Search Results (9,448)

The present work examines methods for enhancing dimensional accuracy and circularity in CNC circular end milling processes. While conventional optimization often focuses solely on mechanical cutting parameters, this research integrates the Taguchi method, Response Surface Methodology (RSM), and Analysis of Variance (ANOVA) to explicitly quantify the impact of thermal equilibrium alongside cutting mechanics. The results reveal a novel finding: warm-up time is the dominant factor, contributing 41.01% to dimensional accuracy and 49.97% to circularity variation, significantly outweighing spindle speed and feed rate. The optimized parameter combination—comprising a specific warm-up protocol, depth of cut, and feed per tooth—improved dimensional accuracy by approximately 38% and circularity by 33%. This study provides a critical operational guideline for precision manufacturing: implementing a thermal stability protocol is a prerequisite for realizing the benefits of mechanical parameter optimization. Full article

This study evaluated the effects of thermocycling on surface roughness (Ra), gloss (GU), color stability (ΔE₀₀), and water sorption of interim materials manufactured by three methods. Disc specimens (n = 20/group) were fabricated from a conventional bis-acryl (PreVISION^® Temp), a computer-aided design/computer-aided manufacturing (CAD/CAM)-milled methacrylate-based composite (StructurCAD Disc^®), and a 3D-printed resin composite (Alias Dental Temp C&B^®). Two disc dimensions were used: 10 × 2 mm for Ra, GU, and color, and 15 × 1 mm for water sorption. Measurements were performed before and after thermocycling (10,000 cycles; 5–55 °C). Nonparametric tests were used (α = 0.05). After thermocycling, Ra increased in the conventional and 3D-printed groups, whereas the milled group demonstrated a decrease (p < 0.05). GU decreased across all groups (p < 0.001) and differed among materials (p = 0.021), with a significant difference only between milled and 3D-printed groups. Color stability differed among materials (p < 0.001): the milled group showed the lowest ΔE₀₀ perceptibility threshold (below PT₀₀ = 0.81), whereas conventional and 3D-printed groups exceeded the acceptability threshold (AT₀₀ = 1.81). Water sorption differed among groups (p < 0.001), with a significant difference between the milled and 3D-printed groups (p < 0.001). The tested 3D-printed material exhibited less favorable post-thermocycling optical properties, whereas the evaluated CAD/CAM-milled material demonstrated more favorable overall surface and optical performance under the applied aging conditions. Full article

Opuntia ficus-indica (L.) Mill., also named Cactus pear, is a crop widespread in many countries with Mediterranean and subtropical climates, where it represents a valuable source of food. However, in southern Europe, this fruit market is limited to a few months, from summer to autumn. The possibility to extend the ripening period of fruit is represented by the special pruning of the first bloom flush and consequent new development of late flowers and fruits. Extending the cultivation period would allow farmers to maximize the crop’s potential, thereby extending the Cactus pear market season throughout much of the year. In this study, conducted in southern Sardinia (Italy), progressive pruning was applied with the aim of evaluating the fruit characteristics in relation to this type of cultivation, also considering the weather conditions during the experimental period. Morphological traits and physicochemical compositions of fruit picked in four harvests during two sampling seasons from August 2022 to March 2023, and from August 2023 to March 2024 were compared. According to principal component analysis (PCA), most of the observed characters showed significant differences among harvest periods but also between the two seasons of cultivation (year of cultivation: r = 0.722 on PC1), suggesting that the meteorological trend strongly modulated fruit traits. Some fruit qualities were partially lost during the winter months, such as juice acidity and total soluble solids (TSS). October was the month with the highest TSS levels (13.5 ± 0.25), followed by August, January and March. On the other hand, juiciness and fresh weight remained unchanged or even improved in fruit harvested out-of-season. As observed in the redundancy analysis (RDA) a contribution of 54% due to weather variability emerged. In Particular, TSS levels, pH and juice dry matter were associated with high temperatures, solar radiation, and wind intensity. Wind speed was also moderately linked with betalain content. Moreover, high relative humidity was associated with lower pH values, higher water content, and higher fruit fresh weight. A significant difference was found between the two years in betalains content (80.0 ± 3.7 µg·mL⁻¹ in 2022–2023 and 28.2 ± 2.5 µg·mL⁻¹ in 2023–2024). The breakdown in the 2023–2024 season was likely due to the strong heat wave of July 2023 (up to 47 °C), which caused their partial degradation. In light of seasonal variability, this work provides some useful insights for future management of Cactus pear, also considering the possibility of usefully extending the period of cultivation and harvesting. Full article

A mandatory prerequisite for a good hydrogen storage material is long-term stability in hydriding/dehydriding reactions, in a suitable temperature interval (250–350 °C for magnesium intermetallics). A 50-cycle hydriding/dehydriding stability test of two Mg₂(Co_1/3Fe_1/3Ni_1/3) materials is presented. Mg₂(Co_1/3Fe_1/3Ni_1/3) was processed progressively by ball milling and annealing, followed by high-pressure torsion. A comparison of the effects of the processing on the cycling test is presented. X-ray diffraction, scanning and transmission electron microscopy, and infrared characterization indicate the morphological and structural changes in the materials after production and cycling. The highest hydrogen storage was 3.55 wt.% and 3.25 wt.% for the ball-milled and annealed Mg₂(Co_1/3Fe_1/3Ni_1/3) and high-pressure torsion processed Mg₂(Co_1/3Fe_1/3Ni_1/3), respectively, at 15 bar and 300 °C. After 50 cycles of hydriding/dehydriding reactions, the hydriding onset temperature is 69 °C and 50 °C for the ball-milled and annealed Mg₂(Co_1/3Fe_1/3Ni_1/3) and high-pressure torsion processed Mg₂(Co_1/3Fe_1/3Ni_1/3), respectively. Meanwhile, the dehydriding onset temperatures are 257 °C and 223 °C, with hydrogen storage losses of 16% and 7.4% for the ball-milled and annealed Mg₂(Co_1/3Fe_1/3Ni_1/3) and the high-pressure torsion processed Mg₂(Co_1/3Fe_1/3Ni_1/3), respectively. Overall, the ball-milled and annealed Mg₂(Co_1/3Fe_1/3Ni_1/3) material presented better performance. Full article

Research on hydrogen production by chemical methods has focused on combining metals to carry out the hydrolysis reaction under ambient conditions. In particular, aluminum and lithium metals were considered, with lithium used at low concentrations in order to activate aluminum. Under these conditions, the metals can react with water to obtain the maximum hydrogen yield. The main objective of this work was to prepare the lithium−aluminum alloy by mechanical milling and its chemical reaction with water to produce hydrogen under laboratory conditions. A high–energy Spex mill was used for material preparation and the time scheduled for alloys preparation was relatively short. Several techniques were used for its characterization, such as X–ray diffraction, scanning electron microscopy, gas chromatography, and low-temperature physical adsorption. According to the results, two phases were produced during the milling process when using 5% lithium. The volume of hydrogen generated was measured using a graduated burette. Depending on the volume obtained, the aluminum reacted to generate hydrogen with an efficiency of 95.24%. No additives or catalysts were used in material synthesis or hydrogen production. According to these results, the hydrogen does not require any purification because it is clean hydrogen and can therefore be used directly in fuel cells. Full article

This study investigates the failure mechanisms and machining performance of 3D-printed H13 tool steel end mills driven by the creation of a Finite Element Analysis (FEA)-based digital twin. The primary objective is to assess the process capability of these tools by integrating CAD and FEA with product design simulation-based data acquisition within a digital manufacturing framework, thereby validating a physical model. This research begins by redesigning a 20 mm end mill into a 6 mm, four-flute configuration, and then FEA simulating H13 tool steel and tungsten carbide (WC) tools. This is carried out to machine Al-6082-T6 under spindle speeds of 5500 rpm and 1500 rpm, with a constant feed rate of 0.5 mm/tooth over 100,000 cycles. The process is integrated with the Siemens Insights hub via Node-RED to replicate the simulation to correlate the CPU signal spikes and enhanced processing capacity, especially in relation to CAD/CAE kernel activities. Based on the simulation insights, two H13 end mills are fabricated using Fused Filament Fabrication (FFF). The first tool, tested at 5500 rpm and a 1100 mm/min feed rate, fractured after 70 mm of cutting. The second trial, using a diamond-coated solid carbide tool at 1500 rpm and 300 mm/min, achieved successful machining with graphene-enhanced coolant. The cutting forces ranged from 300 to 500 N for 3D-printed tools, compared with 150–180 N for the carbide tool. The surface roughness varied between 0.6–1 µm and 4–6 µm for the printed tools, aligning closely with traditional tools (0.5–1 µm). Post-machining analysis using SEM and EDX confirmed tool wear and material changes. This work adopted a methodology to capture and monitor CPU signal spikes via the digital twin platform, enabling real-time comparison with failure thresholds. The results demonstrate the feasibility of using 3D-printed H13 tools for sustainable, customizable machining, offering a pathway for industries to adopt in-house tool design and manufacturing with integrated digital validation. Full article

Mn₅₄Al₄₆ alloys with τ-phase as their main component were successfully obtained in a reproducible processing window combining melt-spinning, annealing at intermediate temperatures (450 °C) and low-energy milling. The complete ε → τ phase transformation was driven by thermal decomposition of ε-phase and favored by high grain boundary density inherent to the melt-spun microstructure. An improved magnetic response of the melt-spun Mn₅₄Al₄₆ alloys was observed, as they exhibited saturation magnetization values between 80 and 90 emu/g, together with intrinsic coercivities around 2000 Oe and Curie temperatures between 640 and 648 K. Significant coercivity enhancement over 6000 Oe was predicted, by means of micromagnetic calculations, for alloys with grain size refinement below 100 nm. The efficient, single-step experimental phase transformation with no additional stabilizers for the τ-phase was explained in terms of microstructural features, whereas magnetic enhancement was attributed to lattice distortions promoted by the milling process. This integrated approach introduces a pathway to achieve τ-phase Mn-Al with tunable magnetic performance useful for applications. Full article

Background/Objectives: Cortisol has become established as a relevant biomarker due to its association with various pathologies, including its potential utility in mental health research. However, regarding the techniques employed for its analysis, the available literature shows a certain degree of heterogeneity both in the methods used to obtain cortisol and in the analytical techniques employed for its measurement. This makes it difficult to compare results across specific populations, particularly in pregnant women, who experience metabolic and physiological changes characteristic of gestation. Therefore, the aim of this study was to describe the procedure for the extraction and analysis of cortisol in hair samples from pregnant women throughout gestation. Methods: Hair samples, three centimeters in length, were obtained from women during the first, second, and third trimesters of pregnancy. These samples underwent a standardized isopropanol washing step, followed by milling in a laboratory mill using zirconium balls of varying diameters. The resulting hair powder was then weighed and subjected to four incubation cycles using HPLC-grade methanol. Cortisol levels were detected using chemiluminescence immunoassay. Results: Mean hair cortisol levels were 4.1 μg/L (ng/mL) in the first trimester, 11.5 μg/L (ng/mL) in the second trimester, and 6.6 μg/L (ng/mL) in the third trimester. Conclusions: Standardizing the methodology for cortisol extraction improves the reproducibility of results and, in the long term, may support its incorporation into clinical practice as a useful tool for assessing cortisol levels in both pregnant women and the general population, since hair cortisol enables retrospective evaluation of its cumulative exposure over time, approximately on a monthly basis. Full article

SAG grinding mills represent critical energy-intensive operations in copper concentrators, accounting for 30%–50% of total plant energy consumption. The accurate prediction of mill power draw and production rate under varying operational conditions is essential for real-time control, production planning, and energy management. This study presents a comprehensive comparison of ML algorithms for modeling Production and Power in a Chilean copper mining industry. Deterministic and stochastic models were fitted and validated using industrial data from a Chilean copper operation. More representative models were re-estimated and subsequently evaluated under different operating regimes to examine their predictive performance under aggregated conditions of the feeding variables. This procedure allowed for the identification of the modeling approaches that provide the most robust performance across varying operational regimes. The results show that XGB achieved the best predictive performance, with test RMSE and R² values of 87.98 and 97.35% for SAG Production, and 431.11 and 95.11% for SAG Power, respectively. Stochastic approaches provided complementary uncertainty quantification, supporting risk-informed decision making under variable operating conditions. The analysis by operational regime indicates that XGB presents better fit in the Thick hydraulic regime, for both responses’ variables, which could be explained why a dense pulp operation provides more predictable grinding dynamics. The comparative analysis reveals trade-offs between model complexity, interpretability, computational requirements, and predictive performance, offering practical guidance for selecting appropriate modeling frameworks based on specific operational objectives and data availability in mineral processing applications. Full article

The extensive utilisation of chemical fertilisers and pesticides in agricultural contexts has precipitated substantial environmental degradation, thereby amplifying the repercussions of climate change. Furthermore, this overuse poses a threat to the sustainability and resilience of global food production systems. The utilisation of microalgae-based biostimulants is a novel and sustainable approach that has the potential to enhance crop productivity and resilience, while reducing dependence on chemical pesticides and their negative effects. The present study evaluated the effectiveness of two novel microalgae-based formulations on the performance of processing tomato (Solanum lycopersicum) crops under field conditions in Spain and Portugal. The formulation comprised enzymatically hydrolysed biomass from L. platensis, N. gaditana and A. obliquus, in combination with olive mill wastewater (alpechin) and aromatic plant extracts. The mixture was applied through drip irrigation and foliar spraying. The application of combined foliar and drip treatments resulted in a substantial enhancement in gross yield up to 51.9%. Concurrently, the acceptable raw material yield demonstrated a notable increase up to 44.9%. Furthermore, an increase in average fruit weight by 2–9 g was recorded. A subsequent foliar nutrient analysis revealed elevated concentrations of N, P, K, Ca, Mg, Fe, and Cu in the plants treated with biostimulants, achieving 3.61, 52.94, 5.96, 36.53, 22.28, 60.41 and 71.32% respectively in the plot L4 with foliar treatment. Although the efficacy of pest control measures was slightly lower than that of conventional pesticides, no significant increase in the incidence of diseased was observed. These findings indicated that microalgae-based biostimulants have the potential to function as sustainable agricultural inputs capable of enhancing crop yields and quality while reducing dependence on chemical fertilisers and pesticides. The outcomes of the study demonstrate the efficacy of microalgae-based formulations in enhancing the yield and quality of tomato crops. This is achieved while maintaining optimal plant health and reducing the reliance on synthetic fertilisers and pesticides. Full article

Mill relining manipulator is essential maintenance equipment used to replace liners in a grinding mill. However, its excessive structural weight significantly constrains maneuverability and operational efficiency. To address this problem, this paper proposed a lightweight design framework for the manipulator’s upper arm, integrating improved multiple operating conditions topology optimization with size optimization. Firstly, a finite element model of the manipulator was established in ANSYS Workbench 2022R2. The loads under the corresponding operating conditions were extracted and applied to the finite element model of the upper arm to perform multi-condition finite element simulations. Secondly, a mathematical model for multi-condition topology optimization was developed using the variable density method combined with the Analytic Hierarchy Process (AHP), and the weight coefficients for each operating condition were determined. Finally, a combined response surface methodology (RSM) and genetic algorithm (GA) approach was employed to optimize the structural parameters of the upper arm. A response surface model with maximum equivalent stress and maximum deformation as the response variables was constructed, and the Pareto optimal set was obtained using the non-dominated sorting genetic algorithm (NSGA-II) to determine the optimal structural design. Quasi-static load tests were conducted on a scaled prototype to verify the reliability of the numerical optimization results. The results demonstrate that the optimized upper arm satisfies the strength and stiffness requirements while achieving a 12% mass reduction (2463 kg), confirming the effectiveness and engineering applicability of the proposed lightweight design methodology. Full article

The paper explores the use of artificial neural networks for surface roughness parameter Ra prediction when milling the finishing of flat surfaces with toroidal milling on C45 steel. The experiments were conducted on a 5-axis CNC center, varying three main parameters: cutting speed, feed per tooth, and tool axis tilt angle. In total, 70 surfaces were processed, with multiple measurements of Ra roughness. The data were preprocessed in MATLAB (noise reduction by Z-score and augmentation to 630 values) and used to train an artificial feedforward neural network with Bayesian regularization. The resulting model showed good performance on the dataset and was experimentally validated on three new parameter combinations, processed and measured independently with a 3D scanner. The results confirm the network’s ability to estimate Ra roughness based on varying process parameters. The paper proposes the model as a useful tool for assessing surface quality in finishing milling and recommends extending the experimental base as the main direction of continuation. Full article

Quinoa fibre-rich fraction (QFi), obtained through wet milling, represents an innovative approach to improving the nutritional and functional quality of cereal-based products. Unlike conventional whole quinoa flour (WhQF), wet milling induces phytate losses during steeping, generating ingredients with enhanced mineral bioavailability. This study evaluated the incorporation of QFi into wheat pasta, assessing dietary fibre contribution, mineral bioavailability, cooking behaviour, and colour. Six fortified formulations were prepared by partially replacing wheat flour with WQF (white, red, or black) or QFi from the same varieties, with inclusion levels adjusted to provide equivalent dietary fibre across formulations. All quinoa-enriched pastas raised dietary fibre contribution compared with the control. Mineral contents also incremented, with the greatest values observed in formulations containing black quinoa ingredients. Fe and Zn contents were greatest in pastas with black WhQF, while Ca concentration was richer in formulations containing black QFi. Mineral absorption may be partially inhibited in pastas with WhQF, particularly in those containing the red quinoa. In contrast, QFi showed reduced phytate levels, highlighting the nutritional advantage of wet milling. Technologically, quinoa ingredients increased water absorption during pasta cooking. Overall, wet milled QFi provides a novel alternative to WhQF, combining improved mineral bioavailability with suitable technological properties for pasta processing. Full article

Tilia cordata Mill. is a long-lived, ecologically important broadleaved tree species that maintains high genetic diversity despite habitat fragmentation and historical range shifts. In this study, we assessed genetic diversity, clonal structure, and population differentiation in six genetic conservation units (GCUs) in Lithuania using nuclear microsatellite markers. A total of 1109 individuals were successfully genotyped, revealing 979 unique multi-locus genotypes, with 17% of individuals assigned to clonal lineages. Clonal groups were generally small and spatially restricted, indicating localized vegetative regeneration. Genetic diversity was high across all populations, with similar levels of observed and expected heterozygosity, consistent with predominantly outcrossing reproduction. Juvenile cohorts exhibited slightly higher allelic richness and latent genetic potential compared to mature trees, suggesting effective regeneration and maintenance of genetic variation. Genetic differentiation among populations was low but significant (F_ST = 0.013; G″_ST = 0.051), with evidence of clustering corresponding to provenance regions. High gene flow (Nm ≈ 10) likely contributes to weak population structure, although regional differentiation persists. The results demonstrate that Lithuanian T. cordata populations retain a robust genetic framework, combining high within-population diversity with moderate structuring. These findings highlight the importance of conserving multiple GCUs and implementing genetic monitoring to ensure long-term population viability under changing environmental conditions. Full article

Monitoring avocado (Persea americana Mill., cv. Semil-34) in tropical mountain landscapes of Cambita, San Cristóbal, Dominican Republic is inherently complex due to the pronounced topographical and climatic heterogeneity that modulates the crop’s ecophysiological responses, specifically vegetative vigor, carbon allocation, and the synchronization of reproductive flushes. This study integrates 5-year (2020–2025) Sentinel-2 time series, ERA5-Land climatic variables (air temperature, total precipitation, and radiation), and geomorphometric covariates to explain variability in yield and fruit quality. Multispectral indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Red Edge (NDRE), and Normalized Difference Moisture Index (NDMI), were analyzed using Partial Least Squares Regression (PLSR) to characterize phenological dynamics and rank dominant predictors. The results revealed coherent spectral phenological trajectories; however, a significant inverse relationship was detected between canopy vigor and yield during reproductive phases. High vegetation index values were significantly and negatively associated with lower production (r = −0.58, p < 0.0021), reflecting a potential source–sink imbalance. Topography functioned as a structural filter, regulating root drainage and productive stability across the landscape. While yield variability was partially explainable (R² = 0.38), internal fruit quality, measured as dry matter content, exhibited comparatively high environmental stability. A central contribution of this research lies in identifying the “vigor paradox” in cv. Semil-34 and the suggestion that topography may exert a stronger influence than direct spectral signals under tropical hillside conditions. These findings provide an exploratory framework for anticipating yield and fruit quality through satellite remote sensing or UAVs, supporting site-specific management decisions in mountain agricultural systems. Full article