Base editing, a revolutionary genome editing technology, has risen to prominence for its distinguished features such as high fidelity, precision, and targeted specificity. It has found broad applications across the sp...
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Low lignin solubility in aqueous solution is one of the major bottlenecks for lignin biodegradation and *** solution contributes to improving lignin solubility,whereas most microbes can not survive in alkaline ***,lig...
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Low lignin solubility in aqueous solution is one of the major bottlenecks for lignin biodegradation and *** solution contributes to improving lignin solubility,whereas most microbes can not survive in alkaline ***,lignin dissolution behaviors in different pH solutions were systematically investigated,which indicated that solution pH above 10.5 contributed to high solubility of alkali *** match with alkaline lignin aqueous system,several alkali-tolerant ligninolytic bacteria were isolated,most of which are distinct to previously reported ***,the ligninolytic capabilities of these isolates were assessed in different pH conditions by determining their assimilation on alkali lignin,lignin-derived monomers and dimers,their decolorization capabilities,and their lignin peroxidase ***,the underlying ligninolytic and alkali-tolerant mechanisms of Sutcliffiella ***1,an alkalophilic bacterium,was analyzed on the basis of its genome *** results not only provide valuable information for lignin biodegradation and lignin valorization,but also expand knowledge on alkali-tolerant bacteria.
This paper deals with the issue of performance-guaranteed control for discrete-time systems under communication constraints. To alleviate communication burdens, an event-triggered mechanism and quantized data-based pr...
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Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...
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Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...
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Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation *** their trans...
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The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation *** their transformative impact in fields such as machine translation and intelligent dialogue systems,LLMs face significant *** challenges include safety,security,and privacy concerns that undermine their trustworthiness and effectiveness,such as hallucinations,backdoor attacks,and privacy *** works often conflated safety issues with security *** contrast,our study provides clearer and more reasonable definitions for safety,security,and privacy within the context of *** on these definitions,we provide a comprehensive overview of the vulnerabilities and defense mechanisms related to safety,security,and privacy in ***,we explore the unique research challenges posed by LLMs and suggest potential avenues for future research,aiming to enhance the robustness and reliability of LLMs in the face of emerging threats.
In this paper we study the eigenvalue problem for integro-differential operators on a lasso *** trace formula of the operator is established by applying the residual technique in complex analysis.
In this paper we study the eigenvalue problem for integro-differential operators on a lasso *** trace formula of the operator is established by applying the residual technique in complex analysis.
To identify the geographical origin of millet accurately, 36 samples of Guangling millet, Qinzhouhuang millet, Liuseng millet, Qiananhuang millet, and 33 samples of Yuzhou millet were collected. Mid-infrared (mid-IR) ...
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With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance *** technology plays a critical role in enhancing publ...
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With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance *** technology plays a critical role in enhancing public ***,traditional methods typically process images and text separately,applying upstream models directly to downstream *** approach significantly increases the complexity ofmodel training and computational ***,the common class imbalance in existing training datasets limitsmodel performance *** address these challenges,we propose an innovative framework named Person Re-ID Network Based on Visual Prompt technology andMulti-Instance Negative Pooling(VPM-Net).First,we incorporate the Contrastive Language-Image Pre-training(CLIP)pre-trained model to accurately map visual and textual features into a unified embedding space,effectively mitigating inconsistencies in data distribution and the training *** enhancemodel adaptability and generalization,we introduce an efficient and task-specific Visual Prompt Tuning(VPT)technique,which improves the model’s relevance to specific ***,we design two key modules:the Knowledge-Aware Network(KAN)and theMulti-Instance Negative Pooling(MINP)*** KAN module significantly enhances the model’s understanding of complex scenarios through deep contextual semantic *** module handles samples,effectively improving the model’s ability to distinguish fine-grained *** experimental outcomes across diverse datasets underscore the remarkable performance of *** results vividly demonstrate the unique advantages and robust reliability of VPM-Net in fine-grained retrieval tasks.
A previous study showed that the thermal performance of the X-lattice cored corrugated honeycomb(XCCH)is better than that of most other periodic cellular materials(PCMs).To further improve the thermal performance of t...
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A previous study showed that the thermal performance of the X-lattice cored corrugated honeycomb(XCCH)is better than that of most other periodic cellular materials(PCMs).To further improve the thermal performance of the XCCH,the effects of different ripple amplitudes(i.e.,a=0.5,0.7 and 1.0)on the characteristics of the flow and heat transfer are numerically investigated by thorough *** terms of the flow characteristics,with the increase of ripple amplitude,the vortex interaction in the channel becomes stronger,which results in evident increase of kinetic energy of turbulence at the boundary of vortex and reduction in the turbulent kinetic energy *** far as the heat transfer is concerned,within the Reynolds number range of 3696–7436,the heat transfer increases with the increase of ripple *** overall Nusselt number of the XCCH with a=1.0 is 15.7%higher than that with a=*** the corresponding range of pumping power,the thermal performance of the XCCH with a=1.0 is up to 7%higher than that with a=0.5 at relatively higher Reynolds numbers.
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