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Ultra-high integrated silicon nitride fluorescence excitation chip for point-to-point excitation of biofluorescence signals

Ultra-high integrated silicon nitride fluorescence excitatio...

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2023 Applied Optics and Photonics China: Optical Sensing, Imaging, and Display Technology and Applications;and Biomedical Optics, AOPC 2023

作者： Yan, Zejun Shi, Qing Wang, Bo Feng, Shilun Feng, Jijun Chen, Chang Zhao, Jianlong State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9781510672321

Current research is focused on the miniaturization and integration of detection devices for biological targets in order to adapt to outdoor and emergency field settings, as well as to enhance the flexibility and practicality of detection. This study proposes an ultra-high integrated silicon nitride fluorescence excitation chip for point-to-point excitation of biological fluorescence signals. By employing the finite-difference time-domain(FDTD) method and utilizing silicon nitride as the functional material, a visible light fluorescence excitation chip operating at the wavelength of 645nm was designed and fabricated. The chip is composed of an input grating coupler, multiple multimode interferometers, and output grating couplers. A grating array containing 2016 excitation points is constructed cascading multiple multimode interference splitters and connecting excitation gratings at the terminals. The single grating coupling efficiency of the chip is 30% with a total excitation light area of 4×4mm² and an emitted light angle of around 80 degrees. By adjusting the positions of different output grating couplers, the chip can adapt to excitation requirements at different locations, making it suitable for various applications such as fluorescence quantitative polymerase chain reaction(PCR) and digital PCR. With the help of microfluidic chambers and a photodetector, the chip successfully achieved the detection limit of 0.5 μmol/L Cyanine 5(Cy5) fluorescent reagent solution, which is sufficient for direct detection of PCR fluorescence signals. © 2023 SPIE. All rights reserved.

关键词： Silicon nitride

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Why was Pakistan extreme precipitation stronger in 2022 than in 2010?

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Advances in Climate Change Research 2023年第6期14卷 913-920页

作者： Xu YUAN Kun YANG Jing SUN Yan WANG Yan-Yi HE Mi-Jun ZOU Yao-Zhi JIANG Polar and Marine Research Institute College of Harbor and Coastal EngineeringJimei UniversityXiamen 361021China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China National Tibetan Plateau Data Center State Key Laboratory of Tibetan Plateau Earth SystemResource and EnvironmentChinese Academy of SciencesBeijing 100101China Institue of Geographic Science and Natural Resources Research Chinese Academy of Sciences Beijing 100101China School of Environmental and Geographical Science Shanghai Normal UniversityShanghai 200234China Yangtze River Delta National Observatory of Wetland Ecosystem Shanghai Normal UniversityShanghai 200234China

In Pakistan,five continuous extreme precipitation events in the summer(July-August)of 2022 caused disastrous floods,depriving thousands of people's lives and ruining millions of *** tremendous disaster in Pakistan also happened in 2010 but with three concentrated extreme precipitation events in the middle of *** amount of Pakistan heavy daily precipitation in 2022 surpasses that in 2010 record,making it the strongest precipitation event ever *** comprehensively understand the causes of extreme precipitation in Pakistan,this study investigated the anomalies in atmospheric circulation and moisture contribution of 2010/2022 extreme precipitation and compared their *** results show that an atmospheric blocking over northern Europe in both 2022 and 2010 enhanced convection in Pakistan by transporting cold-dry air from the high-latitude region and benefiting warm-wet monsoonal air marching to *** employing a moisture track model,the main moisture sources for summer precipitation in Pakistan were *** is found that moisture contributions except from Eurasia were enhanced,causing extreme *** particular,enhanced moisture contribution from the southern Indian Ocean and the northern Indian continent in 2022 are more prominent than that in *** increased moisture contribution in 2010 was due to increased evaporation induced by warming sea surface in the Indian Ocean,while much richer moisture transport in 2022 was attributed to the enhanced cross-equatorial flow induced by the anomalous subtropical high in the Southern ***,attention should be paid to the role of subtropical high in the Southern Hemisphere in addition to those in Northern Hemisphere in understanding disastrous extreme precipitation events inPakistan.

关键词： Extreme precipitation Moisture transport Moisture sources Pakistan

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AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation 38

AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmenta...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Han, Boyu Xu, Qianqian Yang, Zhiyong Bao, Shilong Wen, Peisong Jiang, Yangbangyan Huang, Qingming Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS China School of Computer Science and Tech. University of Chinese Academy of Sciences China Peng Cheng Laboratory China Key Laboratory of Big Data Mining and Knowledge Management CAS China

The Area Under the ROC Curve (AUC) is a well-known metric for evaluating instance-level long-tail learning problems. In the past two decades, many AUC optimization methods have been proposed to improve model performance under long-tail distributions. In this paper, we explore AUC optimization methods in the context of pixel-level long-tail semantic segmentation, a much more complicated scenario. This task introduces two major challenges for AUC optimization techniques. On one hand, AUC optimization in a pixel-level task involves complex coupling across loss terms, with structured inner-image and pairwise inter-image dependencies, complicating theoretical analysis. On the other hand, we find that mini-batch estimation of AUC loss in this case requires a larger batch size, resulting in an unaffordable space complexity. To address these issues, we develop a pixel-level AUC loss function and conduct a dependency-graph-based theoretical analysis of the algorithm's generalization ability. Additionally, we design a Tail-Classes Memory Bank (T-Memory Bank) to manage the significant memory demand. Finally, comprehensive experiments across various benchmarks confirm the effectiveness of our proposed AUCSeg method. The code is available at https://***/boyuh/AUCSeg. © 2024 Neural information processing systems foundation. All rights reserved.

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Avoiding Non-Manhattan Obstacles Based on Projection of Spatial Corners in Indoor Environment

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1190-1200页

作者： Luping Wang Hui Wei the School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China the Laboratory of Algorithms for Cognitive Models Shanghai Key Laboratory of Data ScienceSchool of Computer ScienceFudan UniversityShanghai 201203China

Monocular vision-based navigation is a considerable ability for a home mobile robot. However, due to diverse disturbances, helping robots avoid obstacles, especially nonManhattan obstacles, remains a big challenge. In indoor environments, there are many spatial right-corners that are projected into two dimensional projections with special geometric configurations. These projections, which consist of three lines,might enable us to estimate their position and orientation in 3 D scenes. In this paper, we present a method for home robots to avoid non-Manhattan obstacles in indoor environments from a monocular camera. The approach first detects non-Manhattan obstacles. Through analyzing geometric features and constraints,it is possible to estimate posture differences between orientation of the robot and non-Manhattan obstacles. Finally according to the convergence of posture differences, the robot can adjust its orientation to keep pace with the pose of detected non-Manhattan obstacles, making it possible avoid these obstacles by itself. Based on geometric inferences, the proposed approach requires no prior training or any knowledge of the camera’s internal parameters,making it practical for robots navigation. Furthermore, the method is robust to errors in calibration and image noise. We compared the errors from corners of estimated non-Manhattan obstacles against the ground truth. Furthermore, we evaluate the validity of convergence of differences between the robot orientation and the posture of non-Manhattan obstacles. The experimental results showed that our method is capable of avoiding non-Manhattan obstacles, meeting the requirements for indoor robot navigation.

关键词： Avoiding obstacle monocular vision navigation non-Manhattan obstacle spatial corner

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UAV-Assisted data Synchronization for Digital-Twin-Enabled Vehicular Networks

UAV-Assisted Data Synchronization for Digital-Twin-Enabled V...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Wu, Guoquan Nie, Jiangtian Tang, Jianhang Zhang, Yang Xiao, Jiang Xiong, Zehui Yanshan University School of Information Science and Engineering China Nanyang Technological University School of Computer Science and Engineering Singapore Guizhou University State Key Laboratory of Public Big Data China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology China Huazhong University of Science and Technology School of Computer Science and Technology China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore

ISBN: (纸本)9798350345384

Digital twin (DT) is becoming a promising solution for vehicular networks to improve the interoperability of distributed autonomous driving systems. Mobile edge computing (MEC) has been introduced to provide low-latency services for DT-enabled vehicular networks at the edge of the network. However, it is hard to obtain the dynamic network topology for moving vehicles by the ground-based MEC system, which may deteriorate the service quality for DT synchronization. In this paper, we propose a novel unmanned aerial vehicle (UAV)-assisted synchronization framework for DT-enabled vehicular networks. With the proposed framework, an intelligent resource allocation algorithm is developed to improve UAV resource utilization and maximize the synchronization completion ratio. By leveraging an advantage actor-critic (A2C) algorithm, the synchronization decisions are obtained with low time complexity. Experiment results demonstrate that the proposed algorithm can reduce the synchronization latency and improve the synchronization completion ratio effectively. © 2023 IEEE.

关键词： Resource allocation

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Generalization error bounds for two-stage recommender systems with tree structure 24

Generalization error bounds for two-stage recommender system...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Jin Zhang Ze Liu Defu Lian Enhong Chen School of Artificial Intelligence and Data Science University of Science and Technology of China School of Computer Science and Technology University of Science and Technology of China School of Artificial Intelligence and Data Science and School of Computer Science and Technology University of Science and Technology of China and State Key Laboratory of Cognitive Intelligence Hefei Anhui China

ISBN: (纸本)9798331314385

Two-stage recommender systems play a crucial role in efficiently identifying relevant items and personalizing recommendations from a vast array of options. This paper, based on an error decomposition framework, analyzes the generalization error for two-stage recommender systems with a tree structure, which consist of an efficient tree-based retriever and a more precise yet time-consuming ranker. We use the Rademacher complexity to establish the generalization upper bound for various tree-based retrievers using beam search, as well as for different ranker models under a shifted training distribution. Both theoretical insights and practical experiments on real-world datasets indicate that increasing the branches in tree-based retrievers and harmonizing distributions across stages can enhance the generalization performance of two-stage recommender systems.

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Fine-scale north-to-south genetic admixture profile in Shaanxi Han Chinese revealed by genome-wide demographic history reconstruction

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植物分类学报 2022年第4期60卷 955-972页

作者： Guang-Lin He Meng-Ge Wang Ying-Xiang Li Xing Zou Hui-Yuan Yeh Ren-Kuan Tang Xiao-Min Yang Zheng Wang Jian-Xin Guo Ting Luo Jing Zhao Jin Sun Rong Hu Lan-Hai Wei Gang Chen Yi-Ping Hou Chuan-Chao Wang Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and MedicineState Key Laboratory of Marine Environmental ScienceState Key Laboratory of Cellular Stress Biologyand School of Life SciencesXiamen UniversityXiamen 361005China Institute of Forensic Medicine West China School of Basic Science and Forensic MedicineSichuan UniversityChengdu 610065China Institute of Forensic Medicine West China School of Basic Science and Forensic MedicineSichuan UniversityChengdu 610065China Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and MedicineState Key Laboratory of Marine Environmental ScienceState Key Laboratory of Cellular Stress Biologyand School of Life SciencesXiamen UniversityXiamen 361005China School of Humanities Nanyang Technological UniversityNanyang 639798Singapore Department of Forensic Medicine College of Basic MedicineChongqing Medical UniversityChongqing 400331China Hunan Key Laboratory of Bioinformatics School of Computer Science and EngineeringCentral South UniversityChangsha 410075China

The Han Chinese are the world's largest ethnic group residing across *** province in northern China was a pastoral-agricultural interlacing region sensitive to climate change since Neolithic times,which makes it a vital place for studying population ***,genetic studies of Shaanxi Han are underrepresented due to the lack of high-density sampling and genome-wide ***,we genotyped 700 000 single nucleotide polymorphisms(SNPs)in 200 Han individuals from nine populations in Shaanxi and compared with available modem and ancient Eurasian *** revealed a north-south genetic cline in Han Chinese with Shaanxi Han locating at the northern side of the *** detected the western Eurasian-related admixture in Shaanxi populations,especially in Guanzhong and Shanbei Han Chinese in proportions of 2％-4.6％.Shaanxi Han were suggested to derive a large part of ancestry(39％-69％)from a lineage that also contributed largely to ancient and present-day Tibetans(85％)as well as southern Han,supporting the common northern China origin of modem Sino-Tibetan-speaking populations and southwestward expansion of millet farmers from the middle-upper Yellow River Basin to the Tibetan Plateau and to southern *** rest of the ancestry of Shaanxi Han was from a lineage closely related to ancient and present-day Austronesian and Tai-Kadai speaking populations in southern China and Southeast *** also observed a genetic substructure in Shaanxi Han in terms of north-south-related ancestry corresponding well to the *** mitochondrial DNA and paternal Y-chromosome lineages further demonstrated the aforementioned admixture pattern of Han Chinese in Shaanxi province.

关键词： ancestral makeup genetic relationship haplogroup Northern Han population substructure western Eurasian admixture

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A Programming Language Learning Service by Linking Stack Overflow with Textbooks

A Programming Language Learning Service by Linking Stack Ove...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Wu, Jiawei Sun, Yanchun Zhang, Jiaqi Zhou, Yuqi Huang, Gang Ministry of Education Key Laboratory of High Confidence Software Technologies China Peking University School of Computer Science Beijing China Peking University School of Software and Microelectronics Beijing China National Key Laboratory of Data Space Technology and System China

ISBN: (纸本)9798350304855

Before software developers actually start coding, an essential requirement is to be proficient in a programming language. However, as an important learning resource, programming language textbooks usually contain much about syntax and semantics of a programming language, but little about pragmatics, which is highly relevant with practical skills in solving real-world problems using programming languages. This makes it difficult for learners to transfer knowledge from textbooks to *** solve this problem, this paper proposes a programming language learning service, utilizing abundant development knowledge in Stack Overflow (SO) Q&A posts as the pragmatics knowledge of programming languages to make up for the shortage of pragmatics knowledge in textbooks. To link SO Q&A posts with textbooks, this paper first proposes a deep learning classification model to recognize SO posts containing development knowledge. Second, to align filtered SO posts with programming language learning processes, this paper proposes a weakly supervised link approach to matching SO posts with chapters and sections of textbooks. The feature of weak supervision ensures that the approach can be easily extended to other textbooks. Based on these modules above, this paper implements the programming language learning service in the form of a Chrome plugin. We conduct experiments and user study. Their results demonstrate the effectiveness, scalability and stability of the service. © 2023 IEEE.

关键词： Textbooks

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Current progress,challenges,and future perspectives of language models for protein representation and protein design

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The Innovation 2023年第4期4卷 27-28页

作者： Tao Huang Yixue Li Bio-Med Big Data Center CAS Key Laboratory of Computational BiologyShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Guangzhou Laboratory Guangzhou 510005China School of Life Sciences and Biotechnology Shanghai Jiao Tong UniversityShanghai 200240China Collaborative Innovation Center for Genetics and Development Fudan UniversityShanghai 200433China

The sequence-structure-function paradigm of protein is the basis of molecular *** is the underlying mechanism of such sequence and structure/function corresponding relationship?We reviewed the methods for protein representation and protein *** these protein representation models,we can accurately predict many properties of proteins,such as stability and binding affinity.

关键词： representation function design.

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THINK THRICE BEFORE YOU ACT: PROGRESSIVE THOUGHT REFINEMENT IN LARGE LANGUAGE MOD ELS

arXiv

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arXiv 2024年

作者： Du, Chengyu Han, Jinyi Ying, Yizhou Chen, Aili He, Qianyu Zhao, Haokun Xia, Sirui Guo, Haoran Liang, Jiaqing Chen, Zulong Li, Liangyue Xiao, Yanghua Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China Shanghai Institute of Artificial Intelligence for Education East China Normal University China School of Data Science Fudan University China Alibaba Group China RhineAI Netherlands

Recent advancements in large language models (LLMs) have demonstrated that progressive refinement, rather than providing a single answer, results in more accurate and thoughtful outputs. However, existing methods often rely heavily on supervision signals to evaluate previous responses, making it difficult to effectively assess output quality in more open-ended scenarios. Additionally, these methods are typically designed for specific tasks, which limits their generalization to new domains. To address these limitations, we propose Progressive Thought Refinement (PTR), a framework that enables LLMs to progressively refine their responses. PTR operates in two phases: (1) Thought data construction stage: We propose a weak and strong model collaborative selection strategy to build a high-quality progressive refinement dataset to ensure logical consistency from thought to answers, and the answers are gradually refined in each round. (2) Thought-Mask Fine-Tuning Phase: We design a training structure to mask the "thought" and adjust loss weights to encourage LLMs to refine prior thought, teaching them to implicitly understand "how to improve" rather than "what is correct." Experimental results show that PTR significantly enhances LLM performance across ten diverse tasks (avg. from 49.6% to 53.5%) without task-specific fine-tuning. Notably, in more open-ended tasks, LLMs also demonstrate substantial improvements in the quality of responses beyond mere accuracy, suggesting that PTR truly teaches LLMs to self-improve over time. Copyright © 2024, The Authors. All rights reserved.

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