Search Results (688)

Stress fields imparted with an ultrafast laser can correct low spatial frequency surface figure error of mirrors through ultrafast laser stress figuring (ULSF): the formation of nanograting structures within the bulk substrate generates localized stress, creating bending moments that equilibrize via wafer deformation. For ULSF to be used as an optical figuring process, the ultrafast laser generated stress must be effectively permanent or risk unwanted figure drift. Two isochronal annealing experiments were performed to measure ultrafast laser-generated stress stability in fused silica and Corning ultra-low expansion (ULE) wafers. The first experiment tracked changes to induced astigmatism up to 1000 °C on 25.4 mm-diameter wafers. Only small changes were measured after each thermal cycle up to 500 °C for both materials, but significant changes were observed at higher temperatures. The second experiment tracked stress changes in fused silica and ULE up to 500 °C but with 4 to 16× higher signal-to-noise ratio. Change in trefoil on 100 mm-diameter wafers was measured, and the induced stress in fused silica and ULE was found to be stable after thermal cycling up to 300 °C and 200 °C, respectively, with larger changes at higher temperatures. Full article

The unique characteristics of desert vegetation, such as different leaf morphology, discrete canopy structures, sparse and uneven distribution, etc., pose significant challenges for remote sensing-based estimation of fractional vegetation cover (FVC). The Unmanned Aerial Vehicle (UAV) system can accurately distinguish vegetation patches, extract weak vegetation signals, and navigate through complex terrain, making it suitable for applications in small-scale FVC extraction. In this study, we selected the floodplain fan with Caragana korshinskii Kom as the constructive species in Hatengtaohai National Nature Reserve, Bayannur, Inner Mongolia, China, as our study area. We investigated the remote sensing extraction method of desert sparse vegetation cover by placing samples across three gradients: the top, middle, and edge of the fan. We then acquired UAV multispectral images; evaluated the applicability of various vegetation indices (VIs) using methods such as supervised classification, linear regression models, and machine learning; and explored the feasibility and stability of multiple machine learning models in this region. Our results indicate the following: (1) We discovered that the multispectral vegetation index is superior to the visible vegetation index and more suitable for FVC extraction in vegetation-sparse desert regions. (2) By comparing five machine learning regression models, it was found that the XGBoost and KNN models exhibited relatively lower estimation performance in the study area. The spatial distribution of plots appeared to influence the stability of the SVM model when estimating fractional vegetation cover (FVC). In contrast, the RF and LASSO models demonstrated robust stability across both training and testing datasets. Notably, the RF model achieved the best inversion performance (R² = 0.876, RMSE = 0.020, MAE = 0.016), indicating that RF is one of the most suitable models for retrieving FVC in naturally sparse desert vegetation. This study provides a valuable contribution to the limited existing research on remote sensing-based estimation of FVC and characterization of spatial heterogeneity in small-scale desert sparse vegetation ecosystems dominated by a single species. Full article

This paper presents a method for optimizing the inertia constants and damping coefficients of interconnected virtual synchronous generators (VSGs) using a genetic algorithm. The goal of optimization is to find a balance between minimizing the rate of change of frequency (RoCoF) and enhancing controllability. Five controllability-based metrics are tested: the minimum eigenvalue, the sum of the two smallest eigenvalues, the maximum eigenvalue, the trace, and the determinant of the controllability Gramian matrix. The approach includes the oscillatory modes’ damping ratio constraints to ensure the small-signal stability of the entire system. The results of optimization on the IEEE 9-bus system with three VSGs show that the proposed method improves controllability, reduces RoCoF, and maintains the desired oscillation damping. The proposed approach was tested through time-domain simulations. Full article

Grid-forming (GFM) energy storage can be utilized as a backup power source for the power grid to ensure the security of the power grid. GFM energy storage can also enhance the strength of the power grid and improve its stability. However, the GFM energy storage inherits the characteristics of the synchronous generator. Low-frequency oscillations may occur in GFM energy storage, which affect the stable operation of the power system. This paper proposed an additional damping control strategy for GFM energy storage to address the low-frequency oscillation. Firstly, this paper builds the state-space small-signal mathematical model of the GFM energy storage grid-connected system to analyze the participation factors of the low-frequency oscillation mode and clarify the key control parameters affecting the GFM energy storage grid-connected system the low-frequency oscillation. Then, this paper proposed an additional damping control strategy to increase the damping ratio of the low-frequency oscillation mode and improve the stability of the GFM energy storage grid-connected system. Finally, semi-physical experiments verified the effectiveness of the proposed additional damping control strategy. Full article

Glycated hemoglobin (HbA1c) is an important biomarker applied for the diagnosis, evaluation, and management of diabetes; therefore, its accurate determination is crucial. In this study, an innovative nanoplatform was developed, integrating carbon nanotubes (CNTs) with enhanced hydrophilicity achieved through cyclodextrin (CD) functionalization, and combined with gold nanoparticles (AuNPs) electrochemically deposited onto a screen-printed carbon electrode. The nanomaterials significantly improved the analytical performance of the sensor due to their increased surface area and high electrical conductivity. This nanoplatform was employed as a substrate for the covalent attachment of thiolated ferrocene-labeled HbA1c specific aptamer through Au-S binding. The electrochemical signal of ferrocene was covered by a stronger oxidation peak of Fe²⁺ from the HbA1c structure, leading to the elaboration of a nanostructured aptasensor capable of the direct detection of HbA1c. The electrochemical aptasensor presented a very wide linear range (0.688–11.5%), an acceptable limit of detection (0.098%), and good selectivity and stability, being successfully applied on real samples. This miniaturized, simple, easy-to-use, and fast-responding aptasensor, requiring only a small sample volume, can be considered as a promising candidate for the efficient on-site determination of HbA1c. Full article

Recent insights into the p53-MDM2 nexus have advanced deeper understanding of their regulation and potent impact on cancer heterogeneity. The roles of nuclear phosphoinositide (PIP_ns) in modulating this pathway are emerging as a key mechanism. Here, we dissect the molecular mechanisms by which nuclear PIP_ns stabilize p53 through the recruitment of small heat shock proteins (sHSPs), activate the nuclear phosphatidylinositol 3-kinase (PI3K)-AKT signaling cascade, and modulate MDM2 function to regulate the p53-MDM2 interaction. We propose potential mechanisms by which nuclear PIP_ns coordinate signaling with nuclear p53, AKT, and MDM2. Ultimately, we highlight that nuclear PIP_ns serve as a ‘third messenger’ within the p53-MDM2 axis, expanding the current framework of non-canonical nuclear signaling in cancer biology. Full article

Looking toward the future, governments around the world have started to change their energy mix due to climate change. The new energy mix will consist mainly of Inverter-Based Resources (IBRs), such as wind and solar power. This transition from a synchronous to a non-synchronous grid introduces new challenges in stability, resilience, and synchronization, necessitating advanced control strategies. Among these, Grid-Forming (GFM) control techniques have emerged as an effective solution for ensuring stable operations in microgrids and large-scale power systems with high IBRs integration. This paper presents a systematic review of GFM control techniques, focusing on their principles and applications. Using the PRISMA 2020 methodology, 75 studies published between 2015 and 2025 were synthesized to evaluate the characteristics of GFM control strategies. The review organizes GFM strategies, evaluates their performance under varying operational scenarios, and emphasizes persistent challenges like grid stability, inertia emulation, and fault ride-through capabilities. Furthermore, this study examines real-world implementations of GFM technology in modern power grids. Notable projects include the UK’s National Grid Pathfinder Program, which integrates GFM inverters to enhance stability, and Australia’s Hornsdale Power Reserve, where battery energy storage with GFM capabilities supports grid frequency regulation. Full article

Drought conditions impact plants at the morphological, physiological, and molecular levels. Plant tolerance to drought conditions is frequently associated with maintaining proteome stability, highlighting the significance of proteomic analysis in understanding the mechanisms underlying plant resilience. Here, we performed proteomic and peptidomic analysis of spring wheat (Triticum aestivum L.) under drought stress conditions. Using isobaric tags for relative and absolute quantitation (iTRAQ), we identified 497 and 157 differentially abundant protein (DAP) groups in leaves and roots, respectively. The upregulated DAP groups in leaves were primarily involved in stress responses, such as oxidative stress and heat response, whereas those in roots were associated with responses to water deprivation and sulfur compound metabolic processes. The analysis of the extracellular root peptidome revealed 2294 native peptides, including members of small secreted peptide (SSP) families. In the peptidomes of stress-induced plants, we identified 16 SSPs as well as peptides derived from proteins involved in cell wall catabolism, intercellular signaling, and stress response. These peptides represent potential candidates as regulators of drought responses. Our results help us to understand adaptation mechanisms and develop new agricultural technologies to increase productivity. Full article

Calcium plays a major role in all cellular functions, and its regulation is important in all aspects of human health. This key role calcium plays in cell function can be traced to its unique molecular coordination geometry, which is often overlooked in understanding calcium function. In this review, we integrate calcium’s ability to form various complexes with proteins and small molecules with its role as a key signaling atom. We argue that calcium’s ability to vary its coordination structures, compared to magnesium’s rigid geometry, explains its importance in biological functions. By examining calcium-mediated proteins, such as those containing EF-hand domains and those that assemble and stabilize the extracellular matrix in tissue organization, we demonstrate how calcium’s varied geometric coordination serves as both a signaling molecule and a regulator of physiological homeostasis. Full article

With the increasing level of inverter-based resources (IBRs) in modern power systems, this paper presents a small-signal stability analysis for power systems comprising synchronous generators (SGs) and IBRs. Four types of inverter controls are considered: two grid-following (GFL) controls, with or without grid support functions; droop-based grid-forming (GFM) controls; and virtual oscillator control-based GFM. We also analyze the impact of STATCOM and synchronous condensers on system stability to assess their role in the energy mix transition. With the small-signal dynamic behavior of the major technologies modeled, this paper provides stringent stability assessments using the IEEE 39-bus benchmark system modified to simulate future power systems. The exhaustive test cases allow for (a) assessing the impacts of different types and controls of generation and supplementary grid assets, as well as system inertia and line impedance on grid stability, and (b) elucidating pathways for the stabilization of IBR-dominated power systems. The analysis also indicates that future power systems can be stabilized with only a fraction of the total generation as voltage sources without SGs or significant system inertia if they are well distributed. This study provides insights into future power system operations with a high level of IBRs that can also be used for planning and operation studies. Full article

With China’s high-speed rail network undergoing rapid expansion, turnouts constitute critical elements whose safety and stability are essential to railway operation. At present, the efficiency of wheel–rail force safety monitoring conducted in the small hours reserved for the construction and maintenance of operating lines without marking train operation lines is relatively low. To enhance the efficiency of turnout safety monitoring, in this study, a three-dimensional BIM model of the No. 42 turnout was established and a corresponding wheel–rail force monitoring scheme was devised. Collision detection for monitoring equipment placement and construction process simulation was conducted using Navisworks, such that the rationality of cable routing and the precision of construction sequence alignment were improved. A train wheel–rail force analysis program was developed in MATLAB R2022b to perform signal filtering, and static calibration was applied to calculate key safety evaluation indices—namely, the coefficient of derailment and the rate of wheel load reduction—which were subsequently analyzed. The safety of the No. 42 turnout and the effectiveness of the proposed monitoring scheme were validated, theoretical support was provided for train operational safety and turnout maintenance, and technical guidance was offered for whole-life-cycle management and green, sustainable development of railway infrastructure. Full article

Underwater sonar target recognition is crucial in fields such as national defense, navigation, and environmental monitoring. However, it faces issues such as the complex characteristics of ship-radiated noise, imbalanced data distribution, non-stationarity, and bottlenecks of existing technologies. This paper proposes the MultiFuseNet-AID network, aiming to address these challenges. The network includes the TriFusion block module, the novel lightweight attention residual network (NLARN), the long- and short-term attention (LSTA) module, and the Mamba module. Through the TriFusion block module, the original, differential, and cumulative signals are processed in parallel, and features such as MFCC, CQT, and Fbank are fused to achieve deep multi-domain feature fusion, thereby enhancing the signal representation ability. The NLARN was optimized based on the ResNet architecture, with the SE attention mechanism embedded. Combined with the long- and short-term attention (LSTA) and the Mamba module, it could capture long-sequence dependencies with an O(N) complexity, completing the optimization of lightweight long sequence modeling. At the same time, with the help of feature fusion, and layer normalization and residual connections of the Mamba module, the adaptability of the model in complex scenarios with imbalanced data and strong noise was enhanced. On the DeepShip and ShipsEar datasets, the recognition rates of this model reached 98.39% and 99.77%, respectively. The number of parameters and the number of floating point operations were significantly lower than those of classical models, and it showed good stability and generalization ability under different sample label ratios. The research shows that the MultiFuseNet-AID network effectively broke through the bottlenecks of existing technologies. However, there is still room for improvement in terms of adaptability to extreme underwater environments, training efficiency, and adaptability to ultra-small devices. It provides a new direction for the development of underwater sonar target recognition technology. Full article

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression and have emerged as critical biomarkers in various diseases, including cancer. Their stability in bodily fluids and role as oncogenes or tumor suppressors make them attractive targets for non-invasive diagnostics. However, conventional detection methods, such as Northern blotting, RT-PCR, and microarrays, are limited by low sensitivity, lengthy protocols, and limited specificity. Electrochemical biosensors offer a promising alternative, providing high sensitivity, rapid response times, portability, and cost-effectiveness. These biosensors translate miRNA hybridization events into quantifiable electrochemical signals, often leveraging redox-active labels, mediators, or intercalators. Recent advancements in nanomaterials and signal amplification strategies have further enhanced detection capabilities, enabling sensitive, label-free miRNA quantification. This review provides a comprehensive overview of the recent advances in electrochemical biosensing of miRNAs, emphasizing innovative redox-based detection strategies, probe immobilization techniques, and hybridization modalities. The critical challenges and future perspectives in advancing electrochemical miRNA biosensors toward clinical translation and point-of-care diagnostics are discussed. Full article

Rotor–stator interaction and the coupling between the clearance flow and main flow amplify the flow complexity in small-scale, high-speed automotive pumps. This degrades the pressure fluctuations, compromising the operational stability of these pumps. To better understand the pressure fluctuation distribution characteristics within such a pump, the Reynolds-averaged Navier–Stokes equations and the shear stress transport k-ω turbulence model were applied to numerically compute the pump. The simulation results were compared with experimental data, and good agreement was achieved. The results show that pressure fluctuations in the main flow region are mainly dominated by the blade passing frequency, and the intensity of pressure fluctuations in the near-field area of the tongue reaches its peak value, showing significant fluctuation characteristics. Significant peak signals are captured in the low-frequency band of pressure fluctuations in the clearance region. The pressure fluctuation characteristics are also affected by the rotor–stator interaction between the impeller front shroud and the volute casing, while the dominant frequency is still the blade passing frequency. In addition, the dominant frequencies of pressure fluctuations in the main and clearance flows show a similar distribution to the flow rate, but the minimum amplitude corresponds to different flow rates. Full article

DC link power supply systems that integrate power electronic converters are increasingly being adopted. In particular, emerging “source–load” systems, in which the DC link interfaces with converters, have attracted increasing research interest due to concerns about power quality and system stability. This paper addresses mid- and low-frequency oscillation issues in DC link voltage supplied induction motor drives (IMDs). It begins by constructing a multiple-input multiple-output (MIMO) state-space model of the induction motor. For the first time, the dq-axis control system is represented as an equivalent admittance model that forms two single-input single-output (SISO) loops. The PI controller and induction motor are integrated into the inverter’s input impedance model; Furthermore, the effectiveness and accuracy of the derived impedance model are experimentally validated under various operating conditions of the induction motor using a custom-built test platform. The experimental results offer a practical reference for system enhancement and stability evaluation. Full article