Search Results (12,618)

This work presents a systematic investigation on dry milling of TC18 forged alloy using longitudinal ultrasonic vibration assistance. The effects of key parameters (cutting speed, feed per tooth, cutting depth and ultrasonic amplitude) on three-axis cutting forces, cutting temperature and surface quality are explored, and orthogonal experiments are conducted to determine the optimal parameter combination. Results reveal that increasing ultrasonic amplitude reduces cutting temperature by 31.8% and suppresses cutting forces effectively. Cutting depth and feed per tooth act as major influencing factors; the three-directional cutting forces drop by 31.1%, 56.7% and 22.9%, respectively. Surface roughness rises to 0.435 μm and 0.29 μm with growing feed per tooth and cutting depth, and decreases to 0.24 μm at higher cutting speeds. Under ultrasonic assistance, roughness increases slightly first and then declines remarkably. A threshold value exists for ultrasonic amplitude, and periodic tool–workpiece contact transforms strip textures into fish-scale morphologies. Proper parameter matching for ultrasonic milling lowers cutting forces and temperature, and improves surface quality of TC18 alloy. This study offers experimental data and theoretical references for relevant machining research. Full article

The evaluation of wearable robotic systems remains a challenge, particularly in real-world environments where laboratory-based methods are impractical. Existing approaches rely on external instrumentation, such as surface electromyography (sEMG) or motion capture, which are difficult to deploy continuously and do not directly measure key internal metrics such as joint loading or spinal forces. This work introduces a new paradigm for exoskeleton evaluation in which biomechanical assessment is embedded directly within the device’s sensing and computational architecture. We present the ExoMetrix system, a platform that integrates onboard sensing, real-time data acquisition, cloud-based processing, and user-facing analytics into a unified workflow for continuous evaluation of human–exoskeleton interaction. Sensor data from the device are streamed and processed using physics-based models. The resulting outputs are translated into estimates of internal biomechanical quantities, including joint torques, spinal compression and shear forces, and muscle loading. By enabling real-time feedback and longitudinal monitoring without external instrumentation, this approach transforms evaluation from an external, episodic process into an embedded and continuous capability, supporting safer and more scalable deployment of exoskeleton technologies. Full article

Accurate urban building energy modeling (UBEM) is constrained by mismatches between standard climate inputs and actual urban microclimate conditions. This study introduces a scalable, bottom-up, framework that integrates EnergyPlus building energy modeling simulation outputs with Earth observational and geographical-based urban morphology data, which are enhanced through machine learning techniques to improve energy demand predictions in urban settings. Applied to Los Angeles (LA), California, we evaluate the representativeness of typical meteorological year (TMYx) sampling sites against actual urban environmental conditions. We find that while satellite-derived surface temperatures show reasonable alignment with average city conditions, significant discrepancies are observed in urban form metrics such as tree cover, street cover, and building density, suggesting that TMYx stations should be placed in denser urban areas. We augment EnergyPlus simulations for 19 single-family buildings, with remote sensing data using machine learning models, to generate city-wide residential energy consumption heatmaps corrected for microclimate conditions. Models capture substantial intra-urban variation, with predicted energy use differing by approximately 10% between neighborhoods. Feature importance analysis highlights land surface temperature as a key predictor, underscoring its relevance to building energy research. We also find the majority of TMY3 sampling sites to be in low-vulnerability areas, underscoring the structural mismatch that is embedded in urban form and climate. This framework offers a scalable path for integrating urban microclimate effects into energy modeling to enable more precise and equitable energy policy and planning. Full article

This study focused on burn-through leakage at girth welds of mechanically lined pipe (MLP) during field service. Field failure analysis, experimental tests, and numerical simulation were combined to investigate the process parameters of seal welding and multi-pass girth butt welding. Macroscopic metallography and energy dispersive spectroscopy (EDS) of failed specimens showed that excessive welding heat input (high current) caused severe expansion of the heat-affected zone (HAZ) and significant element dilution. The results indicated that the HAZ width of the solid-wire girth weld increased markedly from 1.312 mm to 2.247 mm under high-current conditions. Meanwhile, the Fe mass fraction in the root pass sharply increased to 33.66%, while key corrosion-resistant elements such as Cr and Ni were greatly reduced, which directly led to local pitting corrosion and perforation leakage. In addition, a moving heat source model was established in Abaqus 2024 to simulate the multi-pass welding process. The results showed that strong stress concentration developed at the groove root and the interface between the backing steel pipe and corrosion-resistant liner during repeated thermal cycles. The maximum von Mises stress reached 686.56 MPa during the second butt welding pass. After final cooling, the residual hoop tensile stress and axial tensile stress at the center of the inner surface reached 500–550 MPa and 480–510 MPa, respectively. By correlating microscopic compositional evolution with the macroscopic residual stress field, this study revealed the weld failure mechanism of MLP joints. The proposed finite element method can also be used as an efficient tool to predict the effects of welding speed, current, and voltage on residual stress, providing guidance for field welding procedure optimization and pipeline structural integrity assessment. Full article

A biogenic ZnO/Ag photoelectrode treated with atmospheric-pressure plasma was evaluated as an anode in a photo-assisted electroflotation system for the transformation of chromophoric pollutants in real industrial wastewater. ZnO was synthesized from Azadirachta indica leaf extract and plasma-treated for 10 min (M2) and 15 min (M3), with an untreated reference (M1). XRD, SEM-EDS, Raman, FTIR, EPR, and XPS analyses showed that the plasma preserved the wurtzite structure, relaxed the bulk, and modified the surface by removing residues, deoxygenating it, and activating oxygen vacancies (V_O). Although M3 reached the highest deoxygenation, M2 showed the most favorable response; thus, the performance did not depend only on the total amount of V_O. Under dark conditions, M2 showed a 14.86 percent decrease in COD compared to the control in a single batch and had the most negative ORP value. However, only ORP came close to statistical significance after multiplicity correction, with p_adj = 0.055. Under illumination, it showed the strongest photoinduced changes in conductivity and total suspended solids. The light–dark differences (ΔL−O) showed sign reversals in COD, conductivity, and pH, which identified three functional regimes and indicated that the electronic coupling of the surface V_O, rather than its amount, controlled the performance. ΔL−O was proposed as an operational test to distinguish these regimes, with the plasma exposure time as a key control variable. Because the effluent responses were single determinations, they are considered exploratory; the mechanism is primarily based on structural and spectroscopic characterization and supported by photoelectrochemical tests. Full article

Background/Objectives: Natural calcium carbonate materials such as Rügen chalk have a long history of use in balneology and rehabilitation, particularly for musculoskeletal disorders, yet their application remains largely confined to traditional, labour-intensive forms such as powders, suspensions, and packs, which limit usability and broader clinical translation. This study aimed to develop an alginate-based solid foam incorporating Rügen chalk and to evaluate how key formulation components influence its structural, mechanical, and thermal properties relevant for therapeutic use. Methods: Alginate–chalk foams were prepared by mechanical mixing of a sodium alginate–Rügen chalk paste with an amino acid-based surfactant, while in situ CO₂ generation from D–glucono–δ–lactone (GDL) induced calcium-mediated alginate gelation and foam stabilization. A central composite design with response surface methodology was used to assess the effects of alginate, chalk, and Perlastan^®–GDL content on foam pH, overrun, firmness, springiness, pore volume, sphericity, pore density, specific internal surface area, and heat-loss time. Foam microstructure was characterized by optical microscopy and microcomputed tomography (µCT), and the thermal conductivity and cooling behaviour of the selected formulation were compared with therapeutic peat. Results: Stable, elastic solid foams with a three-dimensional porous architecture were obtained across the investigated composition range. Foam overrun (30.8–57.1%) was primarily governed by sodium alginate and Rügen chalk concentrations, while firmness (7.4–15.2 N) increased predominantly with alginate content, and springiness remained high (70–78%), indicating good elastic recovery. Response surface modelling and ANOVA confirmed sodium alginate as the dominant factor influencing both mechanical and structural properties, with statistically significant effects on overrun, firmness, springiness, heat loss, porosity, and specific internal surface. µCT analysis revealed that all foam formulations were predominantly composed of fine, closed-cell pores, with over 96% of pores having volumes below 0.5 mm³ and a consistent median pore volume of 0.02 mm³. Structural differences between formulations were governed primarily by pore number and spatial distribution rather than pore size. Strong correlations were identified between µCT-derived parameters, particularly between specific internal surface, porosity, and pore density, confirming that internal architecture is controlled by pore population rather than individual pore dimensions. Thermal analysis demonstrated that the optimized formulation exhibited thermal conductivity comparable to therapeutic peat and maintained clinically relevant temperatures (35–45 °C) for more than one hour. Based on predefined performance criteria (overrun ≥ 50%, firmness ≤ 10 N, heat loss ≥ 120 s), formulation 7 was identified as optimal, combining favourable mechanical properties, structural uniformity and thermal retention. Conclusions: Alginate-based solid foams incorporating Rügen chalk constitute a feasible and tunable platform that combines efficient mineral loading, elastic porosity, and effective heat retention, offering a practical and modern alternative to conventional mineral-based therapeutic applications in balneology and rehabilitation. Full article

Raman spectroscopy (SERS) has emerged as a powerful analytical technique, offering molecular fingerprint specificity and ultrasensitive detection of cardiac biomarkers. Recent advances in plasmonic nanostructures, surface functionalization strategies, and flexible sensing platforms have significantly improved the analytical performance of SERS-based biosensors. In parallel, the integration of artificial intelligence (AI) and machine learning has enabled robust interpretation of complex spectral datasets, facilitating automated biomarker classification and improved diagnostic accuracy in heterogeneous biological environments. Despite these advances, the field remains fragmented, with limited integration between nanomaterial design, biomarker selection, and data-driven analysis, and persistent challenges related to reproducibility, standardization, and clinical validation. This review provides a comprehensive and critical synthesis of AI-assisted SERS platforms for cardiovascular diagnostics, integrating advances in plasmonic materials, biomolecular recognition, and intelligent spectral analysis within a unified framework. It further examines key translational barriers, including data variability, model interpretability, and scalability, and outlines future directions for developing standardized, edge-deployable, and clinically validated SERS-AI systems. Full article

Background: Viral attachment mediated by host cell surface receptors is the first step in viral infection. As a key cell surface receptor, heparan sulfate (HS) mediates the attachment and entry of numerous non-enveloped viruses in livestock, thereby serving as a crucial molecular target for studying virus–host interactions. Methods: Based on the structural scaffold of a nanobody (Nb; PDB: 7TJC), we rationally designed and constructed a mutant Nb targeting HS, designated HS-Mut-Nb1, using molecular docking, site-directed mutagenesis, molecular dynamics (MD) simulations, and experimental characterization. Results: Molecular docking indicated that the active site of wild-type Nb for HS binding was located within the cavity jointly formed by the complementarity-determining region 3 (CDR3) and the framework regions (FRs) of the wild-type Nb. A comprehensive analysis integrating virtual alanine scanning, site-directed mutagenesis, and MD simulations revealed that the combination of three point mutations (Phe47Arg, Asp99Tyr, and Tyr108Pro) significantly enhanced the binding affinity of Mut-Nb1 for HS, with a calculated binding free energy (ΔG) of −83.26 ± 3.06 kcal/mol. Enzyme-linked immunosorbent assay (ELISA) results further confirmed that Mut-Nb1 exhibited high affinity for HS (K_D = 65.87 nM) and specificity (positive/negative ratio, P/N = 3.84; cross-reactivity, CR < 6.60%). Conclusions: This study not only provides novel candidate molecules for elucidating the mechanism of HS–virus interactions and developing related inhibitors but also offers a reference for the rapid construction of mutant Nbs. Full article

Antimicrobial resistance represents a major global health challenge, highlighting the urgent need for alternative bioactive compounds from natural sources. This study investigated the phytochemical composition and antimicrobial potential of saponin-enriched extracts from the trunk bark of Argania spinosa (L.) Skeels, collected from two contrasting Algerian regions: the coastal area of Stidia (ES) and the Saharan region of Tindouf (ET). Extraction yields were comparable (approximately 12.6%). UHPLC-MS analysis revealed distinct phytochemical profiles, with ES enriched in oleanane-type saponins and flavonoids, whereas ET showed a higher abundance of bayogenin-type derivatives. Key compounds included arganine C, E, and J, as well as catechin and quercetin. Antimicrobial activity was evaluated using agar well diffusion and broth microdilution assays against clinically relevant microorganisms, including the reference strains Staphylococcus aureus and Listeria innocua, together with Staphylococcus epidermidis, Escherichia coli, Klebsiella pneumoniae, Serratia marcescens, Proteus mirabilis, and Candida albicans. Both extracts exhibited broad-spectrum antimicrobial activity, although ES consistently showed lower Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal, Fungicidal Concentration (MBC)/(MFC) values than ET. MIC values ranged from 25 to 50 mg/mL for ES and from 50 to 100 mg/mL for ET. Synergistic interactions were observed between ES and gentamicin against S. aureus and between both extracts and kanamycin against K. pneumoniae. Membrane permeability assays demonstrated that both extracts increased bacterial membrane permeability, with ET producing a stronger permeabilizing effect. Atomic force microscopy of ES-treated cells revealed marked alterations in bacterial surface morphology, while molecular docking supported strong interactions of mi-saponin B and arganine derivatives with key bacterial targets. Collectively, these findings highlight the potential of A. spinosa bark saponins as natural antimicrobial agents and promising antibiotic adjuvants against multidrug-resistant pathogens. Full article

The growing demand for sustainable construction materials has led to significant advancements in ultra-high-performance concrete (UHPC), with a particular focus on geopolymer-based systems as an alternative to conventional cementitious binders. This review explores the latest developments in sustainable Ultra-High-Performance Geopolymer Concrete (UHPGPC) by analysing key material composition, mechanical, durability and microstructural properties. The incorporation of ground granulated blast furnace slag (GGBFS), silica fume (SF), and fly ash (FA) has demonstrated notable improvements in compressive strength, durability, and workability. Additionally, the use of activators such as sodium silicate and sodium hydroxide optimizes geopolymerization, resulting in a denser microstructure and enhanced mechanical performance. This review highlights the critical role of fibre reinforcement in UHPGPC, where steel fibres (SFs) and hybrid fibres significantly enhance compressive and tensile strength, as well as crack resistance. The inclusion of waste materials such as rice husk ash and recycled glass promotes sustainability by reducing CO₂ emissions while maintaining structural integrity. However, higher waste-glass content may adversely affect bonding due to its smooth surface texture. The findings highlight the potential of UHPGC as a high-performance, eco-friendly alternative to traditional cement-based UHPC. By integrating industrial by-products and alternative activation techniques, UHPGPC can contribute significantly to the global shift towards sustainable and low-carbon construction materials. Full article

Oat-based beverages are increasingly popular milk alternatives. However, the heat treatment required to ensure shelf stability is limited by rapid fouling formation on heated surfaces, reducing processing efficiency. Oat proteins, considered an important quality attribute of oat drinks, are suspected to play a key role in fouling initiation, but their specific contribution remains poorly understood. This study investigates the role of oat proteins in fouling formation during heat treatment on technical scale. Membrane filtration was applied and validated as sample preparation method for increasing the protein content. Fouling experiments were conducted using a previously validated fouling system with feed solutions containing different protein concentrations. Protein content was increased by filtration using 0.1, 0.8 and 1.4 µm ceramic membranes, yielding retentates with 10–21 g·100 g⁻¹ on a dry matter basis, and further enriched to >40 g·100 g⁻¹ through diafiltration. Fouling experiments (140 °C, 60 min) revealed a dependence of fouling formation on protein content in the feed solution. Fouling deposits were negligible at low protein concentrations (<2.5 g·100 g⁻¹), increased markedly between 8 and 14 g·100 g⁻¹, and reached a plateau at higher protein levels. Using oat supernatant or retentates, the protein content in the fouling correlated linearly with the protein content in the feed solution (R² = 0.98) but did not exceed ~25g·100 g⁻¹, resulting in predominantly carbohydrate-based deposits. In contrast, diafiltered protein-enriched feed solutions produced larger, protein-dominated deposits. A conceptual model describing feed-dependent fouling mechanisms is proposed. Full article

Molecularly imprinted polymers (MIPs) offer robust, cost-effective, and highly selective alternatives to fragile biological receptors. Specifically, electropolymerization has emerged as a versatile strategy that enables the precise, in situ formation of uniform MIP films directly on electrode surfaces. This review provides a comprehensive overview of electropolymerized MIPs (eMIPs) supported on advanced carbon-based materials for electrochemical (bio)sensing. We emphasize how the synergistic integration of eMIPs with carbonaceous architectures significantly enhances electron transfer, active surface area, and overall analytical sensitivity. Key fabrication aspects are systematically discussed, including monomer selection, electropolymerization parameters, and efficient template removal. A central aspect of this work is the critical categorization of sensing mechanisms into direct and indirect detection strategies. This distinction elucidates how eMIPs can quantify a broad spectrum of electroactive and non-electroactive targets in complex matrices, while strategically avoiding excessively high applied potentials. Finally, alongside outlining the transition of these systems into portable technologies, we address a critical shortcoming in the current literature: the urgent need for analytical standardization through the rigorous reporting of Imprinting and Selectivity Factors using Non-Imprinted Polymer (NIP) controls. Full article

Surface oscillation is an important mechanism for the hydrological self-regulation of mires: it prevents the attenuation of flooding by storing water during high precipitation events and snowmelt. To investigate the spatial and temporal variability in surface oscillation, we conducted monthly measurements of the surface elevation and water level at three monitoring sites in the Great Vasyugan Mire (GVM), Western Siberia, over a nine-year period (2017–2025). Surface oscillation in the GVM varied from 14 to 25 cm in winter and early spring as a result of frost heaving, and from 2 to 16 cm in the frost-free period. Surface oscillation depends on the water table level variation, which is disturbed when the water level rises above the surface during freezing–thawing periods and due to released biogenic gases. Our data showed that within large mire systems, such as the Great Vasyugan Mire, the spatial variability in surface oscillation is influenced by several key factors: the type of plant community, peat properties, and the location relative to water flow pathways. Surface oscillation increased along a transect extending from the sedge–Sphagnum community to the pine–dwarf shrub–Sphagnum community, which runs parallel to the slope toward the marginal area. Long-term records demonstrate an increasing trend in surface elevation in the central part of the GVM, while showing a decrease at the mire boundary. Full article

The rapid expansion of urbanization in recent decades has intensified the urban heat island effect, driven by reduced vegetation cover, widespread use of heat-absorbing materials, and increases in surface and atmospheric temperature that may reach 5–6 °C. These conditions negatively impact well-being, quality of life, and human health. In response, numerous studies have examined mitigation strategies based on high-albedo materials and urban vegetation. This systematic review analyzes 225 peer-reviewed articles published between 2016 and 2025 addressing urban heat mitigation, surface thermal conditions, urban vegetation, outdoor thermal comfort and microclimate simulations. It provides a comprehensive synthesis, highlighting key findings and implications for future research. According to the Köppen–Geiger classification, most studies were conducted in humid subtropical and warm Mediterranean climates. The analysis focuses on urban canyon interventions, where vegetation is primarily modeled as shading trees (79.2%), along with other forms such as grass or shrubs (27.1%), mainly during the summer season. Results indicate that integrated mitigation strategies combining vegetation and high-albedo surfaces (≈0.8) generally provide greater cooling benefits than isolated interventions. Overall, the findings underscore the importance of the interaction between vegetation shading and surface properties for mitigating urban heat in outdoor spaces. Full article

The deployment of offshore wind farms (OWFs) has increased impressively over the last decade. While a group of frontrunner countries has led early deployment, the offshore wind sector is expanding to new regions; the Thracian Sea represents a promising area for OWFs deployment due to its favorable wind and wave climate. The successful implementation of OWFs projects depends on a comprehensive understanding of local environmental conditions, with particular emphasis on complex wind–wave interactions quantification, as well as on robust and representative power performance evaluation. In the present paper, hourly environmental data spanning 29 years (1993–2021), including wind and wave parameters, are utilized to quantify joint probability distributions at selected four locations in the Thracian Sea. Corresponding environmental contours are derived and presented using a probabilistic model for given return period. The joint probability distributions of wind and wave conditions are estimated and the environmental contour surfaces for 50- and 100-year return periods are calculated and presented for generic use. Furthermore, the power production of an OWF comprising nine IEA 15 MW turbine units arranged in an orthogonal grid layout is assessed through a numerical model developed in an open access computational tool. The model accounts for key physical processes influencing OWF capacity performance, including wake interactions, atmospheric conditions, turbine control strategies, and layout effects. The results indicate a substantial value of annual energy production and capacity factor for different zones within Thracian Sea achieving a value of 526 GWh and 44%, respectively. The presented results provide practical guidance for OWFs development in the Thracian Sea and contributes to reducing uncertainty in early-stage project planning and future engineering studies. Full article