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Study on the chirality of gyroid photonic crystals in butterfly wing scales
Abstract Some brilliantly colored butterflies are known to possess gyroid photonic crystals in the wing scale. As the gyroid structure is inherently chiral, it is an intriguing question whether the structure has enantiomeric purity or not, considering that biomolecules exhibit homochirality. It has been previously reported for a few lycaenid species that both enantiomeric forms of the gyroid structure are found in multidomain photonic crystals. In this study, we evaluated the chirality of gyroid crystals in the wing scales of the papilionid butterfly Teinopalpus imperialis and found only one enantiomeric form (LH-type) in more than 200 gyroid crystals examined. In another papilionid butterfly, Parides sesostris, the populations of the two enantiomeric forms were found to be highly unbalanced. Because the gyroid crystals of these two butterflies are known to have a strong orientation preference along the surface normal of the scale, we suggest that crystal orientation-controlled development is related to chirality selection. Our findings provide insights into chirality-selected gyroid synthesis in self-organization processes.
PMSM sensorless control based on super-twisting algorithm sliding mode observer with the IAORLS parameter estimations
Antibiofilm efficacy of emodin alone or combined with ampicillin against methicillin-resistant Staphylococcus aureus
Abstract Methicillin-resistant Staphylococcus aureus (MRSA) is recognized as a significant global health concern. The development of resistance to a broad spectrum of antibiotics, particularly following biofilm formation, renders conventional therapeutic options for MRSA ineffective. Three MRSA clinical isolates were examined in vitro to assess their biofilm-forming capacity and the disruptive effects on pre-established biofilm (via crystal violet staining and scanning electron microscopy), and quantify extracellular DNA (eDNA) release after exposed to emodin alone or in combination with ampicillin. In addition, real-time PCR was employed to investigate the impact of emodin on the expression of biofilm-related genes in MRSA biofilms. The inhibitory effect of emodin on biofilm formation and disruption was observed in a dose dependent manner. The antagonistic activity of emodin in combination with ampicillin against MRSA biofilms was confirmed through adhesion assays. Real-time PCR analysis revealed that emodin, either alone or in combination with ampicillin, effectively downregulated the transcriptional levels of the biofilm-related genes fnbpB , clfA and atlA , but not icaA . In addition, drug treatment resulted in a significant reduction in eDNA release and protein contain in EPS (extracellular polymeric substances), which corresponded to the markedly decreased transcript level of atlA and fnbpB , respectively. These observations suggest that emodin, either alone or in combination with ampicillin, holds potential as a therapeutic approach for MRSA biofilm-related infections.
Upcoming FDA approval decisions in Q3 2025
BHGNN-RT: Capturing bidirectionality and network heterogeneity in graphs
Graph neural networks (GNNs) have shown great promise for representation learning on complex graph-structured data, but existing models often fall short when applied to directed heterogeneous graphs. In this study, we proposed a novel embedding method, a bidirectional heterogeneous graph neural network with random teleport (BHGNN-RT) that leverages the bidirectional message-passing process and network heterogeneity, for directed heterogeneous graphs. Our method captures both incoming and outgoing message flows, integrates heterogeneous edge types through relation-specific transformations, and introduces a teleportation mechanism to mitigate the oversmoothing effect in deep GNNs. Extensive experiments were conducted on various datasets to verify the efficacy and efficiency of BHGNN-RT. BHGNN-RT consistently outperforms state-of-the-art baselines, achieving up to 11.5% improvement in classification accuracy and 19.3% in entity clustering. Additional analyses confirm that optimizing message components, model layer and teleportation proportion further enhances the model performance. These results demonstrate the effectiveness and robustness of BHGNN-RT in capturing structural, directional information in directed heterogeneous graphs.
Different effects of verbal and visual working memory loads on Language prediction
Abstract Mounting studies suggest that working memory (WM) plays a crucial role in language prediction, but how varying types of WM loads influence language prediction remains unclear. This study investigated whether verbal and visual WM loads differentially impact language predictions during speech comprehension. Using a dual-task paradigm combined with eye-tracking in a visual world setting, we asked 48 participants to complete a sentence comprehension task under concurrent WM load conditions. Participants were divided into two groups, one of which performed a visual dots memory task and the other completed a visual words memory task, with memory load being applied in half of the trials. Results revealed anticipatory gaze towards target objects, suggesting the prediction of upcoming linguistic information. Notably, early fixations during the tonal cue window indicated tonal prediction in spoken sentence processing. Furthermore, WM load significantly disrupted participants’ language prediction effects, highlighting the involvement of working memory resources in this process. Importantly, the verbal memory task imposed a more severe disruption to language prediction than the visual memory task, suggesting differential roles of WM subtypes in linguistic prediction. This offers novel insights into how verbal WM and visual-spatial WM differentially influence predictive language processing.
Specific energy reduction in a semi-autogenous grinding mill circuit by an automatic control system
Abstract Grinding operations, especially those involving semi-autogenous mills, account for a significant portion of energy use in mineral processing. In this work, we describe the application of an advanced regulatory control strategy in a copper plant aimed at improving energy efficiency through automation. The system combines cascade and feedforward control structures to attenuate variations in the mill load, a key factor influencing energy consumption and process stability. The control scheme was integrated into the plant’s existing automation infrastructure and evaluated through a three-month industrial trial. By shifting from manual to automatic regulation of the feed rate, the plant reduced the influence of process disturbances and maintained more consistent operation. The automated system achieved a 5.84% reduction in specific energy consumption and a 1.90% increase in productivity. These results demonstrate the potential of enhanced regulatory control to deliver measurable performance gains with minimal changes to existing operations.
Deep quanvolutional neural networks with enhanced trainability and gradient propagation
The influence of attachments on the adaptability and quality of life of patients using Invisalign
Circulating amino acids and cardiometabolic risk profile in offspring of women with type 1 diabetes: cross-sectional case-control study
Abstract Branched-chain amino acids (BCAAs) are known to be associated with cardiovascular disease risk in adults. The aim of this study is to investigate whether an increased cardiometabolic risk profile can be observed in the amino acid profile of young adult offspring of women with type 1 diabetes. This cross-sectional case-control study included 73 offspring born to women with type 1 diabetes (cases) and 82 control participants (controls). At the age of 18–23 years, they participated in a clinical assessment including laboratory tests and questionnaires. Amino acid levels were analyzed from venous serum samples after 10 h of fasting using nuclear magnetic resonance (NMR) spectroscopy. No differences in cardiovascular disease or cardiometabolic risk factors were observed between the cases and the controls. Circulating amino acid levels were similar in both groups. The glucogenic score (combined alanine, glycine) was higher in overweight case men (case versus controls adjusted p = 0.015 (mean ratio 1.25 [95% CI 1.11 to 1.49]). The present findings do not support our hypothesis that serum amino acid profiles, determined in early adulthood, are associated with a more adverse cardiometabolic risk profile in offspring of women with type 1 diabetes. Further studies are warranted to clarify the potential role of amino acids in the development of cardiovascular disease in offspring of women with type 1 diabetes.
Moral judgments influence emotional responses and comment lengths through the moderating role of linguistic style matching
Experimental investigation on addition of furfuryl alcohol to diesel plastic fuel blends and optimization using Kissing Numbers
An ensemble-based enhanced short and medium term load forecasting using optimized missing value imputation
Abstract Electricity load forecasting is integral to planning, energy management, and the energy market. Utility companies serve a massive number of customers by supplying electricity. These utility companies require a precise forecast of electricity usage. This paper presents a forecasting model for energy load based on the ensemble voting regressor method. In addition, to enhance the accuracy of forecasting, develop an imputation method for handling missing values in the user’s energy consumption data. A real-time data set is used for performance comparison with multiple imputation techniques to validate the imputation approach by generating random missing data for different missing rates of 10–30%. The proposed forecasting model is compared with other state-of-the-art methods to show its effectiveness in terms of MAPE, MAE, and RMSE. The experimental results demonstrate that the proposed methodology significantly improves the accuracy of the predicted load for a day and week ahead of energy consumption.
Keeping the immuno-oncology flame burning
Cryo-EM structures reveal the PP2A–B55α and Eya3 interaction that can be disrupted by a peptide inhibitor
Structural impact of synonymous mutations in six SARS-CoV-2 Variants of Concern
SARS-CoV-2 continues to spread and infect people worldwide. While most effort into characterizing variants of this virus have focused on non-synonymous changes, accumulation of synonymous mutations in different viral variants has also occurred. Here we characterize six Variants of Concern in terms of their mutational content, and make predictions regarding the impact of those mutations on potential genomic RNA secondary structure and stability. Our hypothesis is that if non-protein changing, yet RNA structure-changing mutations impact viral fitness by imposing deleterious change to predicted RNA structure, we would expect to those mutations to be less abundant, while if those synonymous mutations do not impact viral fitness through influence of RNA structure, we would see them more frequently than non-synonymous mutations. We find that synonymous mutations typically have no or modest impact to RNA secondary structure. As synonymous mutations are free from the selective pressure imposed on protein-altering mutations, the impact of synonymous mutations is largely limited to RNA secondary structure considerations. The absence of major, structure-altering synonymous mutations emphasize the importance of RNA structure, including within coding regions, to viral fitness. Synonymous mutations should be included in the characterization of emerging RNA viruses as these mutations may confer effects to viral fitness via RNA secondary structural modifications.