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PI3K/Akt/mTOR-mediated bidirectional regulation of ampelopsin from Nekemias megalophylla modulates autophagy and apoptosis in cervical cancer 认领 引用
1
作者 Shiyi Xu Siyu Liao +6 位作者 Juan Xi Ling Gong Xue Zou Xiaoli Yang Jiangxue Di Xiuqiao Zhang Chun Gui 《Food Science and Human Wellness》 SCIE CAS CSCD 2026年第2期804-822,共19页
Nekemias megalophylla is a popular folk tea consumed by people in the Western Hubei(China)of which ampelopsin(AMP)is the main active ingredient.In this study,we investigated the effect of AMP on cervical cancer and ex... Nekemias megalophylla is a popular folk tea consumed by people in the Western Hubei(China)of which ampelopsin(AMP)is the main active ingredient.In this study,we investigated the effect of AMP on cervical cancer and explored its mechanism of action,focusing on apoptosis and autophagy.Firstly,we verified that AMP strongly inhibited the growth of C-33A cells and observed apoptosis and autophagy phenomenon in vivo,and found that AMP induces C-33A cell apoptosis via death receptor or mitochondrial pathways.The results also indicated that AMP-induced autophagy occurs via the PI3K/Akt/m TOR pathway.Secondly,when autophagy was inhibited,the AMP-induced apoptosis of C-33A cells was strengthened,when apoptosis was inhibited,the AMP-induced autophagy of C-33A cells was strengthened.PI3K/Akt/m TOR pathway activation enhances AMP-induced apoptosis in C-33A cells,while its inhibition strengthens AMP-induced autophagy.Finally,we confirmed that AMP inhibited cell growth and induced apoptosis and autophagy of C-33A cells in an in vivo nude mouse model of C-33A tumor xenografts.These results elucidate that AMP bidirectionally regulates apoptosis and autophagy in human cervical cancer C-33A cells by mediating the PI3K/Akt/m TOR pathway. 展开更多
关键词 Ampelopsin Apoptosis Autophagy C-33A cell PI3K/Akt/mTOR Bidirectional regulation
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BCAM-Net:A Bidirectional Cross-Attention Multimodal Network for IoT Spectrum Sensing under Generalized Gaussian Noise 认领 引用
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作者 Yuzhou Han Zhuoran Li +2 位作者 Ahmad Gendia Teruji Ide Osamu Muta 《Computers, Materials & Continua》 SCIE EI 2026年第5期272-297,共26页
Spectrum sensing is an indispensable core part of cognitive radio dynamic spectrum access(DSA)and a key approach to alleviating spectrum scarcity in the Internet of Things(IoT).The key issue in practical IoT networks ... Spectrum sensing is an indispensable core part of cognitive radio dynamic spectrum access(DSA)and a key approach to alleviating spectrum scarcity in the Internet of Things(IoT).The key issue in practical IoT networks is robust sensing under the coexistence of low signal-to-noise ratios(SNRs)and non-Gaussian impulsive noise,where observations may be distorted differently across feature modalities,making conventional fusion unstable and degrading detection reliability.To address this challenge,the generalized Gaussian distribution(GGD)is adopted as the noise model,and a multimodal fusion framework termed BCAM-Net(bidirectional cross-attention multimodal network)is proposed.BCAM-Net adopts a parallel dual-branch architecture:a time-frequency branch that leverages the continuous wavelet transform(CWT)to extract time-frequency representations,and a temporal branch that learns long-range dependencies from raw signals.BCAM-Net utilizes a bidirectional cross-attention mechanism to achieve deep alignment and mutual calibration of temporal and time-frequency features,generating a fused representation that is highly robust to complex noise.Simulation results show that,under GGD noise with shape parameterβ=0.5,BCAM-Net achieves high detection probabilities in the low-SNR regime and outperforms representative baselines.At a false alarm probability Pf=0.1 and SNR of−14 dB,it attains a detection probability of 0.9020,exceeding the CNN-Transformer,WT-ResNet,TFCFN,and conventional CNN benchmarks by 5.75%,6.98%,33.3%,and 21.1%,respectively.These results indicate that BCAM-Net can effectively improve spectrum sensing performance in low-SNR impulsive-noise scenarios,and provides a lightweight,high-performance solution for practical cognitive radio spectrum sensing. 展开更多
关键词 Cognitive radio spectrumsensing IoT deep learning bidirectional cross-attention multimodal fusion
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Wind Power Forecasting Utilizing Bidirectional Gated Recurrent Units in Conjunction with Empirical Mode Decomposition and Bayesian Neural Networks 认领 引用
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作者 Xiaolan Li Yanting Wang 《Energy Engineering》 EI 2026年第7期173-196,共24页
To address the operational challenges of power systems with high renewable penetration,this research targets the non-stationarity and stochasticity of wind power.A novel hybrid framework for probabilistic forecasting ... To address the operational challenges of power systems with high renewable penetration,this research targets the non-stationarity and stochasticity of wind power.A novel hybrid framework for probabilistic forecasting and risk assessment is proposed.Initially,Empirical Mode Decomposition(EMD)adaptively decomposes the raw power signal into multi-scale Intrinsic Mode Functions(IMFs)and a residual trend,effectively segregating temporal features and reducing complexity.These components are then fused with historical data to form a comprehensive input.The core predictor is a Bidirectional Gated Recurrent Unit(BiGRU)network enhanced with a Temporal Attention(TA)mechanism.The BiGRU captures bidirectional long-term dependencies,while the TA mechanism dynamically focuses on the most influential historical time steps,enabling precise temporal pattern extraction.To quantify uncertainty,a Bayesian Neural Networks(BNNs)layer is integrated,transforming deterministic point forecasts into probabilistic outputs with prediction intervals.Finally,leveraging these probabilistic forecasts,the Value at Risk(VaR)metric is applied to assess potential operational risks under specified confidence levels,translating uncertainty into quantifiable reliability or financial risk.Simulation results confirm the framework's superiority,achieving a normalized Root Mean Square Error(nRMSE)of 15.73%and a normalized Mean Absolute Error(nMAE)of 10.94%,significantly outperforming benchmarks.The innovative integration of signal processing,attentive deep learning,Bayesian inference,and risk theory within a unified model enhances forecasting accuracy,quantifies uncertainty,and enables proactive risk assessment,providing robust decision support for grid dispatch and renewable integration. 展开更多
关键词 Short-term wind power forecasting empirical mode decomposition(EMD) bidirectional gated recurrent unit(Bi-GRU) temporal attention mechanism Bayesian neural networks(BNNs) predictive uncertainty quantification
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Te-Modulated Fe Single Atom with Synergistic Bidirectional Catalysis for High-Rate and Long-Cycling Lithium-Sulfur Battery 认领 引用 被引量：1
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作者 Jian Guo Lu Chen +4 位作者 Lijun Wang Kangfei Liu Ting He Jia Yu Hongbin Zhao 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第1期827-842,共16页
Single-atom catalysts(SACs)have garnered significant attention in lithium-sulfur(Li-S)batteries for their potential to mitigate the severe polysulfide shuttle effect and sluggish redox kinetics.However,the development... Single-atom catalysts(SACs)have garnered significant attention in lithium-sulfur(Li-S)batteries for their potential to mitigate the severe polysulfide shuttle effect and sluggish redox kinetics.However,the development of highly efficient SACs and a comprehensive understanding of their structure-activity relationships remain enormously challenging.Herein,a novel kind of Fe-based SAC featuring an asymmetric FeN5-TeN4 coordination structure was precisely designed by introducing Te atom adjacent to the Fe active center to enhance the catalytic activity.Theoretical calculations reveal that the neighboring Te atom modulates the local coordination environment of the central Fe site,elevating the d-band center closer to the Fermi level and strengthening the d-p orbital hybridization between the catalyst and sulfur species,thereby immobilizing polysulfides and improving the bidirectional catalysis of Li-S redox.Consequently,the Fe-Te atom pair catalyst endows Li-S batteries with exceptional rate performance,achieving a high specific capacity of 735 mAh g−1 at 5 C,and remarkable cycling stability with a low decay rate of 0.038%per cycle over 1000 cycles at 1 C.This work provides fundamental insights into the electronic structure modulation of SACs and establishes a clear correlation between precisely engineered atomic configurations and their enhanced catalytic performance in Li-S electrochemistry. 展开更多
关键词 Single-atom catalyst Coordination environment Electronic structure Bidirectional catalysis Li-S batteries
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Multifunctional ionic liquid additive enabled ultrastable aqueous zinc-organic batteries with bidirectional interfacial engineering 认领 引用
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作者 Xiao-Jie Huang Zhi-Ying Zhao +6 位作者 Jian-Feng Xiong Ruo-Bei Huang Chao-Hang Liu Zi-Ang Nan Hai-Long Wang Jing-Hua Tian Zhong-Qun Tian 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第4期725-736,I0017,共12页
Aqueous zinc-organic batteries(AzOBs)are promising for grid-scale energy storage but suffer from interfacial instability at both electrodes.Most existing studies focus on stabilizing a single electrode,overlooking the... Aqueous zinc-organic batteries(AzOBs)are promising for grid-scale energy storage but suffer from interfacial instability at both electrodes.Most existing studies focus on stabilizing a single electrode,overlooking the crucial interplay between the anode and cathode.Herein,we propose a bidirectional interface engineering strategy enabled by a multifunctional ionic liquid additive,1-butyl-2,3-dimethylimidazolium chloride(BDMIMCl),which simultaneously stabilizes the zinc anode and polyaniline(PANI)cathode.Mechanistic studies reveal that BDMIMCl enables the formation of a protective layer on the Zn anode.This layer is subsequently converted in situ into a hybrid solid electrolyte interphase(SEI)during cycling,which effectively shields the anode.Moreover,BDMIMCl restructures the Zn2+solvation shell to minimize water-induced side reactions and establishes a Cl--involved multi-ion storage mechanism in the PANI cathode.As a result,Zn||Zn cells exhibit exceptional cycling stability over 2400 h at 1 mA cm-2and 1 mA h cm-2,and Zn||PANI cells retain 84.3%capacity after 2000 cycles at 2 A g-1.This work provides novel insights into bidirectional interface engineering,paving the way for the development of ultrastable and high-performance AzOBs. 展开更多
关键词 Multifunctional additives Ionic liquid Bidirectional interfacial engineering Ultrastable aqueous zinc-organic batteries Multi-ion storage mechanisms
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Thermal Vibrations and Buckling Analysis of Bidirectional Functionally Graded Beams Under Axial and Transverse Temperature Gradients 认领 引用
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作者 Haizhou Liu Yang Zhao +2 位作者 Fangtong Luo Hao Tian Weihua Xie 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2026年第2期152-165,共14页
Bidirectional functionally graded(BDFG)beams are a promising solution for spacecraft structures subjected to extreme thermal and vibrational environments due to their superior thermal performance and design flexibilit... Bidirectional functionally graded(BDFG)beams are a promising solution for spacecraft structures subjected to extreme thermal and vibrational environments due to their superior thermal performance and design flexibility.Therefore,developing an efficient and highly convergent thermal vibration analysis method for BDFG beams under complex temperature fields is of paramount importance.This paper proposes a Chebyshev spectral method based on Reddy’s higher-order shear deformation theory(HSDT)to investigate the thermoelastic vibrations of BDFG beams.The material properties are temperature-dependent and vary with both thickness and length.The proposed method is validated by comparing the results with those in the existing literature.The analysis reveals that the critical buckling temperature rise is primarily influenced by the ceramic content,but thermal buckling can be mitigated by adjusting the material distribution.A trade-off exists between suppressing thermal buckling and relaxing thermal stresses,necessitating a balanced approach.The titanium alloy BDFG beam offers a broader design envelope compared to the metal-ceramic BDFG beam.The method presented in this study will provide theoretical support and guidance for the design of BDFG beams. 展开更多
关键词 Thermal buckling Chebyshev spectral approach Bidirectional functionally graded beams Axial temperature rise Higher-order shear deformation theory
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Intelligent Human Interaction Recognition with Multi-Modal Feature Extraction and Bidirectional LSTM 认领 引用
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作者 Muhammad Hamdan Azhar Yanfeng Wu +4 位作者 Nouf Abdullah Almujally Shuaa S.Alharbi Asaad Algarni Ahmad Jalal Hui Liu 《Computers, Materials & Continua》 SCIE EI 2026年第4期1632-1649,共18页
Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationall... Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationally intensive,sensitive to video resolution changes and often fail in crowded scenes.We propose a novel hybrid system that is computationally efficient,robust to degraded video quality and able to filter out irrelevant individuals,making it suitable for real-life use.The system leverages multi-modal handcrafted features for interaction representation and a deep learning classifier for capturing complex dependencies.Using Mask R-CNN and YOLO11-Pose,we extract grayscale silhouettes and keypoint coordinates of interacting individuals,while filtering out irrelevant individuals using a proposed algorithm.From these,we extract silhouette-based features(local ternary pattern and histogram of optical flow)and keypoint-based features(distances,angles and velocities)that capture distinct spatial and temporal information.A Bidirectional Long Short-Term Memory network(BiLSTM)then classifies the interactions.Extensive experiments on the UT Interaction,SBU Kinect Interaction and the ISR-UOL 3D social activity datasets demonstrate that our system achieves competitive accuracy.They also validate the effectiveness of the chosen features and classifier,along with the proposed system’s computational efficiency and robustness to occlusion. 展开更多
关键词 Human interaction recognition keypoint coordinates grayscale silhouettes bidirectional long shortterm memory network
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An Ultrasonic Microrobot Enabling Ultrafast Bidirectional Navigation in Confinned Tubular Environments 认领 引用
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作者 Meng Cui Liyun Zhen +5 位作者 Xingyu Bai Lihan Yu Xuhao Chen Jingquan Liu Qingkun Liu Bin Yang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第2期183-198,共16页
Pipelines are extensively used in environments such as nuclear power plants,chemical factories,and medical devices to transport gases and liquids.These tubular environments often feature complex geometries,confined sp... Pipelines are extensively used in environments such as nuclear power plants,chemical factories,and medical devices to transport gases and liquids.These tubular environments often feature complex geometries,confined spaces,and millimeter-scale height restrictions,presenting significant challenges to conventional inspection methods.Here,we present an ultrasonic microrobot(weight,80 mg;dimensions,24 mm×7 mm;thickness,210μm)to realize agile and bidirectional navigation in narrow pipelines.The ultrathin structural design of the robot is achieved through a high-performance piezoelectric composite film microstructure based on MEMS technology.The robot exhibits various vibration modes when driven by ultrasonic frequency signals,its motion speed reaches81 cm s-1 at 54.8 k Hz,exceeding that of the fastest piezoelectric microrobots,and its forward and backward motion direction is controllable through frequency modulation,while the minimum driving voltage for initial movement can be as low as 3 VP-P.Additionally,the robot can effortlessly climb slopes up to 24.25°and carry loads more than 36 times its weight.The robot is capable of agile navigation through curved L-shaped pipes,pipes made of various materials(acrylic,stainless steel,and polyvinyl chloride),and even over water.To further demonstrate its inspection capabilities,a micro-endoscope camera is integrated into the robot,enabling real-time image capture inside glass pipes. 展开更多
关键词 Ultrasonic microrobot Piezoelectric composite film microstructure MEMS fabrication Bidirectional locomotion Confined pipeline inspection
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Sustainable Carbon Aerogels from Polyolefin Plastics for High-Linearity Bidirectional Strain Sensing 认领 引用
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作者 Yang Yue Hui Bi +4 位作者 Shiyu Zhang Chen Luan Zhangliu Tian Dayong Ren Fuqiang Huang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第10期706-721,共16页
Achieving highly linear and sensitive strain sensing under both tensile and compressive deformation remains a critical challenge in wearable electronics,as it demands a conductive network capable of reversible reconfi... Achieving highly linear and sensitive strain sensing under both tensile and compressive deformation remains a critical challenge in wearable electronics,as it demands a conductive network capable of reversible reconfiguration without compromising structural uniformity.This challenge is further intensified in hierarchical carbon nanostructures,where catalyst deactivation and unregulated carbon supply frequently lead to nonuniform nanocarbon growth and severely heterogeneous conductive pathways.Herein,we report a hierarchical carbon aerogel derived from plastics.Carbon nanofibers(CNFs)are in situ grown on elastic carbonized cotton fibers via plastic pyrolysis,enabled by Ni-S-modified catalytic interface and sustained carbon flux from plastic decomposition.The coupled regulation suppresses uneven nanocarbon deposition,yielding an elastic fibrous backbone densely interconnected by CNFs.The resulting network facilitates reversible reconstruction of conductive contacts under tension and compression,delivering a nearly linear electromechanical response over a broad bidirectional strain window with linear gauge factors of 7.8 at 82%tension and 1.7 at 28%compression,while maintaining stable sensitivity over 5000 cycles within a±20%strain window.Overall,this work achieves a wide bidirectional strain range,high sensitivity,and long-term stability,rarely combined in carbon-based strain sensors.Moreover,it reliably resolves strain direction and magnitude,enables sensitive adhesion sensing and joint-motion monitoring,highlighting its potential for next-generation human-machine interfaces. 展开更多
关键词 Plastic upcycling Sulfur-modulated catalysts Hierarchical carbon aerogels Coaxial bidirectional strain sensors Linear and sensitive sensing region
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Compilers and LLMs:bidirectional impact of systems and education 认领 引用
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作者 Yu Zhang Li Zhang 《计算机教育》 2026年第6期229-236,共8页
Large language models(LLMs)are changing the way software is developed and taught.At the same time,LLMs fundamentally rely on core compiler concepts and technical foundations.This paper explores the bidirectional impac... Large language models(LLMs)are changing the way software is developed and taught.At the same time,LLMs fundamentally rely on core compiler concepts and technical foundations.This paper explores the bidirectional impact between compiler systems and LLMsÐfrom how LLMs are reshaping compiler design and usage to how compiler principles and techniques are essential for understanding,building,and teaching LLM-based systems.We further examine their implications for software engineering education and propose preliminary thoughts on integrating LLMs in future compiler courses.By bridging traditional compiler foundations with emerging AI paradigms,we advocate for reestablishing the central role of compiler education in training the next generation of intelligent system developers. 展开更多
关键词 Compiler education Large language models(LLMs) Bidirectional impact Curriculum reform
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Research on Teaching Reform of“Introduction to Civil Engineering”through Bidirectional Integration of Generative AI and Problem-Based Learning 认领 引用
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作者 Yuexin Chen 《Journal of Contemporary Educational Research》 2026年第2期90-95,共6页
Under the“Smart+”education initiative,the traditional Introduction to Civil Engineering course faces challenges such as abstract knowledge delivery and disconnection from practical applications.Guided by the core co... Under the“Smart+”education initiative,the traditional Introduction to Civil Engineering course faces challenges such as abstract knowledge delivery and disconnection from practical applications.Guided by the core concept of“bidirectional integration,”this research systematically develops a novel teaching model that deeply incorporates generative artificial intelligence(AI)with project-based learning(PBL).This model not only employs generative AI as an intelligent tool to empower the entire PBL process but also uses authentic PBL project tasks to drive students’high-order and critical use of AI,aiming to simultaneously enhance students’engineering cognition and AI literacy.Teaching practice demonstrates that this model effectively stimulates students’learning interest and improves their comprehensive ability to solve complex engineering problems,providing an actionable pathway and reference for the intelligent teaching reform of similar courses. 展开更多
关键词 Generative artificial intelligence Project-based learning Teaching reform Bidirectional integration
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The Impact of Bidirectional Quality Feedback Nursing Model on the Quality of Life and Self-Management Ability of Patients with Chronic Obstructive Pulmonary Disease(COPD) 认领 引用
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作者 Daidi Tang Chengjin Sheng Lingling Liu 《Journal of Clinical and Nursing Research》 2026年第3期330-335,共6页
Objective:To explore the intervention effect of the bidirectional quality feedback nursing model on the quality of life and self-management ability of patients with chronic obstructive pulmonary disease(COPD).Methods:... Objective:To explore the intervention effect of the bidirectional quality feedback nursing model on the quality of life and self-management ability of patients with chronic obstructive pulmonary disease(COPD).Methods:A total of 60 COPD cases in the stable phase of the disease admitted to our hospital from January to December 2024 were included.Using a random number table method,they were divided into a control group and an observation group,with 30 cases in each group.The control group received the standard nursing protocol,while the observation group underwent a three-month bidirectional quality feedback nursing intervention in addition to the standard protocol.The quality of life and self-management ability scores of the two groups were compared before and after the intervention.Results:After the intervention,compared with the control group,the observation group showed lower scores in all dimensions of the St.George’s Respiratory Questionnaire(SGRQ)and higher scores in all domains and the total score of the Self-Care of Chronic Illness Inventory-Modified for COPD(SCMMS)(p<0.05).Conclusion:The bidirectional quality feedback nursing intervention can significantly improve the self-care level and quality of life of patients with COPD,demonstrating clinical application value. 展开更多
关键词 Bidirectional quality feedback nursing Chronic obstructive pulmonary disease Quality of life Self-management ability
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Bone-organ axes: bidirectional crosstalk 认领 引用 被引量：20
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作者 An-Fu Deng Fu-Xiao Wang +3 位作者 Si-Cheng Wang Ying-Ze Zhang Long Bai Jia-Can Su 《Military Medical Research》 SCIE CAS CSCD 2025年第4期600-632,共33页
In addition to its recognized role in providing structural support, bone plays a crucial role in maintaining the functionality and balance of various organs by secreting specific cytokines(also known as osteokines). T... In addition to its recognized role in providing structural support, bone plays a crucial role in maintaining the functionality and balance of various organs by secreting specific cytokines(also known as osteokines). This reciprocal influence extends to these organs modulating bone homeostasis and development, although this aspect has yet to be systematically reviewed. This review aims to elucidate this bidirectional crosstalk, with a particular focus on the role of osteokines. Additionally, it presents a unique compilation of evidence highlighting the critical function of extracellular vesicles(EVs) within bone-organ axes for the first time. Moreover, it explores the implications of this crosstalk for designing and implementing bone-on-chips and assembloids, underscoring the importance of comprehending these interactions for advancing physiologically relevant in vitro models. Consequently, this review establishes a robust theoretical foundation for preventing, diagnosing, and treating diseases related to the bone-organ axis from the perspective of cytokines, EVs, hormones, and metabolites. 展开更多
关键词 Bone-organ axes Bidirectional crosstalk Cytokines Osteokines Extracellular vesicles(EVs) Hormones Metabolites
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Boosting bidirectional sulfur conversion enabled by introducing boron-doped atoms and phosphorus vacancies in Ni2P for lithium-sulfur batteries 认领 引用 被引量：4
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作者 Lin Peng Yu Bai +3 位作者 Hang Li Meixiu Qu Zhenhua Wang Kening Sun 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2025年第1期760-769,共10页
Lithium-sulfur (Li-S) batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish ... Lithium-sulfur (Li-S) batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish redox dynamics.Herein,we supply a strategy to optimize the electron structure of Ni2P by concurrently introducing B-doped atoms and P vacancies in Ni2P (Vp-B-Ni2P),thereby enhancing the bidirectional sulfur conversion.The study indicates that the simultaneous introduction of B-doped atoms and P vacancies in Ni2P causes the redistribution of electron around Ni atoms,bringing about the upward shift of d-band center of Ni atoms and effective d-p orbital hybridization between Ni atoms and sulfur species,thus strengthening the chemical anchoring for lithium polysulfides (LiPSs) as well as expediting the bidirectional conversion kinetics of sulfur species.Meanwhile,theoretical calculations reveal that the incorporation of B-doped atoms and P vacancies in Ni2P selectively promotes Li2S dissolution and nucleation processes.Thus,the Li-S batteries with Vp-B-Ni2P-separators present outstanding rate ability of 777 m A h g-1at 5 C and high areal capacity of 8.03 mA h cm-2under E/S of 5μL mg-1and sulfur loading of 7.20 mg cm-2.This work elucidates that introducing heteroatom and vacancy in metal phosphide collaboratively regulates the electron structure to accelerate bidirectional sulfur conversion. 展开更多
关键词 B-doped atoms P vacancies Nickel phosphide Bidirectional sulfur conversion Lithium-sulfur batteries
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Coal burst spatio‑temporal prediction method based on bidirectional long short‑term memory network 认领 引用 被引量：1
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作者 Xu Yang Yapeng Liu +4 位作者 Anye Cao Yaoqi Liu Changbin Wang Weiwei Zhao Qiang Niu 《International Journal of Coal Science & Technology》 SCIE EI CAS CSCD 2025年第1期228-245,共18页
The increasingly severe state of coal burst disaster has emerged as a critical factor constraining coal mine safety production,and it has become a challenging task to enhance the accuracy of coal burst disaster predic... The increasingly severe state of coal burst disaster has emerged as a critical factor constraining coal mine safety production,and it has become a challenging task to enhance the accuracy of coal burst disaster prediction.To address the issue of insufficient exploration of the spatio-temporal characteristic of microseismic data and the challenging selection of the optimal time window size in spatio-temporal prediction,this paper integrates deep learning methods and theory to propose a novel coal burst spatio-temporal prediction method based on Bidirectional Long Short-Term Memory(Bi-LSTM)network.The method involves three main modules,including microseismic spatio-temporal characteristic indicators construction,temporal prediction model,and spatial prediction model.To validate the effectiveness of the proposed method,engineering application tests are conducted at a high-risk working face in the Ordos mining area of Inner Mongolia,focusing on 13 high-energy microseismic events with energy levels greater than 105 J.In terms of temporal prediction,the analysis indicates that the temporal prediction results consist of 10 strong predictions and 3 medium predictions,and there is no false alarm detected throughout the entire testing period.Moreover,compared to the traditional threshold-based coal burst temporal prediction method,the accuracy of the proposed method is increased by 38.5%.In terms of spatial prediction,the distribution of spatial prediction results for high-energy events comprises 6 strong hazard predictions,3 medium hazard predictions,and 4 weak hazard predictions. 展开更多
关键词 Coal burst Spatio-temporal prediction Microseismic spatio-temporal characteristic indicators Bidirectional long short-term memory network
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Comprehensive Dynamic Model of Vertical Pneumatic Bellows Actuator System Considering Bidirectional Asymmetric Hysteresis 认领 引用 被引量：1
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作者 Huai Xiao Xuzhi Lai +3 位作者 Qingxin Meng Jinhua She Edwardo F.Fukushima Min Wu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第10期2115-2126,共12页
The complex nonlinear characteristics of pneumatic soft actuators,such as asymmetric hysteresis,rate-dependence,and mechanical load-dependence,pose a challenge in accurately modeling their dynamics.To address this cha... The complex nonlinear characteristics of pneumatic soft actuators,such as asymmetric hysteresis,rate-dependence,and mechanical load-dependence,pose a challenge in accurately modeling their dynamics.To address this challenge,this paper proposes a comprehensive dynamic model aimed at describing bidirectional asymmetric hysteresis,rate-dependent,and mechanical load-dependent characteristics of a vertical pneumatic bellows actuator(PBA)system.The dynamic model contains a hysteresis submodel and a load-dependent dynamic submodel.The hysteresis submodel consists of several sets of weighted double-side play(DSP)and weighted dead-zone(DZ)operators connected in series,and it is used to model the bidirectional asymmetric hysteresis of the system.The load-dependent dynamic submodel is built based on the gated recurrent unit(GRU)neural network,and it is used to fit the nonlinear relationship between the displacement of the system and the frequency of the input air pressure as well as the mechanical load.The model parameters of the hysteresis submodel and the loaddependent dynamic submodel are determined by intelligent optimization method and neural network training method,reseparately.The fitness value(FV)between the output of the dynamic model and the experimental data is calculated to be 96.1736%,demonstrating that the parameters of the dynamic model are valid.We conduct six set of experiments to compare the model output with the experimental data,and calculate the root-meansquare errors and the maximum error,respectively.The experimental results show that,the root-mean-square error remains consistently below 2.7700%,while the maximum error remains below 8.4000%across all experiments,thereby substantiating the validity and generality of the proposed model. 展开更多
关键词 Bidirectional asymmetric hysteresis dynamic model rate-dependent and mechanical load-dependent soft actuator
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Dual-Channel Attention Deep Bidirectional Long Short Term Memory for Enhanced Malware Detection and Risk Mitigation 认领 引用 被引量：2
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作者 Madini O.Alassafi Syed Hamid Hasan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第8期2627-2645,共19页
Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malwar... Over the past few years,Malware attacks have become more and more widespread,posing threats to digital assets throughout the world.Although numerous methods have been developed to detect malicious attacks,these malware detection techniques need to be more efficient in detecting new and progressively sophisticated variants of malware.Therefore,the development of more advanced and accurate techniques is necessary for malware detection.This paper introduces a comprehensive Dual-Channel Attention Deep Bidirectional Long Short-Term Memory(DCADBiLSTM)model for malware detection and riskmitigation.The Dual Channel Attention(DCA)mechanism improves themodel’s capability to concentrate on the features that aremost appropriate in the input data,which reduces the false favourable rates.The Bidirectional Long,Short-Term Memory framework helps capture crucial interdependence from past and future circumstances,which is essential for enhancing the model’s understanding of malware behaviour.As soon as malware is detected,the risk mitigation phase is implemented,which evaluates the severity of each threat and helps mitigate threats earlier.The outcomes of the method demonstrate better accuracy of 98.96%,which outperforms traditional models.It indicates the method detects and mitigates several kinds of malware threats,thereby providing a proactive defence mechanism against the emerging challenges in cybersecurity. 展开更多
关键词 Cybersecurity risk mitigation malware detection bidirectional long short-termmemory dual-channel attention
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Vacancy-driven coordinationfield modulating electron spin state for enhanced bidirectional polysulfide conversion in lithium-sulfur batteries 认领 引用
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作者 Kangdong Tian Ruifeng Li +2 位作者 Miaofa Yuan Jiafeng Li Chengxiang Wang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2025年第12期227-236,I0007,共10页
Modulating the electronic structure has emerged as an effective strategy for optimizing the adsorption and catalytic capabilities of electrocatalysts in lithium-sulfur(Li-S)batteries.However,the regulation of electron... Modulating the electronic structure has emerged as an effective strategy for optimizing the adsorption and catalytic capabilities of electrocatalysts in lithium-sulfur(Li-S)batteries.However,the regulation of electronic structure involving spin-related charge transfer and orbital interactions has been largely underexplored in sulfur electrocatalysts.Herein,selenium-deficient bimetallic selenides embedded in a coaxial carbon layer(CoSe2-x/ZnSe)were meticulously fabricated as electrocatalysts,aiming to modulate the electron spin state of Co catalytic sites to enhance the bidirectional lithium polysulfides(LiPSs)conversion kinetics and suppress the LiPSs shuttling effect.Density functional theory(DFT)calculations and experimental results indicate that the selenium vacancies at the CoSe2-x/ZnSe heterointerfaces weaken the ligand fields and drive the Co 3d orbital electronic structure transition from low-spin to high-spin states.Such tailored spin state configuration generates more unpaired electrons and upshifts the dband center,thus accelerating the charge transfer and strengthening the orbital interactions between LiPSs and Co catalytic sites.As a consequence,the assembled Li-S batteries with CoSe2-x/ZnSe electrocatalysts exhibit an ultralow average decay rate of 0.028%per cycle at 1 C over 1000 cycles.This work presents a novel strategy for manipulating ligand fields to realize electron spin state modulation in sulfur electrocatalysts. 展开更多
关键词 Selenium vacancies Ligand fields Electron spin state Bidirectional polysulfide conversion Lithium-sulfur batteries
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The Joint Model of Multi-Intent Detection and Slot Filling Based on Bidirectional Interaction Structure 认领 引用
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作者 WANG Changjing ZENG Xianghui +2 位作者 WANG Yuxin SUN Yuxin ZUO Zhengkang 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2025年第1期21-31,共11页
Intent detection and slot filling are two important components of natural language understanding.Because their relevance,joint training is often performed to improve performance.Existing studies mostly use a joint mod... Intent detection and slot filling are two important components of natural language understanding.Because their relevance,joint training is often performed to improve performance.Existing studies mostly use a joint model of multi-intent detection and slot-filling with unidirectional interaction,which improves the overall performance of the model by fusing the intent information in the slot-filling part.On this basis,in order to further improve the overall performance of the model by exploiting the correlation between the two,this paper proposes a joint multi-intent detection and slot-filling model based on a bidirectional interaction structure,which fuses the intent encoding information in the encoding part of slot filling and fuses the slot decoding information in the decoding part of intent detection.Experimental results on two public multi-intent joint training datasets,MixATIS and MixSNIPS,show that the bidirectional interaction structure proposed in this paper can effectively improve the performance of the joint model.In addition,in order to verify the generalization of the bidirectional interaction structure between intent and slot,a joint model for single-intent scenarios is proposed on the basis of the model in this paper.This model also achieves excellent performance on two public single-intent joint training datasets,CAIS and SNIPS. 展开更多
关键词 natural language understanding multi-intent detection slot filling bidirectional interaction joint training
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Dynamic Interaction-Aware Trajectory Prediction with Bidirectional Graph Attention Network 认领 引用
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作者 Jun Li Kai Xu +4 位作者 Baozhu Chen Xiaohan Yang Mengting Sun Guojun Li HaoJie Du 《Computers, Materials & Continua》 SCIE EI 2025年第11期3349-3368,共20页
Pedestrian trajectory prediction is pivotal and challenging in applications such as autonomous driving,social robotics,and intelligent surveillance systems.Pedestrian trajectory is governed not only by individual inte... Pedestrian trajectory prediction is pivotal and challenging in applications such as autonomous driving,social robotics,and intelligent surveillance systems.Pedestrian trajectory is governed not only by individual intent but also by interactions with surrounding agents.These interactions are critical to trajectory prediction accuracy.While prior studies have employed Convolutional Neural Networks(CNNs)and Graph Convolutional Networks(GCNs)to model such interactions,these methods fail to distinguish varying influence levels among neighboring pedestrians.To address this,we propose a novel model based on a bidirectional graph attention network and spatio-temporal graphs to capture dynamic interactions.Specifically,we construct temporal and spatial graphs encoding the sequential evolution and spatial proximity among pedestrians.These features are then fused and processed by the Bidirectional Graph Attention Network(Bi-GAT),which models the bidirectional interactions between the target pedestrian and its neighbors.The model computes node attention weights(i.e.,similarity scores)to differentially aggregate neighbor information,enabling fine-grained interaction representations.Extensive experiments conducted on two widely used pedestrian trajectory prediction benchmark datasets demonstrate that our approach outperforms existing state-of-theartmethods regarding Average Displacement Error(ADE)and Final Displacement Error(FDE),highlighting its strong prediction accuracy and generalization capability. 展开更多
关键词 Pedestrian trajectory prediction spatio-temporal modeling bidirectional graph attention network autonomous system
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