Search Results (5,669)

Tubulin is a heterodimeric protein composed of α- and β-subunits, which polymerize to form the cell’s microtubules. The latter are key components in mitotic spindle formation and essential targets in anticancer therapy. Compounds such as paclitaxel, tubulysins, dolastatins and synthetic analogues of these latter compounds, including cemadotin, exert their cytotoxic effects by disrupting microtubule dynamics. Previously, we reported the production and anticancer activity of a library of cemadotin analogues featuring a C-terminal tertiary amide functionalized with a variety of N-substituents, thus resulting in compounds occurring as a mixture of amide rotamers. Here we describe a comprehensive NMR and conformational study that provides new insights into the effect of the conformational equilibrium on the binding mode of the novel cemadotin analogues to the tubulin target. The conformational behavior of the isomer equilibrium of cemadotin’s terminal amide bond was investigated by TOCSY and ROESY NMR experiments, which allowed the identification and quantification of individual rotamer populations. A slow interconversion between the s-cis and s-trans amide rotamers was observed under standard NMR conditions (25 °C), indicating a significant energy barrier and conformational rigidity. Molecular docking and saturation transfer difference (STD) NMR experiments were performed with a representative analogue and tubulin to assess the binding mode. The results revealed that the s-trans rotamer is the predominant conformer in solution and exhibits a more favorable interaction with tubulin compared to the s-cis isomer, thus helping to understand the conformational requirements for an improved tubulin binding and the inhibition of the polymerization process. Full article

Sub-synchronous oscillations (SSOs) induced by the interaction between doubly fed induction generators (DFIGs) and weak grids pose a critical threat to the grid-connected stability of DFIG-based wind power systems. In this paper, a dual-damping-term compensation filter based on the concept of motion-induced amplification (MIA), together with an optimized design method using a linear quadratic regulator (LQR), is applied to the DFIG system. The effectiveness of the proposed approach in suppressing DFIG shafting oscillations and mitigating grid-connected frequency coupling is verified, and the underlying mechanisms are thoroughly investigated. By establishing a shafting dynamics model for the DFIG and a frequency-coupled oscillation impedance model, this study focuses on revealing the differentiated impacts of the dual damping parameters (${\mathrm{Z}}_{\mathrm{p}}$ and ${\mathrm{Z}}_{\mathrm{q}}$) on system stability under two operating modes: maximum power point tracking (MPPT) and constant power operation. Stability analysis based on the generalized Nyquist criterion (GNC), together with time-domain simulations, demonstrates that coordinated optimization of the dual damping terms can effectively suppress shafting oscillations and frequency coupling, thereby significantly enhancing the grid-connected stability of DFIG systems. Full article

Tracking highly maneuvering, non-cooperative UAVs poses significant challenges due to rapid and unpredictable changes in target dynamics. Under such conditions, traditional single-model filters often fail to maintain reliable state estimates, resulting in degraded tracking performance. Multiple-Model Kalman Filter ( (MMKF) approaches, including the Generalized Pseudo Bayesian (GPB1) and Interacting Multiple-Model (IMM) algorithms, improve robustness by simultaneously considering multiple candidate motion models and weighting them according to the observed target behavior. Adaptive strategies, such as ${\chi }^2$-test-based or t-test-based methods, further enhance performance by dynamically responding to changes in maneuvering patterns. This paper presents a multi-criteriacomparative assessment of four MMKF formulations–GPB1, IMM, ${\chi }^2$-test-based, and t-test-based filters– under a consistent modeling and simulation framework. Particular emphasis is placed on systematically analyzing the role of the transition probability matrix (TPM), investigating how fixed, adaptive, and TPM-free strategies affect estimation accuracy, robustness to noise, and mode-identification performance. Beyond conventional Root Mean Square Error (RMSE) metrics, the filters’ comparison is carried out through confusion matrices and dwell time analysis to highlight performance nuances and trade-offs. This allows to establish which filter formulation is preferable in different operational conditions. Full article

Durable responses to cancer immunotherapy remain restricted to a subset of patients, highlighting persistent gaps in understanding immune failure mechanisms. Dendritic cells (DCs) serve as the critical bridge between antigen recognition and adaptive immune activation, yet conventional molecular models centered on discrete components fail to fully explain heterogeneous therapeutic outcomes. This integrative mechanistic synthesis proposes that DC-mediated antitumor immunity is governed by higher-order structural determinants, including membrane microdomain organization, spatial compartmentalization of signaling, and temporal integration of antigenic and co-stimulatory cues. These features determine whether antigen presentation leads to effective T-cell priming or dysfunctional states such as exhaustion or anergy within the tumor microenvironment. By reanalyzing our validated 2025 experimental pipeline alongside high-impact contextual literature, we identify emergent properties of immune competence that transcend linear molecular interactions. The resulting framework distinguishes structurally mediated failure modes from classical resistance paradigms, providing a coherent non-reductionist explanation for variability in immunotherapy efficacy. Membrane raft repair is positioned as a key promising structural condition for effective immune integration, with direct relevance to translational and regulatory contexts involving non-pharmacodynamic platforms and New Approach Methodologies (NAM)-aligned evaluation strategies. This work proposes an integrative mechanistic framework to guide future hypothesis-driven studies and clinical advancement of DC-based approaches. Full article

Alfalfa mosaic virus (AMV) is a devastating plant pathogen with an extensive host range, yet effective control strategies remain limited. This study investigated the prophylactic efficacy and molecular mechanisms of two plant immune inducers, the Paecilomyces variotii extract DYDS and the antiviral agent Dufulin, against AMV infection in cowpea (Vigna unguiculata). Our results demonstrate that both agents possess potent antiviral activity, with inactivation, protective, and therapeutic efficacies all exceeding 21.00%. Notably, DYDS exhibited superior overall performance. RT-qPCR and immunofluorescence assays confirmed a significant downregulation of AMV coat protein (CP) expression in treated plants. Furthermore, exogenous application of these inducers mitigated chlorophyll loss and markedly augmented the activities of key defense enzymes’ activity, including superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), polyphenol oxidase (PPO), and L-phenylalanine ammonia-lyase (PAL), peaking at 5 days post-inoculation. In silico molecular docking simulations further revealed that DYDS and Dufulin interact spontaneously with the AMV-CP, yielding binding free energies of −6.5 and −5.8 kcal/mol, respectively. Gene expression analysis indicated that these inducers trigger a robust immune response through the integrated activation of the salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) signaling pathways. Collectively, these findings suggest that DYDS and Dufulin provide a dual mode of action—direct viral inhibition and host immune priming—offering a promising and sustainable approach for the management of AMV in leguminous crops. Full article

CFRP laminates are widely adopted for the strengthening of steel structures and the debonding damage poses a severe threat to the integrity of CFRP-reinforced structures. However, as the early stage of debonding damage, kissing bond detection in these structures using the conventional ultrasonic guided waves method is a significant challenge due to the imperceptibility of microscale damage and the complexity of the wave properties at the interface. To address this problem, mixed-frequency ultrasonic guided waves with nonlinear characteristics are proposed to identify and evaluate kissing bond damage with different damage sizes in CFRP-reinforced steel structures. A finite element model is developed to simulate a kissing bond in a CFRP-reinforced steel plate and is utilized to investigate the interaction between mixed-frequency guided waves and the interface. Experimental tests are also carried out to verify the kissing bond detection method. Nonlinear parameters calculated based on the damage-induced sum and difference frequency components are employed to quantitatively evaluate the kissing bond damage. In addition, excitations with different wave modes are used in damage detection to compare their sensitivities to kissing bond damage. Both the simulation and experimental results reveal that the nonlinear parameter rises as the length of the kissing bond increases, reflecting the effectiveness of mixed-frequency ultrasonic guided wave for the identification and evaluation of kissing bond damage in CFRP-bonded structures. Full article

With the sharp increase in winter heating demand in northern China, the carbon emissions of combined heat and power (CHP) units remain high. This paper proposes a low-carbon optimal scheduling model for the system, considering the dynamic carbon-green certificate coupling and the multi-source energy supply of carbon capture and storage (CCS). Firstly, we analyze the thermal and electrical demand characteristics of the installed CCS and optimize its supply mode, and propose the corresponding low-carbon operation strategy for the CHP-CCS unit. Secondly, a dynamic coupling mechanism of carbon-green certificates with the acquisition volume of green certificates and the trading volume of carbon emission rights as the interaction medium should be constructed. The transmission effect of the historical trading volume on the current period should be achieved through dynamic prices, and a low-carbon economic scheduling model with the goal of minimizing operating costs should be established. Again, for the source-load uncertainty, by integrating the entropy weight method and the information gap decision theory, an IES optimization scheduling model based on the information gap decision theory method (IGDT) is established. Finally, through multi-scenario case simulation verification, the results confirmed that the proposed model can effectively improve the economy and low-carbon performance of the system. Full article

The aim of this study was to comparatively evaluate echotextural and hemodynamic changes in the corpus luteum (CL), uterus, and uterine artery, together with serum progesterone (P4) concentrations, using B-mode and Doppler ultrasonography between days 5 and 21 post-insemination in pregnant and non-pregnant cows. Twelve clinically healthy Brown Swiss cows were enrolled and allocated into a cyclic non-inseminated group (n = 6) and an inseminated group (n = 6). Ultrasonographic examinations and progesterone measurements were performed daily during the post-insemination period, and pregnancy was confirmed on day 30. Echotextural parameters (mean gray value and homogeneity) were obtained from the corpus luteum and uterus using B-mode ultrasonography. Doppler ultrasonography was used to assess corpus luteum vascular parameters and uterine artery blood flow, and serum progesterone concentrations were measured at each examination. Corpus luteum mean gray value showed a significant time effect (p < 0.001). For Corpus luteum area and perfusion area, both the time effect and the group × time interaction were significant (p < 0.001), and marked differences between pregnant and non-pregnant cows were observed on days 19, 20, and 21 (p < 0.05). Serum progesterone concentrations also differed significantly between groups on days 20 and 21. In conclusion, changes in corpus luteum area and perfusion area were associated with early pregnancy-related differences and may represent earlier functional ultrasonographic indicators compared with uterine artery Doppler parameters and progesterone concentrations alone. These findings may have practical implications for herd management by potentially enabling differentiation between pregnant and non-pregnant cows approximately 1–2 days earlier than serum progesterone measurements. Full article

The polarization of light is recognized as a key physical quantity in describing light-matter interactions. Polarizers are fabricated to selectively respond to light beams with different polarizations. In practice, the operations of a polarization measuring setup require bulky and expensive terminal photodetectors, e.g., a spectrophotometer, to measure the spectral responses associated with different polarizations. To get rid of the unfavorable reliance on conventional photodetectors, polarizers having a Cu-ZnO junction for efficient hot-electron extraction have been designed to give rise to direct electrical readouts. Detailed photoelectric studies reveal that the designed device excites guided-mode resonances with which the device exhibits polarization-dependent energy depositions in absorbable Cu, leading to distinct electrical responses between transverse electric and transverse magnetic polarizations. The electrical extinction ratio increases from 2.7 to 4.4 when the resonance wavelength increases from 767 nm to 869 nm. Full article

The evaluation of resources and environmental carrying capacity (RECC) is of great significance for achieving harmony between humans and resources and the environment to realize sustainable development. However, current research has not reached a consensus on the research objects, theories, and methods for RECC evaluation. Therefore, this study defined the research object of regional RECC evaluation and designed an evaluation process for regional RECC based on the mutation progression method developed from the mutation theory. Then, the RECCs of 16 cities in Shandong Province during 2013–2022 were calculated, and their temporal and spatial evolution characteristics were analyzed. The result shows that: (1) the research object of regional RECC evaluation is essentially the concentrated reflection of the interaction between resources, the environment, the economy, and society; (2) the process of “construct a multilevel evaluation index system–determine the mutation types of the evaluation index system–standardize the lowest level indexes–evaluate the comprehensive regional RECC” could provide reference for RECC evaluation; and (3) from 2013 to 2022, the RECC in Shandong Province showed a steady increasing trend, and the RECC in eastern and central areas in Shandong Province was relatively higher. By analyzing these results, we found that the natural background conditions, the mode of production and life, and the decisions of the central government are the important factors affecting regional RECCs. Full article

This study investigated the α-glucosidase inhibitory potential of enzymatic/alkaline treatments from Palmaria palmata using different proteases and pairwise combinations thereof. Treatments prepared with Alcalase^®, Flavourzyme^®, and Formea^® Prime, alone or in combination, were evaluated for dose-dependent inhibitory activity. Alcalase^®-derived treatments exhibited the highest α-glucosidase inhibition, achieving an IC₅₀ of 2.48 mg·mL⁻¹, outperforming other treatments and combinations. Membrane fractionation of the Alcalase^®-derived treatment into >5 kDa, 3–5 kDa, 1–3 kDa, and <1 kDa fractions revealed a size-dependent trend, with the <1 kDa fraction showing the strongest inhibition (IC₅₀ of 1.94 mg·mL⁻¹). Three peptides, RADIPFRRA, DGIAEAWLG, and FWSQIFGVAF, from the <1 kDa fraction were identified as potential α-glucosidase inhibitors using the BIOPEP-UWM database and were further selected based on a Peptide Ranker score above 0.6 for in silico docking analyses. Docking revealed distinct binding modes: RADIPFRRA and DGIAEAWLG occupied the catalytic cleft, interacting with key residues (Asp518, Asp616, Trp481, Trp613) consistent with competitive inhibition, whereas FWSQIFGVAF bound to a peripheral site, suggesting potential allosteric modulation. Physicochemical analysis further highlighted differences in charge and isoelectric point correlating with their binding behavior. Together, these findings demonstrate that low-molecular-weight peptides derived from P. palmata proteins, particularly those generated by Alcalase^®, possess significant α-glucosidase inhibitory activity, and provide structural insights for the rational design of peptide-based modulators of carbohydrate metabolism. Full article

To address the significant decline in fracture conductivity after cross-layer fracturing in the L3 sand–mudstone interbedded reservoir of the WZ Oilfield, which restricts efficient development, this study investigates three typical fracture types formed after fracturing: simple fractures in muddy siltstone, simple fractures in mudstone, and complex fractures in muddy siltstone. Based on downhole full-diameter cores, fracture conductivity plates were prepared, and long-term (50 h) conductivity evaluation experiments were conducted under a simulated formation closure pressure of 28 MPa. The interaction modes between fracture surfaces and proppants, as well as the conductivity evolution laws of different fracture types were systematically analyzed. The results indicate that the interaction modes between proppants and fracture walls vary significantly with lithology and fracture morphology. Specifically, proppant embedment dominates in simple muddy siltstone fractures, whereas hydration-induced embedding and wrapping by swelled clay particles dominate in mudstone fractures. The conductivity evolution of simple fractures in muddy siltstone and mudstone follows an exponential decay law, with attenuation amplitudes of 35% and 98% after 50 h, respectively. Complex fractures in muddy siltstone exhibit a staged decay pattern with an attenuation amplitude of 92%, and their long-term conductivity primarily depends on shear-induced self-support. The overall conductivity of cross-layer fractures is controlled by the minimum conductivity among the intersected layers. Under the specific experimental conditions of 28 MPa closure pressure and 30/50 mesh ceramic proppant, the poor long-term conductivity of mudstone simple fractures (only 2% of the initial value) becomes the key bottleneck restricting productivity. This study characterizes the evolutionary features of conductivity evolution of cross-layer fractures in sand–mudstone interbedded reservoirs and provides theoretical support and engineering guidance for optimizing fracturing fluid systems to inhibit hydration and refining stage isolation strategies in similar reservoirs. Full article

Agentic AI is increasingly framed as enabling consumers to delegate commerce decisions and actions to digital assistants, yet consumer-facing evidence still centers on assistive chatbots and recommender-like systems, with scarce evaluation of execution-level delegation. This study provides an evidence-mapping review of empirical work on agentic commerce and synthesizes determinants and outcomes of delegation across three questions: (RQ1) how systems are operationalized (autonomy, task scope, interaction mode, and transaction capability/evidence realism), (RQ2) what facilitates or inhibits delegation, and (RQ3) what downstream outcomes follow for marketing performance and consumer experience. We searched Scopus and Web of Science for English-language, peer-reviewed primary studies (2015–2026) and applied conservative coding rules that distinguish claimed capability from simulated or demonstrated execution. The mapped literature is concentrated in text-based, low-autonomy assistants focused on recommendation and post-purchase support; coverage drops sharply for workflow-level autonomy, cart building, checkout/payment execution, and negotiation. Across studies, findings cluster into two motifs: a utility/assurance pathway in which performance cues and interaction quality increase perceived usefulness, satisfaction, and trust, and a governance pathway in which autonomy cues and system-initiated control trigger reactance/powerlessness and reduce acceptance unless mitigated by safeguards; urgency can attenuate governance resistance. Because most outcomes are intention- or vignette-based, calibration, verification, and error-recovery behaviors remain under-measured. Overall, delegation appears to depend less on maximizing autonomy than on coupling capability with user governance (consent, oversight, recourse, accountability), and we outline measurement priorities for evaluating execution-capable agents. Full article

In this paper, we propose a distributed admittance control framework for joint manipulation of objects by multiple robotic arms that addresses the challenges of human–robot interaction. The system is developed to control the joint transportation of an object by N Franka Emika Panda robots (validated with up to four in simulations) using external human force estimation in a distributed manner without relying on centralized computation or force sensors. We integrate a hybrid observer by combining a distributed force estimator with a nonlinear disturbance observer (NDOB) to achieve accurate human force estimation and minimize estimation errors in simulations. Adaptive radial basis function neural networks (RBFNNs) are employed to dynamically adjust the damping and inertia parameters, enhancing the system’s adaptability and stability. Event-based communication minimizes network bandwidth usage, while consensus protocols ensure synchronization of state estimates across robots. Unlike conventional methods, the proposed observer operates in a fully sensorless manner: no human-force measurements are required. The estimation relies solely on locally available robot states, maintaining high accuracy while reducing system complexity. The framework demonstrates scalability to multiple robots, enhancing robustness in distributed settings. Simulation results show superior performance in terms of path tracking, force estimation accuracy, and communication efficiency compared to centralized approaches. Specifically, the event-triggered strategy reduces communication messages by approximately 70% compared to always-connected mode while maintaining comparable RMSE in position $(9.97\times {10}^{-5}$ vs. $7.39\times {10}^{-5}$) and velocity $(2.52\times {10}^{-5}$ vs. $3.76\times {10}^{-5})$, outperforming periodic communication. Full article

Corrosion damage is a vital factor that causes strength weakening or even failure of offshore derrick. To study the influence of local corrosion on the derrick, a regular spherical pitting model was adopted to analyze the evolution mode of pitting corrosion damage and the corresponding pitting corrosion damage models with different morphology. The connection technique for the across-scale interface was discussed, a method for constructing multi-scale models of derrick with pitting corrosion damage was proposed. The pitting damage simulation and ultimate bearing capacity analysis are carried out for an offshore derrick in service. The results show that the interaction between meso-scale pitting corrosion damage and macro-scale structure can be effectively considered, the stress distribution of the pitting corrosion damage and its effect on stress concentration coefficient can be obtained, and the influence of local random pitting distribution location, style, and density on the ultimate bearing capacity can be determined. In addition, the ultimate bearing capacity can be predicted. It provides a new idea for bearing capacity prediction and safety assessment of large steel frame structures in service with local damage. Full article