Dynamic resource allocation for virtual network function placement in satellite edge clouds

Satellite edge computing has become a promising way to provide computing services for Internet of Things (IoT) users in remote areas, which are out of the coverage of terrestrial networks. Nevertheless, it is not suitable for large-scale IoT users due to the resource limitation of satellites. Cloud computing can provide sufficient available resources for IoT users, but it does not meet delay-sensitive services as high network latency. Satellite edge clouds can facilitate flexible service provisioning for numerous IoT users by incorporating the advantages of edge computing and cloud computing. In this paper, we investigate the dynamic resource allocation problem for virtual network function (VNF) placement in satellite edge clouds. The aim is to minimize the network bandwidth cost and the service end-to-end delay jointly. We formulate the VNF placement problem as an integer non-linear programming problem and then propose a distributed VNF placement (D-VNFP) algorithm to address it. The experiments are conducted to evaluate the performance of the proposed D-VNFP algorithm, where Viterbi and Game theory are considered as the baseline algorithms. The results show that the proposed D-VNFP algorithm is effective and efficient for solving the VNF placement problem in satellite edge clouds

Self-Explanation Prompting Improves Dialogue Understanding in Large Language Models

Task-oriented dialogue (TOD) systems facilitate users in executing various activities via multi-turn dialogues, but Large Language Models (LLMs) often struggle to comprehend these intricate contexts. In this study, we propose a novel "Self-Explanation" prompting strategy to enhance the comprehension abilities of LLMs in multi-turn dialogues. This task-agnostic approach requires the model to analyze each dialogue utterance before task execution, thereby improving performance across various dialogue-centric tasks. Experimental results from six benchmark datasets confirm that our method consistently outperforms other zero-shot prompts and matches or exceeds the efficacy of few-shot prompts, demonstrating its potential as a powerful tool in enhancing LLMs' comprehension in complex dialogue tasks

SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents

Task-oriented dialogue (TOD) models have made significant progress in recent years. However, previous studies primarily focus on datasets written by annotators, which has resulted in a gap between academic research and real-world spoken conversation scenarios. While several small-scale spoken TOD datasets are proposed to address robustness issues such as ASR errors, they ignore the unique challenges in spoken conversation. To tackle the limitations, we introduce SpokenWOZ, a large-scale speech-text dataset for spoken TOD, containing 8 domains, 203k turns, 5.7k dialogues and 249 hours of audios from human-to-human spoken conversations. SpokenWOZ further incorporates common spoken characteristics such as word-by-word processing and reasoning in spoken language. Based on these characteristics, we present cross-turn slot and reasoning slot detection as new challenges. We conduct experiments on various baselines, including text-modal models, newly proposed dual-modal models, and LLMs, e.g., ChatGPT. The results show that the current models still have substantial room for improvement in spoken conversation, where the most advanced dialogue state tracker only achieves 25.65% in joint goal accuracy and the SOTA end-to-end model only correctly completes the user request in 52.1% of dialogues. The dataset, code, and leaderboard are available: https://spokenwoz.github.io/SpokenWOZ-github.io/

Dynamic resource management for neighbor-based VNF placement in decentralized satellite networks

By introducing software-defined networking (SDN) and network function virtualization (NFV), low-earth-orbit (LEO) satellite networks can facilitate virtual network function (VNF) placement, which will provide computing services for satellite applications on-demand. In this paper, we study the VNF placement problem in a decentralized LEO satellite network due to the requirements for real-time processing and network resilience, where our aim is to jointly optimize end-toend service delay and network bandwidth cost in a dynamic environment. To this end, a decentralized LEO satellite network architecture is first implemented for resource management by establishing the neighboring sub-network for each satellite. Then we formulate the VNF placement problem as an integer non-linear programming problem with multiple constraints of network resources and service requirements. A neighbor-based VNF placement (N-VNFP) approach is proposed to address the optimization problem. Finally, we conduct the experiments to evaluate the performance of the proposed N-VNFP approach in a Walker constellation with 66 LEO satellites. The simulation results show that the proposed N-VNFP approach provides an effective solution for resource management in a decentralized LEO satellite network and also outperforms the two centralized baselines, i.e., Viterbi and Greedy, in terms of end-to-end service delay and network bandwidth cost

Parallelism and non-parallelism in diabetic nephropathy and diabetic retinopathy

Diabetic nephropathy (DN) and diabetic retinopathy (DR), as microvascular complications of diabetes mellitus, are currently the leading causes of end-stage renal disease (ESRD) and blindness, respectively, in the adult working population, and they are major public health problems with social and economic burdens. The parallelism between the two in the process of occurrence and development manifests in the high overlap of disease-causing risk factors and pathogenesis, high rates of comorbidity, mutually predictive effects, and partial concordance in the clinical use of medications. However, since the two organs, the eye and the kidney, have their unique internal environment and physiological processes, each with specific influencing molecules, and the target organs have non-parallelism due to different pathological changes and responses to various influencing factors, this article provides an overview of the parallelism and non-parallelism between DN and DR to further recognize the commonalities and differences between the two diseases and provide references for early diagnosis, clinical guidance on the use of medication, and the development of new drugs

Satellite edge computing with collaborative computation offloading: an intelligent deep deterministic policy gradient approach

Enabling a satellite network with edge computing capabilities can complement the advantages further of a single terrestrial network and provide users with a full range of computing service. Satellite edge computing is a potentially indispensable technology for the future satellite-terrestrial integrated networks. In this paper, a three-tier edge computing architecture consisting of terminal-satellite-cloud is proposed, where tasks can be processed at three planes and inter-satellites can cooperate to achieve on-board load balancing. Facing varying and random task queues with different service requirements, we formulate the objective problem of minimizing the system energy consumption under the delay and resource constraints, and jointly optimize the offloading decision, communication and computing resource allocation variables. Moreover, the distribution of resources is based on the reservation mechanism to ensure the stability of satellite-terrestrial link and the reliability of computation process. To adapt to the dynamic environment, we propose an intelligent computation offloading scheme based on the deep deterministic policy gradient (DDPG) algorithm, which consists of several different deep neural networks (DNN) to output both discrete and continuous variables. Additionally, by setting the selection process of legal actions, the simultaneous decisions on offloading locations and allocating resources under multi-task concurrency is realized. The simulation results show that the proposed scheme can effectively reduce the total energy consumption of the system by ensuring that the task is completed on demand, and outperform the benchmark algorithms

Research Hotspots and Frontier Prospects in the Field of Agroforestry Picking Robots in China—Cite Space Bibliographic Analysis

The research on picking robots is vital to the transformation and upgrading of the agroforestry industry and the revitalization and development of rural areas. This paper examines the research field of agroforestry picking robots by meticulously combing and analyzing 623 CNKI and 648 WoS core literature from 2004 to 2022 selected in China Knowledge Network (CNKI) and Web of Science (WoS) databases using Cite Space 6.1R3 software. The analysis includes the quantity of literature, issuing countries, organizations, keywords, keyword clustering, emerging terms, etc. On this basis, research hotspots in the field of agroforestry picking robots are identified, such as research based on the identification of picking targets, the control of motion planning, structural design and simulation, and the planning of walking paths. This paper analyzes and discusses these research hotspots and main lines, providing a reference for future studies in this field. This bibliometric approach can provide comprehensive literature information for research in related fields, as well as identify and summarize the major research hotspots in a shorter time, allowing new researchers to enter the field more quickly and obtain more valuable scientific information

Visual Quality Assessment of Historical Street Scenes: A Case Study of the First “Real” Street Established in Baghdad

Historical street scenes materialize essential cultural and artistic values for the cities in which they are located and their citizens. However, the visual quality of historical scenes is susceptible to a number of causes that could result in their deterioration. These causes can be environmental or man-made, with either generating elements that may influence the perceived visual quality of historical scenes. Therefore, this research is to assess the visual quality of historical street scenes and identify the elements that can potentially impact them. The study adopted a photo survey approach employing a Likert Scale as the main method to assess visual quality. In addition, a heatmap analysis technique was utilized to identify the elements that impact the visual quality of historical street scenes. The results indicate respondents’ high levels of dissatisfaction with the visual quality of Baghdad’s historical street scenes. The results also showed that modern facade materials, security concrete walls, and degraded buildings’ facades are elements that had a negative impact to the overall scenic quality. On the other hand, historical religious buildings, urban greenery, and unique historical buildings are elements that have a positive impact on the visual quality of historical street scenes. This research represents an approach for evaluating the visual impact and visual quality of historical street scenes, providing a quantitative tool for future initiatives focusing on the visual quality of historical legacy scenes. This research is a starting point for both researchers in urban conservation and architectural history, and municipal offices of improving the visual quality of historic streets scenes

Integrative Analysis of Metabolome and Transcriptome Reveals the Mechanism of Color Formation in Yellow-Fleshed Kiwifruit

During the development of yellow-fleshed kiwifruit (Actinidia chinensis), the flesh appeared light pink at the initial stage, the pink faded at the fastest growth stage, and gradually changed into green. At the maturity stage, it showed bright yellow. In order to analyze the mechanism of flesh color change at the metabolic and gene transcription level, the relationship between color and changes of metabolites and key enzyme genes was studied. In this study, five time points (20 d, 58 d, 97 d, 136 d, and 175 d) of yellow-fleshed kiwifruit were used for flavonoid metabolites detection and transcriptome, and four time points (20 d, 97 d, 136 d, and 175 d) were used for targeted detection of carotenoids. Through the analysis of the content changes of flavonoid metabolites, it was found that the accumulation of pelargonidin and cyanidin and their respective anthocyanin derivatives was related to the pink flesh of young fruit, but not to delphinidin and its derivative anthocyanins. A total of 140 flavonoid compounds were detected in the flesh, among which anthocyanin and 76% of the flavonoid compounds had the highest content at 20 d, and began to decrease significantly at 58 d until 175 d, resulting in the pale-pink fading of the flesh. At the mature stage of fruit development (175 d), the degradation of chlorophyll and the increase of carotenoids jointly led to the change of flesh color from green to yellow, in addition to chlorophyll degradation. In kiwifruit flesh, 10 carotenoids were detected, with none of them being linear carotenoids. During the whole development process of kiwifruit, the content of β-carotene was always higher than that of α-carotene. In addition, β-cryptoxanthin was the most-accumulated pigment in the kiwifruit at 175 d. Through transcriptome analysis of kiwifruit flesh, seven key transcription factors for flavonoid biosynthesis and ten key transcription factors for carotenoid synthesis were screened. This study was the first to analyze the effect of flavonoid accumulation on the pink color of yellow-fleshed kiwifruit. The high proportion of β-cryptoxanthin in yellow-fleshed kiwifruit was preliminarily found. This provides information on metabolite accumulation for further revealing the pink color of yellow-fleshed kiwifruit, and also provides a new direction for the study of carotenoid biosynthesis and regulation in yellow-fleshed kiwifruit