Search Results (2,956)

To address three critical challenges in traditional digital twin applications for smart manufacturing—static mirroring, localized optimization, and economic decoupling—we propose and validate a novel paradigm: the Twin-Data Mid-End (TDME) system driven by dual technological-economic mechanisms. By integrating real-time big data from production lines, equipment, supply chains, and market terminals through unified semantic frameworks, microservices-based technical modules, and deep reinforcement learning decision engines, this system generates instant reward signals based on multi-dimensional economic metrics including marginal profits, delivery cycles, and inventory turnover. This enables seamless “hot-swappable” reconfiguration of process algorithms, equipment controls, scheduling strategies, and organizational structures without production interruption. The system concurrently facilitates technological iteration and economic restructuring while dynamically optimizing efficiency-profit Pareto frontiers. Objective validation across 12 months of closed-loop industrial trials demonstrates reduced line changeover time by 37%, decreased unit comprehensive costs by 14.6%, shortened market response cycles by 42%, and increased return on investment by 11%, highlighting the paradigm’s practical applicability and broad adaptability. Full article

DNA nanotechnology offers an unprecedented level of structural programmability for organizing metallic nanoparticles into precisely defined architectures, providing a powerful platform for plasmonic biosensing. In particular, gold and silver nanoparticles assembled on DNA nanostructures enable nanometer-scale control over interparticle distance, orientation, and spatial symmetry, which directly govern collective plasmonic behaviors and optical signal transduction. This review summarizes recent advances in DNA nanostructure-mediated assembly of metal nanoparticles, with an emphasis on design principles and assembly strategies that enable static and dynamic control of nanoparticle organization. Representative examples are discussed to illustrate how well-defined plasmonic assemblies give rise to tunable optical responses, including localized surface plasmon resonance modulation, chiroptical signals, fluorescence enhancement or quenching, and surface-enhanced Raman scattering. The role of structural programmability and stimulus-responsive reconfiguration in translating molecular recognition events into amplified optical outputs is highlighted in the context of biosensing. Finally, current challenges and future perspectives are outlined, focusing on structural robustness, signal reproducibility, and integration toward practical and multiplexed biosensing platforms. Full article

To investigate the effects of repeated drying and wetting on the mechanical properties and meso-fabric of metal tailings, lead-zinc tailings from Hunan Province were studied. A self-developed apparatus was used to simulate the cyclic drying-wetting processes. Combined with triaxial shear tests and stereomicroscopic image analysis, the changes in macroscopic mechanical properties and meso-fabric, as well as their correlation mechanisms, were investigated. The results indicate that the wet-dry cycles did not alter the strain-softening characteristics of the tailings’ stress-strain curves; however, they significantly intensified the degree of softening during the later stages of cycling (4–6 cycles). The static strength exhibited a trend characterized by “initial gradual degradation → temporary recovery → further deterioration” with an increasing number of cycles. After six cycles, the strength was significantly reduced compared to the initial state. The effective cohesion (c′) fluctuated markedly, with an amplitude of 31.1%, while the variation in the effective internal friction angle (φ′) was only 6.02%, indicating that dry-wet cycles have a more pronounced effect on the cohesion of tailings. At the microscopic level, the dry-wet cycling process promoted the upward migration of fine particles ranging from 0 to 60 µm, resulting in a decrease in the proportion of smaller particles in the lower layer. The porosity increased overall, with the lower layer rising from 44.06% to 54.26%. Pore evolution was dominated by the enlargement of pores larger than 150 µm. The macro-meso correlation analysis revealed that “fine particle migration → expansion of pores → loss of cementitious material” was the core driving factor for the deterioration of macroscopic mechanics, and the macroscopic mechanical response was the external manifestation of the adjustment of the microscopic structure. This research can provide certain theoretical support for the long-term safe operation and stability improvement of tailings dams. Full article

CO₂ flooding is an effective technique for enhancing oil recovery in low-permeability reservoirs. However, it is often hindered by severe CO₂ channeling. This challenge is particularly pronounced in near-wellbore regions with large pressure differentials and in fractured reservoirs, where high CO₂ injection rates and rapid breakthrough require channel blocking systems with high mechanical strength and excellent CO₂-resistant performance. In this work, a smart responsive polymer was synthesized and subsequently crosslinked with a highly active phenolic resin crosslinking agent to develop a smart responsive polymer gel channel blocking system. The resulting gel exhibits CO₂-responsive strength enhancement and excellent CO₂-resistant performance. The static and dynamic gelation behaviors, nonlinear rheological properties, CO₂-resistant performance, channel blocking, and enhanced oil recovery performance of the smart responsive polymer gel were systematically investigated. The results demonstrate that the polymer gel maintains good structural stability during dynamic transport in the reservoir and does not undergo significant strength degradation under shear conditions. Moreover, the smart responsive polymer gel exhibits excellent CO₂-resistant performance within a temperature range of 80–110 °C, salinity up to 10 × 10⁴ mg/L, and pressure up to 20 MPa. Moreover, the system shows a significant enhancement in channel blocking and enhanced oil recovery performance, highlighting its promising potential for effective CO₂ flooding channel blocking in low-permeability reservoirs. Full article

This study investigates the physical and cyber-physical resilience of smart grids with a high share of renewable energy sources (RESs) dominated by permanent magnet synchronous generators (PMSGs). The originality of this work lies in the development and unified evaluation of five integrated control strategies, the PLL with grid following, VSG with grid shaping, VSG+BESS, VSG+STATCOM, and VSG+BESS+STATCOM, implemented within a coherent simulation framework based on Python. Unlike previous works that analyze these methods in isolation, this study provides a comprehensive quantitative comparison of their dynamic characteristics, including frequency root mean square deviation, maximum deviation, and composite resilience index (RI). To extend the analysis beyond static conditions, a multi-generator (multi-PMSG) scenario with heterogeneous inertia constants and variable load profiles is introduced. This dynamic model allows the evaluation of natural inertia diversity and the effects of inter-generator coupling compared to the synthetic inertia emulation provided by VSG-based control. The combined VSG+BESS+STATCOM configuration achieves the highest synthetic resilience, improving frequency and voltage stability by up to 15%, while the multi-PMSG system demonstrates comparable or even higher RI values due to its inherent mechanical inertia and decentralized response behavior. In addition, a cyber-physical scenario is included to evaluate the effect of communication delays and false data injection (FDI) on VSG frequency control. The results show that a communication delay of 50 ms reduces RI by approximately 0.2%, confirming that even minor cyber disturbances can affect synchronization and transient recovery. However, hybrid control architectures with local energy buffering (BESS) show superior resilience under such conditions. The main technical contribution of this work is the establishment of an integrated analytical and simulation framework that enables the joint assessment of synthetic, natural, and cyber-physical resilience in converter-dominated smart grids. This framework provides a unified basis for the analysis of dynamic stability, hybrid control interaction, and the impact of cyber uncertainty, thereby supporting the design of low-inertia, resilient, and secure next-generation power systems. Full article

This study examines the mechanical response of medium-manganese TRIP steels under different stress states, focusing on deformation-induced austenite-to-martensite transformation and ageing phenomena. Two steels with distinctly different ferrite–austenite morphologies and retained austenite (RA) fractions were analysed: a globular microstructure with 18% RA and a lamellar microstructure with 14% RA, produced by single (SA) and double annealing (DA), respectively. Continuous and interrupted tests were performed under in-plane shear, uniaxial tension, and plane strain stress states. Strain fields were analysed using high-resolution digital image correlation, while RA fractions were quantified as a function of strain by ex situ X-ray diffraction. The results demonstrate a pronounced stress-state dependence. SA samples exhibit discontinuous yielding, with uniaxial tests showing clear Lüders band formation. Both steels exhibit dynamic strain ageing manifested by Portevin–Le Chatelier (PLC) serrations and associated strain bands, which are most pronounced under uniaxial tension, weaker in plane strain, and barely detectable in in-plane shear. Static strain ageing is also evidenced by a strengthened yield response upon unloading–reloading in all samples. The SA globular microstructure exhibits higher PLC band inclination angles than the lamellar DA microstructure, consistent with its more pronounced anisotropy. The propagation velocity in uniaxial tensile samples decreases with increasing strain following the work-hardening response. For both steels, the austenite-to-martensite transformation rate is highest in uniaxial tension, slightly reduced in plane strain, and strongly suppressed under in-plane shear. A Beese–Mohr/Johnson–Mehl–Avrami–Kolmogorov formulation incorporating stress triaxiality and Lode angle captures these trends for both steels. For the stress states considered, the DA condition exhibits a consistently higher transformation rate than the SA condition, accompanied by a higher work-hardening rate. These findings highlight the coupled role of stress state and microstructural morphology in governing localisation behaviour and strain-induced transformation in medium-manganese steels. Full article

4D printing, as an advanced evolution of 3D bioprinting, introduces time as an active design dimension, enabling printed constructs to undergo programmed morphological or functional transformations in response to external or endogenous stimuli. By integrating stimuli-responsive smart materials with precise additive manufacturing, 4D printing provides a bio-inspired strategy to overcome the inherent limitations of static scaffolds and to achieve spatiotemporal dynamic matching with the evolving biological microenvironment during tissue regeneration. Over the past decade, significant progress has been made in applying 4D printing to structurally and functionally complex tissues, including bone, muscle, vasculature, nerve repair, wound closure, and other emerging biomedical scenarios. Rather than emphasizing shape change alone, recent advances demonstrate that 4D-printed constructs can emulate key biological processes such as morphogenesis, contraction, directional guidance, electrophysiological signaling, and microenvironment-responsive regulation, thereby enhancing tissue integration and functional recovery. This review systematically summarizes materials, stimulus–response mechanisms, and representative applications of 4D printing from a bio-inspired perspective, while critically discussing current challenges related to material performance, mechanistic understanding, manufacturing precision, and clinical translation. Finally, future perspectives are outlined, highlighting the importance of interdisciplinary integration, intelligent manufacturing, and clinically oriented evaluation frameworks to advance 4D printing toward personalized and precision regenerative medicine. Full article

During jacking construction of prefabricated utility tunnels, asynchronous jack output and interface friction may induce internal force redistribution and deformation amplification at the leading end. Taking a triple-cell prefabricated utility tunnel in Xiong’an New Area as a case study, a three-dimensional finite element model was established considering inter-segment contact, equivalent bolted connections, and bottom-slab-bedding friction. Jack asynchrony was idealized as a quasi-static thrust imbalance, and a synchronous case, asynchronous cases with thrust differences of 5–30%, and varying friction coefficients were analyzed. For the 30% thrust-difference condition, structural responses were examined at both the gasket-compression stage and the maximum jacking-force stage. The results show that jacking loads attenuate along the tunnel length in a staged manner, with the leading end acting as the primary load-transfer zone. Increasing thrust imbalance drives the response from axial compression toward eccentric compression-bending, accompanied by monotonic increases in principal stresses and vertical displacement. Higher friction further amplifies the leading-end response; nevertheless, for the investigated configuration, stresses and deformations under a 30% thrust imbalance remain within engineeringly acceptable limits. The findings provide a basis for identifying critical leading-end locations, arranging monitoring schemes, and supporting construction control under asynchronous jacking. Full article

While deep fertilization improves crop yields and fertilizer use efficiency, it alters crop growth and soil nutrient/moisture distribution, driving nitrous oxide (N₂O) emissions—a potent greenhouse gas. However, conflicting evidence and the unknown effects of varying fertilizer placement depths in mechanized rapeseed fields leave the critical trade-off between productivity and emissions mitigation poorly understood. A 2-year field experiment (2019–2021) was conducted in the Yangtze River basin, China. The static closed chamber technique combined with gas chromatography was utilized to investigate the impacts of fertilizer placement depths (5 cm, 10 cm, and 15 cm, designated as D5, D10, and D15, respectively) on soil N₂O emissions, with a no-fertilization treatment serving as the control. Results demonstrated that N₂O fluxes under all treatments exhibited a rapid decline during the early growth stages of rapeseed, subsequently stabilizing at low levels; these dynamics were partially linked to soil temperature and soil water content (SWC). Specifically, N₂O flux showed a significant but moderate exponential response to soil temperature and a weak quadratic trend with SWC. As fertilization depth increased, the richness and diversity of AOA, AOB, and nirK communities showed a numerical decline (p > 0.05). N₂O emissions under D5 were on average 8.7% higher than D10 (p > 0.05), but were significantly 18.0% higher than D15 (p < 0.05). Yield-scaled N₂O emissions under D10 were reduced by 12.7% and 22.3% relative to D5 and D15, respectively. Compared with D10 and D15, the N₂O emission factor increased by 12.9% and 29.0% under D5, respectively (p < 0.05). The net ecosystem economic budget under D10 was 6.5% and 48.6% greater than that of D5 and D15, respectively. Considering crop yield, production costs, and carbon emission, a fertilizer placement depth of 10 cm is recommended as optimal. These findings offer valuable insights for mitigating N₂O emissions and informing rational fertilization strategies in rapeseed cultivation. Full article

Underwater optical wireless communication (UOWC) systems are significantly challenged by turbulence-induced signal degradation in dynamic channel conditions. This paper presents a novel framework that integrates Long Short-Term Memory (LSTM) networks with the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to enable real-time turbulence prediction and multi-objective adaptive optimization of transmission parameters, including power, modulation scheme, and beam divergence. Experimental results demonstrate that the proposed LSTM–NSGA-II framework achieves a 45% reduction in bit error rate (BER) and a 36% improvement in energy efficiency compared to conventional static systems, while maintaining a signal-to-noise ratio (SNR) prediction accuracy of 94.7% and an adaptive response latency of 28.6 ms. Validation using field data from the Marine Institute in the Baltic Sea confirms the framework’s practical applicability and robustness, highlighting its potential to enhance autonomous and military underwater operations in turbulent environments. This work represents a significant step toward more reliable and efficient UOWC systems. Full article

This study investigates the seismic response of double- and triple-buried steel pipeline systems using finite-element modeling in RS2, with particular emphasis on soil–pipeline interaction and symmetry-breaking behavior under pseudo-static seismic loading. Although the pipeline systems are initially symmetric in geometry, material properties, and boundary conditions, the analysis demonstrates that directional seismic excitation induces quantitatively measurable asymmetric responses in shear force, displacement, and spacing due to nonlinear soil–pipeline interaction. Five parametric scenarios were examined, including burial depth (1–5 m), pipeline diameter (8–56 in.), groundwater table (1.4–20 m), peak ground acceleration (0.1–0.6 g), and soil type. The results show that maximum shear forces increase with burial depth and diameter, reaching approximately 15–17 kN in clayey soils at a PGA of 0.4 g, whereas sandy and heterogeneous soils produce lower shear forces (≈12–14 kN). Horizontal displacements are strongly governed by groundwater and PGA, increasing from about 1.2–1.8 m in dry or deep groundwater conditions to more than 2.8 m for shallow groundwater and exceeding 5 m at PGA = 0.6 g. Triple-pipeline systems exhibit higher shear demand due to confinement effects, with the middle pipeline often developing the largest shear force, while the pipeline facing the seismic load consistently experiences the greatest displacement. This study makes two primary contributions. First, it demonstrates that initially symmetric multilined buried pipeline systems exhibit systematic, quantifiable symmetry-breaking behavior under directional seismic loading, manifested as unequal shear forces, displacements, and interaction effects among adjacent pipelines. Second, it presents an integrated multi-parameter coupling analysis that simultaneously accounts for burial depth, pipeline diameter, groundwater level, soil type, and peak ground acceleration, revealing interaction mechanisms that cannot be captured through single-parameter or single-pipeline assessments. Full article

Tetra-missing rib honeycombs (TMRHs), characterized by monoclinic geometry, exhibit high elastic stiffness but suffer from poor deformation stability and reduced axial load-bearing capacity, which limit their applicability in energy-absorbing and load-sensitive engineering structures. To address these inherent drawbacks, this study proposes two symmetry-enhanced tetra-missing rib honeycomb configurations through overall axisymmetric design and subunit-level symmetric optimization. A finite element model was established in Abaqus/Explicit and validated against quasi-static compression experiments, demonstrating good agreement in deformation modes and mechanical responses. Systematic numerical investigations were then conducted to compare the mechanical properties and deformation behaviors of three honeycomb layouts, including the conventional TMRH and the proposed symmetric designs. Furthermore, the effects of impact velocity on mechanical performance were examined to evaluate the dynamic response characteristics of the structures. Finally, the influence of subunit angle parameters on the stiffness, energy absorption, and deformation stability of the tetra-missing rib honeycombs was comprehensively analyzed. The results provide insight into the role of symmetry and geometric parameters in improving the mechanical performance of TMRH-based structures and offer guidance for the design of high-performance auxetic honeycombs. Full article

Urban heat not only affects thermal comfort but also constrains the sustainable development of cities, underscoring the necessity of understanding the temporal response of land surface temperature (LST) to urban characteristics over time. Most existing studies rely on single-overpass satellite observations or daily averages, failing to capture continuous diurnal variability and the time-dependent influence of different drivers. In this study, we reconstructed seasonal hourly LST series for Beijing using an improved diurnal temperature cycle (DTC) model (${\mathrm{GEM}}_{\eta }$) based on MODIS data, and employed a random forest framework to quantify the relative contributions of natural, urban morphological, and anthropogenic factors throughout the diurnal cycle. Unlike previous studies that rely on traditional DTC models and machine learning for largely static or single-scale assessments, our research provides a unified, time-explicit comparison of LST driver dominance across seasons, hourly diurnal cycles, and urban–rural contexts. The results indicate that persistent urban heat island (UHI) effects occur in all seasons, with the maximum intensity reaching approximately 5.0 °C in summer. Generally, natural factors exert a cooling influence, whereas urban morphology and human activities contribute to warming. More importantly, the dominant drivers show strong temporal dependence: a nature-dominated regime prevails in summer, where vegetation exerts an overwhelming cooling effect. Conversely, during transition seasons and winter, LST variability is governed by a mixed-driven mechanism characterized by an hourly-resolved diurnal handoff, in which the dominant contributors shift hour by hour between surface physical properties and anthropogenic proxies. Our findings challenge the static view of urban heat drivers and provide quantitative evidence for developing time-sensitive and seasonally adaptive mitigation strategies, thereby supporting sustainable urban planning and enhancing climate resilience in megacities. Full article

This study examines the longitudinal evolution of media framing of TikTok in South Korean news coverage from 2020 to 2024. As a global digital platform increasingly embedded in geopolitical and regulatory controversies, TikTok provides an instructive case for understanding how media frames shift over time in response to external political pressures. Moving beyond static framing analyses and Western-centric perspectives, this study conceptualizes framing as a dynamic process shaped by both short-term events and longer-term structural change. Using 5660 TikTok-related news articles from the BIGKinds database, we apply large language model-assisted frame classification and construct a frame shift index (FSI) to measure temporal changes in dominant frames. Interrupted time series (ITS) analysis is employed to test short-term framing responses to discrete international political and policy events, while the Bai–Perron breakpoint test (BPT) is used to identify long-term structural breaks. The results show that significant frame shifts are closely associated with transnational policy disputes and international political conflicts. While ITS reveals clear event-driven short-term framing adjustments, BPT identifies a statistically significant structural breakpoint in late 2022, indicating a longer-term reorganization of media narratives under sustained geopolitical and regulatory pressures. Full article

Resilience is commonly framed as a psychological trait, yet clinical and experimental evidence demonstrates that resilience failures emerge concurrently across metabolic, endocrine, immune, and cognitive domains. This review examines resilience as a bioenergetic property constrained by how organisms allocate finite metabolic resources under stress. We synthesize evidence from endocrinology, mitochondrial biology, immunometabolism, and stress physiology to propose a parsimonious, hypothesis-driven Energy Allocation System (EAS) in which the hypothalamic-pituitary-adrenal (HPA), thyroid (HPT), and gonadal (HPG) axes are conceptualized as a coordinated energy-governance network. Despite extensive investigation within these individual fields, the literature lacks an integrative physiological framework explaining why multisystem stress responses co-occur in predictable endocrine and metabolic patterns. Within this framework, mitochondrial reserve capacity serves as the limiting substrate through which hormonal signals regulate mobilization, metabolic pacing, immune tolerance, and recovery. The reviewed literature supports predictable patterns of endocrine reorganization during energetic strain, including prioritization of glucocorticoid-mediated mobilization, constrained thyroid hormone activation, suppression of long-term anabolic investment, and impaired recovery following stress. These configurations reflect adaptive energy-conserving strategies rather than isolated organ dysfunction. The novelty of this review lies in organizing established biological mechanisms into a unified, energy-allocation-based framework that generates falsifiable predictions linking endocrine coordination to bioenergetic capacity and recovery dynamics. We further discuss how routinely available biomarkers and validated psychometric measures can be interpreted as functional readouts of energetic allocation rather than static disease markers. Framing resilience through coordinated energy governance offers a unifying mechanistic lens for interpreting multisystem stress responses and generates testable predictions for future experimental and clinical investigation. Full article