Search Results (5,026)

Background and objectives: Type 2 diabetes mellitus (T2DM) affects brain white matter microstructure. While diffusion tensor imaging (DTI) has been used to study white matter abnormalities in T2DM, it lacks specificity for complex white matter tracts. Neurite orientation dispersion and density imaging (NODDI) offers a more specific approach to characterising white matter microstructures. This study aims to explore white matter alterations in T2DM using both DTI and NODDI and assess their association with disease duration and glycaemic control, as indicated by HbA1c levels. Methods and Materials: We analysed white matter microstructure in 48 tracts using data from the UK Biobank, involving 1023 T2DM participants (39% women, mean age 66) and 30,744 non-T2DM controls (53% women, mean age 64). Participants underwent 3.0T multiparametric brain imaging, including T1-weighted and diffusion imaging for DTI and NODDI. We performed region-of-interest analyses on fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and isotropic water fraction (IsoVF) to assess white matter abnormalities. Results: We observed reduced FA and ICVF, and increased MD, AD, RD, ODI, and IsoVF in T2DM participants compared to controls (p < 0.05). These changes were associated with longer disease duration and higher HbA1c levels (0 < r ≤ 0.2, p < 0.05). NODDI identified microstructural changes in white matter that were proxies for reduced neurite density and disrupted fibre orientation, correlating with disease progression and poor glucose control. In conclusion, NODDI contributed to DTI in capturing white matter differences in participants with type 2 diabetes, suggesting the feasibility of NODDI in detecting white matter alterations in type 2 diabetes. Type 2 diabetes can cause white matter microstructural abnormalities that have associations with glucose control. Conclusions: The NODDI diffusion model allows the characterisation of white matter neuroaxonal pathology in type 2 diabetes, giving biophysical information for understanding the impact of type 2 diabetes on brain microstructure. Future research should focus on the longitudinal tracking of these microstructural changes to better understand their potential as early biomarkers for cognitive decline in T2DM. Full article

The absence of gluten is a technological challenge that requires the addition of components to replace the unique viscoelastic properties of gluten, thus altering the nutritional composition of gluten-free (GF) breads. Moreover, GF flours may have different compositions as compared to gluten-containing (GC) counterparts because of a different origin. This may impact the nutritional quality of GF diets. The aim of the study is to provide updated analytical data on moisture, fat, and fibre contents in GF flour and bread samples, and compare them with their GC counterparts, as well as to analyse ingredients and how they impact nutritional quality. A total of 30 different flours and 24 types of bread were analysed using AOAC methods. GF cereal flours contain more fat than GC flours (3.5 ± 2.1% vs. 2.5 ± 2.1%, p < 0.001), as well as GF flours from pseudocereals, except for wholemeal buckwheat (2.6 ± 0.1%). Fibre content is lower in GF flours (3.6 ± 3.1% vs. 7.1 ± 3.9%, p = 0.03), except for GF pseudocereal and legume flours. GF breads contain almost twice as much fat 6.6 ± 2.3% vs. 1.4 ± 0.2%, p < 0.001, and 4.2 ± 1.2%, p < 0.001) and fibre (7.3 ± 2.4% vs. 2.8 ± 0.5%, p < 0.001, and 4.9 ± 2.1%, p = 0.002) as GC breads. This is due to the raw materials themselves and to the addition of ingredients, such as regular and high oleic sunflower oil, and psyllium. Fibre ingredients and additives are more frequently used in ready-to-eat GF flours and breads, and more GF breads also contain fat-based ingredients, as compared to GC. Amaranth and chickpea flours are good alternatives to produce breads with better nutritional quality. Analysis of GF products for critical nutrients is peremptory because of continuing technological and nutritional innovation. Full article

Recycling polyethylene terephthalate (rPET) from packaging materials consumes a vast amount of energy and incurs significant economic and environmental costs. This study proposes directly recycling rPET into woven fabrics to eliminate reprocessing while still preserving the mechanical performance of the material. The mechanical properties of rPET were tested along two orthogonal directions, and the resulting test data were used to calibrate an elasto-plastic model in order to capture the constitutive behaviour of the material. Additionally, the virtual weaving of rPET fibres into fabrics was modelled using finite element analysis (FEA) to replicate the actual manufacturing process. The results show that rPET that is directly recycled into woven fabrics exhibits superior performance to the same material derived from reprocessing. A strong anisotropy of rPET materials was observed, with distinct elastic and ductile behaviours. The FEA simulation also revealed the critical role of the ductility of rPET fibres when used as warp yarns. The process parameters to achieve a successful weaving operation for different yarn configurations, taking into account the motion and tension of the fibres during manufacture, were also identified. A further sensitivity study highlights the influence of friction between the fibres on the tension force of warp yarns. The virtual manufacture-by-weaving model suggests that utilising rPET with a simplified recycling approach can lead to the sustainable manufacture of fabrics with broad industrial applications. Full article

Fibrous networks are porous materials that can have stochastic and uniform microstructures. Various fibrous networks can be found in nature (e.g., collagens, hydrogels, etc.) or manufactured (e.g., composites and nonwovens). This study focuses on the geometrical characterisation of stochastic fibrous networks with continuous fibres in a 2D domain, discussing their main relevant parameters: basis weight, orientation distribution function, crimp, porosity, spatial distribution of fibres (uniformity), and fibre intersections. The comprehensive review of the literature is combined with original results to understand the effect of the analysed parameters on various features of fibrous networks such as mechanical performance, filtration, insulation, etc. Full article

Processing hemp seeds into foods generates several by-products that are rich in nutrients and bioactive phytochemicals. This paper presents a thorough plant metabolite analysis and a comprehensive assessment of the nutrient content of 14 hemp seed-based foods and by-products and evaluates their feasibility to deliver dietary needs and daily recommendations. The protein-85-product was the hemp food and hemp fudge the hemp by-product with the highest content of protein, 93.01 ± 0.18% and 37.66 ± 0.37%, respectively. Hemp seed-hull flour had the richest insoluble non-starch polysaccharide content (39.80 ± 0.07%). Linoleic acid was the most abundant fatty acid across all the hemp seed-based samples (ranging from 53.80 ± 2.02% in the protein-85-product to 69.53 ± 0.45% in the hemp cream). The omega-6 to omega-3 fatty acid ratio varied from 3:1 to 4:1 across all hemp seed-based samples. The majority of hemp seed-based samples were rich sources of potassium, magnesium, and phosphorus. Gentisic acid, p-coumaric acid, and syringaresinol were the most abundant plant metabolites measured and found mainly in bound form. Hemp seed by-products are valuable sources of nutrients capable of meeting dietary needs and, therefore, should be re-valorized into developing healthy food formulations to deliver a truly zero-waste hemp food production. Full article

Carbon materials derived from lignocellulosic biomass (LCB) precursors have emerged as sustainable and versatile candidates, exhibiting outstanding properties for energy storage applications. This study presents an innovative and cost-efficient approach to produce graphitic carbon from an LCB precursor (pinecone) using an optimized hydrothermal treatment process followed by carbonization and graphitization. The developed pinecone-derived graphitic carbon (PDGC) was analyzed using X-ray diffraction (XRD), transmission electron microscopy (TEM) and scanning electron microscopy (SEM). XRD analysis confirmed the formation of a graphitic phase, indicated by a sharp and intense (002) peak, decreased interplanar spacing (d₀₀₂), increased crystallite size (L_c~20.4 nm), and a high degree of graphitization (g~0.7), closely aligning with the characteristics of pure graphite. Additionally, TEM and SEM micrographs revealed a flake-like morphology with well-defined, continuous, and extended graphitic layers within the PDGC structure. The distinctive structural attributes of the developed material position it as a promising candidate for batteries and capacitors, while also serving as a model for converting LCB into advanced carbon materials. Full article

This study explores the mechanical behaviour of intra-laminar hybrid flax/E-glass composites, focusing on the role of micro-scale irregularities in flax fibres. By employing computational micromechanics and Monte Carlo simulations, it analyses the influence of flax fibre geometry and elastic properties on the performance of hybrid and non-hybrid composites. A Non-Circular Fibre Distribution (NCFD) algorithm is introduced to generate microstructures with randomly distributed non-circular flax and circular E-glass fibres, which are then modelled using a 3D representative volume element (RVE) model developed in Python 2.7 and implemented with Abaqus/Standard. The RVE dimensions were specified as ten times the mean characteristic length of flax fibres (580 μm) for the width and length, while the thickness was defined as one-tenth the radius of the E-glass fibre. Results show that Monte Carlo simulations accurately estimate the effect of fibre variabilities on homogenised elastic constants when compared to measured values and Halpin-Tsai predictions, and they effectively evaluate the fibre/matrix interfacial stresses and von Mises matrix stresses. While these variabilities minimally affect the homogenised properties, they increase the presence of highly stressed regions, especially at the interface and matrix of flax/epoxy composites. Additionally, intra-laminar hybridisation further increases local stress in these critical areas. These findings improve our understanding of the relationship between the natural fibre shape and mechanical performance in flax/E-glass composites, providing valuable insights for designing and optimising advanced composite materials to avoid or delay damage, such as matrix cracking and splitting, under higher applied loads. Full article

This study presents a novel approach for filament recognition in fused filament fabrication (FFF) processes using a multi-spectral spectroscopy sensor module combined with machine learning techniques. The sensor module measures 18 wavelengths spanning the visible to near-infrared spectra, with a custom-designed shroud to ensure systematic data collection. Filament samples include polylactic acid (PLA), thermoplastic polyurethane (TPU), thermoplastic copolyester (TPC), carbon fibre, acrylonitrile butadiene styrene (ABS), and ABS blended with Carbon fibre. Data are collected using the Triad Spectroscopy module AS7265x (composed of AS72651, AS72652, AS72653 sensor units) positioned at three measurement distances (12 mm, 16 mm, 20 mm) to evaluate recognition performance under varying configurations. Machine learning models, including k-Nearest Neighbors (kNN), Logistic Regression, Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP), are employed with hyperparameter tuning applied to optimise classification accuracy. Results show that the data collected on the AS72651 sensor, paired with the SVM model, achieves the highest accuracy of 98.95% at a 20 mm measurement distance. This work introduces a compact, high-accuracy filament recognition module that can enhance the autonomy of multi-material 3D printing by dynamically identifying and switching between different filaments, optimising printing parameters for each material, and expanding the versatility of additive manufacturing applications. Full article

The use of a novel chrono-potentiometry method (abbreviated as “CP”) in the determination of the moisture content in wood (abbreviated as “MC”) above the FSP is a practical application of the electrical charging effect (or ECE). In the specific case of this CP method, the ECE consists of an electrical charging phase for the wood and a discharge phase following the interruption of the charging current. The electrical resistance, R, and the electrical chargeability, Cha(E), of three hardwood species were determined from the final potential, E1, of the charging phase and the initial potential, E2, of the discharge phase, with the three hardwood species being birch (Betula spp.), aspen (Populus spp.), and black alder (Alnus glutinosa (L.) Gaertn). An auxiliary variable in the form of U (E1; E2) was defined as a function of E1 and E2. This was used as an independent electrical variable in the calibration model for a CP moisture meter for the three tree species when it came to the moisture content (MC) region above the FSP (fibre saturation point). It was found that upon a determination of the MC in the wood, the traditional calibration model (the R-model), which uses the electrical resistance of wood, was able to predict a single-measurement precision level of +/−10% for the MC while the U-model predicted a precision level of +/−1.75% for the MC over a single MC measurement in the wood. Full article

Background/Objectives: Maternal Body Mass Index (BMI), diet quality, and their associated effects on offspring birth measures are well-established. Emerging evidence, largely from animal studies, has indicated paternal factors can influence offspring birth outcomes. However, this effect is poorly understood in humans. Our aim was to examine the association between paternal BMI and diet quality score and offspring birth measures. Methods: Participants from the STEPS (Steps to the healthy development) Study in Southwest Finland were recruited during the first trimester of pregnancy or after delivery. A total of 1586 fathers and their children were included for BMI analysis, and 208 fathers and their children were included for dietary analyses. Paternal BMI was calculated using self-reported weight and height at recruitment, and dietary behaviour was assessed using the Index of Diet Quality (IDQ) at 30 weeks’ gestation. Offspring birth weight and length z-scores were calculated using the recently published references specific to the Finnish population. Generalized linear model analyses were carried out to determine associations between paternal factors and offspring z-scores. Results: The mean paternal BMI was 26 (SD ± 3.5). Over half of the fathers were classed as having an unhealthy diet, classified as poor in adhering to nutrition recommendations including higher intakes of saturated fatty acids, and inadequate intakes of protein, saccharose, fibre, vitamins, and minerals. Paternal BMI was not significantly associated with offspring birth weight (β = 0.00 p = 0.884) or birth length (β = 0.00, p = 0.774) z-scores when adjusted for maternal and other paternal and parental factors. Paternal diet quality score was not associated with offspring birth weight (β = −0.01, p = 0.515) or birth length (β = 0.07 p = 0.291) z-scores. Conclusions: This study shows paternal BMI or diet quality at 30 weeks’ gestation does not significantly impact offspring birth measures. Given the known impact of nutrition on epigenetics, examining the potential influence of paternal factors at conception on offspring growth is of major importance and should be included in future studies. Full article

Optical Beam-Loss Monitors (oBLMs) allow for cost-efficient and spatially continuous measurements of beam losses at accelerator facilities. A standard oBLM consists of several tens of metres of optical fibre aligned parallel to a beamline, coupled to photosensors at either or both ends. Using the timing information from loss signals, the loss positions can be reconstructed. This paper presents a novel oBLM system recently deployed at the CERN Linear Electron Accelerator for Research (CLEAR). Multiple methods of extracting timing and position information from measured waveforms with silicon photomultipliers (SiPM) and photomultiplier tubes (PMT) are investigated. For this installation, the optimal approach is determined to be applying a constant fraction discrimination (CFD) on the upstream readout. The position resolution is found to be similar for the tested SiPM and PMT. This work has resulted in the development of a user interface to aid operations by visualising the beam losses and their positions in real time. Full article

In the field of liquid composite moulding (LCM) simulations, a long-standing assumption has dominated–the belief in constant resin viscosity. While effective in many cases, this assumption may not hold for the infusion process, which lasts for an extended period. This impacts the mechanical properties of the cured epoxy, which are crucial for load transfer in polymer structures. The majority of epoxy resins operate on a bipartite foundation, wherein their viscosity undergoes dynamic alterations during the process of cross-linking. Temperature and cross-linking intricately interact, with elevated temperatures initially reducing viscosity due to kinetic energy but later increasing it as cross-linking accelerates. This interplay significantly influences the efficiency of the infusion process, especially in large and intricate moulds. This article explores the significant temperature dependence of epoxy resin viscosity, proposing an accurate model rooted in its non-linear evolution. This model aligns with empirical evidence, offering insights into determining the optimal starting temperature for efficient mould filling. This study presents an advanced infusion model that extends existing non-linear dual-split viscosity approaches by incorporating the experimental validation of viscosity variations. Unlike previous models that primarily focus on theoretical or numerical frameworks, this work integrates experimental insights to optimize infusion temperature for efficient resin infusion in large and complex parts. Building on these findings, a novel mould-filling technique is proposed to enhance efficiency and reduce material waste. Full article

This study explores the potential of Arbutus unedo L. pomace, a by-product of the food industry, as a natural ingredient for skincare applications. In Portugal, A. unedo L. fruits are traditionally used to produce “Aguardente de Medronho”, a spirit with a protected geographical indication. The distillation process generates pomace, comprising skins, pulp remnants, seeds, and residual alcohol rich in phenolic compounds, whose levels are significantly increased during distillation. In addition to their documented high antioxidant content, these residues also display notable antimicrobial properties. However, their potential benefits for skin health have not yet been explored. The methodology entailed the preparation of the pomace extract and a comprehensive analysis of its polyphenolic content and antioxidant capacity under laboratory conditions and in preclinical cellular models. The by-products demonstrated a high polyphenol content and potent antioxidant activity, comparable to vitamin C. Bioscreening on human skin models (i.e., dermal fibroblasts and keratinocytes) revealed their ability to reduce reactive oxygen species (ROS) formation under oxidative stress in skin cells, highlighting their potential to mitigate skin aging and damage caused by environmental pollutants. Moreover, bioscreens in vitro revealed a high safety profile, without any interference with cell viability at concentrations up to 100 µg/mL. These findings support the use of A. unedo L. pomace extract as a sustainable ingredient for the development of antioxidant-rich and eco-friendly cosmetic or dermatologic products. Full article

In the transition towards a circular economy, redesigning construction materials for enhanced sustainability becomes crucial. To contribute to this goal, this paper investigates the integration of carbonated aggregates (CAs) and basalt fibre-reinforced polymers (BFRPs) in concrete infrastructures as an alternative to natural sand (NS) and steel reinforcement. CA is manufactured using accelerated carbonation that utilizes CO₂ to turn industrial byproducts into mineralised products. The structural performance of CA and BFRP-reinforced concrete simply supported slab was investigated through conducting a series of experimental tests to assess the key structural parameters, including bond strength, bearing capacity, failure behavior, and cracking bbehaviour. Carbon footprint analysis (CFA) was conducted to understand the environmental impact of incorporating BFRP and CA. The results indicate that CA exhibits a higher water absorption rate compared to NS. As the CA ratio increased, the ultrasonic pulse velocity (UPV), compressive, tensile, and flexural strength decreased, and the absorption capacity of concrete increased. Furthermore, incorporating 25% CA in concrete has no significant effect on the bond strength of BFRP. However, the load capacity decreased with an increasing CA replacement ratio. Finally, integrating BFRP and 50% of CA into concrete slabs reduced the slab’s CFA by 9.7% when compared with steel-reinforced concrete (RC) slabs. Full article

This work analyses promising solutions for controlling the output radiation properties of fibre lasers. The design of fibre lasers is radically different from that of other laser types. This is why many conventionally used solutions and approaches are incompatible with fibre lasers. Furthermore, fibre lasers following “all-fibre” designs also allow certain solutions that are impossible in other types of lasers. This work discusses those solutions, highlighting the promising applications for all-fibre lasers. Both the advantages and disadvantages of the very low sensitivity of the fibre laser cavities to the external factors are covered. Solutions that are already available commercially or may be expected to be in the near future are highlighted. Various aspects of sensor and communications applications of fibre lasers are discussed. Full article