Search Results (2,245)

This study presents the development and characterization of Grätzel cells (DSSCs), part of third-generation photovoltaic technologies, fabricated with and without the addition of graphene nanoparticles. A TiO₂ paste was prepared by combining colloidal solutions of Polyethylene Glycol (PEG) and Titanium Tetrachloride (TiCl₄), and then deposited on FTO (Fluorine-doped Tin Oxide) glass substrates via spin coating and sensitized with N719 dye. Each cell was assembled using two FTO electrodes, a photoanode (TiO₂/N719) and a platinum-coated counter electrode, separated by a liquid iodide/triiodide-based electrolyte to complete the redox cycle. The core objective was to optimize the graphene nanoparticle concentration within the TiO₂ matrix to improve photovoltaic performance. Samples with 0.1%, 0.2%, and 0.5% graphene were tested under simulated illumination (AM 1.5G), evaluating photocurrent, efficiency, and Fill Factor (FF). Optical analysis included desorption of N719 using NaOH to quantify intrinsic light absorption. Graphene’s high transparency and charge transport properties positively affected light harvesting. Results showed that graphene dosage is critical; 0.1% yielded the best efficiency, while excess concentrations diminished electronic and optical behavior. Controlled integration of graphene nanoparticles enhances DSSC performance and supports the development of more efficient and sustainable solar cells. Full article

With the widespread application of multi-view data across various domains, multi-view unsupervised feature selection (MUFS) has achieved remarkable progress in both feature selection (FS) and missing-view completion. However, existing MUFS methods typically rely on centralized servers, which not only fail to meet privacy requirements in distributed settings but also suffer from suboptimal FS quality and poor convergence. To overcome these challenges, we propose a novel federated incomplete MUFS method (Fed-IMUFS), which integrates a fractional Sparsity-Guided Whale Optimization Algorithm (SGWOA) and Tensor Alternating Learning (TAL). Within this federated learning framework, each client performs local optimization in two stages: in the first stage, SGWOA introduces an $L_{2,1}$ proximal projection to enforce row-sparsity in the FS weight matrix, while fractional-order dynamics and fractal-inspired elite kernel injection mechanisms enhance global search ability, yielding a discriminative and stable weight matrix; in the second stage, based on the obtained weight matrix, an alternating optimization framework with tensor decomposition is employed to iteratively complete missing views while simultaneously optimizing low-dimensional representations to preserve cross-view consistency, with the objective function gradually minimized until convergence. During federated training, the server employs an aggregation and distribution strategy driven by normalized mutual information, where clients upload only their local weight matrices and quality indicators, and the server adaptively fuses them into a global FS matrix before distributing it back to clients. This process achieves consistent FS across clients while safeguarding data privacy. Comprehensive evaluations on CEC2022 and several incomplete multi-view datasets confirm that Fed-IMUFS outperforms state-of-the-art methods, delivering stronger global optimization capability, higher-quality feature selection, faster convergence, and more effective handling of missing views. Full article

Background/Objectives: This study proposes a framework for building a statistical prediction model for dental clinics to facilitate the diagnosis of periodontitis and its stages. The method is based on active-matrix metalloproteinase-8 (aMMP-8) mouth rinse point-of-care testing (POCT). Methods: A complete model was created within a three-step modeling scenario: (i) the first function differentiates healthy patients from those with periodontitis; (ii) the second function differentiates stage I and II patients from stage III patients; and (iii) the third function separates stage I and II patients from each other. The model was developed using logistic regression analysis, and the aMMP-8 POCT results utilized in the predictive functions were obtained from an Oralyzer digital reader. Sample data comprised 149 adult patients who visited dental clinics in Thessaloniki, Greece. Results: Patients without periodontitis were identified in 74.2% of cases (95% CI: 55.1–87.5%). Patients with periodontitis were revealed with a success rate of 94.1% (95% CI: 87.7–97.4%), and of these, the correct stage was determined in 71.2% of cases (95% CI: 61.7–79.2%). The complete model was tested on the same patient data from which it was formed. Conclusions: The results of the study showed that logistic regression can be used in the development of a model for dental clinics to reveal and stage periodontitis with sufficient accuracy. In the complete model created, aMMP-8 mouth rinse POCT results in ng/mL, visible plaque index (VPI), and the information on the patient’s missing teeth were statistically important factors in determining the presence and stage of periodontitis. Full article

Mesenchymal chondrosarcoma (MCS) is characterised by small round cell biology, frequent HEY1-NCOA2 fusion, and high vascularity. These features plausibly lessen extracellular matrix barriers and confer relative chemosensitivity. We synthesised peri-operative (preoperative/neoadjuvant; postoperative/adjuvant) and palliative chemotherapy outcomes separately across multiple cohorts and case reports as well as the summarised the guidelines (ESMO/NCCN) In localised disease, integrating multi-agent Ewing-type chemotherapy with complete resection is associated with improved disease control. Contemporary 5-year overall survival (OS) typically spans ~55–73% across studies, while event-free survival (EFS) gains are demonstrated more consistently than OS gains in pooled analyses. In advanced MCS, first-line polychemotherapy yields modest, non-curative activity, with objective response rates (ORRs) of ~25–35% in adults, median progression-free survival (PFS) of ~4.7–6.7 months, and median OS of ~18 months. Activity may be higher in younger patients and for platinum–anthracycline combinations. We also discussed emerging therapies. Trabectedin demonstrates low disease control rate in translocation-related sarcomas, including few MCS cases. Anti-angiogenic tyrosine kinase inhibitors, such as apatinib and pazopanib, demonstrate activity in chondrosarcoma, but MCS-specific data are lacking. IDH1 inhibition benefits conventional subtypes rather than MCS. Early immunotherapy experience is limited, but pathway-directed strategies targeting BCL2 and PI3K-mTOR warrant evaluation. Full article

Background and Objectives: Myofibroblast apoptosis resistance and excessive extracellular matrix (ECM) deposition are central drivers of the irreversibility of pulmonary fibrosis, and both are mechanistically linked to autophagy impairment. Phaseoloidin is a bioactive compound derived from Entada phaseoloides. This study aimed to investigate the therapeutic potential of Phaseoloidin in bleomycin-induced pulmonary fibrosis and its underlying mechanisms. Methods:In vivo, the antifibrotic effects of Phaseoloidin were evaluated using a bleomycin-induced pulmonary fibrosis mouse model in male C57/BL mice. To further elucidate the mechanisms by which Phaseoloidin counteracts fibrosis, in vitro experiments were conducted using primary lung fibroblasts. Results: In vitro experiments showed that Phaseoloidin could activate the AMPK/mTOR pathway in autophagy-deficient myofibroblasts, effectively reversing autophagic defects and promoting collagen degradation. This autophagy activation selectively degraded PTPN13, a negative regulator of apoptosis, thereby enhancing the sensitivity of myofibroblasts to FasL-induced apoptosis and further facilitating fibrosis resolution. After AMPK gene knockout, the pro-autophagic effect of Phaseoloidin completely disappeared, and both collagen clearance and apoptosis recovery were blocked. In vivo experiments confirmed that Phaseoloidin exerted antifibrotic effects by activating AMPK-mediated autophagy in myofibroblasts, which significantly ameliorated pulmonary fibrosis. Conclusions: Phaseoloidin exerts a dual mechanism by activating AMPK-mediated autophagy in myofibroblasts: first, degrading PTPN13 to reverse myofibroblast apoptosis resistance; second, enhancing ECM turnover. These findings indicate that Phaseoloidin is a promising novel therapeutic candidate for pulmonary fibrosis. Full article

The growing generation of solid waste, driven by urbanization and industrialization, represents one of today’s greatest environmental challenges. The construction industry can play a key role in this scenario by incorporating recycling and waste reuse practices. Glass, a fully recyclable material, is still largely disposed of in landfills. A promising alternative is the use of ground glass in cementitious materials, partially or completely replacing cement or aggregates. Thus, in this paper, the effect of partially replacing Portland cement with ground glass of different colors including green, blue, transparent, amber, and colorful (all colors used mixed) in proportions of 15 and 35% in mortars was evaluated. The ground glasses were characterized by laser granulometry and chemical analysis. The properties of the mortars were then evaluated in the fresh and hardened state (apparent specific gravity, mechanical strength, water absorption, and open porosity). Regarding workability, the highest improvement observed was 6.8% for the 35% colored glass series compared to the reference series. In terms of entrapped air, there was an increase of up to 18.8% in the 35% green glass series. At 28 days of hydration, the 15% colored glass series obtained a 33% increase in flexural strength compared to the REF series. In the microstructure, it was found that a 15% glass presence was sufficient to reduce the portlandite index from 16.04 to 13.53, while a 35% glass presence was sufficient to reduce it to 7.51% portlandite, equivalent to a 54% reduction, suggesting significant potential for the reaction of the finer glass fractions with portlandite. This study suggests that the use of glass waste in a cementitious matrix can provide an environmentally appropriate alternative for recycling this material, contributing to a sustainable application and increased recycling rates of glass waste. Full article

Aberrant wound healing in the retina can manifest as proliferative vitreoretinopathy (PVR), which involves the myofibroblast transdifferentiation of retinal pigment epithelial (RPE) cells. In this study, experiments were conducted to examine the structure–activity relationships of endocannabinoid-like compounds, N-acyl dopamines, on the myofibroblast transdifferentiation of RPE cells. The collagen matrix contraction assay was used to assess myofibroblast function. Western blot analysis and immunocytochemistry techniques were used to evaluate myofibroblast markers. N-palmitoyl dopamine (PALDA), N-oleoyl dopamine (OLDA), and N-arachidonoyl dopamine (NADA), in a concentration-dependent manner, inhibited contraction of collagen matrices mediated by either primary porcine RPE cells treated with TGF-β2, or human RPE cells treated with TGF-β2 plus TNFα (TNT). The rank order of potency was PLDA = OLDA > NADA. In contrast, the substitution of dopamine with other polar head groups led to a complete loss of their ability to inhibit myofibroblast transdifferentiation. Western blot analysis demonstrated that PALDA, OLDA, and NADA down-regulated the myofibroblast markers fibronectin and α-SMA. Immunocytochemistry experiments showed that these N-acyl dopamines reduced the incorporation of α-SMA into F-actin stress fibers. Overall, these structure–activity relationship studies demonstrate that the dopamine head group is crucial for N-acyl dopamine to inhibit myofibroblast transdifferentiation of RPE cell, whereas the fatty acid side chain determines the potency of it. This study points to the potential of N-acyl dopamines as a novel class of therapeutic agents for treating retinal fibrotic conditions, such as PVR. Full article

We present the case of a patient with primary CNS lymphoma (PCNSL), with MYD88 and CD79B gene variants, who was unable to complete standard induction and consolidation treatment due to toxicity and co-morbidities after three cycles of MATRix. Although he had responded to truncated induction, acalabrutinib, the BTK inhibitor, was used in an attempt to consolidate and maintain his response. He has an ongoing remission at 18 months of follow-up. Following the case presentation, we provide a review of PCNSL, the evolution of therapy, and how BTK inhibitors are now emerging treatments incorporated into the salvage of relapsed and refractory disease and into first-line treatment in some clinical trials. This is the first reported case in the literature of acalabrutinib use for consolidation and maintenance of PCNSL. We hope this can support clinical trial design for BTKi use in this setting in the future. Full article

Salmonella Enteritidis (SE) remains a leading cause of human illness worldwide, and its persistence in poultry environments might be partially attributed to their ability to form biofilm. This study compared the biofilm capacity of 15 SE and 24 Salmonella Kentucky (SK) isolates from poultry products and processing facilities to uncover genetic factors driving biofilm heterogeneity. Biofilm formation and curli/cellulose production were evaluated at 20–22 °C. Genomic analyses included phylogenetic reconstruction, comparative system profiling, SNP variation, and BLASTp v2.17.0 comparisons. Phenotypic assays showed that most SE isolates (73%) were strong biofilm formers, while the majority of SK isolates (62%) failed to form biofilms, despite many carrying the complete curli–cellulose gene set and other biofilm-associated genes. Genomic analysis identified 124 biofilm-related genes, 108 of which were conserved across all isolates, and revealed 24 variants with potential functional impact. Mutations in cellulose biosynthesis (bcs) genes were linked to weaker biofilms, whereas nonsynonymous variants in tol family genes may impair flagellar biosynthesis and matrix stability. These findings demonstrate that genetic variation, not just gene presence, shapes biofilm phenotypes and highlight key molecular targets that may explain why SE persists in poultry production while SK is less successful. Full article

The control of the quantities of multi-tonnage polymers, in particular, making them biodegradable, is an urgent task. This study suggests a new approach in the application of natural rubber (NR) as an initiator of biodegradation of low-density polyethylene (LDPE) in soil. The study examines the structure, properties and rates of biodegradation of thin LDPE films with different content of NR. Such methods as fourier transform infrared spectroscopy (FTIR), electron paramagnetic resonance (EPR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscope (SEM), atomic force microscopy (AFM), gel-permeation chromatography (GPC), and acoustic microscopy were used for the most complete characterization of NR/LDPE composite systems. It was shown for the first time that at concentrations above 30%, NR is able to form an interpenetrating structure with the LDPE matrix, which has a decisive effect on the initiation of biodegradation during exposure in soil. Thus, the composition with 50% natural rubber exhibits the highest mass loss. The sample with 50% natural rubber content lost 70% of its mass, while the one with 40% NR content lost 38%. Furthermore, after soil burial, a significant decrease in crystallinity was observed: from 39.5% to 31.5% for the 90/10 composition and from 39.1% to 24.2% for the 50/50 composition. The results obtained are confirmed by a noticeable decrease in the molecular weight characteristics of LDPE. Full article

The integrity of real-time monitoring data is paramount to the accuracy of scientific research and the reliability of decision-making. However, data incompleteness arising from transmission interruptions or extreme weather disrupting equipment operations severely compromises the validity of statistical analyses and the stability of modelling. From a mathematical view, real-time monitoring data may be regarded as continuous functions, exhibiting intricate correlations and mutual influences between different indicators. Leveraging their inherent smoothness and interdependencies enables high-precision data imputation. Within the functional data analysis framework, this paper proposes a Diversity Constraint and Adaptive Graph Multi-View Functional Matrix Completion (DCAGMFMC) method. Integrating multi-view learning with an adaptive graph strategy, this approach comprehensively accounts for complex correlations between data from different views while extracting differential information across views, thereby enhancing information utilization and imputation accuracy. Random simulation experiments demonstrate that the DCAGMFMC method exhibits significant imputation advantages over classical methods such as KNN, HFI, SFI, MVNFMC, and GRMFMC. Furthermore, practical applications on meteorological datasets reveal that, compared to these imputation methods, the root mean square error (RMSE), mean absolute error (MAE), and normalized root mean square error (NRMSE) of the DCAGMVNFMC method decreased by an average of 39.11% to 59.15%, 54.50% to 71.97%, and 43.96% to 63.70%, respectively. It also demonstrated stable imputation performance across various meteorological indicators and missing data rates, exhibiting good adaptability and practical value. Full article

As a fundamental information carrier in Industrial Internet of Things (IIoT), electromagnetic spectrum data presents critical challenges for efficient spectrum sensing and situational awareness in smart industrial cognitive radio systems. Addressing sparse sampling limitations caused by energy-constrained transceiver nodes in Unmanned Aerial Vehicle (UAV) spectrum monitoring, this paper proposes a compressive sensing-based 3D spectrum tensor completion framework for extrapolative reconstruction in obstructed areas (e.g., building occlusions). First, a Sparse Coding Neural Gas (SCNG) algorithm constructs an overcomplete dictionary adaptive to wide-range spectral fluctuations. Subsequently, a Bag of Pursuits-optimized Orthogonal Matching Pursuit (BoP-OOMP) framework enables adaptive key-point sampling through multi-path tree search and temporary orthogonal matrix dimensionality reduction. Finally, a Neural Gas competitive learning strategy leverages intermediate BoP solutions for gradient-weighted dictionary updates, eliminating computational redundancy. Benchmark results demonstrate 43.2% reconstruction error reduction at sampling ratios r ≤ 20% across full-space measurements, while achieving decoupling of highly correlated overlapping subspaces—validating superior estimation accuracy and computational efficiency. Full article

We investigate the phenomenon of quantum interference in spontaneous emission pathways for a quantum emitter embedded in a two-dimensional photonic crystal composed of a square lattice of dielectric cylindrical rods. Using a V-type three-level system as a model, we demonstrate that the anisotropic Purcell effect inherent in such photonic structures can amplify quantum interference to its theoretical maximum, where the degree of interference p reaches unity. This results in the complete suppression of spontaneous emission for one polarization (directional suppression) and the emergence of coherent population trapping without the need for external coherent fields. By employing density matrix formalism, we derive analytical expressions for the population dynamics and identify conditions for indefinite or long-lived excited-state population. Our findings can find application in quantum technologies, including high-precision atomic clocks, magnetometry, and quantum information processing. Full article

Oil recovery from low-permeability (‘tight’) oil reservoirs remains low despite the application of modern drilling and completions technologies, which has increased interest in trialing enhanced oil recovery (EOR) schemes. Cyclic gas injection (Huff-n-Puff, HNP) is a promising approach to EOR for these reservoirs. However, the underlying mechanisms of EOR using the HNP scheme in tight reservoirs are not yet fully understood. This laboratory study investigates the performance of lean gas (80%C₁ + 20%C₂; approximating produced gas compositions from the field) HNP using low-permeability core plug samples from the Montney Formation of Canada. An objective of the study was to evaluate the effects of induced fractures, and brine saturation and distribution, on the efficiency of lean gas HNP performance. Both intact and artificially fractured core plugs were studied. The introduction of fractures into the low-permeability core plugs improved recovery factors by 17.5–18.5%. However, the presence of brine limited oil production from both intact and fractured core plugs. Notably, when brine was concentrated along the fracture surfaces, the recovery factor dropped significantly, down to just 1.2% of original oil in place (OOIP). This reduction is primarily attributed to the low solubility of methane and ethane (C₁ + C₂) in brine, which hinders the injectant’s ability to diffuse into the core matrix and mobilize oil. The findings of this study will be of interest to operators evaluating the potential of cyclic gas injection in low-permeability reservoirs. Full article

A long-standing challenge for the structural health monitoring (SHM) community is the masking effect of environmental variability, typically addressed by orthogonal projection (OP)-based data normalization to isolate the influence of environmental variability and enable structural anomaly detection. However, conventional OP techniques, such as principal component analysis, rely on clean and complete data, and their performance degrades in the presence of outliers or missing entries. To overcome this limitation, this paper proposes an integrated approach that combines OP with noisy low-rank matrix completion (NLRMC). The main advantage of NLRMC is its ability to couple low-rank and sparse decomposition with matrix completion, simultaneously handling data corruption and missingness to recover incomplete datasets and enable robust anomaly detection. By incorporating novelty-indicator extraction, a fully online, unsupervised anomaly-detection procedure is established. Validation on a vibration-based SHM dataset from the KW51 railway bridge confirms that the NLRMC-OP approach achieves reliable detection of operational state changes before and after retrofitting, even under both data corruption and missing scenarios. This study advances the usability of SHM data and facilitates efficient decision-making, while also highlighting the broader significance of leveraging the low-rank data structure in AI-enabled operation and maintenance of civil infra-structure. Full article