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51st International Conference on Very Large Data Bases, VLDB 2025

作者： Zhang, Shijie Cheng, Ru Liu, Xinpeng Xiao, Jiang Jin, Hai Li, Bo National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

Increasingly popular decentralized applications (dApps) with complex application logic incur significant overhead for executing smart contract transactions, which greatly limits public block chain performance. Pre-executing transactions off the critical path can mitigate substantial I/O and computation costs during execution. However, pre-execution does not yield any state transitions, rendering the system state inconsistent with actual execution. This inconsistency can lead to deviations in pre-execution paths when processing smart contracts with multiple state-related branches, thus diminishing pre-execution effectiveness. In this paper, we develop Seer, a novel public block chain execution engine that incorporates fine-grained branch prediction to fully exploit pre-execution effectiveness. Seerpredicts state-related branches using a two-level prediction approach, reducing inconsistent execution paths more efficiently than executing all possible branches. To enable effective reuse of pre execution results, Seer employs checkpoint-based fast-path execution, enhancing transaction execution for both successful and unsuccessful predictions. Evaluations with realistic block chain workloads demonstrate that Seer delivers an average of 27.7× transaction-level speedup and an overall 20.6× speedup in the execution phase over vanilla Ethereum, outperforming existing block chain execution acceleration solutions. © 2025, VLDB Endowment, All rights reserved.

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Ultra-low intensity light pulses for large cargo delivery into hard-to-transfect cells using an rGO mixed PDMS microtip device

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Lab on a Chip 2024年第16期24卷 3880-3897页

作者： Padma, Hima Harshan Illath, Kavitha Dominic, Donia Chang, Hwan-You Nagai, Moeto Ojha, Rajdeep Kar, Srabani Santra, Tuhin Subhra Department of Engineering Design Indian Institute of Technology Madras India Department of Medical Science National Tsing Hua University Taiwan Department of Mechanical Engineering Toyohashi University of Technology Japan Department of Physical Medicine and Rehabilitation Christian Medical College Vellore India Department of Physics Indian Institute of Science Education and Research Tirupati India

Nanoparticle-mediated photoporation has arisen as a universal intracellular delivery tool;however, the direct interaction of nanoparticles and cells hampers its clinical translation. Here, we report a uniform contactless intracellular delivery that transfects a large number of cells within a minute and avoids direct contact of nanoparticles and cells, thereby improving the cell viability. Our platform consists of an array of polydimethylsiloxane (PDMS) mixed reduced graphene oxide (rGO) nanoflakes on pyramidal microtips, uniformly distributed at the apex of the tip. The extraordinary optoelectronic properties of rGO were combined with micro-pyramidal cavities to entrap light in micro-cavities and efficiently convert it into heat through multiple reflections and absorptions. As a result, ultralow infra-red laser pulse irradiation could create cavitation bubbles followed by cell membrane deformation and biomolecular delivery. Using this delivery platform, we have achieved the delivery of small to large cargo (668 Da to 465 kDa) in various mammalian cells, including hard-to-transfect H9C2 cardiomyocytes. The best results were achieved for enzyme (465 kDa) delivery with a transfection efficiency and cell viability of 95% and 98%, respectively, in SiHa cells. The highly efficient cargo delivery tool demonstrated a safe and effective approach for cell therapy and diagnostics. © 2024 The Royal Society of Chemistry.

关键词： Cells

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Exploring Integration of Multimodal Deep Learning Approaches for Enhanced Alzheimer's Disease Diagnosis: A Review of Recent Literature

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SN Computer science 2024年第7期5卷 852页

作者： Deshpande, Sonali Kulkarni, Nilima Computer Science & amp Engineering Department MIT SoC MIT Art Design and Technology University Pune India

Alzheimer's disease (AD), is the most common form of dementia that affects the nervous system. In the past few years, non-invasive early AD diagnosis has become more popular as a way to improve patient care and treatment results. Imaging methods, electroencephalogram (EEG) tests, and sound evaluations are some of the new ways that researchers have looked into. This review covers 60 papers published from 2020. They are compared in terms of how they use basic deep learning models such as CNN, LSTM, Alex Net, Inception Net, VGG19, and ResNet to identify AD. But not many studies use more than one method together, like image and EEG, EEG and sounds, or images and sounds. The information from the Scopus database makes it easy to look at the newest information and work. This means that using more than one method to find AD isn't getting as much attention. Our review says that combining the best parts of each method in a mixed way could make Alzheimer's research much more useful and lead to better ways to diagnose. The paper talks about problems and opportunities in the field right now as well as possible study topics and issues for the future. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Alzheimer's disease (AD) Deep learning Electroencephalography Machine learning Magnetic resonance imaging Neurological disorders Sound

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Impact of Process-Induced Inclined Side-Walls on Gate Leakage Current of Nanowire GAA MOSFETs

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IEEE Transactions on Electron Devices 2024年第3期71卷 2196-2202页

作者： Maniyar, Ashraf Raj, Pushp Srinivas, P.S.T.N. Kumar, Arun Chang-Liao, Kuei-Shu Tiwari, Pramod Kumar Indian Institute of Technology Patna Department of Electrical Engineering Bihar Patna801106 India Vellore Institute of Technology School of Electronics Engineering Vellore801106 India National Institute of Technology Silchar Department of Electronics and Communication Engineering Silchar788010 India National Tsing Hua University Department of Engineering and System Science Hsinchu30013 Taiwan

In this work, the influence of process-induced sidewall inclination on direct tunneling gate leakage current (IG) in the trapezoidal (Tz) channel NW GAA MOSFETs has been comprehensively investigated using experimental data and the TCAD simulations results. Variability in device parameters as channel length, height, and width have been taken into account when we examined gate leakage current. The side-wall inclination angle has a significant influence on the gate leakage current, where a rise in IG of up to two times is observed when the inclination angle is increased from 0 to 20. Moreover, it has also been observed that the direct tunneling gate leakage current is significantly influenced by the gate overlap and underlap areas. © 1963-2012 IEEE.

关键词： III-V semiconductors

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Deep Neural Network and GAN-Based Reversible Data Hiding in Encrypted Images: A Privacy-Preserving Approach

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SN Computer science 2024年第1期5卷 45页

作者： Nalavade, Jagannath E. Patil, Akshta Buchade, Amar Jadhav, Nagesh Department of Computer Science and Engineering MIT Art Design and Technology University School of Computing Pune India Department of Computer Engineering Rajarambapu Institute of Technology Sakharale Sangli India

In light of recent incidents involving the leakage of private photographs of Hollywood celebrities from iCloud, the need for robust methods to safeguard image content has gained paramount importance. This paper addresses this concern by introducing a novel framework for reversible image editing (RIT) supported by reversible data hiding with encrypted images (RDH-EI) techniques. Unlike traditional approaches vulnerable to hacking, this framework ensures both efficient and secure data embedding while maintaining the original image’s privacy. The framework leverages two established methods: secret writing and knowledge activity. While secret writing is susceptible to hacking due to the complex nature of cipher languages, RDH-EI-supported RIT adopts a more secure approach. It replaces the linguistic content of the original image with the semantics of a different image, rendering the encrypted image visually indistinguishable from a plaintext image. This novel substitution prevents cloud servers from detecting encrypted data, enabling the adoption of reversible data hiding (RDH) methods designed for plaintext images. The proposed framework offers several distinct advantages. Firstly, it ensures the confidentiality of sensitive information by concealing the linguistic content of the original image. Secondly, it supports reversible image editing, enabling the restoration of the original image from the encrypted version without any loss of data. Lastly, the integration of RDH techniques designed for plaintext images empowers the cloud server to embed supplementary data while preserving image quality. Incorporating convolutional neural network (CNN) and generative adversarial network (GAN) models, the framework ensures accurate data extraction and high-quality image restoration. The applications of this concealed knowledge are vast, spanning law enforcement, medical data privacy, and military communication. By addressing limitations of previous methods, it opens new avenues

关键词： Deep hiding Deep neural network GAN model Reversible data hiding (RDH)

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Bi-Directional Deformation, Stiffness-Tunable, and Electrically Controlled Soft Actuators Based on LCEs 4D Printing 16th

Bi-Directional Deformation, Stiffness-Tunable, and Electrica...

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16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Qiu, Wanglin Wang, Yaohui He, Xiangnan Ge, Qi Xiong, Yi School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9789819964918

The integration of 3D printing with smart materials in 4D printing technology has attracted extensive research attention due to its capability of endowing static printed structures with dynamic behaviors and actions that evolve over time. One such promising smart material is liquid crystal elastomers (LCEs), which offer excellent reversible actuation performance and programmable anisotropy. However, the field of LCEs-based 4D printing faces challenges in achieving sufficient mechanical performance due to their low elastic modulus, which hinders their ability to handle tasks requiring relatively high load-bearing capacity. Moreover, there are also challenges related to their complex actuation environments, which further restrict the applications based on LCEs. In this work, we propose a paradigm for designing and manufacturing electrically-controlled soft actuators capable of reversible deformation and adjustable stiffness. Specifically, we integrate LCEs with continuous fiber-reinforced polymer composites (CFRP) and elastomeric materials into a multilayer sandwich structure. By combining CFRP, we significantly enhance the stiffness of the actuators without compromising their flexibility and adaptability. Furthermore, the inclusion of continuous carbon fibers (CCF) enables electrical control of the actuators. Finally, by incorporating pre-stretched elastomeric materials, we fabricate an electrically-controlled actuator with excellent mechanical performance and reversible actuation capabilities. As a demonstration, we create an intelligent soft gripper with outstanding mechanical performance and reversible actuation, exhibiting high load-bearing capacity and shape adaptability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Stiffness

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Physiological and psychological effects of spotlight in a limited space

Physiological and psychological effects of spotlight in a li...

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AIAA science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Yoshino, Karin Takahashi, Masaki School of Science for Open and Environmental Systems Keio University Kanagawa Yokohama223-8522 Japan Faculty of Science and Technology Department of System Design Engineering Keio University Kanagawa Yokohama223-8522 Japan

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In a limited space, such as pressurized rovers, insufficient personal space is a source of stress for astronauts. The aim of this study is to mitigate effects caused by personal space invasions. The proposed system for that problem is using a spotlight system that automatically adjusts based on vital sign feedback. In this study, experiments with human subjects to test the effects of spotlight exposure are conducted. Specifically, respiration signal was measured to investigate the relationship between respiration, distance and the spotlight in a limited space. The results suggest that changes in respiration may reflect the effects of spatial distance, suggesting that respiration may serve as an indicator of personal spatial discomfort. Furthermore, the usefulness of spotlight lighting in confined spaces was demonstrated through its effects on breathing, demonstrating its potential to enhance comfort by adjusting lighting based on vital sign. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Lighting

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Skeleton-Based Volumetric Parameterizations for Lattice Structures

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Computer Modeling in engineering & sciences 2023年第4期135卷 687-709页

作者： Long Chen Shuxun Liang Nan Yan Xiangqian Yang Baotong Li School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai200093China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Key Laboratory of EducationMinistry for Modern Design&Rotor-Bearing System Xi’an Jiaotong UniversityXi’an710049China

Lattice structures with excellent physical properties have attracted great research *** this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice *** skeleton model is divided into three types of *** the corresponding algorithms are utilized to construct diverse types of volume parametric *** unit-cell is assembled with distinct nodes according to the geometric *** final lattice structure is created by the periodic arrangement of *** different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed *** quality is assessed in terms of the value of the Jacobian ***,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.

关键词： Lattice structure volumetric parameterization skeleton model node modeling

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Preventing 51% Attack by Using Consecutive Block Limits in Bitcoin

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IEEE Access 2024年 12卷 77852-77869页

作者： Mahmood Babur, Sohail Ur Rehman Khan, Shafiq Yang, Jing Chen, Yen-Lin Soon Ku, Chin Yee Por, Lip Government Murray College Department of Information Technology Sialkot51010 Pakistan Capital University of Science and Technology Department of Computer Science Islamabad44730 Pakistan Universiti Malaya Department of Computer System and Technology Kuala Lumpur50603 Malaysia National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

In permissionless blockchain systems, Proof of Work (PoW) is utilized to address the issues of double-spending and transaction starvation. When an attacker acquires more than 50% of the hash power of the entire network, they gain the ability to engage in double-spending activities, posing a significant threat to the PoW consensus algorithm. This research focuses on the consensus algorithm employed in the Bitcoin system, explaining how it operates and the security challenges it faces. The proposed modification to the PoW algorithm imposes a restriction on miners: they are not allowed to accept consecutive blocks from the same miner into the final local blockchain to prevent the 51% attack problem. This modification supports transactions that require six confirmations. In the event an attacker attempts a 51% attack with a private chain that consists of fewer than 6 blocks, it becomes easier to detect a double-spending attack before accepting the attacker's private chain. The modified algorithm introduces a 'Safe Mode Detection Algorithm' that scrutinizes incoming blocks for adjustments at the top of the local blockchain. If inconsistencies are identified, the consensus algorithm proceeds cautiously by comparing the UTXO dictionaries from the attacker's chain with those from the miner's own blockchain. This meticulous comparison aims to detect instances of double-spending. If such instances are detected, the miner rejects the attacker's chain, establishing a double-spend-free environment and thwarting 51% attacks. © 2013 IEEE.

关键词： Blockchain

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Backup subscription scheme for differential protection using IEC61850-9-2 sampled values

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Energy Informatics 2024年第1期7卷 110页

作者： Katoulaei, Mohammad Khalili Rahmani, Aamir Høidalen, Hans Kristian Oleinikova, Irina Mork, Bruce Department of energy systems Norwegian University of Science and Technology Trondheim Norway Department of electrical power system Michigan Technical University Michigan United States Department of Electrical Power Engineering Norwegian University of Science and Technology Trondheim Norway Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI49931 United States

In IEC-61850-based digital substations, the protection IED’s performance is dependent on merging unit’s vendor implementation, communication networks, and measurement circuit’s health conditions. As the process bus Sampled Value(SV) enables the availability of all sensor data on a communication network, this paper proposes a Backup Subscription scheme (BSS) for a transformer differential protection (87T, PDIF) function. BSS utilizes sensor data in digital substations to achieve a flexible protection scheme using a dynamic subscription feature. Thus, in case of failure of one sensor, differential protection would be maintained. The paper presents the implementation and verification of a prototyped scheme using a Hardware-in-the-loop simulation test bed. The main result is that BSS integration into differential protection ensures its dependability and security. Moreover, delay compensation and seamless switching feature increases the availability of differential protection. © The Author(s) 2024.

关键词： Hardware-in-the-loop simulation

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