作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China;[Cheng Tang; Lang Li; Yu Ou] College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China
通讯机构：
[Lang Li] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China
摘要：
Deep learning-based side-channel attacks (DL-SCA) are favored for their strong key recovery capabilities. However, their implementation is based on the attacker being able to manipulate a cloned device to build an attack model, which means that the attacker needs to know secret information in advance. The non-profiled side-channel attacks (NP-SCA) methods can complete the key recovery without knowing the secret information. Differential Deep Learning Analysis (DDLA) is the first NP-DLSCA method proposed in CHES2019, and several improved versions appeared later. In these methods, the bad quality of the raw traces, such as noise, random delay, etc., is often ignored, which limits the efficiency of key recovery. In this work, the conditional generative adversarial network (CGAN) is introduced and a novel framework NPSCA-CGAN is proposed to optimize traces in non-profiled SCA scenarios. We apply CGAN in non-profiled attacks and use plaintext to do trace labeling that optimizes the raw traces by training the generator to learn the label traces. The convolutional module and plaintext feature are added to the generator network to adapt various countermeasures. Moreover, a new traces quality evaluation metric average relative signal-to-noise ratio (AR-SNR) is proposed for non-profiled attack scenarios, which can directly reflect the performance of the traces in practical attack. The method is applied to unprotected, unaligned, and masked traces respectively. The experimental results indicate that it can enormously optimize the quality of the traces and improve the efficiency of non-profiled side-channel attacks.
作者机构：
[Li, Lang] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
通讯机构：
[Li, L ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
关键词：
Side-channel analysis;Sample correlation locally;Deep learning;Kernel density estimation;Profiling analysis
摘要：
Label distribution learning techniques can significantly enhance the effectiveness of side-channel analysis. However, this method relies on using probability density functions to estimate the relationships between labels. The settings of parameters play a crucial role in the impact of the attacks. This study introduces a non-parametric statistical method to calculate the distribution between labels, specifically employing smoothing with the Gaussian kernel function and adjusting bandwidth. Then, the aggregation of the results from each label processed by the Gaussian kernel facilitates a hypothesis-free estimation of the label distribution. This method accurately represents the actual leakage distribution, speeding up guess entropy convergence. Secondly, we exploit similarities between profiling traces, proposing an analysis scheme for sample correlation locally of label distribution learning. Furthermore, Signal to-Noise Ratio (SNR) is employed to re-extract and reduce dataset dimensions to 500 power consumption points, resulting in noise reduction. Our results showcase the successful training of 800 profiling traces using our method for sample correlation locally of label distribution learning, with the findings indicating its exceptional performance.
Label distribution learning techniques can significantly enhance the effectiveness of side-channel analysis. However, this method relies on using probability density functions to estimate the relationships between labels. The settings of parameters play a crucial role in the impact of the attacks. This study introduces a non-parametric statistical method to calculate the distribution between labels, specifically employing smoothing with the Gaussian kernel function and adjusting bandwidth. Then, the aggregation of the results from each label processed by the Gaussian kernel facilitates a hypothesis-free estimation of the label distribution. This method accurately represents the actual leakage distribution, speeding up guess entropy convergence. Secondly, we exploit similarities between profiling traces, proposing an analysis scheme for sample correlation locally of label distribution learning. Furthermore, Signal to-Noise Ratio (SNR) is employed to re-extract and reduce dataset dimensions to 500 power consumption points, resulting in noise reduction. Our results showcase the successful training of 800 profiling traces using our method for sample correlation locally of label distribution learning, with the findings indicating its exceptional performance.
摘要：
Electrochemical conversion of nitrate offers an efficient approach to mitigate nitrate pollution and ammonia synthesis but is still challenged by the slow kinetics and selectivity issues of active sites. Herein, by performing density functional theory (DFT) calculations, we report a double-atom catalyst of PdCu–C 7 N 6 by incorporating Pd and Cu together embedded in C 7 N 6 frameworks, which not only shows outstanding catalytic performance with a low limiting potential of 0.36 V, but also can effectively inhibit the competing hydrogen evolution reactions. The high NO 3 RR activity on PdCu–C 7 N 6 is well explained by the polarizable bond length as well as the asymmetric charge distribution of Pd–Cu dual active sites. This DFT work opens an avenue for developing highly efficient multicomponent NO 3 RR electrocatalysts.
关键词：
out-of-time-ordered correlato;quantum chaos;quantum Rabi model
摘要：
Quantum chaos is an intriguing topic and has attracted a great deal of interests in quantum mechanics and black hole physics. Recently, the exponential growth of out-of-time-ordered correlator (OTOC) has been proposed to diagnose quantum chaos and verify the correspondence principle. Here, good correspondence is found between the linear entanglement entropy and the semiclassical phase space structures in the anisotropic quantum Rabi model. The Loschmidt echo in the chaotic sea decays more faster than that in the stable island. However, the OTOCs grow exponentially at early times for the initial states centered both in the chaotic and stable regions. The exponential growth of the OTOC is attributed to quantum collapse that provides a novel mechanism of yielding exponential growth of the OTOC in quantum systems. Moreover, the quantum collapse effect is more obvious for the initial states centered in the chaotic one. The results show that in the anisotropic quantum Rabi model, the linear entanglement entropy, and Loschmidt echo are more effective than OTOC for diagnosing quantum chaotic signals.
通讯机构：
[Wei, XL ; Cao, JX] X;Xiangtan Univ, Dept Phys, Xiangtan 411105, Peoples R China.;Xiangtan Univ, Hunan Prov Key Lab Smart Carbon Mat & Adv Sensing, Xiangtan 411105, Peoples R China.;Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang 421002, Peoples R China.
摘要：
Two-dimensional black arsenic phosphorus has attracted significant interest due to its extraordinary electronic, optical, and transport properties. Therefore, in this work, we go through all the possibilities, including 3297 nonrepetitive configurations, and demonstrate the lowest energy structure of the As x P 1– x ( x = 0.4) monolayer by first-principles calculations. Our results indicate that both single-layer and bilayer As 4 P 6 host direct and indirect bandgap semiconductors with bandgaps of 1.94 and 1.26 eV, respectively, which exhibit good light adsorption within the visible light and infrared region. Moreover, both single-layer and bilayer As 4 P 6 possess high electron and hole mobilities (up to 2.6 × 10 4 cm 2 v –1 s –1 ), which also exhibit extreme carrier anisotropy originating from their high in-plane lattice anisotropy. Furthermore, bilayer As 4 P 6 exhibits exceptional device characteristics including a lower threshold voltage, higher on-state current, and higher conductance. In addition, the transmission coefficient spectrum of bilayer As 4 P 6 is three times greater than that of the monolayer owing to an increased number of electronic channels. Additionally, the extinction ratio of single-layer As 4 P 6 exhibits high anisotropy, indicating enhanced polarization sensitivity in the zigzag direction. Our findings provide two excellent candidate materials for the application of optoelectronic devices.
摘要：
Janus two-dimensional materials have attracted extensive research attention owing to their intrinsic electric dipole moments and excellent properties. Here, a systematic study on the electronic properties of In 2 Se 2 S/WSiGeX 4 (X = N, P, As) van der Waals heterostructures (vdWHs) is presented. The results showed that the different interfacial stacking configurations can modulate the net dipole moment strength and band alignment of In 2 Se 2 S/WSiGeX 4 vdWHs. The In 2 Se 2 S/WSiGeP 4 vdWHs exhibit type-I band alignment with direct bandgap characteristics when adopting Si(Ge)/Se interfacial contacts, whereas type-II band alignment accompanied by indirect bandgap features emerges in systems with Si(Ge)/S interfacial configurations. Notably, the Si (Ge)/S interface exhibits a higher charge transfer capacity compared to the Si (Ge)/Se interface. Furthermore, the bandgap of heterostructure undergoes significant changes primarily when the interface atoms change from S atom to Se atom. In addition, the bandgap of In 2 Se 2 S/WSiGeP 4 vdWHs with Ge/Se (S) interface contact exhibits a first increase and then decrease tendency under compressive (tensile) strain, and a directly decrease trend under tensile (compressive) strain. Our results provide immense promise for the development and application of Janus heterostructure, offering a useful guidance for future device designs.
作者机构：
[Zhou, Wang; Han, Miaomiao; Liu, Jilei; Gao, Peng; Tang, Rui; Mo, Ying] Hunan Univ, Coll Mat Sci & Engn, Hunan Joint Int Lab Adv Mat & Technol Clean Energy, Hunan Prov Key Lab Adv Carbon Mat & Appl Technol, Changsha 410082, Hunan, Peoples R China.;[Wang, Dan] Hengyang Normal Univ, Univ Hunan Prov, Key Lab Micronano Energy Mat & Applicat Technol, Hengyang 421002, Hunan, Peoples R China.;[Wang, Dan] Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang 421002, Hunan, Peoples R China.;[Chen, Shi] Univ Macau, Inst Appl Phys & Mat Engn, Joint Key Lab, Minist Educ, Taipa 999078, Macao, Peoples R China.;[Yoshii, Takeharu; Wakabayashi, Keigo; Nishihara, Hirotomo] Tohoku Univ, Inst Multidisciplinary Res Adv Mat, 2-1-1 Katahira,Aoba Ku, Sendai, Miyagi 9808577, Japan.
通讯机构：
[Liu, JL ] H;Hunan Univ, Coll Mat Sci & Engn, Hunan Joint Int Lab Adv Mat & Technol Clean Energy, Hunan Prov Key Lab Adv Carbon Mat & Appl Technol, Changsha 410082, Hunan, Peoples R China.
关键词：
Hard carbon;Surface chemistry;C-H bond;Initial coulombic efficiency;Adsorption capacity
摘要：
Controlling surface chemistry is critically important for improving the initial Coulombic efficiency (ICE) and adsorption capacity of hard carbon anode used in Li/Na/K-ion batteries. However, accurately identifying the types and concentrations of hydrogen/oxygen terminated functional groups (HTFG/OTFGs) and distinguishing their functionalities remain challenge. Herein, we quantitatively investigated the surface chemistry on hard carbon via ultra-high temperature programed desorption measurements, and uncovered the role of HTFG/OTFGs in influencing ICE and adsorption capacity in Li/Na/K-ions cells. The C–H group is found to be dominant species on the surface of hard carbon, and presents a positive correlation with ICE values and adsorption capacity. The low reactivity of C–H group with both electrolyte salt and solvent results in the formation of thinner and highly conducive solid electrolyte interphase (SEI) layer, which benefit for the enhanced ICE and improved Li/Na/K-ions diffusion across SEI layer. Additionally, the pimping trapping effect of C–H groups allows the adsorbed Li/Na/K-ions to migrate into graphitic interlayer quickly, enhancing the slope capacity. By fabricating a C–H group-rich surface chemistry on hard carbon, a high ICE value and satisfactory specific capacity have been realized. These findings enrich our understanding of the surface chemistry-induced interfacial reaction, which effectively guides the rational design of high-performance hard carbon.
Controlling surface chemistry is critically important for improving the initial Coulombic efficiency (ICE) and adsorption capacity of hard carbon anode used in Li/Na/K-ion batteries. However, accurately identifying the types and concentrations of hydrogen/oxygen terminated functional groups (HTFG/OTFGs) and distinguishing their functionalities remain challenge. Herein, we quantitatively investigated the surface chemistry on hard carbon via ultra-high temperature programed desorption measurements, and uncovered the role of HTFG/OTFGs in influencing ICE and adsorption capacity in Li/Na/K-ions cells. The C–H group is found to be dominant species on the surface of hard carbon, and presents a positive correlation with ICE values and adsorption capacity. The low reactivity of C–H group with both electrolyte salt and solvent results in the formation of thinner and highly conducive solid electrolyte interphase (SEI) layer, which benefit for the enhanced ICE and improved Li/Na/K-ions diffusion across SEI layer. Additionally, the pimping trapping effect of C–H groups allows the adsorbed Li/Na/K-ions to migrate into graphitic interlayer quickly, enhancing the slope capacity. By fabricating a C–H group-rich surface chemistry on hard carbon, a high ICE value and satisfactory specific capacity have been realized. These findings enrich our understanding of the surface chemistry-induced interfacial reaction, which effectively guides the rational design of high-performance hard carbon.
期刊：
Expert Systems with Applications,2025年272:126693 ISSN：0957-4174
通讯作者：
Chen, WH
作者机构：
[Yan, Li; Chen, Wenhui; Zhao, Huihuang; Yang, Yanqing; Wang, Weijie] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;[Chen, Wenhui; Yang, Yanqing] Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.;[Zhao, Huihuang] Hunan Univ, Natl Engn Lab Robot Visual Percept & Control Techn, Hengyang, Peoples R China.
通讯机构：
[Chen, WH ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
关键词：
Time series floating point data;Lossless compression;Internet of things;Compression algorithm;Heuristic genetic algorithm
摘要：
The processing of large volumes of time series data across various fields presents significant challenges, particularly when it comes to effectively managing floating-point numbers. Current dual precision floating-point lossless compression algorithms often struggle to deliver exceptional performance on diverse datasets, highlighting their inherent limitations. To address this issue, we propose a novel method called the Heuristic Genetic Algorithm Parameter Optimizer for Lossless Compression of Time Series Floating Point Data (HGA-ACTF). This method features a highly effective parameter optimizer designed specifically for compression algorithms that utilize leading zeros. The combination of our parameter optimizer and the HGA-ACTF algorithm strategy has been proven to outperform existing leading compression algorithms across multiple fields. This approach not only enhances the compression ratio but also significantly reduces both compression and decompression times. In our comparative study, we evaluated the HGA-ACTF algorithm against eleven well-performing algorithms and a variant of the algorithm, integrating our parameter optimizer and algorithmic strategy into other adaptable algorithms, and demonstrating notable improvements. Experimental results indicate that the HGA-ACTF algorithm achieves an average compression ratio improvement of 38.87%, with some datasets showing improvements of up to 54.36%. Our approach effectively addresses the transmission and storage of time series data, significantly reducing the overhead associated with data processing. The code can be found at https://github.com/wwj10/HGA-ACTF .
The processing of large volumes of time series data across various fields presents significant challenges, particularly when it comes to effectively managing floating-point numbers. Current dual precision floating-point lossless compression algorithms often struggle to deliver exceptional performance on diverse datasets, highlighting their inherent limitations. To address this issue, we propose a novel method called the Heuristic Genetic Algorithm Parameter Optimizer for Lossless Compression of Time Series Floating Point Data (HGA-ACTF). This method features a highly effective parameter optimizer designed specifically for compression algorithms that utilize leading zeros. The combination of our parameter optimizer and the HGA-ACTF algorithm strategy has been proven to outperform existing leading compression algorithms across multiple fields. This approach not only enhances the compression ratio but also significantly reduces both compression and decompression times. In our comparative study, we evaluated the HGA-ACTF algorithm against eleven well-performing algorithms and a variant of the algorithm, integrating our parameter optimizer and algorithmic strategy into other adaptable algorithms, and demonstrating notable improvements. Experimental results indicate that the HGA-ACTF algorithm achieves an average compression ratio improvement of 38.87%, with some datasets showing improvements of up to 54.36%. Our approach effectively addresses the transmission and storage of time series data, significantly reducing the overhead associated with data processing. The code can be found at https://github.com/wwj10/HGA-ACTF .
作者机构：
[Jiang, Yong; Wang, Chengying; Xiang, Lijun] Anqing Normal Univ, Anqing Forestry Technol Innovat Res Inst, Collaborat Innovat Ctr Targeted Dev Med Resources, Sch Life Sci,Key Lab Biodivers Conservat & Charact, Anqing 246011, Peoples R China.;[Hu, ZF; Hu, Zhifeng; Wang, Yong] Wannan Med Coll, Affliated Hosp 1, Yijishan Hosp, Dept Intervent Therapy, Wuhu, Peoples R China.;[Mao, Yifu; Mao, YF] Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang 421002, Peoples R China.
通讯机构：
[Hu, ZF ] W;[Mao, YF ] H;[Xiang, LJ ] A;Anqing Normal Univ, Anqing Forestry Technol Innovat Res Inst, Collaborat Innovat Ctr Targeted Dev Med Resources, Sch Life Sci,Key Lab Biodivers Conservat & Charact, Anqing 246011, Peoples R China.;Wannan Med Coll, Affliated Hosp 1, Yijishan Hosp, Dept Intervent Therapy, Wuhu, Peoples R China.
关键词：
in vivo multimodal bioimaging;lanthanide fluorides;nanobio-probe
摘要：
Multimodal bioimaging is beneficial for clinical diagnosis and research due to the provision of comprehensive diagnostic information. However, the design of multifunctional bio-probes aggregating multiple bioimaging functions is greatly challenging. In this study, a multifunctional bio-probe based on lanthanide-based nanomaterials Sr(2)GdF(7): Yb(3+)/Er(3+)/Tm(3+)(abbreviated as SGF) was developed forin vivomultimodal imaging by co-adopting apropos lanthanides and tuning their molar ratio. The experimental results indicate that SGF incorporates multiple excellent properties, such as 10 nm small size, optimal red-NIR region emissions, strong paramagnetism, excellent x-ray absorption ability and high biological safety. More importantly, SGF successfully realizedin vivomultimodal imaging of upconversion luminescence, magnetic resonance and x-ray computed tomography at the animal level. Thus, SGF is expected to become a multifunctional bio-probe for clinical research/diagnosis. This research would promote the application and transformation of lanthanide fluorides nanomaterials in the field of clinical diagnosis to a certain extent.
通讯机构：
[Deng, YH ] H;[Xiang, HY ] N;Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang 421002, Hunan, Peoples R China.;Nanjing Univ Sci &Technol, Inst Optoelect & Nanomat, Sch Mat Sci & Engn, MIIT Key Lab Adv Display Mat & Devices, Nanjing 210094, Jiangsu, Peoples R China.
关键词：
perovskite/organic hybrid white light-emitting diodes (WLEDs);LiF interlayer;supplementary emission layer;recombination region;Commission Internationale de L'Eclairage(CIE)
摘要：
Perovskite light-emitting diodes (PeLEDs) have great potential in solid-state lighting and display fields due to their advantages of narrow emission spectrum, excellent optoelectronic properties, simple preparation process, and low cost. However, the compatibility of solvents used in the full solution process substantially hindered the development of multilayer white PeLEDs. Although mixing perovskite and organic materials can avoid this problem, it remains challenging to manufacture white PeLEDs that are close to the Commission Internationale de L'Eclairage (CIE) coordinate of (0.33,0.33). In this paper, the perovskite/organic hybrid white light-emitting diodes composed of a bottom blue perovskite light-emitting unit prepared through a solution method and an organic light-emitting unit fabricated by thermal evaporation are reported. To enhance carrier transport and adjust the recombination region, we employed several strategies: improving the perovskite surface with phenylethylammonium bromide additive, optimizing the thickness of the organic red emission layer, inserting a lithium fluoride layer, and incorporating a blue supplementary emission layer. The best white PeLED shows a maximum luminance of 2281 cd/m2, a maximum external quantum efficiency of 2.64%, a CIE coordinate close to the equal-energy white point of (0.33,0.34), and a correlated color temperature of 5206 K. The results presented in this paper provide a feasible method for obtaining white PeLEDs with excellent CIE coordinates.
作者机构：
[Chen, Haiyang; Wang, Ziyue; Chen, Weijie; Kang, Shuaiqing; Yuan, Jixiang; Zhu, Juan; Chen, Xining; Li, Yaowen; Li, Yongfang; Zhang, Zhichao; Cao, Jianlei; Zheng, Jialei; Xu, Jiacheng] Soochow Univ, Coll Chem Chem Engn & Mat Sci, Suzhou Key Lab Novel Semicond Optoelect Mat & Dev, Lab Adv Optoelect Mat, Suzhou 215123, Peoples R China.;[Jiang, Xingxing] Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang 421002, Hunan, Peoples R China.;[Li, Yaowen; Li, Yongfang] Soochow Univ, Jiangsu Key Lab Adv Negat Carbon Technol, Suzhou 215123, Peoples R China.;[Li, Yaowen] Soochow Univ, Coll Chem Chem Engn & Mat Sci, Jiangsu Key Lab Adv Funct Polymer Design & Applic, State & Local Joint Engn Lab Novel Funct Polymer, Suzhou 215123, Peoples R China.;[Li, Yongfang] Chinese Acad Sci, Beijing Natl Lab Mol Sci, CAS Key Lab Organ Solids, Inst Chem, Beijing 100190, Peoples R China.
通讯机构：
[Li, YW ; Chen, WJ] S;Soochow Univ, Coll Chem Chem Engn & Mat Sci, Suzhou Key Lab Novel Semicond Optoelect Mat & Dev, Lab Adv Optoelect Mat, Suzhou 215123, Peoples R China.;Soochow Univ, Jiangsu Key Lab Adv Negat Carbon Technol, Suzhou 215123, Peoples R China.;Soochow Univ, Coll Chem Chem Engn & Mat Sci, Jiangsu Key Lab Adv Funct Polymer Design & Applic, State & Local Joint Engn Lab Novel Funct Polymer, Suzhou 215123, Peoples R China.
关键词：
Carrier transport;Defect states;Operational stability;Perovskite/organic tandem solar cells;quasi-2D/3D perovskite heterojunction
摘要：
Wide-bandgap (WBG) perovskites are continuously in the limelight owing to their applicability in tandem solar cells. The main bottlenecks of WBG perovskites are interfacial non-radiative recombination and carrier transport loss caused by interfacial defects and large energy-level offsets, which induce additional energy losses when WBG perovskites are stacked with organic solar cells in series because of unbalanced carrier recombination in interconnecting layer (ICL). To solve these issues, 1,3-propanediammonium iodide (PDADI) is incorporated to form Dion-Jacobson -phase quasi-2D perovskites with mixed high-n-values in WBG perovskites. PDADI simultaneously repairs the shallow/deep defects and establishes a Type-II energy-level alignment between quasi-2D/3D and 3D perovskites for rapid carrier extraction. More importantly, the short-chain diammonium cation in quasi-2D perovskite with high n-values results in a short Pb-I inorganic layer spacing, which enhances the interlayer electronic coupling and weakens the quantum-well confinement effect that restricts carrier transport. The suppressed transport loss increases the electron concentration in the ICL for balanced carrier recombination. The 0.0628 and 1.004 cm(2) perovskite/organic tandems achieve remarkable efficiencies of 25.92% and 24.63%, respectively. The quasi-2D capping layer can inhibit ion migration, allowing perovskite/organic tandems to show excellent operational stability (T(85) >1000h).
摘要：
Currently, Camouflaged Object Detection (COD) methods often rely on single-view feature perception, which struggles to fully capture camouflaged objects due to environmental interference such as background clutter, lighting variations, and viewpoint changes. To address this, we propose the Multi-view Collaboration Network (MCNet), inspired by human visual strategies for complex scene analysis. MCNet incorporates multiple perspectives for enhanced feature extraction. The global perception module takes the original, far, and near views, using different large-kernel convolutions and multi-head attention mechanisms for global feature embedding. In parallel, the local perception module processes the tilted, projected, and color-jittered views, extracting fine-grained local features through multi-branch deep convolutions and dilated convolutions. To facilitate deep interaction between global and local features, we introduce the hybrid interactive module, which explores the correlation of multi-view feature information and adaptively fuses features. For feature decoding, the dynamic pyramid shrinkage module integrates dynamic gated convolutions with a pyramid shrinkage mechanism, progressively aggregating semantic features through a hierarchical shrinking strategy and group fusion strategy. Experimental results on popular COD benchmark datasets show that MCNet outperforms 18 state-of-the-art methods.
Currently, Camouflaged Object Detection (COD) methods often rely on single-view feature perception, which struggles to fully capture camouflaged objects due to environmental interference such as background clutter, lighting variations, and viewpoint changes. To address this, we propose the Multi-view Collaboration Network (MCNet), inspired by human visual strategies for complex scene analysis. MCNet incorporates multiple perspectives for enhanced feature extraction. The global perception module takes the original, far, and near views, using different large-kernel convolutions and multi-head attention mechanisms for global feature embedding. In parallel, the local perception module processes the tilted, projected, and color-jittered views, extracting fine-grained local features through multi-branch deep convolutions and dilated convolutions. To facilitate deep interaction between global and local features, we introduce the hybrid interactive module, which explores the correlation of multi-view feature information and adaptively fuses features. For feature decoding, the dynamic pyramid shrinkage module integrates dynamic gated convolutions with a pyramid shrinkage mechanism, progressively aggregating semantic features through a hierarchical shrinking strategy and group fusion strategy. Experimental results on popular COD benchmark datasets show that MCNet outperforms 18 state-of-the-art methods.
摘要：
The CR-39 solid-state nuclear track detector is a commonly used instrument for passively measuring radon. When using CR-39 to measure the radon exhalation rate from the surface of a medium, the effects of leakage are often overlooked. However, to a certain extent, system leakage can affect the accuracy of the measurement results. Therefore, the effect of different effective decay constants (including leakage) on the radon exhalation rate is worth studying. In this study, both theoretical and experimental validation methods were used to verify the effect of the uncertainty of the effective decay constant on the results of CR-39 measurements of radon exhalation rate from the medium surface. In the theoretical validation, different values of radon exhalation rate can be obtained by substituting different effective decay constants into the CR-39 formula for measuring radon exhalation rate while keeping the other variables constant. In the experimental validation, the radon exhalation rate in the same medium was measured using both CR-39 and RAD7. Since the traditional passive method (CR-39 solid-state nuclear track detector) cannot directly obtain the effective decay constant, the effective decay constant in the CR-39 measurement experiment was replaced by the effective decay constant value fitted from the RAD7 experimental data. The results showed that the radon exhalation rate value measured by CR-39 was much larger than that measured by RAD7. From the theoretical and experimental validation, it is concluded that the uncertainty of the effective decay constant has a significant effect on the radon exhalation rate measured by CR-39.
The CR-39 solid-state nuclear track detector is a commonly used instrument for passively measuring radon. When using CR-39 to measure the radon exhalation rate from the surface of a medium, the effects of leakage are often overlooked. However, to a certain extent, system leakage can affect the accuracy of the measurement results. Therefore, the effect of different effective decay constants (including leakage) on the radon exhalation rate is worth studying. In this study, both theoretical and experimental validation methods were used to verify the effect of the uncertainty of the effective decay constant on the results of CR-39 measurements of radon exhalation rate from the medium surface. In the theoretical validation, different values of radon exhalation rate can be obtained by substituting different effective decay constants into the CR-39 formula for measuring radon exhalation rate while keeping the other variables constant. In the experimental validation, the radon exhalation rate in the same medium was measured using both CR-39 and RAD7. Since the traditional passive method (CR-39 solid-state nuclear track detector) cannot directly obtain the effective decay constant, the effective decay constant in the CR-39 measurement experiment was replaced by the effective decay constant value fitted from the RAD7 experimental data. The results showed that the radon exhalation rate value measured by CR-39 was much larger than that measured by RAD7. From the theoretical and experimental validation, it is concluded that the uncertainty of the effective decay constant has a significant effect on the radon exhalation rate measured by CR-39.
通讯机构：
[Zhao, HH ] H;Hengyang Normal Univ, Coll Comp Sci & technol, Hengyang 421008, Peoples R China.;Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421008, Peoples R China.
关键词：
Three-dimensional human pose estimation;Transformer;GCN;Prior knowledge
摘要：
Transformer-based approaches have significantly driven recent progress in three-dimensional human pose estimation. However, existing transformer-based approaches are still deficient in capturing localized features, and they lack task-specific a priori information by obtaining queries, keys, and values through simple linear mappings. Existing methods lack effective human constraints for model training. We introduce the Spatial Encoding Graph Convolutional Network Transformer (SEGCNFormer), designed to enhance model capacity in capturing local features. In addition, we propose a Temporal-Aware Network, which generates queries, keys, and values possessing a priori knowledge of human motion, enabling the model to better understand the structural information of human poses. Finally, we leverage the knowledge of human anatomy and motion to design the Human Structural Science Loss, which performs a rationality assessment of human actions and imposes physical constraints on the generated poses. Our method outperforms existing methods on the Human3.6M dataset in both 27 and 81 sampling frames, and our predicted poses are closer to the actual poses with less error. For the existing three issues, we proposed effective methods and conducted targeted experiments, which confirmed the effectiveness of our strategies.
作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China;[Yezhou Zhang; Lang Li; Yu Ou] College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China
通讯机构：
[Lang Li] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China
摘要：
Deep learning algorithms are increasingly employed to exploit side-channel information, such as power consumption and electromagnetic leakage from hardware devices, significantly enhancing attack capabilities. However, relying solely on power traces for side-channel information often requires adequate domain knowledge. To address this limitation, this work proposes a new attack scheme. Firstly, a Convolutional Neural Network (CNN)-based plaintext-extended bilinear feature fusion model is designed. Secondly, multi-model intermediate layers are fused and trained, yielding in the increase of the amount of effective information and generalization ability. Finally, the model is employed to predict the output probability of three public side-channel datasets (e.g. ASCAD, AES
$$\_$$
HD, and AES
$$\_$$
RD), and analyze the recovery key guessing entropy for each key to efficiently assess attack efficiency. Experimental results showcase that the plaintext-extended bilinear feature fusion model can effectively enhance the Side-Channel Attack (SCA) capabilities and prediction performance. Deploying the proposed method, the number of traces required for a successful attack on the ASCAD
$$\_$$
R dataset is significantly reduced to less than 914, representing an 70.5% reduction in traces compared to the network in Convolutional Neural Network-Visual Geometry Group (CNNVGG16) with plaintext, which incorporating plaintext features before the fully connected layer. Compared to existing solutions, the proposed scheme requires only 80% of the power traces for the attack mask design using only 75 epochs. As a result, the power of the proposed method is well proved through the different experiments and comparison processes.
摘要：
Aqueous zinc-iodine batteries have garnered increasing attention due to their low cost and high safety. However, their practical application is impeded by sluggish iodine redox reaction kinetics and the “shuttle effect” of polyiodides, which result in poor rate performance and limited cycled life. Here, we developed N -doped porous carbon fiber derived from Prussian blue and polyacrylonitrile (PAN) as a self-supporting cathode material for zinc-iodine batteries. The material demonstrates a high iodine adsorption capacity in the electrolyte solution. Density Function Theory (DFT) calculations indicate that the prepared materials demonstrate good catalytic activity. Furthermore, the interconnected carbon fiber network, characterized by high conductivity and a large specific surface area, facilitates rapid electron transport and ion diffusion. Consequently, the zinc-iodine battery demonstrates outstanding rate performance (148mAh g −1 at a high current density of 10 A g −1 ) and a long cycling life of 50,000 cycles, with a capacity retention rate of 72.1 %. Additionally, the battery achieves an impressive calendar life of 8 months and 23 days.
Aqueous zinc-iodine batteries have garnered increasing attention due to their low cost and high safety. However, their practical application is impeded by sluggish iodine redox reaction kinetics and the “shuttle effect” of polyiodides, which result in poor rate performance and limited cycled life. Here, we developed N -doped porous carbon fiber derived from Prussian blue and polyacrylonitrile (PAN) as a self-supporting cathode material for zinc-iodine batteries. The material demonstrates a high iodine adsorption capacity in the electrolyte solution. Density Function Theory (DFT) calculations indicate that the prepared materials demonstrate good catalytic activity. Furthermore, the interconnected carbon fiber network, characterized by high conductivity and a large specific surface area, facilitates rapid electron transport and ion diffusion. Consequently, the zinc-iodine battery demonstrates outstanding rate performance (148mAh g −1 at a high current density of 10 A g −1 ) and a long cycling life of 50,000 cycles, with a capacity retention rate of 72.1 %. Additionally, the battery achieves an impressive calendar life of 8 months and 23 days.
作者机构：
[Guowen Yue; Fangyan Wang] College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, Hunan, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, 421002, Hunan, China;Hunan Engineering Research Center of Cyberspace Security Technology and Applications, Hengyang Normal University, Hengyang, 421002, Hunan, China;[Ge Jiao] College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, Hunan, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, 421002, Hunan, China<&wdkj&>Hunan Engineering Research Center of Cyberspace Security Technology and Applications, Hengyang Normal University, Hengyang, 421002, Hunan, China
通讯机构：
[Ge Jiao] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, Hunan, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, 421002, Hunan, China<&wdkj&>Hunan Engineering Research Center of Cyberspace Security Technology and Applications, Hengyang Normal University, Hengyang, 421002, Hunan, China
摘要：
Current camouflaged object detection (COD) methods primarily rely on a direct mapping from image to mask. However, due to the inherent semantic and structural gap between the image and its corresponding mask, the learned feature representations often exhibit poor generalization ability. To address this issue, we propose a novel intra-domain dual reconstruction framework, termed InDReCT, which reformulates the image-to-mask prediction as a cross-domain transfer task by simultaneously reconstructing both the input image and its corresponding mask. Within this framework, semantic knowledge is transferred through two reconstruction processes from different domains: image reconstruction (appearance domain) and mask reconstruction (structure domain), and is eventually integrated back into the image-to-mask prediction task. This dual reconstruction mechanism implicitly guides the network to extract hidden appearance semantics from image-to-image reconstruction and explicit structural information from mask-to-mask reconstruction, thereby enhancing the model’s generalization capability. Extensive experiments on three benchmark COD datasets and four downstream tasks demonstrate that InDReCT consistently outperforms state-of-the-art methods in both detection accuracy and generalization ability. Notably, on the widely-used COD10K dataset, InDReCT achieves a Mean E-measure ( E m ) of 95.6%, surpassing the latest state-of-the-art model CamoDiffusion by 1.6%. Code and models will be publicly available at: https://github.com/KungFuProgrammerle/InDReCT.
Current camouflaged object detection (COD) methods primarily rely on a direct mapping from image to mask. However, due to the inherent semantic and structural gap between the image and its corresponding mask, the learned feature representations often exhibit poor generalization ability. To address this issue, we propose a novel intra-domain dual reconstruction framework, termed InDReCT, which reformulates the image-to-mask prediction as a cross-domain transfer task by simultaneously reconstructing both the input image and its corresponding mask. Within this framework, semantic knowledge is transferred through two reconstruction processes from different domains: image reconstruction (appearance domain) and mask reconstruction (structure domain), and is eventually integrated back into the image-to-mask prediction task. This dual reconstruction mechanism implicitly guides the network to extract hidden appearance semantics from image-to-image reconstruction and explicit structural information from mask-to-mask reconstruction, thereby enhancing the model’s generalization capability. Extensive experiments on three benchmark COD datasets and four downstream tasks demonstrate that InDReCT consistently outperforms state-of-the-art methods in both detection accuracy and generalization ability. Notably, on the widely-used COD10K dataset, InDReCT achieves a Mean E-measure ( E m ) of 95.6%, surpassing the latest state-of-the-art model CamoDiffusion by 1.6%. Code and models will be publicly available at: https://github.com/KungFuProgrammerle/InDReCT.
摘要：
Deep learning-assisted template attack (DLATA) is a novel side-channel attack (SCA) method proposed by Lichao Wu at CHES2022. It utilizes a triplet network to assist template attacks (TA), avoiding the redundant training and hyperparameter tuning required in traditional DL-based SCA methods. However, the training of the triplet network requires a large number of power samples due to its unique structure. We propose a new optimization scheme, in which the transfer learning (TL) technology is used to train multiple models on several similar datasets with fewer power traces, to mitigation the problem. The approach allows us to leverage pre-trained models to product a new mode on the another target dataset by fine-tuning weights so that significantly reduce the training cost for the triplet network while maintaining attack effectiveness. We remould the structure and dimensionality of similar datasets so that the models trained on them can perform effective transfer learning for training on the target dataset. Concretely, some of parameters and features obtained from pretraining can be used directly for the target task, while the rest only require fine-tuning. Evaluation and experimental validation on the public ASCAD dataset demonstrate that our method achieves or even surpasses the performance of the original method with a 90% reduction in the training set. These findings highlight the effectiveness of the proposed TL strategy in achieving robust attack performance in low-sample training environments.
Deep learning-assisted template attack (DLATA) is a novel side-channel attack (SCA) method proposed by Lichao Wu at CHES2022. It utilizes a triplet network to assist template attacks (TA), avoiding the redundant training and hyperparameter tuning required in traditional DL-based SCA methods. However, the training of the triplet network requires a large number of power samples due to its unique structure. We propose a new optimization scheme, in which the transfer learning (TL) technology is used to train multiple models on several similar datasets with fewer power traces, to mitigation the problem. The approach allows us to leverage pre-trained models to product a new mode on the another target dataset by fine-tuning weights so that significantly reduce the training cost for the triplet network while maintaining attack effectiveness. We remould the structure and dimensionality of similar datasets so that the models trained on them can perform effective transfer learning for training on the target dataset. Concretely, some of parameters and features obtained from pretraining can be used directly for the target task, while the rest only require fine-tuning. Evaluation and experimental validation on the public ASCAD dataset demonstrate that our method achieves or even surpasses the performance of the original method with a 90% reduction in the training set. These findings highlight the effectiveness of the proposed TL strategy in achieving robust attack performance in low-sample training environments.
摘要：
Unlike conventional single-atom catalysts (SACs), ferroelectric materials provide a novel approach to controlling catalytic activity through ferroelectric polarization switching. Herein, utilizing ab initio calculations, we investigated the effect of the polarization switching on the catalytic activities of oxygen reduction (ORR) and oxygen evolution reactions (OER) in ferroelectric SACs with transition-metal atoms anchored on the ferroelectric In 2 Se 3 monolayer. The polarization switching not only enables effective control of the reaction overpotentials but also the corresponding potential limiting steps, thereby activating and enhancing catalytic performance. Notably, reorienting the polarization direction at the specific reaction step can reactivate the stuck catalytic reduction and further improve the activity of specific TM-In 2 Se 3 with poor catalytic activity in both upward and downward polarization. Multilevel corrections involving overpotentials, orbital populations, and d-band centers demonstrate that the modulation of catalytic activity through polarization switching originates from the adjustable d-band centers of the supported metal atoms. These findings demonstrate that ferroelectricity switching is a highly promising avenue for improving OER and ORR activity.
Unlike conventional single-atom catalysts (SACs), ferroelectric materials provide a novel approach to controlling catalytic activity through ferroelectric polarization switching. Herein, utilizing ab initio calculations, we investigated the effect of the polarization switching on the catalytic activities of oxygen reduction (ORR) and oxygen evolution reactions (OER) in ferroelectric SACs with transition-metal atoms anchored on the ferroelectric In 2 Se 3 monolayer. The polarization switching not only enables effective control of the reaction overpotentials but also the corresponding potential limiting steps, thereby activating and enhancing catalytic performance. Notably, reorienting the polarization direction at the specific reaction step can reactivate the stuck catalytic reduction and further improve the activity of specific TM-In 2 Se 3 with poor catalytic activity in both upward and downward polarization. Multilevel corrections involving overpotentials, orbital populations, and d-band centers demonstrate that the modulation of catalytic activity through polarization switching originates from the adjustable d-band centers of the supported metal atoms. These findings demonstrate that ferroelectricity switching is a highly promising avenue for improving OER and ORR activity.
通讯机构：
[Li, HL ; Ma, L ] H;Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang 421008, Peoples R China.;Hebei Univ, Coll Phys Sci & Technol, Baoding 071002, Peoples R China.
摘要：
Two-dimensional ferroelectrics have attracted extensive attention owing to their unique structure and extraordinary physical characteristics. In this work, α-In(2)Se(3)/CaAl(2)Se(4) heterostructure was designed, and the variations of its electronic structure and optoelectronic properties under the action of ferroelectric polarization directions, external strain, and applied electric field were comprehensively investigated by using first-principles calculations. The results show that the band alignment of heterostructure can be dynamically switched between type I and type II with diverse stacking configurations and interface surface terminations. Furthermore, within the strain range from -10% to 10%, the α- In(2)Se(3)↓/CaAl(2)Se(4) heterostructure stably retains its type-I band alignment, whereas the In(2)Se(3)↑/CaAl(2)Se(4) heterostructure showcases type II alignment. In addition, the electric field can effectively modulate the band edge and band alignment of the heterostructure, achieving 15.8% and 16.5% PCEs for the α- In(2)Se(3)↑/CaAl(2)Se(4) and In(2)Se(3)↓/CaAl(2)Se(4) configuration, respectively. These findings lay the theoretical foundation for selective construction of ferroelectric heterostructures and provide a new platform for designing innovative optoelectronic devices.
