Search Results (3,567)

Heusler-type metamagnetic shape memory alloys (MMSMAs) exhibit a large functional response associated with a first-order martensitic transformation (MT). The strong magneto-structural coupling combined with the presence of mixed magnetic interactions enables controlling this MT by means of a magnetic field, resulting in different multifunctional properties, among them giant magnetoresistance, metamagnetic shape memory effect (MMSM), or inverse magnetocaloric effect (MCE). Not only the shift rate of MT as a function of the magnetic field but also its eventual suppression are key parameters in order to develop these effects. Here we present our findings concerning a detailed study of the magnetic field-induced MT and its suppression in MnNi(Fe)Sn MMSMAs, by applying strong steady magnetic fields up to 33 T. These measurements will lead to the creation of the T-μ₀H phase diagrams of the MT. Moreover, we will also give light to the effect of Fe—content and, as a direct consequence, the magnetic coupling on the suppression of the magnetostructural transformation. Full article

Pickering emulsions have emerged as promising multiphase systems owing to their high stability and diverse applications in materials and chemical engineering. However, achieving precise and stimuli-responsive regulation of emulsion type, particularly reversible phase inversion between oil-in-water and water-in-oil states under fixed formulation without additional stabilizers, remains a considerable challenge. In this work, we developed a sol–gel strategy, i.e., in situ hydrolysis and condensation of silane precursors to form a silica shell directly on responsive microgels, to produce H-SiO₂@P(NIPAM-co-MAA) hybrid microgels. The resulting hybrid particles simultaneously retained pH and temperature responsiveness, enabling the transfer of these properties from the polymeric network to the emulsion interface. When employed as stabilizers, the hybrid microgels allowed the controlled formation of Pickering emulsions that remained stable for one week under testing conditions. More importantly, they facilitated in situ reversible phase inversion under external stimuli. Overall, this work establishes a sol–gel approach to fabricate organic–inorganic hybrid microgels with well-defined dispersion and uniform silica deposition, while preserving dual responsiveness and enabling controlled phase inversion of Pickering emulsions. Full article

This study investigates premature fatigue failure in rocker arm gears of large-mining-height shearers operating at alternating ±45° working angles, where insufficient lubrication generates non-uniform thermal -stress fields. In this study, an integrated multiphysics framework combining transient thermal–fluid–structure coupling simulations with fatigue life prediction is proposed. Transient thermo-mechanical coupling analysis simulated dry friction conditions, capturing temperature and stress fields under varying speeds. Fluid–thermal–solid coupling analysis modeled wet lubrication scenarios, incorporating multiphase flow to track oil distribution, and calculated convective heat transfer coefficients at different immersion depths (25%, 50%, 75%). These coupled simulations provided the critical time-varying temperature and thermal stress distributions acting on the gears (Z6 and Z7). Subsequently, these simulated thermo-mechanical loads were directly imported into ANSYS 2024R1 nCode DesignLife to perform fatigue life prediction. Simulations demonstrate that dry friction induces extreme operating conditions, with Z6 gear temperatures reaching over 800 °C and thermal stresses peaking at 803.86 MPa under 900 rpm, both escalating linearly with rotational speed. Lubrication depth critically regulates heat dissipation, where 50% oil immersion optimizes convective heat transfer at 8880 W/m²·K for Z6 and 11,300 W/m²·K for Z7, while 25% immersion exacerbates thermal gradients. Fatigue life exhibits an inverse relationship with speed but improves significantly with cooling. Z6 sustains a lower lifespan, exemplified by 25+ days at 900 rpm without cooling versus 50+ days for Z7, attributable to higher stress concentrations. Based on the multiphysics analysis results, two physics-informed engineering optimizations are proposed to reduce thermal stress and extend gear fatigue life: a staged cooling system using spiral copper tubes and an intelligent lubrication strategy with gear-pump-driven dynamic oil supply and thermal feedback control. These strategies collectively enhance gear longevity, validated via multiphysics-driven topology optimization. Full article

In horizontal well technology, hydraulic fracturing has been established as an essential technique for enhancing hydrocarbon production. However, the complex architecture of fracture networks challenges conventional monitoring methods. Micro-seismic monitoring, recognized for its superior resolution and sensitivity, enables precise fracture morphology characterization. This study advances diagnostic capabilities through integrated field–laboratory investigations and multi-domain signal processing. Hydraulic fracturing experiments under varied geological conditions generated critical micro-seismic datasets, with quantitative analyses revealing asymmetric propagation patterns (total length 312 ± 15 m, east wing 117 m/west wing 194 m) forming a 13.37 × 10⁴ m³ stimulated reservoir volume. Spatial event distribution exhibited density disparities correlating with geophone offsets (west wing 3.8 events/m vs. east 1.2 events/m at 420–794 m distances). Advanced time–frequency analyses and inversion algorithms differentiated signal characteristics demonstrating logarithmic SNR (Signal-to-Noise Ratio)–magnitude relationships (SNR 0.49–4.82, R² = 0.87), with near-field events (<500 m) showing 68% reduced magnitude variance compared to far-field counterparts. Coupled numerical simulations confirmed stress field interactions where fracture trajectories deviated 5–15° from principal stress directions due to prior-stage stress shadows. Branch fracture networks identified in Stages 4/7/9/10 with orthogonal/oblique intersections (45–65° dip angles) enhanced stimulation reservoir volume (SRV) by 37–42% versus planar fractures. These geometric parameters—including height (20 ± 3 m), width (44 ± 5 m), spacing, and complexity—were quantitatively linked to micro-seismic response patterns. The developed diagnostic framework provides operational guidelines for optimizing fracture geometry control, demonstrating how heterogeneity-driven signal variations inform stimulation strategy adjustments to improve reservoir recovery and economic returns. Full article

Background: MicroRNA-129 (miR-129) is a tumor suppressor involved in regulating oncogenic pathways, but its role in gastric adenocarcinoma and its potential connections to vascular and neurological dysfunction remain insufficiently defined. Objectives: To assess gastric juice-derived miR-129 as a diagnostic and prognostic biomarker for gastric cancer and to explore its associations with systemic inflammation, vascular impairment, and neurodegenerative changes. Methods: A prospective study was conducted in 38 patients undergoing upper gastrointestinal endoscopy (22 with histologically confirmed gastric adenocarcinoma, 16 controls). Gastric juice was aspirated prior to biopsy, and miR-129-2-3p expression was quantified by means of RT-qPCR normalized to U6 RNA. Tumor stage, serum biomarkers (CEA, CA 19-9, LDH, and CRP), carotid index (Doppler ultrasound), and neuroimaging (MRI) were recorded. Statistical analyses included ANOVA, Mann–Whitney U, ROC curve analysis, and correlation testing. Results: miR-129 expression was significantly reduced in gastric cancer compared with controls (ANOVA: F(3,34) = 3.70, p = 0.021, η² = 0.25). ΔCt values increased progressively from controls to T2–T4 tumors, indicating stage-dependent downregulation. ROC analysis demonstrated moderate diagnostic performance (AUC = 0.75, 95% CI 0.54–0.92). Lower miR-129 levels correlated inversely with serum tumor markers (CEA, CA 19-9), LDH, and CRP. Patients with elevated carotid index (>1.3) and abnormal brain imaging findings exhibited significantly lower miR-129 expression (both p < 0.05). Conclusion: Gastric juice-derived miR-129 is downregulated in gastric adenocarcinoma, with progressive decline across tumor stages. Its inverse association with systemic tumor and inflammatory markers, as well as vascular and neurological impairment, suggests that miR-129 may function as a minimally invasive, multi-system biomarker for integrated cancer and vascular–neurological risk assessment. Full article

Oujiang color common carp display four striking varieties of pigmentation, but their epigenetic basis is unclear. We integrated genome-wide DNA methylation (MBD-seq) and transcriptomes (RNA-seq) from dorsal skin of four Oujiang color common carp varieties with three biological replicates. Black-spotted groups (RB, WB) showed approximately 6% higher global methylation than non-black-spotted groups (WR, WW), with differential methylation enriched in introns (>23%) and intergenic regions (>47%). Integrative analyses revealed a strong inverse association between promoter methylation and gene expression; 96 pigmentation-related genes were identified, spotlighting genes such as ASIP and frmA as key epigenetically silenced regulators in black-spotted carp. RT-qPCR confirmed directional concordance with RNA-seq for ASIP, frmA, DGAT2, SCARB1, and FOSB. Pathway enrichment implicated melanogenesis metabolism, tyrosine metabolism, lipid metabolism, and fatty acid metabolism, suggesting an interplay between pigment deposition and metabolic regulation. Collectively, the findings present an exploratory view of epigenetic control of coloration and underscore promoter methylation as a core layer influencing color diversity in Oujiang color common carp. Full article

This paper introduces an open-source software framework for implementing Field-Oriented Control (FOC) on a Brushless DC Motor (BLDC) across its entire speed range. The control strategy employs a Direct FOC method with a single Hall sensor combined with Space Vector Pulse Width Modulation (SVPWM) and complementary sensorless techniques. The BLDC motor and supporting circuits are modeled and validated through both simulation and hardware implementation. A modular software architecture enables deployment via distinct system components, promoting hardware abstraction and reducing platform-specific dependencies. The entire setup is conceptualized and executed in MATLAB/Simulink R2024b and the framework supports remote experimentation through a web-based interface, requiring only a single MATLAB license. This scalable solution is designed for academic researchers and industry practitioners alike, offering an accessible low-cost platform for motor control development, validation, and early-stage prototyping. Full article

Background/Objectives: This study aimed at evaluating the association between maternal pre-pregnancy glycemic status and growth delay in offspring using nationwide health screening data. Methods: A retrospective cohort of 258,367 mother–child dyads born between 2014 and 2021 was analyzed. Maternal glycemic status was categorized as normal (<100 mg/dL), impaired fasting glucose (IFG, 100–125 mg/dL), or diabetes mellitus (DM, ≥126 mg/dL). Growth delay was defined as measurements below the 10th percentile of height, weight, and head circumference at 18–24 and 30–36 months. Visual and auditory development were assessed using caregiver questionnaires. Inverse probability of treatment weighting was applied, and weighted relative risks (RRs) were estimated. Results: The prevalence of growth delay was 3.5% for height, 3.8% for weight, and 4.3% for head circumference; visual and auditory problems were reported in 1.2% and 8.2% of children, respectively. Both the DM (1.2%) and IFG (9.3%) groups showed increased risks of growth delay across both age periods. Maternal hyperglycemia was also associated with offspring’s visual and auditory development, with age- and period-specific differences observed. Conclusions: Maternal pre-pregnancy glycemic status was significantly associated with delayed growth in Korean children aged 18–36 months. These findings highlight the importance of optimizing maternal glycemic control prior to pregnancy for favorable child developmental outcomes. Full article

Due to its unique benefits over conventional subtractive manufacturing, additive manufacturing methods continue to attract interest in both academia and industry. One such method is called Cold Spray Additive Manufacturing (CSAM), a solid-state coating deposition technology to manufacture repair metallic components using a gas jet and powder particles. CSAM offers low heat input, stable phases, suitability for heat-sensitive substrates, and high deposition rates. However, persistent challenges include porosity control, geometric accuracy near edges and concavities, anisotropy, and cost sensitivities linked to gas selection and nozzle wear. Interdisciplinary research across manufacturing science, materials characterisation, robotics, control, artificial intelligence (AI), and machine learning (ML) is deployed to overcome these issues. ML supports quality prediction, inverse parameter design, in situ monitoring, and surrogate models that couple process physics with data. To demonstrate the impact of AI and ML on CSAM, this study presents a systematic literature review to identify, evaluate, and analyse published studies in this domain. The most relevant studies in the literature are analysed using keyword co-occurrence and clustering. Four themes were identified: design for CSAM, material analytics, real-time monitoring and defect analytics, and deposition and AI-enabled optimisation. Based on this synthesis, core challenges are identified as small and varied datasets, transfer and identifiability limits, and fragmented sensing. Main opportunities are outlined as physics-based surrogates, active learning, uncertainty-aware inversion, and cloud-edge control for reliable and adaptable ML use in CSAM. By systematically mapping the current landscape, this work provides a critical roadmap for researchers to target the most significant challenges and opportunities in applying AI/ML to industrialise CSAM. Full article

A specific challenge in robotic control applications is the identification and regulation of actuators that provide mechanical traction and motion to the robot links. The design of actuator control laws, grounded in parametric identification and experimental motor characterization, enables numerical simulations to explore diverse operating scenarios. This article presents the initial phases in the development of a robotic rehabilitation system, focused on the kinematic modeling of a parallelogram-configuration robot for upper-limb therapy, the fuzzy identification of its actuators, and their closed-loop evaluation using a fuzzy Parallel Distributed Compensation (PDC) controller with state feedback (Ackermann), whose poles are optimized via the Grey Wolf Optimizer (GWO) metaheuristic. This controller was selected for its congruence with the nonlinear universe of discourse defined by the identified model, a key feature for operation within specific functional ranges in medical applications. The simulation and hardware platform results provide evidence that fuzzy dynamic models constitute a valuable tool for application in rehabilitation systems. This work serves as a foundation for future physical implementations with the fully coupled robotic system, in order to ensure operational safety prior to the start of clinical trials. Full article

Background: The interaction between anthocyanidin intake and dietary inflammatory potential might influence small-for-gestational-age (SGA), but the available evidence has been limited. This study aims to examine the associations of anthocyanidin with SGA and whether these associations change with dietary inflammatory potential. Methods: Data were derived from 2244 pregnant women enrolled in a community-based, randomized controlled trial between 2015 and 2019 in China. Anthocyanidin intake was calculated with the use of validated food-frequency questionnaires. The energy-adjusted dietary inflammatory index (EDII) was determined by aggregating data from 33 food parameters. Infant birth outcome measurements were obtained from hospital records. Associations were assessed by generalized estimating equations with adjustment for confounding factors. Results: During 39.7 gestational weeks of follow-up, 234 SGA cases occurred. The median intake of anthocyanidin was 28.7 mg/d. Higher consumption of total anthocyanidins (OR: 0.96, 95% CI: 0.95 to 0.97), cyanidin (OR: 0.96, 95% CI: 0.95 to 0.97), and peonidin (OR: 0.96, 95% CI: 0.96 to 0.97) subclasses was associated with a reduced risk of SGA. EDII was associated with an increased risk of SGA (OR: 1.08, 95% CI: 1.03 to 1.12). In addition, we observed that higher anthocyanidin intake was inversely associated with EDII (β: −0.40, 95% CI: −0.46 to −0.34). The inverse anthocyanidin-SGA association was mostly greater among women in the highest tertile of EDII (OR: 0.67, 95% CI: 0.65 to 0.68) compared with the lowest tertile. Conclusions: Higher anthocyanidin intake was inversely associated with SGA, especially among women with higher EDII scores. Full article

Background: Evidence on how everyday walking and sleep relate to mood in health profession students from Central–Eastern Europe remains limited. Methods: We conducted a cross-sectional study among 277 Romanian medical students. Data were collected using validated instruments for physical activity (IPAQ-SF), sleep quality (PSQI), and depressive/anxiety symptoms (HADS). Associations were examined using bivariate and multivariable regression models, including sex-stratified analyses. Results: In bivariate analysis, total physical activity was inversely correlated with depressive symptoms (ρ = −0.19, p < 0.001). However, in the multivariable model, this effect was not statistically significant after controlling for other factors. Poor sleep quality emerged as the dominant independent predictor of both depression (β = 0.37, p < 0.001) and anxiety (β = 0.40, p < 0.001). Walking time and frequency were specifically protective against depressive symptoms. Sex-stratified analyses revealed distinct patterns: female students benefited more from walking, whereas male students showed stronger associations between overall physical activity and lower depressive symptoms. Conclusions: Within the constraints of a cross-sectional design, this study provides novel evidence from Eastern Europe that sleep quality and physical activity are central to student mental health. Psychological benefits of walking appear sex-specific, and the null mediation finding suggests benefits operate via direct or unmodelled pathways. Sleep is a critical independent target for tailored, lifestyle-based strategies. Full article

This article presents an innovative approach to optimizing the seismic modeling and analysis of high-rise buildings by automating the process with Python 3.13 and the ETABS 22.1.0 API. The process begins with the collection of information on the base building, a structure of seventeen regular levels, which includes data from structural elements, material properties, geometric configuration, and seismic and gravitational loads. These data are organized in an Excel file for further processing. From this information, a code is developed in Python that automates the structural modeling in ETABS through its API. This code defines the sections, materials, edge conditions, and loads and models the elements according to their coordinates. The resulting base model is used as a starting point to generate an optimal solution using a genetic algorithm. The genetic algorithm adjusts column and beam sections using an approach that includes crossover and controlled mutation operations. Each solution is evaluated by the maximum displacement of the structure, calculating the fitness as the inverse of this displacement, favoring solutions with less deformation. The process is repeated across generations, selecting and crossing the best solutions. Finally, the model that generates the smallest displacement is saved as the optimal solution. Once the optimal solution has been obtained, it is implemented a second code in Python is implemented to perform static and dynamic seismic analysis. The key results, such as displacements, drifts, internal and basal shear forces, are processed and verified in accordance with the Peruvian Technical Standard E.030. The automated model with API shows a significant improvement in accuracy and efficiency compared to traditional methods, highlighting an R² = 0.995 in the static analysis, indicating an almost perfect fit, and an RMSE = 1.93261 × 10⁻⁵, reflecting a near-zero error. In the dynamic drift analysis, the automated model reaches an R² = 0.9385 and an RMSE = 5.21742 × 10⁻⁵, demonstrating its high precision. As for the lead time, the model automated completed the process in 13.2 min, which means a 99.5% reduction in comparison with the traditional method, which takes 3 h. On the other hand, the genetic algorithm had a run time of 191 min due to its stochastic nature and iterative process. The performance of the genetic algorithm shows that although the improvement is significant between Generation 1 and Generation 2, is stabilized in the following generations, with a slight decrease in Generation 5, suggesting that the algorithm has reached its level has reached a point of convergence. Full article

Background: Maple syrup urine disease (MSUD) is a genetic disorder caused by mutations in the branched-chain α-ketoacid dehydrogenase (BCKDH) complex, leading to toxic buildup of branched-chain amino acids (BCAAs) and their ketoacid derivatives. While newborn screening (NBS) and molecular testing are standard diagnostic tools, they face challenges such as delayed results and false positives. Untargeted metabolomics has emerged as a complementary approach, offering comprehensive metabolic profiling and potential for novel biomarker discovery. We previously applied untargeted metabolomics to neonates with MSUD, identifying distinct metabolic signatures. Objective: This follow-up study investigates metabolic changes and biomarkers in pediatric MSUD patients and explores shared dysregulated metabolites between neonatal and pediatric MSUD. Methods: Dried blood spot (DBS) samples from pediatric MSUD patients (n = 14) and matched healthy controls (n = 14) were analyzed using LC/MS-based untargeted metabolomics. Results: In pediatric MSUD, 3716 metabolites were upregulated and 4038 downregulated relative to controls. Among 1080 dysregulated endogenous metabolites, notable biomarkers included uric acid, hypoxanthine, and bilirubin diglucuronide. Affected pathways included sphingolipid, glycerophospholipid, purine, pyrimidine, nicotinate, and nicotinamide metabolism, and steroid hormone biosynthesis. Seventy-two metabolites overlapped with neonatal MSUD cases, some exhibiting inverse trends between age groups. Conclusion: Untargeted metabolomics reveals that the metabolic profiling of MCUD pediatric patients different from that of their controls. Also, there are valuable age-specific and shared metabolic alterations in MSUD, enhancing the understanding of disease progression in MSUD patients. This supports its utility in improving diagnostic precision and developing personalized treatment strategies across developmental stages. Full article

This study presents the design, development, and experimental validation of a novel cable-driven shoulder exosuit (CDSE) for upper limb rehabilitation and assistance. Unlike existing exoskeletons, which are often bulky, limited in degrees of freedom (DOFs), or impractical for home use, the proposed DSE offers a lightweight (≈2 kg), portable, and wearable solution capable of supporting three shoulder movements: abduction, flexion, and horizontal adduction. The system employs a bioinspired tendon-driven mechanism using Bowden cables, transferring actuation forces from a backpack to the arm, thereby reducing user load and improving comfort. Mathematical models and inverse kinematics were derived to determine cable length variations for targeted motions, while control strategies were implemented using a PID-based approach in MATLAB Simscape-Multibody simulations. The prototype was fabricated in three iterations using PLA, aluminum, and carbon fiber—culminating in a durable and ergonomic final version. Experimental evaluations on a healthy subject demonstrated high accuracy in position tracking (<5% error) and torque profiles consistent with simulation outcomes, validating system robustness. The CDSE successfully supported loads up to 4 kg during rehabilitation tasks, highlighting its potential for clinical and at-home applications. This research contributes to advancing wearable robotics by addressing portability, biomechanical alignment, and multi-DOF functionality in upper limb exosuits. Full article