Search Results (19)

Glycopolypeptoids were synthesized and showed effective antifreeze activity, demonstrating their potential as novel antifreeze agents for cryopreservation. These polypeptide analogs offer improved stability and tunability compared with natural antifreeze glycoproteins (AFGPs) and existing synthetic mimics. Using the ring-opening polymerization of N-substituted N-carboxyanhydride monomers followed by click chemistry, glycopolypeptoids with controlled polymerization degrees and varied structures were designed and prepared. Their antifreeze performance was assessed via nanoliter osmometry and ice recrystallization inhibition assays, revealing a strong correlation between the molecular structure and antifreeze activity. The findings highlight glycopolypeptoids as a promising, cost-effective alternative to natural AFGPs, providing new insights into the development of biomimetic cryoprotectants. This study expands the understanding of synthetic antifreeze materials and offers a practical approach for improving cryopreservation efficiency in biomedical and industrial applications. Full article

Developing safe and efficient cryoprotectants is critical for effective cryopreservation in biomedical applications. Inspired by natural antifreeze proteins (AFPs), a series of linear and star-shaped peptoids featuring isopropanol side chains to mimic the amphiphilic characteristics of threonine were prepared. The effects of chain length and molecular topology on antifreeze properties were systematically investigated. Both ice recrystallization inhibition (IRI) and ice crystal growth suppression improved with increasing chain length, and star-shaped peptoids exhibited superior performance. Notably, the star-shaped peptoid S-(A₆)₃ demonstrated excellent antifreeze activity and low cytotoxicity, highlighting its promise as a novel, non-toxic alternative to conventional cryoprotectants like DMSO. These findings provide valuable insight into the structure-property relationship of peptoids for cryopreservation applications. Full article

A pure pursuit method based on an improved sparrow search algorithm is proposed to address low path-tracking accuracy of intelligent agricultural machinery in complex farmland environments. Firstly, we construct a function relating speed to look-ahead distance and develop a fitness function based on the prototype’s speed and pose deviation. Subsequently, an improved sparrow search algorithm (ISSA) is employed to adjust the pure pursuit model’s speed and look-ahead distance dynamically. Finally, improvements are made to the initialization of the original algorithm and the position update method between different populations. Simulation results indicate that the improved sparrow search algorithm exhibits faster convergence speed and better capability to escape local extrema. The real vehicle test results show that the proposed algorithm achieves an average lateral deviation of approximately 3 cm, an average heading deviation below 5°, an average stabilization distance under 5 m, and an average navigation time of around 46 s during path tracking. These results represent reductions of 51.25%, 30.62%, 49.41%, and 10.67%, respectively, compared to the traditional pure pursuit model. Compared to the pure pursuit model that only dynamically adjusts the look-ahead distance, the proposed algorithm shows reductions of 34.11%, 24.96%, 32.13%, and 11.23%, respectively. These metrics demonstrate significant improvements in path-tracking accuracy, pose correction speed, and path-tracking efficiency, indicating that the proposed algorithm can serve as a valuable reference for path-tracking research in complex agricultural environments. Full article

The rapid growth of social media and online information-sharing platforms facilitates the spread of rumors. Accurate rumor detection to minimize manual verification efforts remains a critical research challenge. While multimodal rumor detection leveraging both text and visual data has gained increasing attention due to the diversification of social media content, existing approaches face the following three key limitations: (1) yhey prioritize lexical features of text while neglecting inherent logical inconsistencies in rumor narratives; (2) they treat textual and visual features as independent modalities, failing to model their intrinsic connections; and (3) they overlook semantic incongruities between text and images, which are common in rumor content. This paper proposes a dual-chain multimodal feature learning framework for rumor detection to address these issues. The framework comprehensively extracts rumor content features through the following two parallel processes: a basic semantic feature extraction module that captures fundamental textual and visual semantics, and a logical connection feature learning module that models both the internal logical relationships within text and the cross-modal semantic alignment between text and images. The framework achieves the multi-level fusion of text–image features by integrating modal alignment and cross-modal attention mechanisms. Extensive experiments on the Pheme and Weibo datasets demonstrate that the proposed method performs better than baseline approaches, confirming its effectiveness in detecting multimodal rumors. Full article

In potassium ion electrode materials, MXenes have garnered significant attention in the energy storage field due to their high conductivity and complex surface chemistry. In this work, thiourea was used as a nitrogen–sulfur composite precursor, and a self-assembly method was employed to synthesize a material, named nitrogen–sulfur– MXene (NS-MXene). During the reaction, thiourea molecules attach to the surface and interlayers of MXene, increasing the interlayer spacing. Upon heating, thiourea molecules decompose into nitrogen (N) and sulfur (S), which then combine with the MXene material. The N and S provide additional capacity for potassium ion storage, while the increased interlayer spacing also facilitates the intercalation and deintercalation of K⁺. Use of NS-MXene as anode material for potassium-ion batteries results in a high-rate performance (final capacity of 205.2 mAhg⁻¹ at 0.1 Ag⁻¹), long-term cycling stability (128.5 mAhg⁻¹ at 0.5 Ag⁻¹), and a good specific capacity (141 mAhg⁻¹ at 0.1 Ag⁻¹). This groundbreaking discovery opens the door to investigating MXene-based energy storage materials with superior performance and creates a new standard for MXene derivatives. Full article

In the era of information overload, location-based social software has gained widespread popularity, and the demand for personalized POI (Point of Interest) recommendation services is growing rapidly. Recommending the next POI is crucial in recommendation systems, aiming to suggest appropriate next-visit locations based on users’ historical trajectories and check-in data. However, the existing research often neglects user preferences’ diversity and dynamic nature and the need for the deep modeling of key collaborative relationships across various dimensions. As a result, the recommendation performance is limited. To address these challenges, this paper introduces an innovative Multi-View Contrastive Fusion Hypergraph Learning Model (MVHGAT). The model first constructs three distinct hypergraphs, representing interaction, trajectory, and geographical location, capturing the complex relationships and high-order dependencies between users and POIs from different perspectives. Subsequently, a targeted hypergraph convolutional network is designed for aggregation and propagation, learning the latent factors within each view. Through multi-view weighted contrastive learning, the model uncovers key collaborative effects between views, enhancing both user and POI representations’ consistency and discriminative power. The experimental results demonstrate that MVHGAT significantly outperforms several state-of-the-art methods across three public datasets, effectively addressing issues such as data sparsity and oversmoothing. This model provides new insights and solutions for the next POI recommendation task. Full article

The current research on path tracking primarily focuses on improving control algorithms, such as adaptive and predictive models, to enhance tracking accuracy and stability. To address the issue of low tracking accuracy caused by variable-curvature paths in automatic navigation within agricultural environments, this study proposes a fuzzy control-based path-tracking method. Firstly, a pure-pursuit model and a kinematic model were established based on a Four-Wheel Independent Steering and Four-Wheel Independent Driving (4WIS-4WID) structure. Secondly, a fuzzy controller with three inputs and one output was designed, using the lateral deviation, d_e; heading deviation, θ_e; and bending degree, c, of the look-ahead path as the input variables. Through multiple simulations and adjustments, 75 control rules were developed. The look-ahead distance, Ld, was obtained through fuzzification, fuzzy inference, and defuzzification processes. Next, a speed-control function was constructed based on the agricultural machinery’s pose deviations and the bending degree of the look-ahead path to achieve variable speed control. Finally, field tests were conducted to verify the effectiveness of the proposed path-tracking method. The tracking experiment results for the two types of paths indicate that under the variable-speed dynamic look-ahead distance strategy, the average lateral deviations for the variable-curvature paths were 1.8 cm and 3.3 cm while the maximum lateral deviations were 10.1 cm and 10.5 cm, respectively. Compared to the constant-speed fixed look-ahead pure-pursuit model, the average lateral deviation was reduced by 56.1% and the maximum lateral deviation by 50.4% on the U-shaped path. On the S-shaped path, the average lateral deviation was reduced by 56.0% and the maximum lateral deviation by 58.9%. The proposed method effectively improves the path-tracking accuracy of agricultural machinery on variable-curvature paths, meeting the production requirements for curved operations in agricultural environments. Full article

Accurate knowledge of oscillation parameters (i.e., frequency, amplitude, phase, and damping factor) is crucial for control strategies of power systems under power swing. This paper presents a method for the parameter estimation of power system oscillation signals under power swing based on Clarke–DFT. The proposed method provides accurate parameter estimation of damped sinusoidal signals for both balanced and unbalanced systems, which performs well even in the presence of harmonics. In the meantime, the negative frequency components in the spectra of the damped sinusoidal signals, which are caused by system imbalance, are calculated accurately using complex-valued interpolated DFT. To verify the performance of the proposed method, simulations are performed under balanced and unbalanced conditions. The results of the simulations confirm the effectiveness of the proposed method either in unbalanced or harmonic conditions. Full article

Chaos-based image encryption has become a prominent area of research in recent years. In comparison to ordinary chaotic systems, fractional-order chaotic systems tend to have a greater number of control parameters and more complex dynamical characteristics. Thus, an increasing number of researchers are introducing fractional-order chaotic systems to enhance the security of chaos-based image encryption. However, their suggested algorithms still suffer from some security, practicality, and efficiency problems. To address these problems, we first constructed a new fractional-order 3D Lorenz chaotic system and a 2D sinusoidally constrained polynomial hyper-chaotic map (2D-SCPM). Then, we elaborately developed a multi-image encryption algorithm based on the new fractional-order 3D Lorenz chaotic system and 2D-SCPM (MIEA-FCSM). The introduction of the fractional-order 3D Lorenz chaotic system with the fourth parameter not only enables MIEA-FCSM to have a significantly large key space but also enhances its overall security. Compared with recent alternatives, the structure of 2D-SCPM is simpler and more conducive to application implementation. In our proposed MIEA-FCSM, multi-channel fusion initially reduces the number of pixels to one-sixth of the original. Next, after two rounds of plaintext-related chaotic random substitution, dynamic diffusion, and fast scrambling, the fused 2D pixel matrix is eventually encrypted into the ciphertext one. According to numerous experiments and analyses, MIEA-FCSM obtained excellent scores for key space ($2^{541}$), correlation coefficients (<0.004), information entropy (7.9994), NPCR (99.6098%), and UACI (33.4659%). Significantly, MIEA-FCSM also attained an average encryption rate as high as 168.5608 Mbps. Due to the superiority of the new fractional-order chaotic system, 2D-SCPM, and targeted designs, MIEA-FCSM outperforms many recently reported leading image encryption algorithms. Full article

The assemblage of oceanic islands and seamounts, arising from the widespread presence of mature oceans, plays a crucial role in reconstructing the evolutionary history of the paleoocean. Oceanic islands or seamounts within the Longmuco-Shuanghu metamorphic complex, a remnant of the Paleo-Tethys Ocean in the central Tibetan Plateau, have seldom been reported due to their remoteness. This study has identified an oceanic island-seamount in the Maoershan area, situated to the west of the Longmuco-Shuanghu metamorphic complex, composed of basalt, diabase, limestone, and siliceous rocks. Based on field observations, petrology, zircon U-Pb dating, whole-rock geochemistry, and Sr-Nd isotopes analyses, we have identified a suite of mafic rocks with OIB affinity. The youngest zircon U-Pb age cluster was concentrated at ~243–241 Ma. The geochemical characteristics of the siliceous rocks indicate a mixture of terrigenous material, suggesting that they formed in a continental margin. In combination with regional geological data, we conclude that the Longmuco-Shuanghu Paleo-Tethys Ocean remained open during the Middle Triassic. Furthermore, a fraction of the oceanic island-seamounts underwent scraping and transformed into a metamorphic complex, while other segments experienced deep subduction, resulting in the formation of high-pressure metamorphic rocks. Collectively, these processes gave rise to the distinctive high-pressure metamorphic complex within the central Qiangtang terrane. Full article

Steel slag, desulphurised ash, desulphurised gypsum and ultra-fine iron tailing sand are common industrial solid wastes with low utilisation rates. Herein, industrial solid wastes (steel slag, desulphurised gypsum and desulphurised ash) were used as the main raw materials to prepare a gelling material and ultra-fine tailing was used as an aggregate to prepare a new type of cementing filler for mine filling. The optimal composition of the cementing filler was 75% steel slag, 16.5% desulphurised gypsum, 8.75% desulphurised ash, 1:4 binders and tailing mass ration and 70% concentration. The compressive strength of the 28-day sample reached 1.24 MPa, meeting the mine-filling requirements, while that of the 90-day sample was 3.16 MPa. The microscopic analysis results showed that a small amount of C₃A reacted with the sulphate in the desulphurised gypsum to form ettringite at the early stage of hydration after the steel slag was activated by the desulphurisation by-products. In addition, C₂S produced hydrated calcium silicate gel in an alkaline environment. As hydration proceeded, the sulphite in the desulphurised ash was converted to provide sulphate for the later sustained reaction. Under the long-term joint action of alkali and sulphate, the reactive silica–oxygen tetrahedra and alumina–oxygen tetrahedra depolymerised and then polymerised, further promoting the hydration reaction to generate hydrated calcium silicate gel and ettringite. The low-carbon and low-cost filler studied in this paper represents a new methodology for the synergistic utilisation of multiple forms of solid waste. Full article

The Graphene@PtSe₂ heterostructure is an excellent long-wave infrared detection material. However, the expensive cost of PtSe₂ prevents its widespread use in infrared detection. In this paper, Hf was used to partially replace Pt to form Graphene@(PtSe₂)_n(HfSe₂)_4−n (n = 1, 2, and 3) bidirectional heterostructures consisting of graphene and lateral PtSe₂/HfSe₂ composites based on first-principles calculations. Then, the new bidirectional heterostructures were compared with heterostructures formed by graphene with pure MSe₂ (M = Pt, Hf). It was found that the band gaps of the bidirectional heterostructures were between those of Graphene@PtSe₂ and Graphene@HfSe₂. Among these heterostructures, the Graphene@(PtSe₂)₃(HfSe₂)₁ bidirectional heterostructure has almost the same optical absorption properties in the infrared wavelength region of 1.33~40 µm as the Graphene@PtSe₂ heterostructure, and it improves the absorption in the near-infrared wavelength region of 0.75~1.33 µm. Such a designment may bring the material costs down (since PtSe₂ costs approximately five times more than HfSe₂). This study on the designment of the bidirectional Graphene@(PtSe₂)₃(HfSe₂)₁ heterostructure also illustrates a cost-effective design method for Pt-based IR detectors. Full article

Transcriptional coactivator p15 (PC4) encodes a structurally conserved but functionally diverse protein that plays crucial roles in RNAP-II-mediated transcription, DNA replication and damage repair. Although structures and functions of PC4 have been reported in most vertebrates and some invertebrates, the PC4 genes were less systematically identified and characterized in the bay scallop Argopecten irradians irradians. In this study, five PC4 genes (AiPC4s) were successfully identified in bay scallops via whole-genome scanning through in silico analysis. Protein structure and phylogenetic analyses of AiPC4s were conducted to determine the identities and evolutionary relationships of these genes. Expression levels of AiPC4s were assessed in embryos/larvae at all developmental stages, in healthy adult tissues and in different tissues (mantles, gills, hemocytes and hearts) being processed under 32 °C stress with different time durations (0 h, 6 h, 12 h, 24 h, 3 d, 6 d and 10 d). Spatiotemporal expression profiles of AiPC4s suggested the functional roles of the genes in embryos/larvae at all developmental stages and in healthy adult tissues in bay scallop. Expression regulations (up- and down-) of AiPC4s under high-temperature stress displayed both tissue-specific and time-dependent patterns with function allocations, revealing that AiPC4s performed differentiated functions in response to thermal stress. This work provides clues of molecular function allocation of PC4 in scallops in response to thermal stress and helps in illustrating how marine bivalves resist elevated seawater temperature. Full article

In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness. In the proposed method, early detection of MAs is performed using a hybrid feature embedding approach of pre-trained CNN models, named as VGG-19 and Inception-v3. The performance of the proposed approach was evaluated using publicly available datasets, namely “E-Ophtha” and “DIARETDB1”, and achieved 96% and 94% classification accuracy, respectively. Furthermore, the developed approach outperformed the state-of-the-art approaches in terms of sensitivity and specificity for microaneurysms detection. Full article

This paper focuses on how to improve the operation ability of a soft robotic hand (SRH). A trigger-based dexterous operation (TDO) strategy with multimodal sensors is proposed to perform autonomous choice operations. The multimodal sensors include optical-based fiber curvature sensor (OFCS), gas pressure sensor (GPS), capacitive pressure contact sensor (CPCS), and resistance pressure contact sensor (RPCS). The OFCS embedded in the soft finger and the GPS series connected in the gas channel are used to detect the curvature of the finger. The CPCS attached on the fingertip and the RPCS attached on the palm are employed to detect the touch force. The framework of TDO is divided into sensor detection and action operation. Hardware layer, information acquisition layer, and decision layer form the sensor detection module; action selection layer, actuator drive layer, and hardware layer constitute the action operation module. An autonomous choice decision unit is used to connect the sensor detecting module and action operation module. The experiment results reveal that the TDO algorithm is effective and feasible, and the actions of grasping plastic framework, pinching roller ball pen and screwdriver, and handshake are executed exactly. Full article