Search Results (563)

A novel efficient method to evaluate time-periodic flows is applied to turbomachinery configurations in this paper (PSpTM). The technique reduces the overall computational cost of unsteady CFD calculations relative to conventional implicit approaches. The method is based on a pseudo-spectral definition of the time derivative rearranged in a time-marching fashion. The key advantage of this novel formulation compared with classical harmonic methods is that it requires minor modifications in the CFD solver structure. The method was implemented into an existing unstructured edge-based, second-order, compressible RANS solver. To benchmark the method, a well-established implicit time scheme based on a second-order backward implicit approach (BDF2) is used. Sample unsteady turbomachinery configurations are used to determine the accuracy and efficiency of the method. The accuracy of the solution is highly linked to the number of harmonics prescribed for the solution. An adequate level of accuracy was obtained while retaining a reduced number of harmonics, with approximately twice the number of harmonics of the unsteady perturbation. Notable savings in computational cost were observed when the PSpTM method was used with speed-up factors of between 2 and 10 with respect to the BDF2, depending on the case. However, the PSpTM method exhibits a poor periodic convergence rate, leaving room for further improvements in efficiency. However, even in its current form and with the current understanding, the method has a remarkable performance. Full article

Background/Objectives: Krüppel-like factor 4 (KLF4) emerged as an epigenetically regulated gene in a variety of settings, including cell reprogramming and malignant cell proliferation. The aim of the present manuscript is to explore the relationship described in recent years between circular RNAs, miRNAs, and KLF4. These have been shown to be involved in cancers having diverse histological origins, including some of the most prevalent and deadly tumors for the human population. Expression and protein levels of this transcription factor correlate with invasiveness and prognosis in a context- and tissue-specific fashion. Methods: The literature was obtained through two main PubMed queries. The first is “miRNA and KLF4 and cancer” and is limited to the last 5 years. The second is “circRNA and KLF4”, which yielded publications between 2013 and 2024. The oncological publications were selected. Results: A number of circRNA/miRNA axes that regulate the downstream transcription factor KLF4 emerged in the last few years. circRNAs act as sponges for miRNAs and synergize with KLF4, which can function as either a tumor promoter or suppressor in different tumors. Conclusions: The axes represented by circRNA/miRNA/KLF4 emerged as a new layer of epigenetic regulation. These RNA-based modulators explain the complex regulation of this transcription factor and open the way to new therapeutic targeting possibilities. Full article

In this position paper, we argue that the conventional understanding of ‘information’ (as generally conceived in science, in a digital fashion) is overly simplistic and not consistently applicable to living systems, which are open systems that cannot be reduced to any kind of ‘portion’ (building block) ascribed to the category of quantity. Instead, it is a matter of relationships and qualities in an indivisible analogical (and ontological) relationship between any presumed ‘software’ and ‘hardware’ (information/matter, psyche/soma). Furthermore, in biological systems, contrary to Shannon’s definition, which is well-suited to telecommunications and informatics, any kind of ‘information’ is the opposite of internal entropy, as it depends directly on order: it is associated with distinction and differentiation, rather than flattening and homogenisation. Moreover, the high degree of structural compartmentalisation of living matter prevents its energetics from being thermodynamically described by using a macroscopic, bulk state function. This requires the Second Principle of Thermodynamics to be redefined in order to make it applicable to living systems. For these reasons, any static, bit-related concept of ‘information’ is inadequate, as it fails to consider the system’s evolution, it being, in essence, the organized coupling to its own environment. From the perspective of quantum field theory (QFT), where many vacuum levels, symmetry breaking, dissipation, coherence and phase transitions can be described, a consistent picture emerges that portrays any living system as a relational process that exists as a flux of context-dependent meanings. This epistemological shift is also associated with a transition away from the ‘particle view’ (first quantisation) characteristic of quantum mechanics (QM) towards the ‘field view’ possible only in QFT (second quantisation). This crucial transition must take place in life sciences, particularly regarding the methodological approaches. Foremost because biological systems cannot be conceived as ‘objects’, but rather as non-confinable processes and relationships. Full article

Background/Objective: Hypertrophic cardiomyopathy (HCM) often presents later in the disease course, with frequent misdiagnoses and population-level underdiagnoses. Underserved patients may have even greater diagnostic delays. We aimed to test the hypothesis in a retrospective cohort that artificial intelligence analysis of ECGs (AI-ECG) could have afforded the opportunity for earlier diagnosis of HCM in one health system. Methods: We collected all available ECGs from patients referred to an HCM Center of Excellence over 15 years, both before and after HCM diagnosis. We applied AI-ECG to each ECG in a blinded fashion to predict the probability of HCM. We calculated the time between each patient’s AI-ECG diagnosis and clinical diagnosis. We examined the sensitivity and specificity of AI-ECG for all patients, and by septal subtype and genetic test result. Results: 3499 ECGs were analyzed in 404 patients (age 56 ± 18 years, 52% female). AI-ECG correctly identified HCM in 155 patients with a sensitivity of 67%, specificity of 95%, positive predictive value of 94%, and a negative predictive value of 69%. The AUC was similar using mean probability from all ECGs for each patient (AUC 0.91 [0.88, 0.94]) or using probability from the first ECG (AUC 0.91 [0.87,0.93]). AI-ECG diagnosed 27 patients over 1 year before clinical diagnosis, and up to 16.3 years early. Black patients were more likely than White patients to have an AI-ECG diagnosis before a clinical diagnosis (p = 0.005). Conclusions: AI-ECG offers the potential for advanced HCM diagnosis. Differences in identification timing between subgroups highlight inequities in current care and show the potential of AI-ECG for the greatest benefit in underserved ethnic groups. Full article

In addition to the use of reference instruments, low-cost sensors (LCSs) are becoming increasingly popular for air quality monitoring both indoors and outdoors. These sensors provide real-time measurements of pollutants and facilitate better spatial and temporal coverage. However, these simpler devices are typically characterised by lower accuracy and precision and can be more sensitive to the environmental conditions than the reference instruments. It is therefore crucial to characterise the applicability and limitations of these instruments, for which a possible solution is their comparison with reference measurements in real-world conditions. To this end, a measurement campaign has been carried out to evaluate the PM_2.5 readings of several low- and medium-cost air quality instruments of different types and categories (IQAir AirVisual Pro, TSI DustTrak™ II Aerosol Monitor 8532, Xiaomi Mijia Air Detector, and Xiaomi Smartmi PM_2.5 Air Detector). A GRIMM EDM180 instrument was used as the reference. This campaign took place in Budapest, Hungary, from 12 November to 15 December 2020, during typically humid and foggy weather conditions, when the air pollution level was high due to the increased anthropogenic emissions, including wood burning for heating purposes. The results indicate that the individual sensors tracked the dynamics of PM_2.5 concentration changes well (in a linear fashion), but the readings deviated from the reference measurements to varying degrees. Even though the AirVisual sensors performed generally well (0.85 < R² < 0.93), the accuracy of the units showed inconsistency (13–93%) with typical overestimation, and their readings were significantly affected by elevated relative humidity levels and by temperature. Despite the overall overestimation of PM_2.5 by the Xiaomi sensors, they also exhibited strong correlation coefficients with the reference, with R² values of 0.88 and 0.94. TSI sensors exhibited slight underestimations with high explained variance (R² = 0.93–0.94) and good accuracy. The results indicated that despite the inherent bias, the low-cost sensors are capable of capturing the temporal variability of PM_2.5, thus providing relevant information. After simple and multiple linear regression-based correction, the low-cost sensors provided acceptable results. The results indicate that sensor data correction is a necessary prerequisite for the usability of the instruments. The ensemble method is a reasonable alternative for more accurate estimations of PM_2.5. Full article

Background/Objectives: More than 33 billion chickens are industrially raised for meat and egg production globally and vaccinated against Marek’s disease virus (MDV). The antigenically related herpesvirus of turkey (HVT) is used as a live-attenuated vaccine, commonly provided as a recombinant vector to protect chickens against additional unrelated pathogens. Because HVT replicates in a strictly cell-associated fashion to low levels of infectious units, adherent primary chicken or duck embryo fibroblasts are infected, dislodged from the cultivation surface and distributed as cryocultures in liquid nitrogen to the site of application. Although viable cells are complex products, application of infected cells in ovo confers protection even in presence of maternal antibodies. Methods/Results: The aim of our study was to determine whether a continuous cell line in a scalable cultivation format can be used for production of HVT-based vaccines. The AGE1.CR cell line (from Muscovy duck) was found to be highly permissive in adherent cultures. Propagation in suspension, however, initially gave very low yields. The induction of cell-to-cell contacts in carrier-independent suspensions and a metabolic shock improved titers to levels suitable for vaccine production (>10⁵ infectious units/mL after infection with multiplicity of 0.001). Conclusions: Production of HVT is challenging to scale to large volumes and the reliance on embryonated eggs from biosecure facilities is complex. We demonstrate that a cell-associated HVT vector can be propagated in a carrier-independent suspension culture of AGE1.CR cells in chemically defined medium. The fed-batch production is independent of primary cells and animal-derived material and can be scaled to large volumes. Full article

E. coli attaches to, and forms biofilms on various surfaces, including latex and polystyrene, contributing to nosocomial spread. E. coli responds to both exogenous and endogenous insulin, which induces behavioral changes. Human insulin, a quorum signal surrogate for microbial insulin, may affect the ability of E. coli to interact with latex and polystyrene in the presence of various sugars. E. coli ATCC 25923 was grown in peptone (1%) yeast nitrogen base broth to either the logarithmic or stationary growth phase. Adherence to latex was determined using 6 × 6 mm latex squares placed in a suspension of washed cells (10³ CFU/mL; 30 min; 37 °C) in buffer containing insulin at 2, 20, and 200 µU/mL (Humulin^® R; Lilly) with and without mannose, galactose, fructose, sorbose, arabinose, xylose, lactose, maltose, melibiose, glucose-6-phosphate, glucose-1-phosphate, and glucosamine at concentrations reported to affect behavioral response. Attachment levels to latex were determined by the press plate method. Biofilm levels were measured in a similar fashion but with overnight cultures in flat bottom uncoated polystyrene plates. Controls were media, insulin, sugar, or buffer alone. Glucose served as the positive control. Overall, the stationary phase cells’ adherence to latex was greater, regardless of the test condition, than was measured for the logarithmic phase cells. The effect of insulin on adherence to latex was insulin and sugar concentration dependent. The addition of insulin (200 µU/mL) resulted in a significantly (p < 0.05) increased adherence to latex and biofilm formation on polystyrene compared with sugar alone for 12 of the 13 sugars tested with stationary phase bacteria and 10 of the 13 sugars tested with logarithmic phase bacteria. Adherence in response to sorbose was the only sugar tested that was unaffected by insulin. These findings show that insulin enhances E. coli’s association with materials in common usage in medical environments in a nutrition-dependent manner. Full article

This study investigated how cognitive maps of the environment are formed. During learning trials, participants encoded the spatial locations of objects in a virtual maze either through simulated movement within the maze (first-person perspective) or by inspecting a schematic map (survey perspective). During interleaved test trials, they indicated where the object were on a schematic map (survey perspective). Response accuracy, averaged across objects and participants, increased gradually across test trials. At the level of individual participants and objects, however, accuracy improved abruptly. Furthermore, response accuracy was unaffected by the number of encoded objects used. Notably, the speed of map formation and the absence of a set-size effect were comparable across the two encoding perspectives, despite the fact that first-person encoding required transformation into a survey perspective for testing. Unlike the speed, the accuracy was lower in the first-person perspective compared to the survey encoding perspective. These findings suggest that cognitive maps can be holistic rather than item-dependent representations that emerge in a locally abrupt fashion, regardless of the encoding perspective. In contrast to the emergence speed, map accuracy can be lower when the encoding perspective differs from the test perspective. Full article

As awareness of the negative environmental impact of fashion grows, most companies are choosing to innovate in areas such as recycling and digital transformation. In the context of the rising digital economy and the ongoing development of 3D simulation software, there has been a notable increase in the demand for realistic 3D virtual-fitting effects. However, no standardized evaluation method exists for the realism of virtual fabric drape. This study proposes a systematic approach to enhance the objective evaluation and rapid optimization of virtual fabric drape realism. The research is structured in four stages. First, virtual drape testing conditions are established by referencing real-world fabric drape tests. Second, fuzzy classification is employed to categorize the realism of virtual drape effects into six levels. Third, subjective evaluations of representative fabrics are conducted to define the grading thresholds and reveal differences among the fabric types. Finally, a backpropagation (BP) neural network is used to construct three rapid evaluation models and one optimization model, which are validated through practical application. The proposed method supports accurate assessment and optimization of virtual simulations, contributes to a refined virtual fabric database, and offers insights for improving other 3D fitting software. Full article

When hypotheses are tested in a stream and real-time decision-making is needed, online sequential hypothesis testing procedures are needed. Furthermore, these hypotheses are commonly partitioned into groups by their nature. For example, RNA nanocapsules can be partitioned based on the therapeutic nucleic acids (siRNAs) being used, as well as the delivery nanocapsules. When selecting effective RNA nanocapsules, simultaneous false discovery rate control at multiple partition levels is needed. In this paper, we develop hypothesis testing procedures which control the false discovery rate (FDR) simultaneously for multiple partitions of hypotheses in an online fashion. We provide rigorous proofs for their FDR or modified FDR (mFDR) control properties and use extensive simulations to demonstrate their performances. Full article

In logical geometry, Aristotelian diagrams are studied in a systematic fashion. Recent developments in this field have shown that the square of opposition generalizes in two ways, which correspond precisely to the theory of opposition (leading to $\alpha$-structures) and the theory of implication (leading to ladders) it exhibits. These two kinds of Aristotelian diagrams are dual to each other, in the sense that they are the oppositional and implicative counterpart of the same construction. This paper formalizes this duality as $OI$-companionship, explores its properties, and applies it to various $\sigma$-diagrams. This investigation shows that $OI$-companionship has some interesting, but unusual behaviors. While it is symmetric, and works well on the level of Aristotelian families, it lacks (ir)reflexivity, transitivity, functionality, and seriality. However, we show that all important Aristotelian families from the literature do have a unique $OI$-companion. These findings explore the limits that arise when extending the duality between opposition and implication beyond the limits of $\alpha$-structures and ladders. Full article

Super-enhancers (SEs) are large clusters of highly active enhancers that play key regulatory roles in cell identity, development, and disease. While conventional methods classify SEs in a binary fashion—super-enhancer or not—this threshold-based approach can overlook significant intermediate states of enhancer activity. Here, we present a dataset and accompanying framework that facilitate a more nuanced, non-binary examination of SE activation across mouse tissue types (mammary gland, lung tissue, and NMuMG cells) and various experimental conditions (normal, tumor, and drug-treated samples). By consolidating overlapping SE intervals and capturing continuous enhancer activity metrics (e.g., ChIP-seq signal intensities), our dataset reveals gradual transitions between moderate and high enhancer activity levels that are not captured by strictly binary classification. Additionally, the data include extensive functional annotations, linking SE loci to nearby genes and enabling immediate downstream analyses such as clustering and gene ontology enrichment. The flexible approach supports broader investigations of enhancer landscapes, offering a comprehensive platform for understanding how SE activation underpins disease mechanisms, therapeutic response, and developmental processes. Full article

The chemical interaction of salicylic acid, formaldehyde, and sulfuric acid produced a disalicylic ligand (3,3′-dicarboxy-2,2′-dihydroxydiphenylmethane, DCM), which was then allowed to coordinate with copper (II) ions. The solid compounds’ chemical structures were determined using elemental analysis, UV-Vis, FT-IR, MS, ¹H-NMR, PXRD, SEM, TEM, magnetic studies, as well as molecular modeling based on DFT (density functional theory) calculations. It was proposed that the ligand coordinates in a tetradentate fashion with the copper ion to give a square-planar binuclear complex. A significant difference in the diffraction patterns between Cu(II)–DCM (amorphous) and DCM (crystalline) was displayed using an X-ray diffraction analysis. Spherical granules were identified throughout through morphology analysis using SEM and TEM. UV-Vis spectra were used to quantify the optical characteristics such as the energy gap, optical conductivity, refractive index, and penetration depth. The band gap values that lie within the semiconductor region suggested that the compounds could be used for electronic applications. The optimized structure of the synthesized Cu(II)–DCM complex was investigated using DFT and TD-DFT (time-dependent density functional theory) at the B3LYP/6-31G(d, p) level, with the LANL2DZ basis set for Cu in an ethanol solvent and the gas environment modeled by CPCM. The experimental data suggest a square-planar geometry of the Cu(II) binuclear complex. The theoretical calculations support the proposed structure of the compound. The cytotoxicity of the DCM against HCT–116 (human colon cancer) cells was tested, and the outcome exhibited good inhibitions of growth. A molecular docking (MD) examination was carried out to illustrate the binding mode/affinity of the prepared compounds (DCM and Cu(II)–DCM) in the active site of the receptor protein [CDK2 enzyme, PDB ID: 6GUE]. The compounds formed hydrogen bonds with the amino acid residues of the protein, increasing the binding affinity from −7.2 to −9.3 kcal/mol through the coordination process. The information from this current study, particularly the copper complex, is beneficial for exploring new compounds that have anticancer potential. Full article

The leather tanning industry generates a substantial quantity of solid waste, which, in part, is discarded in the environment in landfills or incinerated. One alternative end-of-life solution is to manufacture engineered materials by forming composites with a thermoplastic polymer/binder. In this work, leather fibres (LFs) were melt-compounded into partially bio-based thermoplastic polyurethane (TPU), at leather fibre contents between 10 and 30% (TPU/LF), followed by compression moulding or 3D printing. The results showed that the incorporation of LF into the polymer matrix produced materials with a Young’s modulus comparable to that of leather. The melt extrusion processing influenced the polymer chain orientation and the resulting mechanical performance. The cyclic stress softening and abrasion resistance of the TPU/LF materials were evaluated to understand the potential of this material to be used in the footwear industry. The level of LF incorporation could be tailored to produce the specific targeted mechanical properties. This work demonstrates that LF could be used to produce materials with a high potential to be used in the fashion industry. Full article

In this paper, we address the challenge of dynamic evolution of user preferences and propose an attribute-sequence-based recommendation model to improve the accuracy and interpretability of recommendation systems. Traditional approaches usually rely on item sequences to model user behavior, but ignore the potential value of attributes shared among different items for preference characterization. To this end, this paper innovatively replaces items in user interaction sequences with attributes, constructs attribute sequences to capture fine-grained preference changes, and reinforces the prioritization of current interests by maintaining the latest state of attributes. Meanwhile, the item–attribute relationship is modeled using LightGCN and a variant of GAT, fusing multi-level features using gated attention mechanism, and introducing rotary encoding to enhance the flexibility of sequence modeling. Experiments on four real datasets (Beauty, Video Games, Men, and Fashion) showed that the model in this paper significantly outperformed the benchmark model in both NDCG@10 and Hit Ratio@10 metrics, with a highest improvement of 6.435% and 3.613%, respectively. The ablation experiments further validated the key role of attribute aggregation and sequence modeling in capturing user preference dynamics. This work provides a new concept for recommender systems that balances fine-grained preference evolution with efficient sequence modeling. Full article