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Researchers have watched a huge crater form on the lunar surface, and its widespread effects could help inform future exploration of the moon and other similar places
The amount of dust in the atmosphere has fallen, which is good for our lungs, but is a loss for ecosystems that depend on wind-borne nutrients
Analysis of the chemistry of ancient T. rex tooth enamel adds weight to the idea that the fierce Cretaceous predator controlled its body temperature
Yet more readers share their insights from their own four-legged friends – and one proposes a more general theory
If every ship on the planet were hauled out of the water, how much would global sea levels change, and how quickly? How different would Earth be if anaerobic life were the only life form, and could it have become sentient?
Feedback enjoys a new piece of research delving into papers whose titles mention Beatles songs – but wonders if there is an ulterior motive at work for those who pulled it together
Tom Gauld weekly cartoon
This week's cartoon from Twisteddoodles
Recent progress on alternatives to animal testing is hugely welcome. But talk of "phasing out" animal research completely is misleading and could even be dangerous to scientists
The longest satellite record ever compiled shows the vast majority of ice loss from Greenland and Antarctica is due to glaciers flowing faster, rather than warmer air temperatures melting them at the surface
Scientists have grown human brain tissue to fill most of a mouse’s cortex, creating a new model for studying brain disease and neural circuits.
A cryptic announcement raises questions about the type of weapons and how they could be used. We talked to an expert about the consequences.
Removing a type of immune cell from lymph nodes in mice reduced brain inflammation and cell damage in a model of Alzheimer’s-like disease.
Four newly described species of Australian plant bug have been named in honor of renowned recording artist Taylor Swift.
Ecologist Merritt Turetsky’s devotion to bogs, fens and other fascinating water-logged spaces saturates her new book.
Scientists are exploring new ways to regain control of overactive nervous systems including humming, tapping on the skin and cold-water immersion.
An expedition of a deep-sea trench near Australia uncovered the eerie sea spider specimens, whose glow may have been chronicled in 19th century documents.
The XENONnT detector glimpsed the ethereal subatomic particles that are born from the main type of fusion reaction that powers the sun.
OpenAI is at the center of another controversy over machines tackling big math problems. This one’s about the twin prime conjecture.
As heatwaves become more frequent and severe, scientists are studying whether heat acclimation can help protect vulnerable populations.
Scientists are working closely with art historians to uncover scientific documentation in historic paintings.
The anniversaries come and go, but the physical and mental health of workers and survivors is still being affected by September 11, 2001.
Historic data and predictions suggest cases will rise in East Africa and southern regions, while the threat may ease in West and Central Africa.
Paleontologist Riley Black’s latest book explores how this misunderstood carnivore might have lived.
In the movie Whalefall, a sperm whale accidentally swallows a scuba diver. It’s technically possible, but unlikely to play out in real life.
For decades, researchers wondered if the Navier-Stokes equations, which describe fluid flow, break down. OpenAI put thousands of agents on the question.
Shingrix, the same vaccine that protects people from the blistering shingles rash, might also lower risk of heart disease.
Teeth and bone fragments unearthed in a cave in China, along with animal bones and stone tools, help paint a picture of Denisovan life.
By studying chickadee cognition in the wild, researchers learned smarter birds stay smart in old age, produce more young and have better gut bacteria.
An analysis of sound-making structures on preserved wings reveals the mating calls of ancient Jurassic insects, re-creating part of an ancient soundscape.
Uncertainties arising from control deviations, geometric deviations, and propellant property deviations during the design, manufacturing, and operation of solid divert control motors (SDCMs) cause the thrust output to deviate from its nominal value, thereby affecting the strike accuracy of kinetic interceptors. To quantitatively evaluate the influence of these uncertainties on strike accuracy, an integrated internal-external ballistic dynamic model of the SDCM is established. Based on this model, a performance dispersion analysis method for the integrated internal-external ballistics is proposed using polynomial chaos expansions. The effects of control deviations, geometric deviations, and propellant property uncertainties on the miss distance are systematically analyzed, and Sobol’ sensitivity analysis is performed to quantify the contribution of each uncertain parameter to the variability of the miss distance. The quantitative evaluation of uncertainty effects provides valuable guidance for the optimal design of SDCMs.
Accurate state of health (SOH) estimation for lithium-ion batteries (LIBs) is essential to ensure operational safety and reliability. However, most of existing SOH estimation studies are conducted under the assumption of complete battery charging data, which are not applicable to practical applications. Partial charging conditions and cell-to-cell degradation variability bring significant challenges for accurate online SOH estimation for LIBs. To address these issues, this paper proposes an enhanced uncertainty-weighted Bayesian-fusion sequential variational Gaussian mixture regression (BF-SVGMR) framework to improve SOH estimation accuracy and robustness under partial charging conditions, integrating historical degradation priors and incomplete charging curves into consideration. Firstly, the probabilistic relationship between extracted partial-charging features and historical capacity information is modeled, and the current-cycle capacity prediction with its uncertainty is then obtained using SVGMR. A prior representing the historical capacity degradation trend is then constructed from the previously observed capacity sequence using a sliding-window strategy. To realize online updating of priors, an uncertainty-weighted Bayesian online correction method is presented. Comparison experiments are conducted on two different datasets to verify the efficiency of the proposed framework. Results indicate that the proposed BF-SVGMR framework is superior to baseline methods, presenting excellent performance under partial charging conditions
The economic viability of offshore wind farms (OWFs) is heavily constrained by exorbitant operation and maintenance (O&M) costs and significant revenue losses during system downtime. While opportunistic maintenance (OM) strategies have been widely adopted to share the high fixed costs of vessel dispatch, existing frameworks largely rely on static degradation models and fail to account for the extreme short-term volatility of modern deregulated electricity markets. To bridge these gaps, this paper proposes a dynamic OM framework driven by day-ahead locational marginal prices (LMPs). Firstly, a hybrid multi-component degradation model is established. A stochastic process is developed to capture the complex crack initiation and propagation mechanisms of wind turbine blades, while the progressive aging of electromechanical components is characterized by Weibull distributions. Secondly, a dynamic and price-responsive OM thresholding mechanism is introduced. By integrating day-ahead weather forecasts and LMPs, the proposed strategy proactively groups preventive maintenance tasks during low-price windows and tightens thresholds during price spikes, thereby minimizing the expected maintenance cost. Numerical case studies based on real-world OWF configurations and historical market data demonstrate that the proposed dynamic strategy significantly outperforms traditional static OM approaches, reducing the expected lifecycle maintenance costs by 18.4% and substantially mitigating financial risks associated with electricity price volatility.
Complex network bottlenecks, as core constraints governing system efficiency, stability, and resilience, reflect structural imbalances among network topology, functional flows, and inter-component coupling. They substantially affect the performance and reliability of critical infrastructure and socioeconomic systems. As a prominent research topic, current studies remain fragmented in theories and methodologies, making it difficult to formulate targeted bottleneck mitigation strategies for diverse network scenarios. Meanwhile, the proliferation of big data, artificial intelligence, and other emerging technologies has reshaped traditional analytical paradigms. This paper systematically reviews state-of-the-art research, which classifies bottlenecks by their identification object, origin, scope, and temporal characteristics, and categorizes identification methods into topology-based, flow/load-based, dynamics-based, machine learning-based, and deep learning-based approaches. We further summarize future development trends and highlight key unresolved challenges.
Multicomponent systems operating in dynamic environments are affected by cumulative environmental shocks and dependent component lifetimes, which may lead to inaccurate reliability evaluation and inefficient reliability allocation if ignored. To address this issue, this paper develops a non-homogeneous pure birth process (NHPBP)-driven stochastic time-scale model for multicomponent systems. The environmental shock-counting process is modeled by an NHPBP, while the stochastic time scale is constructed as a path-dependent cumulative exposure functional driven by the whole shock history. Based on the Laplace transform of the stochastic time scale, component survival functions, joint survival functions, and reliability expressions for typical system structures are derived. Positive quadrant dependence among component lifetimes is also established. Furthermore, a cost-oriented reliability allocation model is formulated under a system-level reliability constraint and solved using a genetic algorithm. Numerical experiments on an automotive braking system show that the conventional non-homogeneous Poisson process (NHPP)-based model may overestimate system reliability under cumulative shock amplification, whereas the proposed NHPBP-based allocation model provides feasible allocation schemes under dynamic environments.
Your WordPress site can load pages before visitors even click. Learn how speculative loading works, what WordPress 6.8 turned on, and how to tune it! The post WordPress Speculative Loading: What It Does and How to Configure It appeared first on Themeisle Blog.
For this post, I decided to use the Section Generator in the free Otter Blocks plugin. I built nine sections of a WordPress site with it, but instead of endlessly prompting until I got it "just right," I relied on a single prompt. Then I took a screenshot of what that prompt produced so I could share the results. The post What WordPress AI Really Builds: 9 Prompts, 9 Unedited Results, and What the Good Ones Have in Common appeared first on Themeisle Blog.
WordPress, Apache, and Zephyr adapt to AI-driven security and infrastructure demands shaping the future of open source at scale.
Skip the analytics tab scavenger hunt. Here's how to ask your AI about traffic, search queries, and indexing, then have it act on the answer. The post Ask Your AI About Your Website Traffic (GA4, Search Console, SEO in One Chat) appeared first on Themeisle Blog.
MCP keeps showing up in AI news, but what is an MCP server actually for? Plain-English answers, plus what it means for your WordPress site. The post What Is MCP (Model Context Protocol)? A Guide for WordPress Users appeared first on Themeisle Blog.
We describe a case study on the application of an Optical Flow algorithm, using predictive velocity and pyramidal search, to the measurement of displacements in two 200 μm thick metal test specimens, compared with a traditional digital image correlation (DIC) implementation. One mesoscale tensile specimen and one mesoscale shear specimen of commercially fabricated electrodeposited nickel alloys, used in Micro Electro Mechanical Systems applications, were tested to fracture. The specimens were 200 μm thick and had gauge widths of 200 and 600 μm. Optical micrographs were taken during the tests. Displacements, strains, and mechanical properties were measured from the same sets of images using Optical Flow versus traditional DIC. The engineering stress–strain curves and shear stress vs shear strain curves from both techniques were similar (to within 1% for the engineering strains and 4%–9% for the shear strains) from the start of the tests to failure. This case study thus suggests Optical Flow shows promise as a measurement tool to complement DIC for mesoscale testing and warrants further investigation with more specimens. Potential advantages provided by Optical Flow in general include increased robustness and the potential for lower image segment search time, which could be especially beneficial for micro- and mesoscale test specimens.
Stress-relief annealing is a critical step in the engineering application of Ti80 alloy, but the effect of its temperature on impact toughness remains unclear. In this work, the Ti80 alloy was first solution treated at 970 °C for 1 h and air cooled, then subjected to stress-relief annealing at 530 °C–620 °C. The microstructure, impact toughness, and crack initiation/propagation behaviors were systematically characterized. Results show that with increasing annealing temperature, the αt needles in βtrans coarsen from 19.95 nm at 530 °C to 62.71 nm at 620 °C, while the dislocation density and subgrains in αp decrease. Thus, the hardness of both phases drops, while βtrans remains the softer phase. Impact toughness drops sharply from 50 J at 530 °C to 24 J at 620 °C. Fracture analysis shows that higher annealing temperature reduces plastic deformation in the initiation zone, shrinks the shear lip, and straightens the crack path. Mechanistic analysis reveals that microvoids preferentially nucleate inside βtrans and at αp/βtrans interfaces. The decrease in impact toughness results from the combined effects of a lower crack initiation threshold due to softening of βtrans and a weaker crack propagation resistance due to coarsening of αt.
Porous chitosan has a high interconnected internal surface area. It is useful for applications such as scaffolds, drug-delivery carriers, wound dressings, filtration, or reactive precursors for the synthesis of chitosan derivatives. This research investigated the impact of oven drying temperature on the morphology, chemical structure stability, and reactivity of porous chitosan produced at the specified temperature. Porous chitosan was produced using a sol-gel method and dried in an oven at 40 °C, 50 °C, and 60 °C. The effect of drying temperature on porous chitosan was characterized using FTIR, XRD, DSC, and SEM. The reactivity of porous chitosan in the formation of chitosan carboxylate was analyzed using FTIR and carboxyl content. The characterization results showed that drying temperatures of 40 °C, 50 °C, and 60 °C did not change the chitosan backbone structure but increased apparent crystallinity and thermal stability. The increase in temperature also made the pores more compact and prone to collapse. The differences in the characteristics of porous chitosan affect its reactivity towards HNO3/H3PO4–NaNO2 in the formation of carboxylated chitosan.
This study theoretically investigates an optical fiber structure coated with a bilayer film of zinc oxide (ZnO) and lithium fluoride (LiF) for ethanol detection. The ZnO thin film exhibits lossy mode resonance (LMR) in the visible and near-infrared spectrum (400–1500nm), which serves as the basis for designing a refractive index (RI) sensor by appropriately selecting the ZnO thickness. To further enhance the resonance characteristics, a dielectric layer of LiF is introduced between the unclad fiber core and the ZnO coating. It Improves phase matching and generates sharper LMR dips with a narrower full width at half maximum. The proposed structure is also analyzed using two different core materials: pure silica and 4% Ge-doped silica. A comparative study of their sensing performance is also presented. Its sensing performance is examined by varying the thicknesses of the ZnO and LiF layers to identify the optimal structural parameters. The designed fiber-optic sensor is then evaluated for detecting ethanol concentrations in ethanol–water mixtures (RI =1.33 for 0% ethanol and RI =1.36 for pure ethanol) using both s- and p-polarized incident light. Calibration curves demonstrating the relationship between resonant wavelength shifts and the RI of the sample are presented. This sensor achieves excellent sensitivities of 1163 nm RIU−1 for s-polarization and 1475 nm RIU−1 for p-polarization, making it promising for the development of High-Figure of Merit biochemical sensors for potential applications.
Phosphate-induced eutrophication poses a critical water quality concern, and adsorption offers an effective remediation approach, yet conventional adsorbents suffer from limited capacity and poor reusability. In this study, a carboxyl-functionalized zirconium-based metal-organic framework (UiO-66-COOH) was synthesized through the hydrothermal method and deeply explored its phosphorus removal performance and potential mechanisms. Batch adsorption experiments were conducted to investigate the effects of initial solution pH, initial phosphate concentration, adsorbent dosage, and reaction temperature on the material’s phosphate adsorption behavior. Under the optimized conditions (pH = 3, dosage 0.2 g l−1), UiO-66-COOH exhibited a remarkable removal efficiency of 97.71%, with an equilibrium adsorption capacity of 48.86 mg g−1. Adsorption kinetics followed the pseudo-second-order model, indicating chemisorption-dominated behavior, while thermodynamic analysis revealed a spontaneous and endothermic process. Comprehensive characterization (such as x-ray powder diffraction, x-ray photoelectron spectroscopy, and Fourier-transform infrared spectroscopy) indicated that the efficient removal of phosphate by UiO-66-COOH was attributed to the synergistic effects of pore filling, carboxyl coordination chelation, and electrostatic interactions. This study not only provides an efficient adsorbent for phosphate pollution control but also offers theoretical and experimental support for the application of functionalized MOF materials in water environment remediation.
Additive manufacturing of architected polymer reinforcements is an emerging geometry-driven approach to improve the mechanical performance of cementitious materials. In contrast to conventional methods, it enables controlled architectures where load transfer and crack propagation are governed by topology and spatial distribution. However, comparisons are difficult due to variability in architectures, materials, processes and testing conditions. This review covers advances in 3D-printed polymer reinforcements, such as discrete and graded lattices, TPMS, auxetic, and origami-inspired structures. The reported improvements are mainly related to ductility, post-cracking response, energy absorption (up to 853%) and flexural toughness (up to 23×), with some systems showing a transition toward strain-hardening behavior. However, these values are strongly influenced by the baseline reference conditions, reinforcement ratio, polymer type, architecture, specimen geometry and testing protocol, limiting direct quantitative comparison between studies. The effects of polymer selection and manufacturing processes are also discussed. The main challenges are geometric inaccuracies, limited interface characterization, insufficient durability assessment, and lack of standard protocols. To address these, better interface design, material selection, and consistent processing–structure–property analysis are needed, which would support a more rational design framework and broader applications.
The effect of sputtering gas, particularly the generation of energetic recoil particles, is crucial in determining interfaces and microstructural evolution of magnetron-sputtered thin films. This is especially critical for nanoscale Ni/Ti multilayers, which are core components in advanced neutron mirrors. In this work, the modulation of the interface and layer structure in Ni/Ti multilayers was comparatively investigated by varying the sputtering gas using Ar and Kr. TRIM simulations reveal that using a heavier sputtering gas (Kr) significantly reduces the energy and number of recoil particles. Comprehensive characterizations using GIXRR, diffuse scattering, XRD, and TEM demonstrate a physical trade-off: the Ar-sputtered multilayer is found to exhibit approximately 1.5 times lower interface roughness (RMS), while it shows stronger Ni (111) crystallization and larger interdiffusion. Conversely, replacing Ar with Kr reduced the crystallization and atomic intermixing, despite the relatively larger interface roughness. These findings provide useful guidance for mitigating interface defects and optimizing the fabrication of high-performance multilayer optics.
A magnetically recoverable Fe3O4/TiO2 composite was synthesized and applied for the removal of Xylenol Orange, a dye widely used in industrial applications, via a peroxymonosulfate assisted photocatalytic process under UV irradiation. The structural and physicochemical properties of the composite were characterized using XRD, FTIR, and SEM–EDS. Complete color removal (100%) was achieved under the optimum conditions of pH 5.0, PMS concentration of 1.0 mM, catalyst dosage of 1 g l−1, 30 min dark adsorption, and 60 min UV irradiation. An increase in the initial XO concentration (25–100 mg l−1) resulted in a decline in removal efficiency. Kinetic analysis revealed that XO degradation followed a pseudo-first-order Langmuir–Hinshelwood model. The composite maintained its activity up to the second cycle and exhibited dual catalytic behavior, involving both photocatalysis and PMS activation via Fe3O4. Life cycle assessment using the ReCiPe 2016 Midpoint (H) method indicated that energy consumption, mainly from UV irradiation, is the primary contributor to environmental impacts. These findings demonstrate an efficient and environmentally relevant approach for azo dye removal.
Polyethylene terephthalate (PET) waste was depolymerized by microwave-assisted alkaline hydrolysis in two separate reagent systems, one based on NaOH and one on KOH, with the aim of recovering terephthalic acid (TPA) and characterizing each system at the process level. The two systems were optimized independently, each within its own operating window, using a Taguchi L9 (34) orthogonal array of four factors at three levels, with four replicates per run (36 runs per system). Because the two campaigns used different catalyst variables, TiO2 loading in the NaOH system and catalyst type (none, zinc acetate, zinc oxide) in the KOH system, the results are reported as process-oriented characterizations of each system rather than as a catalyst-matched comparison of the two cations. Analysis of variance, signal-to-noise (S/N) analysis, main-effect analysis and general linear model (GLM) regression all identified temperature as the controlling factor in both systems, followed by alkali concentration and reaction time. PET conversion approached completion at 195 °C/30 min/12 wt.% NaOH and at 200 °C/36 min/18 wt.% KOH. The GLM models were predictive (R2 ⩾ 98%; leave-one-out predicted R2 within 1.6% of R2), and residual analysis supported the model assumptions. The main methodological contribution is a pair of severity-normalized descriptors, a performance index and an apparent rate index adapted from the combined severity factor of biomass pretreatment, which read efficiency per unit of applied thermal and temporal severity rather than by conversion alone. A preliminary process assessment quantified the alkali stoichiometric excess (≈4.3–4.6-fold) and the inorganic salt by-product stream, both of which identify reagent efficiency as the main obstacle to scale-up. TPA recovery was confirmed by Fourier-transform infrared spectroscopy and 1H NMR, and product morphology was examined by scanning electron microscopy.
This study investigated the long-term release of bisphenol A-glycidyl methacrylate (Bis-GMA), ethoxylated bisphenol A dimethacrylate (Bis-EMA), and urethane dimethacrylate (UDMA) from conventional and bulk-fill resin composites polymerized using different light-curing units and curing times. Three bulk-fill composites and one conventional resin composite were evaluated. Eighty specimens were prepared using standardized metal molds (2 mm × 8 mm for the conventional composite and 4 mm × 8 mm for the bulk-fill composites) and polymerized using either a halogen (Optilux 501) or light-emitting diode (LED; Demi Ultra) curing unit for 20 s or 40 s (n = 5). The specimens were stored in a 75% ethanol/water solution, and monomer release was analyzed after 24 h, 1 week, 1 month, and 6 months using liquid chromatography-tandem mass spectrometry. Data were analyzed using multivariate ANOVA, repeated-measures ANOVA, Tukey HSD, and Tamhane’s T2 tests (α = 0.05). Both curing-unit type and curing time significantly influenced monomer release (p < 0.001). The LED curing unit resulted in lower monomer release than the halogen unit under the tested experimental conditions, while extending curing time from 20 s to 40 s significantly reduced monomer elution. Monomer release remained detectable throughout the six-month observation period. When all experimental conditions were considered collectively, UDMA exhibited the highest overall release and Bis-EMA the lowest, although material- and time-dependent variations were observed. Tetric EvoCeram Bulk Fill released significantly higher amounts of UDMA and Bis-GMA than the other investigated composites (p < 0.001). Within the limitations of this study, both curing conditions and material composition significantly influenced long-term monomer release. These findings highlight the combined contribution of composite formulation and curing protocol to the release behavior of major resin-matrix monomers from contemporary resin composites.
