Search Results (4,164)

The microstrip devices based on multimode resonators represent a class of electromagnetic microwave devices, promising use in tropospheric communication, radar, and navigation systems. The design of wideband bandpass filters, diplexers, and multiplexers with required frequency-selective properties, i.e., bandpass filters, is a complex problem, as electrodynamic modeling is a time-consuming and computationally intensive process. Various planar microstrip resonator topologies can be developed, differing in their topology type, and the search for high-quality structures with unique frequency-selective properties is an important research direction. In this study, we propose an approach for performing an automated search for multimode resonators’ conductor topology parameters using a combination of evolutionary computation approach and surrogate modeling. In particular, a variant of differential evolution optimizer is applied, and the model of the target function landscape is built using Gaussian processes. At every iteration of the algorithm, the model is used to search for new high-quality solutions. In addition, a general approach for target function formulation is presented and applied in the proposed approach. The experiments with two microwave filters have demonstrated that the proposed algorithm is capable of solving the problem of tuning two types of topologies, namely three-mode resonators and six-mode resonators, to the required parameters, and the application of surrogated-assisted algorithm has significantly improved overall performance. Full article

This study investigates the geometric linearization of constraint Hamiltonian systems using the Jacobi metric and the Eisenhart lift. We establish a connection between linearization and maximally symmetric spacetimes, focusing on the Noether symmetries admitted by the constraint Hamiltonian systems. Specifically, for systems derived from the singular Lagrangian $L\left(N,q^k,{\dot{q}}^k\right)={\displaystyle \frac{1}{2N}}{g}_{ij}{\dot{q}}^i{\dot{q}}^j-NV\left(q^k\right),$ where N and $q^i$ are dependent variables and $dim{g}_{ij}=n$, the existence of ${\displaystyle \frac{n\left(n+1\right)}{2}}$ Noether symmetries is shown to be equivalent to the linearization of the equations of motion. The application of these results is demonstrated through various examples of special interest. This approach opens new directions in the study of differential equation linearization. Full article

Motivation: To increase the efficiency of the brake valve by adding a corrective member. Background: The speed of response and smooth transition between modes of operation in the braking system are the primary research questions. Objective and research question: Will the optimal selection of the input parameters of the differentiating part of a conceptual brake valve ensure the speed of operation and enable a smooth transition from the accelerating mode to the tracking mode? Methods: The mathematical model of the differentiating part of the brake valve uses the lumped method, and the solution was obtained by numerical means. Results: Within the assumed range of variation of spring stiffness and control piston bore throughput, the distribution maps of action times and piston lift were determined, and the optimal configuration of the analyzed input parameters was obtained by a genetic algorithm. Future research: future activities will focus on the development of a system of smooth variation of the throughput of the connecting chamber of the differential part of the valve. Conclusions: The determined maps of functional parameter distributions are the basis for the selection of components of the braking system; optimization indicates the directions of modification of the valve in order to obtain an acceptable performance system. Full article

MicroRNAs (miRNAs) are a class of small regulatory RNA that are generated via core protein machinery. The miRNAs direct gene-silencing mechanisms to mediate an essential role in gene expression regulation. In mollusks, miRNAs have been demonstrated to be required to regulate gene expression in various biological processes, including normal development, immune responses, reproduction, and stress adaptation. In this study, we aimed to establishment the requirement of the miRNA pathway as part of the molecular response of exposure of Biomphalaria glabrata (snail host) to Schistosoma mansoni (trematode parasite). Initially, the core pieces of miRNA pathway protein machinery, i.e., Drosha, DGCR8, Exportin-5, Ran, and Dicer, together with the central RNA-induced silencing complex (RISC) effector protein Argonaute2 (Ago2) were elucidated from the B. glabrata genome. Following exposure of B. glabrata to S. mansoni miracidia, we identified significant expression up-regulation of all identified pieces of miRNA pathway protein machinery, except for Exportin-5, at 16 h post exposure. For Ago2, we went on to show that the Bgl-Ago2 protein was localized to regions surrounding the sporocysts in the digestive gland of infected snails 20 days post parasite exposure. In addition to documenting elevated miRNA pathway protein machinery expression at the early post-exposure time point, a total of 13 known B. glabrata miRNAs were significantly differentially expressed. Of these thirteen B. glabrata miRNAs responsive to S. mansoni miracidia exposure, five were significantly reduced in their abundance, and correspondingly, these five miRNAs were determined to putatively target six genes with significantly elevated expression and that have been previously associated with immune responses in other animal species, including humans. In conclusion, this study demonstrates the central importance of a functional miRNA pathway in snails, which potentially forms a critical component of the immune response of snails to parasite exposure. Further, the data reported in this study provide additional evidence of the complexity of the molecular response of B. glabrata to S. mansoni infection: a molecular response that could be targeted in the future to overcome parasite infection and, in turn, human schistosomiasis. Full article

Nanoclay-composite hydrogels represent a promising avenue for advancing bone tissue engineering. Traditional hydrogels face challenges in providing mechanical strength, biocompatibility, and bioactivity necessary for successful bone regeneration. The incorporation of nanoclay into hydrogel matrices offers a potential unique solution to these challenges. This review provides a comprehensive overview of the fabrication, physico-chemical/biological performance, and applications of nanoclay-composite hydrogels in bone tissue engineering. Various fabrication techniques, including in situ polymerization, physical blending, and 3D printing, are discussed. In vitro and in vivo studies evaluating biocompatibility and bioactivity have demonstrated the potential of these hydrogels for promoting cell adhesion, proliferation, and differentiation. Their applications in bone defect repair, osteochondral tissue engineering and drug delivery are also explored. Despite their potential in bone tissue engineering, nanoclay-composite hydrogels face challenges such as optimal dispersion, scalability, biocompatibility, long-term stability, regulatory approval, and integration with emerging technologies to achieve clinical application. Future research directions need to focus on refining fabrication techniques, enhancing understanding of biological interactions, and advancing towards clinical translation and commercialization. Overall, nanoclay-composite hydrogels offer exciting opportunities for improving bone regeneration strategies. Full article

Detecting emotions is a growing field aiming to comprehend and interpret human emotions from various data sources, including text, voice, and physiological signals. Electroencephalogram (EEG) is a unique and promising approach among these sources. EEG is a non-invasive monitoring technique that records the brain’s electrical activity through electrodes placed on the scalp’s surface. It is used in clinical and research contexts to explore how the human brain responds to emotions and cognitive stimuli. Recently, its use has gained interest in real-time emotion detection, offering a direct approach independent of facial expressions or voice. This is particularly useful in resource-limited scenarios, such as brain–computer interfaces supporting mental health. The objective of this work is to evaluate the classification of emotions (positive, negative, and neutral) in EEG signals using machine learning and deep learning, focusing on Graph Convolutional Neural Networks (GCNN), based on the analysis of critical attributes of the EEG signal (Differential Entropy (DE), Power Spectral Density (PSD), Differential Asymmetry (DASM), Rational Asymmetry (RASM), Asymmetry (ASM), Differential Causality (DCAU)). The electroencephalography dataset used in the research was the public SEED dataset (SJTU Emotion EEG Dataset), obtained through auditory and visual stimuli in segments from Chinese emotional movies. The experiment employed to evaluate the model results was “subject-dependent”. In this method, the Deep Neural Network (DNN) achieved an accuracy of 86.08%, surpassing SVM, albeit with significant processing time due to the optimization characteristics inherent to the algorithm. The GCNN algorithm achieved an average accuracy of 89.97% in the subject-dependent experiment. This work contributes to emotion detection in EEG, emphasizing the effectiveness of different models and underscoring the importance of selecting appropriate features and the ethical use of these technologies in practical applications. The GCNN emerges as the most promising methodology for future research. Full article

Stem cell-based therapy holds promise for cartilage regeneration in treating knee osteoarthritis (KOA). Injectable hydrogels have been developed to mimic the extracellular matrix (ECM) and facilitate stem cell growth, proliferation, and differentiation. However, these hydrogels face limitations such as poor mechanical strength, inadequate biocompatibility, and suboptimal biodegradability, collectively hindering their effectiveness in cartilage regeneration. This study introduces an injectable, biodegradable, and self-healing hydrogel composed of chitosan–PEG and PEG–dialdehyde for stem cell delivery. This hydrogel can form in situ by blending two polymer solutions through injection at physiological temperature, encapsulating human adipose-derived stem cells (hADSCs) during the gelation process. Featuring a 3D porous structure with large pore size, optimal mechanical properties, biodegradability, easy injectability, and rapid self-healing capability, the hydrogel supports the growth, proliferation, and differentiation of hADSCs. Notably, encapsulated hADSCs form 3D spheroids during proliferation, with their sizes increasing over time alongside hydrogel degradation while maintaining high viability for at least 10 days. Additionally, hADSCs encapsulated in this hydrogel exhibit upregulated expression of chondrogenic differentiation genes and proteins compared to those cultured on 2D surfaces. These characteristics make the chitosan–PEG/PEG–dialdehyde hydrogel–stem cell construct suitable for direct implantation through minimally invasive injection, enhancing stem cell-based therapy for KOA and other cell-based treatments. Full article

Nearly six million people worldwide have died from the coronavirus disease (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although COVID-19 vaccines are largely successful in reducing the severity of the disease and deaths, the decline in vaccine-induced immunity over time and the continuing emergence of new viral variants or mutations underscore the need for an alternative strategy for developing broad-spectrum host-mediated therapeutics against SARS-CoV-2. A key feature of severe COVID-19 is dysregulated innate immune signaling, culminating in a high expression of numerous pro-inflammatory cytokines and chemokines and a lack of antiviral interferons (IFNs), particularly type I (alpha and beta) and type III (lambda). As a natural host defense, the myeloid differentiation primary response protein, MyD88, plays pivotal roles in innate and acquired immune responses via the signal transduction pathways of Toll-like receptors (TLRs), a type of pathogen recognition receptors (PRRs). However, recent studies have highlighted that infection with viruses upregulates MyD88 expression and impairs the host antiviral response by negatively regulating type I IFN. Galectin-3 (Gal3), another key player in viral infections, has been shown to modulate the host immune response by regulating viral entry and activating TLRs, the NLRP3 inflammasome, and NF-κB, resulting in the release of pro-inflammatory cytokines and contributing to the overall inflammatory response, the so-called “cytokine storm”. These studies suggest that the specific inhibition of MyD88 and Gal3 could be a promising therapy for COVID-19. This review presents future directions for MyD88- and Gal3-targeted antiviral drug discovery, highlighting the potential to restore host immunity in SARS-CoV-2 infections. Full article

While the high-voltage direct current (HVDC) transmission system is in monopolar operation, it produces thousands of amperes of ground-return currents (GRCs). Accurate computation of the GRCs is essential for assessing safety implications for nearby industrial infrastructure. Current three-dimensional forward models of GRCs are typically constructed based on discrete differential equations, and their solving efficiency is constrained by the increased degrees of freedom resulting from the fine discretization grids in high-conductivity conductors and ground points. To address this issue, we present a new resistor network (RN) forward solver based on a multi-resolution grid approach. This solver utilizes an RN to avoid the massive degrees of freedom resulting from fine discretization of high-voltage conductors and enhances grid discretization efficiency near the surface grounding system through multi-resolution grids. We demonstrate, through multiple three-dimensional geoelectrical model cases, that the proposed method reduces the forward modeling misfit to 1% and possesses only 3‰ of the required discrete elements compared to traditional approaches. Furthermore, practical HVDC grid model analyses indicate the successful application of the proposed method for GRC analysis in complex geoelectric conditions. Full article

The accurate measurement of mass flow rates is important in nuclear power plants. Flow meters have been invented and widely applied in several industries; however, the operating environment in advanced nuclear power plants is especially harsh due to high temperatures, high radiation, and potentially corrosive conditions. Traditional flow meters are largely limited to deployment at the outlet of pumps, on pipes, or in limited geometries. Cross-correlation function (CCF) flow estimation, on the other hand, can estimate the flow velocity indirectly without any specific instruments for flow measurement and in any geometry of the flow region. CCF flow estimation relies on redundant instruments, typically temperature sensors, in series in the direction of flow. One challenge for CCF flow estimation is that the accuracy of the flow measurement is mainly determined by inherent, common local process variation across the sensors, which may be small compared to the uncorrelated measurement noise. To differentiate the process variations from the uncorrelated noise, this research implements periodic fluid injection at a different temperature than the bulk fluid before the temperature sensors to amplify process variation. The feasibility and accuracy of this method are investigated through flow loop experiments and Computational Fluid Dynamics (CFD) simulations. This paper focuses on a CFD simulation model to verify the previous experimental results and optimize CCF flow estimation with different configurations. The optimization study is carried out to perform a grid search on the optimal location of the sensor pair under different flow rates. The CFD results show that the optimal sensor spacing depends on the flow rate being measured and provides guidance for sensor location implementation under various anticipated flow rates. Full article

Background: This systematic review searched to identify a potential biomarker in serum/plasma or cerebrospinal fluid (CSF) to differentiate between relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). There is currently no definitive method for determining whether a patient is in the RRMS course or has converted to the SPMS course. A biomarker could therefore aid the clinician to make this diagnosis. The aim of this study is to assess if there are biomarkers or combinations of biomarkers in serum/plasma or CSF that can detect secondary progression in multiple sclerosis at an early stage. Methods: The PubMed and EMBASE databases were searched to identify relevant studies. Both MeSH terms and text words in the title/abstract were used in both search strategies. The method included forward and backward citation searches. A risk of bias tool was used to assess all the studies that were included. Results: A total of 7581 articles were identified from the initial search. Additionally, 3386 articles were added after the citation search. Of these, 39 articles fulfilled the inclusion criteria and none of the exclusion criteria. The review investigated 28 different biomarkers in CSF and serum/plasma. Discussion: Of the 28 different biomarkers, six biomarkers appeared to be the most promising: neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), Galectin-9, YKL-40/CHI3L1, osteopontin, and MCP-1. This review provides new insights into potential directions for future studies to investigate biomarkers as a diagnostic tool for SPMS. Full article

Background: Resveratrol is a potent phytochemical known for its potential in treating cardiometabolic multimorbidity. However, its underlying mechanisms remain unclear. Our study systematically investigates the effects of resveratrol on cardiometabolic multimorbidity and elucidates its mechanisms using network pharmacology and molecular docking techniques. Methods: We screened cardiometabolic multimorbidity-related targets using the OMIM, GeneCards, and DisGeNET databases, and utilized the DSigDB drug characterization database to predict resveratrol’s effects on cardiometabolic multimorbidity. Target identification for resveratrol was conducted using the TCMSP, SymMap, DrugBank, Swiss Target Prediction, CTD, and UniProt databases. SwissADME and ADMETlab 2.0 simulations were used to predict drug similarity and toxicity profiles of resveratrol. Protein–protein interaction (PPI) networks were constructed using Cytoscape 3.9.1 software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed via the DAVID online platform, and target-pathway networks were established. Molecular docking validated interactions between core targets and resveratrol, followed by molecular dynamics simulations on the optimal core proteins identified through docking. Differential analysis using the GEO dataset validated resveratrol as a core target in cardiometabolic multimorbidity. Results: A total of 585 cardiometabolic multimorbidity target genes were identified, and the predicted results indicated that the phytochemical resveratrol could be a major therapeutic agent for cardiometabolic multimorbidity. SwissADME simulations showed that resveratrol has potential drug-like activity with minimal toxicity. Additionally, 6703 targets of resveratrol were screened. GO and KEGG analyses revealed that the main biological processes involved included positive regulation of cell proliferation, positive regulation of gene expression, and response to estradiol. Significant pathways related to MAPK and PI3K-Akt signaling pathways were also identified. Molecular docking and molecular dynamics simulations demonstrated strong interactions between resveratrol and core targets such as MAPK and EGFR. Conclusions: This study predicts potential targets and pathways of resveratrol in treating cardiometabolic multimorbidity, offering a new research direction for understanding its molecular mechanisms. Additionally, it establishes a theoretical foundation for the clinical application of resveratrol. Full article

The aim of this study was to assess the environmental impact of using recycled polyethylene film for shrink-wrapping bottles. For this aim, film properties were tested and the harmfulness of the packaging process was simulated for film made from virgin and recycled material. For the recycled film, the results showed an increase of 14.7% in impact resistance, a change from −21.6 to +94.3% in tear resistance, and a decrease of up to 45.4% in tensile strength in dependence on the test direction. Using differential scanning calorimetry (DSC), the changes in the properties of the two types of film with temperature changes were evaluated. DSC analysis showed that recycled film has a 1.94 °C lower glass transition temperature and a 1.85 °C lower melting point in comparison to polyethylene film. This can reduce the temperature of the packaging process and lead to energy savings. A study conducted with SimaPro 9.3 software showed that a change in films made of virgin raw material to recycled films reduces the negative impact on the environment from 68.5 to 11.5%. The change also reduces resource consumption by about 80 percent. The results of conducted tests and simulations showed that using recycled film for bottle packaging allows reducing the negative environmental impact of examined process, especially in terms of resource consumption and energy savings. Full article

Psoriatic arthritis (PsA) is a chronic inflammatory condition affecting about one-third of individuals with psoriasis. Defining axial involvement in PsA (axPsA) remains debated. While rheumatologists guide clinical practice, consensus on axPsA is still lacking. This paper explores historical and upcoming definitions from the Axial Involvement in Psoriatic Arthritis (AXIS) study, which aims to establish a validated axPsA definition. Epidemiological data reveal diverse axPsA prevalence rates, emphasizing its complex relationship with peripheral arthritis and enthesitis. Unique genetic, clinical, and radiological features differentiate axPsA from ankylosing spondylitis (AS), necessitating refined classification criteria. The recommendations from the Assessment of Spondylarthritis international Society (ASAS) provide valuable guidance due to the limited direct evidence. Emerging therapies, including interleukin-23 (IL-23) inhibitors or Janus kinase (JAK) inhibitors, are under investigation for axPsA. Currently, secukinumab, an interleukin-17 (IL-17) inhibitor, is an evidence-based option for axPsA management. However, given the variability in individual patient responses and disease manifestations, personalized, evidence-based treatment approaches remain essential for optimizing patient outcomes. In the final section, two real-life cases illustrate the challenges in managing axPsA, emphasizing the importance of tailored therapies. Achieving precision in defining axPsA remains a formidable task, making detailed criteria essential for effective strategies and improving patient outcomes. Full article

The bottle gourd [Lagenaria siceraria (Molina) Standl.] is often utilized as a rootstock for watermelon grafting. This practice effectively mitigates the challenges associated with continuous cropping obstacles in watermelon cultivation. The lower ground temperature has a direct impact on the rootstocks’ root development and nutrient absorption, ultimately leading to slower growth and even the onset of yellowing. However, the mechanisms underlying the bottle gourd’s regulation of root growth in response to low root zone temperature (LRT) remain elusive. Understanding the dynamic response of bottle gourd roots to LRT stress is crucial for advancing research regarding its tolerance to low temperatures. In this study, we compared the physiological traits of bottle gourd roots under control and LRT treatments; root sample transcriptomic profiles were monitored after 0 h, 48 h and 72 h of LRT treatment. LRT stress increased the malondialdehyde (MDA) content, relative electrolyte permeability and reactive oxygen species (ROS) levels, especially H₂O₂ and O²⁻. Concurrently, LRT treatment enhanced the activities of antioxidant enzymes like superoxide dismutase (SOD) and peroxidase (POD). RNA-Seq analysis revealed the presence of 2507 and 1326 differentially expressed genes (DEGs) after 48 h and 72 h of LRT treatment, respectively. Notably, 174 and 271 transcription factors (TFs) were identified as DEGs compared to the 0 h control. We utilized quantitative real-time polymerase chain reaction (qRT-PCR) to confirm the expression patterns of DEGs belonging to the WRKY, NAC, bHLH, AP2/ERF and MYB families. Collectively, our study provides a robust foundation for the functional characterization of LRT-responsive TFs in bottle gourd roots. Furthermore, these insights may contribute to the enhancement in cold tolerance in bottle gourd-type rootstocks, thereby advancing molecular breeding efforts. Full article