Search Results (227)

This study investigates the behavior of phosphate ion transport through two structurally distinct anion-exchange membranes—AMV (homogeneous) and HC-A (heterogeneous)—in an electrodialysis system under both static and stirred conditions at varying pH levels. Chronopotentiometric and current–voltage analyses were used to investigate the influence of pH and hydrodynamics on ion transport. Under underlimiting (ohmic) conditions, the AMV membrane exhibited simultaneous transport of H₂PO₄⁻ and HPO₄²⁻ ions at neutral and mildly alkaline pH, while such behavior was not verified at acidic pH and in all cases for the HC-A membrane. Under overlimiting current conditions, AMV favored electroconvection at low pH and exhibited significant water dissociation at high pH, leading to local pH shifts and chemical equilibrium displacement at the membrane–solution interface. In contrast, the HC-A membrane operated predominantly under strong electroconvective regimes, regardless of the pH value, without evidence of water dissociation or equilibrium change phenomena. Stirring significantly impacted the electrochemical responses: it altered the chronopotentiogram profiles through the emergence of intense oscillations in membrane potential drop at overlimiting currents and modified the current–voltage behavior by increasing the limiting current density, reducing electrical resistance, and compressing the plateau region that separates ohmic and overlimiting regimes. Additionally, both membranes showed signs of NH₃ formation at the anodic-side interface under pH 7–8, associated with increased electrical resistance. These findings reveal distinct ionic transport characteristics and hydrodynamic sensitivities of the membranes, thus providing valuable insights for optimizing phosphate recovery via electrodialysis. Full article

This paper presents three realizations of a complete set with a horn antenna and a focusing Gradient Index (GRIN) lens in X-band. The set was specifically designed for advancing additive manufacturing (AM) of polymers with different materials and techniques. The set has three constituent parts: a horn antenna, a support, and a lens. The horn antenna is the active element and must be electrically conductive; it was manufactured with Rigid10K acrylic resin and subsequently metallized using an electroless process. The support needed to be light, robust, and electrically transparent, so that Polyamide 11 (PA11) was used. The lens realization was intended for a dielectric material whose permittivity varies with its density. Therefore, the dielectric permittivity and loss tangent of different polymeric materials used in AM at 2.45, 6.25, and 24.5 GHz were measured. In addition, stochastic and gyroid mesh structures have been studied. These structures allow for printing a volume that presents porosity, enabling control over material density. Measuring the dielectric characteristics of each material with each density enables the establishment of graphs that relate them. The sets were then manufactured, and their frequency response and radiation diagram were measured, showing excellent results when compared with the literature. Full article

The main problem with the conventional plastics presently used is that they are too slow to degrade, and thus, accumulate in the natural environment. This situation occurs on farmlands because low-density polyethylene (LDPE) is widely used in agriculture. Different authors propose employing biodegradable plastics (bioplastics) to solve this problem, and the most studied and promising candidates are poly(hydroxybutyrate) acid (PHB) and poly(lactic) acid (PLA). This work centers on the short-term evaluation of the biodegradability of the three above-mentioned plastic materials in soil type Mediterranean Alfisol and the effect of adding organic amendment (cow manure; CM) on their biodegradation. Two experiments were run for each plastic material: one without this organic amendment and the other by adding CM. Their biodegradation was determined by the procedure described in Standard ISO 17556. The results confirm that PHB is a highly biodegradable polymer, whereas the biodegradability of PLA and LDPE is poor. Using CM did not facilitate plastic polymer biodegradation in our soil. The nature and properties of soil can significantly impact plastics biodegradation. Bioplastics are still not the panacea to solve the plastics pollution problem, so other management options must be considered, such as prevention, reduction, and/or reuse in situ. Full article

Background: Antimicrobial resistance (AMR) represents a critical global health challenge, requiring innovative strategies to combat resistant bacterial strains. Cymbopogon essential oils (EOs) are promising natural antimicrobial agents. Methods: The EO of Cymbopogon commutatus was extracted by hydrodistillation from fresh aerial parts and compared to commercial EOs from C. citratus, C. nardus, and C. winterianus. Antibacterial activity was evaluated against seven bacterial strains (two Gram-positive and five Gram-negative). Both water-soluble fractions and liposome-encapsulated formulations were tested. Liposomes were prepared using soybean lecithin, and their stability was assessed by dynamic light scattering (DLS). The chemical composition of the pure EOs, water-soluble fractions and non-water-soluble fractions was analyzed by gas chromatography–mass spectrometry (GC-MS). Results: Liposome encapsulation improved EO solubility in aqueous media and significantly enhanced antibacterial efficacy, reducing minimum inhibitory concentration (MIC) values compared to the water-soluble fractions (MICs ≥ 25%). Among the tested formulations, the liposome containing C. citratus EO exhibited the strongest inhibitory effect against Staphylococcus aureus (MIC: 0.04%) followed by liposomes with C. nardus and C. commutatus (MIC: 0.08%). Against Enterococcus faecalis, the most effective formulation was the liposome containing C. winterianus EO (MIC: 0.02%), followed by C. citratus (MIC: 0.08%). The liposome formulated with C. winterianus maintained its particle size over 72 h without phase separation. GC-MS analysis revealed distinct phytochemical profiles: C. commutatus EO was rich in piperitone (73.9%) and C. citratus was rich in (Z)-(3,3-Dimethyl)-cyclohexylideneacetaldehyde (39.9%) and citral (32.5%), while C. nardus and C. winterianus were dominated by geraniol (21.5%) and citronellal (30.8%), respectively. Notably, piperitone, the major compound in C. commutatus EO, exhibited strong antibacterial activity against S. aureus (MIC of <0.04%). Conclusions: These findings support the potential of liposome-encapsulated Cymbopogon EOs as an effective and sustainable strategy to address AMR. This study provides a foundation for the development of plant-based antimicrobial formulations with improved efficacy. Full article

The southeastern margin of the Ría de Arosa is a region of great ecological and social importance, characterized by increasing urban development, tourism pressures, and vulnerability to natural hazards, soil erosion, coastal flooding, and mass movements, where sustainable territorial planning poses significant challenges. This study combines Geographic Information Systems tools and quantitative and qualitative overlay techniques to integrate conservation quality and comprehensive risk maps. The main challenge addressed in this research is the integration of geospatial data and diverse natural risk factors. The result was a map of land use recommendations and limitations, and another of degree of land use limitation, which identify priority areas for conservation and zones suitable for the controlled development of recreational, agricultural, and industrial activities. The methodology employed allows for detailed modelling that is easily updated and applicable to other environments for territorial planning and natural resource conservation. Areas of special natural importance, such as Arosa Island and the El Grove Peninsula, stand out as optimal locations for sustainable recreational activities, while the northeastern coastal corridor, between Villanueva de Arosa and Cambados, shows suitability for anthropogenic development. This approach contributes to a balance between socioeconomic development and environmental protection, facilitating the implementation of sustainable planning and conservation strategies in highly fragile coastal areas. Full article

Municipal solid waste (MSW) accumulation is a critical global challenge for society and governments, impacting environmental and social sustainability. Efficient separation of MSW is essential for resource recovery and advancing sustainable urban management practices. However, manual classification remains a slow and inefficient practice. In response, advances in artificial intelligence, particularly in machine learning, offer more precise and efficient alternative solutions to optimize this process. This research presents the development of a light deep neural network called R3sNet (three “Rs” for Reduce, Reuse, and Recycle) with residual modules trained end-to-end for the binary classification of MSW, with the capability for faster inference. The results indicate that the combination of processing techniques, optimized architecture, and training strategies contributes to an accuracy of 87% for organic waste and 94% for inorganic waste. R3sNet outperforms the pre-trained ResNet50 model by up to 6% in the classification of both organic and inorganic MSW, while also reducing the number of hyperparameters by 98.60% and GFLOPS by 65.17% compared to ResNet50. R3sNet contributes to sustainability by improving the waste separation processes, facilitating higher recycling rates, reducing landfill dependency, and promoting a circular economy. The model’s optimized computational requirements also translate into lower energy consumption during inference, making it well-suited for deployment in resource-constrained devices in smart urban environments. These advancements support the following Sustainable Development Goals (SDGs): SDG 11: Sustainable Cities and Communities, SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action. Full article

The rapid growth of industrial activities has increased environmental pollution, and solar-driven heterogeneous photocatalysis using TiO₂ has emerged as a promising solution. However, its wide band gap limits its efficiency, prompting research into various optimization strategies. One of these approaches is surface functionalization. Thus, this study investigates the adsorption of CuSO₄ on the anatase TiO₂ (101) surface using density functional theory calculations. The adsorption process induced a magnetic moment of 0.97 µ_B and a slight reduction in overall bandwidth. A preferential adsorption geometry pattern with an energy of −4.31 eV was identified. Charge transfer analysis revealed a net transfer from the TiO₂ surface to the CuSO₄ molecule, with increased net atomic charges for atoms involved in new chemical bond formation, indicating a chemisorption process. These electronic structure modifications are expected to influence the electronic and catalytic properties of the material. The findings provide insights into the CuSO₄ adsorption mechanism on an anatase TiO₂ (101) surface and its impact on the properties of the material, contributing to a deeper understanding of this system. Full article

Corrosion protection in reinforced concrete structures exposed to aggressive environments remains a critical challenge in civil and architectural engineering. One promising approach involves the application of corrosion-inhibiting monolayers on the reinforcement, such as those formed using 4-aminobenzoic acid. Two methods have previously been employed to generate these monolayers: one relying on the adhesion of an organic compound and the other utilising an externally modified approach via electrolysis. This study assesses the influence of this treatment on the steel–concrete bond strength and durability, both critical properties for the structural performance of reinforced concrete under service conditions. For this purpose, pull-out tests were performed on specimens subjected to load–unload cycles to analyse bond behaviour and monolayer integrity. The results indicate that these treatments do not adversely affect the bond strength between reinforcement and concrete. Furthermore, the rebars treated with the inhibitor exhibit less corrosion damage than the untreated rebars. This fact is particularly significant in the rebars treated using the natural adhesion method, with the steel section loss being 32–37% lower than in the untreated rebars. These findings support the feasibility of applying this treatment without compromising structural functionality. Full article

For computational fluid dynamic (CFD) modeling of advanced combustion engines, the cylinder is usually considered a closed system in which the initial conditions are estimated based on the experimental data. Most of these approximations hinder observing the effect of design parameters on engine performance and emissions accurately, and most studies are limited to a few design parameters. An approach is proposed based on the combination of a 1D gas dynamic and a 3D CFD model to simulate the whole engine with as few simplifications as possible. The impact of changing the in-cylinder initial conditions, injection strategy (dual direct injection or multiple pulse injections), and piston bowl geometry on a reactivity controlled compression ignition (RCCI) engine’s performance, emissions, and fuel stratification levels was investigated. It was found that applying the dual direct injection (DDI) strategy to the engine can be promising to reach higher load operations by reducing the pressure rise rate and causing stronger stratification levels. Increasing the number of injection pulses leads to lower Soot/NOx emissions. The best reduction in the pressure rise rate was found by the dual direct strategy (38.36% compared to the base experimental case) and higher exhaust gas recirculation (EGR) levels (41.83% reduction in comparison with the base experimental case). With the help of a novel piston bowl design, HC and CO emissions were reduced significantly. This resulted in a reduction of 54.58% in HC emissions and 80.22% in CO emissions. Full article

According to the World Health Organization (WHO), peripheral and central neurological disorders affect approximately one billion people worldwide. Ischemic stroke and Alzheimer’s Disease and other dementias are the second and fifth leading causes of death, respectively. In this context, detecting and classifying brain lesions constitute a critical area of research in medical image processing, significantly impacting clinical practice. Traditional lesion detection, segmentation, and feature extraction methods are time-consuming and observer-dependent. In this sense, research in the machine and deep learning methods applied to medical image processing constitute one of the crucial tools for automatically learning hierarchical features to get better accuracy, quick diagnosis, treatment, and prognosis of diseases. This project aims to develop and implement deep learning models for detecting and classifying small brain White Matter hyperintensities (WMH) lesions in magnetic resonance images (MRI), specifically lesions concerning ischemic and demyelination diseases. The methods applied were the UNet and Segmenting Anything model (SAM) for segmentation, while YOLOV8 and Detectron2 (based on MaskRCNN) were also applied to detect and classify the lesions. Experimental results show a Dice coefficient (DSC) of 0.94, 0.50, 0.241, and 0.88 for segmentation of WMH lesions using the UNet, SAM, YOLOv8, and Detectron2, respectively. The Detectron2 model demonstrated an accuracy of 0.94 in detecting and 0.98 in classifying lesions, including small lesions where other models often fail. The methods developed give an outline for the detection, segmentation, and classification of small and irregular morphology brain lesions and could significantly aid clinical diagnostics, providing reliable support for physicians and improving patient outcomes. Full article

Genetic variants related to susceptibility to chronic respiratory conditions such as interstitial lung disease (ILD) could share critical pathways in the pathogenesis of COVID-19 and be implicated in COVID-19 outcomes and post-COVID-19. We aimed to identify the participation of genetic variants in lung function and ILD genes in severe COVID-19 outcomes and post-COVID-19 condition. We studied 936 hospitalized patients with COVID-19. The requirement of invasive mechanical ventilation (IMV) and the acute respiratory distress syndrome (ARDS) classification were considered. The mortality was assessed as the in-hospital death. The post-COVID-19 group included 102 patients evaluated for pulmonary function tests four times during the year after discharge. Five variants (FAM13A rs2609255, DSP rs2076295, TOLLIP rs111521887, TERT rs2736100, and THSD4 rs872471) were genotyped using TaqMan assays. A multifactor dimensionality reduction method (MDR) was performed for epistasis estimation. The TERT rs2736100 and THSD4 rs872471 variants were associated with differential risk for ARDS severity (moderate vs. severe, CC + CA, p = 0.044, OR = 0.66, 95% CI = 0.44–0.99; and GG p = 0.034, OR = 2.22, 95% CI = 1.04–4.72, respectively). These variants and FAM13A rs2609255 were also related to pulmonary function post-COVID-19. The MDR analysis showed differential epistasis and correlation of the genetic variants included in this study. The well-known variants in recognized genes related to pulmonary function worsening and interstitial disorders are related to the severity and mortality of COVID-19 and lung performance in the post-COVID-19 condition. Full article

Introduction: Type 2 diabetes is a significant health concern in the 21st century, and its prevalence continues to rise despite efforts to promote preventive lifestyle changes. This increase has led to higher economic burdens, prompting the search for non-pharmacological methods to manage glucose levels. Objective: To assess the effects of flaxseed consumption on biochemical markers (glucose, glycated hemoglobin, total cholesterol, and triglycerides) in adult patients with Type 2 diabetes in Oaxaca, Mexico. Materials and Methods: Participants were recruited and randomized into clinical trials between April and June 2023, and the study protocol was approved by a Human Research Ethics Committee. Results: Consuming 16 g of flaxseed daily for three months led to a significant decrease in glucose, total cholesterol, and triglyceride levels (p < 0.001) in Type 2 diabetes patients in the intervention group (n = 82). Belonging to the control group (n = 84) was correlated with presenting higher levels of glycated hemoglobin (Spearman’s Rho 0.640; p < 0.001), higher levels of glucose (Spearman’s Rho 0.352; p < 0.001), total cholesterol (Spearman’s Rho 0.796; p < 0.001), and triglycerides (Spearman’s Rho 0.700; p < 0.001). Conclusions: A daily intake of 16 g of flaxseed is an effective supplementary treatment for adult Mexican patients with Type 2 diabetes, as evidenced by reduced levels of glycated hemoglobin, glucose, cholesterol, and triglycerides in the intervention group. Potential implications for clinical practice: Healthcare providers may consider recommending flaxseed in the diets of patients with obesity, prediabetes, or Type 2 diabetes to improve glucose and lipid metabolism and overall metabolic health. Full article

During the last decades, most bacterial strains have become increasingly resistant to antibiotics. This led the WHO to declare a global emergency in 2017 and urge the development of new active compounds. Some families of antibiotics still show high antibacterial efficacy, as is the case of fluoroquinolones, which have a broad spectrum of action. For this reason, our research group derived several compounds from fluoroquinolones, selecting a compound with good antibacterial activity for further evaluations, a difluoroboranil-fluoroquinolone complex labeled 7a. Antibacterial activity was evaluated using the Kirby–Bauer method against S. aureus (clinical isolate HGZ2201#ID). The MIC and MBC were obtained by macrodilutions and reseeding. In vivo antimicrobial activity was evaluated in a Balb/c mouse model infected intratracheally with S. aureus and subsequently treated with ciprofloxacin or 7a (80 mg/kg/day) for five days. A mean of 8.55 ± 0.395 cm² inhibition area was observed using 7a, while ciprofloxacin generated a mean inhibition of 7.86 ± 0.231 cm². Compound 7a showed a MIC and MBC of 0.25 μg/mL. This reduced the generation of pneumonic lung tissue to 5.83%, while the untreated infected group generated 60.51% of pneumonic tissue. Compound 7a proved to be an antimicrobial agent capable of inhibiting the in vitro development of S. aureus. Furthermore, 7a showed effectiveness in decreasing the progression of acute pneumonia induced by S. aureus in a murine model. Full article

The coffee industry generates a large amount of waste that is difficult to treat due to its chemical composition, namely, the presence of caffeine and its derivatives, as well as recalcitrant molecules such as tannins (mainly condensed tannins or polymeric procyanidins), which make it an undervalued waste product. Procyanidins are compounds beneficial to human health and can be found in nature in fruit, grain, seeds, and beverages, among other foods. The zero-waste approach has allowed for the valorization of by-products from the food industry. Currently, coffee pulp is the target of research on extraction, purification, and alternative use. Research on the fungal degradation of procyanidins has emerged as an avenue for the efficient use of these by-products. In this study, the degradation and biotransformation of procyanidin is evaluated and comprises three steps: first, the extraction and partial purification of procyanidins from coffee pulp; second, the production of the potential procyanidin-degrading enzyme by submerged fermentation with Aspergillus niger GH1; third, enzymatic extracellular extract evaluation using a model system with commercial procyanidin C1. The biodegradation/biotransformation results reveal the formation of new compounds, including a final compound with an m/z of 289, possibly a monomeric molecule such as catechin or epicatechin. Identification of the compounds by HPLC-MS confirmed procyanidin C1 depletion under the described assay conditions, which could be used to understand biodegradation pathways proposed for future study. Furthermore, these results confirm that A. niger GH1 is able to degrade and biotransform procyanidin C1. Full article

Optical communication systems face challenges like nonlinear noises, particularly Kerr-induced phase noise, which worsens with higher-order m-QAM formats due to their dense data-symbol sets. Advanced signal processing, including machine learning, is increasingly used to enhance signal integrity during demodulation. This paper explores the application of a spectral clustering algorithm adapted to deal with data streaming to mitigate nonlinear noise in long-haul optical channels dominated by nonlinear phase noise, offering a promising solution to a pressing issue. The spectral clustering algorithm was adapted to handle data streams, enabling potential real-time applications. Additionally, it was combined with a demapping process for m-QAM to resolve labeling inconsistencies when processing windowed data. We demonstrate that the spectral clustering algorithm outperforms the k-means algorithm in the face of nonlinear phase noise in −90, −100, and −110 dBc/Hz scenarios at 1 MHz in a simulated 10 GHz symbol rate channel. Full article