Search Results (5,451)

 Although polylactic acid (PLA) and acrylonitrile–butadiene–styrene (ABS) are among the most widely used polymers in material extrusion, their limited toughness and energy-absorption capacity often restrict the structural performance of 3D-printed functional components. To address the limited comparative understanding of how thermoplastic polyurethane (TPU) modifies the deformation behavior and phase characteristics of these two polymer systems, this study presents a multi-analytical evaluation of TPU-reinforced PLA and ABS blends. To this end, both polymers were blended with TPU at 10–50 wt% and processed into filaments via single-screw extrusion. The resulting filaments were used to fabricate ASTM D638 Type I tensile specimens via material extrusion under matrix-specific, but internally consistent, printing parameters. For each composition, five specimens were tested to obtain representative values of tensile strength, elongation at break, and toughness. In addition to conventional tensile testing, the evolution of strain during deformation was monitored using digital image correlation (DIC), enabling full-field characterization of local deformation behavior. To ensure experimental reliability, specimen masses were carefully controlled, and the datasets were analyzed using MATLAB. Thermal properties were investigated by differential scanning calorimetry (DSC) to determine the influence of TPU on glass transition, melting behavior, and phase mobility, and to relate these thermal characteristics to the mechanical response of the blends. The incorporation of TPU significantly increased ductility and energy absorption in both polymer matrices, although the magnitude of improvement differed. ABS/TPU blends exhibited the highest toughness enhancement, reaching 221.4% at 30 wt% TPU, while PLA/TPU systems showed nearly a twofold increase at 20 wt% TPU. DIC analysis further revealed a transition from localized brittle deformation in neat polymers to more distributed plastic deformation with increasing TPU content. DSC results indicated reduced crystallinity in PLA-rich blends and enhanced segmental mobility in ABS-based systems, consistent with the observed mechanical behavior. Overall, the combined mechanical, optical, and thermal analyses demonstrate that the optimal TPU content is matrix-dependent, providing practical guidelines for tailoring PLA- and ABS-based filaments to achieve a controlled balance between stiffness, ductility, and energy absorption in material extrusion applications.  Full article

Pneumatic transmission lines play a critical role in the dynamic performance of soft robotic actuation systems, yet their behaviour is difficult to capture using conventional integer-order (IO) models. In long, slender pipelines, compressibility, viscothermal losses, and wave propagation give rise to distributed damping and non-exponential relaxation dynamics that are not well represented by finite-dimensional models. This paper presents a control-oriented, experimentally validated fractional-order (FO) modelling framework for pneumatic pipeline dynamics under closed-end boundary conditions. Models are calibrated using measured step-response data from a 13.2 m pipeline, with all parameters—including the fractional order—identified through a unified optimisation procedure. In addition to global fitting accuracy, model performance is evaluated using control-relevant metrics, including effective delay, initial slope and early transient behaviour, and early-time error. The results show that FO models provide a more compact and structurally consistent representation of long-memory dynamics while improving the accuracy of control-relevant features compared to their IO counterparts. These findings demonstrate that fractional dynamics offer a physically meaningful and practically useful framework for modelling pneumatic transmission lines, with direct implications for high-performance control design in soft robotic systems. Full article

Apple detection is a core perception task for harvesting robots operating in complex orchard environments. Targets are frequently affected by branch–foliage occlusion, alternating front/side/back lighting, and strong local illumination fluctuations, which blur object boundaries against background textures and substantially increase detection difficulty. To improve target perception under these conditions, we propose an improved detector, YOLOv11-CBMES. First, based on YOLOv11, we replace the original neck with a weighted BiFPN to enhance cross-scale feature fusion under occlusion. Second, we introduce a Contrast-Driven Feature Aggregation (CDFA) module at the P5 stage, using Haar wavelet decomposition to decouple low-frequency illumination components from high-frequency structural components. Third, we reconstruct spatial feature learning and the upsampling pathway using CSP-based multi-scale blocks and efficient upsampling blocks, and embed a zero-parameter Shift-Context strategy to strengthen local neighbourhood interaction. Finally, we formulate apple detection as a three-class occlusion classification task (No Occlusion, Soft Occlusion, and Hard Occlusion) to support occlusion-aware target recognition. On the apple occlusion dataset, YOLOv11-CBMES achieves ${\mathrm{m}\mathrm{A}\mathrm{P}}_{\mathrm{N}\mathrm{O}}$ = 83.50%, ${\mathrm{m}\mathrm{A}\mathrm{P}}_{\mathrm{S}\mathrm{O}}$ = 67.36%, and ${\mathrm{m}\mathrm{A}\mathrm{P}}_{\mathrm{H}\mathrm{O}}$ = 51.90% at IoU = 0.5. Compared with YOLOv11n under the same training protocol, the gains are +2.16 pp (NO), +3.68 pp (SO), and +5.31 pp (HO), with the largest improvement observed in Hard Occlusion (HO). The results indicate that introducing frequency-domain structural processing into the detection framework improves apple occlusion classification and object detection performance, and provides a theoretical basis for designing perception modules for end-effector operations in apple harvesting robots. Full article

Background/Objectives: Women and girls, particularly in sub-Saharan Africa, face high risks for both HIV and unintended pregnancy. Inconsistent condom use underscores the need for new multipurpose prevention technologies (MPTs) that combine HIV pre-exposure prophylaxis (PrEP) and contraception. Long-acting (LA) injectables are especially promising. To this end, an LA cabotegravir (CAB)/medroxyprogesterone acetate (MPA) in situ-forming implant (ISFI) has been developed. We report pharmacokinetic (PK) modeling to characterize CAB and MPA disposition and absorption to support the development of the MPT ISFI. Methods: Female BALB/c mice received single intravenous (IV) or subcutaneous (SQ) bolus doses of CAB or MPA. Sparse plasma samples were collected (~3 mice/timepoint) for PK analysis by LC-MS/MS. Noncompartmental analysis assessed SQ bioavailability. Macroparameterized compartmental PK models were fit to IV data to derive unit impulse responses (UIRs) for each drug. Results: CAB and MPA exhibited 61% and 42% bioavailability, respectively. CAB IV PK was best described by a two-compartment model with macroconstant parameters: A = 16,621 ng/mL, α = 4.52 h⁻¹, B = 30,206 ng/mL, and β = 0.053 h⁻¹. MPA IV PK was also best described by a two-compartment model, with A = 2506 ng/mL, α = 10.5 h⁻¹, B = 439 ng/mL, and β = 0.65 h⁻¹. These values define the UIR for CAB and MPA. Conclusions: Our IV PK modeling framework fully characterizes CAB/MPA disposition in mouse, enabling downstream deconvolution-based estimation of absorption from controlled-release formulations. This provides a foundation for in vitro–in vivo correlation, facilitating preclinical evaluation of long-acting formulations such as ISFIs. Full article

Over the last decade, 3D printing of clay has gained attention in architecture. Yet most slicing software is designed for thermoplastics with nozzle sizes between 0.3 and 1.0 mm. Clay printing, using larger nozzles (1–30 mm), requires precise control over path arrangement, material flow, and shrinkage—capabilities not sufficiently addressed by conventional software. This paper introduces Termite, an open-source software plugin for Rhinoceros 3D Grasshopper designed specifically for Liquid Deposition Modeling (LDM) 3D printing. The novelty of this work lies in embedding slicing logic directly into a parametric design environment, enabling explicit and flexible control of printing paths tailored to the rheological behavior of clay. The plugin supports designing, simulating, optimizing, and exporting machine data within a unified workflow. In contrast to conventional slicers, it allows variable printing parameters within a single print job, controlled inrun speeds for smoother path starts, adapted material flow at path crossings, and extrusion flattening at path ends to enhance adhesion and precision. The software was evaluated through multiple architectural-scale case studies and student-based design experiments. Results demonstrate that integrating slicing operations into parametric design workflows enables new fabrication strategies and expands accessibility of clay 3D printing for architectural applications. Full article

Using alternative energy sources for animal feed, such as hybrid corn varieties rather than genetically modified ones, is important. Therefore, the objective of this work was to assess the effects of supplementation at the end of gestation with Mexican Puma hybrid corn grain on productive and behavioral parameters in sheep. Twenty Columbia multiparous ewes were used; along with their diet, they were provided 600 g/animal/day of cracked corn during the last 20 days of pregnancy and the first week of lactation. The animals were divided into two groups: one fed commercial cracked corn (n = 11) and the other Mexican Tlaoli Puma hybrid cracked corn (n = 9). The productive parameters evaluated in the mother were: body weight, body condition score (BCS), feed intake, weight change, glucose, and ketone body levels, as well as the estimated quality of milk using Brix refractometer values on days 15 and 30 of lactation. In lambs, their rectal and external temperature was measured 2 h after birth, while their weight was measured 2 h after birth and every week until week 6 postpartum. Behavioral parameters were measured in the first two hours postpartum, including the maternal latency of cleaning the offspring, duration of the first nursing episode, the lamb’s latencies of standing and nursing, and vocalizations in mother and lamb. Weight, BCS and weight change were not affected by the group but were affected by time; these parameters increased at the end of gestation and decreased significantly after delivery (p < 0.05). Ketone body levels were not affected by group or time (p > 0.05) and remained at low values. Glucose levels were not affected by the group but were affected by time; they increased significantly after birth (p < 0.05). Feed intake was similar in both groups (p > 0.05) and decreased as parturition approached (p < 0.05). The estimated milk quality was not affected by the group, nor by the time (p > 0.05). Mothers in both groups began cleaning their offspring within the first three minutes after giving birth and emitted a similar frequency of vocalizations (p > 0.05). However, mothers in the commercial maize group had a longer nursing episode than those in the hybrid maize group (p < 0.05). The lambs in both groups stood up within the first half hour of birth, suckled before one hour after birth and emitted a similar number of vocalizations (p > 0.05). Temperatures and lamb weight were similar in both groups (p > 0.05); however, lamb weight increased as they aged (p < 0.05). It is concluded that supplementing sheep at the end of gestation with Puma hybrid Mexican corn grain can yield similar productive and behavioral benefits as supplementing with commercial grain. Full article

Manual harvesting of white button mushrooms involves coordinated bending and twisting motions to detach the fruiting body while minimizing surface damage; however, replicating these actions in automated systems remains challenging. In this study, a vacuum-based end-effector that mimics manual twist–bend detachment using a single-point contact was designed and evaluated to reduce mechanical damage. Key detachment parameters, including the friction coefficient (mean 0.62), bending angle (average 5.72°), and twisting torque (average 2.56 N·m), were experimentally analyzed to determine the minimum vacuum pressures required for effective bending and twisting, which were −8.64 ± 2.21 kPa and −8.91 ± 2.45 kPa, respectively, with no significant difference observed between the two motions (p = 0.51). A customized vision-based image processing algorithm was developed to quantify postharvest surface damage using a whiteness index (WI). An optimal vacuum pressure of −17.17 kPa was identified, together with a bending angle of 10° and a twisting angle of 90°, balancing high harvesting success with preservation of mushroom quality. The results highlight the influence of end-effector design parameters, including vacuum cup material, contact area, bending direction, and vacuum application duration, on harvesting performance and product marketability, supporting the development of robotic systems for fresh mushroom harvesting. Full article

Background/Objectives: The question addressed in the current work is to develop a simulation of a pharmaceutical process (DNA encapsulation within lipid nanoparticles using a microfluidic micromixer) which will be of utility to the end users (laboratory-scale formulation development). The simulation and the microfluidic approach also address sustainability issues, such as reducing the environmental impact of the process itself, and reducing the need for physical testing. The paper details the implementation and validation, taking into account key performance indicators and control parameters. Methods: The main method applied for simulation development is a novel multi-agent approach to incorporate stochastic probabilistic behavior, combined with theoretical definitions from the process experts and relevant literature, and data/results from laboratory-scale experiments with different parameter configurations. Results: The simulation was implemented as a representation of the real physical process, reproducing the relationships between process parameters (flow rates) and experimental key performance indicators (capsule diameter, poly dispersion index, encapsulation efficiency). The simulation results demonstrated a general agreement with the empirical results and provided useful predictive insights for the laboratory experiments. Conclusions: The simulation has potential as a support tool for laboratory experiments to reduce physical testing and indicate the most promising configurations on which to focus, with potential savings in time, resources and other costs. Full article

Lunar quadruped robots face landing challenges including weak gravity, large mass variations, uncertain sloped terrain, and strict payload acceleration limits, requiring effective impact mitigation and rapid post-landing stabilization. This paper presents a novel end-to-end reinforcement learning-based landing controller with three key novelties: (i) a phase-structured yet implicitly encoded formulation that distinguishes contact preparation, energy dissipation, and stabilization without explicit phase switching; (ii) a terrain-agnostic state and control representation using equivalent support direction construction and contact-gated modulation to decouple normal–tangential dynamics; and (iii) an extremum oriented learning strategy that directly captures peak impact suppression and buffering sufficiency, addressing limitations of cumulative rewards in hybrid, peak-dominated tasks. A hybrid control model for lunar quadruped landing dynamics is established, incorporating variable mass, low impact, and full stroke as key constraints during training. Simulation and full-scale experimental prototypes are built to validate the controller. Simulation results demonstrate robust landing buffering and stability control under varying mass, landing velocity, and slope conditions, with favorable robustness against parameter variations. Experimental verification is conducted under diverse conditions including different masses (200 kg, 250 kg), vertical/horizontal landing velocities (0.8 m/s, 0.2 m/s), and slopes (0, 8). The deviation between simulation and experimental results does not exceed 30%, confirming the effectiveness and transferability of the proposed approach. Full article

Irreversible covalent enzyme inhibitors, including targeted covalent inhibitors (TCIs) and mechanism-based enzyme inhibitors (MBEIs), play an increasingly important role in drug discovery. Their pharmacological behavior is governed by intrinsic inactivation parameters, typically described by the inactivation constant K_I, the maximal inactivation rate constant k_inact, and their ratio k_inact/K_I. However, no consensus exists regarding how these parameters should be experimentally determined and interpreted, particularly in high-throughput screening environments where IC₅₀ values are often used as primary descriptors. This article presents a critical survey of the kinetic methodologies employed to characterize irreversible enzyme inhibition. Continuous progress-curve analysis, discontinuous end-point assays, IC₅₀-based estimation strategies, direct mass-spectrometric monitoring of covalent modification, and numerical approaches required by pre-incubation protocols are examined and compared. Attention is given to the statistical robustness of parameter estimation under realistic experimental error, including bootstrap-based uncertainty analysis. For mechanism-based enzyme inhibitors, the kinetic consequences of branching between productive turnover and irreversible inactivation are analyzed, and limitations of classical half-life-based linearization methods are discussed. Intrinsic inactivation parameters are distinguished from protocol-dependent observables, and experimental conditions that may compromise reliable parameter extraction are identified. The objective is to clarify how irreversible inhibitors should be kinetically characterized when the goal is mechanistic understanding and rational drug design. By bridging classical enzymology with current discovery practices, this review provides practical guidance on what experimental data can legitimately support and where caution is required. Full article

Background/Objectives: Oxidative stress plays an important role in the pathophysiology of endometriosis, contributing to inflammation, immune dysregulation, and lesion progression. This has led to growing interest in antioxidant-based strategies as potential supportive interventions. Methods: A literature search was conducted using PubMed, Scopus, and Web of Science databases, covering studies published from database inception until the end of January 2026. The review focused on clinically relevant endpoints, including pain intensity, markers of inflammation and oxidative stress, reproductive parameters, and quality of life. Results: Among the analyzed interventions, the most consistent clinical effects were observed with melatonin, with randomized controlled trials indicating a moderate reduction in pain. N-acetylcysteine shows potentially beneficial effects; however, the available clinical data remain limited and heterogeneous. For other supplements, the evidence is inconsistent or insufficient to support clear clinical conclusions, and in many cases relies on indirect or mechanistic findings rather than well-established clinical outcomes. Conclusions: Current evidence does not support the use of non-mineral antioxidant supplements as standalone therapy for endometriosis. They may be considered as adjunctive strategies, although their clinical effectiveness remains uncertain and requires confirmation in well-designed randomized clinical trials. Full article

This study systematically investigates the influence of steel fibers on the mechanical properties of cement concrete. End-hook, shear, and milling type steel fibers were selected, with comparisons made to copper-plated and corroded steel fibers. The effects of fiber type, aspect ratio (40–60), and volume content (0.5–1.5%) on the compressive, flexural, and splitting tensile properties of concrete were analyzed. A multi-objective mechanical performance prediction model was established using a combined macro- and micro-scale testing approach, integrated with response surface methodology (RSM) and I-optimal design. The results indicate that steel fibers can significantly enhance the overall mechanical properties of concrete. Among the types tested, the end-hook fiber exhibited the best performance in compressive and splitting tensile strength, and the 28-day compressive strength increased by 41% compared with plain concrete, while the milling fiber showed the greatest improvement in flexural strength, and the value reached up to 72%. Furthermore, the failure mode observations indicated that steel fiber incorporation fundamentally altered the fracture behavior of concrete, transitioning it from brittle fracture to quasi-ductile behavior with post-crack load-carrying capacity, particularly for end-hook and milling fiber types. An optimal parameter window for the fiber reinforcement effect was identified, with the best comprehensive performance achieved at an aspect ratio of 50–60 and a fiber content of 0.5–1.0%. The enhancement effect of copper-plated and corroded steel fibers was limited due to reduced interfacial bonding performance. The developed model demonstrates high prediction accuracy, providing a theoretical and experimental basis for the engineering application of fiber-reinforced concrete. Full article

Background: Diabetic nephropathy (DN), also referred to as diabetic kidney disease, represents one of the most common microvascular complications of type 2 diabetes mellitus (T2DM) and remains a leading cause of end-stage renal disease worldwide. Conventional clinical markers, including albuminuria and estimated glomerular filtration rate (eGFR), are widely used for diagnosis and staging but may have limited sensitivity for detecting early renal injury and predicting disease progression. In recent years, circulating microRNAs (miRNAs) have emerged as promising non-invasive biomarkers that reflect underlying molecular mechanisms of diabetic nephropathy and may complement traditional clinical indicators. Objective: The present study aimed to evaluate serum and urinary levels of hsa-miRNA-770-5p across different stages of diabetic nephropathy and to assess its potential diagnostic value in relation to established indicators of renal function. Methods: A total of 257 participants were included and divided into four groups: healthy controls, patients with T2DM without nephropathy, patients with T2DM and DN in CKD stages I–II, and patients with DN undergoing maintenance hemodialysis (MHD). Serum and urinary levels of miRNA-770-5p were measured using quantitative real-time polymerase chain reaction (qPCR) and analyzed using the 2^−ΔΔCt method. Statistical analyses included comparisons between groups using ANOVA, correlation analyses with renal function parameters such as eGFR and proteinuria/albuminuria, and receiver operating characteristic (ROC) curve analysis to evaluate diagnostic performance. Results: Serum levels of miRNA-770-5p were significantly elevated in patients with DN and in patients undergoing maintenance hemodialysis compared with healthy controls and patients with T2DM without nephropathy. In contrast, urinary levels of miRNA-770-5p were markedly reduced in patients with DN. Serum levels in patients with T2DM without nephropathy were slightly lower than those observed in healthy controls. Significant correlations were identified between miRNA-770-5p levels and renal function parameters, including eGFR and proteinuria/albuminuria, supporting the biological relevance of this microRNA in renal injury. ROC curve analysis demonstrated good discriminatory ability for differentiating DN from T2DM without nephropathy (serum AUC = 0.82; urine AUC = 0.79). Conclusions: hsa-miRNA-770-5p demonstrates distinct and opposite patterns in serum and urine that correlate with the severity of diabetic nephropathy. The complementary changes observed in circulating and urinary levels support the potential of miRNA-770-5p as a non-invasive biomarker that may complement conventional clinical markers and provide additional insight into the molecular mechanisms involved in the development and progression of diabetic nephropathy. Full article

This study presents a comprehensive multi-objective optimization of sewage wastewater treatment using bio-based coagulants, guided by the Grey Wolf Optimizer (GWO) and its multi-objective variant (MOGWO). Experimental coagulation data, employing Citrullus lanatus and Cucumis melo as natural coagulants, were modeled using multivariate regression techniques, yielding high coefficients of determination (R² > 0.95) across key water quality parameters. The optimization process targeted maximal reductions in turbidity, total suspended solids (TSS), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) through strategic manipulation of pH and coagulant dosage. The single-objective GWO achieved significant outcomes, including a 96.68% turbidity reduction at pH 5 and 50 mg/L dosage. The MOGWO algorithm identified Pareto-optimal solutions, such as a 94.2% turbidity reduction at pH 5 and 72 mg/L dosage, and a balanced BOD reduction of 52.7% at pH 7. The predictive models indicated that optimal treatment conditions could reduce chemical usage by up to 90% compared to conventional coagulants, resulting in potential cost savings of up to 30%. Moreover, the algorithms demonstrated rapid convergence, averaging 200 iterations, highlighting their computational efficiency and robustness. These findings illustrate that integrating bio-based coagulants with advanced optimization techniques can achieve high treatment efficiency while reducing chemical inputs, thus directly supporting environmental sustainability by minimizing sludge and secondary pollution. In this situation, the wastewater treatment plant will focus on resource-recovery systems with less or no waste at the end of the treatment process. This approach aligns with circular economy principles by promoting eco-friendly, cost-effective wastewater treatment solutions suitable for resource-limited settings. The study offers a forward-looking pathway for environmentally responsible wastewater management practices that significantly reduce chemical dependency and contribute to pollution mitigation efforts. Full article

Objectives: Colistin is frequently used as a last-line treatment option for periprosthetic joint infections (PJIs) caused by multidrug-resistant (MDR) Gram-negative pathogens, and mortality rates are high in this patient group. This study aimed to evaluate 90-day mortality and its associated clinical factors in MDR Gram-negative PJI cases treated with colistin, with particular attention to the American Society of Anesthesiologists (ASA) score and changes in renal function during therapy. Methods: Patients diagnosed with MDR Gram-negative PJI and treated with intravenous colistin at a single center between 2010 and 2024 were retrospectively reviewed. Demographic data, infection localization, comorbidities, American Society of Anesthesiologists (ASA) score, causative pathogens, presence of sepsis, intensive care unit (ICU) admission, duration of colistin therapy, pre- and post-treatment renal function parameters, and mortality were all recorded. Survivors and non-survivors were compared using univariate analysis. Results: The cohort included 44 patients with a mean age of 72 years (23 women and 21 men). Infections involved the hip in 33 patients (75.0%) and the knee in 11 (25.0%). Twenty-two patients (50.0%) were in the high-ASA group (ASA ≥ III group). Within 90 days of initiating colistin therapy, 25 patients died and 19 survived. A high ASA score was significantly more common among non-survivors than among survivors (18/25 (72.0%) vs. 4/19 (21.1%); p < 0.001), and dialysis requirement was also more common among non-survivors [20/25 (80.0%) vs. 8/19 (42.1%); p = 0.013]. End-of-treatment renal parameters were significantly worse among non-survivors, including urea [71.2 (50.9–78.8) vs. 38.5 (34.8–42.5) mg/dL; p = 0.003], creatinine [2.29 (1.75–2.64) vs. 0.93 (0.72–1.60) mg/dL; p = 0.003], urea delta [42.8 (38.0–48.6) vs. −5.4 (−7.9 to −2.0) mg/dL; p = 0.006], and creatinine delta [0.78 (0.33–1.57) vs. 0.16 (0.10–0.57) mg/dL; p = 0.008] levels. In contrast, age, sepsis, ICU admission, and colistin treatment duration were not significantly associated with 90-day survival. Conclusions: In this high-risk cohort of patients with MDR Gram-negative PJI treated with colistin, the 90-day mortality rate was high and was associated with higher American Society of Anesthesiologists scores, dialysis requirements, and worsening renal function during treatment. No significant association was observed between treatment duration and response in this cohort. These findings should be interpreted cautiously, given the retrospective design and the limited sample size. Full article