The Contribution and Prospect of 5G Technology to China's Economic Development

Since the birth of 5G, it has attracted much attention from all countries in the world. The development of 5G industry is particularly important for domestic economic development. 4G changes life, 5G changes society. 5G will not only accelerate the speed of people surfing the Internet, but also bring revolutionary changes to all aspects of social life, making people's lives, work and entertainment more convenient and diverse. The economic impact of the development of the 5G industry on China cannot be underestimated. Nowadays, information and communication technology has increasingly become a new driving force for economic development. 5G technology has already become a key technology pursuit for countries to compete for the status of world power, and it has also become an indispensable part of contemporary economic and social development. We should give full play to the government's guiding role, and work with network giants to build a new platform for cooperation, promote coordinated industrial development, achieve win-win results, and promote economic and social prosperity and development

Weakly Supervised Deep Learning for Thoracic Disease Classification and Localization on Chest X-rays

Chest X-rays is one of the most commonly available and affordable radiological examinations in clinical practice. While detecting thoracic diseases on chest X-rays is still a challenging task for machine intelligence, due to 1) the highly varied appearance of lesion areas on X-rays from patients of different thoracic disease and 2) the shortage of accurate pixel-level annotations by radiologists for model training. Existing machine learning methods are unable to deal with the challenge that thoracic diseases usually happen in localized disease-specific areas. In this article, we propose a weakly supervised deep learning framework equipped with squeeze-and-excitation blocks, multi-map transfer, and max-min pooling for classifying thoracic diseases as well as localizing suspicious lesion regions. The comprehensive experiments and discussions are performed on the ChestX-ray14 dataset. Both numerical and visual results have demonstrated the effectiveness of the proposed model and its better performance against the state-of-the-art pipelines.Comment: 10 pages. Accepted by the ACM BCB 201

Spear or Shield: Leveraging Generative AI to Tackle Security Threats of Intelligent Network Services

Generative AI (GAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. Despite their numerous applications and potential, such models create opportunities for novel security challenges. In this paper, we examine the challenges and opportunities of GAI in the realm of the security of intelligent network AIGC services such as suggesting security policies, acting as both a ``spear'' for potential attacks and a ``shield'' as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GAI's spear and shield roles, highlighting two primary categories of potential GAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GAI in enhancing network security

DCPT: Darkness Clue-Prompted Tracking in Nighttime UAVs

Existing nighttime unmanned aerial vehicle (UAV) trackers follow an "Enhance-then-Track" architecture - first using a light enhancer to brighten the nighttime video, then employing a daytime tracker to locate the object. This separate enhancement and tracking fails to build an end-to-end trainable vision system. To address this, we propose a novel architecture called Darkness Clue-Prompted Tracking (DCPT) that achieves robust UAV tracking at night by efficiently learning to generate darkness clue prompts. Without a separate enhancer, DCPT directly encodes anti-dark capabilities into prompts using a darkness clue prompter (DCP). Specifically, DCP iteratively learns emphasizing and undermining projections for darkness clues. It then injects these learned visual prompts into a daytime tracker with fixed parameters across transformer layers. Moreover, a gated feature aggregation mechanism enables adaptive fusion between prompts and between prompts and the base model. Extensive experiments show state-of-the-art performance for DCPT on multiple dark scenario benchmarks. The unified end-to-end learning of enhancement and tracking in DCPT enables a more trainable system. The darkness clue prompting efficiently injects anti-dark knowledge without extra modules. Code and models will be released.Comment: Under revie

Surface mass balance and ice flow of the glaciers Austre Lovénbreen and Pedersenbreen, Svalbard, Arctic

The glaciers Austre Lovénbreen and Pedersenbreen are located at Ny-Ålesund, Svalbard. The surface mass balance and ice flow velocity of both glaciers have been determined from the first year of observations(2005/2006), while the front edge of Austre Lovénbreen was also surveyed. The results are as follows: (1)The net mass balances of Austre Lovénbreen and Pedersenbreen are -0.44 and -0.20 m w. e., the annual ablation is -0.99 and -0.94m w. e., and the corresponding equilibrium line altitudes are 478.10 and 494.87 m, respectively (2)Austre Lovénbreen and Pedersenbreen are characterized as ice flow models of surge-type glaciers in Svalbard. The horizontal vectors of the ice flow velocities are parallel or converge to the central lines of both glaciers, with lower velocities in the lower ablation areas and higher velocities in the middle and upper reaches of the glaciers. The vertical vectors of ice flow velocities show that there is a mass loss in the ablation areas, which reduces with increasing altitude, while there is a mass gain near the equilibrium line of Austre Lovénbreen. (3)The front edge of Austre Lovénbreen receded at an average rate of 21.83 m·a-1, with remarkable variability-a maximum rate of 77.30m·a-1 and a minimum rate of 2.76m·a-1

Body-Mounted Robotic System for MRI-Guided Shoulder Arthrography: Cadaver and Clinical Workflow Studies

This paper presents an intraoperative MRI-guided, patient-mounted robotic system for shoulder arthrography procedures in pediatric patients. The robot is designed to be compact and lightweight and is constructed with nonmagnetic materials for MRI safety. Our goal is to transform the current two-step arthrography procedure (CT/x-ray-guided needle insertion followed by diagnostic MRI) into a streamlined single-step ionizing radiation-free procedure under MRI guidance. The MR-conditional robot was evaluated in a Thiel embalmed cadaver study and healthy volunteer studies. The robot was attached to the shoulder using straps and ten locations in the shoulder joint space were selected as targets. For the first target, contrast agent (saline) was injected to complete the clinical workflow. After each targeting attempt, a confirmation scan was acquired to analyze the needle placement accuracy. During the volunteer studies, a more comfortable and ergonomic shoulder brace was used, and the complete clinical workflow was followed to measure the total procedure time. In the cadaver study, the needle was successfully placed in the shoulder joint space in all the targeting attempts with translational and rotational accuracy of 2.07 ± 1.22mm and 1.46 ± 1.06 degrees, respectively. The total time for the entire procedure was 94 min and the average time for each targeting attempt was 20 min in the cadaver study, while the average time for the entire workflow for the volunteer studies was 36 min. No image quality degradation due to the presence of the robot was detected. This Thiel-embalmed cadaver study along with the clinical workflow studies on human volunteers demonstrated the feasibility of using an MR-conditional, patient-mounted robotic system for MRI-guided shoulder arthrography procedure. Future work will be focused on moving the technology to clinical practice

Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network

Liver tumor segmentation and classification are important tasks in computer aided diagnosis. We aim to address three problems: liver tumor screening and preliminary diagnosis in non-contrast computed tomography (CT), and differential diagnosis in dynamic contrast-enhanced CT. A novel framework named Pixel-Lesion-pAtient Network (PLAN) is proposed. It uses a mask transformer to jointly segment and classify each lesion with improved anchor queries and a foreground-enhanced sampling loss. It also has an image-wise classifier to effectively aggregate global information and predict patient-level diagnosis. A large-scale multi-phase dataset is collected containing 939 tumor patients and 810 normal subjects. 4010 tumor instances of eight types are extensively annotated. On the non-contrast tumor screening task, PLAN achieves 95% and 96% in patient-level sensitivity and specificity. On contrast-enhanced CT, our lesion-level detection precision, recall, and classification accuracy are 92%, 89%, and 86%, outperforming widely used CNN and transformers for lesion segmentation. We also conduct a reader study on a holdout set of 250 cases. PLAN is on par with a senior human radiologist, showing the clinical significance of our results.Comment: MICCAI 2023, code: https://github.com/alibaba-damo-academy/pixel-lesion-patient-networ

Frisson Waves: Exploring Automatic Detection, Triggering and Sharing of Aesthetic Chills in Music Performances

Frisson is the feeling and experience of physical reactions such as shivers, tingling skin, and goosebumps. Using entrainment through facilitating interpersonal transmissions of embodied sensations, we present "Frisson Waves" with the aim to enhance live music performance experiences. "Frisson Waves" is an exploratory real-time system to detect, trigger and share frisson in a wave-like pattern over audience members during music performances. The system consists of a physiological sensing wristband for detecting frisson and a thermo-haptic neckband for inducing frisson. In a controlled environment, we evaluate detection (n=19) and triggering of frisson (n=15). Based on our findings, we conducted an in-the-wild music concert with 48 audience members using our system to share frisson. This paper summarizes a framework for accessing, triggering and sharing frisson. We report our research insights, lessons learned, and limitations of "Frisson Waves". Yan He, George Chernyshov, Jiawen Han, Dingding Zheng, Ragnar Thomsen, Danny Hynds, Muyu Liu, Yuehui Yang, Yulan Ju, Yun Suen Pai, Kouta Minamizawa, Kai Kunze, and Jamie A War

An analysis of the correlations between TNF-α and MCP-1 levels in the induced sputum and serum of patients with stable chronic obstructive pulmonary diseaseand pulmonary function and quality of life

Abstract: In this study, we investigated the correlations between airway and systemic Tumor Necrosis Factor-alpha (TNF-α) and Monocyte Chemoattractant Protein -1 (MCP-1) levels and pulmonary function and quality of life in patients with stable COPD. A low-risk COPD patient group (32 cases), a high-risk COPD patient group (29 cases) and a healthy control group (30 cases) were included in the study. The TNF-α and MCP-1 levels in the induced sputum and serum of the three groups were compared. The correlation between inflammatory factor levels in the COPD patients and pulmonary function, body-mass index(BMI), airflow obstruction(FEV 1 %), dyspnea(MMRC scale), exercise capacity(6WMD), BODE index and SGRQ score was analyzed by a multiple variable linear regression model. The TNF-α and MCP-1 levels in induced sputum and serum of the three groups were all significantly different (P＜0.001). The MCP-1 level in the induced sputum of the low-risk COPD patient group was negatively correlated with the 6MWD and with the SGRQ symptom score (P=0.014). The serum TNF-α level in the high-risk COPD patient group was negatively correlated with the FEV 1 /FVC(P=0.001) and was positively correlated with the SGRQ total score (P=0.005). The serum MCP-1 level in the high-risk COPD patient group was negatively correlated with the FEV 1 /FVC and the MMRC dyspnea scale (P=0.007)