize human gait from RGB images, owing to the progress of computer vision technologies. Nevertheless, the perception capability of RGB cameras deteriorates in rough circumstances, and visual surveillance may cause privacy invasion. Due to the robustness and non-invasive feature of millimeter wave (mmWave) radar, radar-based gait recognition has attracted increasing attention in recent years. In this research, we propose a Hierarchical Dynamic Network (HDNet) for gait recognition using mmWave radar. In order to explore more dynamic information, we propose point flow as a novel point clouds descriptor. We also devise a dynamic frame sampling module to promote the efficiency of computation without deteriorating performance noticeably. To prove the superiority of our methods, we perform extensive experiments on two public mmWave radar-based gait recognition datasets, and the results demonstrate that our model is superior to existing state-of-the-art methods.

Whole slide image (WSI) analysis has become increasingly important in the medical imaging community, enabling automated and objective diagnosis, prognosis, and therapeutic-response prediction. However, in clinical practice, the ever-evolving environment hamper the utility of WSI analysis models. In this paper, we propose the FIRST continual learning framework for WSI analysis, named ConSlide, to tackle the challenges of enormous image size, utilization of hierarchical structure, and catastrophic forgetting by progressive model updating on multiple sequential datasets. Our framework contains three key components. The Hierarchical Interaction Transformer (HIT) is proposed to model and utilize the hierarchical structural knowledge of WSI. The Breakup-Reorganize (BuRo) rehearsal method is developed for WSI data replay with efficient region storing buffer and WSI reorganizing operation. The asynchronous updating mechanism is devised to encourage the network to learn generic and specific knowledge respectively during the replay stage, based on a nested cross-scale similarity learning (CSSL) module. We evaluated the proposed ConSlide on four public WSI datasets from TCGA projects. It performs best over other state-of-the-art methods with a fair WSI-based continual learning setting and achieves a better trade-off of the overall performance and forgetting on previous tasks.

With the ceaseless usage of web and other online services, it has turned out that copying, sharing, and transmitting digital media over the Internet are amazingly simple. Since the text is one of the main available data sources and most widely used digital media on the Internet, the significant part of websites, books, articles, daily papers, and so on is just the plain text. Therefore, copyrights protection of plain texts is still a remaining issue that must be improved in order to provide proof of ownership and obtain the desired accuracy. During the last decade, digital watermarking and steganography techniques have been used as alternatives to prevent tampering, distortion, and media forgery and also to protect both copyright and authentication. This paper presents a comparative analysis of information hiding techniques, especially on those ones which are focused on modifying the structure and content of digital texts. Herein, various text watermarking and text steganography techniques characteristics are highlighted along with their applications. In addition, various types of attacks are described and their effects are analyzed in order to highlight the advantages and weaknesses of current techniques. Finally, some guidelines and directions are suggested for future works.

This paper analyses the problems of one-step current-voltage commutation which could cause input current distortion while the input voltage judgment is not accurate, and an improved commutation strategy based on “two-step commutation among transition interval” is proposed. The two-step commutation is adopted in the transition interval, and outside of which the one-step commutation is adopted, and it can effectively avoid inaccurate voltage sector judgment when input voltages are similar. Finally, the effectiveness and correctness of proposed commutation strategy is verified by simulation and experiment, whose results show that the voltage sector can be accurately determined by proposed method and input current will be improved.

Bell's palsy is nonspecific inflammation stylomastoid foramen caused by facial nerve. This is a common disease of self limiting, non progressive. The incidence rate of about 30/100000[1], clinical manifestations include dry eyes, dry mouth, and taste disorders or loss, Hyperacusis, incomplete eyelid closure, numbness of the mouth droop[2, 3]. Risk of ear and facial pain is rare[4, 5]. The prognosis is good, there is some 70% with or without treatment within six months to fully recover. But still some 30% in patients with Bell paralysis sequela and residual facial paralysis (29%), contractures (17%), and hemifacial spasm or associated with sports (16%)[1]. The use of traditional Chinese medicine and acupuncturetherapy is effective, but the clinical study of Zhao's thunder fire moxibustion treatment of Bell palsy is lack of evidence. In this study, Zhao's thunder fire moxibustion cure coldBell's palsy, observation of clinical efficacy, and explore the possible mechanism of its effect.

This paper firstly define the concept of Combined Acupuncture with medicine, to explore the theoretical basis of acupuncture and drugs, Analyzed from the following aspects: comparative analysis of the advantages and disadvantages of acupuncture and Chinese Medicine, the way and method of combination, he current research progress, study on the mechanism of acupuncture combined with medicine. The objective is to grasp the characteristics and advantages of treatment of the acupuncture and Chinese herbal medicine, to explore organic combination of the two modes of treatment, to find the optimal treatment plan, summary of the law of combination of acupuncture and medicine clinical application. Give full play to the advantages of acupuncture and medicine complementary.

Insomnia is common psychophysiogical disorder, characterized by sleeping difficultly or lightly, restless sleep and early awakening, usually with a series of disease, such as neurasthenia, anxiety, depression and so on. Nowadays acupuncture is a complementary therapy for insomnia which is regarded as one of most effective, widely used and well-accepted method. However, acupuncture is usually used independently. In this paper, we present a research protocol designed for a parallel, randomized, controlled trial to evaluate the effect of the acupoint injection combined with acupuncture treatment for insomnia with cardiac-splenic asthenia. In our study, the objective is to evaluate the clinical effect of the acupoint injection combined with acupuncture treatment compared with the acupuncture used independently.

To explore the difference in treatment thoughts and therapy method between traditional acupuncture combines with herbal medicine and the needle-medicine of mutual reinforcement school in the treatment of tinnitus and deafness. Firstly, studied to the ancient cultural heritage and research, in order to understand the application of traditional acupuncture combines with herbal medicine. Secondly, to descry the needle-medicine of mutual reinforcement school in Guangdong Provincial Hospital of Chinese Medicine, base on the cure of tinnitus and deafness, to make a comparison with traditional acupuncture combines with herbal medicine. The needle-medicine of mutual reinforcement school in Guangdong Provincial Hospital of Chinese Medicine carries on the traditional Chinese medicines theory and traditional innovation, even has better clinical operability, strengthens the patients' compliance, lightens the patients' home burden, is the one can continuously inherit and develop the traditional Chinese medicine.

To fit for the demand of extending the power, increasing maintainability and improving performance, a SVG with parallel independent DC capacitance converter modules is presented. In respect that the parameter difference among converters, reactive power of total output sharing has to be resolved. By analyzing the parallel converter mathematics model with DQ analytic transformation, a new control strategy is proposed, which is based on double close-loop decoupling control, reactive power balance current sharing. To reduce tracking error of current, source voltage in d-q coordinators feed forward method is adopted. Active and reactive current, and DC voltage controller is designed. Further, for the purpose of reducing switch frequency of single module, CPS-SPWM is employed to operate the equipment. A based on double FPGA-DSP controller is devised, and a 2Mvar platform is carried out. The simulation and practical performance of SVG are given. The validity and feasibility of the method is demonstrated by the results and the industrial application.