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Haplotype-resolved Chinese male genome assembly based on high-fidelity sequencing

Fundamental Research 2022年第6期2卷 946-953页

作者： Xiaofei Yang Xixi Zhao Shoufang Qu Peng Jia Bo Wang Shenghan Gao Tun Xu Wenxin Zhang Jie Huang Kai Ye Genome Institute the First Affiliated Hospital of Xi'an Jiaotong UniversityXi'an 710061ShaanxiChina School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina National Institutes for food and drug Control(NIFDC) No.2Tiantan XiliDongcheng DistrictBeijing 102629China School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina School of Life Science and Technology Xi'an Jiaotong UniversityXi'an 710049ShaanxiChina Faculty of Science Leiden UniversityLeidenThe Netherlands

The advantages of both the length and accuracy of high-fidelity(HiFi)reads enable chromosome-scale haplotype-resolved genome *** this study,we sequenced a cell line named HJ,established from a Chinese Han male individual by using HiFi and *** assembled two high-quality haplotypes of the HJ genome(haplotype 1(H1):3.1 Gb,haplotype 2(H2):2.9 Gb).The continuity(H1:contig N50=28.2 Mb,H2:contig N50=25.9 Mb)and completeness(BUSCO:H1=94.9%,H2=93.5%)are substantially better than those of other Chinese genomes,for example,HX1,NH1.0,and *** comparing HJ genome with GRCh38,we reported the mutation landscape of HJ and found that 176 and 213 N-gaps were filled in H1 and H2,*** addition,we detected 12.9 Mb and 13.4 Mb novel sequences containing 246 and 135 protein-coding genes in H1 and H2,*** results demonstrate the advantages of HiFi reads in haplotype-resolved genome assembly and provide two high-quality haplotypes of a potential Chinese genome as a reference for the Chinese Han population.

关键词： Genome assembly HiFi reads Human genome Haplotype-resolved Chinese Han Mutation landscape

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A Power Split Strategy for a Vehicular Hybrid Energy Storage System Using Adaptive Neuro Fuzzy Inference System

A Power Split Strategy for a Vehicular Hybrid Energy Storage...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Jiao Li Lijun Zhang Longzhi Yang Bo Wang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Wuhan China Department of Computer Science and Digital Technologies Faculty of Engineering and Environment Northumbria University Newcastle upon Tyne U.K

This paper presents a real-time power split strategy for a battery-supercapacitor hybrid energy storage system. The objective of the proposed strategy is to alleviate battery degradation through effective supercapacitor utilization. The proposed strategy employs an adaptive neural fuzzy inference system, which is capable of learning a power split strategy from offline optimization results and distributing power in real-time. The performance of the strategy proposed and a low pass filtering technique is compared through simulations. The results demonstrate that the proposed method can effectively reduce battery capacity loss and perform well under unknown driving cycles in real time.

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Relational Prompt-based Pre-trained Language Models for Social Event Detection

arXiv

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arXiv 2024年

作者： Pu, L.I. Xiaoyan, Y.U. Peng, Hao Xian, Yantuan Wang, Linqin Li, S.U.N. Zhang, Jingyun Philip, S.Y.U. Faculty of Information Engineering and Automation Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Cyber Science and Technology Beihang University No. 37 Xue Yuan Road Haidian District Beijing100191 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China Department of Computer Science University of Illinois at Chicago ChicagoIL60607 United States

Social Event Detection (SED) aims to identify significant events from social streams, and has a wide application ranging from public opinion analysis to risk management. In recent years, Graph Neural Network (GNN) based solutions have achieved state-of-the-art performance. However, GNN-based methods often struggle with missing and noisy edges between messages, affecting the quality of learned message embedding. Moreover, these methods statically initialize node embedding before training, which, in turn, limits the ability to learn from message texts and relations simultaneously. In this paper, we approach social event detection from a new perspective based on Pre-trained Language Models (PLMs), and present RPLM (Relational prompt-based Pre-trained Language Models for Social Event Detection). We first propose a new pairwise message modeling strategy to construct social messages into message pairs with multi-relational sequences. Secondly, a new multi-relational prompt-based pairwise message learning mechanism is proposed to learn more comprehensive message representation from message pairs with multi-relational prompts using PLMs. Thirdly, we design a new clustering constraint to optimize the encoding process by enhancing intra-cluster compactness and inter-cluster dispersion, making the message representation more distinguishable. We evaluate the RPLM on three real-world datasets, demonstrating that the RPLM model achieves state-of-the-art performance in offline, online, low-resource, and long-tail distribution scenarios for social event detection tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

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Reduced Network Cumulative Constraint Violation for Distributed Bandit Convex Optimization under Slater’s Condition

arXiv

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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Ding, Jinliang Cao, Ming Johansson, Karl H. Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201800 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint violation, existing distributed bandit online algorithms solving this problem directly use the clipped constraint function to replace its original constraint function. However, the use of the clipping operation renders Slater’s condition (i.e, there exists a point that strictly satisfies the inequality constraints at all iterations) ineffective to achieve reduced network cumulative constraint violation. To tackle this challenge, we propose a new distributed bandit online primal–dual algorithm. If local loss functions are convex, we show that the proposed algorithm establishes an O(T max{c,1−c})network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the total number of iterations and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds, the network cumulative constraint violation bound is reduced to O(T 1−c). In addition, if local loss functions are strongly convex, for the case where strongly convex parameters are unknown, the network regret bound is reduced to O(T1−c), and the network cumulative constraint violation bound is O(T1−c/2) and O(T1−c) without and with Slater’s condition, respectively. For the case where strongly convex parameters are known, the network regret bound is further reduced to O)(log(T)), and the network cumulative constraint violation bound is reduced to O(log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is among the first to establish reduced (network) cumulative constraint violation bounds for (distributed) bandit convex optimization with time-varying constraints under Slater’s condition. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2

关键词： Convex optimization

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Grasp-Anything: Large-scale Grasp Dataset from Foundation Models

Grasp-Anything: Large-scale Grasp Dataset from Foundation Mo...

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IEEE International Conference on Robotics and automation (ICRA)

作者： A. D. Vuong M. N. Vu H. Le B. Huang H. T. T. Binh T. Vo A. Kugi A. Nguyen FPT Software AI Center Vietnam Automation & Control Institute TU Wien Vienna Austria AIT Austrian Institute of Technology Vienna Austria Imperial College London UK Hanoi University of Science and Technology Vietnam Faculty of Mathematics and Statistics Ton Duc Thang University Ho Chi Minh City Vietnam Department of Computer Science University of Liverpool UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Foundation models such as ChatGPT have made significant strides in robotic tasks due to their universal representation of real-world domains. In this paper, we leverage foundation models to tackle grasp detection, a persistent challenge in robotics with broad industrial applications. Despite numerous grasp datasets, their object diversity remains limited compared to real-world figures. Fortunately, foundation models possess an extensive repository of real-world knowledge, including objects we encounter in our daily lives. As a consequence, a promising solution to the limited representation in previous grasp datasets is to harness the universal knowledge embedded in these foundation models. We present Grasp-Anything, a new large-scale grasp dataset synthesized from foundation models to implement this solution. Grasp-Anything excels in diversity and magnitude, boasting 1M samples with text descriptions and more than 3M objects, surpassing prior datasets. Empirically, we show that Grasp-Anything successfully facilitates zero-shot grasp detection on vision-based tasks and real-world robotic experiments. Our dataset and code are available at https://***/grasp-anything/.

关键词： Codes Service robots Chatbots Task analysis

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HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation

arXiv

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arXiv 2023年

作者： Vuong, An Nguyen, Toan Vu, Minh Nhat Huang, Baoru Binh, H.T.T. Vo, Thieu Nguyen, Anh FPT Software AI Center Viet Nam Automation & Control Institute TU Wien Austria Austria Imperial College London United Kingdom Hanoi University of Science and Technology Viet Nam Faculty of Mathematics and Statistics TDTU Viet Nam Department of Computer Science University of Liverpool United Kingdom

Visual navigation, a foundational aspect of Embodied AI (E-AI) and robotics has been extensively studied in the past few years. While many 3D simulators have been introduced for the visual navigation tasks, scarcely works have combined human dynamics, creating the gap between simulation and real-world applications. Furthermore, current 3D simulators incorporating human dynamics have several limitations, particularly in terms of computational efficiency, which is a promise of modern simulators. To overcome these issues, we introduce HabiCrowd, the new standard benchmark for crowd-aware visual navigation that includes a crowd dynamics model with diverse human settings into photorealistic environments. Empirical evaluations demonstrate that our proposed human dynamics model achieves state-of-the-art performance in collision avoidance while exhibiting superior computational efficiency compared to its counterparts. We leverage HabiCrowd to conduct several comprehensive studies on crowd-aware visual navigation tasks and human-robot interactions. The source code and data can be found at https://***/. © 2023, CC BY-NC-SA.

关键词： Human robot interaction

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An e-Business Services Composition Framework

An e-Business Services Composition Framework

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International Conference on Communications (COMM)

作者： Eugen Pop Daniela Gî fu Automatics and Industrial Informatics Department Faculty of Automatic Control and Computers University &#x201C Politehnica&#x201D of Bucharest R&#x0026 D Institute for Automation-IPA SA Bucharest Romania Institute of Computer Science of Romanian Academy - Iasi Branch Faculty of Computer Science of Alexandru Ioan Cuza University of Iasi Iasi Romania

E-business offers to economic agents the opportunity to increase the efficiency of their activity, promote and offer their products and services on a large and diversified market. Often a single service, separately, does not meet all the needs of various categories and groups of customers. In such a situation, service composition can provide more technical, commercial, informational facilities than each separate component service can offer. There are many web-based frameworks used for e-business, but still with limitations. The paper presents a Services Composition Framework and a wise algorithm for e-business models, based on REST and SOAP web services. It is intended to be used for the development of e-business models, comprising stock market exchange, e-commerce, e-banking, etc. The customers can access the framework services, through Smartphones, on mobile and wireless communication channels. Within a Quality-of-Service performance analysis of the e-business Service Composition Framework, the response time and throughput for multiuser access simultaneous requests were evaluated. A stock market exchange service is considered, as an e-business service example, while Bucharest Stock Exchange information is the digital content source for data transactions.

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Open-Vocabulary Affordance Detection using Knowledge Distillation and Text-Point Correlation

arXiv

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arXiv 2023年

作者： Van Vo, Tuan Vu, Minh Nhat Huang, Baoru Nguyen, Toan Le, Ngan Vo, Thieu Nguyen, Anh FPT Software AI Center Viet Nam Automation & Control Institute TU Wien Vienna Austria Imperial College London United Kingdom Department of Computer Science University of Arkansas United States Faculty of Mathematics and Statistics Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science University of Liverpool United Kingdom

Affordance detection presents intricate challenges and has a wide range of robotic applications. Previous works have faced limitations such as the complexities of 3D object shapes, the wide range of potential affordances on real-world objects, and the lack of open-vocabulary support for affordance understanding. In this paper, we introduce a new open-vocabulary affordance detection method in 3D point clouds, leveraging knowledge distillation and text-point correlation. Our approach employs pre-trained 3D models through knowledge distillation to enhance feature extraction and semantic understanding in 3D point clouds. We further introduce a new text-point correlation method to learn the semantic links between point cloud features and open-vocabulary labels. The intensive experiments show that our approach outperforms previous works and adapts to new affordance labels and unseen objects. Notably, our method achieves the improvement of 7.96% mIOU score compared to the baselines. Furthermore, it offers real-time inference which is well-suitable for robotic manipulation applications. © 2023, CC BY-NC-SA.

关键词： Distillation

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Cyber-Physical Systems Based Business Models

Cyber-Physical Systems Based Business Models

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IEEE International Conference on automation, Quality and Testing, Robotics, AQTR

作者： Eugen Pop Daniela Gî fu Mihnea Alexandru Moisescu Automatics and Industrial Informatics Department Faculty of Automatic Control and Computers University "Politehnica" of Bucharest R&#x0026 D Institute for Automation - IPA SA Romania Institute of Computer Science Romanian Academy &#x2013 Ia&#x0219 i branch Faculty of Computer Science "Alexandru Ioan Cuza" University of Ia&#x0219 i Romania Automatics and Industrial Informatics Department Faculty of Automatic Control and Computers University "Politehnica" of Bucharest Romania

Currently, the use of cyber-physical systems is becoming widespread in various fields, primarily, because they enable many innovative functionalities through their networking. These systems include complex computation elements that interacts with the physical environment through sensors or actuators. Their solutions are based on sharing of hardware equipment and software services, targeting to provide added value proposition for various customers. The research and development in this domain are going on not only in the technical direction, but is also targeting the value creation for customers, in a technical and business-oriented manner. This paper presents a cyber-physical systems-based business model realized through services composition. The service composition framework integrates Web services which can be interconnected and can be accessed by mobile clients through smartphones, on mobile and wireless communications channels. The response time for multiuser requests for services access is evaluated, because it is an important quality of service performance criteria of our e-business model service composition framework. The results are promising.

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Enhancing Precision Agriculture Through Human-in-the-Loop Planning and control

Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

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IEEE International Conference on automation science and Engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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