Search Results (75)

Accurate estimation of the Remaining Useful Life (RUL) of lithium-ion batteries is essential for enhancing the reliability and efficiency of energy storage systems. This study explores custom deep learning models to predict RUL using a dataset from the Hawaii Natural Energy Institute (HNEI). Three approaches are investigated: an Encoder-only Transformer model, its enhancement with SimSiam transfer learning, and a CNN–Encoder hybrid model. These models leverage advanced mechanisms such as multi-head attention, robust feedforward networks, and self-supervised learning to capture complex degradation patterns in the data. Rigorous preprocessing and optimisation ensure optimal performance, reducing key metrics such as mean squared error (MSE) and mean absolute error (MAE). Experimental results demonstrated that Transformer–CNN with Noise Augmentation outperforms other methods, highlighting its potential for battery health monitoring and predictive maintenance. Full article

This study introduces a novel methodology for estimating loading and fatigue damage in the blades of wind turbines, emphasizing non-Gaussian wind conditions’ impact. By calculating blade loading and fatigue using higher statistical moments of the irregular winds, the study demonstrates the significance of non-Gaussian effects on loading and fatigue predictions. A two-step methodology is developed to synthesize non-Gaussian wind processes, integrating the TurbSim (version 1.5) and Hermite moment model transformation methods. These wind time histories are then utilized in a fully coupled simulation of a floating wind turbine, integrating with a blade beam model. Preliminary analysis of wind thrust and the blade root bending moment indicates non-Gaussian effects on aerodynamic loading. Further analysis of fatigue reveals that fatigue hot spots vary along the blade surface, depending on short-term wind conditions and long-term wind distribution, with total fatigue life estimated by summing the fatigue damage at each potential hot spot. The probability density function of long-term wind process is estimated by fitting the Weibull distribution to measured buoy data. The results show that variations in long-term wind speed distributions lead to an average fatigue life difference of about 1.3 years (16%). The Gaussian wind model overestimates fatigue life by roughly 1.5 years (18%) compared to the non-Gaussian model. This highlights the importance of considering both long-term wind distributions and short-term wind characteristics for accurate fatigue assessment. The findings provide valuable insights for the design and operation of floating offshore wind turbines. Full article

Background: While most Escherichia coli strains are harmless members of the gastrointestinal microbiota, certain pathogenic variants can cause severe intestinal and extraintestinal diseases. A notable outbreak of E. coli O104:H4, involving both enteroaggregative (EAEC) and enterohemorrhagic (EHEC) strains, occurred in Europe, resulting in symptoms ranging from bloody diarrhea to life-threatening colitis and hemolytic uremic syndrome (HUS). Since treatment options remain limited and have changed little over the past 40 years, there is an urgent need for an effective vaccine. Such a vaccine would offer major public health and economic benefits by preventing severe infections and reducing outbreak-related costs. A multiepitope vaccine approach, enabled by advances in immunoinformatics, offers a promising strategy for targeting HUS-causing E. coli (O104:H4 and O157:H7 serotypes) with minimal disruption to normal microbiota. This study aimed to design an immunogenic multiepitope vaccine (MEV) construct using bioinformatics and immunoinformatic tools. Methods and Results: Comparative proteomic analysis identified 672 proteins unique to E. coli O104:H4, excluding proteins shared with the nonpathogenic E. coli K-12-MG1655 strain and those shorter than 100 amino acids. Subcellular localization (P-SORTb) identified 17 extracellular or outer membrane proteins. Four proteins were selected as vaccine candidates based on transmembrane domains (TMHMM), antigenicity (VaxiJen), and conservation among EHEC strains. Epitope prediction revealed ten B-cell, four cytotoxic T-cell, and three helper T-cell epitopes. Four MEVs with different adjuvants were designed and assessed for solubility, stability, and antigenicity. Structural refinement (GALAXY) and docking studies confirmed strong interaction with Toll-Like Receptor 4 (TLR4). In silico immune simulations (C-ImmSim) indicated robust humoral and cellular immune responses. In Conclusions, the proposed MEV construct demonstrated promising immunogenicity and warrants further validation in experimental models. Full article

This study aims to estimate the carbon footprint and relative uncertainties for design components of conventional and geopolymer concrete. All the design components of alkaline-activated geopolymer concrete, such as fly ash, ground granulated blast furnace slag, sodium hydroxide (NaOH), sodium silicate (Na₂SiO₃), superplasticizer, and others, are assessed to reflect the actual scenarios of the carbon footprint. The conjugate application of the life cycle assessment (LCA) tool SimPro 9.4 and @RISK Monte Carlo simulation justifies the variations in carbon emissions rather than a specific determined value for concrete binders, precursors, and filler materials. A reduction of 43% in carbon emissions has been observed by replacing cement with alkali-activated binders. However, the associative uncertainties of chemical admixtures reveal that even a slight increase may cause significant environmental damage rather than its benefit. Pearson correlations of carbon footprint with three admixtures, namely sodium silicate (r = 0.80), sodium hydroxide (r = 0.52), and superplasticizer (r = 0.19), indicate that the shift from cement to alkaline activation needs additional precaution for excessive use. Therefore, a suitable method of manufacturing chemical activators utilizing renewable energy sources may ensure long-term sustainability. Full article

SUMOylation plays a crucial role in regulating gene expression by promoting interactions between transcription factors and corepressors. Daxx, a multifunctional scaffold protein, specifically recognizes and binds SUMOylated transcription factors through its SUMO-interacting motifs (SIMs), acting as a transcriptional corepressor. In this review, we systematically elucidate the structural basis of the interaction between Daxx and SUMO, revealing the synergistic mechanism by which Daxx SIM phosphorylation and SUMO acetylation dynamically regulate Daxx function. In promyelocytic leukemia nuclear bodies (PML NBs), phosphorylation of Daxx’s SIM enhances its binding to SUMOylated PML, leading to the sequestration and inactivation of Daxx within PML NBs. Conversely, SUMO acetylation disrupts the electrostatic interactions between SUMO and SIMs, prompting the release of Daxx from PML NBs and its translocation to the nucleoplasm, where it inhibits the activity of transcription factors such as ETS1, GR, and SMAD4. Daxx SIMs are common binding sites for the interaction between SUMOylated transcription factors and Daxx, and different SUMOylated transcription factors may compete to bind to Daxx, which cross-regulates cellular life activities. This mechanism highlights the dynamic regulation of Daxx subcellular localization and transcriptional repression by SUMO and PML NBs, providing valuable insights into understanding Daxx-mediated transcriptional repression. Full article

Total internal reflection fluorescence–structured illumination microscopy (TIRF-SIM) can enhance the lateral resolution of fluorescence microscopy to twice the diffraction limit, enabling subtler observations of activity in subcellular life. However, the lack of an axial resolution makes it difficult to resolve three-dimensional (3D) subcellular structures. In this paper, we present an alternative TIRF-SIM axial resolution enhancement method by exploiting quantitative information regarding the distance between fluorophores and the surface within the evanescent field. Combining the lateral super-resolution information of TIRF-SIM with reconstructed axial information, a 3D super-resolution image with a 25 nm axial resolution is achieved without attaching special optical components or high-power lasers. The reconstruction results of cell samples demonstrate that the axial resolution enhancement method for TIRF-SIM can effectively resolve the axial depth of densely structured regions. Full article

Passion fruit is an underutilised fruit in Northeastern India, known for its unique flavour and health benefits. This study analysed 15 genotypes (P1 to P15) to explore their morphological and biochemical traits related to fruit quality and yield. P. quadrangularis L. (P15) exhibited maximum flower length, fruit size, weight, juice content, shelf-life, and yield. P. edulis f. flavicarpa (P3, P5, and P2) had the highest seed count per fruit and antioxidant activity, along with greater chlorophyll and anthocyanin levels. Passiflora edulis Sims (P8 and P11) showed superior total soluble solids, carotenoids, and vitamin C. The study found that fruit shelf life positively correlated with seed weight, while the number of fruits per vine negatively correlated with seed traits and peel weight. Additionally, certain traits, such as total carotenoids, had strong positive correlations with reducing sugar and flavonoids. Principal component analysis revealed distinct trait relationships, particularly for genotypes P7 and P10. SDS-PAGE protein profiling indicated a significant distance between P3 and P14, emphasising genetic diversity. In conclusion, this research highlights the diverse morphological and biochemical characteristics of passion fruit genotypes, paving the way for the region’s improved fruit quality, yield, and breeding strategies. Full article

The impact of breast cancer on public health is serious, and due to risk/benefit assessment, screening programs are usually restricted to women older than 49 years. Microwave imaging devices offer advantages such as non-ionizing radiation, low cost, and the ability to distinguish between cancerous and healthy tissues due to their electrical properties. Ensuring the safety of this technology is vital for its potential clinical application. To estimate the temperature increase in breast tissues from a microwave imaging scanner, cases of healthy, benign, and malignant breast tissues were analyzed using three digital models and adding two healthy breast models with varying densities. Virtual experiments were conducted using the Sim4Life software (version 7.2) with a system consisting of a horn antenna in transmission and a Vivaldi antenna in reception. Temperature increases were estimated based on the Specific Absorption Rate distributions computed for different configurations and frequencies. The highest temperature increase obtained in this analysis is lower than 60 μK in fibroglandular tissue or skin, depending on the frequency and breast density. The presence of a receiving antenna acting as a scatterer modifies the temperature increase, which is almost negligible. Microwave examination can be performed without harmful thermal effects due to electromagnetic field exposure. Full article

The use of different nanoparticles (NPs) is increasing in a wide variety of everyday products. Nevertheless, most studies concerning NP risk assessment have evaluated exposure scenarios involving a single kind of NP. A stepwise study distinguishing between the effects resulting from exposure to one kind of NP and those resulting from different co-exposure scenarios to ${\mathrm{Al}}_2{\mathrm{O}}_3$ and ${\mathrm{CeO}}_2$ NPs at concentrations below acute toxicity was conducted with different analytical techniques. As a starting point, WST-1 viability assays were performed to assess whether the chosen exposure concentrations resulted in any acute loss of viability, which would hamper further insight into the cellular response to NP exposure. Then, data on NP dissolution and uptake were obtained via single-particle inductively coupled plasma–mass spectrometry (spICP-MS) and microwave-assisted ICP-MS. Additionally, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was performed to check for differences in the biological response to the exposure scenarios at the single-cell level. It was found that the proposed combined techniques provide insight into changes in biological responses as well as cellular metal contents among the exposure scenarios. In this work, a comprehensive tiered analytical strategy for evaluating the biological responses to challenging exposure scenarios is provided. The results highlight the necessity of selecting situations more closely resembling real life—including concentrations below acute toxicity and potential interactions due to multiple NPs—when estimating potential health risks. These findings thus provide a foundation and an incentive for further research into the complex processes leading to the observed effects. Full article

The purpose of this paper is to provide researchers with a description of a data library representing human interaction with medium- to large-sized objects in everyday life. The library includes motion capture data characterizing human and object motion, as well as data for characterizing haptic interaction with the object via force and torque measurements via a load cell and inertial measurement unit (IMU) readings of the object accelerations. Objects include a box, luggage, briefcase, walker, shopping cart, wheelbarrow, and door. The data collected includes multiple types of interactions with each object, such as manipulating the object and walking while interacting with the object (e.g., pulling, pushing, carrying, operating, etc.). Data processing techniques for synchronizing data, deriving human biomechanics, and segmenting trials are presented. Examples of how the data in the library can be manipulated and processed further are provided. This includes combining ten wheelbarrow lifts of one subject together and analyzing the knee motion, object acceleration, and load cell readings (force and torque) with mean trajectories and standard deviations of the trajectories. From there, the range of motion can be extracted, such as for the hip, knee, and ankle joint minimum angles, maximum angles, and range of motion. A comparison of walking with and without a wheelbarrow is presented using spatiotemporal parameters and cyclograms to demonstrate their differences. The database is available on AddBiomechanics, SimTK, and GitHub. Full article

The literature reports on radiofrequency (RF) transmit (Tx) elements tailored for ultrahigh-field (UHF) magnetic resonance imaging (MRI) showed confounded reproducibility due to variations in simulation tools, modeling assumptions, and meshing techniques. This study proposes a standardized methodology to improve reproducibility and consistency across research sites (testers) and simulation tools (testing conditions). The methodology includes detailed simulation workflow and performance metrics for RF Tx elements. The impact of the used mesh setting is assessed. Following the methodology, a reproducibility study was conducted using CST Microwave Studio Suite, HFSS, and Sim4Life. The methodology and simulations were ultimately validated through 7 T MRI phantom experiments. The reproducibility study showed consistent performance with less than 6% standard deviation for B₁⁺ fields and 12% for peak SAR averaged over 10 g tissue (pSAR_10g). The SAR efficiency metric (|B₁⁺|/√pSAR_10g) was particularly robust (<5%). The simulated and experimental |B₁⁺| maps showed good qualitative agreement. This study demonstrates the feasibility of a standardized methodology for achieving reproducible RF Tx element electromagnetic field simulations. By following the FAIR principles including making the framework publicly available, we promote transparency and collaboration within the MRI community, supporting the advancement of technological innovation and improving patient safety in UHF-MRI. Full article

Transcranial electrical stimulation, as a means of neural modulation, is increasingly favored by researchers. The distribution and magnitude of the electric field generated within the brain may directly affect the results of neural modulation. Therefore, it is important to clarify the change trend of the cortical electric field and the determinants of the induced electric field in the endodermis at different ages during the adult life cycle. In this study, we used SimNIBS software to perform MR image segmentation and realistic head model reconstruction on 476 individuals (aged 18 to 88 years old) and calculated the cortical electric field of four electrode montages commonly used in cognitive tasks. We divided all participants into groups by age with a span of 10 years for each group and compared the electric field distribution patterns, electric field intensities, and focalities of the cortexes and regions of interest related to cognitive tasks within groups. The degree of influence of global and local anatomical parameters on the electric field was analyzed using a stepwise regression model. The results showed that, in the cortexes and regions of interest, the variability of electric field distribution patterns was highest in adolescents (<20 years old) and elderly individuals (>80 years old). Moreover, throughout the adult lifespan, the electric field induced by transcranial electrical stimulation did not decrease linearly with age but rather presented a U-shaped pattern. In terms of the entire adult life cycle, compared with global anatomical parameters (intracranial brain tissue volume), local anatomical parameters (such as scalp or skull thickness below the electrode) have a greater impact on the amplitude of the intracranial electric field. Our research results indicated that it is necessary to consider the effects caused by different brain tissues when using transcranial electrical stimulation to modulate or treat individuals of different ages. Full article

The study explores innovative crosslinking processes for biopolymer gel materials using amino acids and ion-redox initiators to significantly enhance their structural and functional properties. Advanced analytical techniques, including FTIR, Raman spectroscopy, XRD, TEM, TGA, DSC, ToF-SIMS, SEM/EDS, GPC/SEC, and elemental analysis, were employed for comprehensive material characterization. The synthesized materials show potential applications in packaging and medicine, particularly for single-use products with short life cycles. Two crosslinking strategies were developed. The first combines gelatin with polyvinyl alcohol (PVA); keratin hydrolysate; and amino acids such as cysteine, hydroxyproline, proline, and histidine. The second employs endogenous cysteine, activated by ion-redox initiators, leveraging its trans-sulfuration ability to form highly stable polymer networks with optimized mechanical and thermal properties. Notably, the synergy between cysteine and potassium persulfate redox initiators proved particularly effective, making this approach attractive for industrial applications. This study introduces novel crosslinking methods and highlights the potential of amino acid-based strategies for designing advanced biopolymer gels with enhanced properties. Full article

Monitoring marine life through underwater object detection technology serves as a primary means of understanding biodiversity and ecosystem health. However, the complex marine environment, poor resolution, color distortion in underwater optical imaging, and limited computational resources all affect the accuracy and efficiency of underwater object detection. To solve these problems, the YOLOv9s-SD underwater target detection algorithm is proposed to improve the detection performance in underwater environments. We combine the inverted residual structure of MobileNetV2 with Simple Attention Module (SimAM) and Squeeze-and-Excitation Attention (SE) to form the Simple Enhancement attention Module (SME) and optimize AConv, improving the sensitivity of the model to object details. Furthermore, we introduce the lightweight DySample operator to optimize feature recovery, enabling better adaptation to the complex characteristics of underwater targets. Finally, we employ Wise-IoU version 3 (WIoU v3) as the loss function to balance the loss weights for targets of different sizes. In comparison with the YOLOv9s model, according to the experiments conducted on the UPRC and Brackish underwater datasets, YOLOv9s-SD achieves an improvement of 1.3% and 1.2% in the mean Average Precision (mAP), reaching 83.0% and 94.3% on the respective datasets and demonstrating better adaptability to intricate underwater environments. Full article

Background/Objectives: N-acetyl-galactosamine small interfering RNAs (GalNAc-siRNA) are an emerging class of drugs due to their durable knockdown of disease-related proteins. Direct conjugation of GalNAc onto the siRNA enables targeted uptake into hepatocytes via GalNAc recognition of the Asialoglycoprotein Receptor (ASGPR). With a transient plasma exposure combined with a prolonged liver half-life, GalNAc-siRNA exhibits distinct disposition characteristics. We aimed to develop a generic GalNAc-siRNAs whole-body physiologically based pharmacokinetic–pharmacodynamic (WB-PBPK-PD) model for describing the pharmacokinetic–pharmacodynamic (PK-PD) relationship and overall tissue distribution in the open-source platform Open Systems Pharmacology Suite. Methods: Model development was performed using published studies in mice leveraging the PK-Sim^® standard implementation for large molecules with added implementations of ASGPR-mediated liver disposition and downstream target effects. Adequate model performance was achieved across study measurements and included studies adopting a combination of global and compound-specific parameters. Results: The analysis identified significant compound dependencies, e.g., endosomal stability, with direct consequences for the pharmacological effect. Additionally, knowledge gaps in mechanistic understanding related to extravasation and overall tissue distribution were identified during model development. The presented study provides a generic WB-PBPK-PD model for the investigation of GalNAc-siRNAs implemented in a standardized open-source platform. Full article