Search Results (8,846)

Pneumatic soft actuators have been drawing considerable attention in the field of soft robotics, thanks to their inherent flexibility, high power density, and safe interaction. However, the strong, intricate coupling between the material’s hyperelastic behavior and the reinforcement of anisotropic fibers creates significant challenges for both analytical modeling and numerical characterization of these actuators. In this paper, we design and fabricate a fiber-reinforced pneumatic soft actuator using Ecoflex 00-30 silicone rubber as the base material and helically wound fibers as the reinforcing layer. We set up a theoretical framework that combines the Neo-Hookean model for isotropic silicone rubber with a strain energy-based formulation for anisotropic wound fibers. This framework describes how the actuator is stretched, expanded, twisted, and bent. Finite element simulations are then carried out, focusing on three key design parameters: winding fiber density (three levels: high, medium, low), air cavity offset distance from the central axis (1, 2, 3, and 4 mm), and air cavity cross-sectional geometry (cube vs. cylindrical). The simulations reveal that a higher winding fiber density promotes more uniform stress distribution across both the strain and confinement layers. In contrast, a low fiber density can lead to local bulging and large stress variations, which ultimately compromises the bending performance. The offset distance of the air cavity from the neutral axis is directly linked to the bending curvature: a larger offset produces greater air cavity deformation and higher actuation efficiency. Furthermore, the cuboid air cavity yields a larger bending angle (experimentally validated up to 90° at 0.045 MPa) and better efficiency, while the cylindrical air cavity distributes stress more evenly across the outer surface of the strain layer and reduces stress concentration at the edges. These findings provide useful quantitative guidance for optimizing the structure of fiber-reinforced soft actuators and establish a framework for hybrid analytical–numerical prediction of their mechanical behavior. Full article

Prediction of 2 m temperature during extreme cold events remains challenging because it is obtained diagnostically from near-surface atmospheric states and depends on various physical parameterization processes, thereby introducing multiple sources of forecast uncertainty. Our previous study has demonstrated that the Combined Nonlinear Forcing Singular Vectors (C-NFSVs) based ensemble forecasts can effectively characterize forecast uncertainty and recognize the dominant sources. However, the specific dynamical and physical parameterization processes associated with model-related forecast uncertainty remain unclear. In this study, we investigate the sensitivity of model-related 2 m temperature forecast uncertainty within the Weather Research and Forecasting (WRF) model to different dynamical and physical parameterization processes during extreme cold events over southern China. Based on the good reliability of C-NFSVs-based ensemble forecasts, the sensitivities of different temperature tendency terms to model perturbations were diagnosed by comparing the ensemble spreads from experiments using full C-NFSVs and those using only the initial component of C-NFSVs. The results indicate that, for the extreme cold events examined over southern China, the vertical advection and Planetary boundary layer (PBL) parameterization terms in the WRF model exhibit the strongest sensitivities to model perturbations, suggesting their close association with model-related 2 m temperature forecast uncertainty. This sensitivity may be associated with the roles of these processes in regulating the vertical redistribution of heat and the evolution of lower-tropospheric thermal structures. These findings provide new insights into the processes associated with model-related forecast uncertainty of 2 m temperature. Furthermore, they highlight the need for further investigations of vertical advection and PBL-related processes in the WRF model. Such investigations are expected to improve the understanding of their roles in forecast uncertainty and evaluate their potential implications for improving 2 m temperature forecasts during extreme cold events. Full article

The thermal performance of multilayer building wall systems under variable outdoor temperature conditions is an important factor in evaluating building energy efficiency and indoor thermal comfort. This study presents a simplified analytical formulation based on the classical transient heat conduction theory together with a numerical model based on the finite difference method (FDM) implemented in the MATLAB R2026a (Update 5) environment. The analysis includes five types of multilayer wall systems with different structural compositions and thermal masses, combined with three thermal insulation materials (expanded polystyrene (EPS), mineral wool, and aerogel) and various insulation thicknesses, resulting in a total of 55 wall assembly configurations. The investigated wall systems are evaluated using the thermal transmittance coefficient (U-value), decrement factor, time lag, maximum heat flux, and the temporal variation in the interior wall surface temperature. The results demonstrated that the dynamic thermal behavior of multilayer wall systems depends on the combined effects of the thermal mass of the load-bearing layer, the type and thickness of the thermal insulation, and the thermophysical properties of the constituent materials. The comparison between the analytical formulation and the MATLAB simulations demonstrates consistent trends in the predicted thermal behavior of the investigated wall systems, supporting the applicability of the proposed analytical–numerical approach for the preliminary assessment of the thermal performance of multilayer building wall systems. Full article

Firmware forms the persistent software layer controlling embedded and Internet-of-Things (IoT) devices, industrial controllers, automotive systems, and cyber-physical infrastructure. Vulnerabilities in firmware enable remote compromise, supply-chain attacks, and long-lived implants that survive operating-system reinstallation. This review synthesises 118 works published from 2014 to 2026—comprising 78 primary research studies; 23 surveys and systematisations of knowledge; and 17 benchmarks, tools, and background references—covering the full firmware reverse engineering (FRE) pipeline: physical acquisition (including fault injection and side-channel extraction), format analysis and unpacking, static analysis (binary code similarity detection, protocol reverse engineering, and patch diffing), dynamic analysis and hardware emulation, fuzzing-based vulnerability discovery, and artificial intelligence (AI) and large language model (LLM)-assisted analysis. Three additional dimensions are surveyed: digital twin-assisted firmware security testing; secure boot, trusted execution environment (TEE), and over-the-air (OTA) update security; and firmware rootkit and implant detection. Coverage spans two axes—the firmware class (Linux-based IoT, microcontroller-unit bare-metal, RTOS, UEFI/BIOS, PLC/ICS, and automotive ECU) and analysis depth (surface scanning to exploit-validated vulnerability chains). We identify ten structural gaps, including the absence of unified evaluation benchmarks, fragmented peripheral modelling, the scalability–fidelity trade-off in re-hosting, and insufficient grounding of LLM tools in firmware-specific realities. We conclude with six research directions for trustworthy, scalable, and infrastructure-aware firmware analysis. Full article

Accurately simulating convective initiation (CI) in capped High Plains dryline environments remains a significant challenge for convection-permitting numerical weather prediction. As a follow-up work to Lu and White, this study utilizes the Model for Prediction Across Scales (MPAS) at a 3 km grid resolution to evaluate the sensitivity of dryline morphology and CI to two planetary boundary layer (PBL) parameterization schemes: the non-local Yonsei University (YSU) and the local Mellor-Yamada-Nakanishi-Niino (MYNN) frameworks. Radar observations and simulated maximum reflectivity show that while the YSU scheme successfully replicates the timing and spatial development of convective cores triggered along the elevated terrain slope at 21:30 UTC, the MYNN scheme completely suppresses deep convection throughout the study period. Vertical thermodynamic profiles indicate that YSU establishes a deeply mixed boundary layer that weakens the regional capping inversion, enabling surface parcels to break the stable lid and reach their level of free convection (LFC). Conversely, the MYNN scheme confines moisture to a thin layer near the surface beneath an unyielding temperature inversion, preventing parcels from achieving free buoyancy. For the 3 km “grey zone” of turbulence resolution, both PBL schemes successfully resolve horizontal convective rolls (HCRs) near the primary dryline boundary. YSU’s non-local mixing permits these HCR perturbations to couple vertically into deep, cap-breaching updraft plumes, while MYNN’s local turbulent kinetic energy (TKE) closure traps them as shallow horizontal waves. It was shown that the MYNN failure is driven by an intrusive synoptic wind bias, generating anomaly wind velocities of 24–28 m/s throughout the column. These winds act as a mechanical sweeper across the terrain slope which shears, flattens, and dilutes the moisture pool below 2000 m Mean Sea Level (MSL) and physically reduces fuel from the western initiation zone. In contrast, the YSU scheme maintains a well-regulated, moderate wind profile (8–12 m/s aloft), preserving a state of mesoscale equilibrium that allows moisture to ascend the terrain slope and continuously feed developing convective cells. Our findings demonstrate that the choice of PBL parameterization plays significant role in not only local vertical mixing but also the structural translation of macroscale synoptic forcing versus localized thermodynamic regulation in complex terrain. Full article

The three-dimensional (3D) documentation of the Similaun mummy (Ötzi the Iceman) and the associated Copper Age equipment and clothing presents unique challenges due to diverse material properties and strict conservation constraints. This study presents a comprehensive digital preservation workflow, primarily utilizing Structure from Motion (SfM) close-range photogrammetry (a method that reconstructs precise 3D geometry from overlapping 2D digital photographs), integrated with Image-Based Modeling (IBM) and Neural Radiance Field (NeRF) algorithms (a machine learning approach that models a complex scene as a continuous volumetric function method). To overcome the non-Lambertian properties of the mummy’s protective ice layer and wet skin (surfaces that reflect light specularly rather than diffusely, creating glares that can disorient standard reconstruction algorithms), a specialized Polarized Light Photography (PLP) strategy was implemented using custom-built hardware. This integration required advanced anatomical segmentation to resolve postural discrepancies caused by taphonomic processes. The resulting web-based application provides the scientific community with a metrically accurate digital twin, featuring interactive tools for cross-sectioning and X-ray visualization. By adopting a Free/Libre and Open-Source Software (FLOSS) ecosystem, this project establishes a sustainable, modular framework for future forensic investigations and diachronic monitoring, ensuring the long-term digital life of one of the world’s most significant archaeological finds. Full article

Antiretroviral therapy (ART) is essential for controlling human immunodeficiency virus (HIV) infection, requiring strict daily adherence for lifelong viral suppression. However, this continuous oral dosing results in persistent exposure of the gastrointestinal tract (GIT), raising the need to investigate the effects of TC-ART (Tri-combination Abacavir, Dolutegravir, Lamivudine–ART) on epithelial integrity, barrier recovery mechanisms, and surface barrier architecture. TC-ART exposure (125 µM to 4000 µM) showed marked alterations in transepithelial resistance, permeability, and wound-healing abilities even at sub-cytotoxic doses. The dose exposure range at the mid-dose level showed the highest transcriptional activity, characterized by a downregulation of junctional genes [claudins (CLDNs), desmoglein’s (DSGs), and junctional plakoglobin (JUP)] and signaling mediators [the signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase 1 and 3 (MAPK1/3), and catenin beta 1 (CTNNB1)], along with reduced IL-9 expression that is linked to mucin loss. These transcriptional changes were consistent with structural findings, including partial transepithelial electrical resistance (TEER) recovery followed by a decline, delayed wound closure, and waning of the apical mucin layer in a dose-dependent manner. However, several cytokines, like IL-2 and IL-6, showed increased secretion despite lower transcriptional levels, suggesting alternative regulatory control during early stress responses. Together, these results support that TC-ART exposure alters epithelial responses in a way that may transition from early adaptation to signs of impaired recovery, leading to a gradual decline in mucosal barrier function. Such concentration- and time-dependent epithelial stress may contribute to gastrointestinal disturbances observed in treated HIV populations, emphasizing the need for incorporating intestinal epithelial health endpoints in drug safety evaluations. Full article

β-1,6-Glucan is a functionally crucial polysaccharide of the fungal cell wall, although typically less abundant than β-1,3-glucan and chitin, its content, chain length, and branching vary considerably among species. Structurally, it serves as a covalent cross-linker tethering the external mannoprotein layer to the internal β-1,3-glucan-chitin network, contributing to cell wall integrity and plasticity. Biosynthetically, unlike chitin and β-1,3-glucan, which are synthesized by the plasma membrane-associated synthases, β-1,6-glucan biosynthesis depends on a multi-protein cooperative network spanning the endoplasmic reticulum (ER), Golgi, and cell surface, whose core catalytic machinery remains incompletely defined. Genetic and in vitro reconstitution studies have begun to delineate the contributions of ER-resident proteins (Kre5, Big1, Cwh41/Gls1, Rot2/Gls2, and Cne1), Golgi-localized Kre6/Skn1 family members, and cell-surface components (Kre9, Knh1, Kre1, and Kre11). Functionally, its biological roles are established by two complementary lines of evidence, namely enzymatic digestion by endogenous or exogenous β-1,6-glucanases and inactivation of the biosynthetic machinery. Collectively, these studies show that β-1,6-glucan is essential for cell wall architecture, GPI-anchored protein localization, fungal growth, morphogenesis, and virulence, and acts as a potent immunomodulatory molecule at the fungus–host interface. Elucidating its structure, biosynthesis, and function will advance fungal cell wall biology. Full article

Three-dimensional Dirac semimetal (3D DSM), characterized by linear band dispersion and strong terahertz nonlinear optical responses, has attracted increasing interest as promising materials for compact nonlinear photonic devices. Optical bistability (OB), which enables two stable output states under the same input condition, is of particular importance to all-optical switching, optical logic gates, and optical memory. However, achieving OB with a sufficiently low switching threshold remains a key challenge. Here, we propose a prism-coupled multilayer structure incorporating 3D DSMs to realize low-threshold, tunable OB by exciting the surface plasmon polaritons (SPPs). The prism-coupling configuration enables efficient excitation of SPPs, producing strong local-field enhancement around the nonlinear 3D DSM layer. This enhanced light–matter interaction, together with the large nonlinear refractive index of the 3D DSM, substantially reduces the electric-field threshold required for bistable switching. Numerical results show that OB can be achieved with an incident electric-field threshold on the order of 10⁵ V/m through optimizing the material and structural parameters. Moreover, the switching threshold and hysteresis loop width can be flexibly controlled by varying the Fermi energy, relaxation time, and geometric parameters of the 3D DSM multilayer structure. These results suggest that SPP-assisted 3D DSM structures provide an effective platform for low-threshold, actively tunable optical bistable devices in integrated terahertz photonic systems. Full article

Nanofiltration membranes have emerged as a crucial class of pressure-driven separation materials, positioned between ultrafiltration and reverse osmosis in terms of selectivity, permeance, operating pressure, and energy consumption. Their ability to remove fine contaminants—including multivalent ions, organic micropollutants, dyes, and macromolecules—has made them essential in water and wastewater treatment, pharmaceutical processing, and various industrial applications. In spite of their growing relevance, the performance of polymeric nanofiltration membranes, such as polyamide, polysulfone, polyethersulfone, polyvinylidene fluoride, and polyimide, is still constrained by weak hydrophilicity and a strong susceptibility to fouling, which collectively decrease permeance, increase operational costs, and shorten membrane lifespan. In recent years, substantial research efforts have focused on designing and engineering the surface chemistry and structural characteristics of nanofiltration membranes to improve water permeance, reduce foulant adhesion, and improve long-term stability. This review provides a comprehensive and comparative assessment of the most recent modification techniques applied to polymer-based nanofiltration membranes. Strategies such as polymer blending, nanoparticle incorporation, physical surface coating, plasma treatment, chemical attachment, layer-by-layer assembly, and interfacial polymerization are critically examined with respect to their effectiveness and practical limitations supported by recent research examples. Special attention is given to how these modification methods affect membrane morphology, hydrophilicity, permeance, and antifouling properties. Eventually, the review highlights emerging ideas and forward-looking design directions that may guide the next generation of nanofiltration membranes toward higher efficiency, improved durability, and broader industrial applicability. Full article

The development of titanium-based surface alloys and coatings that combine extreme hardness with sufficient toughness remains a major challenge for components operating under severe friction and wear conditions. In this work, titanium–boride composite coatings were synthesized on commercially pure titanium by scanning electron beam surface alloying of preplaced boron. The influence of beam power (900, 1200, and 1500 W) on phase formation, microstructural evolution, and mechanical performance was systematically investigated. At 900 W, insufficient melting resulted in chemically and structurally heterogeneous coatings containing unreacted boron. Increasing the beam power to 1200 W promoted the formation of TiB and TiB₂ phases, leading to a maximum microhardness of approximately 5500 HV_0.2. At 1500 W, complete boron incorporation produced a graded architecture consisting of a Ti/TiB surface layer and a TiB₂-rich sublayer. This hierarchical microstructure exhibited a favorable combination of high hardness and the lowest coefficient of friction (0.21), representing a reduction of more than 50% compared with the untreated titanium substrate. These findings establish a clear relationship between electron beam processing conditions, microstructural development, and mechanical performance, demonstrating that scanning electron beam surface alloying is an effective strategy for tailoring high-performance Ti–B composite surfaces. The developed coatings show strong potential for aerospace and other advanced engineering applications requiring lightweight materials with high hardness and low friction. Full article

The development of sustainable, biocompatible scaffolds with enhanced structural stability remains a primary challenge in bone tissue engineering. In this study, structurally reinforced nanocomposite scaffolds were successfully fabricated by integrating green-synthesized carbon quantum dots (CQDs) into a gelatin (G) matrix, offering an innovative platform that mimics the organic–inorganic interfaces of natural bone tissue. The CQDs were derived from oatmeal via a sustainable, green hydrothermal route, serving simultaneously as zero-dimensional reinforcing fillers and bioactive agents within the biopolymer network. To ensure an additive-free fabrication process that avoids toxic chemical cross-linkers, dehydrothermal (DHT) treatment was employed, successfully modulating the interfacial and chemical cross-linking interactions between the gelatin chains and the oxygen-rich surface groups of the CQDs. Structural characterization confirmed the uniform dispersion of CQDs (average diameter 7–8 nm) within the porous gelatin framework. The incorporation of CQDs significantly improved the physicochemical properties of the scaffolds; the G/CQD 5% formulation emerged as the optimal composition, exhibiting a 118% increase in compression modulus compared to pristine gelatin. The composite demonstrated tuned swelling kinetics and a significantly reduced degradation rate, restricting mass loss after 14 days of incubation to approximately 24% compared to 40% for pristine gelatin, which is essential for maintaining a structural template during the initial stages of tissue formation. Bioactivity assays in simulated body fluid (SBF) confirmed the rapid, biomimetic induction of a crystalline hydroxyapatite layer with a natural Ca/P ratio of 1.61 within 14 days. Furthermore, preliminary in vitro assessments using Human Skin Fibroblasts (HSFs) confirmed excellent general cytocompatibility, with cell viability exceeding 90%. This study highlights the unique potential of utilizing biomass-derived carbon nanostructures and clean manufacturing processing to engineer multifunctional scaffolds with enhanced structural stability and intrinsic bioactivity for potential bone defect repairs. Full article

To address the challenge of balancing flame retardancy and dust suppression in conventional coal mine treatment materials, a multi-component synergistic flame-retardant dust-suppressant gel was fabricated using carboxymethyl cellulose (CMC) as the matrix, compounded with ammonium polyphosphate (APP), zinc borate (ZB), and polycarbodiimide (PCDI) as a cross-linking agent. The optimal formulation was determined via orthogonal experimental design combined with performance characterization, yielding a composition of 1 wt% CMC, 8 wt% APP, 2 wt% ZB, and 0.5 wt% PCDI. Systematic evaluations—including wettability tests, thermogravimetric analysis, and fire-extinguishing trials—demonstrated that the resultant CMC-based composite gel exhibits excellent structural stability and environmental tolerance. Specifically, the contact angle on the coal surface decreased sharply from 72.8° to 17.2°, and the mass loss rate after 30 min of wind erosion was merely 4.16%. Treatment with the gel elevated the critical temperature of the coal–oxygen reaction from 70 °C to 80 °C and reduced CO emissions by 40% at 170 °C. Furthermore, the temperatures corresponding to the maximum weight loss rate, ignition, and burnout increased by 12.9 °C, 16.8 °C, and 28.9 °C, respectively. Fire suppression tests revealed that the gel rapidly cools high-temperature coal seams and effectively prevents reignition. Mechanistic investigations indicate that the CMC-PCDI cross-linked network synergizes with the APP-ZB phosphorus–boron flame-retardant system: the three-dimensional gel architecture provides physical encapsulation and water retention, while the intumescent char layer formed by APP-ZB offers efficient oxygen barrier protection. This study provides a reliable gel-based technical solution for the integrated prevention and control of coal dust pollution and spontaneous combustion disasters in underground mines. Full article

High-frequency induction hardening enhances the surface wear resistance and contact fatigue life of high-speed linear guides, but simultaneously produces an inhomogeneous, layered cross-sectional structure comprising a high-strength, low-ductility outer hardened layer and a low-strength, high-ductility inner core. This structural heterogeneity renders conventional straightening stroke prediction models—predicated on homogeneous material assumptions—fundamentally inadequate. Moreover, the iterative trial-bending operations ubiquitous in industrial practice progressively accumulate plastic strain, causing guide rails to exhibit erratic positive-to-negative deflection reversal during sequential straightening passes. To address these critical challenges, this study proposes a novel two-stage hybrid straightening strategy based on inverse finite element analysis (FEA) and closed-loop experimental feedback. An equivalent hardened layer depth (HD₀) is introduced as a parametric descriptor to construct a layered elastoplastic finite element model, and an inverse simulation strategy is developed to generate a comprehensive three-dimensional stroke–residual deflection prediction dataset encompassing both vertical and lateral straightening conditions across multiple support spans. Displacement-controlled three-point bending experiments validate the layered model and elucidate the mechanism by which cumulative plasticity progressively amplifies cross-sectional plastic sensitivity under repeated loading. Grounded in this physical insight, a hybrid straightening algorithm is formulated, combining dataset-driven initial stroke prediction for rapid large-deformation elimination with an upper-bound constraint and a measurement-feedback-driven sequential reduction compensation scheme for fine-tuning. Comparative experiments demonstrate that the proposed strategy effectively suppresses the oscillatory over-straightening characteristic of conventional empirical trial-and-error approaches, consistently reducing residual deflection below 0.05 mm within two to three loading cycles. This work bridges the gap between theoretical simulation and the complex physical state of actual machining, substantially improving both the efficiency and precision of straightening for guide rails with induction-hardened layers. Full article

Current micro/nanosystems mainly rely on a planar fabrication framework, where structures are built layer-by-layer on flat surfaces. This conventional approach leaves vertical sidewalls underutilized, posing geometric limits in packaging density, three-dimensional (3D) interconnects, and multi-surface functionalization. To overcome these constraints, sidewall patterning has emerged as a promising strategy, enabling 3D integrated circuits, templates for directed nanostructure synthesis, and microfluidic drag reduction. Nevertheless, traditional photolithography and non-photolithographic techniques face challenges when applied to vertical or curved 3D surfaces. Unidirectional radiation and restricted focal depths prevent high-fidelity pattern transfer, even when using soft lithography, scanning probes, or nanoimprinting. To address these geometric and mechanical barriers, our group has developed several approaches for patterning the sidewalls of microsystems, which are the primary focus of this review. Building upon our approaches, this review further surveys related sidewall-patterning strategies, including micro-transfer printing, multi-stimuli-responsive mechanics, block copolymer self-assembly, two-photon polymerization, and laser-induced forward transfer. Collectively, these techniques expand the capabilities of sidewall engineering and provide valuable insights into next-generation 3D micro- and nanomanufacturing. Full article