Search Results (5,126)

This paper investigates the mechanical behavior of PBL shear connectors in UHPC during the elastic stage, utilizing push-out experiments and numerical simulation. This study simplifies the mechanical behavior of PBL shear connectors in UHPC under normal service conditions as a plane strain problem for the UHPC dowel and a Winkler’s Elastic foundation beam theory for the transverse reinforcement. The UHPC dowel is a thick-walled cylindrical shell subjected to non-axisymmetric loads inside and outside simultaneously in the plane-strain state. The stress solution is derived by assuming the contact stress distribution function and using the Airy stress function. The displacement solution is subsequently determined from the stresses by differentiating between elastic and rigid body displacements. By modeling the transverse reinforcement as an infinitely long elastic foundation beam, its displacement solution and stress solution are obtained. We obtain the load–slip curve calculation method by superimposing the displacement of UHPC with the transverse reinforcement in the direction of shear action. The proposed analytical solutions for stress and slip, as well as the method for calculating load–slip, are shown to be reliable by comparing them to the numerical simulation analysis results. Full article

This paper evaluates and corrects systematic odometry errors in a compact omnidirectional mobile platform equipped with three omni-wheels driven by digital servomotors featuring velocity control capabilities. Compared to differential-drive platforms, omnidirectional platforms offer the significant advantage of being able to translate in any direction while rotating simultaneously. The motion capabilities of the platform have been experimentally evaluated, and its systematic motion errors analyzed and corrected. The final motion capabilities achieved confirm that a basic three-wheeled omnidirectional platform driven by servomotors is suitable for use as a testbench for control algorithms and trajectory-tracking experiments. Full article

Non-invasive glucose monitoring remains a persistent challenge in the scientific literature due to the complexity of biological samples and the limitations of traditional optical methods. Although advances have been made in the use of near-infrared (NIR) spectrophotometry, the direct application of the Lambert–Beer Law (LBL) to such systems has proven problematic, particularly due to the non-linear behavior observed in complex organic solutions. In this context, the objective of this work is to propose and validate a methodology for the determination of the extinction coefficient of glucose in blood, taking into account the limitations of the LBL and the specificities of molecular interactions. The method was optimized through an iterative process to provide consistent results over multiple replicates. Whole blood and plasma samples from two individuals were analyzed using spectrophotometry in the 700 nm to 1400 nm. The results showed that glucose has a high spectral sensitivity close to 975 nm.The extinction coefficients obtained for glucose (${\alpha }_g$) ranged from −0.0045 to −0.0053, and for insulin (${\alpha }_i$) from 0.000075 to 0.000078, with small inter-individual variations, indicating strong stability of these parameters. The non-linear behaviour observed in the relationship between absorbance, glucose and insulin concentrations might be explained by the changes imposed by both s and p orbitals of organic molecules. In order to make the LBL valid in this context, the extinction coefficients must be functions of the analyte concentrations, and the insulin concentration must also be a function of glucose. A regression model was found which allows to differentiate glucose from insulin concentration, by considering the cuvette thickness and sample absorbance at 965, 975, and 985 nm. It can also be concluded from experiments that wavelength of approximately 975 nm is more suitable for blood glucose calculation by using photometry. The final spectra are consistent with those reported in mid-infrared validation studies, suggesting that the proposed model encompasses the key aspects of glucose behavior in biological media. Full article

Research Problem and Gap: Live streaming sales rely heavily on streamers, with both genuine and AI-generated virtual streamers gaining popularity. However, these streamer types possess contrasting capabilities. Genuine streamers are superior at building trust and reducing product valuation uncertainty but have limited reach, while virtual streamers excel at broad audience engagement but are less effective at mitigating uncertainty, often leading to higher product return rates. This trade-off creates a critical strategic gap; that is, brand firms lack clear guidance on whether to invest in genuine or virtual streamers or adopt a hybrid approach for their live channels. Objective and Methods: This study addresses this gap by developing a theoretical analytical model to determine a monopolistic brand firm’s optimal streamer strategy among three options: using only a genuine streamer, only a virtual streamer, or a combination of the two (hybrid approach). The researchers model consumer utility, factoring in uncertainty and the streamers’ differential impact on reach, to derive optimal decisions on pricing and streamer selection. Results and Findings: The analysis yields several key findings with direct managerial implications. First, while a hybrid strategy leverages the complementary strengths of both streamer types, its success depends on employing high-quality streamers; in other words, this strategy does not justify settling for inferior talent of either type. Second, employing a virtual streamer requires a moderate price reduction to compensate for higher consumer uncertainty and prevent high profit-eroding return rates. Third, a pure strategy (only genuine or only virtual) is optimal only when that streamer type has a significant cost advantage. Otherwise, the hybrid strategy tends to be the most profitable. Moreover, higher product return costs directly diminish the viability of virtual streamers, making a genuine or hybrid strategy more attractive for products with expensive return processes. Conclusions: The results provide a clear framework for brand firms—that is, the choice of streamer is a strategic decision intertwined with pricing and product return costs. Firms should pursue a hybrid strategy not as a compromise but as a premium approach, use targeted pricing to mitigate the risk of virtual streamers, and avoid virtual options altogether for products with high return costs. Full article

Aluminum alloys under long-term service or repetitive stress are prone to small fatigue cracks (FCs) with arbitrary orientations, necessitating eddy current probes with focused magnetic fields and directional selectivity for reliable detection. This study presents a flexible printed circuit board (FPCB) probe with a double-layer planar excitation coil and a double-layer differential receiving coil. The excitation coil employs a reverse-wound design to enhance magnetic field directionality and focusing, while the differential receiving coil improves sensitivity and suppresses common-mode noise. The probe is optimized by adjusting the excitation coil overlap and the excitation–receiving coil angles to maximize eddy current concentration and detection signals. Finite element simulations and experiments confirm the system’s effectiveness in detecting surface cracks of varying sizes and orientations. To further characterize these defects, two time-domain features are extracted: the peak-to-peak value ($\Delta$P), reflecting amplitude variations associated with defect size and orientation, and the signal width ($\Delta$W), primarily correlated with defect angle. However, substantial overlap in their value ranges for defects with different parameters means that these features alone cannot identify which specific parameter has changed, making prior defect classification using a Transformer-based approach necessary for accurate quantitative analysis. The proposed method demonstrates reliable performance and clear interpretability for defect evaluation in aluminum components. Full article

The biocompatibility of materials used in biomedical applications, especially those in direct contact with human tissue, is crucial to ensuring their safety. Ensuring material biocompatibility requires a wide range of in vitro and in vivo tests, with in vitro tests using cell culture systems being the first step in biomaterial characterization. Among the commonly used methods for assessing cell viability are colorimetric tests, such as MTT and LDH assays. While these assays provide valuable information about cell viability, their results can be affected by biochemical substances. This study focused on evaluating the reliability of MTT and LDH assays in nicotinamide-supplemented medium, which optimized culture conditions for the differentiation of ARPE-19 cells. The results were compared with a live/dead viability test based on fluorescence staining, providing insight into the effectiveness of different cell viability assessment methods in this specific context. This research is important in developing biomaterials for retinal prostheses, where maintaining high biocompatibility is essential for successful implantation. Full article

Breast cancer is a heterogeneous disease and a leading cause of cancer-related deaths worldwide, underscoring the urgent need for effective biomarkers to guide diagnosis, prognosis, and therapeutic decisions. Bioinformatics methodologies, including genomics, transcriptomics, proteomics, and metabolomics data analysis, are essential for deciphering the complex molecular landscape of breast cancer. Bioinformatics tools facilitate the identification of differentially expressed genes, non-coding RNAs, and proteins, unraveling crucial pathways involved in tumor initiation, progression, and metastasis. By constructing and analyzing protein–protein interaction networks and signaling pathways, bioinformatics approaches can identify potential diagnostic, prognostic, and predictive biomarkers. Herein, we explore the role of bioinformatics in breast cancer research and its potential application in identifying novel therapeutic targets and predicting drug response, ultimately enabling the development of tailored treatment strategies. We also address the challenges and future directions in utilizing bioinformatics for biomarker discovery and validation, emphasizing the need for robust statistical methods, standardized data analysis pipelines, and collaborative efforts to translate bioinformatics insights into improved clinical outcomes for breast cancer patients. Full article

Pulmonary fibrosis (PF) is a progressive and fatal lung disease characterized by irreversible alveolar destruction and pathological extracellular matrix (ECM) deposition. Currently approved agents (pirfenidone and nintedanib) slow functional decline but do not reverse established fibrosis or restore functional alveoli. Multifunctional bioscaffolds present a promising therapeutic strategy through targeted modulation of critical cellular processes, including proliferation, migration, and differentiation. This review synthesizes recent advances in scaffold-based interventions for PF, with a focus on their dual mechano-epigenetic regulatory functions. We delineate how scaffold properties (elastic modulus, stiffness gradients, dynamic mechanical cues) direct cell fate decisions via mechanotransduction pathways, exemplified by focal adhesion–cytoskeleton coupling. Critically, we highlight how pathological mechanical inputs establish and perpetuate self-reinforcing epigenetic barriers to regeneration through aberrant chromatin states. Furthermore, we examine scaffolds as platforms for precision epigenetic drug delivery, particularly controlled release of inhibitors targeting DNA methyltransferases (DNMTi) and histone deacetylases (HDACi) to disrupt this mechano-reinforced barrier. Evidence from PF murine models and ex vivo lung slice cultures demonstrate scaffold-mediated remodeling of the fibrotic niche, with key studies reporting substantial reductions in collagen deposition and significant increases in alveolar epithelial cell markers following intervention. These quantitative outcomes highlight enhanced alveolar epithelial plasticity and upregulating antifibrotic gene networks. Emerging integration of stimuli-responsive biomaterials, CRISPR/dCas9-based epigenetic editors, and AI-driven design to enhance scaffold functionality is discussed. Collectively, multifunctional bioscaffolds hold significant potential for clinical translation by uniquely co-targeting mechanotransduction and epigenetic reprogramming. Future work will need to resolve persistent challenges, including the erasure of pathological mechanical memory and precise spatiotemporal control of epigenetic modifiers in vivo, to unlock their full therapeutic potential. Full article

The methylation of CpG sites with 5mC mark is a dynamic epigenetic modification. However, the relationship between the methylation and the surrounding genomic sequence context remains poorly explored. Investigation of the allele methylation provides an opportunity to decipher the interplay between differences in the primary DNA sequence and epigenetic variation. Here, we performed high-coverage long-read whole-genome direct DNA sequencing of one individual using Oxford Nanopore technology. We also used Illumina whole-genome sequencing of the parental genomes in order to identify allele-specific methylation sites with a trio-binning approach. We have compared the results of the haplotype-specific methylation detection and revealed that trio binning outperformed other approaches that do not take into account parental information. Also, we analysed the cis-regulatory effects of the genomic variations for influence on CpG methylation. To this end, we have used available Deep Learning models trained on the primary DNA sequence to score the cis-regulatory potential of the genomic loci. We evaluated the functional role of the allele-specific epigenetic changes with respect to gene expression using long-read Nanopore RNA sequencing. Our analysis revealed that the frequency of SNVs near allele-specific methylation positions is approximately four times higher compared to the biallelic methylation positions. In addition, we identified that allele-specific methylation sites are more conserved and enriched at the chromatin states corresponding to bivalent promoters and enhancers. Together, these findings suggest that significant impact on methylation can be encoded in the DNA sequence context. In order to elucidate the effect of the SNVs around sites of allele-specific methylation, we applied the Deep Learning model for detection of the cis-regulatory modules and estimated the impact that a genomic variant brings with respect to changes to the regulatory activity of a DNA loci. We revealed higher cis-regulatory impact variants near differentially methylated sites that we further coupled with transcriptomic long-read sequencing results. Our investigation also highlights technical aspects of allele methylation analysis and the impact of sequencing coverage on the accuracy of genomic phasing. In particular, increasing coverage above 30X does not lead to a significant improvement in allele-specific methylation discovery, and only the addition of trio binning information significantly improves phasing. We investigated genomic variation in a single human individual and coupled computational discovery of cis-regulatory modules with allele-specific methylation (ASM) profiling. In this proof-of-concept analysis, we observed that SNPs located near methylated CpG sites on the same haplotype were enriched for sequence features suggestive of high-impact regulatory potential. This finding—derived from one deeply sequenced genome—illustrates how phased genetic and epigenetic data analyses can jointly put forward a hypotheses about the involvement of regulatory protein machinery in shaping allele-specific epigenetic states. Our investigation provides a methodological framework and candidate loci for future studies of genomic imprinting and cis-mediated epigenetic regulation in humans. Full article

When a city decides to undertake a certain urban project, is it modifying just the physical environment or the social fabric that dwells within? This work investigates the relationship between the geometric configuration of urban space (geometry–city) and the topology of the networks of encounters of its inhabitants (network–city) that form through daily interactions. The research departs from the hypothesis that changes in geometry–city would not significantly alter the topology of the network–city, testing this proposition conceptually through abstract computational simulations developed specifically for this study. In this simulator, abstract maps with buildings distributed over different primary geometries are generated and have activities (use: home or work) and a population assigned. Encounters of the “inhabitants” are registered while daily commute routines, enough to achieve differentiation and stability, are run. The initial results revealed that the geometry description was not enough, and definitions regarding activity attribution were also necessary. Thus, we could not confirm nor reject the original hypothesis exactly, but it had to be complemented, including the idea of an activity–city dimension. We found that despite the geometry–city per se not determining the structure of the network–city, the spatial (geometric) distribution of activities directly impacts the resulting topology. Urban geometry influences networks–city only insofar as it conforms to activity–city, defining areas for activities or restricting routing between them. But it is the geometry of localization of the activities that has a direct impact on the topology of the network–city. This conceptual discovery can have significant implications for urban planning if corroborated in real-world situations. It could suggest that land use policies may be more effective for intervening in network-based characteristics, like social cohesion and resilience, than purely morphological interventions. Full article

We present a tunable diode-laser absorption spectroscopy (TDLAS) system operating at 1.5711 µm for CO₂ gas concentration measurements. The system can operate in either a traditional direct-mode (dTDLAS) sawtooth wavelength scan or a recently demonstrated wavelength-toggled single laser differential-absorption lidar (WTSL-DIAL) mode using precompensated current pulses. The use of such precompensated pulses offsets the slow thermal constants of the diode laser, leading to fast toggling between ON and OFF-resonance wavelengths. A short measurement time is indeed pivotal for atmospheric sensing, where ambient factors, such as turbulence or mechanical vibrations, would otherwise deteriorate sensitivity, precision and accuracy. Having a system able to operate in both modes allows us to benchmark the novel experimental procedure against the well-established dTDLAS method. The theory behind the new WTSL-DIAL method is also expanded to include the periodicity of the current modulation, fundamental for the calculation of the OFF-resonance wavelength. A two-detector scheme is chosen to suppress the influence of laser intensity fluctuations in time (1/f noise), and its performance is eventually benchmarked against a one-detector approach. The main difference between dTDLAS and WTSL-DIAL, in terms of signal processing, lies in the fact that while the former requires time-consuming data processing, which limits the maximum update rate of the instrument, the latter allows for computationally simpler and faster concentration readings. To compare other performance metrics, the update rate was kept at 2 kHz for both methods. To analyze the dTDLAS data, a four-parameter Lorentzian fit was performed, where the fitting function comprised the six main neighboring absorption lines centered around 1.5711 µm. Similarly, the spectral overlap between the same lines was considered when analyzing the WTSL-DIAL data in real time. Our investigation shows that, for the studied time intervals, the WTSL-DIAL approach is 3.65 ± 0.04 times more precise; however, the dTDLAS-derived CO₂ concentration measurements are less subject to systematic errors, in particular pressure-induced ones. The experimental results are accompanied by a thorough explanation and discussion of the models used, as well as their advantages and limitations. Full article

This study evaluates media-level filtration behaviour and short-term fuel consumption outcomes for five spin-on lubricating oil filters operated under real driving conditions at high altitude. To improve interpretability, filters are reported using parameter-based identifiers (media descriptors and equivalent circular diameter, ECD) rather than internal codes. Pore-scale morphology was quantified by microscopy and expressed as ECD, and bulk fluid cleanliness was summarised using ISO 4406 codes. Trials were conducted over representative urban and extra-urban routes at altitude; fuel consumption was analysed using ANCOVA. The results indicated clear media-level differences (tighter pore envelopes and cleaner ISO codes, particularly for two OEM units). However, fuel-consumption differences were not statistically significant (ANCOVA, p = 0.29). Accordingly, findings are reported as short-term cleanliness and media characterisation under high-altitude duty rather than durability or efficiency claims. The parameter-based framing clarifies trade-offs across metrics and avoids over-generalisation from brand or part numbers. The work highlights the value of ECD as a comparative pore metric and underscores limitations of microscopy/cleanliness data for inferring engine wear or long-term consumption. Future work will incorporate formal multi-pass testing (ISO 4548-12), direct differential-pressure instrumentation, used-oil viscosity tracking, and wear-metal spectrometry to enable cross-vendor benchmarking and causal interpretation. Findings are presented as short-term cleanliness and media characterisation; no durability claims are made in the absence of direct wear measurements. Full article

Background: Primary hepatocellular carcinoma (HCC) and liver metastases differ in origin, progression, and therapeutic response, yet a direct high-resolution spatial comparison of their tumor microenvironments (TMEs) within the liver has not previously been performed. Methods: We applied high-definition spatial transcriptomics to fresh-frozen specimens of one HCC and one liver metastasis (>16,000 genes per sample, >97% mapping rates) as a proof-of-principle two-specimen study, cross-validated in human proteomics and patients’ survival datasets. Transcriptional clustering revealed spatially distinct compartments, rare cell states, and pathway alterations, which were further compared against an independent systemic dataset. Results: HCC displayed an ordered lineage architecture, with transformed hepatocyte-like tumor cells broadly dispersed across the tissue and more differentiated hepatocyte-derived cells restricted to localized zones. By contrast, liver metastases showed two sharply compartmentalized domains: an invasion zone, where proliferative stem-like tumor cells occupied TAM-rich boundaries adjacent to hypoxia-adapted tumor-core cells, and a plasticity zone, which formed a heterogeneous niche of cancer–testis antigen–positive germline-like cells. Across both tumor types, we detected a conserved metabolic program of “porphyrin overdrive,” defined by reduced cytochrome P450 expression, enhanced oxidative phosphorylation gene expression, and upregulation of FLVCR1 and ALOX5, reflecting coordinated rewiring of heme and lipid metabolism. Conclusions: In this pilot study, HCC and liver metastases demonstrated fundamentally different spatial architectures, with metastases uniquely harboring a germline/neural-like plasticity hub. Despite these organizational contrasts, both tumor types converged on a shared program of metabolic rewiring, highlighting potential therapeutic targets that link local tumor niches to systemic host–tumor interactions. Full article

The present work numerically investigates the mechanical behavior of six 6061-T6 aluminum profiles during roll bending, considering, in two specific cases, the application of the process in different bending directions (vertical and horizontal), totaling eight cases analyzed, with emphasis on the influence of multiple bending radii. Notably, two of the profiles are characterized by high geometric complexity, making their analysis particularly relevant within the scope of this study. Using the finite element method in ANSYS^® (version 2022 R2) (SOLID187 element), the study expands the previously validated model to a broader range of geometries and includes an additional validation and verification stage. The results reveal: (i) an inverse relationship between bending radius and von Mises stress, with critical values close to the material’s strength limit at smaller radii; (ii) characteristic displacement patterns for each profile, quantified through specific curve fittings; and (iii) a systematic comparison among the six profiles, highlighting stress concentrations and deformations differentiated by geometry. The simulations provide criteria for predicting forming defects and optimizing process parameters, expanding the database for industrial designs with multiple extruded profiles. Full article

In this paper, we propose a novel image restoration framework that integrates optimal control techniques with the Hamilton–Jacobi–Bellman (HJB) equation. Motivated by models from production planning, our method restores degraded images by balancing an intervention cost against a state-dependent penalty that quantifies the loss of critical image information. Under the assumption of radial symmetry, the HJB equation is reduced to an ordinary differential equation and solved via a shooting method, from which the optimal feedback control is derived. Numerical experiments, supported by extensive parameter tuning and quality metrics such as PSNR and SSIM, demonstrate that the proposed framework achieves significant improvement in image quality. The results not only validate the theoretical model but also suggest promising directions for future research in adaptive and hybrid image restoration techniques. Full article