Search Results (1,193)

Climate concerns are driving the automotive industry to adopt advanced manufacturing technologies that aim to improve energy efficiency and reduce vehicle weight. In this context, lightweight structural materials such as aluminium alloys have gained significant attention due to their favorable strength-to-weight ratio. Laser welding plays a crucial role in assembling such materials, offering high flexibility and fast joining capabilities for thin aluminium sheets. However, welding these materials presents specific challenges, particularly in controlling heat input to minimize distortions and ensure consistent weld quality. As a result, numerical simulations based on the Finite Element Method (FEM) are essential for predicting weld-induced phenomena and optimizing process performance. This study investigates welding-induced distortions in laser butt welding of 1.5 mm-thick Al 6061 samples through FEM simulations performed in the SYSWELD 2024.0 environment. The methodology provided by the software is based on the Moving Heat Source (MHS) model, which simulates the physical movement of the heat source and typically requires extensive calibration through destructive metallographic testing. This transient approach enables the detailed prediction of thermal, metallurgical, and mechanical behavior, but it is computationally demanding. To improve efficiency, the Imposed Thermal Cycle (ITC) model is often used. In this technique, a thermal cycle, extracted from an MHS simulation or experimental data, is imposed on predefined subregions of the model, allowing only mechanical behavior to be simulated while reducing computation time. To avoid MHS-based calibration, this work proposes using thermal cycles acquired in-line during welding via infrared thermography as direct input for the ITC model. The method was validated experimentally and numerically, showing good agreement in the prediction of distortions and a significant reduction in workflow time. The distortion values from simulations differ from the real experiment by less than 0.3%. Our method exhibits a slight decrease in performance, resulting in an increase in estimation error of 0.03% compared to classic approaches, but more than 85% saving in computation time. The integration of real process data into the simulation enables a virtual representation of the process, supporting future developments toward Digital Twin applications. Full article

Polymethyl methacrylate nanoparticles functionalized with three different compounds, acrylic acid (AA), curcumin (CUR), and fumaramide (FA), were tested in a two-step solid–liquid extraction process (extraction and stripping) for yttrium recovery. In both stages, the best conditions were determined: pH, solid–liquid ratio and the compound with the highest affinity for yttrium recovery, obtaining 90% of efficiency for both stages in a single work cycle. The results obtained by SEM ruled out the growing of nanoparticles by swelling and confirmed the formation of structural arrangements by the addition of the metal to the system. In addition, there is evidence that the recovery process can be selective considering the mixing of rare earth elements through changes in pH. Using isothermal titration calorimetry (ITC), the thermodynamic properties of the extraction process were calculated, understanding the system as the union of a macromolecule and a ligand. The results showed that the extraction process was spontaneous and highly entropic. Full article

Strategies to interpret short-wave infrared hyperspectral images of rocks involve the application of analysis and classification steps that guide the extraction of geological and mineralogical information with the aim of creating mineral maps. Pre-existing strategies often rely on the use of statistical measures between reference and image spectra that are scene dependent. Therefore, classification thresholds based on statistical measures to create mineral maps are also scene dependent. This is problematic because thresholds must be adjusted between images to produce mineral maps of the same accuracy. We developed an innovative, knowledge-based strategy to perform mineralogical analyses and create classifications that overcome this problem by using physics-based wavelength positions of absorption features that are invariant between scenes as the main sources of mineral information. The strategy to interpret short-wave infrared hyperspectral images of rocks is implemented using the open source Hyperspectral Python package (HypPy) and demonstrated on a series of hyperspectral images of hydrothermally altered rock samples. The results show how expert knowledge can be embedded into a standardized processing chain to develop reproducible mineral maps without relying on statistical matching criteria. Full article

Accurate crop yield prediction is essential for stabilizing food supply chains and reducing the uncertainties in financial risks related to agricultural production. Yet, it is even more essential to understand how crop yield models make predictions depending on their relationship to Earth Observation (EO) indicators. This study presents a state-of-the-art explainable artificial intelligence (XAI) method to estimate corn yield prediction over the Corn Belt in the continental United States (CONUS). We utilize the recently introduced Kolmogorov–Arnold Network (KAN) architecture, which offers an interpretable alternative to the traditional Multi-Layer Perceptron (MLP) approach by utilizing learnable spline-based activation functions instead of fixed ones. By including a KAN in our crop yield prediction framework, we are able to achieve high prediction accuracy and identify the temporal drivers behind crop yield variability. We create a multi-source dataset that includes biophysical parameters along the crop phenology, as well as meteorological, topographic, and soil parameters to perform end-of-season and in-season predictions of county-level corn yields between 2016–2023. The performance of the KAN model is compared with the commonly used traditional machine learning (ML) models and its architecture-wise equivalent MLP. The KAN-based crop yield model outperforms the other models, achieving an R² of 0.85, an RMSE of 0.84 t/ha, and an MAE of 0.62 t/ha (compared to MLP: R² = 0.81, RMSE = 0.95 t/ha, and MAE = 0.71 t/ha). In addition to end-of-season predictions, the KAN model also proves effective for in-season yield forecasting. Notably, even three months prior to harvest, the KAN model demonstrates strong performance in in-season yield forecasting, achieving an R² of 0.82, an MAE of 0.74 t/ha, and an RMSE of 0.98 t/ha. These results indicate that the model maintains a high level of explanatory power relative to its final performance. Overall, these findings highlight the potential of the KAN model as a reliable tool for early yield estimation, offering valuable insights for agricultural planning and decision-making. Full article

In this study, we present a basic idea for a robust optical measurement method for the practical monitoring of slurry sprays with high mass concentrations, as typically used in combustion processes. The proposed approach is based on analyzing the transparency properties of individual dynamic droplets within the slurry spray. These so-called dynamic slurry droplets consist of a base fluid and suspended solid particles. Our method enables the determination of the mass concentration of solid particles and provides an estimate of their average size. The resolution of this technique allows for the detection of errors in the slurry-mixing process and even in the milling process of the solid particles prior to mixing. To atomize slurries with high mass concentration, an experimental setup with a gas-assisted coaxial nozzle was employed. Slurries with three different mass concentrations and three particle size distributions were tested, resulting in five combinations. The theoretical expectations and experimental results show a strong correlation, highlighting the potential of the proposed method for slurry-spray monitoring. Full article

Neurodegenerative, neurodevelopmental, and psychiatric disorders, as well as epilepsy, affect millions of people. Due to their impact on patients’ quality of life, they represent a major health issue. Natural compounds are arising as new treatments for these diseases. Particularly, glucosinolates (GLS) are secondary metabolites found in Cruciferae family plants. Their basic structure consists of a glucose unit linked to a thiohydroximate-O-sulfonate group and an aliphatic, aralkyl, or indolyl side chain, depending on their precursor amino acid. Specifically, aliphatic GLS derive from methionine, aromatic ones from phenylalanine, and indolic ones from tryptophan. Myrosinase (thioglucoside glucohydrolase) is the crucial enzyme for GLS degradation, leading to the production of isothiocyanates (ITCs). ITCs attracted considerable scientific interest for their protective effects against various diseases, thanks to their antioxidant, anti-inflammatory, and neuroprotective properties. Here, we collected the latest evidence regarding ITC effects in neurodegenerative, neurodevelopmental, and psychiatric disorders, including preclinical and clinical studies published in the last decade. These studies evidenced ITCs’ neuroprotective effects, exerted mainly through antioxidant and anti-inflammatory mechanisms. Thus, ITCs’ integration, also through the diet, may represent a safe and efficacious strategy to improve health and limit the risk of neurological and psychiatric disorders. However, new large-scale trials are needed to determine their therapeutic potential, particularly for diseases with no clinical evidence. Full article

Rationally designing and synthesizing chemosensors capable of simultaneously detecting both anions and cations via water content modulation is challenging. In this study, we synthesized and characterized a novel triazine calixarene derivative-based iodide and copper ion-selective fluorescent “turn-off” sensor. This dual-channeled fluorescent probe is able to recognize Cu²⁺ and I⁻ ions simultaneously in aqueous systems. The fluorescent sensor s4 was synthesized by displacement reaction of acridine with 1, 3-bis (dichloro-mono-triazinoxy) benzene in acetonitrile. Mass spectrometry (MS), UV-vis, and fluorescence spectra were acquired to characterize the fluorescence response of s4 to different cations and anions, while infrared (IR) spectroscopy and isothermal titration calorimetry (ITC) were employed to study the underlying selectivity mechanism of s4 to Cu²⁺ and I⁻. In detail, s4 displayed extremely high sensitivity to Cu²⁺ with over 80% fluorescence decrement caused by the paramagnetic nature of Cu²⁺ in the aqueous media. The reversible fluorescence response to Cu²⁺ and the responses to Cu²⁺ in the solution of other potential interferent cations, such as Li⁺, Na⁺, K⁺, Ca²⁺, Cd²⁺, Zn²⁺, Sr²⁺, Ni²⁺, Co²⁺ were also investigated. Probe s4 also exhibited very good fluorescence selectivity to iodide ions under various anion (F⁻, Cl⁻, Br⁻, NO₃⁻, HSO₄⁻, ClO₄⁻, PF₆⁻, AcO⁻, H₂PO₄⁻) interferences. In addition to the fluorescent response to I⁻, s4 showed a highly selective naked-eye-detectable color change from colorless to yellow with the other tested anions. Full article

The ReAV enzyme from Rhizobium etli, a representative of Class 3 L-asparaginases, is sequentially and structurally different from other known L-asparaginases. This distinctiveness makes ReAV a candidate for novel antileukemic therapies. ReAV is a homodimeric protein, with each subunit containing a highly specific zinc-binding site created by two cysteines, a lysine, and a water molecule. Two Ser-Lys tandems (Ser48-Lys51, Ser80-Lys263) are located in the close proximity of the metal binding site, with Ser48 hypothesized to be the catalytic nucleophile. To further investigate the catalytic process of ReAV, site-directed mutagenesis was employed to introduce alanine substitutions at residues from the Ser-Lys tandems and at Arg47, located near the Ser48-Lys51 tandem. These mutational studies, along with enzymatic assays and X-ray structure determinations, demonstrated that substitution of each of these highly conserved residues abolished the catalytic activity, confirming their essential role in enzyme mechanism. Full article

The increasing demand for accurate and accessible medical imaging has driven efforts to develop technologies that overcome limitations associated with conventional imaging techniques, such as MRI and CT scans. This study presents the design and implementation of an electronic interface for acquiring signals from a piezoelectric ultrasound sensor with the aim of improving image reconstruction quality by addressing electromagnetic interference and speckle noise, two major factors that degrade image fidelity. The proposed interface is installed between the ultrasound transducer and acquisition system, allowing real-time signal capture without altering the medical equipment’s operation. Using a printed circuit board with 110-pin connectors, signals from individual piezoelectric elements were analyzed using an oscilloscope. Results show that noise amplitudes occasionally exceed those of the acoustic echoes, potentially compromising image quality. By enabling direct observation of these signals, the interface facilitates the future development of analog filtering solutions to mitigate high-frequency noise before digital processing. This approach reduces reliance on computationally expensive digital filtering, offering a low-cost, real-time alternative. The findings underscore the potential of the interface to enhance diagnostic accuracy and support further innovation in medical imaging technologies. Full article

Understanding the binding interactions between protein-bound uremic toxins (PBUTs) and human serum albumin (HSA) is critical for advancing treatments for chronic kidney disease (CKD). While previous studies have suggested that putrescine, a diamine PBUT, exhibits moderate binding affinity to HSA, this study provides evidence of the contrary. Using isothermal titration calorimetry and saturation transfer difference nuclear magnetic resonance , we demonstrate that putrescine’s interaction with HSA is weak, non-specific, and thermodynamically negligible in the range of conditions studied. Unlike earlier studies relying on spectroscopy techniques such as UV–visible absorption and fluorescence, which may overestimate binding strength, the results presented here highlight the limitations of indirect methodologies and underscore the importance of more sensitive approaches for accurate energy characterization. Our findings suggest that putrescine only weakly interacts non-specifically with HSA and may bind more preferentially to other plasma proteins, contributing to its accumulation in CKD patients. Full article

Background/Objectives: The increasing prevalence of multidrug-resistant bacteria presents a major global health challenge, prompting a search for innovative antimicrobial strategies. This study aimed to develop and evaluate a novel nanobiostructure combining alumina nanoparticles (NPs) with the antimicrobial peptide lunatin-1 (Lun-1), forming peptide-functionalized nanofilaments. The main objective was to investigate how the site of peptide functionalization (C-terminal vs. N-terminal) affects membrane interactions and antibacterial activity. Methods: NP–peptide conjugates were synthesized via covalent bonding between lun-1 and alumina NP and characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), zeta potential analysis, dynamic light scattering (DLS), Fourier-transform infrared (FTIR), and solid-state ¹³C NMR. Antibacterial activities were assessed against different Gram-positive and Gram-negative strains. Biophysical analyses, including circular dichroism (CD), isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC), and solid-state ²H NMR, were employed to evaluate peptide–membrane interactions in the presence of membrane-mimetic vesicles composed of POPC:POPG (3:1) and DMPC:DMPG (3:1). Results: Characterization confirmed the successful formation of NP–peptide nanofilaments. Functionalization at the N-terminal significantly influenced both antibacterial activity and peptide conformation compared to C-terminal attachment. Biophysical data demonstrated stronger membrane interaction and greater membrane disruption when lun-1 was conjugated at the N-terminal. Conclusions: The site of peptide conjugation plays a crucial role in modulating the biological and biophysical properties of NP–lunatin-1 conjugates. C-terminal attachment of lunatin-1 retains both membrane interaction and antibacterial efficacy, making it a promising strategy for the design of peptide-based nanotherapeutics targeting resistant pathogens. Full article

The Roma population is one of Europe’s largest ethnic minorities, often living in inadequate living conditions, worse than those of the majority population. They frequently lack access to essential services, even in high-income countries. This lack of basic services—particularly in combination with proximity to (stray) animals and human and solid waste—significantly increases environmental health risks, and leads to a higher rate of endoparasitic infections. Our study sheds light on the living conditions and health situation in Roma communities in Slovakia, focusing on the prevalence of intestinal endoparasitic infections across various settlement localisations. It highlights disparities and challenges in access to safe drinking water, sanitation, and hygiene (WASH) and other potentially disease-exposing factors among these marginalised populations. This study combines a comprehensive review of living conditions as per national data provided through the Atlas of Roma communities with an analysis of empirical data on parasitological infection rates in humans, animals, and the environment in settlements, applying descriptive statistical methods. It is the first study in Europe to provide detailed insights into how living conditions vary and cause health risks across Roma settlements, ranging from those integrated within villages (inside, urban), to those isolated on the outskirts (edge, sub-urban) or outside villages (natural/rural). Our study shows clear disparities in access to services, and in health outcomes, based on where people live. Our findings underscore the fact that (i) place—geographical centrality in particular—in an already challenged population group plays a major role in health inequalities and disease exposure, as well as (ii) the urgent need for more current and comprehensive data. Our study highlights persistent disparities in living conditions within high-income countries and stresses the need for greater attention and more sensitive targeted health-promoting approaches with marginalised communities in Europe that take into consideration any and all of the humans, ecology, and animals affected (=One Health). Full article

As urbanization accelerates and urban hydrological cycles evolve, roof typology emerges as a pivotal role in water retention capacity and drainage efficiency. To systematically evaluate the influence of various roof types on urban hydrological processes, this study designed four distinct catchment scenarios: Thiessen Polygon Scenarios (TS), Roof Type Consideration Scenarios (RS), Full Flat-Roof Scenarios (FS), and Full Pitched-Roof Scenarios (PS). This study employed the Urban Flood Intelligent Model (UFIM) to simulate urban flooding scenarios, utilizing precipitation data from 21 August 2024 combined with four distinct return periods (1a, 5a, 10a, and 20a) as hydrological inputs. The results show that roof types significantly affected hydrological processes in urban communities. Flat roofs accumulate water and drain slowly, making it easy to form larger areas of accumulated water during peak rainfall periods, thereby increasing the risk of urban flooding. Pitched roofs drain quickly but experience a brief rise in water level during peak hours due to rapid drainage. Based on these insights, priority should be given to the use of sloped roof design in areas prone to accumulated water to accelerate drainage. In areas requiring runoff mitigation, the strategic integration of flat roofs with green roofs enhances rainwater retention capacity, thereby optimizing urban hydrological regulation and bolstering flood resilience. Full article

The interaction between cucurbit[8]uril (Q[8]) and the guest 1-methyl-4-(4-(1-methylpyridin-1-ium-4-yl)benzamido)pyridin-1-ium (PB²⁺) has been thoroughly investigated. Multiple techniques were employed, including ¹H NMR spectroscopy, mass spectrometry, isothermal titration calorimetry (ITC), UV–vis absorption spectrophotometry, and quantum chemistry calculations. The experimental results and calculation analysis have clearly shown that in aqueous solution, the host Q[8] preferentially encapsulates the phenylpyridinium salt moiety of the PB²⁺ guest within its hydrophobic cavity, forming a 1:2 inclusion complex. Full article

In order to solve the self-heating problem of power electronic devices, this paper adopts a nonequilibrium molecular dynamics approach to study the thermal transport regulation mechanism of the aluminum nitride/graphene/silicon carbide heterogeneous interface. The effects of temperature, size, and vacancy defects on interfacial thermal conductivity are analyzed by phonon state density versus phonon participation rate to reveal their phonon transfer mechanisms during thermal transport. It is shown that the interfacial thermal conductance (ITC) increases about three times when the temperature increases from 300 K to 1100 K. It is analyzed that the increase in temperature will enhance lattice vibration, enhance phonon coupling degree, and thus increase its ITC. With the increase in the number of AlN-SiC layers from 8 to 28, the ITC increases by about 295.3%, and it is analyzed that the increase in the number of AlN-SiC layers effectively reduces the interfacial scattering and improves the phonon interfacial transmission efficiency. The increase in the number of graphene layers from 1 layer to 4 layers decreases the ITC by 70.3%. The interfacial thermal conductivity reaches a minimum, which is attributed to the increase in graphene layers aggravating the degree of phonon localization. Under the influence of the increase in graphene single and double vacancy defects concentration, the ITC is slightly reduced. When the defect rate reaches about 20%, the interfacial thermal conductance of SV (single vacancy) and DV (double vacancy) defects rises back to 5.606 × 10⁻² GW/m²K and 5.224 × 10⁻² GW/m²K, respectively. It is analyzed that the phonon overlapping and the participation rate act at the same time, so the heat-transferring phonons increase, increasing the thermal conductance of their interfaces. The findings provide theoretical support for optimizing the thermal management performance of heterostructure interfaces. Full article