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Mineralogical imprints of earthquake activity in sedimentary structures
Abstract Seismic activity can leave distinct imprints in sediments; however, the geochemical and mineralogical conditions controlling sediment liquefaction and deformation remain incompletely understood. Here, we present a comprehensive study combining laboratory experiments and field samples to investigate the formation of seismically-induced structures, with a particular focus on sideritic and core-rim features. Core-rim structures (CRS) were consistently identified across all experimental and field conditions subjected to shocks, independent of the degree of water mineralization, the presence of iron compounds, or experimental duration. The observations suggest that their formation is largely controlled by physical processes during seismic events, indicating that CRS may represent a potentially indicator of seismic activity in unconsolidated sediments. Additionally, variations in their morphology and elemental distribution appear to reflect fluid flow pathways, providing insights into fluid redistribution during seismic deformation in the field. Sideritic structures, observed exclusively in field samples and laboratory variants with FeO(OH), displayed ring-like morphologies and were primarily composed of FeO and carbonate minerals. Multivariate statistical analyses, including cluster and principal component analysis (PCA), revealed strong similarities between these environments, pointingto comparable geochemical conditions during their formation. Overall, this studydemonstrates the value of integrating experimental and field-based approachesto improve our understanding of seismic deformation processes. Core-rim and sideritic structuresmay contribute useful evidencefor interpreting past seismic events and for refining criteriaused to identify seismites and reconstruct fluid migration patterns in sedimentary systems.
Statistical models to characterize colon tumor stiffness heterogeneity through representative atomic force microscopy maps
Construct validity of real-world digital mobility outcomes in patients after proximal femoral fracture: a cross-sectional observational study
Abstract Digital mobility outcomes (DMOs) offer unique insights into recovery of real-world mobility after proximal femoral fracture (PFF), but their clinical validity remains to be established. This study assessed construct validity (convergent, divergent, and known-groups) of 24 DMOs measuring walking activity (amount, pattern) and gait (pace, rhythm, bout-to-bout variability) in patients within one year after PFF. Patients were recruited from inpatient and outpatient lists at five European sites, resulting in 505 included participants (66% female), with mean age of 77.6 ± 9.4 years and supervised gait speed of 0.7 ± 0.4 m/s. Mobility was monitored over seven days using a single wearable device on the lower back. Convergent and divergent validity analyses were stratified by two groups: acute (≤ 14 days since surgery) and non-acute (≥ 15 days since surgery). Correlations between DMOs and related (clinical- and patient-reported mobility outcomes) and unrelated constructs (hearing impairment and systolic blood pressure) were compared to a priori expected correlations. Known-groups validity was assessed across four recovery phases. The results were evaluated individually by experts and in a subsequent consensus meeting, with 17 of 24 DMOs showing evidence of construct validity in non-acute PFF patients. These findings represent an initial step in a larger process towards regulatory endorsement.
ZIF-8 functionalized PCL/BG composite scaffolds with improved bioactivity and osteogenic differentiation
High refractive index microlenses patterned onto micro-LED arrays using electrohydrodynamic inkjet printing
A computational analysis of biophysical and geometric constraints refutes existing hypotheses of cross-excitation in dorsal root ganglia
Medium -term monitoring and machine learning-based forecasting of drought dynamics in Iran
Macroscopic polarimetric discrimination and quantification of antiangiogenic effect of AGRO aptamer and GK1 peptide in a preclinical melanoma model
Macrophages recruited by implanted fibrin gels promote regeneration of injured lymphatic vessels
Threat and blame frames in political rhetoric about societal issues lead to neural and political polarization
Abstract Online content about societal issues like climate change and immigration are often presented via frames of threat and blame. Here, we investigated how exposure to such framing in the context of an online short video-clip impacts voting behavior and associated brain activity. In a large-scale online study of 1825 Dutch participants, we found that online threat and blame framed video-clips increased agreement with the clips themselves but decreased issue voting, that is, voting in line with the intensity of one’s political beliefs. A follow-up fMRI study with 27 participants replicated this behavioral finding. It also showed that video-clips with threat- or blame-frames, compared to neutral video-clips, were represented more dissimilarly across participants in the dorsolateral prefrontal cortex (DLPFC)—a region involved in narrative understanding. These findings suggest that subtle framing of online political content can influence voter decisions and even the fundamental act of communication itself within a society.
Mechanistic insights and by-product analysis in sonocatalytic degradation of Orange-G dye molecule via potassium persulfate
Application of diamondoids in source and maturity evaluation of light oil: a case study from the Kuqa Depression of the Tarim Basin, NW China
Abstract Determining the origin of light oil presents a significant challenge due to the diversity of genetic types and the limitation of conventional biomarkers. Diamondoid hydrocarbons, characterized by their thermal stability and enrichment in high maturity oil, are considered effective indicators for elucidating generation mechanisms and secondary alteration processes of light oils. In this study, the diamondoid distributions are examined in light oil samples from various regions (i.e., Wushi, Bozi, Dabei, Keshen, Kela, Dina, Dibei, Tuzi, Tudong, Yangtake, Yingmai, Hongqi, and Yaha) in the Kuqa Depression of the Tarim Basin, Northwest China, to discern the origin of the oils. Diamondoids concentrations and ratios in the Kuqa oils show significant variations, indicating two dominant source rock types and various maturity levels. Total diamondoid concentrations (including adamantanes, diamantanes, and triamantanes) vary from 141 to 19,137 ppm. Notably, the light oils from the Kela and Tuzi regions exhibit unusually high diamondoid concentrations (> 9000 ppm), while those from Yingmai, Hongqi, Yaha, Wushi, Keshen, and Tudong regions have relatively lower concentrations (< 2000 ppm). Employing our previously developed source facies discriminant model based on multivariate statistical analysis of multiple diamondoid indices, we suggest that the light oils from the Kela, Keshen, Yangtake, and Yaha regions are originated from lacustrine shales. In contrast, the other studied samples are inferred to primarily derive from coaly source rocks. Meanwhile, our maturity prediction model indicates that the maturity of the Kuqa oils ranges from 0.81 to 2.44 EASY%Ro. The highest maturity is found in the Kela light oils (2.3–2.5 EASY%Ro), while the lowest maturity is observed in the samples from the Wushi, Yingmai, and Hongqi areas (0.8–1.1 EASY%Ro). The formation mechanisms for some samples with anomalous diamondoid distributions are also explored. The Kela light oils, distinguished by their high maturity, abundant diamondoids, and relatively high biomarker concentrations, demonstrate a mixed origin with a notable contribution from highly mature condensates derived from the maturation of lacustrine kerogens. The Tuzi coal-derived oils, exhibiting moderate maturity (1.25% EASYRo) and characterized by elevated adamantane concentrations coupled with inconsistently relatively lower diamantane concentrations, are inferred to be condensates underwent evaporative (or migration) fractionation during upward migration from deeper reservoirs. Our findings corroborate the potential application of diamondoids as previously suggested. In summary, the diamondoid hydrocarbons provide a robust methodology for elucidating the origins, thermal maturity, and formation mechanisms of light oils, particularly within highly mature systems.
Soil dynamics and ecotoxicity of zinc extracted from black mass derived from discarded batteries
Development and validation of green spectrophotometric methods for simultaneous determination of etoricoxib and tramadol
A comprehensive assessment of solar still productivity enhancement using novel wick and energy storage material
Global climatology of submesoscale restratification using machine learning
Abstract Submesoscale eddies are important in setting the stratification in the ocean surface mixed layer and transporting energy between large and small scale motions. However, the study of submesoscale on a global scale has been hindered by a shortage of global, long-term datasets. To meet this need, we apply an unsupervised machine learning method adapted from the profile classification model (PCM) to density profiles collected by Argo floats over the global ocean from 2000-2021, producing the first global observational climatology of submesoscale restratification. The method classifies individual vertical profiles based on the shape of the density profile in the ocean surface mixed layer. The fraction of profiles that exhibit a shape characteristic of submesoscale is referred to as the submesoscale restratification (SR) index. The SR index peaks in spring in both hemispheres and lags the maxima of mixed layer depth by one month, suggesting that submesoscale eddies play an important role in restratifying the mixed layer. Hotspots of SR index can be found in the Norwegian Sea and the Drake Passage in spring. This method enables the study of the spatial and temporal distributions of submesoscale restratification on a global scale.
Electrochemical determination of dihydroxybenzene isomers utilising poly-L-cystine-AgTiCrO2 nanohybrids
Sampled-data control under time-varying delays: a robust approach for high-renewable smart grids
Abstract The increasing reliance on inverter-based renewable energy sources in smart grids makes closed-loop stability highly sensitive to communication-induced uncertainties, including time-varying delays, sampling jitter, and packet loss. Conventional sampled-data and delay-dependent controllers typically address these impairments in isolation or rely on conservative worst-case designs, limiting their effectiveness under dynamically changing communication quality. This paper proposes a robust adaptive sampled-data control framework that explicitly links communication degradation to control-layer adaptation while preserving tractable stability guarantees. A bounded delay–jitter intensity index, $$\theta _k \in [0,1]$$ , is introduced as an online-measurable proxy for communication quality and is used to schedule the feedback gain in real time. Stability is rigorously certified using a delay-weighted Lyapunov–Krasovskii functional and affine Linear Matrix Inequality (LMI) conditions verified at the admissible uncertainty endpoints, ensuring exponential stability under the combined effects of delay, jitter, and packet loss. The proposed approach is validated on a hybrid renewable microgrid with inverter-based distributed energy resources under stochastic communication impairments. Across multiple scenarios—including bounded delay, high jitter, and 10% packet loss–the adaptive controller reduces settling time by up to 33%, overshoot by 52%, and control-related energy cost by 40% compared to fixed-gain and worst-case robust baselines. In addition, cyber-aware operational reliability metrics confirm consistent preservation of admissible operating margins under degraded communication conditions. These results position the proposed method as a stability-certified control-layer complement to cyber-resilient and data-driven smart grid architectures, enabling reliable operation of high-renewable grids under realistic communication constraints.