Browse Articles

MicroCT analysis of the magma-to-mush transition in the 1959 Kīlauea Iki lava lake

Abstract The 1959 Kīlauea Iki eruption emplaced olivine-rich lava into a pre-existing pit crater to form a closed-system lava lake. It was drilled multiple times over the next 29 years, presenting a rare opportunity to study cumulate formation. We quantify olivine content and connectivity through the cumulate and overlying olivine-depleted zone by training deep learning segmentation models on µCT scans of quenched drill cores. In the cumulate, olivine approaches full connectivity at crystal fractions of 25–35 vol%, as predicted by percolation simulations. The depth interval over which the cumulate becomes interconnected aligns with geochemical evidence for diapiric extraction of ~ 30 wt% buoyant interstitial melt and resulting cumulate densification. We suggest, therefore, that early compaction of a deformable crystal network was driven primarily by cooling and crystallization rather than by the weight of overlying crystal mush. Early connectivity and crystal repacking, combined with basal cooling accelerated by foundered crust, explain the peak of olivine content toward the top of the cumulate zone, in contrast to basal olivine accumulation in mafic sills of similar thickness. Early connectivity development also provides an explanation for observed propagation of S-waves through the lava lake’s melt-rich (45% liquid) core in 1976.

Combined mesenchymal stem cells and metformin therapy modulates key macromolecular pathways in pulmonary fibrosis based on evidence from untargeted metabolomics

Abstract Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease with limited therapeutic options, highlighting the need for novel interventions. Mesenchymal stem cells (MSCs) possess immunomodulatory and regenerative capacities, while metformin, a widely used antidiabetic agent, has recently shown anti-fibrotic potential through metabolic reprogramming. Metabolomic profiling offers a comprehensive approach to elucidate disease-associated biochemical alterations and therapeutic mechanisms. In this pilot study, bleomycin-induced pulmonary fibrosis in rats was treated with MSCs, metformin, or their combination. Untargeted LC-MS-based metabolomics of plasma and lung tissue, alongside histopathological evaluation, revealed that combination therapy most effectively corrected metabolic disruptions and attenuated fibrotic remodeling. Histology confirmed marked reductions in alveolar wall thickening, collagen deposition, and fibroblastic foci in the combination group compared to monotherapies. Metabolite changes in lung tissue included sphingosine (lipid metabolism), 5-hydroxyindoleacetic acid (serotonin turnover), cyclic GMP (nitric oxide signaling), and 4-guanidinobutanoic acid (arginine/creatine metabolism). Plasma regulation involved corticosterone (steroid biosynthesis), PC (18:2/18:2) (phospholipid remodeling), methionine (methylation balance), galactose 1-phosphate (carbohydrate metabolism), and niacinamide (NAD⁺ biosynthesis). These findings provide preliminary evidence that combined MSCs–metformin therapy synergistically ameliorates fibrosis and metabolic dysregulation, while identifying metabolites that may serve as potential biomarkers for disease progression and therapeutic response.

Harnessing salt slag and diatomite sludge by co-recycling for zeolite production

Thermal and tribological performance of LM30-corundum aluminum matrix composites for automotive brake rotors

LG-RSD: local–global region self-distillation for robust SAR ship detection

Neuroinflammation promotes the development of pharmacoresistant epilepsy by triggering the MSK1/CREB signaling pathway

Fluid dynamics reduction methods for temporal networks

Abstract Temporal networks, defined as sequences of time-aggregated adjacency matrices, sample latent graph dynamics and trace trajectories in graph space. By interpreting each adjacency matrix as a different time snapshot of a scalar field, we show how fluid-mechanics methods can be applied to construct two distinct eigendecompositions of temporal networks. The first builds on the proper orthogonal decomposition (POD) of flowfields and decomposes the evolution of a network in terms of a basis of orthogonal network eigenmodes which are ordered in terms of their relative importance, hence enabling compression of temporal networks as well as their projection in low-dimensional embeddings. The second proposes a numerical approximation of the Koopman operator, a linear operator acting on a suitable observable of the graph space which provides the best linear approximation of the latent graph dynamics. Its eigendecomposition provides a data-driven spectral description of the temporal network dynamical stability, in terms of dynamic modes which grow, decay or oscillate over time. We illustrate and validate the application of both eigendecompositions in a suite of synthetic generative models of temporal networks with varying complexity.

Facial emotion-based movie recommendation system using optimized compound scaling neural network with polynomial and RBF kernels

From toxicity to conformity: adaptive user behavior to social norms in Telegram communities

Abstract Toxic and antisocial user behavior on social media platforms has received considerable scholarly attention due to its detrimental effects on society. This study takes a holistic perspective on the phenomenon of online toxicity by investigating the impact of local community norms on toxic expression. By using six large-scale datasets, comprising over 500 million Telegram messages collected between 2015 and 2024, we analyze toxic user behavior across multiple chats and languages. We introduce a methodological framework that uses a conformity index to characterize conformist, anti-conformist, and independent behavioral tendencies. Our findings show that most users tend to conform to local normative environments, aligning their toxicity with the toxicity levels of the chats in which they participate. This pattern is consistent across datasets and languages, showing a strong association between community norms and user behavior online. Furthermore, we observe that higher levels of user participation in chats are associated with a stronger tendency toward conformity with the surrounding social contexts. Collectively, these findings contribute to a deeper understanding of toxic online behavior and highlight the importance of contextualized approaches to content moderation.

RSM optimization of efficient phenol adsorption using a novel magnetic biochar/Ca-Al-Fe LDO nanocomposite

Association of EEF1A1 and linc00993 expression with sperm morphology in teratozoospermia: an integrative in silico and in vitro study

Heterogeneity of depression and suicidal ideation among college students in Eastern China: a latent profile analysis and machine learning approach

Evolutionary game and simulation analysis of collaborative governance of sports public opinion

Breathing bad: increased risk for obstructive sleep apnea in current and former smokers

Abstract Obstructive sleep apnea (OSA) and smoking are both prevalent and impactful health risks. While smoking may contribute to OSA through inflammatory and neuromuscular pathways, population-based evidence on this relationship remains limited and inconsistent. A sample ( N  = 1,206) from the population-based Study of Health in Pomerania with complete overnight polysomnography and smoking assessment was investigated in a cross-sectional study for an association between OSA and former as well as recent smoking status. Regression models adjusted for Age and BMI were applied. Current smoking was significantly associated with increased apnea-hypopnea-index (AHI) severity (OR = 1.75, 95% CI [1.27; 2.41], p < .001), with stratified analyses confirming the effect across younger and older participants. Former smokers also showed significantly elevated AHI severity compared to never-smokers (OR = 1.76, 95% CI [1.27; 2.43], p < .001). Both current and former smoking were significantly associated with greater OSA severity in this population-based sample, even after accounting for age and BMI. The findings underscore the long-term respiratory consequences of smoking and highlight the need for integrated approaches in smoking cessation and OSA screening.

IST: an ontology-guided attention-based autoencoder for interpretable analysis of single-cell transcriptomic data

Optoelectronic microwave oscillator based on integrated Si-ITO plasmonic modulator

Hemodynamic effect of coil packing density after tubridge flow diverter for anterior circulation small and medium-sized aneurysms

Abstract Investigating the impact of coil embolization rate on hemodynamic parameters within the aneurysm sac after treating anterior circulation small and medium-sized aneurysms with the Tubridge (TB) flow diverter. Twenty-six patients with 29 intracranial aneurysms were collected between September 2020 and December 2022. The finite element method simulated preoperative conditions, after TB deployment alone, and with TB plus different coil embolization rates. Different hemodynamic parameters were analyzed under these treatment scenarios. Variance analysis and multiple comparisons were conducted to find an appropriate embolization rate. Twenty-nine aneurysms from 26 patients showed, with increasing TB deployment and coil embolization rates, a continuous improvement in the aneurysm sac’s Qinflow, Va, WSS, and normalized and ratio residual blood volume (nRFV and rRFV) under different thresholds (0.1 m/s, 0.15 m/s). Quantitative analysis indicated the impact on hemodynamics was not significant ( P  > 0.05) when the coil embolization rate reached 5% and beyond for Qinflow, Va, WSS, and RFV under different thresholds (0.1 m/s, 0.15 m/s). Adjunctive embolization can improve the hemodynamic environment within the small and medium-sized aneurysm sac when using the Tubridge flow diverter. However, once the embolization rate within the sac reaches 5%, the hemodynamic environment tends to stabilize, making dense embolization unnecessary.

Accurate and robust ambiguity detection in software requirements documents using a GloVe-BiLSTM deep learning framework with data augmentation

Protium heptaphyllum, a tree native to the Atlantic Forest, is a potential source of compounds against important cocoa phytopathogen

Bull’s-Eye for Athletes (BEA): a measure of values-based behavior in sport and a psychometric evaluation using Rasch analysis

Abstract Working with values and values-based behavioral change in psychological interventions for athletes has become more common in sport psychology, but measures adapted for the sport context are needed. A new instrument based on the Bull’s-Eye Values Survey, called Bull’s-Eye for Athletes (BEA), was developed and adapted to assess values and values-based behavior in athletes. BEA consists of four values items, (1) Competition, (2) Training, (3) Preparation and recovery, and (4) Life outside of sport. Athletes identify their values and rate their behavioral commitment for each value item and to what extent they experience obstacles behaving according to their values, both related to their sport and life outside of sport. BEA was completed online by 155 athletes in Sweden competing at junior elite to senior international level. Scale dimensionality, invariance, monotonicity of response categories, and reliability were investigated using Rasch analysis. Convergent and discriminant validity was also investigated through correlation with other scales. Results indicated that BEA worked as a unidimensional scale with satisfactory psychometric properties. Item probability functions were investigated, and response categories were merged to achieve ordered item thresholds. No indication of invariance was found through differential item functioning (DIF) analyses for demographic (age, sex) or sport-related variables (competitive level, sport type, or current injury), nor for temporal stability of item properties through test-retest. Convergent and discriminant validity was supported by medium correlations with psychological inflexibility in athletes, general valued living, life satisfaction, subjective performance, and a few subtypes of performance anxiety and sport motivation. BEA is a promising instrument for measuring and working with values and values-based behavior in sport. Response categories were merged for two items (competition and training) to achieve ordered item thresholds. Labeling of the instrument’s response categories could be a potential improvement for BEA to be investigated. Further investigations are needed across various sports contexts with larger sample sizes, as well as evaluations of its usefulness in longitudinal designs in sport psychological intervention research as a measure of self-reported behavioral change.