Search Results (90)

Accurate prediction of transformer oil temperature is crucial for load optimization scheduling and timely early warning of thermal faults in power transformers. This paper proposes a transformer oil temperature prediction method based on Complementary Ensemble Empirical Mode Decomposition (CEEMD), Outlier-Robust Ensemble Deep Random Vector Functional Link Network (ORedRVFL), and error correction. CEEMD is used to decompose the oil temperature data into multiple subsequences, enhancing the regularity and predictability of the data. Regularization and norm improvements are introduced to edRVFL to obtain a more robust ORedRVFL model. The Tent initialization-based Differential Evolution algorithm (TDE) is employed to optimize the model parameters and predict each subsequence. Finally, error correction is applied to the prediction results. Taking the main transformer of a hydropower station in Yunnan, China as an example, the experimental results show that the proposed method improves the prediction accuracy by 5.05% and 4.13% in winter and summer oil temperature predictions, respectively. Moreover, the model’s degradation is significantly reduced when random noise is added, which verifies its robustness. This method provides an efficient and accurate solution for transformer oil temperature prediction. Full article

Ternary choline chloride-based deep eutectic solvents (TDESs) exhibit unique physicochemical properties, including lower viscosities, lower melting points, higher thermal stabilities, and enhanced solvations compared to binary deep eutectic solvents (BDESs). Although BDESs have been widely studied, the addition of a third component in TDESs offers opportunities to further optimize their performance. This review aims to evaluate the physicochemical properties of TDESs and highlight their potential applications in sustainable industrial processes compared to BDESs. A comprehensive analysis of the existing literature was conducted, focusing on TDES properties, such as phase behavior, density, viscosity, pH, conductivity, and the effect of water, along with their applications in various fields. TDESs demonstrated superior physicochemical characteristics compared to BDESs, including improved solvation and thermal stability. Their applications in biomass conversion, CO₂ capture, heavy oil upgrading, refrigeration gases, and as solvents/catalysts in organic reactions show significant promise for enhancing process efficiency and sustainability. Despite their advantages, TDESs face challenges including limited predictive models, potential instability under certain conditions, and scalability hurdles. Overall, TDESs offer significant potential for advancing sustainable and efficient chemical processes for industrial applications. Full article

This study presents an adaptive sliding mode control strategy tailored for robotic manipulators, featuring a quasi-convex function-based control gain and a time-delay estimation (TDE) enhanced by neural networks. To compensate for TDE errors, the proposed method utilizes both the previous TDE error and radial basis function neural networks with a weight update law that includes damping terms to prevent divergence. Additionally, a continuous gain function that is quasi-convex function dependent on the magnitude of the sliding variable is proposed to replace the traditional switching control gain. This continuous function-based gain has effectiveness in suppressing chattering phenomenon while guaranteeing the stability of the robotic manipulator in terms of uniform ultimate boundedness, which is demonstrated through both simulation and experiment results. Full article

High-frequency (HF) communication is critical for applications such as over-the-horizon positioning and ionospheric detection. However, precise time-delay estimation in complex HF channels faces significant challenges from multipath fading, Doppler shifts, and noise. This paper proposes a Modulation Signal-based Adaptive Time-Delay Estimation (MATE) algorithm, which effectively decouples carrier and modulation signals and integrates phase-locked loop (PLL) and delay-locked loop (DLL) techniques. By leveraging the autocorrelation properties of 8PSK (Eight-Phase Shift Keying) signals, MATE compensates for carrier frequency deviations and mitigates multipath interference. Simulation results based on the Watterson channel model demonstrate that MATE achieves an average time-delay estimation error of approximately 0.01 ms with a standard deviation of approximately 0.01 ms, representing a 94.12% reduction in mean error and a 96.43% reduction in standard deviation compared to the traditional Generalized Cross-Correlation (GCC) method. Validation with actual measurement data further confirms the robustness of MATE against channel variations. MATE offers a high-precision, low-complexity solution for HF time-delay estimation, significantly benefiting applications in HF communication systems. This advancement is particularly valuable for enhancing the accuracy and reliability of time-of-arrival (TOA) detection in HF-based sensor networks and remote sensing systems. Full article

We present early follow-up observations of Einstein Probe (EP) X-ray transients, following its first year of operation. EP is a dedicated wide-field X-ray observatory that is transforming our understanding of the dynamic X-ray universe. During its first year, EP successfully detected a diverse range of high-energy transients—including gamma-ray bursts (GRBs), tidal disruption events (TDEs), and fast X-ray transients (FXTs), besides many stellar flares, disseminating 128 alerts in the aggregate. Ground-based optical follow-up observations, particularly those performed by our BOOTES telescope network, have played a crucial role in multi-wavelength campaigns carried out so far. Out of the 128 events, the BOOTES Network has been able to follow up 58 events, detecting 6 optical counterparts at early times. These complementary optical measurements have enabled rapid identification of counterparts, precise redshift determinations (such as EP250215a at $z=4.61$), and detailed characterization of the transient phenomena. The synergy between EP’s cutting-edge X-ray monitoring and the essential optical follow-up provided by facilities, such as the above-mentioned BOOTES Global Network or other Spanish ground-based facilities we have access to, underscores the importance and necessity of coordinated observations in the era of time-domain and multi-messenger astrophysics. Full article

This paper introduces a novel model-free nonsingular fixed-time sliding mode control (MF-NFxTSMC) strategy for precise trajectory tracking in robot arm systems. Unlike conventional sliding mode control (SMC) approaches that require accurate dynamic models, the proposed method leverages the time delay estimation (TDE) approach to effectively estimate system dynamics and external disturbances in real-time, enabling a fully model-free control solution. This significantly enhances its practicality in real-world scenarios where obtaining precise models is challenging or infeasible. A significant innovation of this work lies in designing a novel fixed-time control framework that achieves faster convergence than traditional fixed-time methods. Building on this, a novel MF-NFxTSMC law is developed, featuring a novel singularity-free fixed-time sliding surface (SF-FxTSS) and a novel fixed-time reaching law (FxTRL). The proposed SF-FxTSS incorporates a dynamic proportional term and an adaptive exponent, ensuring rapid convergence and robust tracking. Notably, its smooth transition between nonlinear and linear dynamics eliminates the singularities often encountered in terminal and fixed-time sliding mode surfaces. Additionally, the designed FxTRL effectively suppresses chattering while guaranteeing fixed-time convergence, leading to smoother control actions and reduced mechanical stress on the robotic hardware. The fixed-time stability of the proposed method is rigorously proven using the Lyapunov theory. Numerical simulations on the SAMSUNG FARA AT2 robotic platform demonstrate the superior performance of the proposed method in terms of tracking accuracy, convergence speed, and control smoothness compared to existing strategies, including conventional SMC, finite-time SMC, approximate fixed-time SMC, and global fixed-time nonsingular terminal SMC (NTSMC). Overall, this approach offers compelling advantages, i.e., model-free implementation, fixed-time convergence, singularity avoidance, and reduced chattering, making it a practical and scalable solution for high-performance control in uncertain robotic systems. Full article

Closed-Kinematic Chain Manipulators (CKCM) have gained attention due to their precise Cartesian motion capability through coordinated active joint movements. Furthermore, ensuring synchronization among the joints of CKCMs is critical for reliable operation. An advanced control scheme for CKCMs that combines Nonsingular Fast Terminal Sliding Mode Control (NFTSMC) with Time Delay Estimation (TDE) while utilizing synchronization errors, namely Syn-TDE-NFTSMC, to effectively address joint errors in CKCMs was developed. NFTSMC enables fast convergence through nonlinear terminal sliding while TDE eliminates the need for prior knowledge of the robot’s dynamics, thereby simplifying its implementation and reducing its computational requirements. It is known that the inclusion of TDE reduces about 98% of the computational requirement of control schemes without TDE. The newly developed control scheme was rigorously evaluated using computer simulation and its control performance was compared with that of existing control methods. This paper presents an experimental study where the newly developed control scheme and other existing control schemes were applied to a real CKCM with 2 degrees of freedom (DOF). The experimental results confirm that the control scheme performed much better than other existing control schemes in terms of synchronization and control performance, achieving a reduction in maximum tracking errors of up to 81% as compared to other existing control schemes. The results confirm the efficacy of the newly developed control scheme in enhancing control precision and system stability, making it a promising solution for improving CKCM control strategies in real-world applications. Full article

In underwater signal processing, accurate time delay estimation (TDE) is of crucial importance for ensuring the reliability of data transmission. However, the complex propagation of sound waves and strong noise interference in the underwater environment make this task extremely challenging. Especially under the condition of low signal-to-noise ratio (SNR), the existing methods based on cross-correlation and deep learning struggle to meet requirements. Aiming at this core issue, this paper proposed an innovative solution. Firstly, a multi-sub-window reconstruction is performed on the frequency-sliding generalized colorboxpinkcross-correlation (FS-GCC) matrix between signals to capture the time delay characteristics from different frequency bands and conduct the enhancement and extraction of features. Then, the grayscale image corresponding to the generated FS-GCC matrix is used, and the multi-level noise features are extracted by the multi-layer convolution of denoising convolutional neural network (DnCNN), effectively suppressing the noise and improving the estimation accuracy. Finally, the model-agnostic meta-learning (MAML) framework is introduced. Through training tasks under various SNR conditions, the model is enabled to possess the ability to quickly adapt to new environments, and it can achieve the desired estimation accuracy even when the number of underwater training samples is limited. Simulation validation was conducted under the NOF and NCS underwater acoustic channels, and results demonstrate that our proposed approach exhibits lower estimation errors and greater stability compared with existing methods under the same conditions. This method enhances the practicality and robustness of the model in complex underwater environments, providing strong support for the efficient and stable operation of underwater sensor networks. Full article

In this paper, various types of quantum circuits for DES components are proposed to analyze the trade-offs in quantum resources for both DES and TDES block ciphers. Specifically, multiple optimized structures within the DES framework are devised, and by integrating different elements from each type, 34 possible configurations for the DES block cipher are generated. The required quantum resources for these configurations are then estimated, identifying not only qubit-optimized and depth-optimized circuits but also those achieving a balanced trade-off between qubit and circuit depth. Building on these optimized DES designs, TDES circuits are constructed, and the corresponding cost of a Grover-based attack on the TDES is estimated. Full article

Exosomes are actively produced extracellular vesicles, released from different cell types, that exert important regulatory roles in vital cellular functions. Tumor-derived exosomes (TDEs) have received increasing attention because they enable intercellular communication between the neoplastic and non-neoplastic cells present in the microenvironment of tumors, affecting important functions of different types of mesenchymal stem cells (MSCs) with the ability to self-renew and differentiate. MSC-derived exosomes (MSC-exos) carry a variety of bioactive molecules that can interact with specific cellular targets and signaling pathways, influencing critical processes in tumor biology, and exhibiting properties that either promote or inhibit tumor progression. They can regulate the tumor microenvironment by modulating immune responses, enhancing or suppressing angiogenesis, and facilitating tumor cells’ communication with distant sites, thus altering the behavior of non-cancerous cells present in the microenvironment. Herein, we explore the main functions of TDEs and their intricate interactions with MSC-exos, in terms of enhancing cancer progression, as well as their promising clinical applications as tumor microenvironment modulators. Full article

The central conducting lymphatics (CCL) and mesenteric lymphatic systems are responsible for lipid absorption, fluid regulation, and protein delivery into the bloodstream. Disruptions in these systems can result in debilitating conditions such as chylothorax, plastic bronchitis, post-operative lymphocele, protein-losing enteropathy (PLE), and chylous ascites. Advances in imaging techniques, including magnetic resonance lymphangiography (MRL), computed tomography lymphangiography (CTL), and fluoroscopic lymphangiography, allow for detailed anatomic and functional evaluation of the lymphatic system, facilitating accurate diagnosis and intervention by interventional radiologists. This review explores the embryology, anatomy, and pathophysiology of the lymphatic system and discusses imaging modalities and interventional techniques employed to manage disorders of the conducting lymphatics in the chest and abdomen. Thoracic duct embolization (TDE), percutaneous transhepatic lymphatic embolization (PTLE), and sclerotherapy are highlighted as effective, minimally invasive approaches to treat lymphatic leaks and obstructions and have shown high success rates in reducing symptoms and improving patient outcomes, particularly when medical management fails. This review seeks to demonstrate how anatomical imaging can facilitate minimally invasive procedures to rectify disorders of lymphatic flow. Full article

Due to the difficulty in ensuring launch safety under unfavorable launch site conditions, restrictions regarding the selection of launch sites significantly weaken the maneuverability of the unsupported random vertical launch (URVL) mode. In this paper, a nonlinear robust control strategy is proposed to control the missile attitude by actively adjusting the oscillation of the launcher through the hydraulic actuator, enhancing the launching safety and the adaptability of the VMLS to the launching site. Firstly, considering the interaction among the launch canister, adapters, and missile, a 6-DOF dynamic model of the launch system is established, in combination with the dynamics of the hydraulic actuator. Then, in order to facilitate the nonlinear controller design, the seventh-order state-space equation is constructed, according to the dynamic model of the launch system. Subsequently, in view of the problem of “differential explosion” in the backstepping controller design of the seventh-order nonlinear system, a nonlinear dynamic surface control (DSC) framework is proposed. Meanwhile, the time delay estimation (TDE) technique is introduced to suppress the influence of the complex nonlinearities of the launch system on the missile attitude control, and a nonlinear robust control (NRC) is introduced to attenuate the TDE error. Both of these are integrated into the DSC framework, which can achieve asymptotic output tracking. Finally, numerical simulations are conducted to validate the superiority of the proposed control strategy in regards to missile launch response control. Full article

Exosomes have emerged as pivotal players in precision oncology, offering innovative solutions to longstanding challenges such as metastasis, therapeutic resistance, and immune evasion. These nanoscale extracellular vesicles facilitate intercellular communication by transferring bioactive molecules that mirror the biological state of their parent cells, positioning them as transformative tools for cancer diagnostics and therapeutics. Recent advancements in exosome engineering, artificial intelligence (AI)-driven analytics, and isolation technologies are breaking barriers in scalability, reproducibility, and clinical application. Bioengineered exosomes are being leveraged for CRISPR-Cas9 delivery, while AI models are enhancing biomarker discovery and liquid biopsy accuracy. Despite these advancements, key obstacles such as heterogeneity in exosome populations and the lack of standardized isolation protocols persist. This review synthesizes pioneering research on exosome biology, molecular engineering, and clinical translation, emphasizing their dual roles as both mediators of tumor progression and tools for intervention. It also explores emerging areas, including microbiome–exosome interactions and the integration of machine learning in exosome-based precision medicine. By bridging innovation with translational strategies, this work charts a forward-looking path for integrating exosomes into next-generation cancer care, setting it apart as a comprehensive guide to overcoming clinical and technological hurdles in this rapidly evolving field. Full article

Background/Objectives: Coronary microvascular dysfunction (CMD) is emerging as a critical factor in patients presenting with anginal symptoms without obstructive coronary artery disease (CAD). This study aims to investigate the relationship between invasive measurements of coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR) using thermodilution techniques, compared to non-invasive assessments of CFR with transthoracic Doppler echocardiography (TDE). Methods: In this observational prospective cross-sectional study, a total of 49 patients, clinically characterized as having angina with no obstructive CAD (ANOCA) or ischemia with no obstructive CAD (INOCA), underwent both TDE and invasive coronary angiography (ICA) followed by thermodilution assessment of CFR and IMR. Results: It was found that there is a statistically significant negative correlation between both non-invasive and invasive CFR measurements and IMR. Specifically, a negative moderate correlation was observed between non-invasive CFR and IMR (r_s = −0.477, p < 0.01), as well as a high negative correlation between invasive CFR and IMR (r = −0.541, p < 0.01). Receiver operating characteristic (ROC) analysis indicated that both non-invasive and invasive CFRs are effective predictors of CMD, defined as IMR > 25. Conclusions: Both noninvasive and invasive CFR measurements are significant independent predictors of CMD. Our results indicate that noninvasive TDE CFR can be a reliable tool for assessing CMD in patients with ANOCA, potentially facilitating earlier diagnosis and management strategies for this patient population. Full article

Skin Conductance Response (SCR) is a physiological index associated with arousing emotions. Previous studies have not explored the relationship between SCR signals and emotions in situations where multiple emotions dynamically fluctuate. Moreover, methods suitable for analyzing such conditions have not yet been established. In this study, we recorded the temporal changes in multiple emotions as subjectively reported by participants using the Temporal Dominance of Emotions (TDE) method. We then matched these subjective reports with the evolving SCR signals through regression analysis. This approach reveals which emotions contribute to increased SCR signals in prolonged, emotionally charged scenarios, such as watching videos or playing video games. To validate our method, we recorded SCR signals while participants played a video game. Participants then performed the TDE task to recall their emotions while viewing recorded footage. This study involved 20 participants. Our analysis showed that emotions such as excitement, tension, and frustration significantly covaried with the physiological signals. These arousing emotions are known to evoke SCR, supporting the validity of our method. This approach introduces a novel experimental methodology for comparing subjective reports and high-responsive physiology signals in settings where multiple emotions dynamically change. Full article