Search Results (1,573)

Metakaolin (MK) obtained from calcined kaolinitic clay is a highly reactive pozzolanic ingredient for use as an emerging supplementary cementitious material (SCM) in modern sustainable binder productions. It provides elevated alumina to promote formations of Alumina Ferrite Monosulfate (AFm) and Calcium-Aluminium-Silicate-Hydrate (C-A-S-H) phases, enhancing the chloride binding capacity. However, due to inherent material uncertainty and lack of approach in quantifying hydration kinetics and chloride binding capacity across varied mixes, robustly assessing the chloride resistance of metakaolin-blended concrete remains challenging. In light of this, a machine learning-aided framework that encompasses physics-based material characterisation and ageing modelling is developed to bridge the knowledge gap. Through applying to laboratory experiments, the impacts of uncertainty on the phase assemblage of hydrated system and chloride penetration are quantified. Moreover, the novel Extended Support Vector Regression (XSVR) method is incorporated and verified against a crude Monte Carlo Simulation (MCS) to demonstrate the capability of achieving effective and efficient uncertainty-aware chloride resistance analyses. With the surrogate model established using XSVR, quality control of metakaolin towards durable design optimisation against chloride-laden environments is discussed. It is found that the fineness and purity of adopted metakaolin play important roles. Full article

Striping noise is a common problem in multi-detector scanning radiometers on remote sensing satellites, typically caused by response inconsistency among detector elements. For payloads with a multi-column redundant architecture, this paper proposes a detector-selection framework that jointly considers sensitivity and uniformity from the perspective of detector-element selection to mitigate striping noise. First, the degree of detector consistency is quantified using the Inter-Row Brightness Temperature Difference (IRBTD). Then, a dynamic programming approach based on the Viterbi algorithm is employed to select detector elements row by row with linear time complexity, optimizing the process through a weighted cost function that integrates sensitivity and consistency. Experiments on raw data from the FY-4B Geostationary High-speed Imager (GHI) show that the method reduces inconsistency by 10–40% while increasing the noise-equivalent temperature difference (NEdT) by only 1–4% (≤4 mK). The average IRBTD decreases by approximately 20–100 mK, and high-frequency striping energy is significantly suppressed (reduction of 50–90%). The algorithm exhibits linear time complexity and low computational overhead, making it suitable for real-time on-board processing. Its weighting parameter enables flexible trade-offs between sensitivity and uniformity. By suppressing striping noise directly during the detector-selection stage without introducing data distortion or requiring calibration adjustments, the proposed method can be widely applied to scanning radiometers that employ multi-column long-linear-arrays. Full article

Background and Objectives: The integrated stress response (ISR) is a convergent node in neurodegeneration. We systematically mapped open-access mammalian in vivo evidence for synthetic ISR modulators, comparing efficacy signals, biomarker engagement, and safety across mechanisms and disease classes. Methods: Following PRISMA 2020, we searched PubMed (MEDLINE), Embase, and Scopus from inception to 22 September 2025. Inclusion required mammalian neurodegeneration models; synthetic ISR modulators (eIF2B activators, PERK inhibitors or activators, GADD34–PP1 ISR prolongers); prespecified outcomes; and full open access. Extracted data included model, dose and route, outcomes, translational biomarkers (ATF4, phosphorylated eIF2α), and safety. Results: Twelve studies met the criteria across tauopathies and Alzheimer’s disease (n = 5), prion disease (n = 1), amyotrophic lateral sclerosis and Huntington’s disease (n = 3), hereditary neuropathies (n = 2), demyelination (n = 1), and aging (n = 1). Among interpretable in vivo entries, 10 of 11 reported benefit in at least one domain. By class, eIF2B activation with ISRIB was positive in three of four studies, with one null Alzheimer’s hAPP-J20 study; PERK inhibition was positive in all three studies; ISR prolongation with Sephin1 or IFB-088 was positive in both studies; and PERK activation was positive in both studies. Typical regimens included ISRIB 0.1–2.5 mg per kg given intraperitoneally (often two to three doses) with reduced ATF4 and phosphorylated eIF2α; oral GSK2606414 50 mg per kg twice daily for six to seven weeks, achieving brain-level exposures; continuous MK-28 delivery at approximately 1 mg per kg; and oral IFB-088 or Sephin1 given over several weeks. Safety was mechanism-linked: systemic PERK inhibition produced pancreatic and other exocrine toxicities at higher exposures, whereas ISRIB and ISR-prolonging agents were generally well-tolerated in the included reports. Conclusions: Directional ISR control yields consistent, context-dependent improvements in behavior, structure, or survival, with biomarker evidence of target engagement. Mechanism matching (down-tuning versus prolonging the ISR) and exposure-driven safety management are central for translation. Full article

Chagas disease remains a significant neglected tropical disease that predominantly affects vulnerable populations in rural, low-income areas of Latin America. The management of this condition is severely hindered by the limitations of current therapies, which are characterized by substantial toxicity, diminished efficacy during the chronic phase, and the emergence of parasitic resistance. Given the promising activity of SB-83 (a 2-aminothiophenic derivative) against Leishmania spp., the present study sought to evaluate its trypanocidal activity against Trypanosoma cruzi. The results showed that SB-83 exhibited potent inhibitory effects on the epimastigote forms of T. cruzi (IC₅₀ = 6.23 ± 0.84 μM), trypomastigotes (EC₅₀ = 7.31 ± 0.52 μM) and intracellular amastigotes (EC₅₀ = 5.12 ± 0.49 μM). Furthermore, the cellular proliferation assay results indicated CC₅₀ values of 77.80 ± 2.05 µM for LLC-MK2 CCL-7 and 24.21 ± 1.2 µM for Vero CCL-87, with a selectivity index above 10 for LLC-MK2 cells. In addition, the compound increased TNF-α, IL-12, nitric oxide, and ROS while decreasing IL-10. Moreover, in silico and in vitro assays confirmed its binding to trypanothione reductase, disrupting redox balance. Flow cytometry further revealed apoptosis induction in trypomastigotes, whereas electron microscopy showed cellular disruption and organelle disorganization. Therefore, SB-83 demonstrated potent activity against the TcI-resistant strain linked to Chagas cardiomyopathy at non-toxic concentrations for host cells, supporting its potential as a therapeutic candidate. Full article

This study presents a graph-based framework for improving predictive maintenance in nuclear power plants (NPPs), integrating data balancing techniques with a proposed Graph Attention Network (GAT) with a Mutual k-Nearest Neighbor (Mk-NN) strategy, named GAT-Mk-NN. To enhance the system’s ability to discriminate between genuine faults and sensor anomalies, we introduce a novel procedure for generating synthetic false positives that simulate realistic sensor failures. To mitigate class imbalance, we employ structured oversampling and multiple synthetic data generation strategies. Our results demonstrate that our GAT-Mk-NN model achieves the best trade-off between accuracy and computational efficiency, reaching an F1-score of 0.882 and an accuracy of 0.884. Performance analysis reveals that low to moderate graph connectivity enhances both robustness and model generalization. Our GAT-Mk-NN model structure outperformed other state-of-the-art graph architectures (enhanced GCN, GraphSAGE, GIN, graph transformer, ChebNet, TAG, ARMA graph, simple GCN, GATv2, and hybrid GNN). The findings highlight the potential of graph-based learning for fault detection in sensor-dense industrial environments, offering actionable insights for deploying fault-tolerant diagnostics in critical systems. Full article

Potassium (K) is a vital macronutrient for plant growth and yield, yet most soil K occurs in insoluble mineral forms, limiting availability to crops. Reliance on chemical K fertilizers is unsustainable due to cost and environmental concerns. Microbial solubilization of mineral K, particularly by purple nonsulfur bacteria (PNSB), offers an eco-friendly alternative. This study focused on isolating mica-potassium-solubilizing purple nonsulfur bacteria (MK-PNSB) from in-dyke alluvial soil and assessing their effects on hybrid maize germination and seedling growth. Among the isolates, the results showed that strain M-Wa-19 released the highest amount of soluble K under microaerobic light conditions (27.4 mg∙L⁻¹). Under aerobic dark conditions, M-Wa-24 and M-Wa-26 released 20.1–21.0 mg∙L⁻¹ of soluble K. Strains M-Wa-21, M-Wa-25, and M-Sl-13 solubilized K in the range of 14.3–25.1 mg∙L⁻¹ and 12.9–24.4 mg∙L⁻¹ under both incubation conditions. The selected strains were identified by 16S rRNA as Rhodopseudomonas palustris strain M-Sl-13 (PX588604), Rhodoplanes pokkaliisoli strain M-Wa-19 (PX588605), Afifella marina strain M-Wa-21 (PX588606), Rhodocista pekingensis strain M-Wa-24 (PX588607), Rhodocista pekingensis strain M-Wa-25 (PX588608), and Rhodocista pekingensis strain M-Wa-26 (PX588609). None exhibited toxicity to maize seeds; instead, all enhanced seed vigor indices by up to 99.7% and improved plant height and root biomass by 19.0–26.2% and 14.4–22.9%, respectively, under static hydroponic conditions. At a 1:1000 (bacteria and distilled water) dilution rate, strains M-Wa-26, M-Wa-25, M-Sl-13, M-Wa-24, M-Wa-19, and M-Wa-21, along with the six-strain mixture, improved seed vigor index by 3.96–7.91%. These findings suggest that MK-PNSB, individually or in mixtures, hold promise as biofertilizer candidates for sustainable K management in crop production. Full article

With the depletion of shallow coal resources, deep extra-thick coal seam mining has become vital for energy security, yet fully mechanized top-coal caving (FMTC) goaf-side roadways face severe challenges of excessive advanced deformation and intense strata behavior. To address this gap, this study took the 4301 tailgate of a coal mine in Shaanxi province as the engineering background, integrating field investigation, theoretical analysis, FLAC^3D numerical simulation, and industrial tests. Guided by the key stratum theory, we systematically analyzed the influence of overlying key strata fracture on strata pressure. The results show three key strata: near-field secondary key strata (KS1, KS2) with “vertical O-X” fracturing and far-field main key stratum (MKS) with “horizontal O-X” fracturing. The radial extrusion force from MKS rotational blocks is the core cause of 200 m range advanced deformation. A collaborative control scheme of near-field key strata directional fracturing roof-cutting pressure relief and high-strength bolt-cable support was proposed. Industrial verification indicates roadway deformation was significantly reduced, with roof subsidence, floor heave, and rib convergence controlled within safe engineering limits. This study fills the gap of insufficient research on far-field key strata’s impact, providing a reliable technical solution for similar extra-thick coal seam FMTC goaf-side roadway surrounding rock control. Full article

Adiabatic demagnetization refrigeration (ADR) is regaining relevance for refrigeration to temperatures below 1 K as global helium-3 supply is increasingly strained. While ADR at these temperatures is long established with paramagnetic hydrated salts, more recently, frustrated rare-earth oxides were found to offer higher entropy densities and practical advantages, since they do not degrade under heating or evacuation. We report structural, magnetic, and thermodynamic properties of the rare-earth borates Ba₃XB₉O₁₈ and Ba₃XB₃O₉ with X = (Yb, Gd). Except for Ba₃GdB₉O₁₈, which orders at 108 mK, the three other materials remain paramagnetic down to their lowest measured temperatures. ADR performance starting at 2 K in a field of 5 T is analyzed and compared to literature. Full article

This study proposes a data-driven framework for predicting forming limit diagrams (FLDs) of AA7075-T6 aluminum sheets under various temperatures and strain rates. To overcome the limitations of costly and time-consuming experiments, a hybrid dataset combining experimental results and virtual data from rate-dependent crystal plasticity finite element (CPFE) simulations coupled with the Marciniak–Kuczyński (M–K) model was developed. Several machine learning (ML) models—including linear regression (LR), random forest regression (RFR), support vector regression (SVR), Gaussian process regression (GPR), and multilayer perceptron (MLP)—were trained to predict FLDs. The nonlinear dependence of the FLD on temperature and strain rate was accurately captured by the ML models, with nonlinear algorithms demonstrating notably improved predictive performance. The proposed approach offers an efficient, accurate, and cost-effective method for FLD prediction and supports data-driven process design in lightweight alloy forming. Full article

N₂-fixing bacteria have great potential to be used as biofertilizer in agriculture to promote plant growth via nitrogen fixation. In this study, a novel species Fontibacillus forbon sp. nov., with strain BL-9^T as the type strain, was isolated from the rhizosphere of Fraxinus chinensis. Strain BL-9^T was able to fix nitrogen and grow on nitrogen-free medium. Phylogenetic analysis of 16S rRNA gene revealed that strain BL-9^T was most closely related to Fontibacillus phaseoli BAPVE7B (98.03%), followed by Fontibacillus solani A4STR04 (96.72%), Fontibacillus panacisegetis (96.6%), Paenibacillus vini (96.6%), and Paenibacillus segetis DB13260 (96.57%). The phylogenomic tree supported that strain BL-9^T was most closely related to F. phaseoli BAPVE7B. The digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) between strain BL-9^T and its closely related type strain, F. phaseoli BAPVE7B, were 42.5% and 90.94%, respectively, which were below the values (70% for dDDH and 95% for ANI) for species discrimination. The DNA G+C content of strain BL-9^T was 49.7%. The genome of strain BL-9^T had a nif (nitrogen fixation) gene cluster containing 10 genes (nifB nifH nifD nifK nifE nifN nifX orf1 hesA nifV). The predominant fatty acid was anteiso-C15:0, the major menaquinone was MK-7, and the major polar lipid was diphosphatidylglycerol. Strain BL-9^T and its closely related species of Fontibacillus had some common and distinguished physiological characteristics. Based on genomic, phylogenetic, chemotaxonomic, and phenotypic features, strain BL-9^T represents a novel species of the genus Fontibacillus. The name proposed for this species is Fontibacillus forbon sp. nov., with the type strain BL-9^T. Full article

Background: Epidermal growth factor receptor (EGFR)-targeted tyrosine kinase inhibitors (TKIs) have exhibited efficacy in EGFR-mutant non-small cell lung cancer (NSCLC) patients. However, the response is modest in patients with wild-type (wt)-EGFR, and approximately 30–40% of patients develop TKI resistance. Recently, a role for BRG1 (SMARCA4) in regulating gene expression and its frequent alteration in various cancers, including NSCLC, has been reported. Yet, its specific function in response to EGFR-TKI therapy remains elusive. Herein, we investigated the role of BRG1 in EGFR-TKI response in vitro and in vivo using lung cancer models. Methods: In vitro, A549, H358, and HCC827 cell lines that varied in their EGFR and BRG1 status were assessed for response to EGFR-TKI upon overexpression or gene silencing of BRG1 through cell viability, cell migration, and Western blotting assays. In vivo, A549 and H358 tumor xenografts that overexpressed BRG1 or had BRG1 silenced were investigated for tumor growth response to EGFR-TKI. Results: EGFRwt/BRG1mt (A549) cells were resistant to TKI, and restoration of wt-BRG1 expression reverted them to TKI sensitivity both in vitro and in vivo. In contrast, silencing of BRG1wt in H358 cells showed a tendency toward TKI resistance. Additionally, wt-EGFR and pAKT^Ser473 protein complex formation in A549 cells was disrupted with an AKT inhibitor (MK2206), resulting in enhanced cytotoxicity in vitro. Conclusions: Our study demonstrates that EGFR-TKI response in wt-EGFR cells is dictated by BRG1 status. These findings propose screening of wt-EGFR NSCLC patients for BRG1 status for identifying individuals likely to benefit from EGFR-TKI therapy versus patients who will benefit from AKT inhibitor treatment. Full article

Formal verification has achieved remarkable outcomes in both theory advancement and engineering practice, with the formalization of mathematical theories serving as its foundational cornerstone—making this process particularly critical. Axiomatic set theory underpins modern mathematics, providing the rigorous basis for constructing almost all theories. Landau’s Foundations of Analysis starts with pure logical axioms from set theory, does not rely on geometric intuition, strictly constructs number systems, and is a benchmark for axiomatic analysis in modern mathematics. In this paper, we first develop a machine proof system for axiomatic set theory rooted in the Morse–Kelley(MK) system. This system encompasses effective proof automation, scale simplification, and specialized handling of the classification axiom for ordered pairs. We then prove the Transfinite Recursion Theorem, leveraging it to further prove the Recursion Theorem for natural numbers—the key result for defining natural number operations. Finally, we detail the implementation of a machine proof system for analysis, which adopts MK as its description language and adheres to Landau’s Foundations of Analysis. This formalization realized all the contents of the book from natural numbers to complex numbers. All formalization does not need to introduce the standard library and has undergone verification by Rocq(Coq) 8.16 to ensure reliability. Implemented using the Rocq proof assistant, the formalization has undergone verification to ensure reliability. This work holds broader applicability such as the formalization of point-set topology and abstract algebra, while also serving as a valuable resource for teaching axiomatic set theory and mathematical analysis. Full article

Climate change and river flow alterations in the Mekong River have significantly exacerbated drought conditions in the Vietnamese Mekong Delta (VMD). Understanding the temporal dynamics and propagation mechanisms of drought, coupled with the compounded impacts of human activities, is crucial. This study analyzed meteorological (1992–2021) and hydrological (2000–2021) drought trends in the Lower Mekong River Basin (LMB) using the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI), respectively, complemented by Mann–Kendall (MK) trend analysis. The results show an increasing trend of meteorological drought in Cambodia and Lao PDR, with mid-Mekong stations exhibiting a strong positive correlation with downstream discharge, particularly Tan Chau (Pearson r ranging from 0.60 to 0.70). A key finding highlights the complexity of flow regulation by the Tonle Sap system, evidenced by a very strong correlation (r = 0.71) between Phnom Penh and the 12-month SDI lagged by one year. Crucially, the comparison revealed a shift in drought severity since 2010: hydrological drought has exhibited greater severity (reaching severe levels in 2020–2021) compared to meteorological drought, which remained moderate. This escalation is substantiated by a statistically significant discharge reduction (95% confidence level) at the Chau Doc station during the wet season, indicating a decline in peak flow due to upstream dam operations. These findings provide a robust database on the altered hydrological regime, underlining the increasing vulnerability of the VMD and motivating the urgent need for comprehensive, adaptive water resource management strategies. Full article

Wood biomass ash (WBA) is a by-product from biofuel energy plants. The disposal of this waste is connected with numerous environmental concerns. A more sustainable choice is to recycle it as a raw material for building and construction materials. However, due to its unstable characteristics, its application in alkali-activated materials (AAM) poses a challenge. One issue is the development of the mechanical properties. To improve them, pozzolanic additives, including coal fly ash (CFA), metakaolin (MK), and natural zeolite (NZ), were added at replacement ratios of 10–40%. Calcium hydroxide, sodium hydroxide, and sodium silicate were used together as ternary activators. The samples were cured at 60 °C for the first 24 h and for the remaining 27 days at room temperature. Mechanical behavior, water absorption, and chemical compositions were examined. The results obtained from XRF were compared with the calculation results of the chemical compositions based on the mix design and oxide compositions of the raw materials. The results show that the respective optimum replacement ratios were 30% CFA, 20% MK, and 20% NZ, with the highest compressive strength corresponding to 22.71, 20.53, and 24.33 MPa, and the highest flexural strength of 4.49, 4.32, and 4.21 MPa. NZ was the most effective in AAM, due to the highest Si/Al ratio in the Ca-rich ambient. Then, CFA contributed less, and MK was the least efficient when used in combination with WBA in AAM. The reduction of Ca/Si ratios in the AAM caused by the pozzolanic additives favors the formation of a binder system made of different hydrates and facilitates the strength enhancement when the Ca/Si ratio is lower than 0.35. Full article

Second cheese whey (SCW), a major by-product of ricotta cheese production, poses significant environmental challenges due to its high organic load. Biohydrogen (bio-H₂) and poly-β-hydroxybutyrate (PHB) production offer a sustainable reuse of SCW, that provides ideal nutrients for microbial growth. This study aimed to convert SCW into Bio-H₂ and PHB using a 5-liter tubular bioreactor in a sequential lactic fermentation and photofermentation system. Two lighting conditions were tested: white LED (WL) and selected LED (SL). Optimal results were achieved with a co-inoculum of Lactococcus lactis MK L84 and Lacticaseibacillus paracasei MK L49 at pH 4.5–5.5, followed by photofermentation with Rhodopseudomonas palustris 42OL under SL condition. The process yielded an average of 0.47 L of H₂ per liter of substrate and 1.66% wPHB/wCDW. This approach successfully transformed dairy waste into high-value products, promoting circular economy principles. Full article