Browse Articles

The crucial role of the Seebeck effect in the degradation behavior of Mg-based biomedical alloys

Biodegradable magnesium alloys hold great promise as orthopedic implants due to their bone-matching elastic modulus and capacity to eliminate secondary removal surgery. Nevertheless, the often-ignored role of the thermoelectric effect of Mg alloy biomedical materials in their corrosion process might have led to a research gap in this field. This overlooked role of the thermoelectric effect has prompted this study, which aims to investigate the effects of Zn content on the microstructure, corrosion behavior, and biophysical properties of Mg–3Sn–xZn (x = 0, 1, 3, 5, 7 wt. %) alloys. Specifically, this study evaluates the micro-current generated by degradation-induced galvanic effects, especially the Seebeck effect, and its subsequent impact on cell viability and migration, which are closely related to the investigated microstructure, corrosion behavior, and biophysical properties of Mg–3Sn–xZn alloys. Results indicate that the Mg–3Sn–5Zn alloy exhibits optimal comprehensive performance, demonstrating favorable degradation kinetics, enhanced biocompatibility, notable antibacterial properties, and improved in vitro corrosion resistance. Critically, the degradation-induced micro-current significantly promotes cell viability and migration, thereby facilitating tissue repair. This work establishes an innovative correlation between the alloy's Seebeck coefficient and biocompatibility, offering mechanistic insights for biodegradable bone-repair materials and advancing their clinical translation.

The impact of fly ash and slag on the microscopic interface of recycled concrete and its destruction evolution

Characteristics of photo-activated avalanche charge domain in semi-insulating GaAs photoconductive switch

According to the photo-activated charge domain theoretical model, the formation characteristics of the photo-activated avalanche charge domain (PAACD) is studied based on the characteristics of the photoelectric thresholds for the high-gain GaAs photoconductive semiconductor switch (PCSS). It is shown that the PAACD with a peak electric field much larger than the intrinsic breakdown electric field of GaAs will be formed within the switch at the instant of optical triggering, and the triggering optical wavelength and spot size have a significant effect on the initial domain characteristics. According to the PAACD model, the dependence of the threshold electric field on threshold laser pulse energy (TLPE) is calculated theoretically. Quantitative agreement between the calculation and the experiment has been achieved. Using the Silvaco software, the transport process of the PAACD is investigated numerically. Moreover, the variations of TLPE with laser spot size under different bias electric fields are studied theoretically. Our study can deepen the understanding of the generation mechanism of high-gain GaAs PCSS and contribute to the optimization of the device's performance.

Evaluation of a sensitive real-time PCR assay for Group B Streptococcus detection in vaginal-rectal swab

Low-field Landau-level crossings in ABA pentalayer graphene revealed by sequential plateau disappearances

We investigated suspended Bernal-stacked (ABA) pentalayer graphene with ultralow disorder and observed well-defined quantum Hall plateaus and Landau-level crossings at magnetic fields below 2 T. As the magnetic field increases, the initially robust plateaus at filling factors ν = −22, −18, −14, −10, and −6 successively disappear from larger |ν| at characteristic fields B* ≈ 0.26, 0.32, 0.42, 0.62, and 1.3 T, respectively, where B* denotes the first field at which a given plateau vanishes. This sequence is consistent with crossings between the Nth Landau level (N = 5, 4, 3, 2, and 1) of a monolayer-graphene-like subband and a nearly field-independent low-lying Landau level of a bilayer-graphene-like subband. A Slonczewski–Weiss–McClure tight-binding model that includes only the dominant hopping parameters γ0 and γ1, augmented by an interaction-induced staggered layer potential, quantitatively reproduces these first-disappearance fields. These results establish ABA pentalayer graphene as a tunable platform in which the interplay between the parity-dictated subband structure and electron–electron interactions governs Landau-level crossings at unusually low magnetic fields.

Multistep loss of catalytic and ligand binding abilities of hexameric purine nucleoside phosphorylase

Abstract It is commonly believed that enzymatic catalysis is such a complex process, that even a small change in any physicochemical property of the enzyme results in a complete loss of the catalytic and ligand-binding capacity of the molecule. Therefore, when the enzyme sample is not fully active, but is electrophoretically pure, the inactive fraction is often considered equal to the non-binding fraction, and constants characterizing ligand binding by such an enzyme and ligand-induced inhibition are determined under this assumption. Here, we present an enzyme, hexameric purine nucleoside phosphorylase, whose gradual loss of a catalytic activity towards natural substrates does not correlate with the loss of the ability to bind ligands, substrates, and inhibitors. The values of dissociation constants characterizing ligand binding depend on the specific activity of the enzyme used in the experiment. Furthermore, there is a stable state of the enzyme, in which it is no longer able to catalyse reaction with natural substrates, but can still catalyse the same reaction if a substrate resembling the transition state is used. The active site conformations of individual subunits in the X-ray structure of this hexameric molecule reflect the presence of intermediate states observed in the enzyme activity decline profiles.

Optimization of bias stability in an interferometric fiber optic gyroscope via optical switch modulation

We demonstrate an interferometric fiber optic gyroscope (IFOG) driven by an amplified spontaneous emission laser source, incorporating optical switch to reduce slowly varying errors and enhance stability. An optical switch operating at a frequency of 25 Hz enables complementary angular rate outputs, effectively suppressing low-frequency drift through differential processing. Current IFOG demonstrates superior performance compared to the feedback method configuration, with its angular random walk improved from 0.0021 to 0.0016 °/h and its bias instability showing a significant threefold improvement (from 0.0117 to 0.0038 °/h). Building upon its simple structure and long-term stability, this IFOG can be widely applied in inertial navigation systems.

BERT-spaCy hybrid NLP and blockchain-enhanced adaptive CTI for IOC extraction and threat prediction

Abstract Cyber-attacks pose a significant risk to digital infrastructure, resulting in losses at both individual and organizational levels, underscoring the need for proactive and intelligent defense mechanisms. This study proposes a hybrid Cyber Threat Intelligence (CTI) system integrating an immutable blockchain ledger, adaptive machine-learning models, and natural-language processing algorithms for timely detection, classification, and secure sharing of threat data. The system forecasts future attacks by analyzing aggregated data and recommending mitigation strategies. A BERT-based model, combined with spaCy and regular expressions for extracting Indicators of Compromise (IOCs) from unstructured data, achieved 95% accuracy and a 95.7% F1-score, with a 55% latency reduction (from 120ms to 54ms for 200 reports). Validation used 10-fold cross-validation with paired t-tests across 10,000 Monte Carlo simulations (t = 3.45, p  < 0.001, Cohen’s d ranging 0.76–1.12 from heatmaps) on CIC-IDS2017 and UNSW-NB15 datasets. The Cross-Dataset Robustness Index (CRI) confirmed strong generalization, with BERT at 0.999, slightly outperforming LSTM (0.998), SVM (0.95), and Naïve Bayes (0.92). The system excels in high-volume data processing, event correlation, and threat detection/response rates. This scalable solution suits Security Operations Centers (SOCs), IoT environments, and financial cybersecurity, providing robust unstructured data handling and adaptability to evolving threats.

Structural and electrical characterization of homoepitaxial (1¯02) <b> <i>β</i> </b> -Ga2O3 layers grown by halide vapor phase epitaxy using synchrotron x-ray topography and emission microscopy

This study demonstrates that (1¯02) β-Ga2O3 is a promising candidate for homoepitaxial growth via halide vapor phase epitaxy. Synchrotron x-ray rocking curve measurements confirmed a uniform full-width at half-maximum of approximately 16 arc sec across the wafer for both the substrate and the epitaxial layer. A donor concentration in the range from 7 × 1015 to 1 × 1016 cm−3 was confirmed by capacitance–voltage measurements of the Schottky barrier diodes (SBDs). Among the 35 SBDs, 32 exhibited a leakage current density lower than the detection limit under a reverse bias of −300 V, resulting in a high yield of approximately 91%. Synchrotron x-ray topography observation further identified that residual polycrystalline defects within the epitaxial film, which persist even after chemical mechanical polishing, were responsible for the reverse leakage current of the SBDs.

Blockchain-enabled traceability evaluation framework for mineral resource development and utilization: a fuzzy comprehensive assessment approach

Abstract Effective traceability management in mineral resource development faces persistent challenges including information asymmetry, data falsification, and verification difficulties across complex value chains. This paper proposes a comprehensive blockchain-enabled traceability evaluation framework integrating distributed ledger technology with systematic assessment methodologies. A four-layer architecture encompassing data acquisition, blockchain storage, analysis processing, and evaluation application is designed to ensure data integrity throughout the mineral lifecycle. A hierarchical indicator system spanning five dimensions—traceability breadth, depth, precision, timeliness, and data credibility—is constructed, with the Analytic Hierarchy Process employed for weight determination and fuzzy comprehensive evaluation applied for performance assessment. Empirical validation through case study analysis of Huaxin Mining Group demonstrates the framework’s practical applicability, yielding a comprehensive traceability score of 81.2 (Good grade). Comparative analysis reveals that blockchain-based systems achieve 96.8% data accuracy versus 82.4% for traditional approaches, with trace-back efficiency improving from 127.3 min to 4.7 min. The blockchain technology contribution ratio reaches 47.3% toward maximum traceability improvement. These findings provide theoretical foundations and practical guidance for advancing transparent and accountable mineral resource governance.

Enhanced graph coevolution network for social network analysis using assimilation modified emotional algorithm

Abstract This paper presents the Assimilation Modified Emotional (AME) algorithm, which is an enhanced version of the traditional label propagation algorithm (LPA) designed to address key challenges in social network analysis and emotional feature extraction. Traditional LPA methods, such as asynchronous label propagation and the Louvain algorithm, do not incorporate emotional representations and are often limited by local structural dependencies. The AME algorithm addresses these limitations by applying spectral algorithms, Markov chains, graph coarsening, and link prediction to simulate and optimize emotional transitions within the network. In addition, the AME algorithm enhances label representation through multi-label encoding, which allows for more accurate simulation of dynamic emotional states. Experimental results show that the AME algorithm achieves better performance than traditional LPA methods in terms of both accuracy and loss values. These findings indicate that the AME algorithm has strong potential for improving AI models used in social network analysis and emotional feature extraction.

Association of cytokine levels with treatment duration and patient family history in Egyptian multiple sclerosis patients

Abstract Multiple sclerosis (MS) is one of the diseases that is widely spreading all over the world, with no clear etiology or definite pathological mechanism. Although there is no cure for MS, multiple therapeutic agents called disease-modifying therapies (DMTs) have been developed to relieve worsening symptoms and counteract its progression. The aim of this study is to investigate the effect of DMTs on some proinflammatory cytokine levels in the serum of Egyptian MS patients over different treatment durations. Additionally, link the levels of serum cytokines with patients’ clinical parameters. A total of 192 MS Egyptian patients were recruited and classified based on treatment duration and DMT types. The levels of IL-6, IL-17A, TNF-α, and IFN-γ were detected using the ELISA technique. Results showed that MS patients treated for a period longer than 24 months were associated with a significant decrease in IL-6, TNF-α, and IFN-γ levels compared to untreated patients or patients treated for less than 12 months. IL-6 correlated directly with the Expanded Disability Status Scale score, whereas IL-17A and IFN-γ were inversely correlated in treatment-naïve MS patients. Additionally, MS patients with a family history of autoimmunity have a lower age at onset of the disease with a higher TNF-α level. In conclusion, proinflammatory cytokine levels were correlated with MS patients on long-term treatment with DMTs. IL-6 was linked with worsening disability in MS patients, while TNF-α was linked to a family history of autoimmunity.

Sonophore enables autonomous observation of micronekton communities in the ocean twilight zone

Abstract The future productivity of pelagic ecosystems and fisheries globally remains uncertain due to a lack of data on mid-trophic mesopelagic micronekton communities. Here, we demonstrate that integrating readily available autonomous profiling floats with autonomous echosounders enables vertically resolved abundance estimates of mesopelagic micronekton communities, a platform we are naming the “Sonophore”. This successful demonstration is a first step towards addressing critical data gaps identified by fisheries management, earth system and ecosystem modelling communities. With planned engineering enhancements, this platform offers a scalable solution for rapid, cost-effective, year-round monitoring of the planet’s largest vertebrate (but deeply uncertain) biomass. The platform is specifically designed for long-term monitoring of remote and spatially extensive oceanic habitats of the global ocean, without the need for large, expensive research vessels.

Local Polarity Engineering via Unsaturated Cu–N ₃ Sites for Enhanced Iodine Redox Chemistry in Zinc‐Iodine Batteries

Abstract Rational engineering of the local microenvironment in catalytic host materials is pivotal for high‐performance zinc‐iodine batteries, as it governs iodine species adsorption, accelerates redox kinetics, and suppresses polyiodides shuttling. Herein, we propose a local polarity engineering strategy by incorporating unsaturated Cu–N 3 sites into carbon matrix to construct polarized microenvironments and promote iodine redox chemistry. Combined theoretical and experimental analyses reveal that the unsaturated coordination of Cu atoms induces intrinsic local polarity, which enhances charge redistribution, lowers the activation barrier of the I 2 /I − redox reaction, and strengthens electronic coupling with polyiodide intermediates. In situ UV–vis and Raman spectroscopies corroborate that the Cu–N 3 sites effectively immobilize polyiodides, thus mitigating the shuttle effect. As cathode host, the Cu–N 3 sites‐rich carbon electrode achieves high discharge capacity of 232.2 mAh g −1 at 0.2 A g −1 and exceptional long‐term stability with 94.02% capacity retention after 50,000 cycles at 10 A g −1 . More importantly, benefiting from its superior catalytic activity toward iodine redox reaction, the Cu–N 3 sites‐rich carbon enables solar cells to achieve a remarkable power conversion efficiency of 9.14%. This work elucidates a novel design principle for regulating local polarity to propel iodine electrochemistry, offering new insights into the development of advanced iodine‐based energy devices.

Stability Thresholds of Atomically Dispersed Platinum Catalysts for Solar Hydrogen Production

Abstract The structural fluidity of single‐atom photocatalysts under illumination challenges conventional assumptions about catalytic identity, prompting a reevaluation of what defines and sustains active sites. Here, we show that the site density of atomically dispersed Pt on TiO 2 nanoparticles dictates their structural evolution and photocatalytic performance during the H 2 evolution reaction (HER). There is a critical dispersion threshold that separates the stable single‐atom state from the aggregative regime with less reactive multi‐atom ensembles. Under optimized conditions, isolated Pt sites resist light‐enhanced agglomeration and deliver HER activities (0.246 s −1 ) up to 82‐fold higher than those of Pt nanoparticles (0.003 s −1 ), achieving an apparent quantum yield of 9.1%. Beyond this threshold, atomic dispersion deteriorates through a first‐order aggregation process, resulting in an exponential loss of isolated sites and a sharp rise in the activation free energy ΔΔ G ‡ up to 17.1 kJ mol −1 . Combined experimental and theoretical analyses quantify the transition in catalyst architecture and activity, revealing a structure–stability–activity relationship. This framework defines a reactivity window governed by the interplay between spatial isolation and structural fragility in single‐atom catalysis.

Modelling lung and muscle oxygen diffusion capacities from sea-level to Mount Everest

Abstract Lung and muscle oxygen diffusion capacities (DLO 2 and DMO 2 , respectively) are difficult to measure at maximal-intensity exercise and at altitude and they are scarcely reported in the literature, yet they are key components of the O 2 transport cascade. The goal of the present study was to compute DLO 2 and DMO 2 at simulated increasing altitudes between sea-level and Mount Everest. Literature data were compiled to compute DLO 2 and DMO 2 at maximal exercise using a forward iterative algorithm. These computations were repeated every 250 m of increasing altitude between seal level and the altitude of Mount Everest. Computed DLO 2 increased from sea-level to 5500 m and then decreased to the altitude of Mount Everest; yet remaining higher than sea-level values. DMO 2 increased from sea-level to 3500 m and then progressively decreased to values lower than sea-level. The computed variations in DLO 2 and DMO 2 fit with the ability of the lung and muscle to increase their diffusion capacity at altitude, which seemingly indicates an existing diffusion capacity reserve. The muscle reserve seems depleted at a lower altitude than the lung reserve. The clinical relevance of the proposed model requires further investigation.

Electron Cloud Polarization of Single‐Atom Cu Boosts Electrocatalytic Reduction of High‐ and Low‐Concentration CO ₂ to Methanol

ABSTRACT Catalysis of the conversion of CO 2 from industrial exhaust gases to methanol at dynamically varying concentrations using renewable electrical energy is crucial for reducing CO 2 emissions and producing valuable chemical feedstocks. However, the challenges associated with the weak activation of linear nonpolar CO 2 molecules and the high energy difference of key proton‐coupled electron transfer steps make it difficult for existing catalysts to simultaneously achieve a high current density and a high selectivity. Herein, we report a strategy for regulating electron polarization in a Cu single‐atom catalyst (CuN 3 ‐C) to achieve efficient electrocatalytic reduction of high‐ and low‐concentration CO 2 to CH 3 OH. For both high‐concentration or low‐concentration CO 2 used as the feedstock, the CuN 3 ‐C catalyst achieves a current density exceeding −450 mA cm −2 , a Faradaic efficiency of 80% for methanol production, and record‐high production rate of 0.57 µmol s −1 cm −2 . In situ characterization and theoretical calculations jointly show that strong electron polarization of the CuN 3 ‐C catalyst facilitates more effective CO 2 activation and preferential *CO hydrogenation toward *CHO and *CHOH. This study provides a strategy for designing highly efficient catalysts for the conversion of CO 2 to methanol via electronic polarization modulation.

Temporal evolution of structure property relationship for UV+RH artificially weathered material extrusion additive manufactured PLA

Abstract This study addresses the underreported temporal evolution of weathering on material extrusion additive-manufactured (MEX-AM) polylactic acid (PLA). Overcoming the limitation of arbitrary exposure durations in existing literature, a time-dependent investigation was conducted on MEX-PLA samples subjected to prolonged artificial weathering for up to 2000 h using a UV-B equipped accelerated weathering chamber with controlled relative humidity. The changes in mechanical, chemical and thermal properties were analysed at 200-hour intervals. The results revealed a time-dependent degradation mechanism characterised by β-chain scission. FTIR analysis confirmed the formation of C = C groups and the progressive loss of H groups, indicating substantial material degradation. Furthermore, DSC and XRD data demonstrated a progressive increase in crystallinity with prolonged exposure, leading to a significant reduction in tensile strength. At the same time, the tensile modulus remained relatively stable for MEX-AM PLA.

Regulating Lithium Bond to Reduce Polysulfide Parasitic Reactivity for High‐Stability Lithium Metal Anode

ABSTRACT Lithium–sulfur (Li–S) batteries hold great potential as high‐energy‐density energy storage devices, yet their practical application is hindered by rapid cycling failure caused by parasitic reactions between lithium polysulfides (LiPSs) and lithium metal anodes. Inspired by lithium bond chemistry, we herein propose a weak cation interaction strategy as a new molecular design principle to intrinsically mitigate the parasitic reactivity of LiPSs and endow long‐cycling Li–S batteries operating at 500 Wh kg −1 level. Specifically, molecular‐level interaction regulation is introduced by employing ammonium cation (NH 4 + ) with weaker polarizing power than Li + to interact with LiPSs, thereby attenuating their electrophilicity, elevating their lowest unoccupied molecular orbital energy levels, and suppressing the detrimental parasitic reactions with lithium metal anodes. This regulation strategy markedly prolongs the lifespan of Li–S coin cells from 53 to 149 cycles under harsh conditions of using 4.2 mg cm −2 ‐loading sulfur cathodes and 50 µm‐thick lithium anodes. More importantly, an 8 Ah‐level Li–S pouch cell achieves a high initial energy density of 502 Wh kg −1 and stable 16 cycles. This work establishes a new weak cation interaction regulation strategy following lithium bond chemistry, offering a generalizable route toward long‐cycling and high‐energy‐density Li–S batteries.

Trend prediction method for capacitive voltage transformer measurement deterioration based on double Gaussian model-KAN fusion