Search Results (8,413)

Self-supervised monocular depth estimation from oblique UAV videos is crucial for enabling autonomous navigation and large-scale mapping. However, existing self-supervised monocular depth estimation methods face key challenges in UAV oblique video scenarios: depth discontinuity from geometric distortion under complex viewing angles, and spatial ambiguity in weakly textured regions. These challenges highlight the need for models that combine global reasoning with geometric awareness. Accordingly, we propose RMTDepth, a self-supervised monocular depth estimation framework for UAV imagery. RMTDepth integrates an enhanced Retentive Vision Transformer (RMT) backbone, introducing explicit spatial priors via a Manhattan distance-driven spatial decay matrix for efficient long-range geometric modeling, and embeds a neural window fully-connected CRF (NeW CRFs) module in the decoder to refine depth edges by optimizing pairwise relationships within local windows. To mitigate noise in COLMAP-generated depth for real-world UAV datasets, we constructed a high-fidelity UE4/AirSim simulation environment, which generated a large-scale precise depth dataset (UAV SIM Dataset) to validate robustness. Comprehensive experiments against seven state-of-the-art methods across UAVID Germany, UAVID China, and UAV SIM datasets demonstrate that our model achieves SOTA performance in most scenarios. Full article

In this paper we present an exact numerical model for the evaluation of a three-echelon supply chain with multiple retailers. Poisson demand, exponentially distributed transportation times and lost sales at the retailers are assumed. The system is modeled as a continuous time Markov chain, and the analysis is based on matrix analytic methods. We analyze the infinitesimal generator matrix of the process and develop an algorithm for its construction. Performance measures for the system are calculated algorithmically from the stationary probabilities vector. The algorithm is used for an extensive numerical investigation of the system so that conclusions of managerial importance may be drawn. Full article

Ovarian cancer is a highly lethal malignancy, characterised by late-stage diagnosis, marked inter- and intra-tumoural heterogeneity, and frequent development of chemoresistance. Existing preclinical models, including conventional two-dimensional cultures, three-dimensional spheroids, and organoids, only partially recapitulate the structural and functional complexity of the ovarian tumour microenvironment (TME). Tumour-on-chip (CoC) technology has emerged as a promising alternative, enabling the co-culture of tumour and stromal cells within a microengineered platform that incorporates relevant extracellular matrix components, biochemical gradients, and biomechanical cues under precisely controlled microfluidic conditions. This review provides a comprehensive overview of CoC technology relevant to ovarian cancer research, outlining fabrication strategies, device architectures, and TME-integration approaches. We systematically analyse published ovarian cancer-specific CoC models, revealing a surprisingly limited number of studies and a lack of standardisation across design parameters, materials, and outcome measures. Based on these findings, we identify critical technical and biological considerations to inform the rational design of next-generation CoC platforms, with the aim of improving their reproducibility, translational value, and potential for personalised medicine applications. Full article

The transition to electric mobility has intensified efforts to develop battery technologies that are not only high-performing but also environmentally sustainable. A critical element in battery system design is the structural housing, which must provide effective impact protection to ensure passenger safety and prevent catastrophic failures. This study examines the impact response of an innovative sheet molding compound (SMC) composite battery housing, manufactured from an Elium resin modified with Martinal ATH matrix, reinforced with glass fibers, that combines fire resistance and recyclability, unlike conventional thermoset and metallic housings. The material was characterized through standardized mechanical tests, and its impact performance was evaluated via drop-weight experiments on plates and a full-scale housing. The impact tests were conducted at varying energy levels to induce barely visible impact damage (BVID) and visible impact damage (VID). A finite element model was developed in LS-DYNA using the experimentally derived material properties and was validated against the impact tests. Parametric simulations of ground and pole collisions revealed the critical velocity thresholds at which housing deformation begins to affect the first battery cells, while lower-energy impacts were absorbed without compromising the pack. The study provides one of the first combined experimental and numerical assessments of Elium SMC in battery enclosures, emphasizing its potential as a sustainable alternative for next-generation battery systems for transport applications. Full article

The valorization of agroindustrial residues represents a sustainable alternative in the production of materials attractive for sustainable technologies. In this work, cellulosic materials were isolated from treated pea pods aiming to obtain highly crystalline, thermally stable reinforcements for biocomposites. Four different treatments were evaluated; two employed 0.5 or 0.75 M oxalic acid (OA) solutions at 90 °C, and two used 5% w/v KOH solutions after each OA treatment. The cellulosic materials (10, 20 wt.%) were compounded with a polylactic acid (PLA) matrix and polyvinyl alcohol (0, 2.5 wt.%) as a compatibilizer by extrusion. Compression molding was used to obtain samples to study the composite’s mechanical and thermal behavior. The cellulosic materials and the composites were characterized by Fourier transform infrared spectroscopy, thermogravimetry, and calorimetry. The composites were also subjected to flexural, thermo-mechanical, and water absorption testing. The cellulosic reinforcements obtained using 0.75 M OA and 0.5 M OA and KOH showed the highest crystallinities (91–92%). In general, 20 wt.% reinforced composites showed lower thermal expansion and higher water absorption than those incorporating 10 wt.% reinforcements. The composites incorporating 10 wt.% of 0.5 M OA treated pea pods exhibited flexural modulus/strength 17/3% higher than that of PLA. The composites incorporating 20 wt.% of 0.5 M OA and KOH-treated pea pods showed the highest flexural modulus/strength, 35/25% higher than that of PLA. These results show that agroresidues treated with low-concentration organic acids can be effectively used to tune the mechanical, thermal, and water absorption behavior of biodegradable composites. Full article

Molecularly imprinted polymer (MIP) biosensors offer an attractive strategy for selective biomolecule detection, yet imprinting proteins with structural fidelity remains a major challenge. In this work, we present a rationally designed electrochemical biosensor for matrix metal-loproteinase-8 (MMP-8), a key salivary biomarker of periodontal disease. By integrating graphene oxide (GO) with electropolymerized poly(eriochrome black T, EBT) films on screen-printed carbon electrodes, the partially reduced GO interface enhanced electrical conductivity and facilitated the formation of well-defined poly(EBT) films with re-designed polymerization route, while template extraction generated artificial antibody-like sites capable of specific protein binding. The MIP-based electrodes were comprehensively validated through morphological, spectroscopic, and electrochemical analyses, demonstrating stable and selective recognition of MMP-8 against structurally similar interferents. Complementary density functional theory (DFT) modeling revealed energetically favorable interactions between the EBT monomer and catalytic residues of MMP-8, providing molecular-level insights into imprinting specificity. These experimental and computational findings highlight the importance of rational monomer selection and nanomaterial-assisted polymerization in achieving selective protein imprinting. This work presents a systematic approach that integrates electrochemical engineering, nanomaterial interfaces, and computational validation to address long-standing challenges in protein-based MIP biosensors. By bridging molecular design with practical sensing performance, this study advances the translational potential of MIP-based electrochemical biosensors for point-of-care applications. Full article

The olive tree (Olea europaea L.) has been cultivated for millennia, with olive oil representing both a cornerstone of the Mediterranean diet and a major agricultural commodity. Its composition, rich in monounsaturated fatty acids, polyphenols, tocopherols and squalene, supports well-documented cardioprotective, antioxidant and anti-inflammatory benefits. Olive oil production generates substantial secondary streams, including pomace, leaves, pits and mill wastewater, which are rich in phenols, triterpenes and fibers. This review consolidates recent advances in their phytochemical characterization, innovative extraction technologies and health-promoting effects, while highlighting the economic and regulatory prospects for industrial adoption. Comparative analysis shows that olive leaves can produce up to 16,674.0–50,594.3 mg/kg total phenolics; oleuropein 4570.0–27,547.7 mg/kg, pomace retains 2.24 g GAE/100 g dried matrix (DM)total phenolics; oil 13.66% DM; protein 6.64% DM, and wastewater contains high concentration of phenolics content of olives. Innovative extraction techniques, such as ultrasound and microwave-assisted methods, allow for a recovery, while reducing solvent use and energy input. The analysis highlights opportunities for integrating these by-products into circular bioeconomy models, supporting the development of functional foods, nutraceutical applications and sustainable waste management. Future research should address techno-economic feasibility, regulatory harmonization and large-scale clinical validation to accelerate market translation. Full article

As native bovine whey (WHEY) poses environmental concerns as a high-water-content by-product, this trial aimed at assessing the effectiveness of a thermal–mechanical microparticulation coupled with a fermentative process to concentrate it into a high-protein soft dairy cream. Compared to native whey, in microparticulated (MPW) and fermented (FMPW) matrices, there was a significant increase in proteins (from 0.7 to 8.8%) and lipids (from 0.3 to 1.3%), and a more brilliant yellowness colour. A factorial discriminant analysis (FDA) showed that FMPW had a higher content of saturated fatty acid (SFA) and some specific polyunsaturated fatty acid (PUFA) n-6, and also identified C14:0, C18:1, C18:1 t-11, C18:2 n-6, and C18:3 n-6 as informative biomarkers of microparticulation and fermentative treatments. The SDS-PAGE indicated no effects on the protein profile but indicated its rearrangement into high molecular weight aggregates. Z-sizer and transmission electron microscopy analyses confirmed a different supramolecular structure corresponding to a higher variability and greater incidence of very large molecular aggregates, suggesting that MPW could be accounted as a colloidal matrix that may have similar ball-bearing lubrication properties. Microparticulation of whey could facilitate its circularity into the dairy supply chain through its re-generation from a waste into a high-value fat replacer for dairy-based food production. Full article

This study presents a method for deriving closed-form solutions for Lagrange multipliers in worst-case performance optimization (WCPO) beamforming. By approximating the array-received signal autocorrelation matrix as a rank-1 Hermitian matrix using the low-rank approximation theory, analytical expressions for the Lagrange multipliers are derived. The method was first developed for a single plane wave scenario and then generalized to multiplane wave cases with an autocorrelation matrix rank of N. Simulations demonstrate that the proposed Lagrange multiplier formula exhibits a performance comparable to that of the second-order cone programming (SOCP) method in terms of signal-to-interference-plus-noise ratio (SINR) and direction-of-arrival (DOA) estimation accuracy, while offering a significant reduction in computational complexity. The proposed method requires three orders of magnitude less computation time than the SOCP and has a computational efficiency similar to that of the diagonal loading (DL) technique, outperforming DL in SINR and DOA estimations. Fourier amplitude spectrum analysis revealed that the beamforming filters obtained using the proposed method and the SOCP shared frequency distribution structures similar to the ideal optimal beamformer (MVDR), whereas the DL method exhibited distinct characteristics. The proposed analytical expressions for the Lagrange multipliers provide a valuable tool for implementing robust and real-time adaptive beamforming for practical applications. Full article

Conductive hydrogels (CHs) have attracted significant attention in the fields of flexible electronics, human–machine interaction, and electronic skin (e-skin) due to their self-adhesiveness, environmental stability, and multi-stimuli responsiveness. However, integrating these diverse functionalities into a single conductive hydrogel system remains a challenge. In this study, polyvinyl alcohol (PVA) and polyacrylamide (PAM) were used as the dual-network matrix, lithium chloride and MXene were added, and a simple immersion strategy was adopted to synthesize a multifunctional MXene-based conductive hydrogel in a glycerol/water (1:1) binary solvent system. A subsequent investigation was then conducted on the hydrogel. The prepared PVA/PAM/LiCl/MXene hydrogel exhibits excellent tensile properties (~1700%), high electrical conductivity (1.6 S/m), and good self-healing ability. Furthermore, it possesses multimodal sensing performance, including humidity sensitivity (sensitivity of −1.09/% RH), temperature responsiveness (heating sensitivity of 2.2 and cooling sensitivity of 1.5), and fast pressure response/recovery times (220 ms/230 ms). In addition, the hydrogel has successfully achieved real-time monitoring of human joint movements (elbow and knee bending) and physiological signals (pulse, breathing), as well as enabled monitoring of spatial pressure distribution via a 3 × 3 sensor array. The performance and versatility of this hydrogel make it a promising candidate for next-generation flexible sensors, which can be applied in the fields of human health monitoring, electronic skin, and human–machine interaction. Full article

Corneal regeneration has gained growing interest in recent years, largely due to the limitations of conventional treatments and the persistent shortage of donor tissue. Among the emerging strategies, extracellular vehicles (EVs), especially those derived from mesenchymal stromal cells (MSCs), have shown great promise as a cell-free therapeutic approach. These nanoscale vesicles contribute to corneal healing by modulating inflammation, supporting epithelial and stromal regeneration, and promoting nerve repair. Their therapeutic potential is largely attributed to the diverse and bioactive proteomic cargo they carry, including growth factors, cytokines, and proteins involved in extracellular matrix remodeling. This review presents a comprehensive examination of the proteomic landscape of EVs in the context of corneal regenerative medicine. We explore the biological functions of EVs in corneal epithelial repair, stromal remodeling, and neurodegeneration. In addition, we discuss advanced proteomic profiling techniques such as mass spectrometry (MS) and liquid chromatography–mass spectrometry (LC-MS/MS), which have been used to identify and characterize the protein contents of EVs. This review also compares the proteomic profiles of EVs derived from various MSC sources, including adipose tissue, bone marrow, and umbilical cord, and considers how environmental cues, such as hypoxia and inflammation, influence their protein composition. By consolidating current findings, this article aims to provide valuable insights for advancing the next generation of cell-free therapies for corneal repair and regeneration. Full article

Landslides are common in mountainous regions and can significantly affect human life and infrastructure. The aim of this study is to analyze the role of hydrothermally altered rocks in generating ground instability and triggering debris flows in the Canoas microbasin, Sierra de Angangueo, within the Monarch Butterfly Biosphere Reserve. We characterized the unaltered (andesite) and altered (andesitic breccia) rocks from the landslide scarp through fieldwork and laboratory analysis. The altered rock exhibited an extremely low simple compressive strength of 0.47 ± 0.05 MPa. In contrast, the unaltered rock exhibited a higher strength of 36.26 ± 18.62 MPa and lower porosity. Petrographic analysis revealed that the unaltered rock primarily consists of an andesitic groundmass with plagioclase and orthopyroxene phenocrysts partially altered to sericite and kaolin. In comparison, the altered rock contains a matrix rich in clay, iron oxides, and completely replaced phenocrysts. The andesitic breccia has a high proportion of clay and silt and displays soil-like mechanical properties, making it vulnerable to saturation collapse during heavy rainfall. This research offers valuable insights into geological risk management in mountainous volcanic regions. The findings demonstrate that the presence of hydrothermally altered andesitic breccia with weak geomechanical properties was the critical factor that triggered the Canoas debris flow, underscoring hydrothermal alteration as a key control of slope instability in volcanic settings. Full article

Head and neck cancer (HNC) is highly heterogeneous and difficult to treat, underscoring the need for rapid, patient-specific models. Standard three-dimensional (3D) cultures often lose stromal partners that influence therapy response. We developed a patient-derived system maintaining tumor cells, cancer-associated fibroblasts (CAFs), and cells undergoing partial epithelial–mesenchymal transition (pEMT) for drug sensitivity testing. Biopsies from four HNC patients were enzymatically dissociated. CAFs were directly cultured, and their conditioned medium (CAF-CM) was collected. Cryopreserved primary tumor cell suspensions were later revived, screened in five different growth media under 2D conditions, and the most heterogeneous cultures were re-embedded in 3D hydrogels with varied gel mixtures, media, and seeding geometries. Tumoroid morphology was quantified using a perimeter-based complexity index. Viability after treatment with cisplatin or Notch modulators (RIN-1, recombination signal-binding protein for immunoglobulin κ J region (RBPJ) inhibitor; FLI-06, inhibitor) was assessed by live imaging and the water-soluble tetrazolium-8 (WST-8) assay. Endothelial Cell Growth Medium 2 (ECM-2) medium alone produced compact CAF-free spheroids, whereas ECM-2 supplemented with CAF-CM generated invasive aggregates that deposited endogenous matrix. Matrigel with this medium and single-point seeding gave the highest complexity scores. Two of the three patient tumoroids were cisplatin-sensitive, and all showed significant growth inhibition with the FLI-06 Notch inhibitor, while the RBPJ inhibitor RIN-1 induced minimal change. The optimized scaffold retains tumor–stroma crosstalk and provides patient-specific drug response data within days after operation, supporting personalized treatment selection in HNC. Full article

Background: The implant–abutment interface has been thoroughly examined due to its impact on the success of implant healing and longevity. Removing the abutment is advantageous, but it changes the biomechanics of the implant fixture and restoration. This in vitro three-dimensional finite element analytical (FEA) study aims to evaluate the distribution of von Mises stress (VMS) in abutment-free and three additional implant abutment connections composed of various titanium alloys. Materials and methods: A three-dimensional implant-supported single-crown prosthesis model was digitally generated on the mandibular section using a combination of microcomputed tomography imaging (microCT), a computer-assisted designing (CAD) program (SolidWorks), Analysis of Systems (ANSYS), and a 3D digital scan (Visual Computing Lab). Four digital models [A (BioHorizons), B (Straumann AG), C abutment-free (Matrix), and D (TRI)] representing three different functional biomaterials [wrought Ti-6Al-4Va ELI, Roxolid (85% Ti, 15% Zr), and Ti-6Al-4V ELI] were subjected to simulated static/cyclic static loading in axial/oblique directions after being restored with highly translucent monolithic zirconia restoration. The stresses generated on the implant fixture, abutment, crown, screw, cortical, and cancellous bones were measured. Results: The highest VMSs were generated by the abutment-free (Model C, Matrix) implant system on the implant fixture [static (32.36 Mpa), cyclic static (83.34 Mpa)], screw [static (16.85 Mpa), cyclic static (30.33 Mpa), oblique (57.46 Mpa)], and cortical bone [static (26.55), cyclic static (108.99 Mpa), oblique (47.8 Mpa)]. The lowest VMSs in the implant fixture, abutment, screw, and crown were associated with the binary alloy Roxolid [83–87% Ti and 13–17% Zr]. Conclusions: Abutment-free implant systems generate twice the stress on cortical bone than other abutment implant systems while producing the highest stresses on the fixture and screw, therefore demanding further clinical investigations. Roxolid, a binary alloy of titanium and zirconia, showed the least overall stresses in different loadings and directions. Full article

A versatile, clear, and accurate method for determining the steady states of multi-component diffusion through composite membranes is presented in this study. This method can be used for simulating and designing membranes with any support orientation with respect to the zeolite film. In the mathematical model of the membrane, it was assumed that mass transport in the zeolite layer occurs by surface diffusion in accordance with the generalized Maxwell–Stefan model. Diffusion in the macroporous support was described by the dusty gas model (DGM). An alternative model of diffusion in the zeolite was proposed to the universally accepted model, which uses a matrix of thermodynamic factors G. Thus, the difficulty of analytically determining this matrix for more complex adsorption equilibria was eliminated. This article is dedicated to methodological and cognitive aspects. The practical features of the method are illustrated using two gas mixtures as examples, namely {H₂, CO₂} and {H₂, n-C₄H₁₀}. The roles of zeolite and support in the separation of these mixtures are discussed. It was demonstrated under what circumstances the presence of the support can be neglected in the steady-state analysis of the membrane. The effect of the alternative application of the dusty gas model or viscous flow only in the microporous support was discussed. Full article